| Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants |
Ancestry distribution GWAS Dev Eval |
Scoring File (FTP Link) |
|---|---|---|---|---|---|---|
| PGS000010 (GRS27) |
PGP000003 | Mega JL et al. Lancet (2015) |
Coronary heart disease | coronary artery disorder | 27 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000010/ScoringFiles/PGS000010.txt.gz |
| PGS000011 (GRS50) |
PGP000004 | Tada H et al. Eur Heart J (2015) |
Coronary artery disease | coronary artery disorder | 50 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000011/ScoringFiles/PGS000011.txt.gz |
| PGS000012 (GRS49K) |
PGP000005 | Abraham G et al. Eur Heart J (2016) |
Coronary artery disease | coronary artery disorder | 49,310 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000012/ScoringFiles/PGS000012.txt.gz | |
| PGS000013 (GPS_CAD) |
PGP000006 | Khera AV et al. Nat Genet (2018) |
Coronary artery disease | coronary artery disorder | 6,630,150 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000013/ScoringFiles/PGS000013.txt.gz | |
| PGS000016 (GPS_AF) |
PGP000006 | Khera AV et al. Nat Genet (2018) |
Atrial fibrillation | atrial fibrillation | 6,730,541 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000016/ScoringFiles/PGS000016.txt.gz | |
| PGS000018 (metaGRS_CAD) |
PGP000007 | Inouye M et al. J Am Coll Cardiol (2018) |
Coronary artery disease | coronary artery disorder | 1,745,179 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000018/ScoringFiles/PGS000018.txt.gz | |
| PGS000019 (GRS_CAD) |
PGP000009 | Paquette M et al. J Clin Lipidol (2017) |
Coronary artery disease | coronary artery disorder | 192 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000019/ScoringFiles/PGS000019.txt.gz |
| PGS000035 (PRS_AF) |
PGP000022 | Weng LC et al. Circulation (2017) |
Atrial fibrillation | atrial fibrillation | 1,168 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000035/ScoringFiles/PGS000035.txt.gz | |
| PGS000038 (PRS90) |
PGP000026 | Rutten-Jacobs LC et al. BMJ (2018) |
Stroke | stroke disorder | 90 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000038/ScoringFiles/PGS000038.txt.gz |
| PGS000039 (metaGRS_ischaemicstroke) |
PGP000027 | Abraham G et al. Nat Commun (2019) |
Ischemic stroke | Ischemic stroke, stroke disorder |
3,225,583 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000039/ScoringFiles/PGS000039.txt.gz | |
| PGS000043 (PRS_VTE) |
PGP000030 | Klarin D et al. Nat Genet (2019) |
Venous thromboembolism | venous thromboembolism | 297 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000043/ScoringFiles/PGS000043.txt.gz |
| PGS000057 (CHD57) |
PGP000042 | Natarajan P et al. Circulation (2017) |
Coronary heart disease | coronary artery disorder | 57 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000057/ScoringFiles/PGS000057.txt.gz |
| PGS000058 (CAD_GRS_204) |
PGP000043 | Morieri ML et al. Diabetes Care (2018) |
Coronary artery disease | coronary artery disorder | 204 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000058/ScoringFiles/PGS000058.txt.gz |
| PGS000059 (CHD46) |
PGP000044 | Hajek C et al. Circ Genom Precis Med (2018) |
Coronary heart disease | coronary artery disorder | 46 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000059/ScoringFiles/PGS000059.txt.gz |
| PGS000116 (CAD_EJ2020) |
PGP000054 | Elliott J et al. JAMA (2020) |
Coronary artery disease | coronary artery disorder | 40,079 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000116/ScoringFiles/PGS000116.txt.gz | |
| PGS000117 (CVD_EJ2020) |
PGP000054 | Elliott J et al. JAMA (2020) |
Cardiovascular disease | cardiovascular disorder | 297,862 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000117/ScoringFiles/PGS000117.txt.gz | |
| PGS000200 (GRS28) |
PGP000082 | Tikkanen E et al. Arterioscler Thromb Vasc Biol (2013) |
Coronary heart disease | coronary artery disorder | 28 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000200/ScoringFiles/PGS000200.txt.gz |
| PGS000296 (GPS_CAD_SA) |
PGP000090 | Wang M et al. J Am Coll Cardiol (2020) |
Coronary artery disease | coronary artery disorder | 6,630,150 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000296/ScoringFiles/PGS000296.txt.gz | |
| PGS000329 (PRS_CHD) |
PGP000100 | Mars N et al. Nat Med (2020) |
Coronary heart disease | coronary artery disorder | 6,423,165 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000329/ScoringFiles/PGS000329.txt.gz | |
| PGS000331 (PRS_AF) |
PGP000100 | Mars N et al. Nat Med (2020) |
Atrial fibrillation | atrial fibrillation | 6,183,494 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000331/ScoringFiles/PGS000331.txt.gz | |
| PGS000337 (MetaPRS_CAD) |
PGP000104 | Koyama S et al. Nat Genet (2020) |
Coronary artery disease | coronary artery disorder | 75,028 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000337/ScoringFiles/PGS000337.txt.gz |
| PGS000338 (GRS97_AF) |
PGP000105 | Kloosterman M et al. Eur J Heart Fail (2020) |
Atrial fibrillation | atrial fibrillation | 97 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000338/ScoringFiles/PGS000338.txt.gz |
| PGS000349 (PRS70_CAD) |
PGP000114 | Pechlivanis S et al. BMC Med Genet (2020) |
Coronary artery disease | coronary artery disorder | 70 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000349/ScoringFiles/PGS000349.txt.gz |
| PGS000665 (GRS_32) |
PGP000125 | Marston NA et al. Circulation (2020) |
Ischemic stroke | Ischemic stroke, stroke disorder |
32 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000665/ScoringFiles/PGS000665.txt.gz |
| PGS000706 (HC215) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Hypertension | hypertensive disorder | 186,726 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000706/ScoringFiles/PGS000706.txt.gz |
| PGS000709 (HC299) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Heart failure | heart failure | 183,287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000709/ScoringFiles/PGS000709.txt.gz |
| PGS000710 (HC326) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Myocardial infarction | myocardial infarction | 183,566 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000710/ScoringFiles/PGS000710.txt.gz |
| PGS000727 (AF_PGS) |
PGP000137 | Ritchie SC et al. Nat Metab (2021) |
Atrial fibrillation | atrial fibrillation | 2,210,336 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000727/ScoringFiles/PGS000727.txt.gz |
| PGS000737 (PRS_BrS) |
PGP000144 | Tadros R et al. Eur Heart J (2019) |
Brugada syndrome | Brugada syndrome | 3 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000737/ScoringFiles/PGS000737.txt.gz |
| PGS000739 (HCM_GRS) |
PGP000146 | Harper AR et al. Nat Genet (2021) |
Hypertrophic cardiomyopathy | hypertrophic cardiomyopathy | 27 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000739/ScoringFiles/PGS000739.txt.gz | |
| PGS000746 (PRS_UKB) |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Coronary artery disease | coronary artery disorder | 1,940 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000746/ScoringFiles/PGS000746.txt.gz | |
| PGS000747 (PRS_EB) |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Coronary artery disease | coronary artery disorder | 375,822 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000747/ScoringFiles/PGS000747.txt.gz | |
| PGS000748 (PRS_DE) |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Coronary artery disease | coronary artery disorder | 3,423,987 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000748/ScoringFiles/PGS000748.txt.gz | |
| PGS000749 (PRS_COMBINED) |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Coronary artery disease | coronary artery disorder | 1,056,021 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000749/ScoringFiles/PGS000749.txt.gz | |
| PGS000753 (PRS29_AAA) |
PGP000159 | Klarin D et al. Circulation (2020) |
Abdominal aortic aneurysm | abdominal aortic aneurysm | 29 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000753/ScoringFiles/PGS000753.txt.gz | |
| PGS000778 (PRSHCM) |
PGP000182 | Tadros R et al. Nat Genet (2021) |
Hypertrophic cardiomyopathy | hypertrophic cardiomyopathy | 20 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000778/ScoringFiles/PGS000778.txt.gz |
| PGS000798 (157SNP_GRS) |
PGP000187 | Severance LM et al. J Cardiovasc Comput Tomogr (2019) |
Coronary heart disease | coronary artery disorder | 157 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000798/ScoringFiles/PGS000798.txt.gz |
| PGS000818 (GRS_Metabo) |
PGP000202 | Bauer A et al. Genet Epidemiol (2021) |
Coronary heart disease | coronary artery disorder | 138 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000818/ScoringFiles/PGS000818.txt.gz |
| PGS000819 (PRS_DR) |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Diabetic retinopathy | diabetic retinopathy | 3,537,914 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000819/ScoringFiles/PGS000819.txt.gz |
| PGS000862 (DR) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Diabetic Retinopathy | diabetic retinopathy | 30 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000862/ScoringFiles/PGS000862.txt.gz |
| PGS000863 (Cardiovascular) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Cardiovascular disease | cardiovascular disorder | 330 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000863/ScoringFiles/PGS000863.txt.gz |
| PGS000899 (PRS176_CHD) |
PGP000232 | Feitosa MF et al. Circ Genom Precis Med (2021) |
Coronary heart disease | coronary artery disorder | 176 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000899/ScoringFiles/PGS000899.txt.gz |
| PGS000911 (PRS_IS) |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Ischemic stroke | Ischemic stroke, stroke disorder |
530,933 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000911/ScoringFiles/PGS000911.txt.gz | |
| PGS000930 (GBE_BIN_FC3006152) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Blood clot (diagnosed by doctor) | thrombotic disease | 118 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000930/ScoringFiles/PGS000930.txt.gz |
| PGS000931 (GBE_BIN_FC11006152) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Blood clot or deep vein thrombosis (diagnosed by doctor) | deep vein thrombosis, thrombotic disease |
534 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000931/ScoringFiles/PGS000931.txt.gz |
| PGS000957 (GBE_HC932) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Essential (primary hypertension) (time-to-event) | essential hypertension | 11,276 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000957/ScoringFiles/PGS000957.txt.gz |
| PGS000958 (GBE_HC273) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Essential hypertension | essential hypertension | 9,400 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000958/ScoringFiles/PGS000958.txt.gz |
| PGS000961 (GBE_HC987) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Phlebitis and thrombophlebitis (time-to-event) | Thrombophlebitis, phlebitis |
1,143 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000961/ScoringFiles/PGS000961.txt.gz |
| PGS000962 (GBE_HC942) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Chronic ischaemic heart disease (time-to-event) | myocardial ischemia | 2,168 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000962/ScoringFiles/PGS000962.txt.gz |
| PGS001024 (GBE_HC61) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Hemorrhoid | hemorrhoid | 786 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001024/ScoringFiles/PGS001024.txt.gz |
| PGS001025 (GBE_HC951) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Nonrheumatic aortic valve disorders (time-to-event) | aortic valve disorder | 36 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001025/ScoringFiles/PGS001025.txt.gz |
| PGS001048 (GBE_HC1576) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
NSTEMI (algorithmically-defined) | Non-ST Elevation Myocardial Infarction | 687 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001048/ScoringFiles/PGS001048.txt.gz |
| PGS001179 (GBE_HC711) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Vascular dementia (time-to-event) | vascular dementia | 7 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001179/ScoringFiles/PGS001179.txt.gz |
| PGS001263 (GBE_HC440) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Atrial flutter | atrial flutter | 2,087 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001263/ScoringFiles/PGS001263.txt.gz |
| PGS001277 (GBE_HC203) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
PE +/- DVT | deep vein thrombosis, pulmonary embolism |
96 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001277/ScoringFiles/PGS001277.txt.gz |
| PGS001278 (GBE_BIN_FC12006152) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
previously: Blood clot in the leg (DVT) or lung | deep vein thrombosis, pulmonary embolism |
551 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001278/ScoringFiles/PGS001278.txt.gz |
| PGS001279 (GBE_BIN_FC8006152) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
previously: Blood clot in the lung | deep vein thrombosis, pulmonary embolism |
94 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001279/ScoringFiles/PGS001279.txt.gz |
| PGS001280 (GBE_HC943) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
PE (time-to-event) | pulmonary embolism | 88 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001280/ScoringFiles/PGS001280.txt.gz |
| PGS001281 (GBE_HC86) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Migraine | migraine disorder | 25 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001281/ScoringFiles/PGS001281.txt.gz |
| PGS001282 (GBE_HC815) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Migraine (time-to-event) | migraine disorder | 329 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001282/ScoringFiles/PGS001282.txt.gz |
| PGS001314 (GBE_HC938) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Acute myocardial infarction (time-to-event) | myocardial infarction | 1,108 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001314/ScoringFiles/PGS001314.txt.gz |
| PGS001315 (GBE_HC326) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Myocardial infarction | myocardial infarction | 1,788 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001315/ScoringFiles/PGS001315.txt.gz |
| PGS001316 (GBE_HC1574) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Myocardial infarction (algorithmically-defined) | myocardial infarction | 1,831 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001316/ScoringFiles/PGS001316.txt.gz |
| PGS001317 (GBE_BIN_FC1006150) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Vascular/heart problems diagnosed by doctor Heart attack | myocardial infarction | 1,030 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001317/ScoringFiles/PGS001317.txt.gz |
| PGS001320 (GBE_HC215) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Hypertension | hypertensive disorder | 13,791 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001320/ScoringFiles/PGS001320.txt.gz |
| PGS001335 (GBE_BIN_FC4006150) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Vascular/heart problems diagnosed by doctor High BP | cardiovascular disorder | 14,076 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001335/ScoringFiles/PGS001335.txt.gz |
| PGS001339 (GBE_HC964) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Atrial fibrillation and flutter (time-to-event) | atrial fibrillation, atrial flutter |
2,142 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001339/ScoringFiles/PGS001339.txt.gz |
| PGS001340 (GBE_HC281) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Atrial fibrillation | atrial fibrillation | 2,955 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001340/ScoringFiles/PGS001340.txt.gz |
| PGS001355 (CAD_AnnoPred_PRS) |
PGP000252 | Ye Y et al. Circ Genom Precis Med (2021) |
Coronary artery disease | coronary artery disorder | 2,994,055 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001355/ScoringFiles/PGS001355.txt.gz | |
| PGS001356 (AF_AnnoPred_PRS) |
PGP000252 | Ye Y et al. Circ Genom Precis Med (2021) |
Atrial fibrillation | atrial fibrillation | 2,996,793 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001356/ScoringFiles/PGS001356.txt.gz | |
| PGS001779 (BRSprs) |
PGP000260 | Barc J et al. Nat Genet (2022) |
Brugada syndrome | Brugada syndrome | 21 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001779/ScoringFiles/PGS001779.txt.gz |
| PGS001780 (CHD_PRSCS) |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Coronary heart disease | coronary artery disorder | 1,090,048 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001780/ScoringFiles/PGS001780.txt.gz |
| PGS001784 (1kgeur_gbmi_leaveUKBBout_AAA_pst_eff_a1_b0.5_phiauto) |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Abdominal aortic aneurysm | abdominal aortic aneurysm | 911,440 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001784/ScoringFiles/PGS001784.txt.gz |
| PGS001790 (1kgeur_gbmi_leaveUKBBout_HF_pst_eff_a1_b0.5_phiauto) |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Heart failure | heart failure | 910,146 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001790/ScoringFiles/PGS001790.txt.gz |
| PGS001793 (1kgeur_gbmi_leaveUKBBout_Stroke_pst_eff_a1_b0.5_phiauto) |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Stroke | stroke disorder | 910,099 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001793/ScoringFiles/PGS001793.txt.gz |
| PGS001796 (1kgeur_gbmi_leaveUKBBout_VTE_pst_eff_a1_b0.5_phiauto) |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Venous thromboembolism | venous thromboembolism | 910,337 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001796/ScoringFiles/PGS001796.txt.gz |
| PGS001798 (1kgeur_gbmi_Stroke_pst_eff_a1_b0.5_phiauto) |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Stroke | stroke disorder | 884,168 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001798/ScoringFiles/PGS001798.txt.gz |
| PGS001819 (portability-PLR_250.7) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Diabetic retinopathy | diabetic retinopathy | 249 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001819/ScoringFiles/PGS001819.txt.gz |
| PGS001838 (portability-PLR_401) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 52,487 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001838/ScoringFiles/PGS001838.txt.gz |
| PGS001839 (portability-PLR_411.4) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Coronary atherosclerosis | coronary atherosclerosis | 25,425 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001839/ScoringFiles/PGS001839.txt.gz |
| PGS001840 (portability-PLR_415) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Pulmonary heart disease | cor pulmonale | 330 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001840/ScoringFiles/PGS001840.txt.gz |
| PGS001841 (portability-PLR_427.2) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Atrial fibrillation and flutter | atrial fibrillation, atrial flutter |
3,980 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001841/ScoringFiles/PGS001841.txt.gz |
| PGS001842 (portability-PLR_428) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Congestive heart failure; nonhypertensive | congestive heart failure | 2,759 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001842/ScoringFiles/PGS001842.txt.gz |
| PGS001843 (portability-PLR_443.9) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Peripheral vascular disease, unspecified | peripheral vascular disease | 242 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001843/ScoringFiles/PGS001843.txt.gz |
| PGS001844 (portability-PLR_451) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Phlebitis and thrombophlebitis | Thrombophlebitis, phlebitis |
431 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001844/ScoringFiles/PGS001844.txt.gz |
| PGS001846 (portability-PLR_455) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Hemorrhoids | hemorrhoid | 5,434 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001846/ScoringFiles/PGS001846.txt.gz |
| PGS001847 (portability-PLR_459.9) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Circulatory disease NEC | vascular disorder | 594 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001847/ScoringFiles/PGS001847.txt.gz |
| PGS002027 (portability-ldpred2_250.7) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Diabetic retinopathy | diabetic retinopathy | 389,029 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002027/ScoringFiles/PGS002027.txt.gz |
| PGS002047 (portability-ldpred2_401) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 918,325 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002047/ScoringFiles/PGS002047.txt.gz |
| PGS002048 (portability-ldpred2_411.4) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Coronary atherosclerosis | coronary atherosclerosis | 762,124 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002048/ScoringFiles/PGS002048.txt.gz |
| PGS002049 (portability-ldpred2_415) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Pulmonary heart disease | cor pulmonale | 222,371 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002049/ScoringFiles/PGS002049.txt.gz |
| PGS002050 (portability-ldpred2_427.2) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Atrial fibrillation and flutter | atrial fibrillation, atrial flutter |
554,908 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002050/ScoringFiles/PGS002050.txt.gz |
| PGS002051 (portability-ldpred2_428) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Congestive heart failure; nonhypertensive | congestive heart failure | 642,241 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002051/ScoringFiles/PGS002051.txt.gz |
| PGS002052 (portability-ldpred2_433.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Occlusion and stenosis of precerebral arteries | occlusion precerebral artery | 490,459 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002052/ScoringFiles/PGS002052.txt.gz |
| PGS002053 (portability-ldpred2_433) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Cerebrovascular disease | cerebrovascular disorder | 599,726 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002053/ScoringFiles/PGS002053.txt.gz |
| PGS002054 (portability-ldpred2_442.11) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Abdominal aortic aneurysm | abdominal aortic aneurysm | 592,187 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002054/ScoringFiles/PGS002054.txt.gz |
| PGS002055 (portability-ldpred2_443.9) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Peripheral vascular disease, unspecified | peripheral vascular disease | 599,514 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002055/ScoringFiles/PGS002055.txt.gz |
| PGS002056 (portability-ldpred2_451) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Phlebitis and thrombophlebitis | Thrombophlebitis, phlebitis |
114,679 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002056/ScoringFiles/PGS002056.txt.gz |
| PGS002058 (portability-ldpred2_455) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Hemorrhoids | hemorrhoid | 780,418 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002058/ScoringFiles/PGS002058.txt.gz |
| PGS002059 (portability-ldpred2_459.9) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Circulatory disease NEC | vascular disorder | 604,572 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002059/ScoringFiles/PGS002059.txt.gz |
| PGS002235 (elasticnet_VTE) |
PGP000267 | Kolin DA et al. Sci Rep (2021) |
Venous thromboembolism | venous thromboembolism | 36 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002235/ScoringFiles/PGS002235.txt.gz | |
| PGS002244 (ldpred_cad) |
PGP000271 | Mars N et al. Cell Genom (2022) |
Coronary artery disease | coronary artery disorder | 6,576,338 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002244/ScoringFiles/PGS002244.txt.gz | |
| PGS002259 (metaPRS_Stroke) |
PGP000285 | Lu X et al. Neurology (2021) |
Stroke | stroke disorder | 534 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002259/ScoringFiles/PGS002259.txt.gz | |
| PGS002262 (metaPRS_CAD) |
PGP000289 | Lu X et al. Eur Heart J (2022) |
Coronary artery disease | coronary artery disorder | 540 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002262/ScoringFiles/PGS002262.txt.gz | |
| PGS002271 (PRS_MVP) |
PGP000301 | Roselli C et al. Eur Heart J (2022) |
Mitral valve prolapse | Mitral valve prolapse | 1,097,364 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002271/ScoringFiles/PGS002271.txt.gz |
| PGS002296 (PRS2166_HT) |
PGP000326 | Maj C et al. Front Cardiovasc Med (2022) |
Hypertension | hypertensive disorder | 2,166 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002296/ScoringFiles/PGS002296.txt.gz | |
| PGS002316 (disease_CARDIOVASCULAR.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Cardiovascular disease | cardiovascular disorder | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002316/ScoringFiles/PGS002316.txt.gz |
| PGS002335 (disease_HYPERTENSION_DIAGNOSED.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertensive disorder | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002335/ScoringFiles/PGS002335.txt.gz |
| PGS002361 (disease_CARDIOVASCULAR.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Cardiovascular disease | cardiovascular disorder | 920,929 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002361/ScoringFiles/PGS002361.txt.gz |
| PGS002388 (disease_CARDIOVASCULAR.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Cardiovascular disease | cardiovascular disorder | 5,621 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002388/ScoringFiles/PGS002388.txt.gz |
| PGS002407 (disease_HYPERTENSION_DIAGNOSED.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertensive disorder | 6,693 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002407/ScoringFiles/PGS002407.txt.gz |
| PGS002437 (disease_CARDIOVASCULAR.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Cardiovascular disease | cardiovascular disorder | 20,431 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002437/ScoringFiles/PGS002437.txt.gz |
| PGS002456 (disease_HYPERTENSION_DIAGNOSED.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertensive disorder | 22,539 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002456/ScoringFiles/PGS002456.txt.gz |
| PGS002486 (disease_CARDIOVASCULAR.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Cardiovascular disease | cardiovascular disorder | 110,640 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002486/ScoringFiles/PGS002486.txt.gz |
| PGS002505 (disease_HYPERTENSION_DIAGNOSED.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertensive disorder | 115,656 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002505/ScoringFiles/PGS002505.txt.gz |
| PGS002535 (disease_CARDIOVASCULAR.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Cardiovascular disease | cardiovascular disorder | 1,218 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002535/ScoringFiles/PGS002535.txt.gz |
| PGS002554 (disease_HYPERTENSION_DIAGNOSED.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertensive disorder | 1,715 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002554/ScoringFiles/PGS002554.txt.gz |
| PGS002584 (disease_CARDIOVASCULAR.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Cardiovascular disease | cardiovascular disorder | 637 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002584/ScoringFiles/PGS002584.txt.gz |
| PGS002603 (disease_HYPERTENSION_DIAGNOSED.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertensive disorder | 949 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002603/ScoringFiles/PGS002603.txt.gz |
| PGS002633 (disease_CARDIOVASCULAR.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Cardiovascular disease | cardiovascular disorder | 381,036 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002633/ScoringFiles/PGS002633.txt.gz |
| PGS002652 (disease_HYPERTENSION_DIAGNOSED.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertensive disorder | 385,766 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002652/ScoringFiles/PGS002652.txt.gz |
| PGS002682 (disease_CARDIOVASCULAR.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Cardiovascular disease | cardiovascular disorder | 972,965 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002682/ScoringFiles/PGS002682.txt.gz |
| PGS002701 (disease_HYPERTENSION_DIAGNOSED.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertensive disorder | 973,782 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002701/ScoringFiles/PGS002701.txt.gz |
| PGS002724 (GIGASTROKE_iPGS_EUR) |
PGP000333 | Mishra A et al. Nature (2022) |
Ischemic stroke | Ischemic stroke, stroke disorder |
1,213,574 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002724/ScoringFiles/PGS002724.txt.gz | |
| PGS002725 (GIGASTROKE_iPGS_EAS) |
PGP000333 | Mishra A et al. Nature (2022) |
Ischemic stroke | Ischemic stroke, stroke disorder |
6,010,730 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002725/ScoringFiles/PGS002725.txt.gz | |
| PGS002756 (Atrial_fibrillation_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Atrial fibrillation | atrial fibrillation | 1,091,491 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002756/ScoringFiles/PGS002756.txt.gz |
| PGS002765 (SBP_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 1,077,894 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002765/ScoringFiles/PGS002765.txt.gz |
| PGS002770 (Stroke_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Stroke | stroke disorder | 1,088,719 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002770/ScoringFiles/PGS002770.txt.gz |
| PGS002772 (Venous_thromboembolism_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Venous thromboembolism | venous thromboembolism | 1,052,790 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002772/ScoringFiles/PGS002772.txt.gz |
| PGS002773 (GTG_AF_maxCT) |
PGP000365 | Wong CK et al. PLoS One (2022) |
Incident atrial fibrillation | atrial fibrillation | 265 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002773/ScoringFiles/PGS002773.txt.gz | |
| PGS002774 (GTG_AF_SCT) |
PGP000365 | Wong CK et al. PLoS One (2022) |
Incident atrial fibrillation | atrial fibrillation | 216,837 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002774/ScoringFiles/PGS002774.txt.gz | |
| PGS002775 (GTG_CAD_maxCT) |
PGP000365 | Wong CK et al. PLoS One (2022) |
Incident coronary artery disease | coronary artery disorder | 1,059 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002775/ScoringFiles/PGS002775.txt.gz | |
| PGS002776 (GTG_CAD_SCT) |
PGP000365 | Wong CK et al. PLoS One (2022) |
Incident coronary artery disease | coronary artery disorder | 390,782 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002776/ScoringFiles/PGS002776.txt.gz | |
| PGS002777 (GTG_Hypertension_maxCT) |
PGP000365 | Wong CK et al. PLoS One (2022) |
Incident hypertension | hypertensive disorder | 61,669 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002777/ScoringFiles/PGS002777.txt.gz | |
| PGS002778 (GTG_Hypertension_SCT) |
PGP000365 | Wong CK et al. PLoS One (2022) |
Incident hypertension | hypertensive disorder | 309,759 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002778/ScoringFiles/PGS002778.txt.gz | |
| PGS002794 (PRS_VTE) |
PGP000375 | Xie J et al. J Thromb Haemost (2022) |
Venous thromboembolism | venous thromboembolism | 10 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002794/ScoringFiles/PGS002794.txt.gz |
| PGS002809 (GRS_CAD) |
PGP000388 | Ahmed R et al. Int J Cardiol Heart Vasc (2022) |
Coronary artery disease | coronary artery disorder | 205 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002809/ScoringFiles/PGS002809.txt.gz |
| PGS002814 (AF-PRS) |
PGP000392 | Miyazawa K et al. Nat Genet (2023) |
Atrial fibrillation | atrial fibrillation | 4,520 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002814/ScoringFiles/PGS002814.txt.gz | |
| PGS002994 (ExPRSweb_Hypertension_20002-1065_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 724,579 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002994/ScoringFiles/PGS002994.txt.gz | |
| PGS002995 (ExPRSweb_Hypertension_20002-1065_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 26,671 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002995/ScoringFiles/PGS002995.txt.gz | |
| PGS002996 (ExPRSweb_Hypertension_20002-1065_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 25,909 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002996/ScoringFiles/PGS002996.txt.gz | |
| PGS002997 (ExPRSweb_Hypertension_20002-1065_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 7,601,215 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002997/ScoringFiles/PGS002997.txt.gz | |
| PGS002998 (ExPRSweb_Hypertension_20002-1065_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 1,113,832 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002998/ScoringFiles/PGS002998.txt.gz | |
| PGS002999 (ExPRSweb_Hypertension_20002-1072_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 313,080 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002999/ScoringFiles/PGS002999.txt.gz | |
| PGS003000 (ExPRSweb_Hypertension_20002-1072_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 83,829 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003000/ScoringFiles/PGS003000.txt.gz | |
| PGS003001 (ExPRSweb_Hypertension_20002-1072_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 81,218 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003001/ScoringFiles/PGS003001.txt.gz | |
| PGS003002 (ExPRSweb_Hypertension_20002-1072_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 7,601,215 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003002/ScoringFiles/PGS003002.txt.gz | |
| PGS003003 (ExPRSweb_Hypertension_20002-1072_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 1,109,030 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003003/ScoringFiles/PGS003003.txt.gz | |
| PGS003004 (ExPRSweb_Hypertension_finngen-R4-FG_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 4,943 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003004/ScoringFiles/PGS003004.txt.gz | |
| PGS003005 (ExPRSweb_Hypertension_finngen-R4-FG_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 2,860 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003005/ScoringFiles/PGS003005.txt.gz | |
| PGS003006 (ExPRSweb_Hypertension_finngen-R4-FG_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 5,212 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003006/ScoringFiles/PGS003006.txt.gz | |
| PGS003007 (ExPRSweb_Hypertension_finngen-R4-FG_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 359 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003007/ScoringFiles/PGS003007.txt.gz | |
| PGS003008 (ExPRSweb_Hypertension_finngen-R4-FG_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 12,076 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003008/ScoringFiles/PGS003008.txt.gz | |
| PGS003009 (ExPRSweb_Hypertension_finngen-R4-I9_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 5,226 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003009/ScoringFiles/PGS003009.txt.gz | |
| PGS003010 (ExPRSweb_Hypertension_finngen-R4-I9_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 1,894 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003010/ScoringFiles/PGS003010.txt.gz | |
| PGS003011 (ExPRSweb_Hypertension_finngen-R4-I9_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 3,300 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003011/ScoringFiles/PGS003011.txt.gz | |
| PGS003012 (ExPRSweb_Hypertension_finngen-R4-I9_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 361 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003012/ScoringFiles/PGS003012.txt.gz | |
| PGS003013 (ExPRSweb_Hypertension_finngen-R4-I9_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 12,076 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003013/ScoringFiles/PGS003013.txt.gz | |
| PGS003014 (ExPRSweb_Hypertension_I10_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 294,142 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003014/ScoringFiles/PGS003014.txt.gz | |
| PGS003015 (ExPRSweb_Hypertension_I10_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 58,725 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003015/ScoringFiles/PGS003015.txt.gz | |
| PGS003016 (ExPRSweb_Hypertension_I10_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 56,978 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003016/ScoringFiles/PGS003016.txt.gz | |
| PGS003017 (ExPRSweb_Hypertension_I10_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 7,094,727 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003017/ScoringFiles/PGS003017.txt.gz | |
| PGS003018 (ExPRSweb_Hypertension_I10_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 1,096,197 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003018/ScoringFiles/PGS003018.txt.gz | |
| PGS003019 (ExPRSweb_Hypertension_finngen-R4-FG_LASSOSUM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 6,731 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003019/ScoringFiles/PGS003019.txt.gz | |
| PGS003020 (ExPRSweb_Hypertension_finngen-R4-FG_PT_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 24 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003020/ScoringFiles/PGS003020.txt.gz | |
| PGS003021 (ExPRSweb_Hypertension_finngen-R4-FG_PLINK_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 24 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003021/ScoringFiles/PGS003021.txt.gz | |
| PGS003022 (ExPRSweb_Hypertension_finngen-R4-FG_DBSLMM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 56 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003022/ScoringFiles/PGS003022.txt.gz | |
| PGS003023 (ExPRSweb_Hypertension_finngen-R4-FG_PRSCS_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 12,097 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003023/ScoringFiles/PGS003023.txt.gz | |
| PGS003024 (ExPRSweb_Hypertension_finngen-R4-I9_LASSOSUM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 7,123 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003024/ScoringFiles/PGS003024.txt.gz | |
| PGS003025 (ExPRSweb_Hypertension_finngen-R4-I9_PT_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 9 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003025/ScoringFiles/PGS003025.txt.gz | |
| PGS003026 (ExPRSweb_Hypertension_finngen-R4-I9_PLINK_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 9 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003026/ScoringFiles/PGS003026.txt.gz | |
| PGS003027 (ExPRSweb_Hypertension_finngen-R4-I9_DBSLMM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 59 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003027/ScoringFiles/PGS003027.txt.gz | |
| PGS003028 (ExPRSweb_Hypertension_finngen-R4-I9_PRSCS_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertensive disorder | 12,097 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003028/ScoringFiles/PGS003028.txt.gz | |
| PGS003332 (PRS_VTE_EUR_GHOUSE) |
PGP000398 | Ghouse J et al. Nat Genet (2023) |
Venous thromboembolism | venous thromboembolism | 1,092,045 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003332/ScoringFiles/PGS003332.txt.gz |
| PGS003355 (1MH_CAD_PRS_2015_Ldpred) |
PGP000409 | Aragam KG et al. Nat Genet (2022) |
Coronary artery disease | coronary artery disorder | 1,532,758 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003355/ScoringFiles/PGS003355.txt.gz |
| PGS003356 (1MH_CAD_PRS_2022_Ldpred) |
PGP000409 | Aragam KG et al. Nat Genet (2022) |
Coronary artery disease | coronary artery disorder | 2,324,683 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003356/ScoringFiles/PGS003356.txt.gz |
| PGS003406 (1_withUKB_sexAll_metaGRS.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm | 6,852,195 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003406/ScoringFiles/PGS003406.txt.gz | |
| PGS003407 (2_withUKB_sexMale_metaGRS.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm, male |
6,618,190 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003407/ScoringFiles/PGS003407.txt.gz | |
| PGS003408 (3_withUKB_sexFemale_metaGRS.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm, female |
6,671,269 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003408/ScoringFiles/PGS003408.txt.gz | |
| PGS003409 (4_withUKB_sexAll_IAonly.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm | 6,852,195 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003409/ScoringFiles/PGS003409.txt.gz | |
| PGS003410 (5_withUKB_sexMale_IAonly.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm, male |
6,618,190 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003410/ScoringFiles/PGS003410.txt.gz | |
| PGS003411 (6_withUKB_sexFemale_IAonly.weights) |
PGP000423 | Bakker MK et al. Stroke (2023) |
Intracranial aneurysm | brain aneurysm, female |
6,671,269 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003411/ScoringFiles/PGS003411.txt.gz | |
| PGS003429 (AAA) |
PGP000436 | Kelemen M et al. Nat Commun (2024) |
Abdominal aortic aneurysm | abdominal aortic aneurysm | 831,447 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003429/ScoringFiles/PGS003429.txt.gz |
| PGS003438 (PRS241_CAD) |
PGP000440 | Marston NA et al. JAMA Cardiol (2023) |
Coronary artery disease | coronary artery disorder | 241 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003438/ScoringFiles/PGS003438.txt.gz |
| PGS003446 (TEM_CAD_PRS) |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |
Coronary artery disease | coronary artery disorder | 538,084 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003446/ScoringFiles/PGS003446.txt.gz |
| PGS003456 (PRS273_VTE) |
PGP000449 | Folsom AR et al. PLoS One (2023) |
Venous thromboembolism | venous thromboembolism | 273 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003456/ScoringFiles/PGS003456.txt.gz |
| PGS003457 (GRS_ICH) |
PGP000450 | Mayerhofer E et al. Stroke (2023) |
Intracerebral hemorrhage | intracerebral hemorrhage | 682,890 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003457/ScoringFiles/PGS003457.txt.gz | |
| PGS003461 (GRS162_AF) |
PGP000454 | Yang L et al. NPJ Digit Med (2023) |
Atrial fibrillation | atrial fibrillation | 162 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003461/ScoringFiles/PGS003461.txt.gz |
| PGS003586 (PE) |
PGP000462 | Honigberg MC et al. Nat Med (2023) |
Pre-eclampsia | preeclampsia | 1,087,033 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003586/ScoringFiles/PGS003586.txt.gz | |
| PGS003587 (GH) |
PGP000462 | Honigberg MC et al. Nat Med (2023) |
Gestational hypertension | preeclampsia | 1,087,916 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003587/ScoringFiles/PGS003587.txt.gz | |
| PGS003725 (GPS_Mult) |
PGP000466 | Patel AP et al. Nat Med (2023) |
Coronary artery disease | coronary artery disorder | 1,296,172 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003725/ScoringFiles/PGS003725.txt.gz | |
| PGS003726 (GPS_CADANC) |
PGP000466 | Patel AP et al. Nat Med (2023) |
Coronary artery disease | coronary artery disorder | 1,296,172 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003726/ScoringFiles/PGS003726.txt.gz | |
| PGS003727 (GPS_CADEUR) |
PGP000466 | Patel AP et al. Nat Med (2023) |
Coronary artery disease | coronary artery disorder | 1,125,113 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003727/ScoringFiles/PGS003727.txt.gz | |
| PGS003761 (PRS165_AF) |
PGP000484 | Zhang J et al. BMC Med (2023) |
Atrial fibrillation | atrial fibrillation | 165 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003761/ScoringFiles/PGS003761.txt.gz |
| PGS003861 (PRS288_PE) |
PGP000499 | Zhang Z et al. BMC Med (2023) |
Pulmonary embolism | pulmonary embolism | 288 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003861/ScoringFiles/PGS003861.txt.gz |
| PGS003866 (CAD_lassosum2_ARB) |
PGP000501 | Shim I et al. Nature Communications (2023) |
Coronary artery disease | coronary artery disorder | 10,440 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003866/ScoringFiles/PGS003866.txt.gz |
| PGS003868 (CM_LDpred2_ARB) |
PGP000501 | Shim I et al. Nature Communications (2023) |
Cardiomyopathy | cardiomyopathy | 1,010,014 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003868/ScoringFiles/PGS003868.txt.gz |
| PGS003969 (PRS39_HF) |
PGP000511 | Rasooly D et al. Nat Commun (2023) |
Heart failure | heart failure | 39 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003969/ScoringFiles/PGS003969.txt.gz |
| PGS003972 (PRSAAA) |
PGP000513 | Roychowdhury T et al. Nat Genet (2023) |
Abdominal aortic aneurysm | abdominal aortic aneurysm | 1,118,997 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003972/ScoringFiles/PGS003972.txt.gz |
| PGS003973 (PRSAAA_woUKB) |
PGP000513 | Roychowdhury T et al. Nat Genet (2023) |
Abdominal aortic aneurysm | abdominal aortic aneurysm | 1,118,997 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003973/ScoringFiles/PGS003973.txt.gz |
| PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,121,845 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003984/ScoringFiles/PGS003984.txt.gz | |
| PGS004000 (lassosum.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 2,371 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004000/ScoringFiles/PGS004000.txt.gz | |
| PGS004015 (lassosum.CV.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 65,138 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004015/ScoringFiles/PGS004015.txt.gz | |
| PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,011,468 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004026/ScoringFiles/PGS004026.txt.gz | |
| PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,011,468 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004041/ScoringFiles/PGS004041.txt.gz | |
| PGS004054 (megaprs.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 852,173 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004054/ScoringFiles/PGS004054.txt.gz | |
| PGS004070 (megaprs.CV.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 852,173 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004070/ScoringFiles/PGS004070.txt.gz | |
| PGS004084 (prscs.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,091,747 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004084/ScoringFiles/PGS004084.txt.gz | |
| PGS004098 (prscs.CV.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,091,747 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004098/ScoringFiles/PGS004098.txt.gz | |
| PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 13 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004108/ScoringFiles/PGS004108.txt.gz | |
| PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 5,808 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004124/ScoringFiles/PGS004124.txt.gz | |
| PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 888,649 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004138/ScoringFiles/PGS004138.txt.gz | |
| PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Stroke | stroke disorder | 1,116,976 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004154/ScoringFiles/PGS004154.txt.gz | |
| PGS004186 (afib_1) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Atrial fibrillation | atrial fibrillation | 3,082 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004186/ScoringFiles/PGS004186.txt.gz |
| PGS004187 (afib_2) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Atrial fibrillation | atrial fibrillation | 5,118 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004187/ScoringFiles/PGS004187.txt.gz |
| PGS004188 (afib_3) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Atrial fibrillation | atrial fibrillation | 2,420 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004188/ScoringFiles/PGS004188.txt.gz |
| PGS004189 (afib_4) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Atrial fibrillation | atrial fibrillation | 3,434 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004189/ScoringFiles/PGS004189.txt.gz |
| PGS004190 (afib_5) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Atrial fibrillation | atrial fibrillation | 1,972 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004190/ScoringFiles/PGS004190.txt.gz |
| PGS004191 (hyper_1) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Hypertension | hypertensive disorder | 23,280 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004191/ScoringFiles/PGS004191.txt.gz |
| PGS004192 (hyper_2) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Hypertension | hypertensive disorder | 9,430 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004192/ScoringFiles/PGS004192.txt.gz |
| PGS004193 (hyper_3) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Hypertension | hypertensive disorder | 18,580 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004193/ScoringFiles/PGS004193.txt.gz |
| PGS004194 (hyper_4) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Hypertension | hypertensive disorder | 14,063 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004194/ScoringFiles/PGS004194.txt.gz |
| PGS004195 (hyper_5) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Hypertension | hypertensive disorder | 2,755 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004195/ScoringFiles/PGS004195.txt.gz |
| PGS004196 (cad_1) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Coronary artery disease | coronary artery disorder | 3,892 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004196/ScoringFiles/PGS004196.txt.gz |
| PGS004197 (cad_2) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Coronary artery disease | coronary artery disorder | 11,490 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004197/ScoringFiles/PGS004197.txt.gz |
| PGS004198 (cad_3) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Coronary artery disease | coronary artery disorder | 5,723 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004198/ScoringFiles/PGS004198.txt.gz |
| PGS004199 (cad_4) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Coronary artery disease | coronary artery disorder | 6,085 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004199/ScoringFiles/PGS004199.txt.gz |
| PGS004200 (cad_5) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Coronary artery disease | coronary artery disorder | 8,361 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004200/ScoringFiles/PGS004200.txt.gz |
| PGS004234 (HTN_PAN-UKBB) |
PGP000531 | Kurniansyah N et al. Nat Commun (2022) |
Hypertension | hypertensive disorder | 234,228 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004234/ScoringFiles/PGS004234.txt.gz | |
| PGS004236 (HTN_Unweighted_PRSsum) |
PGP000531 | Kurniansyah N et al. Nat Commun (2022) |
Hypertension | hypertensive disorder | 398,805 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004236/ScoringFiles/PGS004236.txt.gz | |
| PGS004237 (CAD_PRS_LDpred_UKB_Pub1) |
PGP000532 | Manikpurage HD et al. Circ Genom Precis Med (2021) |
Coronary Artery Disease | coronary artery disorder | 1,146,511 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004237/ScoringFiles/PGS004237.txt.gz | |
| PGS004238 (wGRS35) |
PGP000535 | Cheng CF et al. J Gene Med (2021) |
Cardiovascular disease | cardiovascular disorder | 35 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004238/ScoringFiles/PGS004238.txt.gz |
| PGS004290 (GenoBoost_atrial_fibrillation_0) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Atrial fibrillation | atrial fibrillation | 3,000 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004290/ScoringFiles/PGS004290.txt.gz |
| PGS004291 (GenoBoost_atrial_fibrillation_1) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Atrial fibrillation | atrial fibrillation | 3,000 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004291/ScoringFiles/PGS004291.txt.gz |
| PGS004292 (GenoBoost_atrial_fibrillation_2) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Atrial fibrillation | atrial fibrillation | 700 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004292/ScoringFiles/PGS004292.txt.gz |
| PGS004293 (GenoBoost_atrial_fibrillation_3) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Atrial fibrillation | atrial fibrillation | 2,000 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004293/ScoringFiles/PGS004293.txt.gz |
| PGS004294 (GenoBoost_atrial_fibrillation_4) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Atrial fibrillation | atrial fibrillation | 2,000 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004294/ScoringFiles/PGS004294.txt.gz |
| PGS004305 (GenoBoost_coronary_artery_disease_0) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Coronary artery disease | coronary artery disorder | 3,000 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004305/ScoringFiles/PGS004305.txt.gz |
| PGS004306 (GenoBoost_coronary_artery_disease_1) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Coronary artery disease | coronary artery disorder | 4,000 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004306/ScoringFiles/PGS004306.txt.gz |
| PGS004307 (GenoBoost_coronary_artery_disease_2) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Coronary artery disease | coronary artery disorder | 4,000 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004307/ScoringFiles/PGS004307.txt.gz |
| PGS004308 (GenoBoost_coronary_artery_disease_3) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Coronary artery disease | coronary artery disorder | 1,500 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004308/ScoringFiles/PGS004308.txt.gz |
| PGS004309 (GenoBoost_coronary_artery_disease_4) |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Coronary artery disease | coronary artery disorder | 3,000 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004309/ScoringFiles/PGS004309.txt.gz |
| PGS004321 (PRS27_CAD) |
PGP000554 | Marston NA et al. Circulation (2019) |
Coronary heart disease | coronary artery disorder | 27 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004321/ScoringFiles/PGS004321.txt.gz |
| PGS004322 (GRS30_IS) |
PGP000555 | McElligott B et al. Front Cardiovasc Med (2023) |
Ischemic stroke | Ischemic stroke, stroke disorder |
30 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004322/ScoringFiles/PGS004322.txt.gz |
| PGS004440 (disease.Atrial_fibrillation.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Atrial fibrillation | atrial fibrillation | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004440/ScoringFiles/PGS004440.txt.gz |
| PGS004443 (disease.CAD.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Coronary artery disease (CAD) | coronary artery disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004443/ScoringFiles/PGS004443.txt.gz |
| PGS004444 (disease.CVD.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Coronary vascular disease (CVD) | coronary artery disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004444/ScoringFiles/PGS004444.txt.gz |
| PGS004455 (disease.Hypertension.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Hypertension | hypertensive disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004455/ScoringFiles/PGS004455.txt.gz |
| PGS004456 (disease.I10.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I10 (Essential (primary) hypertension) | essential hypertension | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004456/ScoringFiles/PGS004456.txt.gz |
| PGS004458 (disease.I21.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I21 (Acute myocardial infarction) | acute myocardial infarction | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004458/ScoringFiles/PGS004458.txt.gz |
| PGS004459 (disease.I25.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I25 (Chronic ischemic heart disease) | heart disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004459/ScoringFiles/PGS004459.txt.gz |
| PGS004460 (disease.I26.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I26 (Pulmonary embolism) | pulmonary embolism | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004460/ScoringFiles/PGS004460.txt.gz |
| PGS004461 (disease.I48.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I48 (Atrial fibrillation and flutter) | atrial fibrillation | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004461/ScoringFiles/PGS004461.txt.gz |
| PGS004462 (disease.I50.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I50 (Heart failure) | heart failure | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004462/ScoringFiles/PGS004462.txt.gz |
| PGS004464 (disease.I84.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I84 (Hemorrhoids) | hemorrhoid | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004464/ScoringFiles/PGS004464.txt.gz |
| PGS004501 (disease.VTE.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Venous thromboembolism (VTE) | venous thromboembolism | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004501/ScoringFiles/PGS004501.txt.gz |
| PGS004510 (meta.Atrial_fibrillation.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Atrial fibrillation | atrial fibrillation | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004510/ScoringFiles/PGS004510.txt.gz |
| PGS004513 (meta.CAD.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Coronary artery disease (CAD) | coronary artery disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004513/ScoringFiles/PGS004513.txt.gz |
| PGS004514 (meta.CVD.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Coronary vascular disease (CVD) | coronary artery disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004514/ScoringFiles/PGS004514.txt.gz |
| PGS004525 (meta.Hypertension.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Hypertension | hypertensive disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004525/ScoringFiles/PGS004525.txt.gz |
| PGS004526 (meta.I10.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I10 (Essential (primary) hypertension) | essential hypertension | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004526/ScoringFiles/PGS004526.txt.gz |
| PGS004528 (meta.I21.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I21 (Acute myocardial infarction) | acute myocardial infarction | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004528/ScoringFiles/PGS004528.txt.gz |
| PGS004529 (meta.I25.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I25 (Chronic ischemic heart disease) | heart disorder | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004529/ScoringFiles/PGS004529.txt.gz |
| PGS004530 (meta.I26.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I26 (Pulmonary embolism) | pulmonary embolism | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004530/ScoringFiles/PGS004530.txt.gz |
| PGS004531 (meta.I48.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I48 (Atrial fibrillation and flutter) | atrial fibrillation | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004531/ScoringFiles/PGS004531.txt.gz |
| PGS004532 (meta.I50.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I50 (Heart failure) | heart failure | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004532/ScoringFiles/PGS004532.txt.gz |
| PGS004534 (meta.I84.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
I84 (Hemorrhoids) | hemorrhoid | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004534/ScoringFiles/PGS004534.txt.gz |
| PGS004571 (meta.VTE.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Venous thromboembolism (VTE) | venous thromboembolism | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004571/ScoringFiles/PGS004571.txt.gz |
| PGS004593 (pe) |
PGP000574 | Nurkkala J et al. J Hypertens (2022) |
Preeclampsia | preeclampsia | 1,102,059 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004593/ScoringFiles/PGS004593.txt.gz |
| PGS004595 (PRS_CHD) |
PGP000575 | Oni-Orisan A et al. Clin Pharmacol Ther (2022) |
Coronary heart disease | coronary artery disorder | 164 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004595/ScoringFiles/PGS004595.txt.gz |
| PGS004596 (PRS64_CHD) |
PGP000576 | Peng H et al. Nutrients (2023) |
Coronary heart disease | coronary artery disorder | 64 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004596/ScoringFiles/PGS004596.txt.gz |
| PGS004597 (PRS32_IS) |
PGP000576 | Peng H et al. Nutrients (2023) |
Ischemic stroke | Ischemic stroke, stroke disorder |
32 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004597/ScoringFiles/PGS004597.txt.gz |
| PGS004598 (PRS12_HF) |
PGP000576 | Peng H et al. Nutrients (2023) |
Heart failure | heart failure | 12 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004598/ScoringFiles/PGS004598.txt.gz |
| PGS004612 (PRSECG_AI) |
PGP000591 | Wang X et al. Circ Genom Precis Med (2023) |
ECG-AI predicted 5-year risk of atrial fibrillation | atrial fibrillation | 1,117,399 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004612/ScoringFiles/PGS004612.txt.gz |
| PGS004613 (PRSCHARGE_AF) |
PGP000591 | Wang X et al. Circ Genom Precis Med (2023) |
CHARGE-AF predicted 5-year risk of atrial fibrillation | atrial fibrillation | 1,117,400 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004613/ScoringFiles/PGS004613.txt.gz |
| PGS004696 (multi_anc_hg37CSx) |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Coronary heart disease | coronary artery disorder | 1,289,980 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004696/ScoringFiles/PGS004696.txt.gz | |
| PGS004697 (eur_anc_hg37CSx) |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Coronary heart disease | coronary artery disorder | 1,120,251 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004697/ScoringFiles/PGS004697.txt.gz | |
| PGS004698 (multi_anc_hg37PT) |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Coronary heart disease | coronary artery disorder | 542,218 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004698/ScoringFiles/PGS004698.txt.gz | |
| PGS004705 (afib_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Atrial Fibrillation | atrial fibrillation | 3,575,124 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004705/ScoringFiles/PGS004705.txt.gz |
| PGS004706 (afib_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Atrial Fibrillation | atrial fibrillation | 3,576,958 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004706/ScoringFiles/PGS004706.txt.gz |
| PGS004743 (cad_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Coronary artery disease | coronary artery disorder | 3,606,321 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004743/ScoringFiles/PGS004743.txt.gz |
| PGS004744 (cad_PRSmix_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Coronary artery disease | coronary artery disorder | 7,082,943 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004744/ScoringFiles/PGS004744.txt.gz |
| PGS004745 (cad_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Coronary artery disease | coronary artery disorder | 4,769,577 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004745/ScoringFiles/PGS004745.txt.gz |
| PGS004746 (cad_PRSmixPlus_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Coronary artery disease | coronary artery disorder | 6,483,064 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004746/ScoringFiles/PGS004746.txt.gz |
| PGS004785 (HTN_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Hypertension | hypertensive disorder | 1,170,615 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004785/ScoringFiles/PGS004785.txt.gz |
| PGS004786 (HTN_PRSmix_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Hypertension | hypertensive disorder | 6,622,611 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004786/ScoringFiles/PGS004786.txt.gz |
| PGS004787 (HTN_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Hypertension | hypertensive disorder | 5,191,115 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004787/ScoringFiles/PGS004787.txt.gz |
| PGS004788 (HTN_PRSmixPlus_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Hypertension | hypertensive disorder | 6,622,611 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004788/ScoringFiles/PGS004788.txt.gz |
| PGS004797 (migraine_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Migraine | migraine disorder | 23 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004797/ScoringFiles/PGS004797.txt.gz |
| PGS004798 (migraine_PRSmix_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Migraine | migraine disorder | 3,984,158 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004798/ScoringFiles/PGS004798.txt.gz |
| PGS004799 (migraine_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Migraine | migraine disorder | 4,319,950 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004799/ScoringFiles/PGS004799.txt.gz |
| PGS004800 (migraine_PRSmixPlus_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Migraine | migraine disorder | 2,968,987 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004800/ScoringFiles/PGS004800.txt.gz |
| PGS004835 (stroke_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Stroke | stroke disorder | 2,263,784 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004835/ScoringFiles/PGS004835.txt.gz |
| PGS004836 (stroke_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Stroke | stroke disorder | 5,644,266 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004836/ScoringFiles/PGS004836.txt.gz |
| PGS004853 (VTE_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Venous thromboembolism | venous thromboembolism | 828,099 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004853/ScoringFiles/PGS004853.txt.gz |
| PGS004854 (VTE_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Venous thromboembolism | venous thromboembolism | 2,268,993 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004854/ScoringFiles/PGS004854.txt.gz |
| PGS004861 (hermes.gwama) |
PGP000608 | Zheng SL et al. Nat Genet (2024) |
Dilated cardiomyopathy | dilated cardiomyopathy | 713,932 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004861/ScoringFiles/PGS004861.txt.gz |
| PGS004862 (hermes.mtag) |
PGP000608 | Zheng SL et al. Nat Genet (2024) |
Dilated cardiomyopathy (MTAG) | dilated cardiomyopathy | 709,534 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004862/ScoringFiles/PGS004862.txt.gz |
| PGS004878 (INTERVENE_MegaPRS_Atrial_fibrillation) |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Atrial fibrillation | atrial fibrillation | 785,779 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004878/ScoringFiles/PGS004878.txt.gz | |
| PGS004879 (INTERVENE_MegaPRS_CHD) |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Coronary heart disease | coronary artery disorder | 610,677 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004879/ScoringFiles/PGS004879.txt.gz | |
| PGS004888 (CAD_gePGS) |
PGP000619 | Mandla R et al. Genome Med (2024) |
Coronary artery diseae | coronary artery disorder | 1,110,046 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004888/ScoringFiles/PGS004888.txt.gz | |
| PGS004899 (PRS_SCAD) |
PGP000629 | Saw J et al. Nat Commun (2020) |
Spontaneous coronary artery dissection | spontaneous coronary artery dissection | 7 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004899/ScoringFiles/PGS004899.txt.gz |
| PGS004905 (PRS155_AF) |
PGP000638 | Ma Y et al. Proc Natl Acad Sci U S A (2023) |
Atrial fibrillation | atrial fibrillation | 155 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004905/ScoringFiles/PGS004905.txt.gz |
| PGS004910 (hcm.gwama) |
PGP000642 | Zheng SL et al. Nat Genet (2025) |
Hypertrophic cardiomyopathy | hypertrophic cardiomyopathy | 374,190 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004910/ScoringFiles/PGS004910.txt.gz |
| PGS004911 (hcm.mtag) |
PGP000642 | Zheng SL et al. Nat Genet (2025) |
Hypertrophic cardiomyopathy (MTAG) | hypertrophic cardiomyopathy | 374,114 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004911/ScoringFiles/PGS004911.txt.gz |
| PGS004920 (GRS166_AF) |
PGP000652 | Wang N et al. Eur Heart J (2021) |
Atrial fibrillation | atrial fibrillation | 166 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004920/ScoringFiles/PGS004920.txt.gz |
| PGS004921 (CAD-GRS) |
PGP000654 | Huang Y et al. Circ Genom Precis Med (2020) |
Coronary artery disease | coronary artery disorder | 161 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004921/ScoringFiles/PGS004921.txt.gz | |
| PGS004925 (PRS300_CHD) |
PGP000660 | Kim Y et al. J Intern Med (2023) |
Coronary heart disease | coronary artery disorder | 300 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004925/ScoringFiles/PGS004925.txt.gz |
| PGS004929 (AF_Ldpred2_combined) |
PGP000665 | Moreno-Grau S et al. Human Genomics (2024) |
Atrial fibrillation | atrial fibrillation | 178,814 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004929/ScoringFiles/PGS004929.txt.gz |
| PGS004933 (hemorrhoid_LDpred2_combined) |
PGP000665 | Moreno-Grau S et al. Human Genomics (2024) |
Hemorrhoid | hemorrhoid | 184,519 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004933/ScoringFiles/PGS004933.txt.gz |
| PGS004934 (hypertension_snpnet_combined) |
PGP000665 | Moreno-Grau S et al. Human Genomics (2024) |
Hypertension | hypertensive disorder | 15,056 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004934/ScoringFiles/PGS004934.txt.gz |
| PGS004941 (CAD_MetaPRS) |
PGP000668 | China Kadoorie Biobank Collaborative Group. et al. Nat Hum Behav (2024) |
Coronary artery disease | coronary artery disorder | 3,711,629 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004941/ScoringFiles/PGS004941.txt.gz |
| PGS004943 (ICH_MetaPRS) |
PGP000668 | China Kadoorie Biobank Collaborative Group. et al. Nat Hum Behav (2024) |
Intracerebral hemorrhage | intracerebral hemorrhage | 2,124,631 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004943/ScoringFiles/PGS004943.txt.gz |
| PGS004946 (DCM_GWAS_exclMGBB) |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Dilated cardiomyopathy | dilated cardiomyopathy | 1,098,677 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004946/ScoringFiles/PGS004946.txt.gz |
| PGS004947 (DCM_MTAG_exclMGBB) |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Dilated cardiomyopathy (MTAG) | dilated cardiomyopathy | 1,072,247 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004947/ScoringFiles/PGS004947.txt.gz |
| PGS004948 (DCM_GWAS_exclUKB) |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Dilated cardiomyopathy | dilated cardiomyopathy | 1,068,761 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004948/ScoringFiles/PGS004948.txt.gz |
| PGS004949 (DCM_MTAG_exclUKB) |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Dilated cardiomyopathy (MTAG) | dilated cardiomyopathy | 1,038,394 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004949/ScoringFiles/PGS004949.txt.gz |
| PGS004950 (DCM_GWAS_exclAUMC) |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Dilated cardiomyopathy | dilated cardiomyopathy | 1,098,677 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004950/ScoringFiles/PGS004950.txt.gz |
| PGS004951 (DCM_MTAG_exclAUMC) |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Dilated cardiomyopathy (MTAG) | dilated cardiomyopathy | 1,075,760 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004951/ScoringFiles/PGS004951.txt.gz |
| PGS005034 (Phe_411_2_ldpred_AFRss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005034/ScoringFiles/PGS005034.txt.gz |
| PGS005035 (Phe_411_2_ldpred_EURss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005035/ScoringFiles/PGS005035.txt.gz |
| PGS005036 (Phe_411_2_ldpred_HISss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005036/ScoringFiles/PGS005036.txt.gz |
| PGS005037 (Phe_411_2_ldpred_METAss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005037/ScoringFiles/PGS005037.txt.gz |
| PGS005038 (Phe_411_2_ldpred_METAss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005038/ScoringFiles/PGS005038.txt.gz |
| PGS005039 (Phe_411_2_ldpred_METAss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005039/ScoringFiles/PGS005039.txt.gz |
| PGS005040 (Phe_411_2_prscs_AFRss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005040/ScoringFiles/PGS005040.txt.gz |
| PGS005041 (Phe_411_2_prscs_EURss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005041/ScoringFiles/PGS005041.txt.gz |
| PGS005042 (Phe_411_2_prscs_HISss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005042/ScoringFiles/PGS005042.txt.gz |
| PGS005043 (Phe_411_2_prscs_METAss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005043/ScoringFiles/PGS005043.txt.gz |
| PGS005044 (Phe_411_2_prscs_METAss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005044/ScoringFiles/PGS005044.txt.gz |
| PGS005045 (Phe_411_2_prscs_METAss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005045/ScoringFiles/PGS005045.txt.gz |
| PGS005046 (Phe_411_2_prscsx_METAweight) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Myocardial infarction (PheCode 411.2) | myocardial infarction | 1,273,891 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005046/ScoringFiles/PGS005046.txt.gz |
| PGS005060 (Phe_427_21_ldpred_AFRss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005060/ScoringFiles/PGS005060.txt.gz |
| PGS005061 (Phe_427_21_ldpred_EURss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005061/ScoringFiles/PGS005061.txt.gz |
| PGS005062 (Phe_427_21_ldpred_HISss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005062/ScoringFiles/PGS005062.txt.gz |
| PGS005063 (Phe_427_21_ldpred_METAss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005063/ScoringFiles/PGS005063.txt.gz |
| PGS005064 (Phe_427_21_ldpred_METAss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005064/ScoringFiles/PGS005064.txt.gz |
| PGS005065 (Phe_427_21_ldpred_METAss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005065/ScoringFiles/PGS005065.txt.gz |
| PGS005066 (Phe_427_21_prscs_AFRss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005066/ScoringFiles/PGS005066.txt.gz |
| PGS005067 (Phe_427_21_prscs_EURss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005067/ScoringFiles/PGS005067.txt.gz |
| PGS005068 (Phe_427_21_prscs_HISss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005068/ScoringFiles/PGS005068.txt.gz |
| PGS005069 (Phe_427_21_prscs_METAss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005069/ScoringFiles/PGS005069.txt.gz |
| PGS005070 (Phe_427_21_prscs_METAss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005070/ScoringFiles/PGS005070.txt.gz |
| PGS005071 (Phe_427_21_prscs_METAss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005071/ScoringFiles/PGS005071.txt.gz |
| PGS005072 (Phe_427_21_prscsx_METAweight) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Atrial fibrillation (PheCode 427.21) | atrial fibrillation | 1,273,891 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005072/ScoringFiles/PGS005072.txt.gz |
| PGS005073 (Phe_428_1_ldpred_AFRss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005073/ScoringFiles/PGS005073.txt.gz |
| PGS005074 (Phe_428_1_ldpred_EURss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005074/ScoringFiles/PGS005074.txt.gz |
| PGS005075 (Phe_428_1_ldpred_HISss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005075/ScoringFiles/PGS005075.txt.gz |
| PGS005076 (Phe_428_1_ldpred_METAss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005076/ScoringFiles/PGS005076.txt.gz |
| PGS005077 (Phe_428_1_ldpred_METAss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005077/ScoringFiles/PGS005077.txt.gz |
| PGS005078 (Phe_428_1_ldpred_METAss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,286,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005078/ScoringFiles/PGS005078.txt.gz |
| PGS005079 (Phe_428_1_prscs_AFRss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005079/ScoringFiles/PGS005079.txt.gz |
| PGS005080 (Phe_428_1_prscs_EURss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005080/ScoringFiles/PGS005080.txt.gz |
| PGS005081 (Phe_428_1_prscs_HISss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005081/ScoringFiles/PGS005081.txt.gz |
| PGS005082 (Phe_428_1_prscs_METAss_afrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005082/ScoringFiles/PGS005082.txt.gz |
| PGS005083 (Phe_428_1_prscs_METAss_amrld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005083/ScoringFiles/PGS005083.txt.gz |
| PGS005084 (Phe_428_1_prscs_METAss_eurld) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,273,897 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005084/ScoringFiles/PGS005084.txt.gz |
| PGS005085 (Phe_428_1_prscsx_METAweight) |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Congestive heart failure (CHF), NOS (PheCode 428.1) | congestive heart failure | 1,256,161 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005085/ScoringFiles/PGS005085.txt.gz |
| PGS005091 (PGS_LDP2Auto) |
PGP000684 | Abramowitz SA et al. JAMA (2024) |
Coronary artery disease | coronary artery disorder | 1,428,772 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005091/ScoringFiles/PGS005091.txt.gz |
| PGS005092 (PGS_prscsx) |
PGP000684 | Abramowitz SA et al. JAMA (2024) |
Coronary artery disease | coronary artery disorder | 1,279,502 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005092/ScoringFiles/PGS005092.txt.gz |
| PGS005093 (MetPRS) |
PGP000685 | Yang X et al. Nat Commun (2026) |
Coronary artery disease | coronary artery disorder | 4,595 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005093/ScoringFiles/PGS005093.txt.gz |
| PGS005094 (ProPRS) |
PGP000685 | Yang X et al. Nat Commun (2026) |
Coronary artery disease | coronary artery disorder | 5,249 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005094/ScoringFiles/PGS005094.txt.gz |
| PGS005097 (prscsx_meta_HF) |
PGP000691 | Lee DSM et al. Nat Genet (2025) |
Heart failure | heart failure | 1,274,692 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005097/ScoringFiles/PGS005097.txt.gz |
| PGS005112 (PGS_CAD) |
PGP000701 | Loesch DP et al. Nat Commun (2025) |
Coronary artery disease | coronary artery disorder | 1,106,628 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005112/ScoringFiles/PGS005112.txt.gz |
| PGS005143 (Coronary artery disease (PRS-CS; EAS)) |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Coronary artery disease | coronary artery disorder | 943,274 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005143/ScoringFiles/PGS005143.txt.gz |
| PGS005144 (Hypertension (PRS-CS; EAS)) |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Hypertension | hypertensive disorder | 908,466 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005144/ScoringFiles/PGS005144.txt.gz |
| PGS005152 (Coronary artery disease (PRS-CSx; EAS+EUR)) |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Coronary artery disease | coronary artery disorder | 943,274 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005152/ScoringFiles/PGS005152.txt.gz |
| PGS005153 (Hypertension (CT-SLEB; EAS+EUR)) |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Hypertension | hypertensive disorder | 492,555 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005153/ScoringFiles/PGS005153.txt.gz |
| PGS005156 (Stroke (PRS-CSx; EAS+EUR)) |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Stroke | stroke disorder | 908,465 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005156/ScoringFiles/PGS005156.txt.gz |
| PGS005158 (PRS19_PAD) |
PGP000705 | Zhu K et al. Diabetes Care (2024) |
Peripheral artery disease | peripheral arterial disease | 19 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005158/ScoringFiles/PGS005158.txt.gz |
| PGS005159 (GRS142_AF) |
PGP000709 | Frederiksen TC et al. Heart (2024) |
Atrial fibrillation | atrial fibrillation | 142 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005159/ScoringFiles/PGS005159.txt.gz |
| PGS005168 (PRSAF) |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Atrial fibrillation | atrial fibrillation | 1,113,668 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005168/ScoringFiles/PGS005168.txt.gz |
| PGS005171 (PRS142_AF) |
PGP000719 | Dai L et al. Diabetes Metab Syndr (2024) |
Atrial fibrillation | atrial fibrillation | 142 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005171/ScoringFiles/PGS005171.txt.gz |
| PGS005217 (PRS_PAD) |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Peripheral artery disease | peripheral arterial disease | 1,296,292 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005217/ScoringFiles/PGS005217.txt.gz | |
| PGS005230 (PRS71_STROKE) |
PGP000736 | Ma Y et al. Stroke (2023) |
Stroke | stroke disorder | 71 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005230/ScoringFiles/PGS005230.txt.gz |
| PGS005231 (GRS142_CAD) |
PGP000738 | Severance LM et al. JACC Cardiovasc Imaging (2021) |
Coronary artery disease | coronary artery disorder | 142 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005231/ScoringFiles/PGS005231.txt.gz |
| PGS005236 (CAD_AnnoPred) |
PGP000740 | Hu J et al. PLoS Comput Biol (2025) |
Coronary artery disease | coronary artery disorder | 2,994,055 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005236/ScoringFiles/PGS005236.txt.gz | |
| PGS005252 (IAVGC_AS_PRS) |
PGP000745 | Small AM et al. Nat Genet (2025) |
Aortic stenosis | aortic stenosis | 1,119,377 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005252/ScoringFiles/PGS005252.txt.gz |
| PGS005253 (CVD_MetaPRS) |
PGP000746 | Sun D et al. Genome Med (2025) |
Cardiovascular disease | cardiovascular disorder | 3,846,195 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005253/ScoringFiles/PGS005253.txt.gz |
| PGS005254 (aortic_stenosis) |
PGP000747 | Kany S et al. Nat Genet (2025) |
Aortic stenosis | aortic stenosis | 1,110,912 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005254/ScoringFiles/PGS005254.txt.gz |
| PGS005255 (mean_gradient) |
PGP000747 | Kany S et al. Nat Genet (2025) |
Mean pressure gradient | aortic stenosis, aortic measurement |
1,111,632 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005255/ScoringFiles/PGS005255.txt.gz |
| PGS005256 (peak_velocity) |
PGP000747 | Kany S et al. Nat Genet (2025) |
Peak aortic velocity | aortic stenosis, aortic measurement |
1,111,632 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005256/ScoringFiles/PGS005256.txt.gz |
| PGS005285 (BBJ_HF_PRS_HG19) |
PGP000757 | Enzan N et al. Nat Commun (2025) |
Heart failure | heart failure | 993,899 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005285/ScoringFiles/PGS005285.txt.gz |
| PGS005287 (Jorda_AF_MTAG-PGS_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Atrial fibrillation | atrial fibrillation | 1,016,634 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005287/ScoringFiles/PGS005287.txt.gz | |
| PGS005288 (Jorda_AF_MTAG-PGS_females_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Atrial fibrillation | atrial fibrillation | 1,016,634 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005288/ScoringFiles/PGS005288.txt.gz | |
| PGS005289 (Jorda_AF_MTAG-PGS_males_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Atrial fibrillation | atrial fibrillation | 1,016,634 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005289/ScoringFiles/PGS005289.txt.gz | |
| PGS005290 (Jorda_AF_SingleTrait-PGS_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Atrial fibrillation | atrial fibrillation | 1,045,170 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005290/ScoringFiles/PGS005290.txt.gz | |
| PGS005291 (Jorda_AF_SingleTrait-PGS_females_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Atrial fibrillation | atrial fibrillation | 1,045,170 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005291/ScoringFiles/PGS005291.txt.gz | |
| PGS005292 (Jorda_AF_SingleTrait-PGS_males_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Atrial fibrillation | atrial fibrillation | 1,045,170 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005292/ScoringFiles/PGS005292.txt.gz | |
| PGS005293 (Jorda_CAD_MTAG-PGS_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Coronary artery disease | coronary artery disorder | 1,003,984 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005293/ScoringFiles/PGS005293.txt.gz | |
| PGS005294 (Jorda_CAD_MTAG-PGS_females_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Coronary artery disease | coronary artery disorder | 1,003,984 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005294/ScoringFiles/PGS005294.txt.gz | |
| PGS005295 (Jorda_CAD_MTAG-PGS_males_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Coronary artery disease | coronary artery disorder | 1,003,984 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005295/ScoringFiles/PGS005295.txt.gz | |
| PGS005296 (Jorda_CAD_SingleTrait-PGS_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Coronary artery disease | coronary artery disorder | 1,042,395 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005296/ScoringFiles/PGS005296.txt.gz | |
| PGS005297 (Jorda_CAD_SingleTrait-PGS_females_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Coronary artery disease | coronary artery disorder | 1,042,395 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005297/ScoringFiles/PGS005297.txt.gz | |
| PGS005298 (Jorda_CAD_SingleTrait-PGS_males_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Coronary artery disease | coronary artery disorder | 1,042,395 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005298/ScoringFiles/PGS005298.txt.gz | |
| PGS005299 (Jorda_HF_MTAG-PGS-inf_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Heart failure | heart failure | 923,722 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005299/ScoringFiles/PGS005299.txt.gz |
| PGS005300 (Jorda_HF_MTAG-PGS_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Heart failure | heart failure | 923,722 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005300/ScoringFiles/PGS005300.txt.gz | |
| PGS005301 (Jorda_HF_MTAG-PGS_females_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Heart failure | heart failure | 923,722 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005301/ScoringFiles/PGS005301.txt.gz | |
| PGS005302 (Jorda_HF_MTAG-PGS_males_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Heart failure | heart failure | 923,722 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005302/ScoringFiles/PGS005302.txt.gz | |
| PGS005303 (Jorda_HF_SingleTrait-PGS-inf_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Heart failure | heart failure | 1,042,531 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005303/ScoringFiles/PGS005303.txt.gz |
| PGS005304 (Jorda_HF_SingleTrait-PGS_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Heart failure | heart failure | 1,042,531 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005304/ScoringFiles/PGS005304.txt.gz | |
| PGS005305 (Jorda_HF_SingleTrait-PGS_females_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Heart failure | heart failure | 1,042,531 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005305/ScoringFiles/PGS005305.txt.gz | |
| PGS005306 (Jorda_HF_SingleTrait-PGS_males_2024) |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Heart failure | heart failure | 1,042,531 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005306/ScoringFiles/PGS005306.txt.gz | |
| PGS005313 (AF_PGS_YuanS) |
PGP000761 | Yuan S et al. Nat Commun (2025) |
Atrial fibrillation | atrial fibrillation | 1,271,239 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005313/ScoringFiles/PGS005313.txt.gz |
| PGS005319 (HF_PRS) |
PGP000766 | Türkmen D et al. Pharmacogenomics J (2024) |
Heart failure | heart failure | 12 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005319/ScoringFiles/PGS005319.txt.gz |
| PGS005322 (PRS_EC) |
PGP000768 | Marston NA et al. Nat Med (2025) |
Coronary artery disease (Endothelial cell-related) | coronary artery disorder | 36 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS005322/ScoringFiles/PGS005322.txt.gz |
| PGS012519 (VTE) |
PGP000786 | Huang YJ et al. Nat Commun (2026) |
Venous thromboembolism | venous thromboembolism | 46 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012519/ScoringFiles/PGS012519.txt.gz |
| PGS012527 (VTE_LD) |
PGP000786 | Huang YJ et al. Nat Commun (2026) |
Venous thromboembolism | venous thromboembolism | 516,802 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012527/ScoringFiles/PGS012527.txt.gz |
| PGS012530 (PRSCAD+) |
PGP000787 | Wang H et al. Genomics Proteomics Bioinformatics (2026) |
Coronary artery disease | coronary artery disorder | 1,083,724 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012530/ScoringFiles/PGS012530.txt.gz | |
| PGS012531 (ALLmeta) |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Atrial fibrillation | atrial fibrillation | 7,356,514 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012531/ScoringFiles/PGS012531.txt.gz |
| PGS012532 (Mult-t-EUR) |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Atrial fibrillation | atrial fibrillation | 7,356,472 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012532/ScoringFiles/PGS012532.txt.gz | |
| PGS012533 (Mult-t-AMR) |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Atrial fibrillation | atrial fibrillation | 7,356,472 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012533/ScoringFiles/PGS012533.txt.gz | |
| PGS012534 (Mult-t-AFR) |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Atrial fibrillation | atrial fibrillation | 7,356,472 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012534/ScoringFiles/PGS012534.txt.gz | |
| PGS012535 (Mult-t-SAS) |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Atrial fibrillation | atrial fibrillation | 7,356,472 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012535/ScoringFiles/PGS012535.txt.gz | |
| PGS012536 (Mult-t-EAS) |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Atrial fibrillation | atrial fibrillation | 7,356,461 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012536/ScoringFiles/PGS012536.txt.gz | |
| PGS012537 (UKB_Mult-t-AFR) |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Atrial fibrillation | atrial fibrillation | 7,356,497 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012537/ScoringFiles/PGS012537.txt.gz |
| PGS012538 (UKB_Mult-t-SAS) |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Atrial fibrillation | atrial fibrillation | 7,356,497 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012538/ScoringFiles/PGS012538.txt.gz |
| PGS012542 (EN_model_CAD) |
PGP000790 | Hu J et al. Genet Med (2026) |
Coronary artery disease | coronary artery disorder | 969,769 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012542/ScoringFiles/PGS012542.txt.gz | |
| PGS012544 (EN_model_HF) |
PGP000790 | Hu J et al. Genet Med (2026) |
Heart failure | heart failure | 969,507 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012544/ScoringFiles/PGS012544.txt.gz | |
| PGS012546 (EN_model_PAD) |
PGP000790 | Hu J et al. Genet Med (2026) |
Peripheral arterial disease | peripheral arterial disease | 969,771 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012546/ScoringFiles/PGS012546.txt.gz | |
| PGS012551 (PRS_stroke) |
PGP000794 | Ye Y et al. Front Bioinform (2024) |
Stroke | stroke disorder | 1,997,066 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012551/ScoringFiles/PGS012551.txt.gz |
| PGS012552 (PRS_HF) |
PGP000794 | Ye Y et al. Front Bioinform (2024) |
Heart failure | heart failure | 1,935,626 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012552/ScoringFiles/PGS012552.txt.gz |
| PGS012558 (CAD_EAS_MIXPRSplus) |
PGP000799 | Xu L et al. Nat Genet (2026) |
Coronary artery disease | coronary artery disorder | 786,215 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012558/ScoringFiles/PGS012558.txt.gz |
| PGS012563 (PRS31_AAA) |
PGP000803 | Ma Y et al. Eur Heart J (2024) |
Abdominal aortic aneurysm | abdominal aortic aneurysm | 31 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012563/ScoringFiles/PGS012563.txt.gz |
| PGS012577 (GRS134_AF) |
PGP000812 | Chen Y et al. Eur J Psychotraumatol (2024) |
Atrial fibrillation | atrial fibrillation | 134 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012577/ScoringFiles/PGS012577.txt.gz |
| PGS012579 (PRS11_stroke) |
PGP000814 | Zheng J et al. J Intern Med (2024) |
Stroke | stroke disorder | 11 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012579/ScoringFiles/PGS012579.txt.gz |
| PGS012580 (PRS25_AF) |
PGP000814 | Zheng J et al. J Intern Med (2024) |
Atrial fibrillation | atrial fibrillation | 25 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012580/ScoringFiles/PGS012580.txt.gz |
| PGS012581 (PRS169_CAD) |
PGP000814 | Zheng J et al. J Intern Med (2024) |
Coronary artery disease | coronary artery disorder | 169 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS012581/ScoringFiles/PGS012581.txt.gz |
| PGS018408 (MultiPRS_coronary-heart-disease) |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Coronary heart disease | coronary artery disorder | 1,105,536 | - - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018408/ScoringFiles/PGS018408.txt.gz |
| PGS018409 (MultiPRS_heart-failure) |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Heart failure | heart failure | 1,105,535 | - - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018409/ScoringFiles/PGS018409.txt.gz |
| PGS018412 (MultiPRS_myocardial-infarction) |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Myocardial infarction | myocardial infarction | 1,105,535 | - - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018412/ScoringFiles/PGS018412.txt.gz |
| PGS018640 (TPMI_228_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Hemangioma and lymphangioma any site | lymphangioma, hemangioma |
488 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018640/ScoringFiles/PGS018640.txt.gz | |
| PGS018641 (TPMI_228_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Hemangioma and lymphangioma any site | lymphangioma, hemangioma |
939,901 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018641/ScoringFiles/PGS018641.txt.gz | |
| PGS018642 (TPMI_228_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Hemangioma and lymphangioma any site | lymphangioma, hemangioma |
34,069 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018642/ScoringFiles/PGS018642.txt.gz | |
| PGS018643 (TPMI_228_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Hemangioma and lymphangioma any site | lymphangioma, hemangioma |
983,831 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018643/ScoringFiles/PGS018643.txt.gz | |
| PGS018644 (TPMI_228_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Hemangioma and lymphangioma any site | lymphangioma, hemangioma |
1,011,189 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018644/ScoringFiles/PGS018644.txt.gz | |
| PGS018740 (TPMI_250.7_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 96 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018740/ScoringFiles/PGS018740.txt.gz | |
| PGS018741 (TPMI_250.7_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 939,811 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018741/ScoringFiles/PGS018741.txt.gz | |
| PGS018742 (TPMI_250.7_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 80,280 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018742/ScoringFiles/PGS018742.txt.gz | |
| PGS018743 (TPMI_250.7_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 983,771 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018743/ScoringFiles/PGS018743.txt.gz | |
| PGS018744 (TPMI_250.7_PRSmix+) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 1,071,355 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018744/ScoringFiles/PGS018744.txt.gz | |
| PGS018745 (TPMI_250.7_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Diabetic retinopathy | diabetic retinopathy | 1,014,773 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018745/ScoringFiles/PGS018745.txt.gz | |
| PGS018986 (TPMI_340_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Migraine | migraine disorder | 154,713 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018986/ScoringFiles/PGS018986.txt.gz | |
| PGS018987 (TPMI_340_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Migraine | migraine disorder | 356,947 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018987/ScoringFiles/PGS018987.txt.gz | |
| PGS018988 (TPMI_340_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Migraine | migraine disorder | 19,422 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018988/ScoringFiles/PGS018988.txt.gz | |
| PGS018989 (TPMI_340_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Migraine | migraine disorder | 983,774 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018989/ScoringFiles/PGS018989.txt.gz | |
| PGS018990 (TPMI_340_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Migraine | migraine disorder | 959,731 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS018990/ScoringFiles/PGS018990.txt.gz | |
| PGS019132 (TPMI_401.1_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Essential hypertension | essential hypertension | 41,812 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019132/ScoringFiles/PGS019132.txt.gz | |
| PGS019133 (TPMI_401.1_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Essential hypertension | essential hypertension | 939,820 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019133/ScoringFiles/PGS019133.txt.gz | |
| PGS019134 (TPMI_401.1_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Essential hypertension | essential hypertension | 131,984 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019134/ScoringFiles/PGS019134.txt.gz | |
| PGS019135 (TPMI_401.1_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Essential hypertension | essential hypertension | 983,772 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019135/ScoringFiles/PGS019135.txt.gz | |
| PGS019136 (TPMI_401.1_PRSmix+) |
PGP000835 | Chen HH et al. Nature (2025) |
Essential hypertension | essential hypertension | 1,071,467 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019136/ScoringFiles/PGS019136.txt.gz | |
| PGS019137 (TPMI_401.1_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Essential hypertension | essential hypertension | 1,004,286 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019137/ScoringFiles/PGS019137.txt.gz | |
| PGS019138 (TPMI_401.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart and or renal disease | hypertensive heart disease | 73,378 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019138/ScoringFiles/PGS019138.txt.gz | |
| PGS019139 (TPMI_401.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart and or renal disease | hypertensive heart disease | 939,834 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019139/ScoringFiles/PGS019139.txt.gz | |
| PGS019140 (TPMI_401.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart and or renal disease | hypertensive heart disease | 116,032 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019140/ScoringFiles/PGS019140.txt.gz | |
| PGS019141 (TPMI_401.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart and or renal disease | hypertensive heart disease | 983,785 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019141/ScoringFiles/PGS019141.txt.gz | |
| PGS019142 (TPMI_401.2_PRSmix+) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart and or renal disease | hypertensive heart disease | 1,071,467 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019142/ScoringFiles/PGS019142.txt.gz | |
| PGS019143 (TPMI_401.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart and or renal disease | hypertensive heart disease | 1,018,628 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019143/ScoringFiles/PGS019143.txt.gz | |
| PGS019144 (TPMI_401.3_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other hypertensive complications | hypertensive disorder | 35,755 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019144/ScoringFiles/PGS019144.txt.gz | |
| PGS019145 (TPMI_401.3_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other hypertensive complications | hypertensive disorder | 939,864 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019145/ScoringFiles/PGS019145.txt.gz | |
| PGS019146 (TPMI_401.3_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other hypertensive complications | hypertensive disorder | 84,636 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019146/ScoringFiles/PGS019146.txt.gz | |
| PGS019147 (TPMI_401.3_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other hypertensive complications | hypertensive disorder | 983,809 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019147/ScoringFiles/PGS019147.txt.gz | |
| PGS019148 (TPMI_401.3_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Other hypertensive complications | hypertensive disorder | 442,448 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019148/ScoringFiles/PGS019148.txt.gz | |
| PGS019149 (TPMI_401.21_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart disease | hypertensive heart disease | 69,926 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019149/ScoringFiles/PGS019149.txt.gz | |
| PGS019150 (TPMI_401.21_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart disease | hypertensive heart disease | 939,832 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019150/ScoringFiles/PGS019150.txt.gz | |
| PGS019151 (TPMI_401.21_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart disease | hypertensive heart disease | 86,725 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019151/ScoringFiles/PGS019151.txt.gz | |
| PGS019152 (TPMI_401.21_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart disease | hypertensive heart disease | 983,789 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019152/ScoringFiles/PGS019152.txt.gz | |
| PGS019153 (TPMI_401.21_PRSmix+) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart disease | hypertensive heart disease | 1,071,463 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019153/ScoringFiles/PGS019153.txt.gz | |
| PGS019154 (TPMI_401.21_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Hypertensive heart disease | hypertensive heart disease | 1,001,869 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019154/ScoringFiles/PGS019154.txt.gz | |
| PGS019155 (TPMI_411_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Ischemic Heart Disease | myocardial ischemia | 34,377 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019155/ScoringFiles/PGS019155.txt.gz | |
| PGS019156 (TPMI_411_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Ischemic Heart Disease | myocardial ischemia | 939,890 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019156/ScoringFiles/PGS019156.txt.gz | |
| PGS019157 (TPMI_411_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Ischemic Heart Disease | myocardial ischemia | 39,211 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019157/ScoringFiles/PGS019157.txt.gz | |
| PGS019158 (TPMI_411_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Ischemic Heart Disease | myocardial ischemia | 983,824 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019158/ScoringFiles/PGS019158.txt.gz | |
| PGS019159 (TPMI_411_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Ischemic Heart Disease | myocardial ischemia | 931,264 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019159/ScoringFiles/PGS019159.txt.gz | |
| PGS019160 (TPMI_411.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Myocardial infarction | myocardial infarction | 162,159 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019160/ScoringFiles/PGS019160.txt.gz | |
| PGS019161 (TPMI_411.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Myocardial infarction | myocardial infarction | 394,972 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019161/ScoringFiles/PGS019161.txt.gz | |
| PGS019162 (TPMI_411.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Myocardial infarction | myocardial infarction | 684,078 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019162/ScoringFiles/PGS019162.txt.gz | |
| PGS019163 (TPMI_411.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Myocardial infarction | myocardial infarction | 983,764 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019163/ScoringFiles/PGS019163.txt.gz | |
| PGS019164 (TPMI_411.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Myocardial infarction | myocardial infarction | 1,031,953 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019164/ScoringFiles/PGS019164.txt.gz | |
| PGS019165 (TPMI_411.4_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Coronary atherosclerosis | coronary atherosclerosis | 18,489 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019165/ScoringFiles/PGS019165.txt.gz | |
| PGS019166 (TPMI_411.4_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Coronary atherosclerosis | coronary atherosclerosis | 939,870 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019166/ScoringFiles/PGS019166.txt.gz | |
| PGS019167 (TPMI_411.4_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Coronary atherosclerosis | coronary atherosclerosis | 31,979 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019167/ScoringFiles/PGS019167.txt.gz | |
| PGS019168 (TPMI_411.4_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Coronary atherosclerosis | coronary atherosclerosis | 983,811 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019168/ScoringFiles/PGS019168.txt.gz | |
| PGS019169 (TPMI_411.4_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Coronary atherosclerosis | coronary atherosclerosis | 941,902 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019169/ScoringFiles/PGS019169.txt.gz | |
| PGS019170 (TPMI_411.8_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other chronic ischemic heart disease unspecified | chronic pulmonary heart disease | 36,363 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019170/ScoringFiles/PGS019170.txt.gz | |
| PGS019171 (TPMI_411.8_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other chronic ischemic heart disease unspecified | chronic pulmonary heart disease | 939,887 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019171/ScoringFiles/PGS019171.txt.gz | |
| PGS019172 (TPMI_411.8_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other chronic ischemic heart disease unspecified | chronic pulmonary heart disease | 36,574 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019172/ScoringFiles/PGS019172.txt.gz | |
| PGS019173 (TPMI_411.8_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other chronic ischemic heart disease unspecified | chronic pulmonary heart disease | 983,825 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019173/ScoringFiles/PGS019173.txt.gz | |
| PGS019174 (TPMI_411.8_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Other chronic ischemic heart disease unspecified | chronic pulmonary heart disease | 935,962 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019174/ScoringFiles/PGS019174.txt.gz | |
| PGS019175 (TPMI_414_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other forms of chronic heart disease | chronic pulmonary heart disease | 583,608 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019175/ScoringFiles/PGS019175.txt.gz | |
| PGS019176 (TPMI_414_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Other forms of chronic heart disease | chronic pulmonary heart disease | 939,813 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019176/ScoringFiles/PGS019176.txt.gz | |
| PGS019177 (TPMI_414_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other forms of chronic heart disease | chronic pulmonary heart disease | 189,507 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019177/ScoringFiles/PGS019177.txt.gz | |
| PGS019178 (TPMI_414_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Other forms of chronic heart disease | chronic pulmonary heart disease | 983,765 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019178/ScoringFiles/PGS019178.txt.gz | |
| PGS019179 (TPMI_414_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Other forms of chronic heart disease | chronic pulmonary heart disease | 1,024,278 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019179/ScoringFiles/PGS019179.txt.gz | |
| PGS019180 (TPMI_414.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
ASCVD | cardiovascular disorder | 72 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019180/ScoringFiles/PGS019180.txt.gz | |
| PGS019181 (TPMI_414.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
ASCVD | cardiovascular disorder | 363,229 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019181/ScoringFiles/PGS019181.txt.gz | |
| PGS019182 (TPMI_414.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
ASCVD | cardiovascular disorder | 170,713 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019182/ScoringFiles/PGS019182.txt.gz | |
| PGS019183 (TPMI_414.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
ASCVD | cardiovascular disorder | 983,768 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019183/ScoringFiles/PGS019183.txt.gz | |
| PGS019184 (TPMI_414.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
ASCVD | cardiovascular disorder | 1,022,962 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019184/ScoringFiles/PGS019184.txt.gz | |
| PGS019185 (TPMI_427_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Cardiac dysrhythmias | cardiac arrhythmia | 2,731 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019185/ScoringFiles/PGS019185.txt.gz | |
| PGS019186 (TPMI_427_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Cardiac dysrhythmias | cardiac arrhythmia | 939,890 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019186/ScoringFiles/PGS019186.txt.gz | |
| PGS019187 (TPMI_427_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Cardiac dysrhythmias | cardiac arrhythmia | 38,526 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019187/ScoringFiles/PGS019187.txt.gz | |
| PGS019188 (TPMI_427_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Cardiac dysrhythmias | cardiac arrhythmia | 983,828 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019188/ScoringFiles/PGS019188.txt.gz | |
| PGS019189 (TPMI_427_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Cardiac dysrhythmias | cardiac arrhythmia | 144,250 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019189/ScoringFiles/PGS019189.txt.gz | |
| PGS019190 (TPMI_427.1_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Paroxysmal tachycardia unspecified | paroxysmal tachycardia | 70 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019190/ScoringFiles/PGS019190.txt.gz | |
| PGS019191 (TPMI_427.1_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Paroxysmal tachycardia unspecified | paroxysmal tachycardia | 215,523 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019191/ScoringFiles/PGS019191.txt.gz | |
| PGS019192 (TPMI_427.1_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Paroxysmal tachycardia unspecified | paroxysmal tachycardia | 593,905 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019192/ScoringFiles/PGS019192.txt.gz | |
| PGS019193 (TPMI_427.1_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Paroxysmal tachycardia unspecified | paroxysmal tachycardia | 983,780 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019193/ScoringFiles/PGS019193.txt.gz | |
| PGS019194 (TPMI_427.1_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Paroxysmal tachycardia unspecified | paroxysmal tachycardia | 1,005,558 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019194/ScoringFiles/PGS019194.txt.gz | |
| PGS019195 (TPMI_427.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Atrial fibrillation and flutter | atrial fibrillation | 837 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019195/ScoringFiles/PGS019195.txt.gz | |
| PGS019196 (TPMI_427.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Atrial fibrillation and flutter | atrial fibrillation | 939,820 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019196/ScoringFiles/PGS019196.txt.gz | |
| PGS019197 (TPMI_427.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Atrial fibrillation and flutter | atrial fibrillation | 587,354 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019197/ScoringFiles/PGS019197.txt.gz | |
| PGS019198 (TPMI_427.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Atrial fibrillation and flutter | atrial fibrillation | 983,783 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019198/ScoringFiles/PGS019198.txt.gz | |
| PGS019199 (TPMI_427.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Atrial fibrillation and flutter | atrial fibrillation | 979,132 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019199/ScoringFiles/PGS019199.txt.gz | |
| PGS019200 (TPMI_427.5_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Arrhythmia cardiac NOS | cardiac arrhythmia | 11 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019200/ScoringFiles/PGS019200.txt.gz | |
| PGS019201 (TPMI_427.5_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Arrhythmia cardiac NOS | cardiac arrhythmia | 939,875 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019201/ScoringFiles/PGS019201.txt.gz | |
| PGS019202 (TPMI_427.5_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Arrhythmia cardiac NOS | cardiac arrhythmia | 14,836 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019202/ScoringFiles/PGS019202.txt.gz | |
| PGS019203 (TPMI_427.5_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Arrhythmia cardiac NOS | cardiac arrhythmia | 983,820 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019203/ScoringFiles/PGS019203.txt.gz | |
| PGS019204 (TPMI_427.5_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Arrhythmia cardiac NOS | cardiac arrhythmia | 955,432 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019204/ScoringFiles/PGS019204.txt.gz | |
| PGS019210 (TPMI_427.21_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Atrial fibrillation | atrial fibrillation | 883 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019210/ScoringFiles/PGS019210.txt.gz | |
| PGS019211 (TPMI_427.21_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Atrial fibrillation | atrial fibrillation | 939,817 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019211/ScoringFiles/PGS019211.txt.gz | |
| PGS019212 (TPMI_427.21_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Atrial fibrillation | atrial fibrillation | 538,308 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019212/ScoringFiles/PGS019212.txt.gz | |
| PGS019213 (TPMI_427.21_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Atrial fibrillation | atrial fibrillation | 983,779 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019213/ScoringFiles/PGS019213.txt.gz | |
| PGS019214 (TPMI_427.21_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Atrial fibrillation | atrial fibrillation | 992,954 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019214/ScoringFiles/PGS019214.txt.gz | |
| PGS019215 (TPMI_430_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracranial hemorrhage | intracranial hemorrhage | 709,249 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019215/ScoringFiles/PGS019215.txt.gz | |
| PGS019216 (TPMI_430_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracranial hemorrhage | intracranial hemorrhage | 939,872 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019216/ScoringFiles/PGS019216.txt.gz | |
| PGS019217 (TPMI_430_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracranial hemorrhage | intracranial hemorrhage | 23,091 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019217/ScoringFiles/PGS019217.txt.gz | |
| PGS019218 (TPMI_430_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracranial hemorrhage | intracranial hemorrhage | 983,811 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019218/ScoringFiles/PGS019218.txt.gz | |
| PGS019219 (TPMI_430_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracranial hemorrhage | intracranial hemorrhage | 1,006,461 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019219/ScoringFiles/PGS019219.txt.gz | |
| PGS019220 (TPMI_430.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracerebral hemorrhage | intracerebral hemorrhage | 239,850 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019220/ScoringFiles/PGS019220.txt.gz | |
| PGS019221 (TPMI_430.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracerebral hemorrhage | intracerebral hemorrhage | 939,827 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019221/ScoringFiles/PGS019221.txt.gz | |
| PGS019222 (TPMI_430.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracerebral hemorrhage | intracerebral hemorrhage | 26,024 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019222/ScoringFiles/PGS019222.txt.gz | |
| PGS019223 (TPMI_430.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracerebral hemorrhage | intracerebral hemorrhage | 983,782 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019223/ScoringFiles/PGS019223.txt.gz | |
| PGS019224 (TPMI_430.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Intracerebral hemorrhage | intracerebral hemorrhage | 1,012,521 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019224/ScoringFiles/PGS019224.txt.gz | |
| PGS019225 (TPMI_433_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebrovascular disease | cerebrovascular disorder | 157,854 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019225/ScoringFiles/PGS019225.txt.gz | |
| PGS019226 (TPMI_433_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebrovascular disease | cerebrovascular disorder | 939,895 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019226/ScoringFiles/PGS019226.txt.gz | |
| PGS019227 (TPMI_433_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebrovascular disease | cerebrovascular disorder | 35,297 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019227/ScoringFiles/PGS019227.txt.gz | |
| PGS019228 (TPMI_433_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebrovascular disease | cerebrovascular disorder | 983,828 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019228/ScoringFiles/PGS019228.txt.gz | |
| PGS019229 (TPMI_433_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebrovascular disease | cerebrovascular disorder | 950,004 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019229/ScoringFiles/PGS019229.txt.gz | |
| PGS019230 (TPMI_433.2_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Occlusion of cerebral arteries | cerebral artery occlusion | 562,676 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019230/ScoringFiles/PGS019230.txt.gz | |
| PGS019231 (TPMI_433.2_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Occlusion of cerebral arteries | cerebral artery occlusion | 939,882 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019231/ScoringFiles/PGS019231.txt.gz | |
| PGS019232 (TPMI_433.2_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Occlusion of cerebral arteries | cerebral artery occlusion | 33,950 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019232/ScoringFiles/PGS019232.txt.gz | |
| PGS019233 (TPMI_433.2_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Occlusion of cerebral arteries | cerebral artery occlusion | 983,818 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019233/ScoringFiles/PGS019233.txt.gz | |
| PGS019234 (TPMI_433.2_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Occlusion of cerebral arteries | cerebral artery occlusion | 969,384 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019234/ScoringFiles/PGS019234.txt.gz | |
| PGS019240 (TPMI_433.6_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Acute but ill defined cerebrovascular disease | cerebrovascular disorder | 356,084 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019240/ScoringFiles/PGS019240.txt.gz | |
| PGS019241 (TPMI_433.6_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Acute but ill defined cerebrovascular disease | cerebrovascular disorder | 939,874 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019241/ScoringFiles/PGS019241.txt.gz | |
| PGS019242 (TPMI_433.6_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Acute but ill defined cerebrovascular disease | cerebrovascular disorder | 436,050 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019242/ScoringFiles/PGS019242.txt.gz | |
| PGS019243 (TPMI_433.6_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Acute but ill defined cerebrovascular disease | cerebrovascular disorder | 983,814 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019243/ScoringFiles/PGS019243.txt.gz | |
| PGS019244 (TPMI_433.6_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Acute but ill defined cerebrovascular disease | cerebrovascular disorder | 999,333 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019244/ScoringFiles/PGS019244.txt.gz | |
| PGS019245 (TPMI_433.8_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Late effects of cerebrovascular disease | cerebrovascular disorder | 703,260 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019245/ScoringFiles/PGS019245.txt.gz | |
| PGS019246 (TPMI_433.8_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Late effects of cerebrovascular disease | cerebrovascular disorder | 332,716 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019246/ScoringFiles/PGS019246.txt.gz | |
| PGS019247 (TPMI_433.8_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Late effects of cerebrovascular disease | cerebrovascular disorder | 11,065 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019247/ScoringFiles/PGS019247.txt.gz | |
| PGS019248 (TPMI_433.8_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Late effects of cerebrovascular disease | cerebrovascular disorder | 983,823 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019248/ScoringFiles/PGS019248.txt.gz | |
| PGS019249 (TPMI_433.8_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Late effects of cerebrovascular disease | cerebrovascular disorder | 1,001,105 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019249/ScoringFiles/PGS019249.txt.gz | |
| PGS019250 (TPMI_433.21_Lassosum2) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebral artery occlusion with cerebral infarction | cerebral artery occlusion | 48,064 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019250/ScoringFiles/PGS019250.txt.gz | |
| PGS019251 (TPMI_433.21_LDpred2) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebral artery occlusion with cerebral infarction | cerebral artery occlusion | 939,870 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019251/ScoringFiles/PGS019251.txt.gz | |
| PGS019252 (TPMI_433.21_MegaPRS) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebral artery occlusion with cerebral infarction | cerebral artery occlusion | 23,452 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019252/ScoringFiles/PGS019252.txt.gz | |
| PGS019253 (TPMI_433.21_PRS-CS) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebral artery occlusion with cerebral infarction | cerebral artery occlusion | 983,812 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019253/ScoringFiles/PGS019253.txt.gz | |
| PGS019254 (TPMI_433.21_SBayesR) |
PGP000835 | Chen HH et al. Nature (2025) |
Cerebral artery occlusion with cerebral infarction | cerebral artery occlusion | 976,798 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS019254/ScoringFiles/PGS019254.txt.gz | |
| PGS020002 (PRS12_HF) |
PGP000860 | Shi Q et al. JACC Asia (2024) |
Heart failure | heart failure | 12 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS020002/ScoringFiles/PGS020002.txt.gz |
| PGS020004 (PRS22_AAA) |
PGP000862 | Zhu D et al. JACC Adv (2024) |
Abdominal aortic aneurysm | abdominal aortic aneurysm | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS020004/ScoringFiles/PGS020004.txt.gz |
| PGS020005 (eMERGE_AF_PRS) |
PGP000864 | Lennon NJ et al. Nat Med (2024) |
Atrial fibrillation | atrial fibrillation | 166 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS020005/ScoringFiles/PGS020005.txt.gz |
|
PGS Performance Metric ID (PPM) |
Evaluated Score |
PGS Sample Set ID (PSS) |
Performance Source | Trait |
PGS Effect Sizes (per SD change) |
Classification Metrics | Other Metrics | Covariates Included in the Model |
PGS Performance: Other Relevant Information |
|---|---|---|---|---|---|---|---|---|---|
| PPM000014 | PGS000010 (GRS27) |
PSS000008| European Ancestry| 42,998 individuals |
PGP000003 | Mega JL et al. Lancet (2015) |
Reported Trait: Coronary heart disease | HR: 1.21 [1.17, 1.26] | — | — | age, sex, diabetes status, smoking, race, family history of coronary heart disease, HDL cholesterol, LDL cholesterol, and hypertension | Meta-analysis of sub-cohort effect sizes |
| PPM000015 | PGS000010 (GRS27) |
PSS000009| European Ancestry| 4,877 individuals |
PGP000003 | Mega JL et al. Lancet (2015) |
Reported Trait: Coronary heart disease | HR: 1.14 [1.02, 1.28] | — | — | age, sex, diabetes status, smoking, race, family history of coronary heart disease, HDL cholesterol, LDL cholesterol, and hypertension | Meta-analysis of sub-cohort effect sizes |
| PPM000018 | PGS000012 (GRS49K) |
PSS000012| European Ancestry| 12,676 individuals |
PGP000005 | Abraham G et al. Eur Heart J (2016) |
Reported Trait: Incident coronary artery disease | HR: 1.74 [1.61, 1.86] OR: 1.74 [1.61, 1.89] |
— | — | sex, sub-cohort, location (east/west), 5 genetic PCs | Used only the 42,364 SNPs that were available in FINRISK |
| PPM000020 | PGS000012 (GRS49K) |
PSS000011| European Ancestry| 3,406 individuals |
PGP000005 | Abraham G et al. Eur Heart J (2016) |
Reported Trait: Incident coronary artery disease | HR: 1.28 [1.18, 1.38] OR: 1.28 [1.17, 1.41] |
— | — | sex, sub-cohort, 5 genetic PCs | Used only the 46,773 SNPs that were available in FHS |
| PPM001620 | PGS000013 (GPS_CAD) |
PSS000837| European Ancestry| 4,847 individuals |
PGP000129 | Mosley JD et al. JAMA (2020) |Ext. |
Reported Trait: Incident coronary heart disease (10-year risk) | — | C-index: 0.7 [0.677, 0.721] | Δ C-index (PRS+covariates vs. covariates alone): -0.001 [-0.009, 0.006] | Pooled cohort risk percentile, age, sex, PCs (1-5) | — |
| PPM001639 | PGS000043 (PRS_VTE) |
PSS000850| European Ancestry| 715 individuals |
PGP000133 | Naito T et al. Gastroenterology (2020) |Ext. |
Reported Trait: Thromboembolic disease event in individuals with inflammatory bowel disease | — | — | Odds Ratio (OR, top 5% vs. remaining 95%): 2.7 [1.03, 7.09] | Age at last visit, PCs(1-2) | Included 265/297 variants from the original score |
| PPM000027 | PGS000018 (metaGRS_CAD) |
PSS000018| Multi-ancestry (including European)| 482,629 individuals |
PGP000007 | Inouye M et al. J Am Coll Cardiol (2018) |
Reported Trait: Incident coronary artery disease | HR: 1.706 [1.682, 1.73] | AUROC: 0.79 C-index: 0.623 [0.615, 0.631] |
AUPRC: 0.161 | sex, genetic PCs (1-10), genotyping array | age-as-time-scale Cox regression |
| PPM000028 | PGS000012 (GRS49K) |
PSS000018| Multi-ancestry (including European)| 482,629 individuals |
PGP000007 | Inouye M et al. J Am Coll Cardiol (2018) |Ext. |
Reported Trait: Incident coronary artery disease | HR: 1.524 [1.498, 1.551] | — | — | sex, genetic PCs (1-10), genotyping array | Used GRS46K (excludes A/T and C/G SNPs, with performance similar to GRS49K) |
| PPM000038 | PGS000019 (GRS_CAD) |
PSS000023| European Ancestry| 725 individuals |
PGP000009 | Paquette M et al. J Clin Lipidol (2017) |
Reported Trait: Coronary artery disease in familial hypercholesterolemia patients | OR: 1.66 [1.06, 2.62] | — | — | age, gender, prior statin use, smoking, diabetes, hypertension, BMI, LDL-C, HDL-C, TGs, Lp(a), and type of LDLR mutation | Performance metrics are from Model 2 (adjusted for cardiovascular risk factors) |
| PPM000039 | PGS000019 (GRS_CAD) |
PSS000024| European Ancestry| 725 individuals |
PGP000009 | Paquette M et al. J Clin Lipidol (2017) |
Reported Trait: Coronary artery disease in familial hypercholesterolemia patients | OR: 1.8 [1.14, 2.85] | — | — | age, gender, prior statin use, smoking, diabetes, hypertension, BMI, LDL-C, HDL-C, TGs, Lp(a), and type of LDLR mutation | Performance metrics are from Model 2 (adjusted for cardiovascular risk factors) |
| PPM000016 | PGS000011 (GRS50) |
PSS000010| European Ancestry| 23,595 individuals |
PGP000004 | Tada H et al. Eur Heart J (2015) |
Reported Trait: Incident coronary heart disease | HR: 1.23 [1.18, 1.28] | — | — | age, sex, systolic blood pressure, hypertension treatment, smoking, apoB, apoA-I, prevalent diabetes | — |
| PPM000079 | PGS000035 (PRS_AF) |
PSS000053| Multi-ancestry (including European)| 4,606 individuals |
PGP000022 | Weng LC et al. Circulation (2017) |
Reported Trait: Incident atrial fibrillation | HR: 1.14 [1.11, 1.16] | — | — | Clinical risk (CHARGE-AF Score: height, weight, systolic and diastolic blood pressure, current smoking status, use of antihypertensive medication, diabetes mellitus, history of myocardial infarction and heart failure), age, sex, genotyping array, 1 PC of ancestry | Unadjusted for Competing Risk of Death |
| PPM000090 | PGS000038 (PRS90) |
PSS000057| European Ancestry| 306,473 individuals |
PGP000026 | Rutten-Jacobs LC et al. BMJ (2018) |
Reported Trait: Incident stroke | — | — | HR (High [top 33%] vs. Low [bottom 33%] of genetic risk): 1.35 [1.21, 1.5] | age, sex, 10 PCs of genetic ancestry, genotyping batch | The best performing PRS (e.g. C+T thresholds) were selected based on this sample set, as well as being used for the evaluation. |
| PPM000091 | PGS000039 (metaGRS_ischaemicstroke) |
PSS000058| European Ancestry| 395,393 individuals |
PGP000027 | Abraham G et al. Nat Commun (2019) |
Reported Trait: Ischaemic stroke before age 75 | HR: 1.26 [1.22, 1.31] | C-index: 0.585 [0.574, 0.595] | — | Sex, genotyping chip, 10 PCs | — |
| PPM000092 | PGS000038 (PRS90) |
PSS000058| European Ancestry| 395,393 individuals |
PGP000027 | Abraham G et al. Nat Commun (2019) |Ext. |
Reported Trait: Ischaemic stroke before age 75 | HR: 1.13 [1.1, 1.17] | — | — | Sex, genotyping chip, 10 PCs | — |
| PPM000102 | PGS000043 (PRS_VTE) |
PSS000066| European Ancestry| 55,965 individuals |
PGP000030 | Klarin D et al. Nat Genet (2019) |
Reported Trait: Venous thromboembolism | — | — | OR (top 5% of individuals with the highest PRS_VTE relative to the rest of the population): 2.89 [2.52, 3.3] | age, sex, 5 PCs of ancestry | — |
| PPM001011 | PGS000013 (GPS_CAD) |
PSS000515| African Ancestry| 6,979 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | — | AUROC: 0.58 | — | PCs (1-10) of ancestry | — |
| PPM001010 | PGS000013 (GPS_CAD) |
PSS000517| Hispanic or Latin American Ancestry| 7,048 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | — | AUROC: 0.63 | — | PCs (1-10) of ancestry | — |
| PPM001009 | PGS000013 (GPS_CAD) |
PSS000516| European Ancestry| 10,344 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | — | AUROC: 0.53 | — | PCs (1-10) of ancestry | — |
| PPM001008 | PGS000013 (GPS_CAD) |
PSS000515| African Ancestry| 6,979 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | OR: 1.29 [1.23, 1.34] | — | — | age, sex, PCs (1-10) of ancestry | — |
| PPM001007 | PGS000013 (GPS_CAD) |
PSS000517| Hispanic or Latin American Ancestry| 7,048 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | OR: 1.5 [1.44, 1.57] | — | — | age, sex, PCs (1-10) of ancestry | — |
| PPM001006 | PGS000013 (GPS_CAD) |
PSS000516| European Ancestry| 10,344 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | OR: 1.52 [1.46, 1.58] | — | — | age, sex, PCs (1-10) of ancestry | — |
| PPM001005 | PGS000013 (GPS_CAD) |
PSS000514| Multi-ancestry (including European)| 24,371 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | — | AUROC: 0.61 | — | PCs (1-10) of ancestry | — |
| PPM001004 | PGS000013 (GPS_CAD) |
PSS000519| Multi-ancestry (including European)| 9,070 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | — | AUROC: 0.6 | — | PCs (1-10) of ancestry | — |
| PPM001003 | PGS000013 (GPS_CAD) |
PSS000518| Multi-ancestry (including European)| 13,667 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | — | AUROC: 0.59 | — | PCs (1-10) of ancestry | — |
| PPM001002 | PGS000013 (GPS_CAD) |
PSS000514| Multi-ancestry (including European)| 24,371 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | OR: 1.42 [1.35, 1.48] | — | — | age, sex, PCs (1-10) of ancestry | — |
| PPM001001 | PGS000013 (GPS_CAD) |
PSS000519| Multi-ancestry (including European)| 9,070 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | OR: 1.45 [1.38, 1.52] | — | — | age, sex, PCs (1-10) of ancestry, genotyping array | — |
| PPM001000 | PGS000013 (GPS_CAD) |
PSS000518| Multi-ancestry (including European)| 13,667 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | OR: 1.41 [1.34, 1.47] | — | — | age, sex, PCs (1-10) of ancestry, genotyping array | — |
| PPM000583 | PGS000200 (GRS28) |
PSS000330| European Ancestry| 24,124 individuals |
PGP000082 | Tikkanen E et al. Arterioscler Thromb Vasc Biol (2013) |
Reported Trait: Incident cardiovascular disease | HR: 1.18 [1.12, 1.24] | — | — | sex, total cholesterol, high-density lipoprotein–cholesterol, body mass index, systolic blood pressure, antihypertensive treatment, smoking, type 2 diabetes mellitus | Age as timescale Cox regression |
| PPM000150 | PGS000059 (CHD46) |
PSS000094| European Ancestry| 1,320 individuals |
PGP000044 | Hajek C et al. Circ Genom Precis Med (2018) |
Reported Trait: Incident coronary heart disease | — | — | HR (top vs. bottom quartiles of GRS): 0.76 [0.41, 1.39] p-value (association between risk and incidence): 0.31 |
NR | — |
| PPM000999 | PGS000013 (GPS_CAD) |
PSS000520| Multi-ancestry (including European)| 47,108 individuals |
PGP000116 | Aragam KG et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Prevalent Coronary Artery Disease | OR: 1.42 [1.38, 1.46] | — | — | age, sex, PCs (1-10) of ancestry, genotyping array | — |
| PPM000589 | PGS000011 (GRS50) |
PSS000334| European Ancestry| 39,758 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.2 [1.15, 1.25] | C-index: 0.698 | — | sex, eMERGE site, first five ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000585 | PGS000200 (GRS28) |
PSS000328| European Ancestry| 24,124 individuals |
PGP000082 | Tikkanen E et al. Arterioscler Thromb Vasc Biol (2013) |
Reported Trait: Incident acute coronary syndrome | HR: 1.27 [1.18, 1.37] | — | — | sex, total cholesterol, high-density lipoprotein–cholesterol, body mass index, systolic blood pressure, antihypertensive treatment, smoking, type 2 diabetes mellitus | Age as timescale Cox regression |
| PPM000597 | PGS000018 (metaGRS_CAD) |
PSS000336| Hispanic or Latin American Ancestry| 2,194 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.53 [1.23, 1.9] | C-index: 0.683 | — | sex, eMERGE site, first five ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000596 | PGS000013 (GPS_CAD) |
PSS000336| Hispanic or Latin American Ancestry| 2,194 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.16 [0.96, 1.41] | C-index: 0.659 | — | sex, eMERGE site, first five ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000595 | PGS000011 (GRS50) |
PSS000336| Hispanic or Latin American Ancestry| 2,194 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.13 [0.93, 1.36] | C-index: 0.654 | — | sex, eMERGE site, first five ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000594 | PGS000018 (metaGRS_CAD) |
PSS000332| African Ancestry| 7,070 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.27 [1.13, 1.43] | C-index: 0.663 | — | sex, eMERGE site, first five ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000593 | PGS000013 (GPS_CAD) |
PSS000332| African Ancestry| 7,070 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.19 [1.07, 1.33] | C-index: 0.656 | — | sex, eMERGE site, first five ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000592 | PGS000011 (GRS50) |
PSS000332| African Ancestry| 7,070 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.05 [0.94, 1.17] | C-index: 0.649 | — | sex, eMERGE site, first five ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000591 | PGS000018 (metaGRS_CAD) |
PSS000334| European Ancestry| 39,758 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.53 [1.46, 1.6] | C-index: 0.719 | — | sex, eMERGE site, first five ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000619 | PGS000013 (GPS_CAD) |
PSS000332| African Ancestry| 7,070 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.17 [1.04, 1.31] | C-index: 0.712 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000618 | PGS000011 (GRS50) |
PSS000332| African Ancestry| 7,070 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.05 [0.94, 1.18] | C-index: 0.704 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000617 | PGS000200 (GRS28) |
PSS000332| African Ancestry| 7,070 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.11 [0.99, 1.25] | C-index: 0.706 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000616 | PGS000018 (metaGRS_CAD) |
PSS000334| European Ancestry| 39,758 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.49 [1.43, 1.56] | C-index: 0.75 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000615 | PGS000013 (GPS_CAD) |
PSS000334| European Ancestry| 39,758 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.47 [1.41, 1.54] | C-index: 0.75 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000614 | PGS000011 (GRS50) |
PSS000334| European Ancestry| 39,758 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.2 [1.15, 1.25] | C-index: 0.736 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000613 | PGS000200 (GRS28) |
PSS000334| European Ancestry| 39,758 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.17 [1.12, 1.22] | C-index: 0.735 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000620 | PGS000018 (metaGRS_CAD) |
PSS000332| African Ancestry| 7,070 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.25 [1.12, 1.41] | C-index: 0.723 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000624 | PGS000018 (metaGRS_CAD) |
PSS000336| Hispanic or Latin American Ancestry| 2,194 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.5 [1.21, 1.87] | C-index: 0.725 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000623 | PGS000013 (GPS_CAD) |
PSS000336| Hispanic or Latin American Ancestry| 2,194 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.14 [0.94, 1.39] | C-index: 0.708 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000622 | PGS000011 (GRS50) |
PSS000336| Hispanic or Latin American Ancestry| 2,194 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.12 [0.93, 1.36] | C-index: 0.708 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000621 | PGS000200 (GRS28) |
PSS000336| Hispanic or Latin American Ancestry| 2,194 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.13 [0.93, 1.37] | C-index: 0.709 | — | sex, eMERGE site, diabetes, hypertension, hyperlipidemia, statin use, first 5 ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM001666 | PGS000018 (metaGRS_CAD) |
PSS000868| European Ancestry| 3,087 individuals |
PGP000137 | Ritchie SC et al. Nat Metab (2021) |Ext. |
Reported Trait: Incident myocardial infarction | HR: 2.89 [1.66, 5.04] | — | — | age, sex, 10 genetic PCs | — |
| PPM001668 | PGS000727 (AF_PGS) |
PSS000867| European Ancestry| 3,087 individuals |
PGP000137 | Ritchie SC et al. Nat Metab (2021) |
Reported Trait: Incident atrial fibrillation | HR: 1.72 [1.2, 2.47] | — | — | age, sex, 10 genetic PCs | — |
| PPM000590 | PGS000013 (GPS_CAD) |
PSS000334| European Ancestry| 39,758 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.5 [1.43, 1.56] | C-index: 0.719 | — | sex, eMERGE site, first five ancestry-specific principal components | Age-as-time-scale Cox regression |
| PPM000584 | PGS000200 (GRS28) |
PSS000329| European Ancestry| 24,124 individuals |
PGP000082 | Tikkanen E et al. Arterioscler Thromb Vasc Biol (2013) |
Reported Trait: Incident coronary heart disease | HR: 1.27 [1.2, 1.35] | — | — | sex, total cholesterol, high-density lipoprotein–cholesterol, body mass index, systolic blood pressure, antihypertensive treatment, smoking, type 2 diabetes mellitus | Age as timescale Cox regression |
| PPM000385 | PGS000016 (GPS_AF) |
PSS000217| European Ancestry| 10,303 individuals |
PGP000057 | Homburger JR et al. Genome Med (2019) |Ext. |
Reported Trait: Atrial Fibrillation (personal history) | OR: 1.277 [1.12, 1.46] | AUROC: 0.78 | — | age, sex | — |
| PPM000496 | PGS000011 (GRS50) |
PSS000285| European Ancestry| 22,389 individuals |
PGP000076 | Khera AV et al. N Engl J Med (2016) |Ext. |
Reported Trait: Incident coronary artery disease | — | — | Hazard Ratio (HR; top 20% of score vs bottom 20%): 1.98 [1.76, 2.23] | age, sex, self reported education level | — |
| PPM000495 | PGS000011 (GRS50) |
PSS000286| European Ancestry| 21,222 individuals |
PGP000076 | Khera AV et al. N Engl J Med (2016) |Ext. |
Reported Trait: Incident coronary artery disease | — | — | Hazard Ratio (HR; top 20% of score vs bottom 20%): 1.94 [1.58, 2.39] | age, self reported education level, treatment (vitamin E vs aspirin), 5 genetic principal components | — |
| PPM000494 | PGS000011 (GRS50) |
PSS000283| European Ancestry| 7,814 individuals |
PGP000076 | Khera AV et al. N Engl J Med (2016) |Ext. |
Reported Trait: Incident coronary artery disease | — | — | Hazard Ratio (HR; top 20% of score vs bottom 20%): 1.75 [1.46, 2.1] | age, sex, self reported education level, 5 genetic principal components | — |
| PPM001839 | PGS000747 (PRS_EB) |
PSS000931| European Ancestry| 431,814 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Reported Trait: Coronary artery disease | — | AUROC: 0.6043 [0.6004, 0.6082] | Area under the Precision-Recall curve (AUPRC): 0.0712 [0.0703, 0.076] | — | — |
| PPM001841 | PGS000748 (PRS_DE) |
PSS000930| European Ancestry| 27,048 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Reported Trait: Coronary artery disease | — | AUROC: 0.6156 [0.5963, 0.6349] | Area under the Precision-Recall curve (AUPRC): 0.0506 [0.0504, 0.0508] | — | — |
| PPM001842 | PGS000748 (PRS_DE) |
PSS000931| European Ancestry| 431,814 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Reported Trait: Coronary artery disease | — | AUROC: 0.5989 [0.595, 0.6028] | Area under the Precision-Recall curve (AUPRC): 0.0696 [0.0694, 0.0698] | — | — |
| PPM001843 | PGS000749 (PRS_COMBINED) |
PSS000930| European Ancestry| 27,048 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Reported Trait: Coronary artery disease | — | AUROC: 0.6112 [0.5919, 0.6305] | Area under the Precision-Recall curve (AUPRC): 0.048 [0.0473, 0.0487] | — | — |
| PPM001845 | PGS000018 (metaGRS_CAD) |
PSS000929| European Ancestry| 5,581 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Coronary artery disease | — | AUROC: 0.5015 [0.483, 0.514] | Area under the Precision-Recall curve (AUPRC): 0.5205 [0.5201, 0.521] | — | — |
| PPM001846 | PGS000018 (metaGRS_CAD) |
PSS000930| European Ancestry| 27,048 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Coronary artery disease | — | AUROC: 0.6597 [0.6405, 0.6789] | Area under the Precision-Recall curve (AUPRC): 0.0673 [0.0668, 0.0679] | — | — |
| PPM000017 | PGS000010 (GRS27) |
PSS000010| European Ancestry| 23,595 individuals |
PGP000004 | Tada H et al. Eur Heart J (2015) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.2 [1.15, 1.25] | — | — | age, sex, systolic blood pressure, hypertension treatment, smoking, apoB, apoA-I, prevalent diabetes | — |
| PPM000022 | PGS000013 (GPS_CAD) |
PSS000015| European Ancestry| 288,978 individuals |
PGP000006 | Khera AV et al. Nat Genet (2018) |
Reported Trait: Coronary artery disease | — | AUROC: 0.81 [0.81, 0.81] | Nagelkerke’s R2 (estimate of variance explained by the PGS after covariate adjustment): 0.04 | age; sex; Ancestry PC 1-4; genotyping chip | — |
| PPM000025 | PGS000016 (GPS_AF) |
PSS000013| European Ancestry| 288,978 individuals |
PGP000006 | Khera AV et al. Nat Genet (2018) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.77 [0.76, 0.77] | Nagelkerke’s R2 (estimate of variance explained by the PGS after covariate adjustment): 0.029 | age; sex; Ancestry PC 1-4; genotyping chip | — |
| PPM000029 | PGS000011 (GRS50) |
PSS000018| Multi-ancestry (including European)| 482,629 individuals |
PGP000007 | Inouye M et al. J Am Coll Cardiol (2018) |Ext. |
Reported Trait: Incident coronary artery disease | HR: 1.263 [1.247, 1.28] | — | — | sex, genetic PCs (1-10), genotyping array | — |
| PPM000030 | PGS000013 (GPS_CAD) |
PSS000021| European Ancestry| 1,964 individuals |
PGP000008 | Wünnemann F et al. Circ Genom Precis Med (2019) |Ext. |
Reported Trait: Coronary artery disease (prevalent) | OR: 1.64 [1.48, 1.81] | AUROC: 0.72 [0.7, 0.74] | — | age, sex, first four genetic PCs | — |
| PPM000031 | PGS000013 (GPS_CAD) |
PSS000022| European Ancestry| 3,309 individuals |
PGP000008 | Wünnemann F et al. Circ Genom Precis Med (2019) |Ext. |
Reported Trait: Coronary artery disease (prevalent) | OR: 1.55 [1.38, 1.73] | AUROC: 0.89 [0.88, 0.91] | — | age, sex, first four genetic PCs | — |
| PPM000032 | PGS000013 (GPS_CAD) |
PSS000019| European Ancestry| 5,762 individuals |
PGP000008 | Wünnemann F et al. Circ Genom Precis Med (2019) |Ext. |
Reported Trait: Coronary artery disease (prevalent) | OR: 1.69 [1.44, 1.99] | AUROC: 0.84 [0.81, 0.87] | — | age, sex, first four genetic PCs, cohort recruitment centre | — |
| PPM000033 | PGS000013 (GPS_CAD) |
PSS000020| European Ancestry| 3,195 individuals |
PGP000008 | Wünnemann F et al. Circ Genom Precis Med (2019) |Ext. |
Reported Trait: Reccurent coronary artery disease events | OR: 1.13 [1.06, 1.22] | — | — | age, sex, first four genetic PCs | — |
| PPM000034 | PGS000018 (metaGRS_CAD) |
PSS000021| European Ancestry| 1,964 individuals |
PGP000008 | Wünnemann F et al. Circ Genom Precis Med (2019) |Ext. |
Reported Trait: Coronary artery disease (prevalent) | OR: 1.74 [1.57, 1.93] | AUROC: 0.72 [0.7, 0.75] | — | age, sex, first four genetic PCs | — |
| PPM000035 | PGS000018 (metaGRS_CAD) |
PSS000022| European Ancestry| 3,309 individuals |
PGP000008 | Wünnemann F et al. Circ Genom Precis Med (2019) |Ext. |
Reported Trait: Coronary artery disease (prevalent) | OR: 1.6 [1.43, 1.8] | AUROC: 0.89 [0.88, 0.91] | — | age, sex, first four genetic PCs | — |
| PPM000036 | PGS000018 (metaGRS_CAD) |
PSS000019| European Ancestry| 5,762 individuals |
PGP000008 | Wünnemann F et al. Circ Genom Precis Med (2019) |Ext. |
Reported Trait: Coronary artery disease (prevalent) | OR: 1.75 [1.49, 2.05] | AUROC: 0.84 [0.81, 0.87] | — | age, sex, first four genetic PCs, cohort recruitment centre | — |
| PPM000037 | PGS000018 (metaGRS_CAD) |
PSS000020| European Ancestry| 3,195 individuals |
PGP000008 | Wünnemann F et al. Circ Genom Precis Med (2019) |Ext. |
Reported Trait: Reccurent coronary artery disease events | OR: 1.17 [1.08, 1.26] | — | — | age, sex, first four genetic PCs | — |
| PPM000103 | PGS000043 (PRS_VTE) |
PSS000067| European Ancestry| 10,975 individuals |
PGP000030 | Klarin D et al. Nat Genet (2019) |
Reported Trait: Venous thromboembolism | — | — | HR (top 5% of individuals with the highest PRS_VTE relative to the rest of the population): 2.51 [1.97, 3.19] | age, 10 PCs of ancestry, hormone therapy intervention status | — |
| PPM000144 | PGS000057 (CHD57) |
PSS000091| Ancestry Not Reported| 2,440 individuals |
PGP000042 | Natarajan P et al. Circulation (2017) |
Reported Trait: Coronary heart disease (incident) | — | — | HR (highest vs. lowest quintile of PGS): 1.66 [1.21, 2.29] | age, sex, diabetes meliitus status, smoking status, LDL cholesterol, HDL cholesterol, systolic blood pressure, antihypertensive medication status, family history of CHD | — |
| PPM000145 | PGS000057 (CHD57) |
PSS000090| Ancestry Not Reported| 1,154 individuals |
PGP000042 | Natarajan P et al. Circulation (2017) |
Reported Trait: Coronary artery calcification | OR: 1.32 [1.04, 1.68] | — | OR (highest vs. lowest quintile of PGS): 2.51 [1.08, 5.85] | age, sex, diabetes meliitus status, smoking status, LDL cholesterol, HDL cholesterol, systolic blood pressure, antihypertensive medication status, family history of CHD | — |
| PPM000146 | PGS000057 (CHD57) |
PSS000089| Ancestry Not Reported| 4,392 individuals |
PGP000042 | Natarajan P et al. Circulation (2017) |
Reported Trait: Carotid artery plaque burden | β: 1.097 [1.022, 1.178] | — | — | age, sex, diabetes meliitus status, smoking status, LDL cholesterol, HDL cholesterol, systolic blood pressure, antihypertensive medication status, family history of CHD | — |
| PPM000147 | PGS000058 (CAD_GRS_204) |
PSS000092| European Ancestry| 5,360 individuals |
PGP000043 | Morieri ML et al. Diabetes Care (2018) |
Reported Trait: Major coronary events (MCE) events among Type 2 Diabetes patients | HR: 1.27 [1.18, 1.37] | — | — | age, sex, ACCORD study covariates (randomized treament assignement, clinical network, genotyping platform, PCs of genetic ancestry) | — |
| PPM000148 | PGS000058 (CAD_GRS_204) |
PSS000093| European Ancestry| 1,931 individuals |
PGP000043 | Morieri ML et al. Diabetes Care (2018) |
Reported Trait: Major coronary events (MCE) events among Type 2 Diabetes patients | HR: 1.35 [1.16, 1.58] | — | — | age, sex, ORIGIN study covariates (randomized treament assignement, PCs of genetic ancestry) | — |
| PPM000149 | PGS000059 (CHD46) |
PSS000095| European Ancestry| 1,206 individuals |
PGP000044 | Hajek C et al. Circ Genom Precis Med (2018) |
Reported Trait: Incident coronary heart disease | — | — | HR (top vs. bottom quartiles of GRS): 1.92 [1.19, 3.11] p-value (association between risk and incidence): 0.029 |
NR | — |
| PPM000898 | PGS000331 (PRS_AF) |
PSS000439| European Ancestry| 10,561 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Incident atrial fibrillation | — | C-index: 0.734 | — | CHARGE-AF calculator (age, height, weight, SBP, DBP, smoking status, blood-pressure-lowering medication, diabetes, heart failure and history of myocardial infarction), FINRISK cohort, genotyping array/batch, 10 ancestry PCs | 5-year risk |
| PPM000896 | PGS000329 (PRS_CHD) |
PSS000440| European Ancestry| 20,165 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Incident coronary heart disease | — | C-index: 0.82 | — | ASCVD risk calculator(age, sex, total cholesterol, HDL, SBP, blood-pressure-lowering medication, diabetes and smoking status), FINRISK cohort, genotyping array/batch, 10 ancestry PCs | 10-year risk |
| PPM000893 | PGS000331 (PRS_AF) |
PSS000439| European Ancestry| 10,561 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Incident atrial fibrillation | HR: 1.62 [1.54, 1.7] | C-index: 0.751 | — | age, sex, FINRISK cohort, genotyping array/batch, 10 ancestry PCs | 5-year risk |
| PPM000891 | PGS000329 (PRS_CHD) |
PSS000440| European Ancestry| 20,165 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Incident coronary heart disease | HR: 1.25 [1.18, 1.32] | C-index: 0.832 | — | age, sex, FINRISK cohort, genotyping array/batch, 10 ancestry PCs | 10-year risk |
| PPM000909 | PGS000337 (MetaPRS_CAD) |
PSS000456| East Asian Ancestry| 49,230 individuals |
PGP000104 | Koyama S et al. Nat Genet (2020) |
Reported Trait: Mortality (diseases of the circulatory system) | HR: 1.10351 [1.057, 1.152] | — | — | Sex, age, age^2, PCs (1-10), disease status | — |
| PPM000908 | PGS000337 (MetaPRS_CAD) |
PSS000454| East Asian Ancestry| 49,230 individuals |
PGP000104 | Koyama S et al. Nat Genet (2020) |
Reported Trait: All-cause Mortality | HR: 1.03159 [1.011, 1.052] | — | — | Sex, age, age^2, PCs (1-10), disease status | — |
| PPM000383 | PGS000013 (GPS_CAD) |
PSS000219| European Ancestry| 11,010 individuals |
PGP000057 | Homburger JR et al. Genome Med (2019) |Ext. |
Reported Trait: Coronary artery disease (personal history) | OR: 1.589 [1.32, 1.92] | AUROC: 0.86 | — | age, sex | — |
| PPM000402 | PGS000013 (GPS_CAD) |
PSS000227| Additional Asian Ancestries| 544 individuals |
PGP000060 | Khera AV et al. Circulation (2019) |Ext. |
Reported Trait: Early-onset mycardial infarction (age ≤55 years) | OR: 2.16 [1.35, 1.59] | — | Odds Ratio (OR; top 5% vs. rest): 3.33 [0.82, 13.51] | 4 genetic PCs | — |
| PPM000401 | PGS000013 (GPS_CAD) |
PSS000229| Hispanic or Latin American Ancestry| 919 individuals |
PGP000060 | Khera AV et al. Circulation (2019) |Ext. |
Reported Trait: Early-onset mycardial infarction (age ≤55 years) | OR: 1.56 [1.29, 1.88] | — | Odds Ratio (OR; top 5% vs. rest): 3.38 [2.03, 5.64] | 4 genetic PCs | — |
| PPM000400 | PGS000013 (GPS_CAD) |
PSS000228| African Ancestry| 1,298 individuals |
PGP000060 | Khera AV et al. Circulation (2019) |Ext. |
Reported Trait: Early-onset mycardial infarction (age ≤55 years) | OR: 1.46 [1.28, 1.66] | — | Odds Ratio (OR; top 5% vs. rest): 2.02 [1.29, 3.16] | 4 genetic PCs | — |
| PPM000399 | PGS000013 (GPS_CAD) |
PSS000230| European Ancestry| 3,081 individuals |
PGP000060 | Khera AV et al. Circulation (2019) |Ext. |
Reported Trait: Early-onset mycardial infarction (age ≤55 years) | OR: 2.06 [1.89, 2.25] | — | Odds Ratio (OR; top 5% vs. rest): 5.09 [3.82, 6.78] | 4 genetic PCs | — |
| PPM000518 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Plaque vulnerability score | β: 0.07 [0.003, 0.137] | — | — | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000517 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Microvessels | β: 0.037 [-0.006, 0.08] | — | — | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000516 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Number of smoooth muscle cells | β: -0.004 [-0.038, 0.031] | — | — | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000515 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Number of macrophages | β: 0.01 [-0.015, 0.036] | — | — | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000514 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Moderate/heavy macrophages | OR: 1.103 [0.983, 1.237] | — | — | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000513 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Moderate/heavy smooth muscle cells | OR: 1.004 [0.88, 1.145] | — | — | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000512 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Presence of IPH | OR: 1.126 [0.999, 1.27] | — | — | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000511 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Presence of lipid core >10% | OR: 1.171 [1.026, 1.337] | — | — | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000510 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Moderate/heavy collagen | OR: 1.064 [0.919, 1.231] | — | — | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000509 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Moderate/heavy calficiations | OR: 0.94 [0.826, 1.07] | — | — | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000508 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Plaque vulnerability score | OR: 0.198 [0.003, 0.364] | — | — | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000507 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Microvessels | — | — | Beta (top 20% vs. rest): 0.072 [-0.037, 0.182] | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000506 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Number of smoooth muscle cells | — | — | Beta (top 20% vs. rest): -0.056 [-0.143, 0.031] | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000505 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Number of macrophages | — | — | Beta (top 20% vs. rest): 0.55 [-0.012, 0.121] | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000504 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Moderate/heavy macrophages | — | — | Odds Ratio (OR; top 20% vs. rest): 1.49 [1.118, 1.986] | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000503 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Moderate/heavy smooth muscle cells | — | — | Odds Ratio (OR; top 20% vs. rest): 0.908 [0.652, 1.265] | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000502 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Presence of IPH | — | — | Odds Ratio (OR; top 20% vs. rest): 1.112 [0.821, 1.506] | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000501 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Presence of lipid core >10% | — | — | Odds Ratio (OR; top 20% vs. rest): 1.591 [1.105, 2.291] | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000500 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Moderate/heavy collagen | — | — | Odds Ratio (OR; top 20% vs. rest): 1.091 [0.755, 1.577] | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000499 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Moderate/heavy calficiations | — | — | Odds Ratio (OR; top 20% vs. rest): 1.001 [0.754, 1.33] | Age, sex, surgery year, type of cerebrovascular symptoms, array, 4 genetic PCs | — |
| PPM000498 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. Atherosclerosis (2020) |Ext. |
Reported Trait: Secondary cardiovascular events | HR: 1.15 [1.02, 1.29] | — | — | Age, sex, diabetes, BMI, smoking, hypercholesterolemia, array, 4 genetics PCs | — |
| PPM000019 | PGS000010 (GRS27) |
PSS000012| European Ancestry| 12,676 individuals |
PGP000005 | Abraham G et al. Eur Heart J (2016) |Ext. |
Reported Trait: Incident coronary artery disease | HR: 1.21 [1.12, 1.3] | — | — | — | — |
| PPM000021 | PGS000010 (GRS27) |
PSS000011| European Ancestry| 3,406 individuals |
PGP000005 | Abraham G et al. Eur Heart J (2016) |Ext. |
Reported Trait: Incident coronary artery disease | HR: 1.2 [1.07, 1.26] | — | — | — | — |
| PPM000389 | PGS000016 (GPS_AF) |
PSS000217| European Ancestry| 10,303 individuals |
PGP000057 | Homburger JR et al. Genome Med (2019) |Ext. |
Reported Trait: Atrial Fibrillation (personal history) | — | AUROC: 0.57 | — | — | — |
| PPM000387 | PGS000013 (GPS_CAD) |
PSS000219| European Ancestry| 11,010 individuals |
PGP000057 | Homburger JR et al. Genome Med (2019) |Ext. |
Reported Trait: Coronary artery disease (personal history) | — | AUROC: 0.6 | — | — | — |
| PPM000497 | PGS000011 (GRS50) |
PSS000284| European Ancestry| 4,260 individuals |
PGP000076 | Khera AV et al. N Engl J Med (2016) |Ext. |
Reported Trait: Coronary artery calcification | — | — | Agatston score (mean, top 20% of GRS): 46.0 [9.0, 54.0] Agatston score (mean, btttom 25% of GRS): 21.0 [18.0, 25.0] |
— | — |
| PPM000916 | PGS000338 (GRS97_AF) |
PSS000462| European Ancestry| 3,759 individuals |
PGP000105 | Kloosterman M et al. Eur J Heart Fail (2020) |
Reported Trait: Atrial fibrillation | OR: 2.13 [1.86, 2.44] | — | — | age, sex, PCs (1-10) of ancestry | — |
| PPM000913 | PGS000338 (GRS97_AF) |
PSS000462| European Ancestry| 3,759 individuals |
PGP000105 | Kloosterman M et al. Eur J Heart Fail (2020) |
Reported Trait: Atrial fibrillation | OR: 2.12 [1.84, 2.45] | — | — | age, height, weight, systolic blood pressure, diastolic blood pressure, current smoking, hypertension, diabetes, myocardial infarction, PCs (1-10) of ancestry | — |
| PPM000911 | PGS000337 (MetaPRS_CAD) |
PSS000457| East Asian Ancestry| 49,230 individuals |
PGP000104 | Koyama S et al. Nat Genet (2020) |
Reported Trait: Mortality (ischemic heart disease) | HR: 1.2158 [1.109, 1.333] | — | — | Sex, age, age^2, PCs (1-10), disease status | — |
| PPM000917 | PGS000338 (GRS97_AF) |
PSS000461| European Ancestry| 2,262 individuals |
PGP000105 | Kloosterman M et al. Eur J Heart Fail (2020) |
Reported Trait: Atrial fibrillation in individuals with heart failure and a reduced ejection fraction | OR: 2.12 [1.77, 2.54] | — | — | age, sex, PCs (1-10) of ancestry | — |
| PPM000915 | PGS000338 (GRS97_AF) |
PSS000460| European Ancestry| 530 individuals |
PGP000105 | Kloosterman M et al. Eur J Heart Fail (2020) |
Reported Trait: Atrial fibrillation in individuals with heart failure and a preserved ejection fraction | OR: 2.02 [1.37, 2.99] | — | — | age, height, weight, systolic blood pressure, diastolic blood pressure, current smoking, hypertension, diabetes, myocardial infarction, PCs (1-10) of ancestry | — |
| PPM000914 | PGS000338 (GRS97_AF) |
PSS000461| European Ancestry| 2,262 individuals |
PGP000105 | Kloosterman M et al. Eur J Heart Fail (2020) |
Reported Trait: Atrial fibrillation in individuals with heart failure and a reduced ejection fraction | OR: 2.08 [1.72, 2.5] | — | — | age, height, weight, systolic blood pressure, diastolic blood pressure, current smoking, hypertension, diabetes, myocardial infarction, PCs (1-10) of ancestry | — |
| PPM000920 | PGS000338 (GRS97_AF) |
PSS000462| European Ancestry| 3,759 individuals |
PGP000105 | Kloosterman M et al. Eur J Heart Fail (2020) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.721 [0.704, 737.0] | — | PCs (1-10) of ancestry, CHARGE-AF risk factors (age, height, weight, systolic blood pressure, diastolic blood pressure, current smoking, myocardial infarction, diabetes) | — |
| PPM000919 | PGS000338 (GRS97_AF) |
PSS000462| European Ancestry| 3,759 individuals |
PGP000105 | Kloosterman M et al. Eur J Heart Fail (2020) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.606 [0.588, 0.624] | — | PCs (1-10) of ancestry | — |
| PPM000912 | PGS000337 (MetaPRS_CAD) |
PSS000455| East Asian Ancestry| 49,230 individuals |
PGP000104 | Koyama S et al. Nat Genet (2020) |
Reported Trait: Mortality (congestive heart failure) | HR: 1.15604 [1.042, 1.2283] | — | — | Sex, age, age^2, PCs (1-10), disease status | — |
| PPM000910 | PGS000337 (MetaPRS_CAD) |
PSS000458| East Asian Ancestry| 49,230 individuals |
PGP000104 | Koyama S et al. Nat Genet (2020) |
Reported Trait: Mortality (diseases of the respiratory system) | HR: 1.07133 [1.012, 1.134] | — | — | Sex, age, age^2, PCs (1-10), disease status | — |
| PPM000907 | PGS000337 (MetaPRS_CAD) |
PSS000459| East Asian Ancestry| 10,999 individuals |
PGP000104 | Koyama S et al. Nat Genet (2020) |
Reported Trait: Coronary artery disease | OR: 1.84 [1.744, 1.943] | AUROC: 0.674 [0.661, 0.687] | R²: 0.087 [0.074, 0.101] | — | — |
| PPM000918 | PGS000338 (GRS97_AF) |
PSS000460| European Ancestry| 530 individuals |
PGP000105 | Kloosterman M et al. Eur J Heart Fail (2020) |
Reported Trait: Atrial fibrillation in individuals with heart failure and a preserved ejection fraction | OR: 1.82 [1.28, 2.59] | — | — | age, sex, PCs (1-10) of ancestry | — |
| PPM000933 | PGS000013 (GPS_CAD) |
PSS000469| Multi-ancestry (including European)| 325,003 individuals |
PGP000108 | Hindy G et al. Arterioscler Thromb Vasc Biol (2020) |Ext. |
Reported Trait: Incident coronary artery disease | — | C-index: 0.768 [0.76, 0.776] | — | age, sex, PCs (1-10), Pooled Cohort Equations risk estimator | — |
| PPM000932 | PGS000013 (GPS_CAD) |
PSS000469| Multi-ancestry (including European)| 325,003 individuals |
PGP000108 | Hindy G et al. Arterioscler Thromb Vasc Biol (2020) |Ext. |
Reported Trait: Incident coronary artery disease | — | C-index: 0.756 [0.75, 0.762] | — | age, sex, PCs (1-10) | — |
| PPM000929 | PGS000013 (GPS_CAD) |
PSS000468| Multi-ancestry (including European)| 5,685 individuals |
PGP000108 | Hindy G et al. Arterioscler Thromb Vasc Biol (2020) |Ext. |
Reported Trait: Incident coronary artery disease | — | C-index: 0.802 [0.763, 0.8841] | — | age, sex, PCs (1-10), Pooled Cohort Equations risk estimator | — |
| PPM000928 | PGS000013 (GPS_CAD) |
PSS000468| Multi-ancestry (including European)| 5,685 individuals |
PGP000108 | Hindy G et al. Arterioscler Thromb Vasc Biol (2020) |Ext. |
Reported Trait: Incident coronary artery disease | — | C-index: 0.759 [0.724, 0.794] | — | age, sex, PCs (1-10) | — |
| PPM000927 | PGS000013 (GPS_CAD) |
PSS000468| Multi-ancestry (including European)| 5,685 individuals |
PGP000108 | Hindy G et al. Arterioscler Thromb Vasc Biol (2020) |Ext. |
Reported Trait: Incident coronary artery disease | HR: 1.45 [1.34, 1.56] | — | — | age, sex, clinical risk factors (systolic blood pressure, diastolic blood pressure, apolipoprotein B, apolipoprotein A1, total cholesterol, LDL cholesterol, HDL cholesterol, body mass index, current smoker, diabetes), family history of CAD | — |
| PPM000930 | PGS000013 (GPS_CAD) |
PSS000469| Multi-ancestry (including European)| 325,003 individuals |
PGP000108 | Hindy G et al. Arterioscler Thromb Vasc Biol (2020) |Ext. |
Reported Trait: Incident coronary artery disease | HR: 1.53 [1.49, 1.56] | — | — | age, sex | — |
| PPM000926 | PGS000013 (GPS_CAD) |
PSS000467| Multi-ancestry (including European)| 28,556 individuals |
PGP000108 | Hindy G et al. Arterioscler Thromb Vasc Biol (2020) |Ext. |
Reported Trait: Incident coronary artery disease | HR: 1.45 [1.4, 1.49] | — | — | age, sex | — |
| PPM000931 | PGS000013 (GPS_CAD) |
PSS000469| Multi-ancestry (including European)| 325,003 individuals |
PGP000108 | Hindy G et al. Arterioscler Thromb Vasc Biol (2020) |Ext. |
Reported Trait: Incident coronary artery disease | HR: 1.46 [1.42, 1.49] | — | — | age, sex, clinical risk factors (systolic blood pressure, diastolic blood pressure, apolipoprotein B, apolipoprotein A1, total cholesterol, LDL cholesterol, HDL cholesterol, body mass index, current smoker, diabetes), family history of CAD | — |
| PPM000996 | PGS000349 (PRS70_CAD) |
PSS000508| European Ancestry| 3,748 individuals |
PGP000114 | Pechlivanis S et al. BMC Med Genet (2020) |
Reported Trait: Coronary artery calcification | OR: 1.19 [1.1, 1.29] | — | — | age, sex, cardiovascular risk factors (systolic blood pressure, antihypertensive medication, smoking, LDL-cholestrol, HDL-cholesterol, lipid lowering medication, BMI and diabetes). | — |
| PPM000995 | PGS000349 (PRS70_CAD) |
PSS000505| European Ancestry| 4,041 individuals |
PGP000114 | Pechlivanis S et al. BMC Med Genet (2020) |
Reported Trait: Coronary artery calcification | OR: 1.18 [1.1, 1.27] | — | — | age, sex, cardiovascular risk factors (systolic blood pressure, antihypertensive medication, smoking, LDL-cholestrol, HDL-cholesterol, lipid lowering medication, BMI and diabetes). | — |
| PPM000993 | PGS000349 (PRS70_CAD) |
PSS000509| European Ancestry| 2,560 individuals |
PGP000114 | Pechlivanis S et al. BMC Med Genet (2020) |
Reported Trait: Incident Coronary Heart Disease in indiviuals with coronary artery calcification > 0 | HR: 1.21 [1.08, 1.36] | — | — | age, sex, cardiovascular risk factors (systolic blood pressure, antihypertensive medication, smoking, LDL-cholestrol, HDL-cholesterol, lipid lowering medication, BMI and diabetes). | — |
| PPM000992 | PGS000349 (PRS70_CAD) |
PSS000510| European Ancestry| 1,765 individuals |
PGP000114 | Pechlivanis S et al. BMC Med Genet (2020) |
Reported Trait: Incident Coronary Heart Disease in males | HR: 1.23 [1.07, 1.41] | — | — | age, cardiovascular risk factors (systolic blood pressure, antihypertensive medication, smoking, LDL-cholestrol, HDL-cholesterol, lipid lowering medication, BMI and diabetes) and coronary artery calcification. | — |
| PPM000991 | PGS000349 (PRS70_CAD) |
PSS000506| European Ancestry| 1,919 individuals |
PGP000114 | Pechlivanis S et al. BMC Med Genet (2020) |
Reported Trait: Incident Coronary Heart Disease in males | HR: 1.25 [1.1, 1.42] | — | — | age | — |
| PPM000990 | PGS000349 (PRS70_CAD) |
PSS000507| European Ancestry| 3,748 individuals |
PGP000114 | Pechlivanis S et al. BMC Med Genet (2020) |
Reported Trait: Incident Coronary Heart Disease | HR: 1.18 [1.06, 1.31] | — | — | age, sex, cardiovascular risk factors (systolic blood pressure, antihypertensive medication, smoking, LDL-cholestrol, HDL-cholesterol, lipid lowering medication, BMI and diabetes) and coronary artery calcification. | — |
| PPM000989 | PGS000349 (PRS70_CAD) |
PSS000504| European Ancestry| 4,041 individuals |
PGP000114 | Pechlivanis S et al. BMC Med Genet (2020) |
Reported Trait: Incident Coronary Heart Disease | HR: 1.18 [1.06, 1.31] | — | — | age, sex | — |
| PPM002180 | PGS000818 (GRS_Metabo) |
PSS001064| European Ancestry| 1,939 individuals |
PGP000202 | Bauer A et al. Genet Epidemiol (2021) |
Reported Trait: Incident coronary heart disease | HR: 1.2341 [1.1137, 1.3676] | — | — | — | — |
| PPM002181 | PGS000818 (GRS_Metabo) |
PSS001064| European Ancestry| 1,939 individuals |
PGP000202 | Bauer A et al. Genet Epidemiol (2021) |
Reported Trait: Incident coronary heart disease | HR: 1.2126 [1.0766, 1.3659] | — | — | Age, sex, survey | — |
| PPM002182 | PGS000013 (GPS_CAD) |
PSS001063| European Ancestry| 2,909 individuals |
PGP000202 | Bauer A et al. Genet Epidemiol (2021) |Ext. |
Reported Trait: Incident coronary heart disease | — | C-index: 0.573 [0.5254, 0.6212] | — | — | Only 6,481,934 SNPs from PGS000013 were utilised. SNPs were not included due to imputation quality R^2 < 0.3 |
| PPM000607 | PGS000200 (GRS28) |
PSS000334| European Ancestry| 39,758 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.18 [1.13, 1.23] | C-index: 0.697 | — | sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM001757 | PGS000737 (PRS_BrS) |
PSS000905| European Ancestry| 1,185 individuals |
PGP000144 | Tadros R et al. Eur Heart J (2019) |
Reported Trait: Ajmaline-induced Type I Brugada syndrome electrocardiogram | OR: 1.174 [1.138, 1.21] | — | — | — | — |
| PPM001758 | PGS000737 (PRS_BrS) |
PSS000905| European Ancestry| 1,185 individuals |
PGP000144 | Tadros R et al. Eur Heart J (2019) |
Reported Trait: Ajmaline-induced Type I Brugada syndrome electrocardiogram | — | C-index: 0.68 [0.65, 0.71] | correlation coefficient (r): -0.14 | — | — |
| PPM000994 | PGS000349 (PRS70_CAD) |
PSS000511| European Ancestry| 1,426 individuals |
PGP000114 | Pechlivanis S et al. BMC Med Genet (2020) |
Reported Trait: Incident Coronary Heart Disease in males with coronary artery calcification > 0 | HR: 1.26 [1.09, 1.46] | — | — | age, cardiovascular risk factors (systolic blood pressure, antihypertensive medication, smoking, LDL-cholestrol, HDL-cholesterol, lipid lowering medication, BMI and diabetes). | — |
| PPM000825 | PGS000117 (CVD_EJ2020) |
PSS000388| Multi-ancestry (including European)| 204,675 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (under age 55) | — | C-index: 0.66 [0.65, 0.66] | — | age,sex | — |
| PPM000826 | PGS000117 (CVD_EJ2020) |
PSS000388| Multi-ancestry (including European)| 204,675 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (under age 55) | — | C-index: 0.7 [0.7, 0.71] | — | pooled cohort equations | — |
| PPM000828 | PGS000117 (CVD_EJ2020) |
PSS000384| Multi-ancestry (including European)| 147,985 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (over age 55) | — | C-index: 0.7 [0.69, 0.71] | — | age,sex | — |
| PPM000829 | PGS000117 (CVD_EJ2020) |
PSS000384| Multi-ancestry (including European)| 147,985 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (over age 55) | — | C-index: 0.77 [0.76, 0.78] | — | pooled cohort equations | — |
| PPM000831 | PGS000117 (CVD_EJ2020) |
PSS000392| Multi-ancestry (including European)| 147,363 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (in males) | — | C-index: 0.67 [0.66, 0.67] | — | age,sex | — |
| PPM000832 | PGS000117 (CVD_EJ2020) |
PSS000392| Multi-ancestry (including European)| 147,363 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (in males) | — | C-index: 0.71 [0.71, 0.72] | — | pooled cohort equations | — |
| PPM001765 | PGS000739 (HCM_GRS) |
PSS000909| Multi-ancestry (including European)| 41,597 individuals |
PGP000146 | Harper AR et al. Nat Genet (2021) |
Reported Trait: Hypertrophic cardiomyopathy | OR: 1.73 [1.63, 1.83] | — | — | Age, gender, PCs(1-10) | — |
| PPM000834 | PGS000117 (CVD_EJ2020) |
PSS000396| Multi-ancestry (including European)| 205,297 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (in females) | — | C-index: 0.69 [0.68, 0.7] | — | age,sex | — |
| PPM000835 | PGS000117 (CVD_EJ2020) |
PSS000396| Multi-ancestry (including European)| 205,297 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (in females) | — | C-index: 0.74 [0.73, 0.75] | — | pooled cohort equations | — |
| PPM001373 | PGS000665 (GRS_32) |
PSS000602| European Ancestry| 51,288 individuals |
PGP000125 | Marston NA et al. Circulation (2020) |
Reported Trait: Incident ischemic stroke | — | — | Hazard Ratio (HR, top vs. bottom tertile): 1.24 [1.05, 1.45] Hazard Ratio (HR, intermediate vs. bottom tertile): 1.15 [0.98, 1.36] |
age, sex, PCs(1-5), hypertension, hyperlipidemia, diabetes mellitus, smoking, bascular disease, congestive heart failure, atrial fibrillation | — |
| PPM001374 | PGS000665 (GRS_32) |
PSS000602| European Ancestry| 51,288 individuals |
PGP000125 | Marston NA et al. Circulation (2020) |
Reported Trait: Incident ischemic stroke | — | C-index: 0.65 [0.63, 0.66] | — | Clinical variables from the Revised Framingham Stroke Risk score, geographic region | — |
| PPM001375 | PGS000665 (GRS_32) |
PSS000601| European Ancestry| 11,187 individuals |
PGP000125 | Marston NA et al. Circulation (2020) |
Reported Trait: Incident ischemic stroke in individuals with atrial fibrillation | — | — | Hazard Ratio (HR, top vs. bottom tertile): 1.29 [1.01, 1.64] | age, sex, PCs(1-5), hypertension, hyperlipidemia, diabetes mellitus, smoking, bascular disease, congestive heart failure, atrial fibrillation, components of CHA2DS2-VASc score | — |
| PPM000608 | PGS000200 (GRS28) |
PSS000332| African Ancestry| 7,070 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.11 [0.99, 1.24] | C-index: 0.652 | — | sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000823 | PGS000117 (CVD_EJ2020) |
PSS000400| Multi-ancestry (including European)| 352,660 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease | — | C-index: 0.75 [0.75, 0.76] | — | pooled cohort equations | — |
| PPM000605 | PGS000013 (GPS_CAD) |
PSS000335| Hispanic or Latin American Ancestry| 2,493 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.42 [1.25, 1.61] | AUROC: 0.776 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000604 | PGS000011 (GRS50) |
PSS000335| Hispanic or Latin American Ancestry| 2,493 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.2 [1.06, 1.35] | AUROC: 0.769 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000603 | PGS000018 (metaGRS_CAD) |
PSS000331| African Ancestry| 7,597 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.4 [1.3, 1.52] | AUROC: 0.775 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000602 | PGS000013 (GPS_CAD) |
PSS000331| African Ancestry| 7,597 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.3 [1.21, 1.41] | AUROC: 0.771 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000601 | PGS000011 (GRS50) |
PSS000331| African Ancestry| 7,597 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.05 [0.98, 1.14] | AUROC: 0.763 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000600 | PGS000018 (metaGRS_CAD) |
PSS000333| European Ancestry| 45,645 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.73 [1.68, 1.78] | AUROC: 0.772 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000599 | PGS000013 (GPS_CAD) |
PSS000333| European Ancestry| 45,645 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.66 [1.62, 1.71] | AUROC: 0.77 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000598 | PGS000011 (GRS50) |
PSS000333| European Ancestry| 45,645 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.28 [1.25, 1.32] | AUROC: 0.75 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000612 | PGS000200 (GRS28) |
PSS000335| Hispanic or Latin American Ancestry| 2,493 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.27 [1.12, 1.42] | AUROC: 0.771 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000611 | PGS000200 (GRS28) |
PSS000331| African Ancestry| 7,597 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.07 [0.99, 1.16] | AUROC: 0.763 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000610 | PGS000200 (GRS28) |
PSS000333| European Ancestry| 45,645 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.24 [1.21, 1.28] | AUROC: 0.748 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000609 | PGS000200 (GRS28) |
PSS000336| Hispanic or Latin American Ancestry| 2,194 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.14 [0.94, 1.37] | C-index: 0.655 | — | sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM001746 | PGS000013 (GPS_CAD) |
PSS000898| African Ancestry| 16,755 individuals |
PGP000143 | Fahed AC et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.25 [1.12, 1.4] | — | — | PCs(1-4) | — |
| PPM001747 | PGS000013 (GPS_CAD) |
PSS000902| South Asian Ancestry| 8,102 individuals |
PGP000143 | Fahed AC et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.47 [1.36, 1.59] | — | — | PCs(1-4) | — |
| PPM000606 | PGS000018 (metaGRS_CAD) |
PSS000335| Hispanic or Latin American Ancestry| 2,493 individuals |
PGP000083 | Dikilitas O et al. Am J Hum Genet (2020) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.93 [1.67, 2.22] | AUROC: 0.794 | — | age at first EHR record, duration of EHR, sex, eMERGE site, first five ancestry-specific principal components | — |
| PPM000836 | PGS000116 (CAD_EJ2020) |
PSS000401| Multi-ancestry (including European)| 350,730 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease | — | C-index: 0.74 [0.73, 0.75] | — | QRISK3 | — |
| PPM000837 | PGS000116 (CAD_EJ2020) |
PSS000389| Multi-ancestry (including European)| 203,620 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (over age 55) | — | C-index: 0.75 [0.74, 0.76] | — | QRISK3 | — |
| PPM000838 | PGS000116 (CAD_EJ2020) |
PSS000385| Multi-ancestry (including European)| 147,110 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (under age 55) | — | C-index: 0.83 [0.81, 0.84] | — | QRISK3 | — |
| PPM000839 | PGS000116 (CAD_EJ2020) |
PSS000393| Multi-ancestry (including European)| 146,573 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (in males) | — | C-index: 0.73 [0.72, 0.74] | — | QRISK3 | — |
| PPM000840 | PGS000116 (CAD_EJ2020) |
PSS000397| Multi-ancestry (including European)| 204,157 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (in females) | — | C-index: 0.78 [0.76, 0.79] | — | QRISK3 | — |
| PPM000841 | PGS000117 (CVD_EJ2020) |
PSS000402| Multi-ancestry (including European)| 350,730 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease | — | C-index: 0.75 [0.75, 0.76] | — | QRISK3 | — |
| PPM000842 | PGS000117 (CVD_EJ2020) |
PSS000390| Multi-ancestry (including European)| 203,620 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (over age 55) | — | C-index: 0.7 [0.7, 0.71] | — | QRISK3 | — |
| PPM000843 | PGS000117 (CVD_EJ2020) |
PSS000386| Multi-ancestry (including European)| 147,110 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (under age 55) | — | C-index: 0.77 [0.76, 0.78] | — | QRISK3 | — |
| PPM000844 | PGS000117 (CVD_EJ2020) |
PSS000394| Multi-ancestry (including European)| 146,573 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (in males) | — | C-index: 0.71 [0.71, 0.72] | — | QRISK3 | — |
| PPM000845 | PGS000117 (CVD_EJ2020) |
PSS000398| Multi-ancestry (including European)| 204,157 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (in females) | — | C-index: 0.74 [0.73, 0.75] | — | QRISK3 | — |
| PPM000743 | PGS000296 (GPS_CAD_SA) |
PSS000365| South Asian Ancestry| 491 individuals |
PGP000090 | Wang M et al. J Am Coll Cardiol (2020) |
Reported Trait: Myocardial infarction (first-ever) | OR: 1.6 [1.32, 1.94] | AUROC: 0.6632 | — | age, sex, top 5 genetic PCs | — |
| PPM000745 | PGS000296 (GPS_CAD_SA) |
PSS000366| South Asian Ancestry| 2,963 individuals |
PGP000090 | Wang M et al. J Am Coll Cardiol (2020) |
Reported Trait: Coronary artery disease | OR: 1.66 [1.53, 1.81] | AUROC: 0.712 | — | age, sex, top 5 genetic PCs | — |
| PPM001749 | PGS000013 (GPS_CAD) |
PSS000901| Hispanic or Latin American Ancestry| 9,085 individuals |
PGP000143 | Fahed AC et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.52 [1.43, 1.62] | — | — | PCs(1-4) | — |
| PPM000746 | PGS000296 (GPS_CAD_SA) |
PSS000366| South Asian Ancestry| 2,963 individuals |
PGP000090 | Wang M et al. J Am Coll Cardiol (2020) |
Reported Trait: Coronary artery disease | OR: 1.58 [1.42, 1.75] | — | — | age, sex, top 5 genetic PCs, diabetes, hypertension, hypercholesterolemia, smoking, body mass index | — |
| PPM000747 | PGS000013 (GPS_CAD) |
PSS000367| South Asian Ancestry| 7,244 individuals |
PGP000090 | Wang M et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.5302 | AUROC: 0.8021 | — | age, sex, top 5 genetic PCs | — |
| PPM000748 | PGS000013 (GPS_CAD) |
PSS000365| South Asian Ancestry| 491 individuals |
PGP000090 | Wang M et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Myocardial infarction (first-ever) | OR: 1.4605 | AUROC: 0.6482 | — | age, sex, top 5 genetic PCs | — |
| PPM000749 | PGS000013 (GPS_CAD) |
PSS000366| South Asian Ancestry| 2,963 individuals |
PGP000090 | Wang M et al. J Am Coll Cardiol (2020) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.5793 | AUROC: 0.7066 | — | age, sex, top 5 genetic PCs | — |
| PPM000888 | PGS000331 (PRS_AF) |
PSS000442| European Ancestry| 135,300 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Atrial fibrillation (incident and prevalent cases) | HR: 1.62 [1.59, 1.65] | — | — | genotyping array/batch, 10 ancestry PCs, stratified by sex | — |
| PPM000886 | PGS000329 (PRS_CHD) |
PSS000445| European Ancestry| 135,300 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Coronary heart disease (incident and prevalent cases) | HR: 1.31 [1.29, 1.33] | — | — | genotyping array/batch, 10 ancestry PCs, stratified by sex | — |
| PPM000807 | PGS000116 (CAD_EJ2020) |
PSS000399| Multi-ancestry (including European)| 352,660 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease | — | C-index: 0.76 [0.75, 0.76] | — | age,sex | — |
| PPM000808 | PGS000116 (CAD_EJ2020) |
PSS000399| Multi-ancestry (including European)| 352,660 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease | — | C-index: 0.78 [0.77, 0.79] | — | pooled cohort equations | — |
| PPM000810 | PGS000116 (CAD_EJ2020) |
PSS000387| Multi-ancestry (including European)| 204,675 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (over age 55) | — | C-index: 0.71 [0.7, 0.72] | — | age,sex | — |
| PPM000811 | PGS000116 (CAD_EJ2020) |
PSS000387| Multi-ancestry (including European)| 204,675 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (over age 55) | — | C-index: 0.74 [0.73, 0.74] | — | pooled cohort equations | — |
| PPM000813 | PGS000116 (CAD_EJ2020) |
PSS000383| Multi-ancestry (including European)| 147,985 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (under age 55) | — | C-index: 0.76 [0.75, 0.78] | — | age,sex | — |
| PPM000814 | PGS000116 (CAD_EJ2020) |
PSS000383| Multi-ancestry (including European)| 147,985 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (under age 55) | — | C-index: 0.8 [0.79, 0.82] | — | pooled cohort equations | — |
| PPM001767 | PGS000739 (HCM_GRS) |
PSS000910| Multi-ancestry (including European)| 20,501 individuals |
PGP000146 | Harper AR et al. Nat Genet (2021) |
Reported Trait: Hypertrophic cardiomyopathy carrying a pathogenic sarcomere mutation | OR: 1.54 [1.39, 1.69] | — | — | Age, gender, PCs(1-10) | — |
| PPM000816 | PGS000116 (CAD_EJ2020) |
PSS000391| Multi-ancestry (including European)| 147,363 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (in males) | — | C-index: 0.68 [0.67, 0.69] | — | age,sex | — |
| PPM000817 | PGS000116 (CAD_EJ2020) |
PSS000391| Multi-ancestry (including European)| 147,363 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (in males) | — | C-index: 0.71 [0.7, 0.72] | — | pooled cohort equations | — |
| PPM002190 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Retinal hemorrhage in inidividuals with type 2 diabetes | OR: 1.44 [1.03, 2.02] | — | — | — | — |
| PPM000819 | PGS000116 (CAD_EJ2020) |
PSS000395| Multi-ancestry (including European)| 205,297 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (in females) | — | C-index: 0.71 [0.7, 0.73] | — | age,sex | — |
| PPM000820 | PGS000116 (CAD_EJ2020) |
PSS000395| Multi-ancestry (including European)| 205,297 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (in females) | — | C-index: 0.76 [0.74, 0.77] | — | pooled cohort equations | — |
| PPM000822 | PGS000117 (CVD_EJ2020) |
PSS000400| Multi-ancestry (including European)| 352,660 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease | — | C-index: 0.71 [0.71, 0.72] | — | age,sex | — |
| PPM000744 | PGS000296 (GPS_CAD_SA) |
PSS000365| South Asian Ancestry| 491 individuals |
PGP000090 | Wang M et al. J Am Coll Cardiol (2020) |
Reported Trait: Myocardial infarction (first-ever) | OR: 1.51 [1.22, 1.88] | — | — | age, sex, top 5 genetic PCs, diabetes, hypertension, hypercholesterolemia, family history of heart disease, current smoking, family history of myocardial infarction | — |
| PPM000824 | PGS000117 (CVD_EJ2020) |
PSS000388| Multi-ancestry (including European)| 204,675 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (under age 55) | — | C-index: 0.56 [0.55, 0.56] | — | — | — |
| PPM000827 | PGS000117 (CVD_EJ2020) |
PSS000384| Multi-ancestry (including European)| 147,985 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (over age 55) | — | C-index: 0.59 [0.58, 0.61] | — | — | — |
| PPM000830 | PGS000117 (CVD_EJ2020) |
PSS000392| Multi-ancestry (including European)| 147,363 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (in males) | — | C-index: 0.57 [0.56, 0.57] | — | — | — |
| PPM000833 | PGS000117 (CVD_EJ2020) |
PSS000396| Multi-ancestry (including European)| 205,297 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease (in females) | — | C-index: 0.56 [0.55, 0.57] | — | — | — |
| PPM000806 | PGS000116 (CAD_EJ2020) |
PSS000399| Multi-ancestry (including European)| 352,660 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease | HR: 1.32 [1.3, 1.34] | C-index: 0.61 [0.6, 0.62] | — | — | — |
| PPM000809 | PGS000116 (CAD_EJ2020) |
PSS000387| Multi-ancestry (including European)| 204,675 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (over age 55) | — | C-index: 0.6 [0.59, 0.61] | — | — | — |
| PPM000812 | PGS000116 (CAD_EJ2020) |
PSS000383| Multi-ancestry (including European)| 147,985 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (under age 55) | — | C-index: 0.64 [0.63, 0.66] | — | — | — |
| PPM000815 | PGS000116 (CAD_EJ2020) |
PSS000391| Multi-ancestry (including European)| 147,363 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (in males) | — | C-index: 0.61 [0.6, 0.62] | — | — | — |
| PPM000818 | PGS000116 (CAD_EJ2020) |
PSS000395| Multi-ancestry (including European)| 205,297 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident coronary artery disease (in females) | — | C-index: 0.61 [0.6, 0.63] | — | — | — |
| PPM000821 | PGS000117 (CVD_EJ2020) |
PSS000400| Multi-ancestry (including European)| 352,660 individuals |
PGP000054 | Elliott J et al. JAMA (2020) |
Reported Trait: Incident cardiovascular disease | — | C-index: 0.56 [0.56, 0.57] | — | — | — |
| PPM001598 | PGS000706 (HC215) |
PSS000822| European Ancestry| 87,413 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Hypertension | — | AUROC: 0.623 | — | Age, sex, PCs(1-10) | — |
| PPM001601 | PGS000709 (HC299) |
PSS000820| European Ancestry| 87,413 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Heart failure | — | AUROC: 0.53217 | — | Age, sex, PCs(1-10) | — |
| PPM001602 | PGS000710 (HC326) |
PSS000826| European Ancestry| 87,413 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Myocardial infarction | — | AUROC: 0.59348 | — | Age, sex, PCs(1-10) | — |
| PPM001606 | PGS000710 (HC326) |
PSS000827| European Ancestry| 135,300 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Myocardial infarction | HR: 1.19 [1.17, 1.22] | C-index: 0.707 | — | Age as time scale, sex, batch, PCs(1-10) | — |
| PPM001614 | PGS000709 (HC299) |
PSS000821| European Ancestry| 135,300 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Heart failure | HR: 1.08 [1.06, 1.1] | C-index: 0.635 | — | Age as time scale, sex, batch, PCs(1-10) | — |
| PPM001617 | PGS000013 (GPS_CAD) |
PSS000839| European Ancestry| 4,847 individuals |
PGP000129 | Mosley JD et al. JAMA (2020) |Ext. |
Reported Trait: Prevalent and incident coronary heart disease | OR: 1.89 [1.75, 2.03] | — | — | Age, sex, PCs (1-5) | — |
| PPM001618 | PGS000013 (GPS_CAD) |
PSS000837| European Ancestry| 4,847 individuals |
PGP000129 | Mosley JD et al. JAMA (2020) |Ext. |
Reported Trait: Incident coronary heart disease (10-year risk) | HR: 1.24 [1.15, 1.34] | C-index: 0.669 [0.644, 0.691] | — | Age, sex, PCs (1-5) | — |
| PPM001619 | PGS000013 (GPS_CAD) |
PSS000838| European Ancestry| 2,390 individuals |
PGP000129 | Mosley JD et al. JAMA (2020) |Ext. |
Reported Trait: Incident coronary heart disease (10-year risk) | HR: 1.38 [1.21, 1.58] | C-index: 0.672 [0.627, 0.705] | — | Age, sex, PCs (1-5) | — |
| PPM001621 | PGS000013 (GPS_CAD) |
PSS000838| European Ancestry| 2,390 individuals |
PGP000129 | Mosley JD et al. JAMA (2020) |Ext. |
Reported Trait: Incident coronary heart disease (10-year risk) | — | C-index: 0.681 [0.637, 0.715] | Δ C-index (PRS+covariates vs. covariates alone): 0.021 [-0.0004, 0.043] | Pooled cohort risk percentile, age, sex, PCs (1-5) | — |
| PPM001622 | PGS000013 (GPS_CAD) |
PSS000837| European Ancestry| 4,847 individuals |
PGP000129 | Mosley JD et al. JAMA (2020) |Ext. |
Reported Trait: Incident coronary heart disease (10-year risk) | — | C-index: 0.549 [0.521, 0.571] | — | PCs (1-5) | — |
| PPM001623 | PGS000013 (GPS_CAD) |
PSS000838| European Ancestry| 2,390 individuals |
PGP000129 | Mosley JD et al. JAMA (2020) |Ext. |
Reported Trait: Incident coronary heart disease (10-year risk) | — | C-index: 0.587 [0.532, 0.623] | — | PCs (1-5) | — |
| PPM001640 | PGS000043 (PRS_VTE) |
PSS000850| European Ancestry| 715 individuals |
PGP000133 | Naito T et al. Gastroenterology (2020) |Ext. |
Reported Trait: Thromboembolic disease event in individuals with inflammatory bowel disease | — | — | Odds Ratio (OR, top 5% vs. remaining 95%): 3.13 [1.37, 7.18] | Disease duration, age at disease onset, PCs(1-2) | Included 265/297 variants from the original score |
| PPM001641 | PGS000043 (PRS_VTE) |
PSS000850| European Ancestry| 715 individuals |
PGP000133 | Naito T et al. Gastroenterology (2020) |Ext. |
Reported Trait: Thromboembolic disease event in in individuals of inflammatory bowel disease that are carriers of at least 1 thrombophillia pathogenic variant | — | — | Odds Ratio (OR, top 5% vs. remaining 95%): 8.56 [1.76, 41.57] | Age at last visit, PCs(1-2) | Included 265/297 variants from the original score |
| PPM001745 | PGS000013 (GPS_CAD) |
PSS000900| European Ancestry| 474,498 individuals |
PGP000143 | Fahed AC et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.6 [1.44, 1.78] | — | — | PCs(1-4) | — |
| PPM001748 | PGS000013 (GPS_CAD) |
PSS000899| East Asian Ancestry| 3,988 individuals |
PGP000143 | Fahed AC et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.66 [1.47, 1.86] | — | — | PCs(1-4) | — |
| PPM001766 | PGS000739 (HCM_GRS) |
PSS000908| Multi-ancestry (including European)| 21,095 individuals |
PGP000146 | Harper AR et al. Nat Genet (2021) |
Reported Trait: Hypertrophic cardiomyopathy in individuals who do not carry a pathogenic sarcomere mutation | OR: 1.8 [1.67, 1.93] | — | — | Age, gender, PCs(1-10) | — |
| PPM001848 | PGS000013 (GPS_CAD) |
PSS000929| European Ancestry| 5,581 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Coronary artery disease | — | AUROC: 0.6699 [0.6557, 0.684] | — | — | — |
| PPM001849 | PGS000013 (GPS_CAD) |
PSS000930| European Ancestry| 27,048 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Coronary artery disease | — | AUROC: 0.5617 [0.5402, 0.5833] | — | — | — |
| PPM001850 | PGS000013 (GPS_CAD) |
PSS000931| European Ancestry| 431,814 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Coronary artery disease | — | AUROC: 0.6374 [0.6335, 0.6412] | — | — | May be an overlap between score development and testing samples |
| PPM001836 | PGS000746 (PRS_UKB) |
PSS000931| European Ancestry| 431,814 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Reported Trait: Coronary artery disease | — | AUROC: 0.6133 [0.6094, 0.6172] | Area under the Precision-Recall curve (AUPRC): 0.0752 [0.0745, 0.076] | — | — |
| PPM001837 | PGS000747 (PRS_EB) |
PSS000929| European Ancestry| 5,581 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Reported Trait: Coronary artery disease | — | AUROC: 0.5407 [0.5253, 0.5561] | Area under the Precision-Recall curve (AUPRC): 0.498 [0.4962, 0.4998] | — | — |
| PPM001838 | PGS000747 (PRS_EB) |
PSS000930| European Ancestry| 27,048 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Reported Trait: Coronary artery disease | — | AUROC: 0.6565 [0.6369, 0.676] | Area under the Precision-Recall curve (AUPRC): 0.0765 [0.0755, 0.0774] | — | — |
| PPM001840 | PGS000748 (PRS_DE) |
PSS000929| European Ancestry| 5,581 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Reported Trait: Coronary artery disease | — | AUROC: 0.6752 [0.6612, 0.6891] | Area under the Precision-Recall curve (AUPRC): 0.6891 [0.6887, 0.6895] | — | — |
| PPM001844 | PGS000749 (PRS_COMBINED) |
PSS000931| European Ancestry| 431,814 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Reported Trait: Coronary artery disease | — | AUROC: 0.5988 [0.5949, 0.6027] | Area under the Precision-Recall curve (AUPRC): 0.0697 [0.0688, 0.0705] | — | — |
| PPM001834 | PGS000746 (PRS_UKB) |
PSS000929| European Ancestry| 5,581 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Reported Trait: Coronary artery disease | — | AUROC: 0.5143 [0.4992, 0.5294] | Area under the Precision-Recall curve (AUPRC): 0.5607 [0.5593, 0.5621] | — | — |
| PPM001835 | PGS000746 (PRS_UKB) |
PSS000930| European Ancestry| 27,048 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Reported Trait: Coronary artery disease | — | AUROC: 0.6049 [0.5857, 0.6241] | Area under the Precision-Recall curve (AUPRC): 0.046 [0.0454, 0.0466] | — | — |
| PPM001847 | PGS000018 (metaGRS_CAD) |
PSS000931| European Ancestry| 431,814 individuals |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Coronary artery disease | — | AUROC: 0.6377 [0.6339, 0.6416] | Area under the Precision-Recall curve (AUPRC): 0.0832 [0.083, 0.0835] | — | May be an overlap between score development and testing sample |
| PPM001912 | PGS000753 (PRS29_AAA) |
PSS000958| European Ancestry| 46,564 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.37 [1.3, 1.44] | — | — | Age, sex, PCs (1-5) | — |
| PPM001913 | PGS000753 (PRS29_AAA) |
PSS000956| African Ancestry| 47,098 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.15 [1.07, 1.24] | — | — | Age, sex, PCs (1-5) | — |
| PPM001915 | PGS000753 (PRS29_AAA) |
PSS000959| European Ancestry| 10,231 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.31 [1.18, 1.46] | — | — | Age, sex, PCs (1-5) | — |
| PPM001917 | PGS000753 (PRS29_AAA) |
PSS000956| African Ancestry| 47,098 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.13 [1.04, 1.22] | — | — | Age, sex, PCs (1-5), smoking, hypertension, low-density lipoprotein cholesterol with statin adjustment, high-density lipoprotein cholesterol, triglycerides, coronary artery disease as a marker of atherosclerosis burden. | — |
| PPM001918 | PGS000753 (PRS29_AAA) |
PSS000957| European Ancestry| 9,525 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.58 [1.25, 1.98] | — | — | Age, sex, PCs (1-5), smoking, hypertension, low-density lipoprotein cholesterol with statin adjustment, high-density lipoprotein cholesterol, triglycerides, coronary artery disease as a marker of atherosclerosis burden. | — |
| PPM001914 | PGS000753 (PRS29_AAA) |
PSS000957| European Ancestry| 9,525 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 2.46 [1.46, 4.14] | — | — | Age, sex, PCs (1-5) | — |
| PPM001916 | PGS000753 (PRS29_AAA) |
PSS000958| European Ancestry| 46,564 individuals |
PGP000159 | Klarin D et al. Circulation (2020) |
Reported Trait: Prevalent abdominal aortic aneurysm | OR: 1.34 [1.27, 1.41] | — | — | Age, sex, PCs (1-5), smoking, hypertension, low-density lipoprotein cholesterol with statin adjustment, high-density lipoprotein cholesterol, triglycerides, coronary artery disease as a marker of atherosclerosis burden. | — |
| PPM002398 | PGS000863 (Cardiovascular) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 0.95 [0.86, 1.05] | — | — | PC1-10 | — |
| PPM001939 | PGS000043 (PRS_VTE) |
PSS000973| European Ancestry| 29,663 individuals |
PGP000166 | Marston NA et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Venous Thromboembolism | HR: 1.47 [1.29, 1.68] | — | Hazard Ratio (HR, top tertile vs bottom tertile): 2.7 [1.8, 4.06] | Age, sex, PCs(1-5), obesity(BMI≥30), active smoking, history of heart failure, diabetes status. | 273 of original 297 SNPs from Klarin et al (PGS000043) used that reached minimum imputation of 0.58. |
| PPM001940 | PGS000043 (PRS_VTE) |
PSS000973| European Ancestry| 29,663 individuals |
PGP000166 | Marston NA et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Venous Thromboembolism | — | — | Hazard Ratio (HR, middle tertile vs bottom 3.33%): 1.88 [1.23, 2.89] | Age, sex, PCs(1-5), obesity(BMI≥30), active smoking, history of heart failure, diabetes status. | 273 of original 297 SNPs from Klarin et al (PGS000043) used that reached minimum imputation of 0.58. |
| PPM001941 | PGS000043 (PRS_VTE) |
PSS000973| European Ancestry| 29,663 individuals |
PGP000166 | Marston NA et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Venous Thromboembolism | — | C-index: 0.67 [0.63, 0.71] | — | — | 273 of original 297 SNPs from Klarin et al (PGS000043) used that reached minimum imputation of 0.58. |
| PPM001942 | PGS000043 (PRS_VTE) |
PSS000973| European Ancestry| 29,663 individuals |
PGP000166 | Marston NA et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Venous Thromboembolism | — | C-index: 0.67 [0.63, 0.71] | — | Age, obesity(BMI≥30), active smoking, history of heart failure, diabetes status. | 273 of original 297 SNPs from Klarin et al (PGS000043) used that reached minimum imputation of 0.58. |
| PPM001943 | PGS000043 (PRS_VTE) |
PSS000973| European Ancestry| 29,663 individuals |
PGP000166 | Marston NA et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Venous Thromboembolism in individuals without monogenic mutations | HR: 1.53 [1.3, 1.82] | — | Hazard Ratio (HR, top tertile vs. bottom tertile): 2.88 [1.85, 4.49] | Age, sex, PCs(1-5), obesity(BMI≥30), active smoking, history of heart failure, diabetes status. | 273 of original 297 SNPs from Klarin et al (PGS000043) used that reached minimum imputation of 0.58. |
| PPM001944 | PGS000043 (PRS_VTE) |
PSS000973| European Ancestry| 29,663 individuals |
PGP000166 | Marston NA et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Venous Thromboembolism in individuals without monogenic mutations | — | — | Hazard Ratio (HR, middle tertile vs. bottom tertile): 2.11 [1.34, 3.33] | Age, sex, PCs(1-5), obesity(BMI≥30), active smoking, history of heart failure, diabetes status. | 273 of original 297 SNPs from Klarin et al (PGS000043) used that reached minimum imputation of 0.58. |
| PPM002016 | PGS000778 (PRSHCM) |
PSS000999| Ancestry Not Reported| 368 individuals |
PGP000182 | Tadros R et al. Nat Genet (2021) |
Reported Trait: Clinical events in individuals with a pathogenic or likely pathogenic sarcomeric variant | HR: 1.28 [1.06, 1.54] β: 0.247 (0.095) |
— | — | Genetic relatedness matrix, sex | Clinical events includes time to septal reduction therapy, cardiac transplantation, sustained ventricular arrhythmia, sudden cardiac death, appropriate ICD therapy or atrial fibrillation/flutter. |
| PPM002017 | PGS000778 (PRSHCM) |
PSS001000| Ancestry Not Reported| 368 individuals |
PGP000182 | Tadros R et al. Nat Genet (2021) |
Reported Trait: Major clinical events in individuals with a pathogenic or likely pathogenic sarcomeric variant | HR: 1.29 [1.04, 1.59] β: 0.255 (0.108) |
— | — | Genetic relatedness matrix, sex | Major clinical events includes time to septal reduction therapy, cardiac transplantation, sustained ventricular arrhythmia, sudden cardiac death or appropriate ICD therapy. |
| PPM002018 | PGS000778 (PRSHCM) |
PSS001004| Ancestry Not Reported| 368 individuals |
PGP000182 | Tadros R et al. Nat Genet (2021) |
Reported Trait: Septal reduction therapy in individuals with a pathogenic or likely pathogenic sarcomeric variant | HR: 1.36 [1.06, 1.74] β: 0.304 (0.127) |
— | — | Genetic relatedness matrix, sex | Septal reduction therapy includes time time to septal myectomy or alcohol septal ablation. |
| PPM002019 | PGS000016 (GPS_AF) |
PSS000998| Ancestry Not Reported| 368 individuals |
PGP000182 | Tadros R et al. Nat Genet (2021) |Ext. |
Reported Trait: Atrial fibrillation or atrial flutter in individuals with a pathogenic or likely pathogenic sarcomeric variant | HR: 1.5 [1.17, 1.91] β: 0.402 (0.124) |
— | — | Genetic relatedness matrix, sex | — |
| PPM002020 | PGS000778 (PRSHCM) |
PSS001003| Ancestry Not Reported| 194 individuals |
PGP000182 | Tadros R et al. Nat Genet (2021) |
Reported Trait: Maximal left ventricular wall thickness indexed to body surface area (mm/m^2) in individuals with a pathogenic or likely pathogenic sarcomeric variant | β: 0.731 (0.238) | — | — | Genetic relatedness matrix | Each standard deviation increase in the polgyenic risk score is associated with 0.7 mm m^-2 increase in maximal left ventricular wall thickness. |
| PPM002021 | PGS000778 (PRSHCM) |
PSS001002| Ancestry Not Reported| 214 individuals |
PGP000182 | Tadros R et al. Nat Genet (2021) |
Reported Trait: Clinical events in in individuals with a pathogenic or likely pathogenic sarcomeric variant | HR: 1.53 [1.05, 2.22] β: 0.422 (0.193) |
— | — | Genetic relatedness matrix, sex | Clinical events includes time to septal reduction therapy, cardiac transplantation, sustained ventricular arrhythmia, sudden cardiac death, appropriate ICD therapy or atrial fibrillation/flutter. |
| PPM002075 | PGS000798 (157SNP_GRS) |
PSS001026| Multi-ancestry (including European)| 6,660 individuals |
PGP000187 | Severance LM et al. J Cardiovasc Comput Tomogr (2019) |
Reported Trait: Cornary artery calcium (non-zero CAC score) | OR: 1.37 [1.29, 1.45] | — | — | Age, sex | — |
| PPM002015 | PGS000778 (PRSHCM) |
PSS001001| Ancestry Not Reported| 322 individuals |
PGP000182 | Tadros R et al. Nat Genet (2021) |
Reported Trait: Maximal left ventricular wall thickness indexed to body surface area (mm/m^2) in individuals with a pathogenic or likely pathogenic sarcomeric variant | β: 0.726 (0.188) | — | — | Genetic relatedness matrix | Each standard deviation increase in the polgyenic risk score is associated with 0.7 mm m^-2 increase in maximal left ventricular wall thickness. |
| PPM002221 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.41 [1.2, 1.65] | AUROC: 0.685 [0.64, 0.73] | Hazard Ratio (HR, top 33.3% vs bottom 33.3%): 1.74 [1.19, 2.56] | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 12,405 individuals (171 cases) were used due to missing values. For AUROC values this was 11,385 individuals (158 cases). |
| PPM002222 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | — | — | Net reclassification index (NRI): 0.252 [0.175, 0.434] | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 11,385 individuals (158 cases) were used. |
| PPM002223 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.43 [1.22, 1.68] | — | — | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin, PCs(1-10) | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 12,405 individuals (171 cases) were used due to missing values. |
| PPM002224 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.43 [1.22, 1.68] | — | — | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin, intake of antihypertensive drugs, intake of statin | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 12,405 individuals (171 cases) were used due to missing values. |
| PPM002225 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.41 [1.2, 1.66] | — | — | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin, index of relative socio-economic advantage and disadvantage(1-10) | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 12,405 individuals (171 cases) were used due to missing values. |
| PPM002226 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.4 [1.2, 1.64] | — | — | Age, sex, systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, alcohol consumption (current versus former or never consumption) | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. Only 12,405 individuals (171 cases) were used due to missing values. |
| PPM002227 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident ischemic stroke | — | AUROC: 0.582 [0.537, 0.628] | — | — | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. For AUROC values only 11,385 individuals (158 cases) were used. |
| PPM002228 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident large vessel ischemic stroke | HR: 1.43 [1.05, 1.94] | — | — | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. |
| PPM002229 | PGS000039 (metaGRS_ischaemicstroke) |
PSS001082| European Ancestry| 12,792 individuals |
PGP000209 | Neumann JT et al. Stroke (2021) |Ext. |
Reported Trait: Incident cardiometabolic ischemic stroke | HR: 1.74 [1.24, 2.43] | — | — | Age, sex, smoking status (current or former versus never), systolic blood pressure, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index, alcohol consumption (current versus former or never consumption), family history of stroke (event occuring before the age of 50 in a first-degree relative), diabetes, randomization to aspirin | Only 3,219,276 SNPs from PGS000039 were utilised due to variant identifier mismatch. |
| PPM002178 | PGS000818 (GRS_Metabo) |
PSS001063| European Ancestry| 2,909 individuals |
PGP000202 | Bauer A et al. Genet Epidemiol (2021) |
Reported Trait: Incident coronary heart disease | — | C-index: 0.7571 [0.7234, 0.7908] | — | Age, sex, survey | — |
| PPM002179 | PGS000818 (GRS_Metabo) |
PSS001063| European Ancestry| 2,909 individuals |
PGP000202 | Bauer A et al. Genet Epidemiol (2021) |
Reported Trait: Incident coronary heart disease | — | C-index: 0.792 [0.7622, 0.8219] | — | Age, sex, survey, Framingham risk score (diabetes status, current and former smoking status, systolic blood pressure, antihypertensive medication, HDL cholesterol, total cholesterol) | — |
| PPM002183 | PGS000013 (GPS_CAD) |
PSS001063| European Ancestry| 2,909 individuals |
PGP000202 | Bauer A et al. Genet Epidemiol (2021) |Ext. |
Reported Trait: Incident coronary heart disease | — | C-index: 0.7752 [0.7443, 0.8029] | — | Age, sex, survey | Only 6,481,934 SNPs from PGS000013 were utilised. SNPs were not included due to imputation quality R^2 < 0.3 |
| PPM002184 | PGS000013 (GPS_CAD) |
PSS001063| European Ancestry| 2,909 individuals |
PGP000202 | Bauer A et al. Genet Epidemiol (2021) |Ext. |
Reported Trait: Incident coronary heart disease | — | C-index: 0.8012 [0.7775, 0.8353] | — | Age, sex, survey, Framingham risk score (diabetes status, current and former smoking status, systolic blood pressure, antihypertensive medication, HDL cholesterol, total cholesterol) | Only 6,481,934 SNPs from PGS000013 were utilised. SNPs were not included due to imputation quality R^2 < 0.3 |
| PPM002185 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.12 [1.04, 1.2] | — | — | — | — |
| PPM002186 | PGS000819 (PRS_DR) |
PSS001066| European Ancestry| 978 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.22 [1.02, 1.41] | — | — | — | — |
| PPM002187 | PGS000819 (PRS_DR) |
PSS001065| African Ancestry| 1,925 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.15 [1.03, 1.28] | — | — | — | — |
| PPM002188 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | — | — | Odds Ratio (OR, top 10% vs bottom 10%): 1.8 [1.28, 2.55] | Age, sex, body mass index, PCs(1-20), history of hypertension, glucose levels | — |
| PPM002189 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.14 [1.05, 1.23] | — | — | PCs(1-20), type 2 diabetes duration, type 2 diabetes medication, hyperglycemia, elevated HbA1c, hypertension, hypercholesterolemia, hyperlipidemia, insomina, sleep apnea, age, sex, body mass index | — |
| PPM002191 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diplopia in individuals with type 2 diabetes | OR: 1.31 [1.02, 1.7] | — | — | — | — |
| PPM002192 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Time to diabetic retinopathy diagnosis in individuals with type 2 diabetes | HR: 1.13 [1.05, 1.21] | — | — | Age, sex, body mass index, PCs(1-20), history of hypertension, glucose levels | — |
| PPM002393 | PGS000862 (DR) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 0.98 [0.89, 1.08] | — | — | PC1-10 | — |
| PPM002395 | PGS000862 (DR) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.09 [1.02, 1.17] | — | — | PC1-10 | — |
| PPM002400 | PGS000863 (Cardiovascular) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.02 [0.96, 1.1] | — | — | PC1-10 | — |
| PPM002401 | PGS000863 (Cardiovascular) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 0.98 [0.92, 1.05] | — | — | PC1-10 | — |
| PPM002402 | PGS000863 (Cardiovascular) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 0.98 [0.93, 1.04] | — | — | PC1-10 | — |
| PPM002641 | PGS000899 (PRS176_CHD) |
PSS001168| European Ancestry| 7,403 individuals |
PGP000232 | Feitosa MF et al. Circ Genom Precis Med (2021) |
Reported Trait: Prevalent coronary heart disease age-at-onset | HR: 1.35 [1.26, 1.45] | — | — | Age, sex, study, type II diabetes, hypertension, high density lipoprotein cholesterol, low density lipoprotein cholesterol, waist circumference, current cigarette smoking, current alcohol drinking. | — |
| PPM002642 | PGS000899 (PRS176_CHD) |
PSS001168| European Ancestry| 7,403 individuals |
PGP000232 | Feitosa MF et al. Circ Genom Precis Med (2021) |
Reported Trait: Prevalent coronary heart disease age-at-onset | HR: 1.7 [1.41, 2.05] | — | — | Age, sex, study, PRS*sex, PRS*LLFS, PRS*FamnHS-High risk, type II diabetes, hypertension, high density lipoprotein cholesterol, low density lipoprotein cholesterol, waist circumference, current cigarette smoking, current alcohol drinking. | — |
| PPM002643 | PGS000899 (PRS176_CHD) |
PSS001168| European Ancestry| 7,403 individuals |
PGP000232 | Feitosa MF et al. Circ Genom Precis Med (2021) |
Reported Trait: Prevalent coronary heart disease age-at-onset | HR: 1.75 [1.16, 2.65] | — | — | Age, sex, study, PRS*LLFS, PRS*FamnHS-High risk, type II diabetes, hypertension, high density lipoprotein cholesterol, low density lipoprotein cholesterol, menopause, waist circumference, current cigarette smoking, current alcohol drinking. | — |
| PPM002644 | PGS000899 (PRS176_CHD) |
PSS001168| European Ancestry| 7,403 individuals |
PGP000232 | Feitosa MF et al. Circ Genom Precis Med (2021) |
Reported Trait: Prevalent coronary heart disease age-at-onset (males) | HR: 1.57 [1.28, 1.92] | — | — | Age, study, PRS*LLFS, PRS*FamnHS-High risk, type II diabetes, hypertension, high density lipoprotein cholesterol, low density lipoprotein cholesterol, waist circumference, current cigarette smoking, current alcohol drinking. | — |
| PPM002645 | PGS000899 (PRS176_CHD) |
PSS001168| European Ancestry| 7,403 individuals |
PGP000232 | Feitosa MF et al. Circ Genom Precis Med (2021) |
Reported Trait: Prevalent coronary heart disease age-at-onset (males) | HR: 1.42 [1.3, 1.54] | — | — | Age, study, type II diabetes, hypertension, high density lipoprotein cholesterol, low density lipoprotein cholesterol, waist circumference, current cigarette smoking, current alcohol drinking. | — |
| PPM002647 | PGS000899 (PRS176_CHD) |
PSS001168| European Ancestry| 7,403 individuals |
PGP000232 | Feitosa MF et al. Circ Genom Precis Med (2021) |
Reported Trait: Prevalent coronary heart disease age-at-onset (females) | HR: 1.18 [1.04, 1.34] | — | — | Age, study, type II diabetes, hypertension, high density lipoprotein cholesterol, low density lipoprotein cholesterol, waist circumference, current cigarette smoking, current alcohol drinking. | — |
| PPM002640 | PGS000899 (PRS176_CHD) |
PSS001168| European Ancestry| 7,403 individuals |
PGP000232 | Feitosa MF et al. Circ Genom Precis Med (2021) |
Reported Trait: Prevalent coronary heart disease age-at-onset | HR: 1.6 [1.33, 1.92] | — | — | Age, sex, study, PRS*LLFS, PRS*FamnHS-High risk, type II diabetes, hypertension, high density lipoprotein cholesterol, low density lipoprotein cholesterol, waist circumference, current cigarette smoking, current alcohol drinking. | — |
| PPM002646 | PGS000899 (PRS176_CHD) |
PSS001168| European Ancestry| 7,403 individuals |
PGP000232 | Feitosa MF et al. Circ Genom Precis Med (2021) |
Reported Trait: Prevalent coronary heart disease age-at-onset (females) | HR: 1.76 [1.16, 2.68] | — | — | Age, study, PRS*LLFS, PRS*FamnHS-High risk, type II diabetes, hypertension, high density lipoprotein cholesterol, low density lipoprotein cholesterol, waist circumference, current cigarette smoking, current alcohol drinking. | — |
| PPM002960 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | OR: 1.14 [1.06, 1.23] | — | — | Age at recruitment, sex, UK Biobank array type, PCs(1-10) | — |
| PPM002961 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | OR: 1.14 [1.06, 1.23] | AUROC: 0.605 [0.583, 0.626] | — | Age at recruitment, sex, UK Biobank array type, PCs(1-10), presence of warfarin prescription | — |
| PPM002962 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases who had not been prescribed warfarin | OR: 1.14 [1.05, 1.24] | — | — | Age at recruitment, sex, UK Biobank array type, PCs(1-10) | — |
| PPM002963 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | OR: 1.14 [1.06, 1.23] | — | — | Age at recruitment, sex, UK Biobank array type, PCs(1-10), cumulative CHA2DS2-VASc score | — |
| PPM002964 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | OR: 1.14 | — | — | Age at recruitment, sex, UK Biobank array type, PCs(1-10), individual components of CHA2DS2-VASc score | — |
| PPM002965 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | HR: 1.13 [1.04, 1.21] | C-index: 0.56 [0.54, 0.58] | — | Sex, UK Biobank array, PCs(1-10) | — |
| PPM002966 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | HR: 1.14 [1.01, 1.23] | C-index: 0.56 [0.54, 0.58] | — | Sex, age, UK Biobank array, PCs(1-10) | — |
| PPM002967 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases who had not been prescribed warfarin | HR: 1.13 [1.04, 1.22] | C-index: 0.57 [0.54, 0.59] | — | Sex, UK Biobank array, PCs(1-10) | — |
| PPM002968 | PGS000911 (PRS_IS) |
PSS001445| European Ancestry| 15,929 individuals |
PGP000239 | O'Sullivan JW et al. Circ Genom Precis Med (2021) |
Reported Trait: Ischemic stroke in atrial fibrillation cases | — | C-index: 0.61 [0.58, 0.63] | — | Sex, UK Biobank array, PCs(1-10), cumulative CHA2DS2-VASc score | — |
| PPM002399 | PGS000863 (Cardiovascular) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 0.99 [0.93, 1.07] | — | — | PC1-10 | — |
| PPM002397 | PGS000862 (DR) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.01 [0.96, 1.07] | — | — | PC1-10 | — |
| PPM005152 | PGS000018 (metaGRS_CAD) |
PSS003597| Multi-ancestry (including European)| 12,413 individuals |
PGP000248 | Liou L et al. Breast Cancer Res (2021) |Ext. |
Reported Trait: Incident coronary artery disease survival in individuals with breast cancer | HR: 1.36 [1.23, 1.5] | — | — | Age | SNPs with imputation quality scores of less than 0.3 and ambiguous strand SNPs (A/T and G/C pairs) were excluded from PGS000018. |
| PPM005153 | PGS000018 (metaGRS_CAD) |
PSS003596| European Ancestry| 8,946 individuals |
PGP000248 | Liou L et al. Breast Cancer Res (2021) |Ext. |
Reported Trait: Incident coronary artery disease in individuals with breast cancer | HR: 1.36 [1.23, 1.51] | — | — | Age at diagnosis, genotype array, PCs(1-8) | SNPs with imputation quality scores of less than 0.3 and ambiguous strand SNPs (A/T and G/C pairs) were excluded from PGS000018. |
| PPM005154 | PGS000018 (metaGRS_CAD) |
PSS003596| European Ancestry| 8,946 individuals |
PGP000248 | Liou L et al. Breast Cancer Res (2021) |Ext. |
Reported Trait: Incident coronary artery disease in individuals with breast cancer | HR: 1.34 [1.21, 1.49] | — | — | Age at diagnosis, genotype array, PCs(1-8), body mass index, smoking | SNPs with imputation quality scores of less than 0.3 and ambiguous strand SNPs (A/T and G/C pairs) were excluded from PGS000018. |
| PPM005155 | PGS000018 (metaGRS_CAD) |
PSS003596| European Ancestry| 8,946 individuals |
PGP000248 | Liou L et al. Breast Cancer Res (2021) |Ext. |
Reported Trait: Incident coronary artery disease in individuals with breast cancer | HR: 1.34 [1.21, 1.48] | — | — | Age at diagnosis, genotype array, PCs(1-8), body mass index, smoking, sociodemographic variables | SNPs with imputation quality scores of less than 0.3 and ambiguous strand SNPs (A/T and G/C pairs) were excluded from PGS000018. |
| PPM005156 | PGS000018 (metaGRS_CAD) |
PSS003596| European Ancestry| 8,946 individuals |
PGP000248 | Liou L et al. Breast Cancer Res (2021) |Ext. |
Reported Trait: Incident coronary artery disease in individuals with breast cancer | HR: 1.33 [1.2, 1.48] | — | — | Age at diagnosis, genotype array, PCs(1-8), body mass index, smoking, sociodemographic variables, medical variables | SNPs with imputation quality scores of less than 0.3 and ambiguous strand SNPs (A/T and G/C pairs) were excluded from PGS000018. |
| PPM005157 | PGS000018 (metaGRS_CAD) |
PSS003596| European Ancestry| 8,946 individuals |
PGP000248 | Liou L et al. Breast Cancer Res (2021) |Ext. |
Reported Trait: Incident coronary artery disease in individuals with breast cancer | HR: 1.33 [1.2, 1.47] | — | — | Age at diagnosis, genotype array, PCs(1-8), body mass index, smoking, sociodemographic variables, medical variables, oncotherapies | SNPs with imputation quality scores of less than 0.3 and ambiguous strand SNPs (A/T and G/C pairs) were excluded from PGS000018. |
| PPM005158 | PGS000012 (GRS49K) |
PSS003596| European Ancestry| 8,946 individuals |
PGP000248 | Liou L et al. Breast Cancer Res (2021) |Ext. |
Reported Trait: Incident coronary artery disease in individuals with breast cancer | HR: 1.31 [1.19, 1.44] | — | — | Age at diagnosis, genotype array, PCs(1-8), body mass index, smoking, sociodemographic variables, medical variables, oncotherapies | — |
| PPM005187 | PGS001355 (CAD_AnnoPred_PRS) |
PSS003605| European Ancestry| 176,238 individuals |
PGP000252 | Ye Y et al. Circ Genom Precis Med (2021) |
Reported Trait: Coronary artery disease | — | AUROC: 0.6425 | — | Age, sex, PCs(1-10) | — |
| PPM005188 | PGS001356 (AF_AnnoPred_PRS) |
PSS003604| European Ancestry| 178,651 individuals |
PGP000252 | Ye Y et al. Circ Genom Precis Med (2021) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.6321 | — | Age, sex, PCs(1-10) | — |
| PPM002394 | PGS000862 (DR) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.03 [0.96, 1.1] | — | — | PC1-10 | — |
| PPM002396 | PGS000862 (DR) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.09 [1.02, 1.17] | — | — | PC1-10 | — |
| PPM009241 | PGS000013 (GPS_CAD) |
PSS007665| European Ancestry| 1,132 individuals |
PGP000257 | Wells QS et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Coronary artery calcium score > 20 | OR: 1.74 [1.29, 2.36] | AUROC: 0.794 [0.728, 0.84] | — | Age, sex, PCs(1-5) | — |
| PPM009242 | PGS000013 (GPS_CAD) |
PSS007665| European Ancestry| 1,132 individuals |
PGP000257 | Wells QS et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Coronary artery calcium score > 20 | OR: 1.87 [1.41, 2.5] | — | — | — | — |
| PPM009243 | PGS000013 (GPS_CAD) |
PSS007665| European Ancestry| 1,132 individuals |
PGP000257 | Wells QS et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Coronary artery calcium score > 20 | — | AUROC: 0.864 [0.807, 0.904] | C statistic change (vs. no PRS): 0.015 [0.004, 0.028] Integrated discrimination improvement (vs. no PRS): 0.027 [-0.006, 0.054] |
Age, sex, PCs(1-5), systolic blood pressure, total cholesterol, high density lipoprotein cholesterol, triglycerides, current smoker, waist circumference | — |
| PPM009244 | PGS000013 (GPS_CAD) |
PSS007666| European Ancestry| 663 individuals |
PGP000257 | Wells QS et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Coronary artery calcium score > 300 | OR: 1.9 [1.42, 2.54] | AUROC: 0.804 [0.751, 0.845] | — | Age, sex, PCs(1-5) | — |
| PPM009245 | PGS000013 (GPS_CAD) |
PSS007666| European Ancestry| 663 individuals |
PGP000257 | Wells QS et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Coronary artery calcium score > 300 | OR: 2.11 [1.57, 2.83] | — | — | — | — |
| PPM009246 | PGS000013 (GPS_CAD) |
PSS007666| European Ancestry| 663 individuals |
PGP000257 | Wells QS et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Coronary artery calcium score > 300 | — | AUROC: 0.855 [0.805, 0.887] | C statistic change (vs. no PRS): 0.02 [0.001, 0.039] Integrated discrimination improvement (vs. no PRS): 0.039 [0.0005, 0.072] |
Age, sex, PCs(1-5), systolic blood pressure, total cholesterol, high density lipoprotein cholesterol, triglycerides, current smoker, body mass index | — |
| PPM009271 | PGS001779 (BRSprs) |
PSS007680| European Ancestry| 359,017 individuals |
PGP000260 | Barc J et al. Nat Genet (2022) |
Reported Trait: Supraventricular tachycardia | OR: 0.92 [0.89, 0.96] | — | p-value: 4e-05 | — | — |
| PPM015480 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Uterine cancer death | HR: 0.68 [0.46, 1.0] | — | — | — | — |
| PPM007477 | PGS000930 (GBE_BIN_FC3006152) |
PSS003914| African Ancestry| 4,286 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot diagnosed by doctor | — | AUROC: 0.64618 [0.56748, 0.72489] | R²: 0.02826 Incremental AUROC (full-covars): 0.00845 PGS R2 (no covariates): 0.00198 PGS AUROC (no covariates): 0.53535 [0.45318, 0.61752] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007478 | PGS000930 (GBE_BIN_FC3006152) |
PSS003915| East Asian Ancestry| 945 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot diagnosed by doctor | — | AUROC: 0.83468 [0.6451, 1.0] | R²: 0.18847 Incremental AUROC (full-covars): -0.00149 PGS R2 (no covariates): 0.00357 PGS AUROC (no covariates): 0.56702 [0.36049, 0.77355] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007479 | PGS000930 (GBE_BIN_FC3006152) |
PSS003916| European Ancestry| 17,235 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot diagnosed by doctor | — | AUROC: 0.62906 [0.59189, 0.66622] | R²: 0.02094 Incremental AUROC (full-covars): 0.04321 PGS R2 (no covariates): 0.01048 PGS AUROC (no covariates): 0.59654 [0.5564, 0.63667] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007480 | PGS000930 (GBE_BIN_FC3006152) |
PSS003917| South Asian Ancestry| 5,381 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot diagnosed by doctor | — | AUROC: 0.71068 [0.63185, 0.78951] | R²: 0.04649 Incremental AUROC (full-covars): 0.02778 PGS R2 (no covariates): 0.00789 PGS AUROC (no covariates): 0.59225 [0.49685, 0.68766] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007481 | PGS000930 (GBE_BIN_FC3006152) |
PSS003918| European Ancestry| 46,847 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot diagnosed by doctor | — | AUROC: 0.6205 [0.59778, 0.64322] | R²: 0.01789 Incremental AUROC (full-covars): 0.05259 PGS R2 (no covariates): 0.01324 PGS AUROC (no covariates): 0.60274 [0.57915, 0.62633] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007482 | PGS000931 (GBE_BIN_FC11006152) |
PSS003790| African Ancestry| 4,390 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot or DVT diagnosed by doctor | — | AUROC: 0.61925 [0.57619, 0.6623] | R²: 0.02193 Incremental AUROC (full-covars): -0.00229 PGS R2 (no covariates): 0.00035 PGS AUROC (no covariates): 0.50724 [0.46275, 0.55173] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007483 | PGS000931 (GBE_BIN_FC11006152) |
PSS003791| East Asian Ancestry| 952 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot or DVT diagnosed by doctor | — | AUROC: 0.68652 [0.54244, 0.83061] | R²: 0.05141 Incremental AUROC (full-covars): 0.00532 PGS R2 (no covariates): 0.00103 PGS AUROC (no covariates): 0.5328 [0.37688, 0.68873] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007484 | PGS000931 (GBE_BIN_FC11006152) |
PSS003792| European Ancestry| 17,648 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot or DVT diagnosed by doctor | — | AUROC: 0.64786 [0.62647, 0.66925] | R²: 0.03411 Incremental AUROC (full-covars): 0.03737 PGS R2 (no covariates): 0.01507 PGS AUROC (no covariates): 0.59359 [0.57084, 0.61634] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007485 | PGS000931 (GBE_BIN_FC11006152) |
PSS003793| South Asian Ancestry| 5,480 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot or DVT diagnosed by doctor | — | AUROC: 0.63964 [0.59263, 0.68666] | R²: 0.02677 Incremental AUROC (full-covars): 0.01249 PGS R2 (no covariates): 0.00502 PGS AUROC (no covariates): 0.55473 [0.50496, 0.60449] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007486 | PGS000931 (GBE_BIN_FC11006152) |
PSS003794| European Ancestry| 48,060 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot or DVT diagnosed by doctor | — | AUROC: 0.62837 [0.61546, 0.64128] | R²: 0.02953 Incremental AUROC (full-covars): 0.0429 PGS R2 (no covariates): 0.01795 PGS AUROC (no covariates): 0.59176 [0.57816, 0.60536] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007609 | PGS000957 (GBE_HC932) |
PSS004711| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE essential (primary hypertension) | — | AUROC: 0.71865 [0.70527, 0.73203] | R²: 0.17042 Incremental AUROC (full-covars): -0.00133 PGS R2 (no covariates): 0.00389 PGS AUROC (no covariates): 0.53092 [0.51597, 0.54587] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007610 | PGS000957 (GBE_HC932) |
PSS004712| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE essential (primary hypertension) | — | AUROC: 0.7519 [0.72118, 0.78262] | R²: 0.18828 Incremental AUROC (full-covars): 0.01726 PGS R2 (no covariates): 0.02831 PGS AUROC (no covariates): 0.59059 [0.55566, 0.62552] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007611 | PGS000957 (GBE_HC932) |
PSS004713| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE essential (primary hypertension) | — | AUROC: 0.74724 [0.74015, 0.75433] | R²: 0.19436 Incremental AUROC (full-covars): 0.02015 PGS R2 (no covariates): 0.03223 PGS AUROC (no covariates): 0.60027 [0.59183, 0.6087] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007612 | PGS000957 (GBE_HC932) |
PSS004714| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE essential (primary hypertension) | — | AUROC: 0.73072 [0.71892, 0.74253] | R²: 0.19598 Incremental AUROC (full-covars): 0.00857 PGS R2 (no covariates): 0.01913 PGS AUROC (no covariates): 0.56924 [0.55569, 0.58279] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007613 | PGS000957 (GBE_HC932) |
PSS004715| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE essential (primary hypertension) | — | AUROC: 0.72352 [0.71925, 0.72779] | R²: 0.16706 Incremental AUROC (full-covars): 0.02959 PGS R2 (no covariates): 0.04055 PGS AUROC (no covariates): 0.60837 [0.60349, 0.61326] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007614 | PGS000958 (GBE_HC273) |
PSS004403| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Essential hypertension | — | AUROC: 0.72155 [0.708, 0.7351] | R²: 0.17503 Incremental AUROC (full-covars): -0.00192 PGS R2 (no covariates): 0.00286 PGS AUROC (no covariates): 0.52821 [0.51311, 0.54331] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007615 | PGS000958 (GBE_HC273) |
PSS004404| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Essential hypertension | — | AUROC: 0.74478 [0.71204, 0.77751] | R²: 0.16987 Incremental AUROC (full-covars): 0.01358 PGS R2 (no covariates): 0.01557 PGS AUROC (no covariates): 0.56972 [0.5318, 0.60763] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007616 | PGS000958 (GBE_HC273) |
PSS004405| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Essential hypertension | — | AUROC: 0.74583 [0.73846, 0.75319] | R²: 0.1847 Incremental AUROC (full-covars): 0.01683 PGS R2 (no covariates): 0.02709 PGS AUROC (no covariates): 0.59474 [0.58596, 0.60351] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007617 | PGS000958 (GBE_HC273) |
PSS004406| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Essential hypertension | — | AUROC: 0.73161 [0.71966, 0.74357] | R²: 0.19538 Incremental AUROC (full-covars): 0.00693 PGS R2 (no covariates): 0.01804 PGS AUROC (no covariates): 0.56789 [0.55414, 0.58165] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007618 | PGS000958 (GBE_HC273) |
PSS004407| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Essential hypertension | — | AUROC: 0.72364 [0.71923, 0.72805] | R²: 0.16114 Incremental AUROC (full-covars): 0.02564 PGS R2 (no covariates): 0.03436 PGS AUROC (no covariates): 0.60148 [0.5964, 0.60656] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007629 | PGS000961 (GBE_HC987) |
PSS004756| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE phlebitis and thrombophlebitis | — | AUROC: 0.63235 [0.59259, 0.67211] | R²: 0.02507 Incremental AUROC (full-covars): 0.00771 PGS R2 (no covariates): 0.00171 PGS AUROC (no covariates): 0.53507 [0.4917, 0.57844] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007630 | PGS000961 (GBE_HC987) |
PSS004757| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE phlebitis and thrombophlebitis | — | AUROC: 0.66631 [0.52571, 0.80691] | R²: 0.04004 Incremental AUROC (full-covars): -0.006 PGS R2 (no covariates): 4e-05 PGS AUROC (no covariates): 0.50807 [0.37643, 0.63972] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007631 | PGS000961 (GBE_HC987) |
PSS004758| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE phlebitis and thrombophlebitis | — | AUROC: 0.66949 [0.64981, 0.68916] | R²: 0.04365 Incremental AUROC (full-covars): 0.03126 PGS R2 (no covariates): 0.01428 PGS AUROC (no covariates): 0.59647 [0.57489, 0.61804] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007632 | PGS000961 (GBE_HC987) |
PSS004759| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE phlebitis and thrombophlebitis | — | AUROC: 0.63064 [0.58623, 0.67504] | R²: 0.02362 Incremental AUROC (full-covars): 0.00728 PGS R2 (no covariates): 0.0042 PGS AUROC (no covariates): 0.55251 [0.5057, 0.59933] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007633 | PGS000961 (GBE_HC987) |
PSS004760| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE phlebitis and thrombophlebitis | — | AUROC: 0.64191 [0.63056, 0.65326] | R²: 0.03444 Incremental AUROC (full-covars): 0.03745 PGS R2 (no covariates): 0.01698 PGS AUROC (no covariates): 0.58931 [0.57719, 0.60143] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007634 | PGS000962 (GBE_HC942) |
PSS004726| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE chronic ischaemic heart disease | — | AUROC: 0.7358 [0.70724, 0.76436] | R²: 0.09751 Incremental AUROC (full-covars): 0.00137 PGS R2 (no covariates): 0.00275 PGS AUROC (no covariates): 0.53401 [0.49965, 0.56838] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007635 | PGS000962 (GBE_HC942) |
PSS004727| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE chronic ischaemic heart disease | — | AUROC: 0.76843 [0.69891, 0.83795] | R²: 0.12929 Incremental AUROC (full-covars): 0.00772 PGS R2 (no covariates): 0.01452 PGS AUROC (no covariates): 0.60835 [0.52909, 0.68761] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007636 | PGS000962 (GBE_HC942) |
PSS004728| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE chronic ischaemic heart disease | — | AUROC: 0.77959 [0.76878, 0.7904] | R²: 0.1649 Incremental AUROC (full-covars): 0.00919 PGS R2 (no covariates): 0.0145 PGS AUROC (no covariates): 0.58654 [0.57236, 0.60073] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007637 | PGS000962 (GBE_HC942) |
PSS004729| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE chronic ischaemic heart disease | — | AUROC: 0.76819 [0.75382, 0.78257] | R²: 0.19358 Incremental AUROC (full-covars): 0.00859 PGS R2 (no covariates): 0.01217 PGS AUROC (no covariates): 0.56681 [0.54864, 0.58499] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007638 | PGS000962 (GBE_HC942) |
PSS004730| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE chronic ischaemic heart disease | — | AUROC: 0.76113 [0.75467, 0.7676] | R²: 0.14665 Incremental AUROC (full-covars): 0.01428 PGS R2 (no covariates): 0.01869 PGS AUROC (no covariates): 0.59199 [0.58389, 0.60008] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007883 | PGS001024 (GBE_HC61) |
PSS004541| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haemorrhoids / piles | — | AUROC: 0.57317 [0.5447, 0.60164] | R²: 0.01288 Incremental AUROC (full-covars): -0.00092 PGS R2 (no covariates): 0.00035 PGS AUROC (no covariates): 0.50826 [0.48122, 0.53531] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007884 | PGS001024 (GBE_HC61) |
PSS004542| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haemorrhoids / piles | — | AUROC: 0.59643 [0.55346, 0.63941] | R²: 0.02452 Incremental AUROC (full-covars): -0.00644 PGS R2 (no covariates): 0.00062 PGS AUROC (no covariates): 0.48158 [0.43444, 0.52871] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007885 | PGS001024 (GBE_HC61) |
PSS004543| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haemorrhoids / piles | — | AUROC: 0.58423 [0.56992, 0.59855] | R²: 0.01383 Incremental AUROC (full-covars): 0.00316 PGS R2 (no covariates): 0.00067 PGS AUROC (no covariates): 0.51671 [0.50198, 0.53143] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007886 | PGS001024 (GBE_HC61) |
PSS004544| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haemorrhoids / piles | — | AUROC: 0.59907 [0.57631, 0.62183] | R²: 0.01861 Incremental AUROC (full-covars): -0.00302 PGS R2 (no covariates): 0.0 PGS AUROC (no covariates): 0.50215 [0.47847, 0.52583] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007887 | PGS001024 (GBE_HC61) |
PSS004545| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haemorrhoids / piles | — | AUROC: 0.56311 [0.5545, 0.57173] | R²: 0.00825 Incremental AUROC (full-covars): 0.00353 PGS R2 (no covariates): 0.00132 PGS AUROC (no covariates): 0.5223 [0.51348, 0.53112] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007888 | PGS001025 (GBE_HC951) |
PSS004736| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE nonrheumatic aortic valve disorders | — | AUROC: 0.82312 [0.77164, 0.87459] | R²: 0.11205 Incremental AUROC (full-covars): -0.00433 PGS R2 (no covariates): 0.00601 PGS AUROC (no covariates): 0.42408 [0.32798, 0.52019] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007889 | PGS001025 (GBE_HC951) |
PSS004737| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE nonrheumatic aortic valve disorders | — | AUROC: 0.85035 [0.70276, 0.99795] | R²: 0.20912 Incremental AUROC (full-covars): 0.0036 PGS R2 (no covariates): 0.00383 PGS AUROC (no covariates): 0.57568 [0.385, 0.76636] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007890 | PGS001025 (GBE_HC951) |
PSS004738| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE nonrheumatic aortic valve disorders | — | AUROC: 0.7688 [0.74115, 0.79645] | R²: 0.09382 Incremental AUROC (full-covars): 0.00229 PGS R2 (no covariates): 0.00416 PGS AUROC (no covariates): 0.55883 [0.52408, 0.59358] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007891 | PGS001025 (GBE_HC951) |
PSS004739| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE nonrheumatic aortic valve disorders | — | AUROC: 0.7872 [0.73952, 0.83487] | R²: 0.10086 Incremental AUROC (full-covars): 2e-05 PGS R2 (no covariates): 0.00021 PGS AUROC (no covariates): 0.49071 [0.41731, 0.5641] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007892 | PGS001025 (GBE_HC951) |
PSS004740| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE nonrheumatic aortic valve disorders | — | AUROC: 0.72257 [0.70467, 0.74046] | R²: 0.05934 Incremental AUROC (full-covars): 0.00304 PGS R2 (no covariates): 0.00268 PGS AUROC (no covariates): 0.5466 [0.52408, 0.56913] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007998 | PGS001048 (GBE_HC1576) |
PSS004287| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD NSTEMI | — | AUROC: 0.65512 [0.5866, 0.72364] | R²: 0.02925 Incremental AUROC (full-covars): 0.00342 PGS R2 (no covariates): 0.00035 PGS AUROC (no covariates): 0.50799 [0.43141, 0.58457] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007999 | PGS001048 (GBE_HC1576) |
PSS004288| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD NSTEMI | — | AUROC: 0.79982 [0.67861, 0.92103] | R²: 0.1062 Incremental AUROC (full-covars): -0.01024 PGS R2 (no covariates): 0.00383 PGS AUROC (no covariates): 0.43146 [0.20864, 0.65427] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008000 | PGS001048 (GBE_HC1576) |
PSS004289| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD NSTEMI | — | AUROC: 0.7508 [0.72681, 0.77479] | R²: 0.07667 Incremental AUROC (full-covars): 0.00242 PGS R2 (no covariates): 0.00192 PGS AUROC (no covariates): 0.53573 [0.50331, 0.56815] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008001 | PGS001048 (GBE_HC1576) |
PSS004290| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD NSTEMI | — | AUROC: 0.73853 [0.70755, 0.76951] | R²: 0.08258 Incremental AUROC (full-covars): -0.0018 PGS R2 (no covariates): 0.00033 PGS AUROC (no covariates): 0.5125 [0.47119, 0.55382] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008002 | PGS001048 (GBE_HC1576) |
PSS004291| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD NSTEMI | — | AUROC: 0.72145 [0.70591, 0.73699] | R²: 0.06213 Incremental AUROC (full-covars): 0.004 PGS R2 (no covariates): 0.00234 PGS AUROC (no covariates): 0.54042 [0.52208, 0.55876] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008585 | PGS001179 (GBE_HC711) |
PSS004618| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vascular dementia | — | AUROC: 0.89609 [0.78011, 1.0] | R²: 0.23133 Incremental AUROC (full-covars): -0.00271 PGS R2 (no covariates): 0.00098 PGS AUROC (no covariates): 0.45314 [0.26337, 0.6429] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008586 | PGS001179 (GBE_HC711) |
PSS004619| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vascular dementia | — | AUROC: 0.86436 [0.80883, 0.91989] | R²: 0.14328 Incremental AUROC (full-covars): 0.00289 PGS R2 (no covariates): 0.00776 PGS AUROC (no covariates): 0.59245 [0.49395, 0.69095] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008587 | PGS001179 (GBE_HC711) |
PSS004620| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vascular dementia | — | AUROC: 0.83842 [0.72824, 0.9486] | R²: 0.14604 Incremental AUROC (full-covars): 0.00843 PGS R2 (no covariates): 0.0135 PGS AUROC (no covariates): 0.61894 [0.47358, 0.76431] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008588 | PGS001179 (GBE_HC711) |
PSS004621| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vascular dementia | — | AUROC: 0.82562 [0.78593, 0.86531] | R²: 0.10475 Incremental AUROC (full-covars): 0.00707 PGS R2 (no covariates): 0.01123 PGS AUROC (no covariates): 0.61306 [0.55366, 0.67245] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008820 | PGS001263 (GBE_HC440) |
PSS004501| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Atrial flutter | — | AUROC: 0.76033 [0.71757, 0.80309] | R²: 0.10534 Incremental AUROC (full-covars): 0.00055 PGS R2 (no covariates): 0.00351 PGS AUROC (no covariates): 0.54665 [0.4962, 0.5971] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008821 | PGS001263 (GBE_HC440) |
PSS004502| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Atrial flutter | — | AUROC: 0.82631 [0.7516, 0.90103] | R²: 0.15678 Incremental AUROC (full-covars): 0.02031 PGS R2 (no covariates): 0.01354 PGS AUROC (no covariates): 0.59968 [0.4662, 0.73316] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008822 | PGS001263 (GBE_HC440) |
PSS004503| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Atrial flutter | — | AUROC: 0.78179 [0.76842, 0.79516] | R²: 0.1422 Incremental AUROC (full-covars): 0.02171 PGS R2 (no covariates): 0.02517 PGS AUROC (no covariates): 0.61716 [0.59934, 0.63498] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008823 | PGS001263 (GBE_HC440) |
PSS004504| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Atrial flutter | — | AUROC: 0.73743 [0.69955, 0.77531] | R²: 0.09462 Incremental AUROC (full-covars): -0.00059 PGS R2 (no covariates): 0.00793 PGS AUROC (no covariates): 0.57035 [0.52788, 0.61283] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008824 | PGS001263 (GBE_HC440) |
PSS004505| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Atrial flutter | — | AUROC: 0.76368 [0.75572, 0.77165] | R²: 0.12819 Incremental AUROC (full-covars): 0.02207 PGS R2 (no covariates): 0.02215 PGS AUROC (no covariates): 0.60821 [0.59797, 0.61845] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008883 | PGS001277 (GBE_HC203) |
PSS004344| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: PE +/- DVT | — | AUROC: 0.65081 [0.59936, 0.70226] | R²: 0.03099 Incremental AUROC (full-covars): 0.01 PGS R2 (no covariates): 0.00418 PGS AUROC (no covariates): 0.55179 [0.49456, 0.60901] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008884 | PGS001277 (GBE_HC203) |
PSS004345| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: PE +/- DVT | — | AUROC: 0.8083 [0.66236, 0.95424] | R²: 0.12334 Incremental AUROC (full-covars): -0.0014 PGS R2 (no covariates): 0.0 PGS AUROC (no covariates): 0.51341 [0.35575, 0.67107] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008885 | PGS001277 (GBE_HC203) |
PSS004346| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: PE +/- DVT | — | AUROC: 0.67497 [0.64702, 0.70293] | R²: 0.03998 Incremental AUROC (full-covars): 0.03149 PGS R2 (no covariates): 0.01508 PGS AUROC (no covariates): 0.61144 [0.58149, 0.6414] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008886 | PGS001277 (GBE_HC203) |
PSS004347| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: PE +/- DVT | — | AUROC: 0.69135 [0.62082, 0.76187] | R²: 0.03814 Incremental AUROC (full-covars): 0.03509 PGS R2 (no covariates): 0.01582 PGS AUROC (no covariates): 0.63463 [0.5672, 0.70206] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008887 | PGS001277 (GBE_HC203) |
PSS004348| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: PE +/- DVT | — | AUROC: 0.64659 [0.63085, 0.66233] | R²: 0.02867 Incremental AUROC (full-covars): 0.03414 PGS R2 (no covariates): 0.0129 PGS AUROC (no covariates): 0.59812 [0.58116, 0.61507] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008888 | PGS001278 (GBE_BIN_FC12006152) |
PSS003795| African Ancestry| 6,348 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot in the leg (DVT) or lung | — | AUROC: 0.59279 [0.55016, 0.63542] | R²: 0.01242 Incremental AUROC (full-covars): -0.00635 PGS R2 (no covariates): 0.00013 PGS AUROC (no covariates): 0.5015 [0.45729, 0.5457] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008889 | PGS001278 (GBE_BIN_FC12006152) |
PSS003796| East Asian Ancestry| 1,640 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot in the leg (DVT) or lung | — | AUROC: 0.66743 [0.52454, 0.81033] | R²: 0.03638 Incremental AUROC (full-covars): 0.00793 PGS R2 (no covariates): 7e-05 PGS AUROC (no covariates): 0.50497 [0.35161, 0.65832] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008890 | PGS001278 (GBE_BIN_FC12006152) |
PSS003797| European Ancestry| 24,838 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot in the leg (DVT) or lung | — | AUROC: 0.65354 [0.63231, 0.67477] | R²: 0.03366 Incremental AUROC (full-covars): 0.03495 PGS R2 (no covariates): 0.01331 PGS AUROC (no covariates): 0.59164 [0.56886, 0.61442] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008891 | PGS001278 (GBE_BIN_FC12006152) |
PSS003798| South Asian Ancestry| 7,556 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot in the leg (DVT) or lung | — | AUROC: 0.63523 [0.58822, 0.68224] | R²: 0.02321 Incremental AUROC (full-covars): 0.01038 PGS R2 (no covariates): 0.00457 PGS AUROC (no covariates): 0.55523 [0.50541, 0.60504] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008892 | PGS001278 (GBE_BIN_FC12006152) |
PSS003799| European Ancestry| 67,349 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot in the leg (DVT) or lung | — | AUROC: 0.63525 [0.6226, 0.64791] | R²: 0.02918 Incremental AUROC (full-covars): 0.03836 PGS R2 (no covariates): 0.01554 PGS AUROC (no covariates): 0.58956 [0.57602, 0.6031] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008893 | PGS001279 (GBE_BIN_FC8006152) |
PSS004014| African Ancestry| 6,348 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot in the lung | — | AUROC: 0.63917 [0.56071, 0.71763] | R²: 0.02075 Incremental AUROC (full-covars): 0.01133 PGS R2 (no covariates): 0.00182 PGS AUROC (no covariates): 0.53508 [0.45261, 0.61756] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008894 | PGS001279 (GBE_BIN_FC8006152) |
PSS004015| East Asian Ancestry| 1,640 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot in the lung | — | AUROC: 0.82557 [0.62097, 1.0] | R²: 0.16736 Incremental AUROC (full-covars): -0.00024 PGS R2 (no covariates): 0.00388 PGS AUROC (no covariates): 0.57456 [0.37482, 0.77429] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008895 | PGS001279 (GBE_BIN_FC8006152) |
PSS004016| European Ancestry| 24,838 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot in the lung | — | AUROC: 0.62994 [0.59262, 0.66726] | R²: 0.01985 Incremental AUROC (full-covars): 0.03629 PGS R2 (no covariates): 0.00848 PGS AUROC (no covariates): 0.59191 [0.55186, 0.63196] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008896 | PGS001279 (GBE_BIN_FC8006152) |
PSS004017| South Asian Ancestry| 7,556 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot in the lung | — | AUROC: 0.71053 [0.63261, 0.78846] | R²: 0.04621 Incremental AUROC (full-covars): 0.02759 PGS R2 (no covariates): 0.00898 PGS AUROC (no covariates): 0.60144 [0.50751, 0.69537] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008897 | PGS001279 (GBE_BIN_FC8006152) |
PSS004018| European Ancestry| 67,349 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Blood clot in the lung | — | AUROC: 0.62416 [0.60164, 0.64668] | R²: 0.01763 Incremental AUROC (full-covars): 0.04457 PGS R2 (no covariates): 0.01146 PGS AUROC (no covariates): 0.60034 [0.57683, 0.62385] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008898 | PGS001280 (GBE_HC943) |
PSS004731| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE PE | — | AUROC: 0.64593 [0.59381, 0.69806] | R²: 0.02844 Incremental AUROC (full-covars): 0.007 PGS R2 (no covariates): 0.00302 PGS AUROC (no covariates): 0.54566 [0.48787, 0.60344] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008899 | PGS001280 (GBE_HC943) |
PSS004732| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE PE | — | AUROC: 0.80741 [0.66178, 0.95305] | R²: 0.12326 Incremental AUROC (full-covars): -0.00228 PGS R2 (no covariates): 2e-05 PGS AUROC (no covariates): 0.51798 [0.36629, 0.66968] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008900 | PGS001280 (GBE_HC943) |
PSS004733| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE PE | — | AUROC: 0.67617 [0.64866, 0.70368] | R²: 0.04057 Incremental AUROC (full-covars): 0.02926 PGS R2 (no covariates): 0.01403 PGS AUROC (no covariates): 0.60765 [0.57812, 0.63719] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008901 | PGS001280 (GBE_HC943) |
PSS004734| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE PE | — | AUROC: 0.68371 [0.61554, 0.75187] | R²: 0.03438 Incremental AUROC (full-covars): 0.03127 PGS R2 (no covariates): 0.01152 PGS AUROC (no covariates): 0.6164 [0.54879, 0.684] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008902 | PGS001280 (GBE_HC943) |
PSS004735| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE PE | — | AUROC: 0.65102 [0.6355, 0.66654] | R²: 0.03061 Incremental AUROC (full-covars): 0.03417 PGS R2 (no covariates): 0.01357 PGS AUROC (no covariates): 0.59996 [0.58313, 0.61679] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008903 | PGS001281 (GBE_HC86) |
PSS004672| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Migraine | — | AUROC: 0.68314 [0.64175, 0.72454] | R²: 0.04548 Incremental AUROC (full-covars): 0.00141 PGS R2 (no covariates): 7e-05 PGS AUROC (no covariates): 0.51212 [0.4664, 0.55784] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008904 | PGS001281 (GBE_HC86) |
PSS004673| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Migraine | — | AUROC: 0.70929 [0.59332, 0.82526] | Incremental AUROC (full-covars): 0.00197 R²: 0.0907 PGS R2 (no covariates): 0.00054 PGS AUROC (no covariates): 0.51635 [0.40666, 0.62605] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008905 | PGS001281 (GBE_HC86) |
PSS004674| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Migraine | — | AUROC: 0.65031 [0.63271, 0.66791] | R²: 0.03585 Incremental AUROC (full-covars): 0.00524 PGS R2 (no covariates): 0.00376 PGS AUROC (no covariates): 0.54846 [0.52849, 0.56843] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008906 | PGS001281 (GBE_HC86) |
PSS004675| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Migraine | — | AUROC: 0.71746 [0.68326, 0.75166] | R²: 0.07262 Incremental AUROC (full-covars): 0.00414 PGS R2 (no covariates): 0.0051 PGS AUROC (no covariates): 0.55594 [0.51785, 0.59403] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008907 | PGS001281 (GBE_HC86) |
PSS004676| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Migraine | — | AUROC: 0.6514 [0.64118, 0.66162] | R²: 0.03715 Incremental AUROC (full-covars): 0.00474 PGS R2 (no covariates): 0.0025 PGS AUROC (no covariates): 0.53959 [0.52853, 0.55066] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008908 | PGS001282 (GBE_HC815) |
PSS004642| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE migraine | — | AUROC: 0.68512 [0.64613, 0.72411] | PGS R2 (no covariates): 0.00032 R²: 0.04881 Incremental AUROC (full-covars): 0.00144 PGS AUROC (no covariates): 0.5084 [0.46412, 0.55269] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008909 | PGS001282 (GBE_HC815) |
PSS004643| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE migraine | — | AUROC: 0.71233 [0.61741, 0.80724] | R²: 0.08258 Incremental AUROC (full-covars): 0.00023 PGS R2 (no covariates): 3e-05 PGS AUROC (no covariates): 0.49923 [0.40691, 0.59154] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008910 | PGS001282 (GBE_HC815) |
PSS004644| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE migraine | — | AUROC: 0.63835 [0.62244, 0.65426] | R²: 0.03299 Incremental AUROC (full-covars): 0.00984 PGS R2 (no covariates): 0.00527 PGS AUROC (no covariates): 0.55358 [0.53641, 0.57074] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008911 | PGS001282 (GBE_HC815) |
PSS004645| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE migraine | — | AUROC: 0.71231 [0.68018, 0.74443] | R²: 0.07365 Incremental AUROC (full-covars): 0.00305 PGS R2 (no covariates): 0.00344 PGS AUROC (no covariates): 0.54217 [0.50698, 0.57735] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008912 | PGS001282 (GBE_HC815) |
PSS004646| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE migraine | — | AUROC: 0.64859 [0.63934, 0.65784] | R²: 0.03899 Incremental AUROC (full-covars): 0.00619 PGS R2 (no covariates): 0.0031 PGS AUROC (no covariates): 0.5408 [0.53085, 0.55076] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009063 | PGS001314 (GBE_HC938) |
PSS004721| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE acute myocardial infarction | — | AUROC: 0.70154 [0.65456, 0.74852] | R²: 0.05819 Incremental AUROC (full-covars): 0.00259 PGS R2 (no covariates): 0.00375 PGS AUROC (no covariates): 0.54944 [0.49708, 0.6018] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009064 | PGS001314 (GBE_HC938) |
PSS004722| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE acute myocardial infarction | — | AUROC: 0.75783 [0.66508, 0.85058] | R²: 0.11318 Incremental AUROC (full-covars): -0.01214 PGS R2 (no covariates): 4e-05 PGS AUROC (no covariates): 0.50047 [0.38016, 0.62077] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009065 | PGS001314 (GBE_HC938) |
PSS004723| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE acute myocardial infarction | — | AUROC: 0.77705 [0.76156, 0.79255] | R²: 0.12586 Incremental AUROC (full-covars): 0.00931 PGS R2 (no covariates): 0.01217 PGS AUROC (no covariates): 0.59003 [0.56941, 0.61066] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009066 | PGS001314 (GBE_HC938) |
PSS004724| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE acute myocardial infarction | — | AUROC: 0.77134 [0.75168, 0.791] | R²: 0.14992 Incremental AUROC (full-covars): 0.00612 PGS R2 (no covariates): 0.00867 PGS AUROC (no covariates): 0.56612 [0.54027, 0.59198] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009067 | PGS001314 (GBE_HC938) |
PSS004725| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE acute myocardial infarction | — | AUROC: 0.76117 [0.75218, 0.77016] | R²: 0.11781 Incremental AUROC (full-covars): 0.00966 PGS R2 (no covariates): 0.01066 PGS AUROC (no covariates): 0.57977 [0.56827, 0.59127] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009068 | PGS001315 (GBE_HC326) |
PSS004447| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Heart attack (MI) | — | AUROC: 0.69844 [0.6569, 0.73997] | R²: 0.06159 Incremental AUROC (full-covars): -0.00208 PGS R2 (no covariates): 0.00235 PGS AUROC (no covariates): 0.54374 [0.49552, 0.59197] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009069 | PGS001315 (GBE_HC326) |
PSS004448| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Heart attack (MI) | — | AUROC: 0.77737 [0.69516, 0.85958] | R²: 0.12911 Incremental AUROC (full-covars): -0.00257 PGS R2 (no covariates): 0.00655 PGS AUROC (no covariates): 0.55983 [0.43749, 0.68218] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009070 | PGS001315 (GBE_HC326) |
PSS004449| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Heart attack (MI) | — | AUROC: 0.77933 [0.76476, 0.79391] | R²: 0.13255 Incremental AUROC (full-covars): 0.00791 PGS R2 (no covariates): 0.0101 PGS AUROC (no covariates): 0.58124 [0.56203, 0.60045] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009071 | PGS001315 (GBE_HC326) |
PSS004450| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Heart attack (MI) | — | AUROC: 0.76924 [0.75056, 0.78793] | R²: 0.15526 Incremental AUROC (full-covars): 0.00484 PGS R2 (no covariates): 0.00641 PGS AUROC (no covariates): 0.55598 [0.53163, 0.58034] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009072 | PGS001315 (GBE_HC326) |
PSS004451| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Heart attack (MI) | — | AUROC: 0.75834 [0.74967, 0.76701] | R²: 0.11912 Incremental AUROC (full-covars): 0.01051 PGS R2 (no covariates): 0.0122 PGS AUROC (no covariates): 0.58432 [0.57339, 0.59525] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009073 | PGS001316 (GBE_HC1574) |
PSS004282| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD myocardial infarction | — | AUROC: 0.70025 [0.65881, 0.74169] | R²: 0.06323 Incremental AUROC (full-covars): -0.00109 PGS R2 (no covariates): 0.00341 PGS AUROC (no covariates): 0.55032 [0.50157, 0.59907] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009074 | PGS001316 (GBE_HC1574) |
PSS004283| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD myocardial infarction | — | AUROC: 0.77563 [0.69186, 0.85939] | R²: 0.13082 Incremental AUROC (full-covars): -0.00431 PGS R2 (no covariates): 0.00883 PGS AUROC (no covariates): 0.56569 [0.44162, 0.68977] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009075 | PGS001316 (GBE_HC1574) |
PSS004284| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD myocardial infarction | — | AUROC: 0.77999 [0.76527, 0.7947] | R²: 0.13319 Incremental AUROC (full-covars): 0.0073 PGS R2 (no covariates): 0.00977 PGS AUROC (no covariates): 0.57998 [0.56066, 0.59929] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009076 | PGS001316 (GBE_HC1574) |
PSS004285| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD myocardial infarction | — | AUROC: 0.76882 [0.75001, 0.78764] | R²: 0.15463 Incremental AUROC (full-covars): 0.0037 PGS R2 (no covariates): 0.00504 PGS AUROC (no covariates): 0.54779 [0.52311, 0.57248] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009077 | PGS001316 (GBE_HC1574) |
PSS004286| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: AD myocardial infarction | — | AUROC: 0.75963 [0.75098, 0.76829] | R²: 0.12014 Incremental AUROC (full-covars): 0.01074 PGS R2 (no covariates): 0.01247 PGS AUROC (no covariates): 0.58557 [0.57459, 0.59655] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009078 | PGS001317 (GBE_BIN_FC1006150) |
PSS003775| African Ancestry| 3,906 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Vascular/heart problems diagnosed by doctor Heart attack | — | AUROC: 0.72462 [0.66421, 0.78503] | R²: 0.08703 Incremental AUROC (full-covars): -0.01046 PGS R2 (no covariates): 0.0002 PGS AUROC (no covariates): 0.50663 [0.44094, 0.57232] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009079 | PGS001317 (GBE_BIN_FC1006150) |
PSS003776| East Asian Ancestry| 1,308 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Vascular/heart problems diagnosed by doctor Heart attack | — | AUROC: 0.78888 [0.66178, 0.91598] | R²: 0.10419 Incremental AUROC (full-covars): -0.00694 PGS R2 (no covariates): 0.00068 PGS AUROC (no covariates): 0.53242 [0.37336, 0.69148] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009080 | PGS001317 (GBE_BIN_FC1006150) |
PSS003777| European Ancestry| 18,556 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Vascular/heart problems diagnosed by doctor Heart attack | — | AUROC: 0.82479 [0.80685, 0.84274] | R²: 0.1758 Incremental AUROC (full-covars): 0.00552 PGS R2 (no covariates): 0.00895 PGS AUROC (no covariates): 0.5766 [0.55039, 0.60282] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009081 | PGS001317 (GBE_BIN_FC1006150) |
PSS003778| South Asian Ancestry| 5,342 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Vascular/heart problems diagnosed by doctor Heart attack | — | AUROC: 0.82696 [0.80387, 0.85004] | R²: 0.22573 Incremental AUROC (full-covars): 0.00709 PGS R2 (no covariates): 0.00972 PGS AUROC (no covariates): 0.57536 [0.54237, 0.60835] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009082 | PGS001317 (GBE_BIN_FC1006150) |
PSS003779| European Ancestry| 48,989 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Vascular/heart problems diagnosed by doctor Heart attack | — | AUROC: 0.82191 [0.8123, 0.83152] | R²: 0.18282 Incremental AUROC (full-covars): 0.01045 PGS R2 (no covariates): 0.01654 PGS AUROC (no covariates): 0.60058 [0.58663, 0.61453] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009092 | PGS001320 (GBE_HC215) |
PSS004349| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hypertension | — | AUROC: 0.7113 [0.69875, 0.72385] | R²: 0.17724 Incremental AUROC (full-covars): 0.00194 PGS R2 (no covariates): 0.01116 PGS AUROC (no covariates): 0.55174 [0.53775, 0.56573] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009093 | PGS001320 (GBE_HC215) |
PSS004350| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hypertension | — | AUROC: 0.75955 [0.7336, 0.78551] | R²: 0.22552 Incremental AUROC (full-covars): 0.03121 PGS R2 (no covariates): 0.05514 PGS AUROC (no covariates): 0.62221 [0.59228, 0.65214] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009094 | PGS001320 (GBE_HC215) |
PSS004351| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hypertension | — | AUROC: 0.731 [0.72434, 0.73765] | R²: 0.19145 Incremental AUROC (full-covars): 0.03394 PGS R2 (no covariates): 0.05533 PGS AUROC (no covariates): 0.62108 [0.61358, 0.62857] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009095 | PGS001320 (GBE_HC215) |
PSS004352| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hypertension | — | AUROC: 0.73444 [0.72324, 0.74564] | R²: 0.21325 Incremental AUROC (full-covars): 0.02055 PGS R2 (no covariates): 0.03841 PGS AUROC (no covariates): 0.59979 [0.58706, 0.61252] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009096 | PGS001320 (GBE_HC215) |
PSS004353| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Hypertension | — | AUROC: 0.7189 [0.71489, 0.72291] | R²: 0.17852 Incremental AUROC (full-covars): 0.04424 PGS R2 (no covariates): 0.06493 PGS AUROC (no covariates): 0.62908 [0.62467, 0.63349] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009161 | PGS001335 (GBE_BIN_FC4006150) |
PSS003949| African Ancestry| 6,259 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Vascular/heart problems diagnosed by doctor High BP | — | AUROC: 0.70003 [0.68681, 0.71325] | R²: 0.1567 Incremental AUROC (full-covars): 0.00805 PGS R2 (no covariates): 0.0187 PGS AUROC (no covariates): 0.56975 [0.5553, 0.58419] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009162 | PGS001335 (GBE_BIN_FC4006150) |
PSS003950| East Asian Ancestry| 1,636 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Vascular/heart problems diagnosed by doctor High BP | — | AUROC: 0.76033 [0.73318, 0.78748] | R²: 0.20594 Incremental AUROC (full-covars): 0.02832 PGS R2 (no covariates): 0.05248 PGS AUROC (no covariates): 0.61998 [0.5877, 0.65226] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009163 | PGS001335 (GBE_BIN_FC4006150) |
PSS003951| European Ancestry| 24,199 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Vascular/heart problems diagnosed by doctor High BP | — | AUROC: 0.7249 [0.71777, 0.73204] | R²: 0.17206 Incremental AUROC (full-covars): 0.04382 PGS R2 (no covariates): 0.06274 PGS AUROC (no covariates): 0.63418 [0.62624, 0.64212] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009164 | PGS001335 (GBE_BIN_FC4006150) |
PSS003952| South Asian Ancestry| 7,284 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Vascular/heart problems diagnosed by doctor High BP | — | AUROC: 0.72573 [0.71331, 0.73816] | R²: 0.18575 Incremental AUROC (full-covars): 0.02654 PGS R2 (no covariates): 0.04646 PGS AUROC (no covariates): 0.61155 [0.59761, 0.62549] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009165 | PGS001335 (GBE_BIN_FC4006150) |
PSS003953| European Ancestry| 65,564 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Vascular/heart problems diagnosed by doctor High BP | — | AUROC: 0.7135 [0.70921, 0.71779] | R²: 0.16154 Incremental AUROC (full-covars): 0.05215 PGS R2 (no covariates): 0.06872 PGS AUROC (no covariates): 0.63791 [0.63326, 0.64256] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009181 | PGS001339 (GBE_HC964) |
PSS004746| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE atrial fibrillation and flutter | — | AUROC: 0.75135 [0.70951, 0.7932] | R²: 0.09804 Incremental AUROC (full-covars): -0.00345 PGS R2 (no covariates): 0.00273 PGS AUROC (no covariates): 0.53955 [0.48964, 0.58946] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009182 | PGS001339 (GBE_HC964) |
PSS004747| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE atrial fibrillation and flutter | — | AUROC: 0.8247 [0.75141, 0.898] | R²: 0.15451 Incremental AUROC (full-covars): 0.0187 PGS R2 (no covariates): 0.01158 PGS AUROC (no covariates): 0.59663 [0.46689, 0.72636] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009183 | PGS001339 (GBE_HC964) |
PSS004748| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE atrial fibrillation and flutter | — | AUROC: 0.77656 [0.76352, 0.7896] | R²: 0.14023 Incremental AUROC (full-covars): 0.02188 PGS R2 (no covariates): 0.02447 PGS AUROC (no covariates): 0.613 [0.59591, 0.6301] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009184 | PGS001339 (GBE_HC964) |
PSS004749| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE atrial fibrillation and flutter | — | AUROC: 0.73999 [0.70422, 0.77576] | R²: 0.09669 Incremental AUROC (full-covars): -0.00357 PGS R2 (no covariates): 0.00629 PGS AUROC (no covariates): 0.56035 [0.51988, 0.60082] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009185 | PGS001339 (GBE_HC964) |
PSS004750| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE atrial fibrillation and flutter | — | AUROC: 0.76362 [0.75604, 0.7712] | R²: 0.133 Incremental AUROC (full-covars): 0.02354 PGS R2 (no covariates): 0.0246 PGS AUROC (no covariates): 0.6108 [0.60113, 0.62048] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009186 | PGS001340 (GBE_HC281) |
PSS004413| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.75367 [0.71087, 0.79646] | R²: 0.10139 Incremental AUROC (full-covars): -0.00517 PGS R2 (no covariates): 0.00295 PGS AUROC (no covariates): 0.5427 [0.49184, 0.59356] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009187 | PGS001340 (GBE_HC281) |
PSS004414| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.82329 [0.75147, 0.89511] | R²: 0.15391 Incremental AUROC (full-covars): 0.01729 PGS R2 (no covariates): 0.01132 PGS AUROC (no covariates): 0.5932 [0.45826, 0.72815] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009188 | PGS001340 (GBE_HC281) |
PSS004415| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.77562 [0.76201, 0.78924] | R²: 0.13687 Incremental AUROC (full-covars): 0.02036 PGS R2 (no covariates): 0.02331 PGS AUROC (no covariates): 0.61305 [0.59537, 0.63074] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009189 | PGS001340 (GBE_HC281) |
PSS004416| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.73506 [0.69832, 0.7718] | R²: 0.09299 Incremental AUROC (full-covars): -0.00714 PGS R2 (no covariates): 0.00594 PGS AUROC (no covariates): 0.56086 [0.51842, 0.60331] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009190 | PGS001340 (GBE_HC281) |
PSS004417| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.76157 [0.75368, 0.76945] | R²: 0.12768 Incremental AUROC (full-covars): 0.02194 PGS R2 (no covariates): 0.02239 PGS AUROC (no covariates): 0.60727 [0.59722, 0.61733] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009452 | PGS001819 (portability-PLR_250.7) |
PSS009289| European Ancestry| 19,330 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0366 [0.0226, 0.0507] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009453 | PGS001819 (portability-PLR_250.7) |
PSS009063| European Ancestry| 4,032 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0638 [0.033, 0.0946] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009454 | PGS001819 (portability-PLR_250.7) |
PSS008617| European Ancestry| 6,465 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0315 [0.0071, 0.0559] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009455 | PGS001819 (portability-PLR_250.7) |
PSS008393| Greater Middle Eastern Ancestry| 1,162 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0471 [-0.1048, 0.011] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009456 | PGS001819 (portability-PLR_250.7) |
PSS008171| South Asian Ancestry| 6,081 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0325 [0.0074, 0.0577] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009457 | PGS001819 (portability-PLR_250.7) |
PSS007958| East Asian Ancestry| 1,764 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0249 [-0.0718, 0.022] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009594 | PGS001838 (portability-PLR_401) |
PSS009310| European Ancestry| 20,000 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1882 [0.1748, 0.2016] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009595 | PGS001838 (portability-PLR_401) |
PSS009084| European Ancestry| 4,136 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1633 [0.1334, 0.1929] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009596 | PGS001838 (portability-PLR_401) |
PSS008638| European Ancestry| 6,660 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.157 [0.1335, 0.1804] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009598 | PGS001838 (portability-PLR_401) |
PSS008192| South Asian Ancestry| 6,331 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1567 [0.1326, 0.1807] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009599 | PGS001838 (portability-PLR_401) |
PSS007974| East Asian Ancestry| 1,810 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1165 [0.0706, 0.162] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009600 | PGS001838 (portability-PLR_401) |
PSS007757| African Ancestry| 2,484 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1101 [0.071, 0.149] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009601 | PGS001838 (portability-PLR_401) |
PSS008861| African Ancestry| 3,924 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.0682 [0.0369, 0.0993] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009602 | PGS001839 (portability-PLR_411.4) |
PSS009311| European Ancestry| 19,308 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.1021 [0.0881, 0.1161] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009603 | PGS001839 (portability-PLR_411.4) |
PSS009085| European Ancestry| 4,021 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.1391 [0.1086, 0.1693] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009604 | PGS001839 (portability-PLR_411.4) |
PSS008639| European Ancestry| 6,492 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.0994 [0.0753, 0.1235] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009605 | PGS001839 (portability-PLR_411.4) |
PSS008413| Greater Middle Eastern Ancestry| 1,158 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.0815 [0.0235, 0.1389] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009607 | PGS001839 (portability-PLR_411.4) |
PSS007975| East Asian Ancestry| 1,794 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.0452 [-0.0014, 0.0915] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009608 | PGS001839 (portability-PLR_411.4) |
PSS007758| African Ancestry| 2,396 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.0269 [-0.0133, 0.067] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009609 | PGS001839 (portability-PLR_411.4) |
PSS008862| African Ancestry| 3,793 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.0157 [-0.0163, 0.0475] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009610 | PGS001840 (portability-PLR_415) |
PSS009312| European Ancestry| 19,808 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.0355 [0.0216, 0.0494] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009611 | PGS001840 (portability-PLR_415) |
PSS009086| European Ancestry| 4,113 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.0647 [0.0341, 0.0952] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009612 | PGS001840 (portability-PLR_415) |
PSS008640| European Ancestry| 6,617 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.038 [0.0139, 0.0621] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009613 | PGS001840 (portability-PLR_415) |
PSS008414| Greater Middle Eastern Ancestry| 1,190 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): -0.0071 [-0.0643, 0.0503] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009614 | PGS001840 (portability-PLR_415) |
PSS008194| South Asian Ancestry| 6,283 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.03 [0.0052, 0.0547] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009615 | PGS001840 (portability-PLR_415) |
PSS007976| East Asian Ancestry| 1,805 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.0109 [-0.0355, 0.0572] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009616 | PGS001840 (portability-PLR_415) |
PSS007759| African Ancestry| 2,457 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.0171 [-0.0226, 0.0568] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009617 | PGS001840 (portability-PLR_415) |
PSS008863| African Ancestry| 3,858 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.0366 [0.005, 0.0682] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009619 | PGS001841 (portability-PLR_427.2) |
PSS009087| European Ancestry| 3,980 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.0701 [0.039, 0.101] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009620 | PGS001841 (portability-PLR_427.2) |
PSS008641| European Ancestry| 6,397 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.0741 [0.0496, 0.0984] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009621 | PGS001841 (portability-PLR_427.2) |
PSS008415| Greater Middle Eastern Ancestry| 1,151 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.091 [0.0329, 0.1485] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009622 | PGS001841 (portability-PLR_427.2) |
PSS008195| South Asian Ancestry| 6,001 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.0436 [0.0182, 0.0688] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009623 | PGS001841 (portability-PLR_427.2) |
PSS007977| East Asian Ancestry| 1,768 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.0317 [-0.0153, 0.0784] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009624 | PGS001841 (portability-PLR_427.2) |
PSS007760| African Ancestry| 2,381 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.0464 [0.0061, 0.0866] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009625 | PGS001841 (portability-PLR_427.2) |
PSS008864| African Ancestry| 3,769 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.0414 [0.0094, 0.0733] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009626 | PGS001842 (portability-PLR_428) |
PSS009314| European Ancestry| 19,961 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0293 [0.0154, 0.0432] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009627 | PGS001842 (portability-PLR_428) |
PSS009088| European Ancestry| 4,128 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0213 [-0.0093, 0.0519] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009628 | PGS001842 (portability-PLR_428) |
PSS008642| European Ancestry| 6,648 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0227 [-0.0014, 0.0467] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009629 | PGS001842 (portability-PLR_428) |
PSS008416| Greater Middle Eastern Ancestry| 1,197 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0369 [-0.0203, 0.0938] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009631 | PGS001842 (portability-PLR_428) |
PSS007978| East Asian Ancestry| 1,808 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0692 [0.023, 0.1152] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009632 | PGS001842 (portability-PLR_428) |
PSS007761| African Ancestry| 2,472 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0218 [-0.0178, 0.0613] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009633 | PGS001842 (portability-PLR_428) |
PSS008865| African Ancestry| 3,905 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): -0.0133 [-0.0447, 0.0182] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009634 | PGS001843 (portability-PLR_443.9) |
PSS009318| European Ancestry| 19,668 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): 0.0151 [0.0011, 0.029] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009636 | PGS001843 (portability-PLR_443.9) |
PSS008646| European Ancestry| 6,566 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): 0.0229 [-0.0013, 0.0471] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009637 | PGS001843 (portability-PLR_443.9) |
PSS008420| Greater Middle Eastern Ancestry| 1,189 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): -0.0194 [-0.0766, 0.038] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009638 | PGS001843 (portability-PLR_443.9) |
PSS008200| South Asian Ancestry| 6,258 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): 0.0011 [-0.0237, 0.0259] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009640 | PGS001843 (portability-PLR_443.9) |
PSS007765| African Ancestry| 2,444 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): -0.0417 [-0.0814, -0.0019] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009641 | PGS001843 (portability-PLR_443.9) |
PSS008869| African Ancestry| 3,878 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): 0.0129 [-0.0186, 0.0445] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009642 | PGS001844 (portability-PLR_451) |
PSS009319| European Ancestry| 18,164 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): 0.0525 [0.038, 0.067] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009643 | PGS001844 (portability-PLR_451) |
PSS009093| European Ancestry| 3,734 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): 0.068 [0.036, 0.1] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009644 | PGS001844 (portability-PLR_451) |
PSS008647| European Ancestry| 6,014 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): 0.0468 [0.0215, 0.072] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009645 | PGS001844 (portability-PLR_451) |
PSS008421| Greater Middle Eastern Ancestry| 1,102 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): 0.0855 [0.0261, 0.1444] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009646 | PGS001844 (portability-PLR_451) |
PSS008201| South Asian Ancestry| 5,719 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): 0.0329 [0.0069, 0.0588] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009647 | PGS001844 (portability-PLR_451) |
PSS007983| East Asian Ancestry| 1,622 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): -0.0182 [-0.0671, 0.0308] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009648 | PGS001844 (portability-PLR_451) |
PSS007766| African Ancestry| 2,283 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): 0.0073 [-0.0339, 0.0485] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009649 | PGS001844 (portability-PLR_451) |
PSS008870| African Ancestry| 3,611 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): -0.0032 [-0.0359, 0.0295] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009658 | PGS001846 (portability-PLR_455) |
PSS009321| European Ancestry| 19,218 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.0438 [0.0297, 0.0579] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009659 | PGS001846 (portability-PLR_455) |
PSS009095| European Ancestry| 3,955 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.03 [-0.0013, 0.0612] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009660 | PGS001846 (portability-PLR_455) |
PSS008649| European Ancestry| 6,440 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.0317 [0.0073, 0.0561] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009661 | PGS001846 (portability-PLR_455) |
PSS008423| Greater Middle Eastern Ancestry| 1,179 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.0421 [-0.0155, 0.0995] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009662 | PGS001846 (portability-PLR_455) |
PSS008203| South Asian Ancestry| 6,161 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.0213 [-0.0037, 0.0463] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009663 | PGS001846 (portability-PLR_455) |
PSS007985| East Asian Ancestry| 1,785 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.0326 [-0.0141, 0.0791] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009664 | PGS001846 (portability-PLR_455) |
PSS007768| African Ancestry| 2,423 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): -0.0211 [-0.061, 0.0189] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009665 | PGS001846 (portability-PLR_455) |
PSS008872| African Ancestry| 3,828 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.002 [-0.0298, 0.0337] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009667 | PGS001847 (portability-PLR_459.9) |
PSS009096| European Ancestry| 4,066 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0326 [0.0018, 0.0634] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009668 | PGS001847 (portability-PLR_459.9) |
PSS008650| European Ancestry| 6,570 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0229 [-0.0013, 0.0471] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009669 | PGS001847 (portability-PLR_459.9) |
PSS008424| Greater Middle Eastern Ancestry| 1,182 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): -0.0084 [-0.0659, 0.0491] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009670 | PGS001847 (portability-PLR_459.9) |
PSS008204| South Asian Ancestry| 6,220 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0091 [-0.0158, 0.0339] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009671 | PGS001847 (portability-PLR_459.9) |
PSS007986| East Asian Ancestry| 1,790 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0149 [-0.0317, 0.0614] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009672 | PGS001847 (portability-PLR_459.9) |
PSS007769| African Ancestry| 2,467 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): -0.0097 [-0.0493, 0.03] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009673 | PGS001847 (portability-PLR_459.9) |
PSS008873| African Ancestry| 3,882 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.003 [-0.0285, 0.0345] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011090 | PGS002027 (portability-ldpred2_250.7) |
PSS009289| European Ancestry| 19,330 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0451 [0.031, 0.0592] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011091 | PGS002027 (portability-ldpred2_250.7) |
PSS009063| European Ancestry| 4,032 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0607 [0.0298, 0.0915] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011092 | PGS002027 (portability-ldpred2_250.7) |
PSS008617| European Ancestry| 6,465 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0241 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011093 | PGS002027 (portability-ldpred2_250.7) |
PSS008393| Greater Middle Eastern Ancestry| 1,162 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0311 [-0.0889, 0.027] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011094 | PGS002027 (portability-ldpred2_250.7) |
PSS008171| South Asian Ancestry| 6,081 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0351 [0.01, 0.0603] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011095 | PGS002027 (portability-ldpred2_250.7) |
PSS007958| East Asian Ancestry| 1,764 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0302 [-0.077, 0.0168] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011096 | PGS002027 (portability-ldpred2_250.7) |
PSS007739| African Ancestry| 2,385 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0204 [-0.0606, 0.0199] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011238 | PGS002047 (portability-ldpred2_401) |
PSS009310| European Ancestry| 20,000 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1966 [0.1832, 0.2099] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011239 | PGS002047 (portability-ldpred2_401) |
PSS009084| European Ancestry| 4,136 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1843 [0.1546, 0.2137] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011241 | PGS002047 (portability-ldpred2_401) |
PSS008412| Greater Middle Eastern Ancestry| 1,200 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1675 [0.1115, 0.2224] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011242 | PGS002047 (portability-ldpred2_401) |
PSS008192| South Asian Ancestry| 6,331 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1679 [0.1438, 0.1917] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011243 | PGS002047 (portability-ldpred2_401) |
PSS007974| East Asian Ancestry| 1,810 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1101 [0.0641, 0.1556] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011244 | PGS002047 (portability-ldpred2_401) |
PSS007757| African Ancestry| 2,484 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.0996 [0.0603, 0.1385] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011245 | PGS002047 (portability-ldpred2_401) |
PSS008861| African Ancestry| 3,924 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.0804 [0.0492, 0.1115] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011246 | PGS002048 (portability-ldpred2_411.4) |
PSS009311| European Ancestry| 19,308 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.1078 [0.0938, 0.1217] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011247 | PGS002048 (portability-ldpred2_411.4) |
PSS009085| European Ancestry| 4,021 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.1435 [0.113, 0.1737] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011248 | PGS002048 (portability-ldpred2_411.4) |
PSS008639| European Ancestry| 6,492 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.1061 [0.0819, 0.1301] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011250 | PGS002048 (portability-ldpred2_411.4) |
PSS008193| South Asian Ancestry| 6,070 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.1246 [0.0997, 0.1493] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011251 | PGS002048 (portability-ldpred2_411.4) |
PSS007975| East Asian Ancestry| 1,794 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.0522 [0.0057, 0.0985] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011252 | PGS002048 (portability-ldpred2_411.4) |
PSS007758| African Ancestry| 2,396 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.0358 [-0.0044, 0.0759] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011253 | PGS002048 (portability-ldpred2_411.4) |
PSS008862| African Ancestry| 3,793 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.01 [-0.0219, 0.0419] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011254 | PGS002049 (portability-ldpred2_415) |
PSS009312| European Ancestry| 19,808 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.0397 [0.0258, 0.0536] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011255 | PGS002049 (portability-ldpred2_415) |
PSS009086| European Ancestry| 4,113 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.0663 [0.0357, 0.0967] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011256 | PGS002049 (portability-ldpred2_415) |
PSS008640| European Ancestry| 6,617 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.0336 [0.0095, 0.0577] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011257 | PGS002049 (portability-ldpred2_415) |
PSS008414| Greater Middle Eastern Ancestry| 1,190 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): -0.0019 [-0.0592, 0.0554] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011258 | PGS002049 (portability-ldpred2_415) |
PSS008194| South Asian Ancestry| 6,283 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.0331 [0.0083, 0.0578] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011259 | PGS002049 (portability-ldpred2_415) |
PSS007976| East Asian Ancestry| 1,805 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.0075 [-0.0389, 0.0539] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011260 | PGS002049 (portability-ldpred2_415) |
PSS007759| African Ancestry| 2,457 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.014 [-0.0257, 0.0537] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011261 | PGS002049 (portability-ldpred2_415) |
PSS008863| African Ancestry| 3,858 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Pulmonary heart disease | — | — | Partial Correlation (partial-r): 0.0322 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011263 | PGS002050 (portability-ldpred2_427.2) |
PSS009087| European Ancestry| 3,980 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.0689 [0.0379, 0.0999] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011264 | PGS002050 (portability-ldpred2_427.2) |
PSS008641| European Ancestry| 6,397 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.0839 [0.0594, 0.1082] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011265 | PGS002050 (portability-ldpred2_427.2) |
PSS008415| Greater Middle Eastern Ancestry| 1,151 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.0983 [0.0402, 0.1557] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011266 | PGS002050 (portability-ldpred2_427.2) |
PSS008195| South Asian Ancestry| 6,001 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.043 [0.0177, 0.0683] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011267 | PGS002050 (portability-ldpred2_427.2) |
PSS007977| East Asian Ancestry| 1,768 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.041 [-0.0059, 0.0877] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011268 | PGS002050 (portability-ldpred2_427.2) |
PSS007760| African Ancestry| 2,381 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.0475 [0.0072, 0.0877] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011269 | PGS002050 (portability-ldpred2_427.2) |
PSS008864| African Ancestry| 3,769 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.0418 [0.0098, 0.0737] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011270 | PGS002051 (portability-ldpred2_428) |
PSS009314| European Ancestry| 19,961 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0235 [0.0097, 0.0374] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011271 | PGS002051 (portability-ldpred2_428) |
PSS009088| European Ancestry| 4,128 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0368 [0.0062, 0.0673] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011272 | PGS002051 (portability-ldpred2_428) |
PSS008642| European Ancestry| 6,648 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0327 [0.0086, 0.0567] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011274 | PGS002051 (portability-ldpred2_428) |
PSS008196| South Asian Ancestry| 6,294 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0021 [-0.0226, 0.0269] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011275 | PGS002051 (portability-ldpred2_428) |
PSS007978| East Asian Ancestry| 1,808 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0376 [-0.0087, 0.0838] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011276 | PGS002051 (portability-ldpred2_428) |
PSS007761| African Ancestry| 2,472 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.025 [-0.0146, 0.0645] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011277 | PGS002051 (portability-ldpred2_428) |
PSS008865| African Ancestry| 3,905 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0121 [-0.0193, 0.0436] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011278 | PGS002052 (portability-ldpred2_433.1) |
PSS009316| European Ancestry| 19,445 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0199 [0.0058, 0.034] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011279 | PGS002052 (portability-ldpred2_433.1) |
PSS009090| European Ancestry| 4,046 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0001 [-0.0308, 0.031] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011280 | PGS002052 (portability-ldpred2_433.1) |
PSS008644| European Ancestry| 6,521 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0191 [-0.0052, 0.0434] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011282 | PGS002052 (portability-ldpred2_433.1) |
PSS008198| South Asian Ancestry| 6,173 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0003 [-0.0247, 0.0253] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011283 | PGS002052 (portability-ldpred2_433.1) |
PSS007980| East Asian Ancestry| 1,789 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): -0.0132 [-0.0598, 0.0334] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011284 | PGS002052 (portability-ldpred2_433.1) |
PSS007763| African Ancestry| 2,407 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0003 [-0.0398, 0.0404] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011285 | PGS002052 (portability-ldpred2_433.1) |
PSS008867| African Ancestry| 3,806 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): 0.0054 [-0.0265, 0.0372] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011286 | PGS002053 (portability-ldpred2_433) |
PSS009315| European Ancestry| 19,915 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0233 [0.0094, 0.0371] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011287 | PGS002053 (portability-ldpred2_433) |
PSS009089| European Ancestry| 4,121 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0114 [-0.0193, 0.042] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011288 | PGS002053 (portability-ldpred2_433) |
PSS008643| European Ancestry| 6,641 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0244 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011289 | PGS002053 (portability-ldpred2_433) |
PSS008417| Greater Middle Eastern Ancestry| 1,198 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0536 [-0.0036, 0.1103] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011290 | PGS002053 (portability-ldpred2_433) |
PSS008197| South Asian Ancestry| 6,308 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0165 [-0.0082, 0.0412] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011291 | PGS002053 (portability-ldpred2_433) |
PSS007979| East Asian Ancestry| 1,804 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0131 [-0.0333, 0.0595] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011293 | PGS002053 (portability-ldpred2_433) |
PSS008866| African Ancestry| 3,912 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0287 [-0.0027, 0.0601] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011294 | PGS002054 (portability-ldpred2_442.11) |
PSS009317| European Ancestry| 19,545 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Abdominal aortic aneurysm | — | — | Partial Correlation (partial-r): 0.0144 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011295 | PGS002054 (portability-ldpred2_442.11) |
PSS009091| European Ancestry| 4,042 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Abdominal aortic aneurysm | — | — | Partial Correlation (partial-r): 0.0382 [0.0073, 0.069] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011296 | PGS002054 (portability-ldpred2_442.11) |
PSS008645| European Ancestry| 6,542 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Abdominal aortic aneurysm | — | — | Partial Correlation (partial-r): 0.0139 [-0.0104, 0.0382] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011297 | PGS002054 (portability-ldpred2_442.11) |
PSS008419| Greater Middle Eastern Ancestry| 1,183 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Abdominal aortic aneurysm | — | — | Partial Correlation (partial-r): 0.0222 [-0.0354, 0.0795] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011298 | PGS002054 (portability-ldpred2_442.11) |
PSS008199| South Asian Ancestry| 6,205 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Abdominal aortic aneurysm | — | — | Partial Correlation (partial-r): 0.0007 [-0.0243, 0.0256] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011299 | PGS002054 (portability-ldpred2_442.11) |
PSS007981| East Asian Ancestry| 1,791 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Abdominal aortic aneurysm | — | — | Partial Correlation (partial-r): 0.025 [-0.0216, 0.0715] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011300 | PGS002054 (portability-ldpred2_442.11) |
PSS007764| African Ancestry| 2,435 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Abdominal aortic aneurysm | — | — | Partial Correlation (partial-r): 0.0069 [-0.033, 0.0468] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011301 | PGS002054 (portability-ldpred2_442.11) |
PSS008868| African Ancestry| 3,861 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Abdominal aortic aneurysm | — | — | Partial Correlation (partial-r): -0.0158 [-0.0474, 0.0158] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011302 | PGS002055 (portability-ldpred2_443.9) |
PSS009318| European Ancestry| 19,668 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): 0.0175 [0.0035, 0.0315] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011304 | PGS002055 (portability-ldpred2_443.9) |
PSS008646| European Ancestry| 6,566 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): 0.0261 [0.0018, 0.0503] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011305 | PGS002055 (portability-ldpred2_443.9) |
PSS008420| Greater Middle Eastern Ancestry| 1,189 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): -0.0296 [-0.0868, 0.0278] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011306 | PGS002055 (portability-ldpred2_443.9) |
PSS008200| South Asian Ancestry| 6,258 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): 0.0061 [-0.0187, 0.0309] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011307 | PGS002055 (portability-ldpred2_443.9) |
PSS007982| East Asian Ancestry| 1,794 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): -0.0276 [-0.074, 0.019] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011308 | PGS002055 (portability-ldpred2_443.9) |
PSS007765| African Ancestry| 2,444 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): -0.0324 [-0.0721, 0.0074] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011309 | PGS002055 (portability-ldpred2_443.9) |
PSS008869| African Ancestry| 3,878 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): 0.0345 [0.003, 0.066] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011310 | PGS002056 (portability-ldpred2_451) |
PSS009319| European Ancestry| 18,164 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): 0.0561 [0.0416, 0.0706] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011311 | PGS002056 (portability-ldpred2_451) |
PSS009093| European Ancestry| 3,734 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): 0.0729 [0.0408, 0.1048] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011312 | PGS002056 (portability-ldpred2_451) |
PSS008647| European Ancestry| 6,014 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): 0.0469 [0.0216, 0.0722] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011313 | PGS002056 (portability-ldpred2_451) |
PSS008421| Greater Middle Eastern Ancestry| 1,102 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): 0.085 [0.0256, 0.1439] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011314 | PGS002056 (portability-ldpred2_451) |
PSS008201| South Asian Ancestry| 5,719 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): 0.0284 [0.0025, 0.0543] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011315 | PGS002056 (portability-ldpred2_451) |
PSS007983| East Asian Ancestry| 1,622 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): -0.0188 [-0.0677, 0.0302] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011316 | PGS002056 (portability-ldpred2_451) |
PSS007766| African Ancestry| 2,283 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): -0.001 [-0.0422, 0.0402] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011317 | PGS002056 (portability-ldpred2_451) |
PSS008870| African Ancestry| 3,611 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Phlebitis and thrombophlebitis | — | — | Partial Correlation (partial-r): -0.0043 [-0.037, 0.0284] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011326 | PGS002058 (portability-ldpred2_455) |
PSS009321| European Ancestry| 19,218 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.0589 [0.0448, 0.073] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011327 | PGS002058 (portability-ldpred2_455) |
PSS009095| European Ancestry| 3,955 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.062 [0.0308, 0.0931] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011328 | PGS002058 (portability-ldpred2_455) |
PSS008649| European Ancestry| 6,440 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.0553 [0.0309, 0.0797] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011329 | PGS002058 (portability-ldpred2_455) |
PSS008423| Greater Middle Eastern Ancestry| 1,179 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): -0.001 [-0.0586, 0.0565] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011331 | PGS002058 (portability-ldpred2_455) |
PSS007985| East Asian Ancestry| 1,785 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.0713 [0.0247, 0.1175] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011332 | PGS002058 (portability-ldpred2_455) |
PSS007768| African Ancestry| 2,423 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.0085 [-0.0315, 0.0485] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011333 | PGS002058 (portability-ldpred2_455) |
PSS008872| African Ancestry| 3,828 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.042 [0.0103, 0.0737] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011334 | PGS002059 (portability-ldpred2_459.9) |
PSS009322| European Ancestry| 19,705 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0497 [0.0358, 0.0636] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011335 | PGS002059 (portability-ldpred2_459.9) |
PSS009096| European Ancestry| 4,066 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0288 [-0.002, 0.0596] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011336 | PGS002059 (portability-ldpred2_459.9) |
PSS008650| European Ancestry| 6,570 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0323 [0.0081, 0.0565] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011337 | PGS002059 (portability-ldpred2_459.9) |
PSS008424| Greater Middle Eastern Ancestry| 1,182 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): -0.0502 [-0.1074, 0.0073] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011339 | PGS002059 (portability-ldpred2_459.9) |
PSS007986| East Asian Ancestry| 1,790 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0257 [-0.0209, 0.0722] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011340 | PGS002059 (portability-ldpred2_459.9) |
PSS007769| African Ancestry| 2,467 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0063 [-0.0333, 0.0459] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012709 | PGS002235 (elasticnet_VTE) |
PSS009500| European Ancestry| 269,164 individuals |
PGP000267 | Kolin DA et al. Sci Rep (2021) |
Reported Trait: Incident venous thromboembolism | — | — | Odds Ratio (OR, top 1% vs bottom 99%): 5.37 [5.34, 5.4] | — | — |
| PPM012710 | PGS002235 (elasticnet_VTE) |
PSS009500| European Ancestry| 269,164 individuals |
PGP000267 | Kolin DA et al. Sci Rep (2021) |
Reported Trait: Incident venous thromboembolism | — | — | Subhazard ratio (SHR, top 20.2% vs bottom 79.8%): 3.02 [2.63, 3.47] | — | — |
| PPM012711 | PGS002235 (elasticnet_VTE) |
PSS009500| European Ancestry| 269,164 individuals |
PGP000267 | Kolin DA et al. Sci Rep (2021) |
Reported Trait: Incident venous thromboembolism | — | — | Subhazard ratio (SHR, top 20.2% vs bottom 79.8%): 7.51 [6.28, 8.98] | — | — |
| PPM009459 | PGS001819 (portability-PLR_250.7) |
PSS008842| African Ancestry| 3,732 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0089 [-0.0233, 0.041] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009458 | PGS001819 (portability-PLR_250.7) |
PSS007739| African Ancestry| 2,385 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0193 [-0.0596, 0.021] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009597 | PGS001838 (portability-PLR_401) |
PSS008412| Greater Middle Eastern Ancestry| 1,200 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1797 [0.1239, 0.2344] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009606 | PGS001839 (portability-PLR_411.4) |
PSS008193| South Asian Ancestry| 6,070 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.1113 [0.0863, 0.1361] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009618 | PGS001841 (portability-PLR_427.2) |
PSS009313| European Ancestry| 19,230 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.1026 [0.0885, 0.1165] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009630 | PGS001842 (portability-PLR_428) |
PSS008196| South Asian Ancestry| 6,294 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): 0.0004 [-0.0244, 0.0251] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009635 | PGS001843 (portability-PLR_443.9) |
PSS009092| European Ancestry| 4,063 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): 0.0365 [0.0057, 0.0672] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009639 | PGS001843 (portability-PLR_443.9) |
PSS007982| East Asian Ancestry| 1,794 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): -0.0031 [-0.0496, 0.0434] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009666 | PGS001847 (portability-PLR_459.9) |
PSS009322| European Ancestry| 19,705 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0405 [0.0266, 0.0545] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011097 | PGS002027 (portability-ldpred2_250.7) |
PSS008842| African Ancestry| 3,732 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0062 [-0.0259, 0.0384] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011240 | PGS002047 (portability-ldpred2_401) |
PSS008638| European Ancestry| 6,660 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | — | — | Partial Correlation (partial-r): 0.1669 [0.1434, 0.1902] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011249 | PGS002048 (portability-ldpred2_411.4) |
PSS008413| Greater Middle Eastern Ancestry| 1,158 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Coronary atherosclerosis | — | — | Partial Correlation (partial-r): 0.0727 [0.0146, 0.1302] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011262 | PGS002050 (portability-ldpred2_427.2) |
PSS009313| European Ancestry| 19,230 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation and flutter | — | — | Partial Correlation (partial-r): 0.1034 [0.0894, 0.1174] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011273 | PGS002051 (portability-ldpred2_428) |
PSS008416| Greater Middle Eastern Ancestry| 1,197 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | — | — | Partial Correlation (partial-r): -0.0001 [-0.0572, 0.0571] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011281 | PGS002052 (portability-ldpred2_433.1) |
PSS008418| Greater Middle Eastern Ancestry| 1,183 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Occlusion and stenosis of precerebral arteries | — | — | Partial Correlation (partial-r): -0.0093 [-0.0667, 0.0482] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011292 | PGS002053 (portability-ldpred2_433) |
PSS007762| African Ancestry| 2,470 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Cerebrovascular disease | — | — | Partial Correlation (partial-r): 0.0139 [-0.0257, 0.0535] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011303 | PGS002055 (portability-ldpred2_443.9) |
PSS009092| European Ancestry| 4,063 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Peripheral vascular disease, unspecified | — | — | Partial Correlation (partial-r): 0.011 [-0.0198, 0.0418] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011330 | PGS002058 (portability-ldpred2_455) |
PSS008203| South Asian Ancestry| 6,161 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Hemorrhoids | — | — | Partial Correlation (partial-r): 0.057 [0.032, 0.0819] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011338 | PGS002059 (portability-ldpred2_459.9) |
PSS008204| South Asian Ancestry| 6,220 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0197 [-0.0052, 0.0446] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011341 | PGS002059 (portability-ldpred2_459.9) |
PSS008873| African Ancestry| 3,882 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Circulatory disease NEC | — | — | Partial Correlation (partial-r): 0.0041 [-0.0275, 0.0356] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009270 | PGS001779 (BRSprs) |
PSS007675| European Ancestry| 359,017 individuals |
PGP000260 | Barc J et al. Nat Genet (2022) |
Reported Trait: Conduction system disorder orbradyarrhythmia | OR: 1.06 [1.03, 1.08] | — | p-value: 4.63e-06 | — | — |
| PPM009272 | PGS001779 (BRSprs) |
PSS007676| European Ancestry| 11,942 individuals |
PGP000260 | Barc J et al. Nat Genet (2022) |
Reported Trait: PQ interval | β: 2.69866 | — | p-value: 1.90e-45 | — | — |
| PPM012736 | PGS002244 (ldpred_cad) |
PSS009517| European Ancestry| 110,597 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Coronary artery disease | OR: 1.47 [1.43, 1.52] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012740 | PGS002244 (ldpred_cad) |
PSS009513| East Asian Ancestry| 178,726 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Coronary artery disease | OR: 1.32 [1.3, 1.34] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012744 | PGS002244 (ldpred_cad) |
PSS009525| European Ancestry| 69,422 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Coronary artery disease | OR: 1.44 [1.4, 1.48] | — | — | birth year, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012752 | PGS002244 (ldpred_cad) |
PSS009529| African Ancestry| 1,535 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Coronary artery disease | OR: 1.1 [0.96, 1.26] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012756 | PGS002244 (ldpred_cad) |
PSS009541| European Ancestry| 343,676 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Coronary artery disease | OR: 1.64 [1.61, 1.67] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012761 | PGS002244 (ldpred_cad) |
PSS009537| African Ancestry| 7,618 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Coronary artery disease | OR: 1.32 [1.13, 1.54] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012766 | PGS002244 (ldpred_cad) |
PSS009545| South Asian Ancestry| 7,628 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Coronary artery disease | OR: 1.41 [1.3, 1.53] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM009273 | PGS001779 (BRSprs) |
PSS007677| European Ancestry| 11,566 individuals |
PGP000260 | Barc J et al. Nat Genet (2022) |
Reported Trait: P wave duration | β: 0.7576 | — | p-value: 5.32e-09 | — | — |
| PPM012880 | PGS000013 (GPS_CAD) |
PSS009590| Multi-ancestry (including European)| 5,152 individuals |
PGP000290 | Mordi IR et al. Diabetes Care (2022) |Ext. |
Reported Trait: Incident major adverse cardiovascular events in type 2 diabetes | HR: 1.68 [1.49, 1.9] | — | — | Age, sex, glycated hemoglobin, duration of diabetes, retinal risk score, and PCE | — |
| PPM009286 | PGS001780 (CHD_PRSCS) |
PSS007689| European Ancestry| 343,672 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Prevalent coronary heart disease | OR: 1.77 [1.73, 1.8] | AUROC: 0.811 [0.808, 0.815] | — | year of birth, sex | — |
| PPM009276 | PGS001780 (CHD_PRSCS) |
PSS007681| European Ancestry| 309,154 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.56 [1.53, 1.58] | AUROC: 0.871 [0.869, 0.873] | — | year of birth, sex, ten first principal components of Finnish ancestry, batch, genotyping array | — |
| PPM012881 | PGS000013 (GPS_CAD) |
PSS009590| Multi-ancestry (including European)| 5,152 individuals |
PGP000290 | Mordi IR et al. Diabetes Care (2022) |Ext. |
Reported Trait: Incident major adverse cardiovascular events in type 2 diabetes | — | AUROC: 0.686 [0.667, 0.704] | — | Retinal risk score, age, sex | — |
| PPM009274 | PGS001779 (BRSprs) |
PSS007678| European Ancestry| 11,877 individuals |
PGP000260 | Barc J et al. Nat Genet (2022) |
Reported Trait: QRS complex duration | β: 1.23043 | — | p-value: 4.21e-55 | — | — |
| PPM009278 | PGS001780 (CHD_PRSCS) |
PSS007687| European Ancestry| 343,672 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.72 [1.7, 1.75] | AUROC: 0.792 [0.789, 0.795] | — | year of birth, sex | — |
| PPM009282 | PGS001780 (CHD_PRSCS) |
PSS007688| European Ancestry| 332,370 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Incident coronary heart disease | OR: 1.61 [1.57, 1.65] | AUROC: 0.756 [0.751, 0.761] | — | year of birth, sex | — |
| PPM009284 | PGS001780 (CHD_PRSCS) |
PSS007683| European Ancestry| 309,154 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Prevalent coronary heart disease | OR: 1.59 [1.57, 1.62] | AUROC: 0.869 [0.867, 0.871] | — | year of birth, sex, ten first principal components of Finnish ancestry, batch, genotyping array | — |
| PPM009280 | PGS001780 (CHD_PRSCS) |
PSS007682| European Ancestry| 291,720 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Incident coronary heart disease | OR: 1.44 [1.41, 1.47] | AUROC: 0.913 [0.911, 0.916] | — | year of birth, sex, ten first principal components of Finnish ancestry, batch, genotyping array | — |
| PPM012867 | PGS002259 (metaPRS_Stroke) |
PSS009585| East Asian Ancestry| 41,006 individuals |
PGP000285 | Lu X et al. Neurology (2021) |
Reported Trait: Incident stroke | HR: 1.28 [1.21, 1.36] | — | Hazard Ratio (HR, highest vs lowest quintile): 1.99 [1.66, 2.38] | Sex | — |
| PPM012868 | PGS002259 (metaPRS_Stroke) |
PSS009585| East Asian Ancestry| 41,006 individuals |
PGP000285 | Lu X et al. Neurology (2021) |
Reported Trait: Incident ischemic stroke | HR: 1.29 [1.2, 1.39] | — | Hazard Ratio (HR, highest vs lowest quintile): 2.13 [1.69, 2.69] | Sex | — |
| PPM012869 | PGS002259 (metaPRS_Stroke) |
PSS009585| East Asian Ancestry| 41,006 individuals |
PGP000285 | Lu X et al. Neurology (2021) |
Reported Trait: Incident hemorrhagic stroke | HR: 1.3 [1.17, 1.45] | — | Hazard Ratio (HR, highest vs lowest quintile): 1.98 [1.41, 2.77] | Sex | — |
| PPM012875 | PGS002262 (metaPRS_CAD) |
PSS009589| East Asian Ancestry| 41,271 individuals |
PGP000289 | Lu X et al. Eur Heart J (2022) |
Reported Trait: Incident coronary artery disease | HR: 1.44 [1.36, 1.52] | C-index: 0.615 [0.598, 0.631] | — | — | — |
| PPM012876 | PGS002262 (metaPRS_CAD) |
PSS009589| East Asian Ancestry| 41,271 individuals |
PGP000289 | Lu X et al. Eur Heart J (2022) |
Reported Trait: Incident coronary artery disease | — | — | Hazard Ratio (HR, highest vs lowest quintile): 2.91 [2.43, 3.49] | — | — |
| PPM012877 | PGS002262 (metaPRS_CAD) |
PSS009589| East Asian Ancestry| 41,271 individuals |
PGP000289 | Lu X et al. Eur Heart J (2022) |
Reported Trait: Incident coronary artery disease (men) | — | — | Hazard Ratio (HR, highest vs lowest quintile): 3.88 [2.94, 5.13] | sex and first 4 PCs | — |
| PPM012878 | PGS002262 (metaPRS_CAD) |
PSS009589| East Asian Ancestry| 41,271 individuals |
PGP000289 | Lu X et al. Eur Heart J (2022) |
Reported Trait: Incident coronary artery disease (women) | — | — | Hazard Ratio (HR, highest vs lowest quintile): 2.27 [1.78, 2.9] | sex and first 4 PCs | — |
| PPM012879 | PGS002262 (metaPRS_CAD) |
PSS009589| East Asian Ancestry| 41,271 individuals |
PGP000289 | Lu X et al. Eur Heart J (2022) |
Reported Trait: Coronary artery disease | — | — | Hazard Ratio (HR, highest vs lowest quintile): 5.66 [3.98, 8.04] | sex, first 4 PCs and CAD family history | — |
| PPM009268 | PGS001779 (BRSprs) |
PSS007671| European Ancestry| 359,017 individuals |
PGP000260 | Barc J et al. Nat Genet (2022) |
Reported Trait: Atrial fibrillation or flutter | OR: 0.94 [0.92, 0.95] | — | p-value: 6.22e-13 | — | — |
| PPM009269 | PGS001779 (BRSprs) |
PSS007672| European Ancestry| 359,017 individuals |
PGP000260 | Barc J et al. Nat Genet (2022) |
Reported Trait: Atrioventricular conduction disorder | OR: 1.16 [1.1, 1.21] | — | p-value: 1.47e-09 | — | — |
| PPM009275 | PGS001779 (BRSprs) |
PSS007679| European Ancestry| 11,893 individuals |
PGP000260 | Barc J et al. Nat Genet (2022) |
Reported Trait: QT interval | β: -1.56242 | — | p-value: 4.75e-16 | — | — |
| PPM009266 | PGS001779 (BRSprs) |
PSS007673| European Ancestry| 2,469 individuals |
PGP000260 | Barc J et al. Nat Genet (2022) |
Reported Trait: SCN5A Mutation in Burgada syndrome cases | β: -0.45 | — | p-value: 2.10e-17 | — | — |
| PPM009267 | PGS001779 (BRSprs) |
PSS007674| European Ancestry| 2,820 individuals |
PGP000260 | Barc J et al. Nat Genet (2022) |
Reported Trait: Brugada baseline or drug-induced type 1 ECG in Burgada syndrome cases | β: 0.18 | — | p-value: 2e-05 | — | — |
| PPM012925 | PGS002271 (PRS_MVP) |
PSS009620| European Ancestry| 393,229 individuals |
PGP000301 | Roselli C et al. Eur Heart J (2022) |
Reported Trait: Risk of mitral valve prolapse | — | AUROC: 0.6614 [0.641, 0.6819] | — | Age, sex | — |
| PPM013025 | PGS002296 (PRS2166_HT) |
PSS009654| European Ancestry| 2,244 individuals |
PGP000326 | Maj C et al. Front Cardiovasc Med (2022) |
Reported Trait: Hypertension | OR: 3.22 [2.06, 5.1] | — | — | — | — |
| PPM014736 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009879| European Ancestry| 403,489 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: incident ischemic stroke cases | HR: 1.19 [1.16, 1.21] | C-index: 0.645 | ∆C-index (improvement in C-index over covariates-only model): 0.01 | age, sex, 5 PCs | — |
| PPM012924 | PGS002271 (PRS_MVP) |
PSS009620| European Ancestry| 393,229 individuals |
PGP000301 | Roselli C et al. Eur Heart J (2022) |
Reported Trait: Risk of mitral valve prolapse | — | AUROC: 0.6772 [0.6563, 0.6982] | — | Age, sex, hypertension, all-cause heart failure, myocardial infarction, and diabetes (Type 1 and Type 2)] | — |
| PPM014747 | PGS002725 (GIGASTROKE_iPGS_EAS) |
PSS009881| East Asian Ancestry| 87,682 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: prevalent ischemic stroke cases | OR: 1.18 [1.12, 1.25] | AUROC: 0.765 | ∆AUROC (improvement in AUROC over covariates-only model): 0.003 | age, sex, 5 PCs | — |
| PPM012732 | PGS002244 (ldpred_cad) |
PSS009521| European Ancestry| 258,402 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Coronary artery disease | OR: 1.53 [1.5, 1.55] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012748 | PGS002244 (ldpred_cad) |
PSS009533| European Ancestry| 25,696 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Coronary artery disease | OR: 1.35 [1.29, 1.4] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM015478 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Brain cancer death | HR: 0.71 [0.52, 0.97] | — | — | — | — |
| PPM012951 | PGS000010 (GRS27) |
PSS009630| European Ancestry| 4,932 individuals |
PGP000306 | Thompson PL et al. BMC Cardiovasc Disord (2022) |Ext. |
Reported Trait: Reccurent cardiovascular event (coronary heart disease death, non-fatal myocardial infraction, unstable angina pectoris, coronary artery bypass graft and Percutaneous coronary intervention) | — | C-index: 0.7 | NRI (GRS-added vs. baseline model): 0.097 | Hypertension, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, diabetes, sex, age, current smoking | Basline model C-index = 0.69 |
| PPM012987 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009641| European Ancestry| 3,071 individuals |
PGP000315 | Hämmerle M et al. Stroke (2022) |Ext. |
Reported Trait: Stroke | — | — | Odds ratio (OR, top 1% vs. rest): 5.82 [2.08, 14.0] | Age, sex, BMI, hypertension, cholesterol, diabetes, smoker | — |
| PPM015479 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Pneumonia death | HR: 1.14 [1.0, 1.3] | — | — | — | — |
| PPM017150 | PGS003438 (PRS241_CAD) |
PSS010137| European Ancestry| 330,201 individuals |
PGP000440 | Marston NA et al. JAMA Cardiol (2023) |
Reported Trait: Myocardial infarction | HR: 1.07 [1.06, 1.08] | — | — | — | — |
| PPM017151 | PGS003438 (PRS241_CAD) |
PSS010137| European Ancestry| 330,201 individuals |
PGP000440 | Marston NA et al. JAMA Cardiol (2023) |
Reported Trait: Myocardial infarction in >60 years | HR: 1.42 [1.37, 1.48] | — | — | — | — |
| PPM017152 | PGS003438 (PRS241_CAD) |
PSS010137| European Ancestry| 330,201 individuals |
PGP000440 | Marston NA et al. JAMA Cardiol (2023) |
Reported Trait: Myocardial infarction in aged 50-60 years | HR: 1.46 [1.38, 1.53] | — | — | — | — |
| PPM017153 | PGS003438 (PRS241_CAD) |
PSS010137| European Ancestry| 330,201 individuals |
PGP000440 | Marston NA et al. JAMA Cardiol (2023) |
Reported Trait: Myocardial infarction in < 50 years | HR: 1.72 [1.56, 1.89] | — | — | — | — |
| PPM017154 | PGS003438 (PRS241_CAD) |
PSS010137| European Ancestry| 330,201 individuals |
PGP000440 | Marston NA et al. JAMA Cardiol (2023) |
Reported Trait: Atherosclerotic Cardiovascular Disease (ASCVD) events | — | C-index: 0.74 [0.73, 0.74] | — | — | — |
| PPM017155 | PGS003438 (PRS241_CAD) |
PSS010137| European Ancestry| 330,201 individuals |
PGP000440 | Marston NA et al. JAMA Cardiol (2023) |
Reported Trait: Atherosclerotic Cardiovascular Disease (ASCVD) events in >60 years | — | C-index: 0.68 [0.67, 0.69] | — | — | — |
| PPM017156 | PGS003438 (PRS241_CAD) |
PSS010137| European Ancestry| 330,201 individuals |
PGP000440 | Marston NA et al. JAMA Cardiol (2023) |
Reported Trait: Atherosclerotic Cardiovascular Disease (ASCVD) events in aged 50-60 years | — | C-index: 0.71 [0.7, 0.73] | — | — | — |
| PPM017157 | PGS003438 (PRS241_CAD) |
PSS010137| European Ancestry| 330,201 individuals |
PGP000440 | Marston NA et al. JAMA Cardiol (2023) |
Reported Trait: Atherosclerotic Cardiovascular Disease (ASCVD) events in < 50 years | — | C-index: 0.76 [0.73, 0.78] | — | — | — |
| PPM009310 | PGS001796 (1kgeur_gbmi_leaveUKBBout_VTE_pst_eff_a1_b0.5_phiauto) |
PSS007700| African Ancestry| 6,137 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Venous thromboembolism | — | AUROC: 0.672 | Nagelkerke's R2 (covariates regressed out): 0.00488 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM017186 | PGS003446 (TEM_CAD_PRS) |
PSS010158| African Ancestry| 17,072 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |
Reported Trait: Coronary artery disease | OR: 1.21 [1.15, 1.28] | — | — | — | — |
| PPM017187 | PGS003446 (TEM_CAD_PRS) |
PSS010159| Hispanic or Latin American Ancestry| 6,314 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |
Reported Trait: Coronary artery disease | OR: 1.43 [1.27, 1.61] | — | — | — | — |
| PPM017189 | PGS000013 (GPS_CAD) |
PSS010161| Hispanic or Latin American Ancestry| 30,648 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization | OR: 1.52 [1.45, 1.59] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017190 | PGS000013 (GPS_CAD) |
PSS010160| African Ancestry| 76,709 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization | OR: 1.17 [1.14, 1.21] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017191 | PGS000013 (GPS_CAD) |
PSS010162| European Ancestry| 292,438 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.36 [1.35, 1.37] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017192 | PGS000013 (GPS_CAD) |
PSS010161| Hispanic or Latin American Ancestry| 30,648 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.32 [1.28, 1.36] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017193 | PGS000013 (GPS_CAD) |
PSS010160| African Ancestry| 76,709 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.1 [1.08, 1.12] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017194 | PGS000013 (GPS_CAD) |
PSS010162| European Ancestry| 292,438 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization in incident coronary artery disease | OR: 1.46 [1.43, 1.49] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017196 | PGS000013 (GPS_CAD) |
PSS010160| African Ancestry| 76,709 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization in incident coronary artery disease | OR: 1.15 [1.1, 1.2] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017197 | PGS000013 (GPS_CAD) |
PSS010162| European Ancestry| 292,438 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Incident coronary artery disease | OR: 1.26 [1.24, 1.28] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017198 | PGS000013 (GPS_CAD) |
PSS010161| Hispanic or Latin American Ancestry| 30,648 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Incident coronary artery disease | OR: 1.22 [1.15, 1.29] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017199 | PGS000013 (GPS_CAD) |
PSS010160| African Ancestry| 76,709 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Incident coronary artery disease | OR: 1.1 [1.07, 1.14] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017200 | PGS000018 (metaGRS_CAD) |
PSS010162| European Ancestry| 292,438 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization | OR: 1.54 [1.52, 1.56] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017201 | PGS000018 (metaGRS_CAD) |
PSS010161| Hispanic or Latin American Ancestry| 30,648 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization | OR: 1.62 [1.54, 1.71] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017202 | PGS000018 (metaGRS_CAD) |
PSS010160| African Ancestry| 76,709 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization | OR: 1.2 [1.17, 1.2] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017203 | PGS000018 (metaGRS_CAD) |
PSS010162| European Ancestry| 292,438 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.38 [1.36, 1.39] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017204 | PGS000018 (metaGRS_CAD) |
PSS010161| Hispanic or Latin American Ancestry| 30,648 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.39 [1.34, 1.43] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017205 | PGS000018 (metaGRS_CAD) |
PSS010160| African Ancestry| 76,709 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.12 [1.1, 1.14] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017206 | PGS000018 (metaGRS_CAD) |
PSS010162| European Ancestry| 292,438 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization in incident coronary artery disease | OR: 1.47 [1.44, 1.5] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017207 | PGS000018 (metaGRS_CAD) |
PSS010161| Hispanic or Latin American Ancestry| 30,648 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization in incident coronary artery disease | OR: 1.5 [1.38, 1.63] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017208 | PGS000018 (metaGRS_CAD) |
PSS010160| African Ancestry| 76,709 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization in incident coronary artery disease | OR: 1.17 [1.12, 1.22] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017209 | PGS000018 (metaGRS_CAD) |
PSS010162| European Ancestry| 292,438 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Incident coronary artery disease | OR: 1.27 [1.25, 1.29] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017210 | PGS000018 (metaGRS_CAD) |
PSS010161| Hispanic or Latin American Ancestry| 30,648 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Incident coronary artery disease | OR: 1.24 [1.17, 1.32] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017211 | PGS000018 (metaGRS_CAD) |
PSS010160| African Ancestry| 76,709 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Incident coronary artery disease | OR: 1.1 [1.07, 1.14] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM014904 | PGS000013 (GPS_CAD) |
PSS009922| European Ancestry| 2,119 individuals |
PGP000353 | Sapkota Y et al. JACC CardioOncol (2022) |Ext. |
Reported Trait: Coronary artery disease in childhood cancer survivors | HR: 1.25 [1.04, 1.49] | — | — | — | — |
| PPM014905 | PGS000013 (GPS_CAD) |
PSS009922| European Ancestry| 2,119 individuals |
PGP000353 | Sapkota Y et al. JACC CardioOncol (2022) |Ext. |
Reported Trait: Coronary artery disease in childhood cancer survivors aged <10 years at diagnosis and treated with >25 Gy | — | AUROC: 0.714 | Hazard Ratio (HR, top vs. bottom tertile): 15.49 [5.24, 45.52] | — | — |
| PPM009294 | PGS001790 (1kgeur_gbmi_leaveUKBBout_HF_pst_eff_a1_b0.5_phiauto) |
PSS007713| European Ancestry| 358,905 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Heart Failure | — | AUROC: 0.75 | Nagelkerke's R2 (covariates regressed out): 0.00698 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM009300 | PGS001796 (1kgeur_gbmi_leaveUKBBout_VTE_pst_eff_a1_b0.5_phiauto) |
PSS007719| European Ancestry| 356,269 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Venous thromboembolism | — | AUROC: 0.675 | Nagelkerke's R2 (covariates regressed out): 0.02221 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM009306 | PGS001793 (1kgeur_gbmi_leaveUKBBout_Stroke_pst_eff_a1_b0.5_phiauto) |
PSS007705| Additional Asian Ancestries| 8,091 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Stroke | — | AUROC: 0.745 | Nagelkerke's R2 (covariates regressed out): 0.01187 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM009314 | PGS001798 (1kgeur_gbmi_Stroke_pst_eff_a1_b0.5_phiauto) |
PSS007696| European Ancestry| 7,128 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Stroke | — | AUROC: 0.704 | Nagelkerke's R2 (covariates regressed out): 0.00746 | sex,age, 20PCs | — |
| PPM009297 | PGS001793 (1kgeur_gbmi_leaveUKBBout_Stroke_pst_eff_a1_b0.5_phiauto) |
PSS007716| European Ancestry| 350,408 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Stroke | — | AUROC: 0.706 | Nagelkerke's R2 (covariates regressed out): 0.00278 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM009288 | PGS001784 (1kgeur_gbmi_leaveUKBBout_AAA_pst_eff_a1_b0.5_phiauto) |
PSS007707| European Ancestry| 350,767 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Abdominal aortic aneurysm | — | AUROC: 0.868 | Nagelkerke's R2 (covariates regressed out): 0.01466 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM015476 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Cerebrovascular death | HR: 1.11 [1.03, 1.2] | — | — | — | — |
| PPM014973 | PGS002773 (GTG_AF_maxCT) |
PSS009940| European Ancestry| 12,306 individuals |
PGP000365 | Wong CK et al. PLoS One (2022) |
Reported Trait: Incident atrial fibrillation | OR: 1.41 [1.35, 1.48] | AUROC: 0.599 [0.585, 0.613] | — | — | — |
| PPM014974 | PGS002774 (GTG_AF_SCT) |
PSS009940| European Ancestry| 12,306 individuals |
PGP000365 | Wong CK et al. PLoS One (2022) |
Reported Trait: Incident atrial fibrillation | OR: 1.49 [1.42, 1.57] | AUROC: 0.613 [0.599, 0.626] | — | — | — |
| PPM014975 | PGS002775 (GTG_CAD_maxCT) |
PSS009941| European Ancestry| 16,374 individuals |
PGP000365 | Wong CK et al. PLoS One (2022) |
Reported Trait: Incident coronary artery disease | OR: 1.29 [1.24, 1.35] | AUROC: 0.572 [0.56, 0.584] | — | — | — |
| PPM014976 | PGS002776 (GTG_CAD_SCT) |
PSS009941| European Ancestry| 16,374 individuals |
PGP000365 | Wong CK et al. PLoS One (2022) |
Reported Trait: Incident coronary artery disease | OR: 1.36 [1.31, 1.42] | AUROC: 0.587 [0.576, 0.599] | — | — | — |
| PPM014977 | PGS002777 (GTG_Hypertension_maxCT) |
PSS009942| European Ancestry| 21,970 individuals |
PGP000365 | Wong CK et al. PLoS One (2022) |
Reported Trait: Incident hypertension | OR: 1.23 [1.18, 1.27] | AUROC: 0.559 [0.55, 0.569] | — | — | — |
| PPM014978 | PGS002778 (GTG_Hypertension_SCT) |
PSS009942| European Ancestry| 21,970 individuals |
PGP000365 | Wong CK et al. PLoS One (2022) |
Reported Trait: Incident hypertension | OR: 1.26 [1.22, 1.3] | AUROC: 0.566 [0.556, 0.576] | — | — | — |
| PPM014990 | PGS000043 (PRS_VTE) |
PSS009948| Multi-ancestry (including European)| 615,967 individuals |
PGP000369 | Jaworek T et al. Neurology (2022) |Ext. |
Reported Trait: Early onset stroke | OR: 1.13 [1.1, 1.16] | — | — | 10 principal components for ancestry and sex | — |
| PPM014737 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009879| European Ancestry| 403,489 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: incident ischemic stroke cases | HR: 1.13 [1.1, 1.15] | C-index: 0.64 | ∆C-index (improvement in C-index over covariates-only model): 0.006 | age, sex, 5 PCs | — |
| PPM014738 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009876| European Ancestry| 51,288 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: incident ischemic stroke cases | HR: 1.19 [1.11, 1.27] | C-index: 0.644 | ∆C-index (improvement in C-index over covariates-only model): 0.008 | age, sex, 5 PCs | — |
| PPM014739 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009876| European Ancestry| 51,288 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: incident ischemic stroke cases | HR: 1.14 [1.06, 1.21] | C-index: 0.641 | ∆C-index (improvement in C-index over covariates-only model): 0.006 | age, sex, 5 PCs | — |
| PPM014740 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009878| African Ancestry| 107,343 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: incident ischemic stroke cases | HR: 1.11 [1.06, 1.17] | C-index: 0.653 | ∆C-index (improvement in C-index over covariates-only model): 0.003 | age, sex, 5 PCs | — |
| PPM014741 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009878| African Ancestry| 107,343 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: incident ischemic stroke cases | HR: 1.09 [1.04, 1.14] | C-index: 0.652 | ∆C-index (improvement in C-index over covariates-only model): 0.002 | age, sex, 5 PCs | — |
| PPM014742 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009880| African Ancestry| 3,434 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: prevalent ischemic stroke cases | OR: 1.09 [1.02, 1.17] | AUROC: 0.548 | ∆AUROC (improvement in AUROC over covariates-only model): 0.007 | age, sex, 5 PCs | — |
| PPM014744 | PGS002725 (GIGASTROKE_iPGS_EAS) |
PSS009875| East Asian Ancestry| 41,929 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: prevalent ischemic stroke cases | OR: 1.33 [1.26, 1.4] | AUROC: 0.653 | ∆AUROC (improvement in AUROC over covariates-only model): 0.019 | age, sex, 5 PCs | — |
| PPM014745 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009875| East Asian Ancestry| 41,929 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: prevalent ischemic stroke cases | OR: 1.18 [1.12, 1.25] | AUROC: 0.643 | ∆AUROC (improvement in AUROC over covariates-only model): 0.009 | age, sex, 5 PCs | — |
| PPM014748 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009881| East Asian Ancestry| 87,682 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: prevalent ischemic stroke cases | OR: 1.1 [1.04, 1.16] | AUROC: 0.763 | ∆AUROC (improvement in AUROC over covariates-only model): 0.001 | age, sex, 5 PCs | — |
| PPM014988 | PGS000016 (GPS_AF) |
PSS009946| European Ancestry| 36,662 individuals |
PGP000368 | Marston NA et al. Eur Heart J (2022) |Ext. |
Reported Trait: Atrial fibrillation | HR: 1.4 [1.32, 1.49] | — | — | — | — |
| PPM014989 | PGS000016 (GPS_AF) |
PSS009947| Multi-ancestry (excluding European)| 4,873 individuals |
PGP000368 | Marston NA et al. Eur Heart J (2022) |Ext. |
Reported Trait: Atrial fibrillation | HR: 2.15 [1.57, 2.95] | — | — | — | — |
| PPM015477 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Dementia death | HR: 1.11 [1.02, 1.21] | — | — | — | — |
| PPM014991 | PGS000043 (PRS_VTE) |
PSS009948| Multi-ancestry (including European)| 615,967 individuals |
PGP000369 | Jaworek T et al. Neurology (2022) |Ext. |
Reported Trait: Late onset stroke | OR: 1.04 [1.01, 1.08] | — | — | 10 principal components for ancestry and sex | — |
| PPM014734 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS009877| European Ancestry| 102,099 individuals |
PGP000333 | Mishra A et al. Nature (2022) |
Reported Trait: incident ischemic stroke cases | HR: 1.26 [1.19, 1.34] | C-index: 0.631 | ∆C-index (improvement in C-index over covariates-only model): 0.027 | age, sex, 5 PCs | — |
| PPM014735 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009877| European Ancestry| 102,099 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: incident ischemic stroke cases | HR: 1.19 [1.12, 1.26] | C-index: 0.618 | ∆C-index (improvement in C-index over covariates-only model): 0.014 | age, sex, 5 PCs | — |
| PPM014743 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009880| African Ancestry| 3,434 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: prevalent ischemic stroke cases | OR: 1.07 [1.0, 1.15] | AUROC: 0.547 | ∆AUROC (improvement in AUROC over covariates-only model): 0.006 | age, sex, 5 PCs | — |
| PPM014746 | PGS000039 (metaGRS_ischaemicstroke) |
PSS009875| East Asian Ancestry| 41,929 individuals |
PGP000333 | Mishra A et al. Nature (2022) |Ext. |
Reported Trait: prevalent ischemic stroke cases | OR: 1.17 [1.11, 1.23] | AUROC: 0.641 | ∆AUROC (improvement in AUROC over covariates-only model): 0.007 | age, sex, 5 PCs | — |
| PPM015454 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Self-reported family history of myocardial infarction | OR: 1.16 [1.13, 1.2] | — | — | — | — |
| PPM015455 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Self-reported family history of stroke | OR: 1.07 [1.04, 1.11] | — | — | — | — |
| PPM015456 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Self-reported history of breast cancer | OR: 0.81 [0.69, 0.95] | — | — | — | — |
| PPM015457 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Self-reported history of non-melanoma skin cancer | OR: 0.93 [0.89, 0.98] | — | — | — | — |
| PPM015458 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Self-reported family history of colon cancer | OR: 0.95 [0.91, 0.99] | — | — | — | — |
| PPM015459 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Self-reported history of colonoscopy | OR: 0.96 [0.93, 0.99] | — | — | — | — |
| PPM015461 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident PTCA | OR: 1.53 [1.43, 1.63] | — | — | Smoking status, self-reported diabetes at baseline, systolic blood pressure, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol | — |
| PPM015462 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident myocardial infarction | OR: 1.41 [1.32, 1.5] | — | — | Smoking status, self-reported diabetes at baseline, systolic blood pressure, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol | — |
| PPM015463 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident coronary heart disease | OR: 1.31 [1.23, 1.38] | — | — | Smoking status, self-reported diabetes at baseline, systolic blood pressure, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol | — |
| PPM015464 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident CABG | OR: 1.53 [1.39, 1.7] | — | — | Smoking status, self-reported diabetes at baseline, systolic blood pressure, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol | — |
| PPM015465 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident all angina | OR: 1.38 [1.26, 1.51] | — | — | Smoking status, self-reported diabetes at baseline, systolic blood pressure, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol | — |
| PPM015466 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident ischemic stroke | OR: 1.11 [1.04, 1.19] | — | — | Smoking status, self-reported diabetes at baseline, systolic blood pressure, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol | — |
| PPM015467 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident all stroke | OR: 1.09 [1.03, 1.16] | — | — | Smoking status, self-reported diabetes at baseline, systolic blood pressure, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol | — |
| PPM015468 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident TIA | OR: 1.21 [1.04, 1.41] | — | — | Smoking status, self-reported diabetes at baseline, systolic blood pressure, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol | — |
| PPM015469 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident peripheral artery disease | OR: 1.16 [1.01, 1.32] | — | — | Smoking status, self-reported diabetes at baseline, systolic blood pressure, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol | — |
| PPM015470 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident carotid disease | OR: 1.14 [1.0, 1.3] | — | — | Smoking status, self-reported diabetes at baseline, systolic blood pressure, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol | — |
| PPM015471 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident any cancer | OR: 0.96 [0.93, 0.99] | — | — | Smoking status, alcohol consumption, weekly physical activity, dietary health measured by the alternative healthy eating index, and BMI | — |
| PPM015472 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident lung cancer | OR: 0.91 [0.83, 0.99] | — | — | Smoking status, alcohol consumption, weekly physical activity, dietary health measured by the alternative healthy eating index, and BMI | — |
| PPM015473 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident breast cancer | OR: 0.96 [0.92, 1.0] | — | — | Smoking status, alcohol consumption, weekly physical activity, dietary health measured by the alternative healthy eating index, and BMI | — |
| PPM015474 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Coronary heart disease death | HR: 1.29 [1.16, 1.43] | — | — | — | — |
| PPM015475 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Death of unknown cause | HR: 1.28 [1.07, 1.54] | — | — | — | — |
| PPM015451 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Self-reported hypertension | OR: 1.2 [1.16, 1.24] | — | — | — | — |
| PPM015452 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Self-reported hypercholesterolemia | OR: 1.17 [1.12, 1.23] | — | — | — | — |
| PPM015453 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Self-reported rheumatoid arthritis | OR: 1.11 [1.03, 1.19] | — | — | — | — |
| PPM015460 | PGS000018 (metaGRS_CAD) |
PSS009958| European Ancestry| 21,863 individuals |
PGP000372 | Clarke SL et al. Commun Med (Lond) (2022) |Ext. |
Reported Trait: Incident coronary revascularization | OR: 1.54 [1.45, 1.63] | — | — | Smoking status, self-reported diabetes at baseline, systolic blood pressure, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol | — |
| PPM015491 | PGS000013 (GPS_CAD) |
PSS009960| Ancestry Not Reported| 172,066 individuals |
PGP000374 | Zaccardi F et al. Nutr Metab Cardiovasc Dis (2022) |Ext. |
Reported Trait: 10-year risk of coronary artery disease for slow walkers | — | — | Hazard Ratio (HR, top 20% vs. bottom 80%): 9.6 [8.62, 10.57] | — | — |
| PPM015493 | PGS000013 (GPS_CAD) |
PSS009960| Ancestry Not Reported| 172,066 individuals |
PGP000374 | Zaccardi F et al. Nutr Metab Cardiovasc Dis (2022) |Ext. |
Reported Trait: Difference in 10-year risk of coronary artery disease between slow walkers and brisk walkers | — | — | Hazard Ratio (HR, top 20% vs. bottom 80%): 3.63 [2.58, 4.67] | — | — |
| PPM015502 | PGS000018 (metaGRS_CAD) |
PSS009965| European Ancestry| 836 individuals |
PGP000378 | Schoepf IC et al. Clin Infect Dis (2021) |Ext. |
Reported Trait: Coronary artery disease | — | — | Odds Ratio (OR, fifth vs. first quintile): 3.17 [1.74, 5.79] | Clinical risk factors | — |
| PPM015504 | PGS000018 (metaGRS_CAD) |
PSS009965| European Ancestry| 836 individuals |
PGP000378 | Schoepf IC et al. Clin Infect Dis (2021) |Ext. |
Reported Trait: Coronary artery disease | — | — | Odds Ratio (OR, fifth vs. first quintile): 3.67 [2.0, 6.73] | Clinical risk factors, PRS_longetivity | Combined as metaPRS |
| PPM015520 | PGS000016 (GPS_AF) |
PSS009971| Multi-ancestry (including European)| 36,422 individuals |
PGP000381 | Hao L et al. Nat Med (2022) |Ext. |
Reported Trait: Atrial fibrillation | OR: 2.37 [2.12, 2.64] | — | — | 4 genetic PCs | — |
| PPM015521 | PGS000013 (GPS_CAD) |
PSS009971| Multi-ancestry (including European)| 36,422 individuals |
PGP000381 | Hao L et al. Nat Med (2022) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.86 [1.69, 2.05] | — | — | 4 genetic PCs | — |
| PPM015490 | PGS000013 (GPS_CAD) |
PSS009961| Ancestry Not Reported| 208,627 individuals |
PGP000374 | Zaccardi F et al. Nutr Metab Cardiovasc Dis (2022) |Ext. |
Reported Trait: 10-year risk of coronary artery disease for slow walkers | — | — | Hazard Ratio (HR, top 20% vs. bottom 80%): 2.72 [2.3, 3.13] | — | — |
| PPM015492 | PGS000013 (GPS_CAD) |
PSS009961| Ancestry Not Reported| 208,627 individuals |
PGP000374 | Zaccardi F et al. Nutr Metab Cardiovasc Dis (2022) |Ext. |
Reported Trait: Difference in 10-year risk of coronary artery disease between slow walkers and brisk walkers | — | — | Hazard Ratio (HR, top 20% vs. bottom 80%): 1.26 [0.81, 1.71] | — | — |
| PPM015494 | PGS000013 (GPS_CAD) |
PSS009961| Ancestry Not Reported| 208,627 individuals |
PGP000374 | Zaccardi F et al. Nutr Metab Cardiovasc Dis (2022) |Ext. |
Reported Trait: 10-year risk of coronary artery disease | — | C-index: 0.801 [0.793, 0.808] | — | Age (continuous), Townsend deprivation index (continuous), systolic blood pressure (continuous), LDL cholesterol (continuous), smoking status (current/former/never), history of diabetes (yes/no), family history of myocardial infarction (yes/no), walking pace | — |
| PPM015495 | PGS000013 (GPS_CAD) |
PSS009960| Ancestry Not Reported| 172,066 individuals |
PGP000374 | Zaccardi F et al. Nutr Metab Cardiovasc Dis (2022) |Ext. |
Reported Trait: 10-year risk of coronary artery disease | — | C-index: 0.732 [0.728, 0.737] | — | Age (continuous), Townsend deprivation index (continuous), systolic blood pressure (continuous), LDL cholesterol (continuous), smoking status (current/former/never), history of diabetes (yes/no), family history of myocardial infarction (yes/no), walking pace | — |
| PPM015496 | PGS002794 (PRS_VTE) |
PSS009962| Ancestry Not Reported| 359,310 individuals |
PGP000375 | Xie J et al. J Thromb Haemost (2022) |
Reported Trait: Incident venous thromboembolism witihin 28 days after first dose of COVID-19 vaccination | HR: 1.38 [1.13, 1.7] | — | — | Age (at the index date), sex, and genetic ancestry (quantified by the first ten principal components | — |
| PPM015497 | PGS002794 (PRS_VTE) |
PSS009962| Ancestry Not Reported| 359,310 individuals |
PGP000375 | Xie J et al. J Thromb Haemost (2022) |
Reported Trait: Incident venous thromboembolism witihin 90 days after first dose of COVID-19 vaccination | HR: 1.34 [1.2, 1.5] | — | — | Age (at the index date), sex, and genetic ancestry (quantified by the first ten principal components | — |
| PPM014956 | PGS002756 (Atrial_fibrillation_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Atrial fibrillation | OR: 1.87 [1.79, 1.96] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM014970 | PGS002770 (Stroke_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Stroke | OR: 1.15 [1.08, 1.22] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM015569 | PGS000337 (MetaPRS_CAD) |
PSS009986| Greater Middle Eastern Ancestry| 7,023 individuals |
PGP000386 | Saad M et al. Circ Genom Precis Med (2022) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.81 [1.66, 1.98] | AUROC: 0.667 [0.649, 0.685] | — | — | — |
| PPM014965 | PGS002765 (SBP_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.57 [1.51, 1.62] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM014972 | PGS002772 (Venous_thromboembolism_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Venous thromboembolism | OR: 1.41 [1.34, 1.48] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM015570 | PGS000296 (GPS_CAD_SA) |
PSS009986| Greater Middle Eastern Ancestry| 7,023 individuals |
PGP000386 | Saad M et al. Circ Genom Precis Med (2022) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.53 [1.42, 1.64] | AUROC: 0.683 [0.665, 0.701] | — | — | — |
| PPM015571 | PGS000018 (metaGRS_CAD) |
PSS009986| Greater Middle Eastern Ancestry| 7,023 individuals |
PGP000386 | Saad M et al. Circ Genom Precis Med (2022) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.54 [1.43, 1.66] | AUROC: 0.686 [0.667, 0.704] | — | — | — |
| PPM015572 | PGS000749 (PRS_COMBINED) |
PSS009986| Greater Middle Eastern Ancestry| 7,023 individuals |
PGP000386 | Saad M et al. Circ Genom Precis Med (2022) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.66 [1.51, 1.82] | AUROC: 0.645 [0.627, 0.663] | — | — | — |
| PPM015577 | PGS002809 (GRS_CAD) |
PSS009989| European Ancestry| 360,098 individuals |
PGP000388 | Ahmed R et al. Int J Cardiol Heart Vasc (2022) |
Reported Trait: Incident coronary artery disease | — | — | Hazard ratio (HR, >=3 vs <0.5 risk): 3.02 [2.73, 3.33] | — | Calculated as Population‐standardized GRS |
| PPM015578 | PGS002809 (GRS_CAD) |
PSS009989| European Ancestry| 360,098 individuals |
PGP000388 | Ahmed R et al. Int J Cardiol Heart Vasc (2022) |
Reported Trait: Incident coronary artery disease in subjects with borderline-/intermediate-ASCVD risk | — | — | Hazard ratio (HR, >=3 vs <0.5 risk): 2.91 [2.59, 3.26] | — | — |
| PPM015602 | PGS002814 (AF-PRS) |
PSS009995| East Asian Ancestry| 24,147 individuals |
PGP000392 | Miyazawa K et al. Nat Genet (2023) |
Reported Trait: Atrial fibrillation | OR: 1.94332 β: 0.66 |
AUROC: 0.74 | Nagelkerke’s pseudo R2: 0.14 | age, sex, and the top 20 PCs | We assessed the PRS performance using logistic regression model adjusted for covariates using glm in R. |
| PPM015889 | PGS003004 (ExPRSweb_Hypertension_finngen-R4-FG_LASSOSUM_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 0.983 [0.955, 1.012] β: -0.0172 (0.0149) |
AUROC: 0.51 [0.5, 0.519] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015872 | PGS002997 (ExPRSweb_Hypertension_20002-1065_DBSLMM_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.338 [1.299, 1.379] β: 0.291 (0.0153) |
AUROC: 0.58 [0.572, 0.59] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015873 | PGS002994 (ExPRSweb_Hypertension_20002-1065_LASSOSUM_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.638 [1.587, 1.691] β: 0.494 (0.0162) |
AUROC: 0.628 [0.62, 0.636] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015874 | PGS002996 (ExPRSweb_Hypertension_20002-1065_PLINK_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.55 [1.501, 1.6] β: 0.438 (0.0164) |
AUROC: 0.611 [0.602, 0.619] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015875 | PGS002998 (ExPRSweb_Hypertension_20002-1065_PRSCS_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.67 [1.617, 1.725] β: 0.513 (0.0165) |
AUROC: 0.63 [0.622, 0.639] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015876 | PGS002995 (ExPRSweb_Hypertension_20002-1065_PT_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.556 [1.507, 1.607] β: 0.442 (0.0164) |
AUROC: 0.612 [0.603, 0.62] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015877 | PGS003002 (ExPRSweb_Hypertension_20002-1072_DBSLMM_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.003 [0.974, 1.033] β: 0.0026 (0.015) |
AUROC: 0.486 [0.478, 0.495] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015878 | PGS002999 (ExPRSweb_Hypertension_20002-1072_LASSOSUM_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.036 [1.006, 1.067] β: 0.0358 (0.015) |
AUROC: 0.508 [0.498, 0.516] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015880 | PGS003003 (ExPRSweb_Hypertension_20002-1072_PRSCS_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.059 [1.029, 1.09] β: 0.0573 (0.0149) |
AUROC: 0.516 [0.507, 0.524] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015881 | PGS003000 (ExPRSweb_Hypertension_20002-1072_PT_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.034 [1.004, 1.065] β: 0.0338 (0.015) |
AUROC: 0.507 [0.498, 0.516] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015882 | PGS003017 (ExPRSweb_Hypertension_I10_DBSLMM_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.006 [0.977, 1.036] β: 0.0057 (0.015) |
AUROC: 0.492 [0.484, 0.502] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015883 | PGS003014 (ExPRSweb_Hypertension_I10_LASSOSUM_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.065 [1.035, 1.097] β: 0.0634 (0.015) |
AUROC: 0.517 [0.509, 0.526] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015884 | PGS003016 (ExPRSweb_Hypertension_I10_PLINK_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.066 [1.035, 1.098] β: 0.064 (0.015) |
AUROC: 0.521 [0.512, 0.53] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015885 | PGS003018 (ExPRSweb_Hypertension_I10_PRSCS_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.07 [1.038, 1.102] β: 0.0672 (0.015) |
AUROC: 0.519 [0.51, 0.527] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015886 | PGS003015 (ExPRSweb_Hypertension_I10_PT_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.07 [1.039, 1.102] β: 0.0677 (0.015) |
AUROC: 0.522 [0.513, 0.53] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015887 | PGS003007 (ExPRSweb_Hypertension_finngen-R4-FG_DBSLMM_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.015 [0.986, 1.045] β: 0.0153 (0.0149) |
AUROC: 0.498 [0.489, 0.507] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015890 | PGS003019 (ExPRSweb_Hypertension_finngen-R4-FG_LASSOSUM_UKB_20211120) |
PSS010030| European Ancestry| 203,639 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.016 [1.004, 1.027] β: 0.0156 (0.00586) |
AUROC: 0.505 [0.502, 0.509] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015891 | PGS003006 (ExPRSweb_Hypertension_finngen-R4-FG_PLINK_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 0.987 [0.959, 1.017] β: -0.0127 (0.015) |
AUROC: 0.502 [0.492, 0.511] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015892 | PGS003021 (ExPRSweb_Hypertension_finngen-R4-FG_PLINK_UKB_20211120) |
PSS010030| European Ancestry| 203,639 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.01 [0.999, 1.022] β: 0.0101 (0.00587) |
AUROC: 0.503 [0.5, 0.507] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015893 | PGS003008 (ExPRSweb_Hypertension_finngen-R4-FG_PRSCS_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 0.988 [0.959, 1.017] β: -0.0122 (0.0149) |
AUROC: 0.5 [0.49, 0.508] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015895 | PGS003005 (ExPRSweb_Hypertension_finngen-R4-FG_PT_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.016 [0.986, 1.046] β: 0.0155 (0.015) |
AUROC: 0.506 [0.497, 0.515] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015896 | PGS003020 (ExPRSweb_Hypertension_finngen-R4-FG_PT_UKB_20211120) |
PSS010030| European Ancestry| 203,639 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 0.992 [0.98, 1.003] β: -0.00832 (0.00587) |
AUROC: 0.506 [0.503, 0.509] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015897 | PGS003012 (ExPRSweb_Hypertension_finngen-R4-I9_DBSLMM_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.019 [0.99, 1.05] β: 0.0193 (0.0149) |
AUROC: 0.502 [0.493, 0.511] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015898 | PGS003027 (ExPRSweb_Hypertension_finngen-R4-I9_DBSLMM_UKB_20211120) |
PSS010030| European Ancestry| 203,639 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.0 [0.989, 1.011] β: -7e-05 (0.00584) |
AUROC: 0.492 [0.489, 0.494] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015899 | PGS003009 (ExPRSweb_Hypertension_finngen-R4-I9_LASSOSUM_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 0.99 [0.961, 1.019] β: -0.0105 (0.015) |
AUROC: 0.512 [0.503, 0.521] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015900 | PGS003024 (ExPRSweb_Hypertension_finngen-R4-I9_LASSOSUM_UKB_20211120) |
PSS010030| European Ancestry| 203,639 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.01 [0.998, 1.022] β: 0.00982 (0.00587) |
AUROC: 0.503 [0.5, 0.507] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015901 | PGS003011 (ExPRSweb_Hypertension_finngen-R4-I9_PLINK_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.023 [0.993, 1.054] β: 0.0229 (0.0151) |
AUROC: 0.505 [0.496, 0.514] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015902 | PGS003026 (ExPRSweb_Hypertension_finngen-R4-I9_PLINK_UKB_20211120) |
PSS010030| European Ancestry| 203,639 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.006 [0.994, 1.018] β: 0.00592 (0.00587) |
AUROC: 0.502 [0.498, 0.505] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015903 | PGS003013 (ExPRSweb_Hypertension_finngen-R4-I9_PRSCS_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 0.991 [0.962, 1.02] β: -0.00951 (0.0149) |
AUROC: 0.5 [0.491, 0.509] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015905 | PGS003010 (ExPRSweb_Hypertension_finngen-R4-I9_PT_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.023 [0.993, 1.053] β: 0.0224 (0.015) |
AUROC: 0.507 [0.498, 0.515] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015906 | PGS003025 (ExPRSweb_Hypertension_finngen-R4-I9_PT_UKB_20211120) |
PSS010030| European Ancestry| 203,639 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 0.991 [0.98, 1.002] β: -0.00913 (0.00587) |
AUROC: 0.504 [0.501, 0.507] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015879 | PGS003001 (ExPRSweb_Hypertension_20002-1072_PLINK_MGI_20211120) |
PSS010008| European Ancestry| 23,316 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.032 [1.002, 1.063] β: 0.0318 (0.015) |
AUROC: 0.507 [0.498, 0.516] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015888 | PGS003022 (ExPRSweb_Hypertension_finngen-R4-FG_DBSLMM_UKB_20211120) |
PSS010030| European Ancestry| 203,639 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.002 [0.99, 1.013] β: 0.0015 (0.00585) |
AUROC: 0.491 [0.488, 0.494] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015894 | PGS003023 (ExPRSweb_Hypertension_finngen-R4-FG_PRSCS_UKB_20211120) |
PSS010030| European Ancestry| 203,639 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.012 [1.001, 1.024] β: 0.012 (0.00587) |
AUROC: 0.506 [0.502, 0.509] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015904 | PGS003028 (ExPRSweb_Hypertension_finngen-R4-I9_PRSCS_UKB_20211120) |
PSS010030| European Ancestry| 203,639 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Hypertension | OR: 1.009 [0.997, 1.021] β: 0.00888 (0.00587) |
AUROC: 0.505 [0.502, 0.509] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016211 | PGS003356 (1MH_CAD_PRS_2022_Ldpred) |
PSS010059| European Ancestry| 14,298 individuals |
PGP000409 | Aragam KG et al. Nat Genet (2022) |
Reported Trait: Recurrent coronary artery disease | HR: 1.2 [1.11, 1.29] | — | — | age, sex and ancestry (PCs 1-5) | — |
| PPM016212 | PGS003355 (1MH_CAD_PRS_2015_Ldpred) |
PSS010059| European Ancestry| 14,298 individuals |
PGP000409 | Aragam KG et al. Nat Genet (2022) |
Reported Trait: Recurrent coronary artery disease | HR: 1.13 [1.04, 1.22] | — | — | age, sex and ancestry (PCs 1-5) | — |
| PPM016151 | PGS000039 (metaGRS_ischaemicstroke) |
PSS010050| Ancestry Not Reported| 454,756 individuals |
PGP000401 | Cho BPH et al. JAMA Neurol (2022) |Ext. |
Reported Trait: Stroke | HR: 1.23 [1.2, 1.26] | — | — | age, sex, ethnicity, exome sequencing batch, and the first 10 principal components of genetic ancestry | — |
| PPM016143 | PGS003332 (PRS_VTE_EUR_GHOUSE) |
PSS010047| European Ancestry| 436,440 individuals |
PGP000398 | Ghouse J et al. Nat Genet (2023) |
Reported Trait: Prevalent VTE | OR: 1.51 | AUROC: 0.664 [0.659, 0.669] | — | age, sex, 4 PCs | — |
| PPM016208 | PGS003356 (1MH_CAD_PRS_2022_Ldpred) |
PSS010060| Ancestry Not Reported| 5,685 individuals |
PGP000409 | Aragam KG et al. Nat Genet (2022) |
Reported Trait: Incident coronary artery disease | HR: 1.61 [1.5, 1.72] | — | — | age, sex and ancestry (PCs 1-5) | — |
| PPM016210 | PGS003355 (1MH_CAD_PRS_2015_Ldpred) |
PSS010060| Ancestry Not Reported| 5,685 individuals |
PGP000409 | Aragam KG et al. Nat Genet (2022) |
Reported Trait: Incident coronary artery disease | HR: 1.49 [1.39, 1.59] | — | — | age, sex and ancestry (PCs 1-5) | — |
| PPM016209 | PGS003356 (1MH_CAD_PRS_2022_Ldpred) |
PSS010060| Ancestry Not Reported| 5,685 individuals |
PGP000409 | Aragam KG et al. Nat Genet (2022) |
Reported Trait: Incident coronary artery disease | HR: 1.54 | — | — | age, sex and ancestry (PCs 1–5), established risk factors for CAD (total cholesterol, HDL cholesterol, systolic blood pressure, body mass index, type 2 diabetes, current smoking status and family history of CAD) | — |
| PPM017048 | PGS003406 (1_withUKB_sexAll_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard | HR: 1.344 | C-index: 0.652 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017049 | PGS003407 (2_withUKB_sexMale_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard (men only) | HR: 1.254 | C-index: 0.571 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017050 | PGS003408 (3_withUKB_sexFemale_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard (women only) | HR: 1.374 | C-index: 0.727 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017051 | PGS003409 (4_withUKB_sexAll_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard | HR: 1.254 | C-index: 0.65 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017052 | PGS003410 (5_withUKB_sexMale_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard (men only) | HR: 1.199 | C-index: 0.593 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017053 | PGS003411 (6_withUKB_sexFemale_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Aneurysmal subarachnoid hemorrhage hazard (women only) | HR: 1.295 | C-index: 0.722 | — | sex, systolic blood pressure, cigarette packs per day | — |
| PPM017054 | PGS003406 (1_withUKB_sexAll_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases | OR: 1.094 | C-index: 0.763 | — | — | — |
| PPM017055 | PGS003407 (2_withUKB_sexMale_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases (men only) | OR: 1.091 | C-index: 0.762 | — | — | — |
| PPM017056 | PGS003408 (3_withUKB_sexFemale_metaGRS.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases (women only) | OR: 1.089 | C-index: 0.77 | — | — | — |
| PPM017057 | PGS003409 (4_withUKB_sexAll_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases | OR: 1.124 | C-index: 0.764 | — | — | — |
| PPM017058 | PGS003410 (5_withUKB_sexMale_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases (men only) | OR: 1.165 | C-index: 0.763 | — | — | — |
| PPM017059 | PGS003411 (6_withUKB_sexFemale_IAonly.weights) |
PSS010105| European Ancestry| 69,396 individuals |
PGP000423 | Bakker MK et al. Stroke (2023) |
Reported Trait: Intracranial aneurysm cases (women only) | OR: 1.085 | C-index: 0.77 | — | — | — |
| PPM017084 | PGS000018 (metaGRS_CAD) |
PSS010120| European Ancestry| 4,218 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Atherosclerotic cardiovascular disease (incident and prevalent) | OR: 1.36 [1.21, 1.52] | AUROC: 0.772 [0.748, 0.796] | — | sex, age | — |
| PPM017085 | PGS000018 (metaGRS_CAD) |
PSS010122| European Ancestry| 4,218 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.63 [1.45, 1.83] | AUROC: 0.793 [0.77, 0.816] | — | sex, age | — |
| PPM017086 | PGS000018 (metaGRS_CAD) |
PSS010119| European Ancestry| 3,383 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Incident atherosclerotic cardiovascular disease | HR: 1.31 [1.13, 1.51] | AUROC: 0.769 [0.734, 0.804] C-index: 0.779 [0.746, 0.811] |
— | sex, age, 10 principal components | — |
| PPM017087 | PGS000018 (metaGRS_CAD) |
PSS010121| European Ancestry| 3,383 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.62 [1.43, 1.84] | AUROC: 0.784 [0.757, 0.811] C-index: 0.79 [0.764, 0.816] |
— | sex, age, 10 principal components | — |
| PPM017088 | PGS000013 (GPS_CAD) |
PSS010120| European Ancestry| 4,218 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Atherosclerotic cardiovascular disease (incident and prevalent) | OR: 1.34 [1.2, 1.5] | AUROC: 0.766 [0.741, 0.792] | — | sex, age | — |
| PPM017089 | PGS000013 (GPS_CAD) |
PSS010122| European Ancestry| 4,218 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.6 [1.44, 1.79] | AUROC: 0.784 [0.76, 0.808] | — | sex, age | — |
| PPM017090 | PGS000013 (GPS_CAD) |
PSS010119| European Ancestry| 3,383 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Incident atherosclerotic cardiovascular disease | HR: 1.29 [1.13, 1.48] | — | — | sex, age, 10 principal components | — |
| PPM017091 | PGS000013 (GPS_CAD) |
PSS010121| European Ancestry| 3,383 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.59 [1.41, 1.8] | — | — | sex, age, 10 principal components | — |
| PPM017092 | PGS000329 (PRS_CHD) |
PSS010120| European Ancestry| 4,218 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Atherosclerotic cardiovascular disease (incident and prevalent) | OR: 1.33 [1.2, 1.49] | AUROC: 0.765 [0.74, 0.79] | — | sex, age | — |
| PPM017093 | PGS000329 (PRS_CHD) |
PSS010122| European Ancestry| 4,218 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.59 [1.42, 1.77] | AUROC: 0.779 [0.756, 0.803] | — | sex, age | — |
| PPM017094 | PGS000329 (PRS_CHD) |
PSS010119| European Ancestry| 3,383 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Incident atherosclerotic cardiovascular disease | HR: 1.29 [1.12, 1.47] | — | — | sex, age, 10 principal components | — |
| PPM017095 | PGS000329 (PRS_CHD) |
PSS010121| European Ancestry| 3,383 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.57 [1.4, 1.77] | — | — | sex, age, 10 principal components | — |
| PPM017096 | PGS000117 (CVD_EJ2020) |
PSS010120| European Ancestry| 4,218 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Atherosclerotic cardiovascular disease (incident and prevalent) | OR: 1.36 [1.21, 1.52] | AUROC: 0.768 [0.743, 0.794] | — | sex, age | — |
| PPM017097 | PGS000117 (CVD_EJ2020) |
PSS010119| European Ancestry| 3,383 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Incident atherosclerotic cardiovascular disease | HR: 1.3 [1.13, 1.5] | — | — | sex, age, 10 principal components | — |
| PPM017098 | PGS000116 (CAD_EJ2020) |
PSS010122| European Ancestry| 4,218 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Coronary heart disease (incident and prevalent) | OR: 1.69 [1.5, 1.92] | AUROC: 0.781 [0.575, 0.805] | — | sex, age | — |
| PPM017099 | PGS000116 (CAD_EJ2020) |
PSS010121| European Ancestry| 3,383 individuals |
PGP000433 | de La Harpe R et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.67 [1.46, 1.92] | — | — | sex, age, 10 principal components | — |
| PPM000588 | PGS000200 (GRS28) |
PSS000328| European Ancestry| 24,124 individuals |
PGP000082 | Tikkanen E et al. Arterioscler Thromb Vasc Biol (2013) |
Reported Trait: Incident acute coronary syndrome | — | C-index: 0.859 | ΔC-index (over covariate only model): 0.004 [0.003, 0.005] | sex, total cholesterol, high-density lipoprotein-cholesterol, body mass index, systolic blood pressure, antihypertensive treatment, smoking, type 2 diabetes mellitus, family history | Age as timescale Cox regression |
| PPM000587 | PGS000200 (GRS28) |
PSS000329| European Ancestry| 24,124 individuals |
PGP000082 | Tikkanen E et al. Arterioscler Thromb Vasc Biol (2013) |
Reported Trait: Incident coronary heart disease | — | C-index: 0.856 | ΔC-index (over covariate only model): 0.005 [0.004, 0.006] | sex, total cholesterol, high-density lipoprotein-cholesterol, body mass index, systolic blood pressure, antihypertensive treatment, smoking, type 2 diabetes mellitus, family history | Age as timescale Cox regression |
| PPM000586 | PGS000200 (GRS28) |
PSS000330| European Ancestry| 24,124 individuals |
PGP000082 | Tikkanen E et al. Arterioscler Thromb Vasc Biol (2013) |
Reported Trait: Incident cardiovascular disease | — | C-index: 0.84 | ΔC-index (over covariate only model): 0.003 [0.002, 0.004] | sex, total cholesterol, high-density lipoprotein-cholesterol, body mass index, systolic blood pressure, antihypertensive treatment, smoking, type 2 diabetes mellitus, family history | Age as timescale Cox regression |
| PPM013081 | PGS002316 (disease_CARDIOVASCULAR.BOLT-LMM) |
PSS009707| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.009 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013149 | PGS002335 (disease_HYPERTENSION_DIAGNOSED.BOLT-LMM) |
PSS009784| East Asian Ancestry| 913 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0326 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013100 | PGS002335 (disease_HYPERTENSION_DIAGNOSED.BOLT-LMM) |
PSS009783| African Ancestry| 6,438 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0144 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013130 | PGS002316 (disease_CARDIOVASCULAR.BOLT-LMM) |
PSS009708| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0256 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013179 | PGS002316 (disease_CARDIOVASCULAR.BOLT-LMM) |
PSS009709| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0419 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013198 | PGS002335 (disease_HYPERTENSION_DIAGNOSED.BOLT-LMM) |
PSS009785| European Ancestry| 43,392 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0527 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013228 | PGS002316 (disease_CARDIOVASCULAR.BOLT-LMM) |
PSS009710| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0283 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013247 | PGS002335 (disease_HYPERTENSION_DIAGNOSED.BOLT-LMM) |
PSS009786| South Asian Ancestry| 7,948 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0444 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013273 | PGS002361 (disease_CARDIOVASCULAR.BOLT-LMM-BBJ) |
PSS009707| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013319 | PGS002361 (disease_CARDIOVASCULAR.BOLT-LMM-BBJ) |
PSS009709| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013342 | PGS002361 (disease_CARDIOVASCULAR.BOLT-LMM-BBJ) |
PSS009710| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013369 | PGS002388 (disease_CARDIOVASCULAR.P+T.0.0001) |
PSS009707| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013388 | PGS002407 (disease_HYPERTENSION_DIAGNOSED.P+T.0.0001) |
PSS009783| African Ancestry| 6,438 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013418 | PGS002388 (disease_CARDIOVASCULAR.P+T.0.0001) |
PSS009708| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013437 | PGS002407 (disease_HYPERTENSION_DIAGNOSED.P+T.0.0001) |
PSS009784| East Asian Ancestry| 913 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0023 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013467 | PGS002388 (disease_CARDIOVASCULAR.P+T.0.0001) |
PSS009709| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0156 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013486 | PGS002407 (disease_HYPERTENSION_DIAGNOSED.P+T.0.0001) |
PSS009785| European Ancestry| 43,392 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0185 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013516 | PGS002388 (disease_CARDIOVASCULAR.P+T.0.0001) |
PSS009710| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0076 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013535 | PGS002407 (disease_HYPERTENSION_DIAGNOSED.P+T.0.0001) |
PSS009786| South Asian Ancestry| 7,948 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.012 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013565 | PGS002437 (disease_CARDIOVASCULAR.P+T.0.001) |
PSS009707| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013584 | PGS002456 (disease_HYPERTENSION_DIAGNOSED.P+T.0.001) |
PSS009783| African Ancestry| 6,438 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013614 | PGS002437 (disease_CARDIOVASCULAR.P+T.0.001) |
PSS009708| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0065 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013633 | PGS002456 (disease_HYPERTENSION_DIAGNOSED.P+T.0.001) |
PSS009784| East Asian Ancestry| 913 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0028 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013663 | PGS002437 (disease_CARDIOVASCULAR.P+T.0.001) |
PSS009709| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0146 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013682 | PGS002456 (disease_HYPERTENSION_DIAGNOSED.P+T.0.001) |
PSS009785| European Ancestry| 43,392 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0182 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013712 | PGS002437 (disease_CARDIOVASCULAR.P+T.0.001) |
PSS009710| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0054 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013731 | PGS002456 (disease_HYPERTENSION_DIAGNOSED.P+T.0.001) |
PSS009786| South Asian Ancestry| 7,948 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0066 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013761 | PGS002486 (disease_CARDIOVASCULAR.P+T.0.01) |
PSS009707| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013780 | PGS002505 (disease_HYPERTENSION_DIAGNOSED.P+T.0.01) |
PSS009783| African Ancestry| 6,438 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013810 | PGS002486 (disease_CARDIOVASCULAR.P+T.0.01) |
PSS009708| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013829 | PGS002505 (disease_HYPERTENSION_DIAGNOSED.P+T.0.01) |
PSS009784| East Asian Ancestry| 913 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013859 | PGS002486 (disease_CARDIOVASCULAR.P+T.0.01) |
PSS009709| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0099 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013878 | PGS002505 (disease_HYPERTENSION_DIAGNOSED.P+T.0.01) |
PSS009785| European Ancestry| 43,392 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0115 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013908 | PGS002486 (disease_CARDIOVASCULAR.P+T.0.01) |
PSS009710| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0029 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013927 | PGS002505 (disease_HYPERTENSION_DIAGNOSED.P+T.0.01) |
PSS009786| South Asian Ancestry| 7,948 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0044 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013957 | PGS002535 (disease_CARDIOVASCULAR.P+T.1e-06) |
PSS009707| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0054 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013976 | PGS002554 (disease_HYPERTENSION_DIAGNOSED.P+T.1e-06) |
PSS009783| African Ancestry| 6,438 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0034 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014006 | PGS002535 (disease_CARDIOVASCULAR.P+T.1e-06) |
PSS009708| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0021 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014025 | PGS002554 (disease_HYPERTENSION_DIAGNOSED.P+T.1e-06) |
PSS009784| East Asian Ancestry| 913 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0057 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014055 | PGS002535 (disease_CARDIOVASCULAR.P+T.1e-06) |
PSS009709| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0116 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014074 | PGS002554 (disease_HYPERTENSION_DIAGNOSED.P+T.1e-06) |
PSS009785| European Ancestry| 43,392 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0128 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014104 | PGS002535 (disease_CARDIOVASCULAR.P+T.1e-06) |
PSS009710| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0045 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014123 | PGS002554 (disease_HYPERTENSION_DIAGNOSED.P+T.1e-06) |
PSS009786| South Asian Ancestry| 7,948 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0086 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014172 | PGS002603 (disease_HYPERTENSION_DIAGNOSED.P+T.5e-08) |
PSS009783| African Ancestry| 6,438 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.004 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014202 | PGS002584 (disease_CARDIOVASCULAR.P+T.5e-08) |
PSS009708| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0028 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014221 | PGS002603 (disease_HYPERTENSION_DIAGNOSED.P+T.5e-08) |
PSS009784| East Asian Ancestry| 913 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.004 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014270 | PGS002603 (disease_HYPERTENSION_DIAGNOSED.P+T.5e-08) |
PSS009785| European Ancestry| 43,392 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.011 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014300 | PGS002584 (disease_CARDIOVASCULAR.P+T.5e-08) |
PSS009710| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0042 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014319 | PGS002603 (disease_HYPERTENSION_DIAGNOSED.P+T.5e-08) |
PSS009786| South Asian Ancestry| 7,948 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.007 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014349 | PGS002633 (disease_CARDIOVASCULAR.PolyFun-pred) |
PSS009707| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0141 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_CARDIOVASCULAR.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014564 | PGS002701 (disease_HYPERTENSION_DIAGNOSED.SBayesR) |
PSS009783| African Ancestry| 6,438 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0146 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014368 | PGS002652 (disease_HYPERTENSION_DIAGNOSED.PolyFun-pred) |
PSS009783| African Ancestry| 6,438 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0195 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_HYPERTENSION_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014398 | PGS002633 (disease_CARDIOVASCULAR.PolyFun-pred) |
PSS009708| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0281 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_CARDIOVASCULAR.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014417 | PGS002652 (disease_HYPERTENSION_DIAGNOSED.PolyFun-pred) |
PSS009784| East Asian Ancestry| 913 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0417 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_HYPERTENSION_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014447 | PGS002633 (disease_CARDIOVASCULAR.PolyFun-pred) |
PSS009709| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0429 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_CARDIOVASCULAR.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014466 | PGS002652 (disease_HYPERTENSION_DIAGNOSED.PolyFun-pred) |
PSS009785| European Ancestry| 43,392 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0539 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_HYPERTENSION_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014496 | PGS002633 (disease_CARDIOVASCULAR.PolyFun-pred) |
PSS009710| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0294 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_CARDIOVASCULAR.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014515 | PGS002652 (disease_HYPERTENSION_DIAGNOSED.PolyFun-pred) |
PSS009786| South Asian Ancestry| 7,948 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0476 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_HYPERTENSION_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014545 | PGS002682 (disease_CARDIOVASCULAR.SBayesR) |
PSS009707| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0093 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014594 | PGS002682 (disease_CARDIOVASCULAR.SBayesR) |
PSS009708| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0237 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014613 | PGS002701 (disease_HYPERTENSION_DIAGNOSED.SBayesR) |
PSS009784| East Asian Ancestry| 913 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0335 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014643 | PGS002682 (disease_CARDIOVASCULAR.SBayesR) |
PSS009709| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0402 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014662 | PGS002701 (disease_HYPERTENSION_DIAGNOSED.SBayesR) |
PSS009785| European Ancestry| 43,392 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0506 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014692 | PGS002682 (disease_CARDIOVASCULAR.SBayesR) |
PSS009710| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0306 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014711 | PGS002701 (disease_HYPERTENSION_DIAGNOSED.SBayesR) |
PSS009786| South Asian Ancestry| 7,948 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Hypertension | — | — | Incremental R2 (full model vs. covariates alone): 0.0453 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013296 | PGS002361 (disease_CARDIOVASCULAR.BOLT-LMM-BBJ) |
PSS009708| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014153 | PGS002584 (disease_CARDIOVASCULAR.P+T.5e-08) |
PSS009707| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.005 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014251 | PGS002584 (disease_CARDIOVASCULAR.P+T.5e-08) |
PSS009709| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Cardiovascular disease | — | — | Incremental R2 (full model vs. covariates alone): 0.0101 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM017265 | PGS003461 (GRS162_AF) |
PSS010183| European Ancestry| 62,927 individuals |
PGP000454 | Yang L et al. NPJ Digit Med (2023) |
Reported Trait: Incident atrial fibrillation | — | — | Hazard ratio (HR, high vs low tertile): 2.54 [2.26, 2.85] | — | — |
| PPM017267 | PGS003461 (GRS162_AF) |
PSS010183| European Ancestry| 62,927 individuals |
PGP000454 | Yang L et al. NPJ Digit Med (2023) |
Reported Trait: Incident atrial fibrillation with circadian rest-activity characteristics delayed acrophase | HR: 2.69 [2.18, 3.33] | — | — | Age, sex, first 10 principal components of ancestry, Townsend deprivation index, recruitment centre, education level, season of accelerometer wear, BMI categories, healthy diet score, smoking status, alcohol intake, coffee consumption, tea consumption, hypertension, diabetes, dyslipidemia, sleep efficiency, sleep duration | — |
| PPM017268 | PGS003461 (GRS162_AF) |
PSS010183| European Ancestry| 62,927 individuals |
PGP000454 | Yang L et al. NPJ Digit Med (2023) |
Reported Trait: Incident atrial fibrillation with circadian rest-activity characteristics low Pseudo-F | HR: 2.55 [2.04, 3.18] | — | — | Age, sex, first 10 principal components of ancestry, Townsend deprivation index, recruitment centre, education level, season of accelerometer wear, BMI categories, healthy diet score, smoking status, alcohol intake, coffee consumption, tea consumption, hypertension, diabetes, dyslipidemia, sleep efficiency, sleep duration | — |
| PPM017269 | PGS003461 (GRS162_AF) |
PSS010183| European Ancestry| 62,927 individuals |
PGP000454 | Yang L et al. NPJ Digit Med (2023) |
Reported Trait: Incident atrial fibrillation with circadian rest-activity characteristics low mesor | HR: 3.67 [2.97, 4.54] | — | — | Age, sex, first 10 principal components of ancestry, Townsend deprivation index, recruitment centre, education level, season of accelerometer wear, BMI categories, healthy diet score, smoking status, alcohol intake, coffee consumption, tea consumption, hypertension, diabetes, dyslipidemia, sleep efficiency, sleep duration | — |
| PPM017257 | PGS003456 (PRS273_VTE) |
PSS010177| African Ancestry| 2,484 individuals |
PGP000449 | Folsom AR et al. PLoS One (2023) |
Reported Trait: Total venous thromboembolism | — | — | Hazard ratio (HR, high vs low tertile): 1.35 [0.81, 2.25] | Adjusted for age, sex, principal components of ancestry, hormone replacement therapy (current, former, never for women, with men as referent category), education level (<high school, high school grad, >high school grad), household income (<$12,000, $12,000 to $24,999, $25,000 to $49,999, $50,000+, missing), height (continuous), weight (continuous), estimated glomerular filtration rate (continuous), diabetes (yes defined as >126 mg/dL, medication or physician diagnosis; no), smoking status (current, former, never), sports physical activity level (continuous), systolic blood pressure (continuous), antihypertensive medication use (yes, no) | — |
| PPM017258 | PGS003457 (GRS_ICH) |
PSS010179| Multi-ancestry (including European)| 5,530 individuals |
PGP000450 | Mayerhofer E et al. Stroke (2023) |
Reported Trait: Incident intracerebral hemorrhage in anticoagulation therapy | HR: 1.24 [1.01, 1.53] | — | R²: 0.02 | age at baseline (controls) or ICH event (cases), sex, PC1 to 10, and genotyping array | — |
| PPM017259 | PGS003457 (GRS_ICH) |
PSS010179| Multi-ancestry (including European)| 5,530 individuals |
PGP000450 | Mayerhofer E et al. Stroke (2023) |
Reported Trait: Incident intracerebral hemorrhage in anticoagulation therapy | HR: 1.33 [1.11, 1.59] | C-index: 0.57 [0.5, 0.64] | — | age at baseline (controls) or ICH event (cases), sex, PC1 to 10, and genotyping array, clinical risk score | — |
| PPM017185 | PGS003446 (TEM_CAD_PRS) |
PSS010163| European Ancestry| 67,738 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |
Reported Trait: Coronary artery disease | OR: 1.35 [1.31, 138.0] | — | — | — | — |
| PPM017188 | PGS000013 (GPS_CAD) |
PSS010162| European Ancestry| 292,438 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization | OR: 1.51 [1.49, 1.53] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017195 | PGS000013 (GPS_CAD) |
PSS010161| Hispanic or Latin American Ancestry| 30,648 individuals |
PGP000446 | Tcheandjieu C et al. Nat Med (2022) |Ext. |
Reported Trait: Acute myocardial infarction or revascularization in incident coronary artery disease | OR: 1.49 [1.38, 1.61] | — | — | age, sex, genotyping batch and top 10 genotype-based PCs | — |
| PPM017266 | PGS003461 (GRS162_AF) |
PSS010183| European Ancestry| 62,927 individuals |
PGP000454 | Yang L et al. NPJ Digit Med (2023) |
Reported Trait: Incident atrial fibrillation with circadian rest-activity characteristics low amplitude | HR: 3.87 [3.07, 4.87] | — | — | Age, sex, first 10 principal components of ancestry, Townsend deprivation index, recruitment centre, education level, season of accelerometer wear, BMI categories, healthy diet score, smoking status, alcohol intake, coffee consumption, tea consumption, hypertension, diabetes, dyslipidemia, sleep efficiency, sleep duration | — |
| PPM017256 | PGS003456 (PRS273_VTE) |
PSS010178| European Ancestry| 8,808 individuals |
PGP000449 | Folsom AR et al. PLoS One (2023) |
Reported Trait: Total venous thromboembolism | — | — | Hazard ratio (HR, high vs low tertile): 2.52 [1.99, 3.2] | Adjusted for age, sex, principal components of ancestry, hormone replacement therapy (current, former, never for women, with men as referent category), education level (<high school, high school grad, >high school grad), household income (<$12,000, $12,000 to $24,999, $25,000 to $49,999, $50,000+, missing), height (continuous), weight (continuous), estimated glomerular filtration rate (continuous), diabetes (yes defined as >126 mg/dL, medication or physician diagnosis; no), smoking status (current, former, never), sports physical activity level (continuous), systolic blood pressure (continuous), antihypertensive medication use (yes, no) | — |
| PPM018281 | PGS003587 (GH) |
PSS010956| European Ancestry| 25,582 individuals |
PGP000462 | Honigberg MC et al. Nat Med (2023) |
Reported Trait: Pre-eclampsia/eclampsia | OR: 1.2 [1.14, 1.26] | — | — | maternal age at delivery, age2, and the first ten principal components of genetic ancestry | — |
| PPM018420 | PGS003725 (GPS_Mult) |
PSS010961| African Ancestry| 7,281 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.25 [1.07, 1.46] OR: 1.39 [1.17, 1.67] |
— | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018467 | PGS000018 (metaGRS_CAD) |
PSS010981| European Ancestry| 3,459 individuals |
PGP000468 | Hodel F et al. Elife (2023) |Ext. |
Reported Trait: Coronary heart disease | HR: 1.32 [1.16, 1.51] | — | — | — | — |
| PPM018280 | PGS003586 (PE) |
PSS010956| European Ancestry| 25,582 individuals |
PGP000462 | Honigberg MC et al. Nat Med (2023) |
Reported Trait: Pre-eclampsia/eclampsia | OR: 1.31 [1.24, 1.38] | — | — | maternal age at delivery, age2, and the first ten principal components of genetic ancestry | — |
| PPM018527 | PGS000739 (HCM_GRS) |
PSS011008| European Ancestry| 184,511 individuals |
PGP000476 | Biddinger KJ et al. JAMA Cardiol (2022) |Ext. |
Reported Trait: Hypertrophic cardiomyopathy | OR: 1.556 [1.361, 1.778] | — | — | — | — |
| PPM018528 | PGS000739 (HCM_GRS) |
PSS011008| European Ancestry| 184,511 individuals |
PGP000476 | Biddinger KJ et al. JAMA Cardiol (2022) |Ext. |
Reported Trait: Hypertrophic cardiomyopathy in noncarriers of an HCM-ACMG rare variant | OR: 1.585 [1.375, 1.828] | — | — | — | — |
| PPM018529 | PGS000739 (HCM_GRS) |
PSS011007| European Ancestry| 30,716 individuals |
PGP000476 | Biddinger KJ et al. JAMA Cardiol (2022) |Ext. |
Reported Trait: Hypertrophic cardiomyopathy | OR: 1.35 [1.21, 1.51] | — | — | — | — |
| PPM018530 | PGS000739 (HCM_GRS) |
PSS011008| European Ancestry| 184,511 individuals |
PGP000476 | Biddinger KJ et al. JAMA Cardiol (2022) |Ext. |
Reported Trait: Hypertrophic cardiomyopathy | HR: 1.795 [1.521, 2.117] | AUROC: 0.725 [0.678, 0.771] | — | Age, sex, genotyping array, and PCs 1-5 | — |
| PPM018531 | PGS000739 (HCM_GRS) |
PSS011008| European Ancestry| 184,511 individuals |
PGP000476 | Biddinger KJ et al. JAMA Cardiol (2022) |Ext. |
Reported Trait: Hypertrophic cardiomyopathy | — | AUROC: 0.821 [0.772, 0.871] | — | Clinical risk factors (obesity, HTN, AF, CAD), HCM-ACMG rare variant carrier status, age, sex, genotyping array, and PCs 1-5 | — |
| PPM018421 | PGS003725 (GPS_Mult) |
PSS010962| East Asian Ancestry| 1,464 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.72 [1.13, 2.6] OR: 2.14 [1.34, 3.49] |
— | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018419 | PGS003725 (GPS_Mult) |
PSS010960| European Ancestry| 308,264 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.75 [1.71, 1.78] OR: 2.14 [2.1, 2.19] |
— | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018422 | PGS003725 (GPS_Mult) |
PSS010963| South Asian Ancestry| 8,982 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.62 [1.49, 1.77] OR: 2.02 [1.83, 2.23] |
— | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018423 | PGS003725 (GPS_Mult) |
PSS010964| African Ancestry| 33,096 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | OR: 1.25 [1.21, 1.29] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018424 | PGS003725 (GPS_Mult) |
PSS010965| European Ancestry| 124,467 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | OR: 1.72 [1.69, 1.75] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018425 | PGS003725 (GPS_Mult) |
PSS010966| Hispanic or Latin American Ancestry| 16,433 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | OR: 1.61 [1.53, 1.7] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018426 | PGS003725 (GPS_Mult) |
PSS010967| South Asian Ancestry| 16,874 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | OR: 1.83 [1.69, 1.99] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018427 | PGS003726 (GPS_CADANC) |
PSS010960| European Ancestry| 308,264 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.73 [1.69, 1.76] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018428 | PGS003726 (GPS_CADANC) |
PSS010961| African Ancestry| 7,281 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.18 [1.01, 1.37] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018430 | PGS003726 (GPS_CADANC) |
PSS010963| South Asian Ancestry| 8,982 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.6 [1.47, 1.74] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018431 | PGS003727 (GPS_CADEUR) |
PSS010960| European Ancestry| 308,264 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.67 [1.64, 1.7] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018432 | PGS003727 (GPS_CADEUR) |
PSS010961| African Ancestry| 7,281 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.15 [0.99, 1.34] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018433 | PGS003727 (GPS_CADEUR) |
PSS010962| East Asian Ancestry| 1,464 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.54 [1.03, 2.32] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018434 | PGS003727 (GPS_CADEUR) |
PSS010963| South Asian Ancestry| 8,982 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.57 [1.44, 1.7] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018429 | PGS003726 (GPS_CADANC) |
PSS010962| East Asian Ancestry| 1,464 individuals |
PGP000466 | Patel AP et al. Nat Med (2023) |
Reported Trait: Coronary artery disease | HR: 1.64 [1.09, 2.48] | — | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM018556 | PGS002259 (metaPRS_Stroke) |
PSS011021| East Asian Ancestry| 41,006 individuals |
PGP000483 | Cui Q et al. Sci China Life Sci (2023) |Ext. |
Reported Trait: Incident stroke | — | — | Hazard ratio (HR, high vs low tertile): 3.01 [2.03, 4.45] | Sex, cohort | Age as the underlying time scale |
| PPM018557 | PGS002259 (metaPRS_Stroke) |
PSS011021| East Asian Ancestry| 41,006 individuals |
PGP000483 | Cui Q et al. Sci China Life Sci (2023) |Ext. |
Reported Trait: Incident stroke with high clinical risk | — | — | Hazard ratio (HR, high vs low tertile): 2.12 [1.38, 3.27] | Sex, cohort | Age as the underlying time scale |
| PPM018558 | PGS003761 (PRS165_AF) |
PSS011022| Multi-ancestry (including European)| 84,206 individuals |
PGP000484 | Zhang J et al. BMC Med (2023) |
Reported Trait: 10-year risk of atrial fibrillation with elevated risk burden | — | — | Hazard ratio (elevated risk factor burden and high PRS vs optimal risk factor burden and low PRS): 7.32 [3.02, 17.7] | sex | — |
| PPM018559 | PGS003761 (PRS165_AF) |
PSS011023| Multi-ancestry (including European)| 117,520 individuals |
PGP000484 | Zhang J et al. BMC Med (2023) |
Reported Trait: 10-year risk of atrial fibrillation with elevated risk burden | — | — | Hazard ratio (elevated risk factor burden and high PRS vs optimal risk factor burden and low PRS): 8.41 [4.37, 16.2] | sex | — |
| PPM018560 | PGS003761 (PRS165_AF) |
PSS011024| Multi-ancestry (including European)| 147,178 individuals |
PGP000484 | Zhang J et al. BMC Med (2023) |
Reported Trait: 10-year risk of atrial fibrillation with elevated risk burden | — | — | Hazard ratio (elevated risk factor burden and high PRS vs optimal risk factor burden and low PRS): 4.12 [2.76, 6.14] | sex | — |
| PPM018751 | PGS003861 (PRS288_PE) |
PSS011090| East Asian Ancestry| 9,456 individuals |
PGP000499 | Zhang Z et al. BMC Med (2023) |
Reported Trait: Pulmonary embolism | — | AUROC: 0.765 | Odds ratio (OR, 30-70th quantile vs <90th quantile): 5.08 [4.109, 6.282] | — | — |
| PPM018758 | PGS003866 (CAD_lassosum2_ARB) |
PSS011097| Greater Middle Eastern Ancestry| 2,669 individuals |
PGP000501 | Shim I et al. Nature Communications (2023) |
Reported Trait: Coronary artery disease | OR: 1.51 [1.42, 1.61] | AUROC: 0.795 [0.7768, 0.8132] | — | age, sex, array version, and the first 10 principal components of ancestry | — |
| PPM018760 | PGS003868 (CM_LDpred2_ARB) |
PSS011097| Greater Middle Eastern Ancestry| 2,669 individuals |
PGP000501 | Shim I et al. Nature Communications (2023) |
Reported Trait: Cardiomyopathy | OR: 1.34 [1.13, 1.64] | AUROC: 0.6453 [0.6086, 0.6819] | — | age, sex, array version, and the first 10 principal components of ancestry | — |
| PPM019123 | PGS003969 (PRS39_HF) |
PSS011190| European Ancestry| 75,119 individuals |
PGP000511 | Rasooly D et al. Nat Commun (2023) |
Reported Trait: Heart failure | OR: 1.28 [1.24, 1.31] | — | — | — | — |
| PPM019106 | PGS001355 (CAD_AnnoPred_PRS) |
PSS011183| European Ancestry| 166,714 individuals |
PGP000506 | Jowell A et al. Eur J Prev Cardiol (2023) |Ext. |
Reported Trait: Family history of heart disease | OR: 1.17 [1.16, 1.19] | — | — | — | — |
| PPM019134 | PGS003972 (PRSAAA) |
PSS011199| European Ancestry| 6,940 individuals |
PGP000513 | Roychowdhury T et al. Nat Genet (2023) |
Reported Trait: Abdominal aortic aneurysm | — | AUROC: 0.69 | — | — | — |
| PPM019135 | PGS003972 (PRSAAA) |
PSS011197| European Ancestry| 7,324 individuals |
PGP000513 | Roychowdhury T et al. Nat Genet (2023) |
Reported Trait: Abdominal aortic aneurysm | — | AUROC: 0.66 | — | — | — |
| PPM019136 | PGS003972 (PRSAAA) |
PSS011198| European Ancestry| 3,768 individuals |
PGP000513 | Roychowdhury T et al. Nat Genet (2023) |
Reported Trait: Abdominal aortic aneurysm | — | AUROC: 0.64 | — | — | — |
| PPM019137 | PGS003973 (PRSAAA_woUKB) |
PSS011200| European Ancestry| 7,517 individuals |
PGP000513 | Roychowdhury T et al. Nat Genet (2023) |
Reported Trait: Abdominal aortic aneurysm | — | C-index: 0.882 [0.872, 0.892] | — | Age, Age^2, Sex | — |
| PPM019431 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.11588 [1.08343617, 1.14930168] β: 0.10965 [0.08013763, 0.13915452] |
AUROC: 0.5311 [0.52258315, 0.53960799] | R²: 0.00249 [0.00124561, 0.00391129] | 0 | beta = log(or)/sd_pgs |
| PPM019432 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16332 [1.14877996, 1.17804017] β: 0.15128 [0.13870048, 0.16385218] |
AUROC: 0.54311 [0.53949521, 0.54672704] | R²: 0.00473 [0.00398409, 0.00555064] | 0 | beta = log(or)/sd_pgs |
| PPM019433 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1116 [1.01001276, 1.22340576] β: 0.1058 [0.00996296, 0.20163858] |
AUROC: 0.53257 [0.50585239, 0.55929704] | R²: 0.00172 [0.0000423, 0.00562594] | 0 | beta = log(or)/sd_pgs |
| PPM019434 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13921 [1.10739553, 1.17193764] β: 0.13033 [0.10201089, 0.15865848] |
AUROC: 0.53729 [0.52919837, 0.54537871] | R²: 0.00351 [0.002153, 0.00526917] | 0 | beta = log(or)/sd_pgs |
| PPM019435 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21092 [1.05660791, 1.38776963] β: 0.19138 [0.05506369, 0.32769787] |
AUROC: 0.5645 [0.52632653, 0.60268065] | R²: 0.00568 [0.000437, 0.01665509] | 0 | beta = log(or)/sd_pgs |
| PPM019436 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20936 [1.15728071, 1.26378987] β: 0.19009 [0.14607304, 0.23411504] |
AUROC: 0.55309 [0.54044775, 0.56573307] | R²: 0.00745 [0.00442536, 0.01118625] | 0 | beta = log(or)/sd_pgs |
| PPM019437 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08291 [1.0515096, 1.11523886] β: 0.07965 [0.05022684, 0.10906861] |
AUROC: 0.52243 [0.51400537, 0.53085786] | R²: 0.00132 [0.000512, 0.0024261] | 0 | beta = log(or)/sd_pgs |
| PPM019438 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06579 [1.05251543, 1.07923704] β: 0.06372 [0.05118295, 0.07625435] |
AUROC: 0.51814 [0.51449934, 0.52177675] | R²: 0.00084 [0.000519, 0.00120992] | 0 | beta = log(or)/sd_pgs |
| PPM019439 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 0.97393 [0.88492665, 1.07188237] β: -0.02642 [-0.1222505, 0.06941632] |
AUROC: 0.51051 [0.4829624, 0.53805337] | R²: 0.00011 [0.0, 0.00229604] | 0 | beta = log(or)/sd_pgs |
| PPM019440 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06709 [1.03737253, 1.09765048] β: 0.06493 [0.0366911, 0.09317197] |
AUROC: 0.5176 [0.50942967, 0.5257663] | R²: 0.00088 [0.00027871, 0.00193499] | 0 | beta = log(or)/sd_pgs |
| PPM019441 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 0.99729 [0.87003302, 1.1431701] β: -0.00271 [-0.1392241, 0.13380519] |
AUROC: 0.49948 [0.4589389, 0.54002276] | R²: 1.14e-06 [0.0, 0.00307562] | 0 | beta = log(or)/sd_pgs |
| PPM019442 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08405 [1.03738951, 1.13280412] β: 0.0807 [0.03670747, 0.12469608] |
AUROC: 0.52424 [0.51165085, 0.53683071] | R²: 0.00134 [0.0003, 0.00302841] | 0 | beta = log(or)/sd_pgs |
| PPM019443 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06894 [1.03785867, 1.10095983] β: 0.06667 [0.03715962, 0.09618237] |
AUROC: 0.51987 [0.51135121, 0.52838787] | R²: 0.00092 [0.00032, 0.00188246] | 0 | beta = log(or)/sd_pgs |
| PPM019444 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10078 [1.08703793, 1.11469876] β: 0.09602 [0.0834565, 0.1085842] |
AUROC: 0.527 [0.52339166, 0.53061368] | R²: 0.00191 [0.00143669, 0.00245807] | 0 | beta = log(or)/sd_pgs |
| PPM019445 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12773 [1.02478049, 1.24102559] β: 0.12021 [0.02447843, 0.21593812] |
AUROC: 0.53267 [0.5056658, 0.55967946] | R²: 0.00223 [0.00015, 0.00674387] | 0 | beta = log(or)/sd_pgs |
| PPM019446 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | β: 0.1023 [0.07398085, 0.13062111] OR: 1.10772 [1.07678618, 1.13953594] |
AUROC: 0.52919 [0.52105192, 0.53732734] | R²: 0.00216 [0.00113918, 0.003649] | 0 | beta = log(or)/sd_pgs |
| PPM019447 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14403 [0.99833483, 1.31097774] β: 0.13455 [-0.0016666, 0.27077322] |
AUROC: 0.54498 [0.50570189, 0.58425451] | R²: 0.00281 [0.0, 0.01104227] | 0 | beta = log(or)/sd_pgs |
| PPM019448 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13266 [1.08394966, 1.18356209] β: 0.12457 [0.08061146, 0.16852861] |
AUROC: 0.53537 [0.52278904, 0.54795879] | R²: 0.00321 [0.00129459, 0.00578736] | 0 | beta = log(or)/sd_pgs |
| PPM019449 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12083 [1.08824491, 1.15438327] β: 0.11407 [0.08456622, 0.14356623] |
AUROC: 0.53316 [0.52473906, 0.54158598] | R²: 0.00269 [0.00138125, 0.00425231] | 0 | beta = log(or)/sd_pgs |
| PPM019450 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15341 [1.13900681, 1.16800282] β: 0.14273 [0.13015666, 0.1552953] |
AUROC: 0.54057 [0.53695, 0.54418221] | R²: 0.00422 [0.00347622, 0.00499623] | 0 | beta = log(or)/sd_pgs |
| PPM019451 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09189 [0.99222365, 1.20156871] β: 0.08791 [-0.0078067, 0.18362796] |
AUROC: 0.52519 [0.49747233, 0.55290272] | R²: 0.00119 [0.0, 0.00512013] | 0 | beta = log(or)/sd_pgs |
| PPM019452 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12141 [1.09009411, 1.15362816] β: 0.11459 [0.08626403, 0.1429119] |
AUROC: 0.53176 [0.52370534, 0.53981953] | R²: 0.00271 [0.00155187, 0.00420533] | 0 | beta = log(or)/sd_pgs |
| PPM019453 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18126 [1.0309514, 1.3534912] β: 0.16658 [0.03048206, 0.30268733] |
AUROC: 0.54628 [0.50596882, 0.58659045] | R²: 0.00432 [0.0000589, 0.0151188] | 0 | beta = log(or)/sd_pgs |
| PPM019454 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20912 [1.15705376, 1.26353856] β: 0.1899 [0.14587692, 0.23391617] |
AUROC: 0.55395 [0.54139946, 0.56649182] | R²: 0.00744 [0.00445914, 0.01137928] | 0 | beta = log(or)/sd_pgs |
| PPM019455 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08855 [1.05690373, 1.12115148] β: 0.08485 [0.05534362, 0.11435627] |
AUROC: 0.52349 [0.51495565, 0.53202719] | R²: 0.00149 [0.000605, 0.00274949] | 0 | beta = log(or)/sd_pgs |
| PPM019456 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14381 [1.12951156, 1.15828947] β: 0.13436 [0.1217853, 0.14694432] |
AUROC: 0.53828 [0.53466313, 0.5419004] | R²: 0.00373 [0.00305951, 0.00454449] | 0 | beta = log(or)/sd_pgs |
| PPM019457 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09703 [0.99682003, 1.20732376] β: 0.09261 [-0.003185, 0.18840614] |
AUROC: 0.5291 [0.50288518, 0.55530775] | R²: 0.00132 [0.00000145, 0.00481747] | 0 | beta = log(or)/sd_pgs |
| PPM019458 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09561 [1.06503669, 1.12705809] β: 0.09131 [0.06300925, 0.11961078] |
AUROC: 0.52636 [0.518281, 0.53443847] | R²: 0.00173 [0.000859, 0.0029266] | 0 | beta = log(or)/sd_pgs |
| PPM019459 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15035 [1.00389913, 1.31816921] β: 0.14007 [0.00389155, 0.27624381] |
AUROC: 0.546 [0.50679306, 0.5852031] | R²: 0.00305 [0.00000558, 0.0114294] | 0 | beta = log(or)/sd_pgs |
| PPM019460 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20185 [1.1499474, 1.25608606] β: 0.18386 [0.1397162, 0.22800058] |
AUROC: 0.55073 [0.53804918, 0.56340897] | R²: 0.00693 [0.00408496, 0.01084329] | 0 | beta = log(or)/sd_pgs |
| PPM019462 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17327 [1.15860257, 1.18812042] β: 0.15979 [0.1472146, 0.17237258] |
AUROC: 0.54565 [0.54203694, 0.54925403] | R²: 0.00528 [0.00445693, 0.00618855] | 0 | beta = log(or)/sd_pgs |
| PPM019463 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08287 [0.98396133, 1.19171469] β: 0.07961 [-0.0161687, 0.17539318] |
AUROC: 0.52297 [0.49629776, 0.54965208] | R²: 0.00098 [0.0, 0.00425361] | 0 | beta = log(or)/sd_pgs |
| PPM019464 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14197 [1.11007941, 1.17478122] β: 0.13276 [0.10443155, 0.16108194] |
AUROC: 0.53789 [0.52982296, 0.5459495] | R²: 0.00364 [0.00225276, 0.00536145] | 0 | beta = log(or)/sd_pgs |
| PPM019466 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23115 [1.17806817, 1.28661969] β: 0.20795 [0.16387596, 0.25201838] |
AUROC: 0.55734 [0.54468967, 0.56999809] | R²: 0.0089 [0.00560709, 0.01298353] | 0 | beta = log(or)/sd_pgs |
| PPM019467 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10756 [1.07535568, 1.14073718] β: 0.10216 [0.07265147, 0.13167471] |
AUROC: 0.5292 [0.52067772, 0.53772878] | R²: 0.00216 [0.00102377, 0.00349455] | 0 | beta = log(or)/sd_pgs |
| PPM019468 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16199 [1.1474617, 1.17669591] β: 0.15013 [0.13755229, 0.16271043] |
AUROC: 0.5426 [0.53897714, 0.5462198] | R²: 0.00466 [0.00392453, 0.00548885] | 0 | beta = log(or)/sd_pgs |
| PPM019469 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13492 [1.03111003, 1.24918283] β: 0.12656 [0.03063592, 0.2224896] |
AUROC: 0.53686 [0.51016061, 0.56355653] | R²: 0.00246 [0.000238, 0.00707626] | 0 | beta = log(or)/sd_pgs |
| PPM019470 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1247 [1.09330509, 1.15699978] β: 0.11752 [0.08920531, 0.14583026] |
AUROC: 0.53363 [0.52552193, 0.54173886] | R²: 0.00286 [0.00168306, 0.0043577] | 0 | beta = log(or)/sd_pgs |
| PPM019471 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23606 [1.07905703, 1.41590013] β: 0.21193 [0.07608754, 0.34776547] |
AUROC: 0.56859 [0.52989812, 0.60728942] | R²: 0.00702 [0.000879, 0.01908019] | 0 | beta = log(or)/sd_pgs |
| PPM019472 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21946 [1.16691439, 1.27436893] β: 0.19841 [0.154363, 0.2424511] |
AUROC: 0.55462 [0.54203646, 0.56719931] | R²: 0.00811 [0.00490666, 0.01217568] | 0 | beta = log(or)/sd_pgs |
| PPM019473 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | β: 0.11337 [0.0838625, 0.14287805] OR: 1.12005 [1.08747936, 1.15358912] |
AUROC: 0.53265 [0.52410638, 0.54119598] | R²: 0.00266 [0.00137051, 0.00420657] | 0 | beta = log(or)/sd_pgs |
| PPM019474 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16971 [1.15508988, 1.18450788] β: 0.15675 [0.14417816, 0.16932739] |
AUROC: 0.54467 [0.54105858, 0.54827219] | R²: 0.00508 [0.00428569, 0.00597661] | 0 | beta = log(or)/sd_pgs |
| PPM019475 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09218 [0.99244315, 1.20193532] β: 0.08817 [-0.0075855, 0.18393302] |
AUROC: 0.52469 [0.49822599, 0.55115016] | R²: 0.0012 [0.0, 0.00477209] | 0 | beta = log(or)/sd_pgs |
| PPM019476 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1469 [1.11485209, 1.17987041] β: 0.13706 [0.10872174, 0.16540461] |
AUROC: 0.53902 [0.53097366, 0.54705807] | R²: 0.00388 [0.00235764, 0.00565486] | 0 | beta = log(or)/sd_pgs |
| PPM019477 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23492 [1.07805871, 1.41460106] β: 0.211 [0.07516194, 0.34684756] |
AUROC: 0.56842 [0.52959783, 0.60723511] | R²: 0.00696 [0.000789, 0.01932319] | 0 | beta = log(or)/sd_pgs |
| PPM019478 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21483 [1.16243507, 1.26958012] β: 0.1946 [0.15051701, 0.23868624] |
AUROC: 0.55421 [0.54154316, 0.56688511] | R²: 0.00779 [0.00457599, 0.01180516] | 0 | beta = log(or)/sd_pgs |
| PPM019479 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12262 [1.08997461, 1.15624017] β: 0.11566 [0.0861544, 0.1451735] |
AUROC: 0.53342 [0.52488642, 0.54195793] | R²: 0.00277 [0.00147025, 0.00431716] | 0 | beta = log(or)/sd_pgs |
| PPM019480 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17236 [1.15771305, 1.18719934] β: 0.15902 [0.14644655, 0.17159704] |
AUROC: 0.54524 [0.54162844, 0.54884559] | R²: 0.00523 [0.00440696, 0.00610806] | 0 | beta = log(or)/sd_pgs |
| PPM019481 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09524 [0.99518242, 1.20534758] β: 0.09097 [-0.0048292, 0.18676797] |
AUROC: 0.52535 [0.49869346, 0.55200012] | R²: 0.00128 [0.00000209, 0.00487633] | 0 | beta = log(or)/sd_pgs |
| PPM019482 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14508 [1.11308982, 1.17799207] β: 0.13548 [0.10713977, 0.16381135] |
AUROC: 0.53866 [0.53061568, 0.54669435] | R²: 0.00379 [0.00230863, 0.00554488] | 0 | beta = log(or)/sd_pgs |
| PPM019483 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.24252 [1.08479041, 1.42318679] β: 0.21714 [0.08138679, 0.35289857] |
AUROC: 0.56986 [0.53098801, 0.60872389] | R²: 0.00738 [0.000997, 0.02006623] | 0 | beta = log(or)/sd_pgs |
| PPM019484 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.22477 [1.1719543, 1.27996152] β: 0.20275 [0.1586727, 0.24683001] |
AUROC: 0.55628 [0.54365516, 0.56889903] | R²: 0.00845 [0.0051498, 0.01257724] | 0 | beta = log(or)/sd_pgs |
| PPM019485 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10211 [1.07007216, 1.13510722] β: 0.09723 [0.06772609, 0.12672711] |
AUROC: 0.52781 [0.51930204, 0.53632099] | R²: 0.00196 [0.00095, 0.00333554] | 0 | beta = log(or)/sd_pgs |
| PPM019486 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15335 [1.13893748, 1.16794189] β: 0.14267 [0.1300958, 0.15524313] |
AUROC: 0.54022 [0.53659848, 0.54383588] | R²: 0.00421 [0.00351947, 0.00498262] | 0 | beta = log(or)/sd_pgs |
| PPM019487 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14227 [1.03770693, 1.25736482] β: 0.13302 [0.03701341, 0.22901812] |
AUROC: 0.54029 [0.51369443, 0.56688289] | R²: 0.00272 [0.000301, 0.00753558] | 0 | beta = log(or)/sd_pgs |
| PPM019488 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.11617 [1.08500902, 1.14821592] β: 0.1099 [0.0815883, 0.13820937] |
AUROC: 0.53213 [0.52404907, 0.54020559] | R²: 0.0025 [0.00141635, 0.00391061] | 0 | beta = log(or)/sd_pgs |
| PPM019489 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23173 [1.07615164, 1.40980329] β: 0.20842 [0.07339138, 0.34345019] |
AUROC: 0.56612 [0.52672065, 0.60551542] | R²: 0.00686 [0.000655, 0.01792159] | 0 | beta = log(or)/sd_pgs |
| PPM019490 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.19231 [1.14094472, 1.24597857] β: 0.17589 [0.13185662, 0.21992122] |
AUROC: 0.54928 [0.53668704, 0.56187681] | R²: 0.00637 [0.00353314, 0.00992459] | 0 | beta = log(or)/sd_pgs |
| PPM019491 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10161 [1.06958778, 1.13458485] β: 0.09677 [0.06727333, 0.12626681] |
AUROC: 0.52784 [0.51933058, 0.53634845] | R²: 0.00194 [0.000893, 0.00326912] | 0 | beta = log(or)/sd_pgs |
| PPM019492 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15354 [1.13912614, 1.16813032] β: 0.14283 [0.13026142, 0.15540445] |
AUROC: 0.54048 [0.53685753, 0.54410481] | R²: 0.00422 [0.0034919, 0.00502618] | 0 | beta = log(or)/sd_pgs |
| PPM019493 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1249 [1.02197512, 1.23819444] β: 0.1177 [0.02173715, 0.21365422] |
AUROC: 0.5344 [0.5074307, 0.56137249] | R²: 0.00213 [0.000118, 0.00670413] | 0 | beta = log(or)/sd_pgs |
| PPM019494 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10581 [1.0749525, 1.13755428] β: 0.10058 [0.07227647, 0.12888059] |
AUROC: 0.52957 [0.52148152, 0.53766659] | R²: 0.00209 [0.00111885, 0.00347131] | 0 | beta = log(or)/sd_pgs |
| PPM019495 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23758 [1.08131404, 1.41642239] β: 0.21316 [0.078177, 0.34813425] |
AUROC: 0.56725 [0.52859169, 0.60591655] | R²: 0.00718 [0.000735, 0.0191671] | 0 | beta = log(or)/sd_pgs |
| PPM019496 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20497 [1.15317504, 1.25910106] β: 0.18646 [0.14251904, 0.23039802] |
AUROC: 0.55291 [0.54034145, 0.56548567] | R²: 0.00719 [0.00426528, 0.01097952] | 0 | beta = log(or)/sd_pgs |
| PPM019497 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09992 [1.06793864, 1.13285627] β: 0.09524 [0.06573028, 0.12474211] |
AUROC: 0.52666 [0.51816735, 0.53515816] | R²: 0.00188 [0.000883, 0.00325281] | 0 | beta = log(or)/sd_pgs |
| PPM019499 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.03582 [0.94136503, 1.13975765] β: 0.0352 [-0.0604243, 0.13081565] |
AUROC: 0.50962 [0.48298884, 0.53625086] | R²: 0.00019 [0.0, 0.00223248] | 0 | beta = log(or)/sd_pgs |
| PPM019500 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | β: 0.11869 [0.09034983, 0.14703744] OR: 1.12602 [1.09455712, 1.15839733] |
AUROC: 0.53372 [0.52560348, 0.541837] | R²: 0.00291 [0.00175846, 0.00438719] | 0 | beta = log(or)/sd_pgs |
| PPM019501 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.05895 [0.92378141, 1.21390666] β: 0.05728 [-0.0792798, 0.1938438] |
AUROC: 0.51989 [0.48202597, 0.55775222] | R²: 0.00051 [0.0, 0.00614416] | 0 | beta = log(or)/sd_pgs |
| PPM019502 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12993 [1.08122629, 1.18082159] β: 0.12215 [0.07809585, 0.16621046] |
AUROC: 0.53743 [0.52459314, 0.55027481] | R²: 0.00307 [0.00128569, 0.00553223] | 0 | beta = log(or)/sd_pgs |
| PPM019503 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10789 [1.07566831, 1.14107726] β: 0.10246 [0.07294215, 0.13197278] |
AUROC: 0.52857 [0.52001445, 0.53712397] | R²: 0.00217 [0.00104555, 0.00351577] | 0 | beta = log(or)/sd_pgs |
| PPM019504 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14267 [1.12839302, 1.15713496] β: 0.13337 [0.12079452, 0.14594709] |
AUROC: 0.53782 [0.53420355, 0.54143959] | R²: 0.00368 [0.00303669, 0.00446067] | 0 | beta = log(or)/sd_pgs |
| PPM019505 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10577 [1.00477493, 1.21692241] β: 0.10054 [0.00476357, 0.19632506] |
AUROC: 0.53471 [0.50835875, 0.56105638] | R²: 0.00156 [0.0000331, 0.00511287] | 0 | beta = log(or)/sd_pgs |
| PPM019506 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12027 [1.08897574, 1.15246834] β: 0.11357 [0.08523757, 0.14190602] |
AUROC: 0.5326 [0.52447165, 0.54073587] | R²: 0.00266 [0.00147464, 0.00427621] | 0 | beta = log(or)/sd_pgs |
| PPM019507 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18187 [1.03090876, 1.35493138] β: 0.1671 [0.0304407, 0.30375081] |
AUROC: 0.55554 [0.51834024, 0.59273181] | R²: 0.00431 [0.000121, 0.01349001] | 0 | beta = log(or)/sd_pgs |
| PPM019508 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17792 [1.12708219, 1.2310461] β: 0.16375 [0.11963216, 0.2078643] |
AUROC: 0.5452 [0.53247659, 0.557919] | R²: 0.00551 [0.00285031, 0.0090806] | 0 | beta = log(or)/sd_pgs |
| PPM020119 | PGS004186 (afib_1) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.73831 | — | year of birth, sex | — |
| PPM020120 | PGS004186 (afib_1) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.73501 | — | year of birth, sex | — |
| PPM020121 | PGS004187 (afib_2) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.74377 | — | year of birth, sex | — |
| PPM020122 | PGS004188 (afib_3) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.73914 | — | year of birth, sex | — |
| PPM020123 | PGS004189 (afib_4) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.74461 | — | year of birth, sex | — |
| PPM020124 | PGS004190 (afib_5) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Hypertension | — | AUROC: 0.69573 | — | year of birth, sex | — |
| PPM020126 | PGS004192 (hyper_2) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Hypertension | — | AUROC: 0.70254 | — | year of birth, sex | — |
| PPM020127 | PGS004193 (hyper_3) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Hypertension | — | AUROC: 0.70358 | — | year of birth, sex | — |
| PPM020128 | PGS004194 (hyper_4) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Hypertension | — | AUROC: 0.69503 | — | year of birth, sex | — |
| PPM020129 | PGS004195 (hyper_5) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Coronary artery disease | — | AUROC: 0.75746 | — | year of birth, sex | — |
| PPM020130 | PGS004196 (cad_1) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Coronary artery disease | — | AUROC: 0.74561 | — | year of birth, sex | — |
| PPM020131 | PGS004197 (cad_2) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Coronary artery disease | — | AUROC: 0.75684 | — | year of birth, sex | — |
| PPM020132 | PGS004198 (cad_3) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Coronary artery disease | — | AUROC: 0.75212 | — | year of birth, sex | — |
| PPM020133 | PGS004199 (cad_4) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Coronary artery disease | — | AUROC: 0.75031 | — | year of birth, sex | — |
| PPM020253 | PGS004234 (HTN_PAN-UKBB) |
PSS011312| Multi-ancestry (including European)| 39,035 individuals |
PGP000531 | Kurniansyah N et al. Nat Commun (2022) |
Reported Trait: Prevelant hypertension | — | AUROC: 0.763 [0.75, 0.775] | — | sex, age, age2, study site, race/ethnic background, smoking status, BMI, and 11 ancestral principal components | — |
| PPM020255 | PGS004236 (HTN_Unweighted_PRSsum) |
PSS011312| Multi-ancestry (including European)| 39,035 individuals |
PGP000531 | Kurniansyah N et al. Nat Commun (2022) |
Reported Trait: Prevelant hypertension | OR: 2.1 [1.99, 2.21] | AUROC: 0.764 [0.751, 0.777] | — | sex, age, age2, study site, race/ethnic background, smoking status, BMI, and 11 ancestral principal components | PRSsum based on selected CV-PRS (which summed the CV-PRS from the three phenotypes). |
| PPM020256 | PGS004236 (HTN_Unweighted_PRSsum) |
PSS011312| Multi-ancestry (including European)| 39,035 individuals |
PGP000531 | Kurniansyah N et al. Nat Commun (2022) |
Reported Trait: New-onset hypertension (normotensive) | OR: 1.72 [1.55, 1.91] | AUROC: 0.656 | — | sex, age, age2, study site, race/ethnic background, smoking status, BMI, and 11 ancestral principal components | PRSsum based on selected CV-PRS (which summed the CV-PRS from the three phenotypes). |
| PPM020257 | PGS004236 (HTN_Unweighted_PRSsum) |
PSS011312| Multi-ancestry (including European)| 39,035 individuals |
PGP000531 | Kurniansyah N et al. Nat Commun (2022) |
Reported Trait: New-onset hypertension (elevated) | OR: 1.48 [1.27, 1.71] | AUROC: 0.582 | — | sex, age, age2, study site, race/ethnic background, smoking status, BMI, and 11 ancestral principal components | PRSsum based on selected CV-PRS (which summed the CV-PRS from the three phenotypes). |
| PPM020258 | PGS004237 (CAD_PRS_LDpred_UKB_Pub1) |
PSS011313| European Ancestry| 403,422 individuals |
PGP000532 | Manikpurage HD et al. Circ Genom Precis Med (2021) |
Reported Trait: Prevalent Coronary Artery Disease | OR: 1.56 [1.56, 1.58] | AUROC: 0.766 | R²: 0.158 | Age, Sex and Genetic Principal Components (1 to 10) | — |
| PPM020259 | PGS004237 (CAD_PRS_LDpred_UKB_Pub1) |
PSS011313| European Ancestry| 403,422 individuals |
PGP000532 | Manikpurage HD et al. Circ Genom Precis Med (2021) |
Reported Trait: Prevalent Myocardial Infarction | OR: 1.63 [1.6, 1.65] | AUROC: 0.772 | R²: 0.129 | Age, Sex and Genetic Principal Components (1 to 10) | — |
| PPM020260 | PGS004237 (CAD_PRS_LDpred_UKB_Pub1) |
PSS011313| European Ancestry| 403,422 individuals |
PGP000532 | Manikpurage HD et al. Circ Genom Precis Med (2021) |
Reported Trait: Prevalent Myocardial Infarction and Coronary Revascularization procedure | OR: 1.73 [1.7, 1.76] | AUROC: 0.789 | R²: 0.162 | Age, Sex and Genetic Principal Components (1 to 10) | — |
| PPM020261 | PGS004237 (CAD_PRS_LDpred_UKB_Pub1) |
PSS011313| European Ancestry| 403,422 individuals |
PGP000532 | Manikpurage HD et al. Circ Genom Precis Med (2021) |
Reported Trait: Incident Myocardial Infarction | HR: 1.53 [1.49, 1.56] | C-index: 0.729 | — | Age, Sex and Genetic Principal Components (1 to 10) | — |
| PPM020262 | PGS004237 (CAD_PRS_LDpred_UKB_Pub1) |
PSS011313| European Ancestry| 403,422 individuals |
PGP000532 | Manikpurage HD et al. Circ Genom Precis Med (2021) |
Reported Trait: Mortality | HR: 1.08 [1.06, 1.09] | — | — | Age, Sex and Genetic Principal Components (1 to 10) | — |
| PPM020267 | PGS000013 (GPS_CAD) |
PSS011315| East Asian Ancestry| 901 individuals |
PGP000534 | Bhak Y et al. PLoS One (2021) |Ext. |
Reported Trait: Early onset acute myocardial infarction following percutaneous coronary intervention | OR: 1.83 [1.69, 1.99] | AUROC: 0.65 [0.61, 0.69] | — | — | — |
| PPM020269 | PGS000013 (GPS_CAD) |
PSS011316| East Asian Ancestry| 197 individuals |
PGP000534 | Bhak Y et al. PLoS One (2021) |Ext. |
Reported Trait: Cumulative event of repeat revascularization following percutaneous coronary intervention | HR: 1.64 [1.12, 2.38] | — | Hazard ratio (HR, top 50% vs bottom 50%): 2.19 [1.47, 2.36] | — | — |
| PPM020270 | PGS000013 (GPS_CAD) |
PSS011316| East Asian Ancestry| 197 individuals |
PGP000534 | Bhak Y et al. PLoS One (2021) |Ext. |
Reported Trait: Cumulative event of repeat revascularization following percutaneous coronary intervention | HR: 1.65 [1.11, 2.46] | — | — | Body mass index, hypertension, current smoking, diabetes mellitus, hypercholesterolemia, family history of coronary artery disease | — |
| PPM020271 | PGS004238 (wGRS35) |
PSS011317| East Asian Ancestry| 385 individuals |
PGP000535 | Cheng CF et al. J Gene Med (2021) |
Reported Trait: Cardiovascular disease in patients with type II diabetes Mellitus | — | AUROC: 0.666 [0.595, 0.737] | — | — | — |
| PPM020272 | PGS004238 (wGRS35) |
PSS011317| East Asian Ancestry| 385 individuals |
PGP000535 | Cheng CF et al. J Gene Med (2021) |
Reported Trait: Cardiovascular disease in patients with type II diabetes Mellitus | — | AUROC: 0.78 [0.717, 0.843] | — | Age, gender, body mass index | — |
| PPM020273 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS011318| African Ancestry| 18,505 individuals |
PGP000536 | Vassy JL et al. JAMA Cardiol (2023) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.05 [0.95, 1.17] | — | — | age, sex, and principal components of genetic ancestry | — |
| PPM020274 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS011319| Hispanic or Latin American Ancestry| 6,785 individuals |
PGP000536 | Vassy JL et al. JAMA Cardiol (2023) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.08 [0.85, 1.36] | — | — | age, sex, and principal components of genetic ancestry | — |
| PPM020275 | PGS002724 (GIGASTROKE_iPGS_EUR) |
PSS011320| European Ancestry| 53,861 individuals |
PGP000536 | Vassy JL et al. JAMA Cardiol (2023) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.15 [1.08, 1.21] | — | — | age, sex, and principal components of genetic ancestry | — |
| PPM020276 | PGS002244 (ldpred_cad) |
PSS011318| African Ancestry| 18,505 individuals |
PGP000536 | Vassy JL et al. JAMA Cardiol (2023) |Ext. |
Reported Trait: Incident myocardial infarction | HR: 1.1 [1.02, 1.19] | — | — | age, sex, and principal components of genetic ancestry | — |
| PPM020277 | PGS002244 (ldpred_cad) |
PSS011319| Hispanic or Latin American Ancestry| 6,785 individuals |
PGP000536 | Vassy JL et al. JAMA Cardiol (2023) |Ext. |
Reported Trait: Incident myocardial infarction | HR: 1.26 [1.09, 1.46] | — | — | age, sex, and principal components of genetic ancestry | — |
| PPM020278 | PGS002244 (ldpred_cad) |
PSS011320| European Ancestry| 53,861 individuals |
PGP000536 | Vassy JL et al. JAMA Cardiol (2023) |Ext. |
Reported Trait: Incident myocardial infarction | HR: 1.23 [1.18, 1.29] | — | — | age, sex, and principal components of genetic ancestry | — |
| PPM020125 | PGS004191 (hyper_1) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Hypertension | — | AUROC: 0.70167 | — | year of birth, sex | — |
| PPM020134 | PGS004200 (cad_5) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Lipoprotein A | — | — | R²: 0.57648 | year of birth, sex | — |
| PPM020268 | PGS000013 (GPS_CAD) |
PSS011315| East Asian Ancestry| 901 individuals |
PGP000534 | Bhak Y et al. PLoS One (2021) |Ext. |
Reported Trait: Early onset acute myocardial infarction following percutaneous coronary intervention | — | AUROC: 0.92 [0.9, 0.94] | — | Current smoking, hypercholesterolemia, body mass index, hypertension, family history of coronary artery disease, diabetes mellitus | significant contribution of the PRS to the risk factor model p=0.015 |
| PPM017103 | PGS003429 (AAA) |
PSS010126| European Ancestry| 91,731 individuals |
PGP000436 | Kelemen M et al. Nat Commun (2024) |
Reported Trait: Abdominal aortic aneurysm | — | AUROC: 0.708 [0.691, 0.725] | R²: 0.00547 | — | — |
| PPM020358 | PGS004290 (GenoBoost_atrial_fibrillation_0) |
PSS011337| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.75753 | Covariate-adjusted pseudo-R2: 0.03378 AUPRC: 0.75753 |
age, sex, PC1-10 | — |
| PPM020359 | PGS004291 (GenoBoost_atrial_fibrillation_1) |
PSS011337| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.75566 | Covariate-adjusted pseudo-R2: 0.03105 AUPRC: 0.75566 |
age, sex, PC1-10 | — |
| PPM020360 | PGS004292 (GenoBoost_atrial_fibrillation_2) |
PSS011337| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.75591 | Covariate-adjusted pseudo-R2: 0.03151 AUPRC: 0.75591 |
age, sex, PC1-10 | — |
| PPM020361 | PGS004293 (GenoBoost_atrial_fibrillation_3) |
PSS011337| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.75627 | Covariate-adjusted pseudo-R2: 0.03251 AUPRC: 0.75627 |
age, sex, PC1-10 | — |
| PPM019461 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12873 [1.09591702, 1.16253397] β: 0.1211 [0.09159147, 0.15060208] |
AUROC: 0.53509 [0.52657818, 0.54361127] | R²: 0.00303 [0.00161439, 0.00460309] | 0 | beta = log(or)/sd_pgs |
| PPM019465 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18096 [1.03046264, 1.35342652] β: 0.16632 [0.03000786, 0.30263954] |
AUROC: 0.55516 [0.51584288, 0.59448045] | R²: 0.00429 [0.000133, 0.01465822] | 0 | beta = log(or)/sd_pgs |
| PPM019498 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti R et al. Am J Hum Genet (2024) |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12015 [1.10615947, 1.134316] β: 0.11346 [0.10089408, 0.12602982] |
AUROC: 0.53218 [0.52855431, 0.53580164] | R²: 0.00266 [0.00209727, 0.00327205] | 0 | beta = log(or)/sd_pgs |
| PPM020373 | PGS004305 (GenoBoost_coronary_artery_disease_0) |
PSS011339| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Coronary artery disease | — | AUROC: 0.75531 | Covariate-adjusted pseudo-R2: 0.02237 AUPRC: 0.75531 |
age, sex, PC1-10 | — |
| PPM020375 | PGS004307 (GenoBoost_coronary_artery_disease_2) |
PSS011339| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Coronary artery disease | — | AUROC: 0.75669 | Covariate-adjusted pseudo-R2: 0.0242 AUPRC: 0.75669 |
age, sex, PC1-10 | — |
| PPM020376 | PGS004308 (GenoBoost_coronary_artery_disease_3) |
PSS011339| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Coronary artery disease | — | AUROC: 0.75454 | Covariate-adjusted pseudo-R2: 0.02173 AUPRC: 0.75454 |
age, sex, PC1-10 | — |
| PPM020377 | PGS004309 (GenoBoost_coronary_artery_disease_4) |
PSS011339| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Coronary artery disease | — | AUROC: 0.75719 | Covariate-adjusted pseudo-R2: 0.02427 AUPRC: 0.75719 |
age, sex, PC1-10 | — |
| PPM020426 | PGS004321 (PRS27_CAD) |
PSS011357| European Ancestry| 14,298 individuals |
PGP000554 | Marston NA et al. Circulation (2019) |
Reported Trait: Major vascular events (placebo arm) | HR: 1.1 [1.03, 1.18] | — | — | — | — |
| PPM020427 | PGS004321 (PRS27_CAD) |
PSS011357| European Ancestry| 14,298 individuals |
PGP000554 | Marston NA et al. Circulation (2019) |
Reported Trait: Major coronary events (placebo arm) | HR: 1.17 [1.08, 1.26] | — | — | — | — |
| PPM020428 | PGS004321 (PRS27_CAD) |
PSS011357| European Ancestry| 14,298 individuals |
PGP000554 | Marston NA et al. Circulation (2019) |
Reported Trait: Major vascular events (evolocumab vs placebo) | — | — | p-value (pvalue, evolocumab and high PRS vs. placebo and low PRS): 0.07 | — | — |
| PPM020429 | PGS004322 (GRS30_IS) |
PSS011358| European Ancestry| 454,493 individuals |
PGP000555 | McElligott B et al. Front Cardiovasc Med (2023) |
Reported Trait: Incident ischaemic stroke | HR: 1.26 [1.17, 1.35] | — | — | age, gender, 10-yr ASCVD Risk by PCE, genetic background, and sepsis | — |
| PPM020430 | PGS004322 (GRS30_IS) |
PSS011358| European Ancestry| 454,493 individuals |
PGP000555 | McElligott B et al. Front Cardiovasc Med (2023) |
Reported Trait: Any incident myocardial infarction, ischaemic stroke, or venous thromboembolism | HR: 1.05 [1.01, 1.1] | — | — | age, gender, 10-yr ASCVD Risk by PCE, genetic background, and sepsis | — |
| PPM020555 | PGS004440 (disease.Atrial_fibrillation.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Atrial fibrillation | OR: 1.28672 | — | — | — | — |
| PPM020558 | PGS004443 (disease.CAD.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Coronary artery disease (CAD) | OR: 1.48578 | — | — | — | — |
| PPM020559 | PGS004444 (disease.CVD.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Coronary vascular disease (CVD) | OR: 1.28186 | — | — | — | — |
| PPM020570 | PGS004455 (disease.Hypertension.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Hypertension | OR: 1.54004 | — | — | — | — |
| PPM020573 | PGS004458 (disease.I21.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I21 (Acute myocardial infarction) | OR: 1.28137 | — | — | — | — |
| PPM020574 | PGS004459 (disease.I25.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I25 (Chronic ischaemic heart disease) | OR: 1.35918 | — | — | — | — |
| PPM020575 | PGS004460 (disease.I26.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I26 (Pulmonary embolism) | OR: 1.16684 | — | — | — | — |
| PPM020576 | PGS004461 (disease.I48.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I48 (Atrial fibrillation and flutter) | OR: 1.34588 | — | — | — | — |
| PPM020577 | PGS004462 (disease.I50.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I50 (Heart failure) | OR: 1.15815 | — | — | — | — |
| PPM020579 | PGS004464 (disease.I84.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I84 (Haemorrhoids) | OR: 1.13492 | — | — | — | — |
| PPM020616 | PGS004501 (disease.VTE.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Venous thromboembolism (VTE) | OR: 1.25405 | — | — | — | — |
| PPM020625 | PGS004510 (meta.Atrial_fibrillation.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Atrial fibrillation | OR: 1.2456 | — | — | — | — |
| PPM020628 | PGS004513 (meta.CAD.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Coronary artery disease (CAD) | OR: 1.57686 | — | — | — | — |
| PPM020629 | PGS004514 (meta.CVD.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Coronary vascular disease (CVD) | OR: 1.34059 | — | — | — | — |
| PPM020640 | PGS004525 (meta.Hypertension.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Hypertension | OR: 1.57854 | — | — | — | — |
| PPM020643 | PGS004528 (meta.I21.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I21 (Acute myocardial infarction) | OR: 1.39148 | — | — | — | — |
| PPM020644 | PGS004529 (meta.I25.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I25 (Chronic ischaemic heart disease) | OR: 1.44467 | — | — | — | — |
| PPM020645 | PGS004530 (meta.I26.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I26 (Pulmonary embolism) | OR: 1.24245 | — | — | — | — |
| PPM020646 | PGS004531 (meta.I48.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I48 (Atrial fibrillation and flutter) | OR: 1.27953 | — | — | — | — |
| PPM020647 | PGS004532 (meta.I50.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I50 (Heart failure) | OR: 1.26713 | — | — | — | — |
| PPM020649 | PGS004534 (meta.I84.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I84 (Haemorrhoids) | OR: 1.15041 | — | — | — | — |
| PPM020706 | PGS000016 (GPS_AF) |
PSS011375| Multi-ancestry (including European)| 95 individuals |
PGP000565 | Al-Kaisey A et al. Heart Rhythm (2023) |Ext. |
Reported Trait: Complex signals on electrogram | — | — | beta (PRS above mean vs PRS below mean): 0.24 | Age, sex, persistent atrial fibrillation, atrial fibrillation duration | — |
| PPM020713 | PGS000013 (GPS_CAD) |
PSS011380| European Ancestry| 1,863 individuals |
PGP000568 | Khan SS et al. Circulation (2022) |Ext. |
Reported Trait: Incident coronary heart diseaase | HR: 1.82 [1.56, 2.12] | — | — | 30-year traditional risk factor score linear predictor | — |
| PPM020714 | PGS000013 (GPS_CAD) |
PSS011379| European Ancestry| 2,154 individuals |
PGP000568 | Khan SS et al. Circulation (2022) |Ext. |
Reported Trait: Incident coronary heart diseaase | HR: 1.6 [1.43, 1.79] | — | — | 30-year traditional risk factor score linear predictor | — |
| PPM020715 | PGS000013 (GPS_CAD) |
PSS011378| European Ancestry| 5,740 individuals |
PGP000568 | Khan SS et al. Circulation (2022) |Ext. |
Reported Trait: Incident coronary heart diseaase | HR: 1.16 [1.09, 1.23] | — | — | 30-year traditional risk factor score linear predictor | — |
| PPM020716 | PGS000013 (GPS_CAD) |
PSS011380| European Ancestry| 1,863 individuals |
PGP000568 | Khan SS et al. Circulation (2022) |Ext. |
Reported Trait: Incident coronary heart diseaase | HR: 1.98 [1.7, 2.3] | C-index: 0.73 | — | Age, sex | — |
| PPM020778 | PGS000035 (PRS_AF) |
PSS011403| Multi-ancestry (including European)| 3,335 individuals |
PGP000586 | Khurshid S et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Incident atrial fibrillation | HR: 1.49 [1.3, 1.71] | C-index: 0.617 [0.574, 0.66] | R²: 0.016 [0.004, 0.027] | — | — |
| PPM020717 | PGS000013 (GPS_CAD) |
PSS011379| European Ancestry| 2,154 individuals |
PGP000568 | Khan SS et al. Circulation (2022) |Ext. |
Reported Trait: Incident coronary heart diseaase | HR: 1.64 [1.47, 1.84] | C-index: 0.66 | — | Age, sex | — |
| PPM020718 | PGS000013 (GPS_CAD) |
PSS011378| European Ancestry| 5,740 individuals |
PGP000568 | Khan SS et al. Circulation (2022) |Ext. |
Reported Trait: Incident coronary heart diseaase | HR: 1.22 [1.15, 1.3] | C-index: 0.66 | — | Age, sex | — |
| PPM020686 | PGS004571 (meta.VTE.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Venous thromboembolism (VTE) | OR: 1.21176 | — | — | — | — |
| PPM020704 | PGS000016 (GPS_AF) |
PSS011375| Multi-ancestry (including European)| 95 individuals |
PGP000565 | Al-Kaisey A et al. Heart Rhythm (2023) |Ext. |
Reported Trait: Arrhythmia-free survival following catheter ablation | — | — | Hazard ratio (HR, PRS above mean vs PRS below mean): 1.8 [0.9, 3.3] | — | — |
| PPM020705 | PGS000016 (GPS_AF) |
PSS011375| Multi-ancestry (including European)| 95 individuals |
PGP000565 | Al-Kaisey A et al. Heart Rhythm (2023) |Ext. |
Reported Trait: Left atrial conduction heterogeneity on electrogram | — | — | beta (PRS above mean vs PRS below mean): 0.26 [0.02, 0.55] | Age, sex, persistent atrial fibrillation, atrial fibrillation duration | — |
| PPM020743 | PGS004593 (pe) |
PSS011387| European Ancestry| 138,317 individuals |
PGP000574 | Nurkkala J et al. J Hypertens (2022) |
Reported Trait: Gestational hypertension | HR: 1.16 [1.14, 1.19] | — | — | Collection year, genotyping batch, and the first 10 genetic principal components | — |
| PPM020744 | PGS004593 (pe) |
PSS011388| European Ancestry| 136,354 individuals |
PGP000574 | Nurkkala J et al. J Hypertens (2022) |
Reported Trait: Preeclampsia | HR: 1.21 [1.18, 1.24] | — | — | Collection year, genotyping batch, and the first 10 genetic principal components | — |
| PPM020745 | PGS004595 (PRS_CHD) |
PSS011389| European Ancestry| 21,824 individuals |
PGP000575 | Oni-Orisan A et al. Clin Pharmacol Ther (2022) |
Reported Trait: Myocardial infarction in non-statin users | HR: 1.59 [1.42, 1.78] | — | — | Age, sex, hypertension, diabetes, and cigarette smoking status | — |
| PPM020746 | PGS004595 (PRS_CHD) |
PSS011389| European Ancestry| 21,824 individuals |
PGP000575 | Oni-Orisan A et al. Clin Pharmacol Ther (2022) |
Reported Trait: Major adverse cardiovascular event in non-statin users | HR: 1.35 [1.25, 1.46] | — | — | Age, sex, hypertension, diabetes, and cigarette smoking status | — |
| PPM020747 | PGS004598 (PRS12_HF) |
PSS011390| Multi-ancestry (including European)| 13,348 individuals |
PGP000576 | Peng H et al. Nutrients (2023) |
Reported Trait: Incident heart failure in breast cancer survivors | — | — | Hazard ratio (HR, top 50% vs bottom 50% of PRS): 1.4 [1.06, 1.84] | Age at diagnosis of breast cancer, race, Townsend Deprivation Index, diabetes, hypertension, antihypertensive medications, insulin treatment, lipid treatments, hormone replacement therapy, menopause, surgical treatment of breast cancer, genetic testing batches, 10 PCs | — |
| PPM020748 | PGS004596 (PRS64_CHD) |
PSS011390| Multi-ancestry (including European)| 13,348 individuals |
PGP000576 | Peng H et al. Nutrients (2023) |
Reported Trait: Incident coronary artery disease in breast cancer survivors | — | — | Hazard ratio (HR, top 50% vs bottom 50% of PRS): 1.36 [1.1, 1.67] | Age at diagnosis of breast cancer, race, Townsend Deprivation Index, diabetes, hypertension, antihypertensive medications, insulin treatment, lipid treatments, hormone replacement therapy, menopause, surgical treatment of breast cancer, genetic testing batches, 10 PCs | — |
| PPM020749 | PGS004597 (PRS32_IS) |
PSS011390| Multi-ancestry (including European)| 13,348 individuals |
PGP000576 | Peng H et al. Nutrients (2023) |
Reported Trait: Incident ischaemic stroke in breast cancer survivors | — | — | Hazard ratio (HR, top 50% vs bottom 50% of PRS): 1.25 [0.91, 1.72] | Age at diagnosis of breast cancer, race, Townsend Deprivation Index, diabetes, hypertension, antihypertensive medications, insulin treatment, lipid treatments, hormone replacement therapy, menopause, surgical treatment of breast cancer, genetic testing batches, 10 PCs | — |
| PPM020750 | PGS004598 (PRS12_HF) |
PSS011390| Multi-ancestry (including European)| 13,348 individuals |
PGP000576 | Peng H et al. Nutrients (2023) |
Reported Trait: Incident heart failure in breast cancer survivors with lifestyle | — | — | Hazard ratio (HR, unhealthy lifestyle and PRS in top 50% vs healthy lifestyle and PRS in bottom 50%): 0.39 [0.21, 0.73] | Age at diagnosis of breast cancer, race, Townsend Deprivation Index, diabetes, hypertension, antihypertensive medications, insulin treatment, lipid treatments, hormone replacement therapy, menopause, surgical treatment of breast cancer, genetic testing batches, 10 PCs | — |
| PPM020751 | PGS004596 (PRS64_CHD) |
PSS011390| Multi-ancestry (including European)| 13,348 individuals |
PGP000576 | Peng H et al. Nutrients (2023) |
Reported Trait: Incident coronary artery disease in breast cancer survivors with lifestyle | — | — | Hazard ratio (HR, unhealthy lifestyle and PRS in top 50% vs healthy lifestyle and PRS in bottom 50%): 0.37 [0.24, 0.56] | Age at diagnosis of breast cancer, race, Townsend Deprivation Index, diabetes, hypertension, antihypertensive medications, insulin treatment, lipid treatments, hormone replacement therapy, menopause, surgical treatment of breast cancer, genetic testing batches, 10 PCs | — |
| PPM020752 | PGS004597 (PRS32_IS) |
PSS011390| Multi-ancestry (including European)| 13,348 individuals |
PGP000576 | Peng H et al. Nutrients (2023) |
Reported Trait: Incident ischaemic stroke in breast cancer survivors with lifestyle | — | — | Hazard ratio (HR, unhealthy lifestyle and PRS in top 50% vs healthy lifestyle and PRS in bottom 50%): 0.37 [0.15, 0.93] | Age at diagnosis of breast cancer, race, Townsend Deprivation Index, diabetes, hypertension, antihypertensive medications, insulin treatment, lipid treatments, hormone replacement therapy, menopause, surgical treatment of breast cancer, genetic testing batches, 10 PCs | — |
| PPM020787 | PGS004612 (PRSECG_AI) |
PSS011412| Multi-ancestry (including European)| 424,411 individuals |
PGP000591 | Wang X et al. Circ Genom Precis Med (2023) |
Reported Trait: 5-year incident atrial fibrillation | HR: 1.07 [1.04, 1.09] | C-index: 0.738 | — | Age at enrollment, sex, genotyping array, 20 PCs of ancestry | — |
| PPM020788 | PGS004613 (PRSCHARGE_AF) |
PSS011412| Multi-ancestry (including European)| 424,411 individuals |
PGP000591 | Wang X et al. Circ Genom Precis Med (2023) |
Reported Trait: 5-year incident atrial fibrillation | HR: 1.12 [1.09, 1.14] | C-index: 0.739 | — | Age at enrollment, sex, genotyping array, 20 PCs of ancestry | — |
| PPM020775 | PGS000035 (PRS_AF) |
PSS011406| Multi-ancestry (including European)| 473,681 individuals |
PGP000586 | Khurshid S et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Incident atrial fibrillation | HR: 1.34 [1.31, 1.37] | C-index: 0.584 [0.577, 0.59] | R²: 0.004 [0.004, 0.005] | — | — |
| PPM020776 | PGS000035 (PRS_AF) |
PSS011404| European Ancestry| 10,560 individuals |
PGP000586 | Khurshid S et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Incident atrial fibrillation | HR: 1.48 [1.31, 1.66] | C-index: 0.615 [0.579, 0.65] | R²: 0.011 [0.004, 0.018] | — | — |
| PPM020777 | PGS000035 (PRS_AF) |
PSS011405| Multi-ancestry (including European)| 55,517 individuals |
PGP000586 | Khurshid S et al. Circ Genom Precis Med (2021) |Ext. |
Reported Trait: Incident atrial fibrillation | HR: 1.28 [1.21, 1.35] | C-index: 0.569 [0.554, 0.584] | R²: 0.003 [0.002, 0.005] | — | — |
| PPM020882 | PGS003356 (1MH_CAD_PRS_2022_Ldpred) |
PSS011442| European Ancestry| 564 individuals |
PGP000599 | Guarischi-Sousa R et al. Circ Genom Precis Med (2023) |Ext. |
Reported Trait: Raised coronary lesion | OR: 1.44 [1.18, 1.76] | — | — | — | — |
| PPM020897 | PGS003356 (1MH_CAD_PRS_2022_Ldpred) |
PSS011441| African Ancestry| 504 individuals |
PGP000599 | Guarischi-Sousa R et al. Circ Genom Precis Med (2023) |Ext. |
Reported Trait: Raised coronary lesion | OR: 1.0 [0.81, 1.24] | — | — | — | — |
| PPM020903 | PGS004697 (eur_anc_hg37CSx) |
PSS011448| European Ancestry| 52,702 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.55 [1.5, 1.6] | AUROC: 0.773 | — | age, sex, 10 PCs | — |
| PPM020904 | PGS004696 (multi_anc_hg37CSx) |
PSS011448| European Ancestry| 52,702 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.65 [1.59, 1.71] | AUROC: 0.774 | — | age, sex, 10 PCs | — |
| PPM020905 | PGS004697 (eur_anc_hg37CSx) |
PSS011446| African Ancestry| 17,008 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.25 [1.17, 1.33] | AUROC: 0.734 | — | age, sex, 10 PCs | — |
| PPM020906 | PGS004696 (multi_anc_hg37CSx) |
PSS011446| African Ancestry| 17,008 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.2 [1.15, 1.26] | AUROC: 0.736 | — | age, sex, 10 PCs | — |
| PPM020907 | PGS004697 (eur_anc_hg37CSx) |
PSS011449| Hispanic or Latin American Ancestry| 6,138 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.52 [1.36, 1.71] | AUROC: 0.708 | — | age, sex, 10 PCs | — |
| PPM020908 | PGS004696 (multi_anc_hg37CSx) |
PSS011449| Hispanic or Latin American Ancestry| 6,138 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.51 [1.35, 1.69] | AUROC: 0.706 | — | age, sex, 10 PCs | — |
| PPM020909 | PGS004697 (eur_anc_hg37CSx) |
PSS011447| East Asian Ancestry| 22,751 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.51 [1.44, 1.59] | AUROC: 0.756 | — | age, sex, 10 PCs | — |
| PPM020910 | PGS004696 (multi_anc_hg37CSx) |
PSS011447| East Asian Ancestry| 22,751 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.59 [1.54, 1.64] | AUROC: 0.762 | — | age, sex, 10 PCs | — |
| PPM020911 | PGS004697 (eur_anc_hg37CSx) |
PSS011450| South Asian Ancestry| 9,178 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 2.47 [2.23, 2.73] | AUROC: 0.803 | — | age, sex, 10 PCs | — |
| PPM020912 | PGS004696 (multi_anc_hg37CSx) |
PSS011450| South Asian Ancestry| 9,178 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 2.67 [2.39, 3.01] | AUROC: 0.803 | — | age, sex, 10 PCs | — |
| PPM020913 | PGS004698 (multi_anc_hg37PT) |
PSS011448| European Ancestry| 52,702 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.65 [1.59 -1.72) | AUROC: 0.773 | — | age, sex, 10 PCs | — |
| PPM020914 | PGS004698 (multi_anc_hg37PT) |
PSS011446| African Ancestry| 17,008 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.16 [1.11, 1.21] | AUROC: 0.735 | — | age, sex, 10 PCs | — |
| PPM020915 | PGS004698 (multi_anc_hg37PT) |
PSS011449| Hispanic or Latin American Ancestry| 6,138 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.38 [1.24, 1.54] | AUROC: 0.699 | — | age, sex, 10 PCs | — |
| PPM020916 | PGS004698 (multi_anc_hg37PT) |
PSS011447| East Asian Ancestry| 22,751 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 1.56 [1.5, 1.61] | AUROC: 0.748 | — | age, sex, 10 PCs | — |
| PPM020880 | PGS003332 (PRS_VTE_EUR_GHOUSE) |
PSS011439| Multi-ancestry (including European)| 70,406 individuals |
PGP000597 | Shi Z et al. Thromb Res (2023) |Ext. |
Reported Trait: Incident cancer-associated thrombosis | — | — | Hazard ratio (HR, top PRS decile vs rest): 1.75 [1.62, 1.88] | Age, gender, BMI and 10 PCs | — |
| PPM020917 | PGS004698 (multi_anc_hg37PT) |
PSS011450| South Asian Ancestry| 9,178 individuals |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Reported Trait: Incident coronary heart disease | OR: 2.75 [2.41, 3.14] | AUROC: 0.786 | — | age, sex, 10 PCs | — |
| PPM020571 | PGS004456 (disease.I10.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I10 (Essential (primary) hypertension) | OR: 1.47509 | — | — | — | — |
| PPM020641 | PGS004526 (meta.I10.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: I10 (Essential (primary) hypertension) | OR: 1.54547 | — | — | — | — |
| PPM020930 | PGS004705 (afib_PRSmix_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Atrial Fibrillation | — | — | Incremental R2 (Full model versus model with only covariates): 0.042 [0.034, 0.05] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM020931 | PGS004706 (afib_PRSmixPlus_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Atrial Fibrillation | — | — | Incremental R2 (Full model versus model with only covariates): 0.044 [0.036, 0.053] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM020968 | PGS004743 (cad_PRSmix_eur) |
PSS011487| European Ancestry| 7,465 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Coronary artery disease | — | — | Incremental R2 (Full model versus model with only covariates): 0.039 [0.03, 0.048] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM020969 | PGS004744 (cad_PRSmix_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Coronary artery disease | — | — | Incremental R2 (Full model versus model with only covariates): 0.014 [0.009, 0.019] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM020970 | PGS004745 (cad_PRSmixPlus_eur) |
PSS011487| European Ancestry| 7,465 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Coronary artery disease | — | — | Incremental R2 (Full model versus model with only covariates): 0.05 [0.04, 0.059] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM020971 | PGS004746 (cad_PRSmixPlus_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Coronary artery disease | — | — | Incremental R2 (Full model versus model with only covariates): 0.02 [0.014, 0.026] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021010 | PGS004785 (HTN_PRSmix_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Hypertension | — | — | Incremental R2 (Full model versus model with only covariates): 0.066 [0.056, 0.076] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021011 | PGS004786 (HTN_PRSmix_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Hypertension | — | — | Incremental R2 (Full model versus model with only covariates): 0.022 [0.016, 0.028] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021012 | PGS004787 (HTN_PRSmixPlus_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Hypertension | — | — | Incremental R2 (Full model versus model with only covariates): 0.073 [0.063, 0.083] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021013 | PGS004788 (HTN_PRSmixPlus_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Hypertension | — | — | Incremental R2 (Full model versus model with only covariates): 0.027 [0.02, 0.033] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021022 | PGS004797 (migraine_PRSmix_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Migraine | — | — | Incremental R2 (Full model versus model with only covariates): 0.003 [0.001, 0.005] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021023 | PGS004798 (migraine_PRSmix_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Migraine | — | — | Incremental R2 (Full model versus model with only covariates): 0.004 [0.001, 0.006] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021024 | PGS004799 (migraine_PRSmixPlus_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Migraine | — | — | Incremental R2 (Full model versus model with only covariates): 0.019 [0.013, 0.024] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021060 | PGS004835 (stroke_PRSmix_eur) |
PSS011506| European Ancestry| 7,889 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Stroke | — | — | Incremental R2 (Full model versus model with only covariates): 0.007 [0.003, 0.01] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021061 | PGS004836 (stroke_PRSmixPlus_eur) |
PSS011506| European Ancestry| 7,889 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Stroke | — | — | Incremental R2 (Full model versus model with only covariates): 0.017 [0.011, 0.022] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021025 | PGS004800 (migraine_PRSmixPlus_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Migraine | — | — | Incremental R2 (Full model versus model with only covariates): 0.011 [0.007, 0.016] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021078 | PGS004853 (VTE_PRSmix_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: venous thromboembolism | — | — | Incremental R2 (Full model versus model with only covariates): 0.047 [0.039, 0.056] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021079 | PGS004854 (VTE_PRSmixPlus_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: venous thromboembolism | — | — | Incremental R2 (Full model versus model with only covariates): 0.058 [0.049, 0.067] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021092 | PGS004861 (hermes.gwama) |
PSS011521| European Ancestry| 347,585 individuals |
PGP000608 | Zheng SL et al. Nat Genet (2024) |
Reported Trait: Dilated cardiomyopathy | OR: 1.56 | AUROC: 0.7 | R²: 0.048 | age, age^2, sex, PC1-10 | — |
| PPM021093 | PGS004862 (hermes.mtag) |
PSS011521| European Ancestry| 347,585 individuals |
PGP000608 | Zheng SL et al. Nat Genet (2024) |
Reported Trait: Dilated cardiomyopathy | OR: 1.76 | AUROC: 0.71 | R²: 0.05 | age, age^2, sex, PC1-10 | — |
| PPM021204 | PGS004878 (INTERVENE_MegaPRS_Atrial_fibrillation) |
PSS011542| European Ancestry| 29,427 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident AF | HR: 1.55 [1.48, 1.62] | C-index: 0.63 [0.61, 0.64] | — | PCs 1-10 | — |
| PPM021205 | PGS004878 (INTERVENE_MegaPRS_Atrial_fibrillation) |
PSS011540| European Ancestry| 44,186 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident AF | HR: 1.42 [1.29, 1.56] | — | — | PCs 1-10 | — |
| PPM021202 | PGS004878 (INTERVENE_MegaPRS_Atrial_fibrillation) |
PSS011544| European Ancestry| 32,089 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident AF | HR: 1.36 [1.32, 1.39] | C-index: 0.59 [0.58, 0.6] | — | PCs 1-10 | — |
| PPM021203 | PGS004878 (INTERVENE_MegaPRS_Atrial_fibrillation) |
PSS011543| European Ancestry| 69,715 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident AF | HR: 1.68 [1.64, 1.73] | C-index: 0.65 [0.64, 0.65] | — | PCs 1-10 | — |
| PPM021206 | PGS004878 (INTERVENE_MegaPRS_Atrial_fibrillation) |
PSS011541| European Ancestry| 7,018 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident AF | HR: 1.62 [1.5, 1.75] | C-index: 0.66 [0.63, 0.68] | — | PCs 1-10 | — |
| PPM021207 | PGS004878 (INTERVENE_MegaPRS_Atrial_fibrillation) |
PSS011539| European Ancestry| 412,090 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident AF | HR: 1.61 [1.6, 1.63] | C-index: 0.62 [0.62, 0.62] | — | PCs 1-10 | — |
| PPM021209 | PGS004879 (INTERVENE_MegaPRS_CHD) |
PSS011573| European Ancestry| 38,448 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident CHD | HR: 1.18 [1.16, 1.2] | C-index: 0.55 [0.55, 0.56] | — | PCs 1-10 | — |
| PPM021210 | PGS004879 (INTERVENE_MegaPRS_CHD) |
PSS011572| European Ancestry| 69,715 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident CHD | HR: 1.39 [1.36, 1.42] | C-index: 0.6 [0.59, 0.6] | — | PCs 1-10 | — |
| PPM021211 | PGS004879 (INTERVENE_MegaPRS_CHD) |
PSS011571| European Ancestry| 29,427 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident CHD | HR: 1.32 [1.27, 1.38] | C-index: 0.6 [0.58, 0.61] | — | PCs 1-10 | — |
| PPM021212 | PGS004879 (INTERVENE_MegaPRS_CHD) |
PSS011569| European Ancestry| 44,168 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident CHD | HR: 1.27 [1.23, 1.32] | — | — | PCs 1-10 | — |
| PPM021213 | PGS004879 (INTERVENE_MegaPRS_CHD) |
PSS011570| European Ancestry| 7,018 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident CHD | HR: 1.13 [1.07, 1.19] | C-index: 0.56 [0.54, 0.57] | — | PCs 1-10 | — |
| PPM021214 | PGS004879 (INTERVENE_MegaPRS_CHD) |
PSS011568| European Ancestry| 412,090 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident CHD | HR: 1.41 [1.4, 1.43] | C-index: 0.62 [0.62, 0.62] | — | PCs 1-10 | — |
| PPM021215 | PGS004879 (INTERVENE_MegaPRS_CHD) |
PSS011567| European Ancestry| 148,312 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident CHD | HR: 1.18 [1.16, 1.21] | C-index: 0.58 [0.57, 0.58] | — | PCs 1-10 | — |
| PPM021266 | PGS004888 (CAD_gePGS) |
PSS011669| Multi-ancestry (including European)| 11,515 individuals |
PGP000619 | Mandla R et al. Genome Med (2024) |
Reported Trait: Incident coronary artery disease cases without diabetes | HR: 1.27 [1.18, 1.36] | C-index: 0.752 | — | first 10 ancestry PCs, age, sex, smoking status, systolic blood pressure, HDL, and total cholesterol combined into a clinical risk score | — |
| PPM021268 | PGS004888 (CAD_gePGS) |
PSS011669| Multi-ancestry (including European)| 11,515 individuals |
PGP000619 | Mandla R et al. Genome Med (2024) |
Reported Trait: Incident coronary artery disease cases with diabetes | HR: 1.13 [1.02, 1.25] | C-index: 0.668 | — | first 10 ancestry PCs, age, sex, smoking status, systolic blood pressure, HDL, and total cholesterol combined into a clinical risk score | — |
| PPM021296 | PGS000013 (GPS_CAD) |
PSS011679| Multi-ancestry (including European)| 90,053 individuals |
PGP000626 | Douville NJ et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Myocardial injury following non cardiac surgery | OR: 1.23 [1.11, 1.37] | AUROC: 0.72 (0.011) | — | Age, sex, race | — |
| PPM021297 | PGS000013 (GPS_CAD) |
PSS011679| Multi-ancestry (including European)| 90,053 individuals |
PGP000626 | Douville NJ et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Myocardial injury following non cardiac surgery | OR: 1.12 [1.02, 1.24] | AUROC: 0.793 (0.014) | — | High-risk surgery, history of ischemic heart disease, history of congestive heart failure, history of cerebrovascular disease, insulin therapy for diabetes mellitus, preoperative creatinine >2.0 mg/dL | — |
| PPM021298 | PGS000013 (GPS_CAD) |
PSS011679| Multi-ancestry (including European)| 90,053 individuals |
PGP000626 | Douville NJ et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Myocardial injury following non cardiac surgery | OR: 1.19 [1.07, 1.31] | AUROC: 0.912 (0.006) | — | Age, admission type (admit and inpatient versus outpatient reference), composite RCRI score, history of a cardiac arrhythmia, history of fluid or electrolyte disorder, history of hypertension | — |
| PPM021299 | PGS000013 (GPS_CAD) |
PSS011679| Multi-ancestry (including European)| 90,053 individuals |
PGP000626 | Douville NJ et al. Circ Genom Precis Med (2020) |Ext. |
Reported Trait: Myocardial injury following non cardiac surgery | OR: 1.17 [1.06, 1.3] | AUROC: 0.921 (0.006) | — | Age, admission type (admit and inpatient versus outpatient reference), composite RCRI score, history of a cardiac arrhythmia, history of fluid or electrolyte disorder, history of hypertension, case duration (hours), pRBC transfusion (units), crystalloid resuscitation (L), estimated blood loss (L), total epinephrine dose (100mcg), total ephedrine dose (50mcg), total norepinephrine dose (40mcg), total phenylephrine dose (1000mcg), total vasopressin dose (10 units), time with myocardial injury after non cardiac surgery < 50 mmHg (min). | — |
| PPM021300 | PGS000012 (GRS49K) |
PSS011680| European Ancestry| 26,203 individuals |
PGP000627 | Martikainen P et al. J Epidemiol Community Health (2021) |Ext. |
Reported Trait: Incident coronary heart disease hospitalization or death | — | — | Hazard Ratio (HR, top 25% vs bottom 25%): 2.26 [1.97, 2.59] | Age as timescale, sex, region of residence, calendar year, study batch, PCs(1-10) | — |
| PPM021301 | PGS000012 (GRS49K) |
PSS011680| European Ancestry| 26,203 individuals |
PGP000627 | Martikainen P et al. J Epidemiol Community Health (2021) |Ext. |
Reported Trait: Incident coronary heart disease hospitalization or death | — | — | Hazard Ratio (HR, top 25% vs bottom 25%): 2.27 [1.98, 2.61] | Age as timescale, sex, region of residence, calendar year, study batch, PCs(1-10), education | — |
| PPM021351 | PGS000911 (PRS_IS) |
PSS011699| European Ancestry| 407,311 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Incident heart failure | HR: 1.08 [1.06, 1.1] | — | — | Sex, 5 PCs, genotyping array, cubic splines of age at enrolment, height, weight, BMI, systolic blood pressure, diastolic blood pressure | — |
| PPM021302 | PGS000012 (GRS49K) |
PSS011680| European Ancestry| 26,203 individuals |
PGP000627 | Martikainen P et al. J Epidemiol Community Health (2021) |Ext. |
Reported Trait: Incident coronary heart disease hospitalization or death | — | — | Hazard Ratio (HR, top 25% vs bottom 25%): 2.12 [1.48, 2.43] | Age as timescale, sex, region of residence, calendar year, study batch, PCs(1-10), smoking, alcohol use, body mass index, high-density lipoprotein and total cholesterol, blood pressure, diabetes | — |
| PPM021303 | PGS000011 (GRS50) |
PSS011680| European Ancestry| 26,203 individuals |
PGP000627 | Martikainen P et al. J Epidemiol Community Health (2021) |Ext. |
Reported Trait: Incident coronary heart disease hospitalization or death | — | — | Hazard Ratio (HR, top 25% vs bottom 25%): 1.55 [1.38, 1.76] | Age as timescale, sex, region of residence, calendar year, study batch, PCs(1-10) | — |
| PPM021304 | PGS000011 (GRS50) |
PSS011680| European Ancestry| 26,203 individuals |
PGP000627 | Martikainen P et al. J Epidemiol Community Health (2021) |Ext. |
Reported Trait: Incident coronary heart disease hospitalization or death | — | — | Hazard Ratio (HR, top 25% vs bottom 25%): 1.56 [1.38, 1.77] | Age as timescale, sex, region of residence, calendar year, study batch, PCs(1-10), education | — |
| PPM021305 | PGS000011 (GRS50) |
PSS011680| European Ancestry| 26,203 individuals |
PGP000627 | Martikainen P et al. J Epidemiol Community Health (2021) |Ext. |
Reported Trait: Incident coronary heart disease hospitalization or death | — | — | Hazard Ratio (HR, top 25% vs bottom 25%): 1.53 [1.35, 1.73] | Age as timescale, sex, region of residence, calendar year, study batch, PCs(1-10), smoking, alcohol use, body mass index, high-density lipoprotein and total cholesterol, blood pressure, diabetes | — |
| PPM021306 | PGS000018 (metaGRS_CAD) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident cardiovascular disease outcome | HR: 1.31 [1.27, 1.34] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021307 | PGS000018 (metaGRS_CAD) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.49 [1.44, 1.54] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021308 | PGS000018 (metaGRS_CAD) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.57 [1.51, 1.62] | — | — | Age at baseline, stratified by study centre, sex | — |
| PPM021309 | PGS000018 (metaGRS_CAD) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident stroke | HR: 1.09 [1.04, 1.13] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021310 | PGS000018 (metaGRS_CAD) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Combination of incident coronary heart disease, stroke and cardiac revascularisation procedures | HR: 1.39 [1.36, 1.42] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021311 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident cardiovascular disease outcome | HR: 1.18 [1.15, 1.21] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021312 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident coronary heart disease | HR: 1.2 [1.16, 1.24] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021313 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident stroke | HR: 1.19 [1.14, 1.24] | — | — | Age at baseline, stratified by study centre, sex | — |
| PPM021314 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Incident stroke | HR: 1.16 [1.11, 1.21] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021315 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011681| European Ancestry| 306,654 individuals |
PGP000628 | Sun L et al. PLoS Med (2021) |Ext. |
Reported Trait: Combination of incident coronary heart disease, stroke and cardiac revascularisation procedures | HR: 1.19 [1.16, 1.22] | — | — | Age at baseline, smoking status, history of diabetes, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol levels, stratified by study centre, sex | — |
| PPM021316 | PGS004899 (PRS_SCAD) |
PSS011682| Ancestry Not Reported| 412 individuals |
PGP000629 | Saw J et al. Nat Commun (2020) |
Reported Trait: Spontaneous coronary artery dissection | OR: 1.82 [1.09, 3.02] β: 0.597 (0.259) |
— | — | Age, sex | — |
| PPM021317 | PGS004899 (PRS_SCAD) |
PSS011685| European Ancestry| 373,056 individuals |
PGP000629 | Saw J et al. Nat Commun (2020) |
Reported Trait: Myocardial infarction | HR: 0.91 [0.89, 0.93] β: -0.094 (0.011) |
— | — | Age, sex, genotyping array and batch, PCs (1-4) | — |
| PPM021318 | PGS004899 (PRS_SCAD) |
PSS011685| European Ancestry| 373,056 individuals |
PGP000629 | Saw J et al. Nat Commun (2020) |
Reported Trait: Myocardial infarction in males | HR: 0.91 [0.89, 0.93] β: -0.092 (0.013) |
— | — | Age, genotyping array and batch, PCs (1-4) | — |
| PPM021319 | PGS004899 (PRS_SCAD) |
PSS011685| European Ancestry| 373,056 individuals |
PGP000629 | Saw J et al. Nat Commun (2020) |
Reported Trait: Myocaridal infarction in females | HR: 0.91 [0.87, 0.95] β: -0.099 (0.022) |
— | — | Age, genotyping array and batch, PCs (1-4) | — |
| PPM021320 | PGS004899 (PRS_SCAD) |
PSS011683| European Ancestry| 294,465 individuals |
PGP000629 | Saw J et al. Nat Commun (2020) |
Reported Trait: Coronary artery disease | β: -0.05 (0.004) OR: 0.95 [0.94, 0.96] |
— | — | Age (at the time of event in cases and at the time of last VA visit prior to August 2018 for controls), sex, PCs(1-10) | — |
| PPM021321 | PGS004899 (PRS_SCAD) |
PSS011683| European Ancestry| 294,465 individuals |
PGP000629 | Saw J et al. Nat Commun (2020) |
Reported Trait: Coronary artery disease in males | OR: 0.95 [0.94, 0.96] β: -0.05 (0.004) |
— | — | Age (at the time of event in cases and at the time of last VA visit prior to August 2018 for controls), PCs(1-10) | — |
| PPM021322 | PGS004899 (PRS_SCAD) |
PSS011684| European Ancestry| 314,434 individuals |
PGP000629 | Saw J et al. Nat Commun (2020) |
Reported Trait: Myocardial infarction | OR: 0.96 [0.95, 0.98] β: -0.04 (0.009) |
— | — | Age (at the time of event in cases and at the time of last VA visit prior to August 2018 for controls), sex, PCs(1-10) | — |
| PPM021323 | PGS004899 (PRS_SCAD) |
PSS011684| European Ancestry| 314,434 individuals |
PGP000629 | Saw J et al. Nat Commun (2020) |
Reported Trait: Myocardial infarction in males | OR: 0.96 [0.95, 0.98] β: -0.039 (0.009) |
— | — | Age (at the time of event in cases and at the time of last VA visit prior to August 2018 for controls), PCs(1-10) | — |
| PPM021334 | PGS000013 (GPS_CAD) |
PSS011689| European Ancestry| 5,453 individuals |
PGP000632 | Aday AW et al. Atherosclerosis (2023) |Ext. |
Reported Trait: Incident myocardial infarction or fatal coronary event | HR: 1.37 [1.26, 1.49] | C-index: 0.74 [0.71, 0.76] | — | Age, sex, 5 PCs, pooled cohort equations, high-sensitivity C-reactive protein | — |
| PPM021345 | PGS000016 (GPS_AF) |
PSS011698| European Ancestry| 1,567 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Cardiovascular death, stroke, hospitalization for worsening of HF, or acute coronary syndrome | HR: 0.99 [0.88, 1.11] | — | — | — | — |
| PPM021346 | PGS000016 (GPS_AF) |
PSS011698| European Ancestry| 1,567 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Stroke | HR: 1.1 [0.83, 1.45] | — | — | — | — |
| PPM021347 | PGS000016 (GPS_AF) |
PSS011698| European Ancestry| 1,567 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Recurrent atrial fibrillation | HR: 1.08 [1.0, 1.16] | — | — | — | — |
| PPM021348 | PGS000911 (PRS_IS) |
PSS011698| European Ancestry| 1,567 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Cardiovascular death, stroke, hospitalization for worsening of HF, or acute coronary syndrome | HR: 1.13 [1.0, 1.27] | — | — | Treatment group | — |
| PPM021349 | PGS000911 (PRS_IS) |
PSS011698| European Ancestry| 1,567 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Stroke | HR: 1.0 [0.75, 1.34] | — | — | Treatment group | — |
| PPM021350 | PGS000911 (PRS_IS) |
PSS011698| European Ancestry| 1,567 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Worsening of heart failure | HR: 1.23 [1.05, 1.43] | — | — | Treatment group | — |
| PPM021352 | PGS000911 (PRS_IS) |
PSS011699| European Ancestry| 407,311 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Incident stroke | HR: 1.08 [1.06, 1.11] | — | — | Sex, 5 PCs, genotyping array, cubic splines of age at enrolment, height, weight, BMI, systolic blood pressure, diastolic blood pressure | — |
| PPM021353 | PGS000911 (PRS_IS) |
PSS011699| European Ancestry| 407,311 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Incident ischemic stroke | HR: 1.11 [1.08, 1.14] | — | — | Sex, 5 PCs, genotyping array, cubic splines of age at enrolment, height, weight, BMI, systolic blood pressure, diastolic blood pressure | — |
| PPM021354 | PGS000911 (PRS_IS) |
PSS011699| European Ancestry| 407,311 individuals |
PGP000637 | Kany S et al. Cardiovasc Res (2023) |Ext. |
Reported Trait: Incident atrial fibrillation or atrial flutter | HR: 1.15 [1.14, 1.67] | — | — | Sex, 5 PCs, genotyping array, cubic splines of age at enrolment, height, weight, BMI, systolic blood pressure, diastolic blood pressure | — |
| PPM021333 | PGS000013 (GPS_CAD) |
PSS011690| European Ancestry| 2,017 individuals |
PGP000632 | Aday AW et al. Atherosclerosis (2023) |Ext. |
Reported Trait: Incident myocardial infarction or fatal coronary event | HR: 1.38 [1.16, 1.63] | C-index: 0.74 [0.69, 0.77] | — | Age, sex, 5 PCs, pooled cohort equations, high-sensitivity C-reactive protein | — |
| PPM021367 | PGS004911 (hcm.mtag) |
PSS011704| European Ancestry| 343,182 individuals |
PGP000642 | Zheng SL et al. Nat Genet (2025) |
Reported Trait: Hypertrophic cardiomyopathy | HR: 2.34 OR: 1.33 |
AUROC: 0.8 | R²: 0.048 Odds ratio (OR, high vs median tertile): 5.9 |
age, age^2, sex, PC1-10 | — |
| PPM021208 | PGS004878 (INTERVENE_MegaPRS_Atrial_fibrillation) |
PSS011538| European Ancestry| 148,312 individuals |
PGP000618 | Jermy B et al. Nat Commun (2024) |
Reported Trait: Incident AF | HR: 1.56 [1.52, 1.6] | C-index: 0.62 [0.61, 0.63] | — | PCs 1-10 | — |
| PPM021355 | PGS004905 (PRS155_AF) |
PSS011700| Multi-ancestry (including European)| 401,251 individuals |
PGP000638 | Ma Y et al. Proc Natl Acad Sci U S A (2023) |
Reported Trait: Incident atrial fibrillation | HR: 2.145 [2.085, 2.205] | — | — | Age, sex, ethnicity, education, employment, alcohol consumption status, smoking status, healthy diet score, physical activity, BMI, hypertension, hyperlipidemia, diabetes, genotyping batch, 10 PCs | — |
| PPM020362 | PGS004294 (GenoBoost_atrial_fibrillation_4) |
PSS011337| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.75648 | Covariate-adjusted pseudo-R2: 0.03265 AUPRC: 0.75648 |
age, sex, PC1-10 | — |
| PPM020374 | PGS004306 (GenoBoost_coronary_artery_disease_1) |
PSS011339| European Ancestry| 67,428 individuals |
PGP000546 | Ohta R et al. Nat Commun (2024) |
Reported Trait: Coronary artery disease | — | AUROC: 0.75619 | Covariate-adjusted pseudo-R2: 0.02397 AUPRC: 0.75619 |
age, sex, PC1-10 | — |
| PPM021386 | PGS000011 (GRS50) |
PSS011721| Ancestry Not Reported| 23,594 individuals |
PGP000650 | Sjögren M et al. Int J Cardiol Heart Vasc (2019) |Ext. |
Reported Trait: Number of cardiovascular-related hospitalizations | — | — | Incidence Rate Ratio (IRR, top vs bottom PGS quintiles): 1.31 [1.2, 1.43] | Age, sex, follow up time | — |
| PPM021387 | PGS000011 (GRS50) |
PSS011720| Ancestry Not Reported| 23,594 individuals |
PGP000650 | Sjögren M et al. Int J Cardiol Heart Vasc (2019) |Ext. |
Reported Trait: Number of hospitilization days for any cause | — | — | Incidence Rate Ratio (IRR, top vs bottom PGS quintiles): 1.17 [1.08, 1.26] | Age, sex, follow up time, hypertension, prevalent diabetes, smoking, ApoA1 and ApoB | — |
| PPM021388 | PGS000011 (GRS50) |
PSS011720| Ancestry Not Reported| 23,594 individuals |
PGP000650 | Sjögren M et al. Int J Cardiol Heart Vasc (2019) |Ext. |
Reported Trait: Any hospitilization event | — | — | Odds Ratio (OR, top vs bottom PGS quintiles): 1.18 [1.07, 1.3] | Age, sex, follow up time | — |
| PPM021389 | PGS000011 (GRS50) |
PSS011722| Ancestry Not Reported| 23,594 individuals |
PGP000650 | Sjögren M et al. Int J Cardiol Heart Vasc (2019) |Ext. |
Reported Trait: Cardiovascular-related death | — | — | Hazard Ratio (HR, top vs bottom PGS quintiles): 1.44 [1.25, 1.66] | Age, sex, hypertension, prevalent diabetes, smoking, aPoA1, ApoB | — |
| PPM021399 | PGS004921 (CAD-GRS) |
PSS011730| European Ancestry| 317,509 individuals |
PGP000654 | Huang Y et al. Circ Genom Precis Med (2020) |
Reported Trait: Prevalent coronary artery disease | OR: 1.41 [1.38, 1.44] | — | — | Age, population stratification, smoking status, alcohol consumption, BMI, history of diabetes or hypertension, cholesterol medication use, education, Townsend deprivation index | — |
| PPM021400 | PGS004921 (CAD-GRS) |
PSS011731| European Ancestry| 146,246 individuals |
PGP000654 | Huang Y et al. Circ Genom Precis Med (2020) |
Reported Trait: Prevalent coronary artery disease | OR: 1.44 [1.4, 1.48] | — | — | Age, population stratification, smoking status, alcohol consumption, BMI, history of diabetes or hypertension, cholesterol medication use, education, Townsend deprivation index | — |
| PPM021401 | PGS004921 (CAD-GRS) |
PSS011732| European Ancestry| 171,263 individuals |
PGP000654 | Huang Y et al. Circ Genom Precis Med (2020) |
Reported Trait: Prevalent coronary artery disease | OR: 1.33 [1.27, 1.39] | — | — | Age, population stratification, smoking status, alcohol consumption, BMI, history of diabetes or hypertension, cholesterol medication use, education, Townsend deprivation index | — |
| PPM021402 | PGS004921 (CAD-GRS) |
PSS011727| European Ancestry| 307,151 individuals |
PGP000654 | Huang Y et al. Circ Genom Precis Med (2020) |
Reported Trait: Incident coronary artery disease | OR: 1.34 [1.31, 1.36] | — | — | Age, population stratification, smoking status, alcohol consumption, BMI, history of diabetes or hypertension, cholesterol medication use, education, Townsend deprivation index | — |
| PPM021403 | PGS004921 (CAD-GRS) |
PSS011728| European Ancestry| 138,270 individuals |
PGP000654 | Huang Y et al. Circ Genom Precis Med (2020) |
Reported Trait: Incident coronary artery disease | OR: 1.38 [1.34, 1.41] | — | — | Age, population stratification, smoking status, alcohol consumption, BMI, history of diabetes or hypertension, cholesterol medication use, education, Townsend deprivation index | — |
| PPM021404 | PGS004921 (CAD-GRS) |
PSS011729| European Ancestry| 168,881 individuals |
PGP000654 | Huang Y et al. Circ Genom Precis Med (2020) |
Reported Trait: Incident coronary artery disease | OR: 1.25 [1.21, 1.3] | — | — | Age, population stratification, smoking status, alcohol consumption, BMI, history of diabetes or hypertension, cholesterol medication use, education, Townsend deprivation index | — |
| PPM021391 | PGS004920 (GRS166_AF) |
PSS011724| European Ancestry| 193,819 individuals |
PGP000652 | Wang N et al. Eur Heart J (2021) |
Reported Trait: Atrial fibrillation | HR: 2.68 [2.53, 2.84] | — | — | Age, sex, ethnicity, Townsend index, education, smoking status, BMI <25.0 kg/m2, physical activity goal (≥150 min/week of moderate intensity, ≥75 min/week of vigorous intensity, or an equivalent combination), dietary score ≥4 proposed in previous studies, total cholesterol <5.18 mmol/L without using lipid-lowering medication, glycated haemoglobin <5.7% (39 mmol/mol) and no history of diabetes, blood pressure <120/<80 mmHg without using blood pressure-lowering medication | — |
| PPM021717 | PGS003446 (TEM_CAD_PRS) |
PSS011762| European Ancestry| 8,417 individuals |
PGP000665 | Moreno-Grau S et al. Human Genomics (2024) |Ext. |
Reported Trait: Coronary artery disease | OR: 1.6 [1.42, 1.82] | AUROC: 0.82 | — | — | — |
| PPM021711 | PGS002262 (metaPRS_CAD) |
PSS011758| East Asian Ancestry| 34,111 individuals |
PGP000662 | Xia X et al. Am J Clin Nutr (2023) |Ext. |
Reported Trait: Incident CAD | HR: 1.37 [1.29, 1.46] | — | — | Age, sex, urbanicity, per-capita household income, educational attainment, family history of CAD, smoking, alcohol consumption, BMI, physical activity, red meat intake, poultry intake, fish intake, hypertension, diabetes, and hypercholesteremia | — |
| PPM021704 | PGS002262 (metaPRS_CAD) |
PSS011752| East Asian Ancestry| 39,164 individuals |
PGP000658 | Hu C et al. Med Sci Sports Exerc (2023) |Ext. |
Reported Trait: Incident CAD | HR: 1.38 [1.3, 1.47] | — | — | Age, sex, cohort source, living geographical zone, urban or rural residents, education attainment, family history of CVD, current smoking status, drinking, healthy diet score, sleep duration, physical activity level, BMI, hypertension, diabetes, and dyslipidemia | — |
| PPM021707 | PGS004925 (PRS300_CHD) |
PSS011755| European Ancestry| 77,500 individuals |
PGP000660 | Kim Y et al. J Intern Med (2023) |
Reported Trait: Incident coronary heart disease | HR: 1.63 [1.49, 1.78] | — | — | Sex, genotype array type, 10 PCs | — |
| PPM021765 | PGS000039 (metaGRS_ischaemicstroke) |
PSS011789| European Ancestry| 332 individuals |
PGP000674 | Lin F et al. Front Stroke (2023) |Ext. |
Reported Trait: Ischemic stroke | OR: 3.0 [0.3, 26.4] | — | — | Age, smoking status | — |
| PPM021856 | PGS005066 (Phe_427_21_prscs_AFRss_afrld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.238 [1.09, 1.41] | C-index: 0.74525 | — | age, sex, 20 PCs | — |
| PPM021858 | PGS005067 (Phe_427_21_prscs_EURss_eurld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.183 [1.08, 1.3] | C-index: 0.74595 | — | age, sex, 20 PCs | — |
| PPM021859 | PGS005072 (Phe_427_21_prscsx_METAweight) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.232 [1.11, 1.36] | C-index: 0.74713 | — | age, sex, 20 PCs | — |
| PPM021716 | PGS004929 (AF_Ldpred2_combined) |
PSS011762| European Ancestry| 8,417 individuals |
PGP000665 | Moreno-Grau S et al. Human Genomics (2024) |
Reported Trait: Atrial fibrillation | OR: 1.44 [1.28, 1.63] | AUROC: 0.71 | — | — | — |
| PPM021721 | PGS004933 (hemorrhoid_LDpred2_combined) |
PSS011762| European Ancestry| 8,417 individuals |
PGP000665 | Moreno-Grau S et al. Human Genomics (2024) |
Reported Trait: Hemorrhoid | OR: 1.1 [1.04, 1.15] | AUROC: 0.56 | — | — | — |
| PPM021722 | PGS004934 (hypertension_snpnet_combined) |
PSS011762| European Ancestry| 8,417 individuals |
PGP000665 | Moreno-Grau S et al. Human Genomics (2024) |
Reported Trait: Hypertension | OR: 1.42 [1.35, 1.5] | AUROC: 0.72 | — | — | — |
| PPM021739 | PGS004941 (CAD_MetaPRS) |
PSS011772| East Asian Ancestry| 72,149 individuals |
PGP000668 | China Kadoorie Biobank Collaborative Group. et al. Nat Hum Behav (2024) |
Reported Trait: Incident coronary artery disease | HR: 1.42 [1.36, 1.49] | C-index: 0.809 [0.799, 0.819] | — | age, sex | — |
| PPM021741 | PGS004943 (ICH_MetaPRS) |
PSS011773| East Asian Ancestry| 72,149 individuals |
PGP000668 | China Kadoorie Biobank Collaborative Group. et al. Nat Hum Behav (2024) |
Reported Trait: Incident intracerebral hemorrhage | HR: 1.31 [1.24, 1.39] | C-index: 0.748 [0.734, 0.761] | — | age, sex | — |
| PPM021742 | PGS000018 (metaGRS_CAD) |
PSS011775| Multi-ancestry (including European)| 199,997 individuals |
PGP000669 | Saadatagah S et al. JACC Adv (2023) |Ext. |
Reported Trait: Coronary heart disease onset > 70 years | — | — | Odds ratio (OR, top 5th percentile vs 20-80th percentile): 1.91 [1.68, 2.17] | Sex, 4 PCs | — |
| PPM021743 | PGS000018 (metaGRS_CAD) |
PSS011775| Multi-ancestry (including European)| 199,997 individuals |
PGP000669 | Saadatagah S et al. JACC Adv (2023) |Ext. |
Reported Trait: Coronary heart disease onset < 50 years | — | — | Odds ratio (OR, top 5th percentile vs 20-80th percentile): 3.25 [2.73, 3.85] | Sex, 4 PCs | — |
| PPM021857 | PGS005068 (Phe_427_21_prscs_HISss_amrld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.074 [0.96, 1.2] | C-index: 0.74301 | — | age, sex, 20 PCs | — |
| PPM021754 | PGS004947 (DCM_MTAG_exclMGBB) |
PSS011781| Multi-ancestry (including European)| 96,016 individuals |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Reported Trait: Non-ischemic dilated cardiomyopathy | OR: 1.73 β: 0.55 (0.04) |
— | Nagelkerke pseudo-R^2 full model: 0.068 Nagelkerke pseudo-R^2 delta PRS/residual: 0.028 Liability-scale R^2 (assuming 0.4% prev) full model: 0.235 Liability-scale R^2 (assuming 0.4% prev) delta PRS/residual: 0.076 Univariate (PRS only) AUC: 0.66 [0.63, 0.68] Univariate (PRS only) AUPRC: 0.0109 |
Age, age^2, sex, PC1-12 | beta represents log(OR) per SD of PRS |
| PPM021755 | PGS004948 (DCM_GWAS_exclUKB) |
PSS011782| Multi-ancestry (including European)| 326,106 individuals |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Reported Trait: Non-ischemic dilated cardiomyopathy | OR: 1.64 β: 0.49 (0.04) |
— | Nagelkerke pseudo-R^2 full model: 0.049 Nagelkerke pseudo-R^2 delta PRS/residual: 0.018 Liability-scale R^2 (assuming 0.4% prev) full model: 0.186 Liability-scale R^2 (assuming 0.4% prev) delta PRS/residual: 0.06 Univariate (PRS only) AUC: 0.64 [0.62, 0.66] Univariate (PRS only) AUPRC: 0.0042 |
Age, age^2, sex, array, PC1-12 | beta represents log(OR) per SD of PRS |
| PPM021756 | PGS004949 (DCM_MTAG_exclUKB) |
PSS011782| Multi-ancestry (including European)| 326,106 individuals |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Reported Trait: Non-ischemic dilated cardiomyopathy | OR: 1.91 β: 0.65 (0.04) |
— | Nagelkerke pseudo-R^2 full model: 0.06 Nagelkerke pseudo-R^2 delta PRS/residual: 0.029 Liability-scale R^2 (assuming 0.4% prev) full model: 0.216 Liability-scale R^2 (assuming 0.4% prev) delta PRS/residual: 0.095 Univariate (PRS only) AUC: 0.68 [0.66, 0.69] Univariate (PRS only) AUPRC: 0.0052 |
Age, age^2, sex, array, PC1-12 | beta represents log(OR) per SD of PRS |
| PPM021757 | PGS004950 (DCM_GWAS_exclAUMC) |
PSS011780| European Ancestry| 7,761 individuals |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Reported Trait: Clinical dilated cardiomyopathy | OR: 1.71 β: 0.54 (0.04) |
— | Nagelkerke pseudo-R^2 full model: 0.101 Nagelkerke pseudo-R^2 delta PRS/residual: 0.052 Liability-scale R^2 (assuming 0.4% prev) full model: 0.13 Liability-scale R^2 (assuming 0.4% prev) delta PRS/residual: 0.073 Univariate (PRS only) AUC: 0.64 [0.62, 0.66] Univariate (PRS only) AUPRC: 0.1765 |
Sex, PC1-12 | beta represents log(OR) per SD of PRS |
| PPM021758 | PGS004951 (DCM_MTAG_exclAUMC) |
PSS011780| European Ancestry| 7,761 individuals |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Reported Trait: Clinical dilated cardiomyopathy | OR: 1.93 β: 0.66 (0.04) |
— | Nagelkerke pseudo-R^2 full model: 0.124 Nagelkerke pseudo-R^2 delta PRS/residual: 0.076 Liability-scale R^2 (assuming 0.4% prev) full model: 0.162 Liability-scale R^2 (assuming 0.4% prev) delta PRS/residual: 0.101 Univariate (PRS only) AUC: 0.67 [0.65, 0.69] Univariate (PRS only) AUPRC: 0.2023 |
Sex, PC1-12 | beta represents log(OR) per SD of PRS |
| PPM021861 | PGS005083 (Phe_428_1_prscs_METAss_amrld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.319 [1.14, 1.53] | C-index: 0.79127 | — | age, sex, 20 PCs | — |
| PPM021862 | PGS005084 (Phe_428_1_prscs_METAss_eurld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.396 [1.2, 1.62] | C-index: 0.79297 | — | age, sex, 20 PCs | — |
| PPM021797 | PGS005043 (Phe_411_2_prscs_METAss_afrld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.282 [1.14, 1.45] | C-index: 0.82411 | — | age, sex, 20 PCs | — |
| PPM021798 | PGS005044 (Phe_411_2_prscs_METAss_amrld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.392 [1.23, 1.58] | C-index: 0.82594 | — | age, sex, 20 PCs | — |
| PPM021799 | PGS005045 (Phe_411_2_prscs_METAss_eurld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.353 [1.19, 1.54] | C-index: 0.82389 | — | age, sex, 20 PCs | — |
| PPM021800 | PGS005040 (Phe_411_2_prscs_AFRss_afrld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.172 [1.0, 1.38] | C-index: 0.82194 | — | age, sex, 20 PCs | — |
| PPM021801 | PGS005042 (Phe_411_2_prscs_HISss_amrld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.194 [1.03, 1.38] | C-index: 0.82033 | — | age, sex, 20 PCs | — |
| PPM021803 | PGS005046 (Phe_411_2_prscsx_METAweight) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.376 [1.21, 1.56] | C-index: 0.82539 | — | age, sex, 20 PCs | — |
| PPM021804 | PGS005043 (Phe_411_2_prscs_METAss_afrld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.434 [1.36, 1.51] | C-index: 0.77954 | — | age, sex, 20 PCs | — |
| PPM021805 | PGS005044 (Phe_411_2_prscs_METAss_amrld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.546 [1.47, 1.63] | C-index: 0.78362 | — | age, sex, 20 PCs | — |
| PPM021806 | PGS005045 (Phe_411_2_prscs_METAss_eurld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.554 [1.47, 1.64] | C-index: 0.78385 | — | age, sex, 20 PCs | — |
| PPM021807 | PGS005040 (Phe_411_2_prscs_AFRss_afrld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.071 [1.02, 1.13] | C-index: 0.76867 | — | age, sex, 20 PCs | — |
| PPM021808 | PGS005042 (Phe_411_2_prscs_HISss_amrld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.122 [1.07, 1.18] | C-index: 0.76923 | — | age, sex, 20 PCs | — |
| PPM021809 | PGS005041 (Phe_411_2_prscs_EURss_eurld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.535 [1.46, 1.62] | C-index: 0.78373 | — | age, sex, 20 PCs | — |
| PPM021810 | PGS005046 (Phe_411_2_prscsx_METAweight) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.527 [1.45, 1.61] | C-index: 0.78337 | — | age, sex, 20 PCs | — |
| PPM021811 | PGS005043 (Phe_411_2_prscs_METAss_afrld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.309 [1.19, 1.44] | C-index: 0.74091 | — | age, sex, 20 PCs | — |
| PPM021812 | PGS005044 (Phe_411_2_prscs_METAss_amrld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.365 [1.24, 1.51] | C-index: 0.7435 | — | age, sex, 20 PCs | — |
| PPM021813 | PGS005045 (Phe_411_2_prscs_METAss_eurld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.351 [1.22, 1.49] | C-index: 0.74237 | — | age, sex, 20 PCs | — |
| PPM021814 | PGS005040 (Phe_411_2_prscs_AFRss_afrld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.198 [1.07, 1.34] | C-index: 0.73492 | — | age, sex, 20 PCs | — |
| PPM021815 | PGS005042 (Phe_411_2_prscs_HISss_amrld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.036 [0.94, 1.14] | C-index: 0.73253 | — | age, sex, 20 PCs | — |
| PPM021816 | PGS005041 (Phe_411_2_prscs_EURss_eurld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.247 [1.13, 1.37] | C-index: 0.73945 | — | age, sex, 20 PCs | — |
| PPM021817 | PGS005046 (Phe_411_2_prscsx_METAweight) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.345 [1.22, 1.48] | C-index: 0.74289 | — | age, sex, 20 PCs | — |
| PPM021839 | PGS005069 (Phe_427_21_prscs_METAss_afrld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.344 [1.18, 1.53] | C-index: 0.82333 | — | age, sex, 20 PCs | — |
| PPM021841 | PGS005071 (Phe_427_21_prscs_METAss_eurld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.397 [1.23, 1.59] | C-index: 0.82533 | — | age, sex, 20 PCs | — |
| PPM021842 | PGS005066 (Phe_427_21_prscs_AFRss_afrld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.215 [1.06, 1.39] | C-index: 0.81844 | — | age, sex, 20 PCs | — |
| PPM021843 | PGS005068 (Phe_427_21_prscs_HISss_amrld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.167 [1.02, 1.34] | C-index: 0.81866 | — | age, sex, 20 PCs | — |
| PPM021844 | PGS005067 (Phe_427_21_prscs_EURss_eurld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.344 [1.18, 1.53] | C-index: 0.82419 | — | age, sex, 20 PCs | — |
| PPM021845 | PGS005072 (Phe_427_21_prscsx_METAweight) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.414 [1.25, 1.6] | C-index: 0.82572 | — | age, sex, 20 PCs | — |
| PPM021846 | PGS005069 (Phe_427_21_prscs_METAss_afrld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.578 [1.51, 1.65] | C-index: 0.82183 | — | age, sex, 20 PCs | — |
| PPM021847 | PGS005070 (Phe_427_21_prscs_METAss_amrld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.685 [1.61, 1.76] | C-index: 0.82621 | — | age, sex, 20 PCs | — |
| PPM021848 | PGS005071 (Phe_427_21_prscs_METAss_eurld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.693 [1.62, 1.77] | C-index: 0.82616 | — | age, sex, 20 PCs | — |
| PPM021853 | PGS005069 (Phe_427_21_prscs_METAss_afrld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.191 [1.08, 1.31] | C-index: 0.74595 | — | age, sex, 20 PCs | — |
| PPM021854 | PGS005070 (Phe_427_21_prscs_METAss_amrld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.226 [1.11, 1.36] | C-index: 0.74683 | — | age, sex, 20 PCs | — |
| PPM021855 | PGS005071 (Phe_427_21_prscs_METAss_eurld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.261 [1.14, 1.4] | C-index: 0.74915 | — | age, sex, 20 PCs | — |
| PPM021863 | PGS005079 (Phe_428_1_prscs_AFRss_afrld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.098 [0.97, 1.24] | C-index: 0.78907 | — | age, sex, 20 PCs | — |
| PPM021864 | PGS005081 (Phe_428_1_prscs_HISss_amrld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.033 [0.91, 1.18] | C-index: 0.78774 | — | age, sex, 20 PCs | — |
| PPM021865 | PGS005080 (Phe_428_1_prscs_EURss_eurld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.364 [1.15, 1.62] | C-index: 0.79082 | — | age, sex, 20 PCs | — |
| PPM021866 | PGS005085 (Phe_428_1_prscsx_METAweight) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.303 [1.14, 1.49] | C-index: 0.79251 | — | age, sex, 20 PCs | — |
| PPM021867 | PGS005082 (Phe_428_1_prscs_METAss_afrld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.39 [1.32, 1.47] | C-index: 0.75065 | — | age, sex, 20 PCs | — |
| PPM021868 | PGS005083 (Phe_428_1_prscs_METAss_amrld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.455 [1.38, 1.54] | C-index: 0.75368 | — | age, sex, 20 PCs | — |
| PPM021870 | PGS005079 (Phe_428_1_prscs_AFRss_afrld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.127 [1.07, 1.19] | C-index: 0.7408 | — | age, sex, 20 PCs | — |
| PPM021871 | PGS005081 (Phe_428_1_prscs_HISss_amrld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.09 [1.04, 1.15] | C-index: 0.73963 | — | age, sex, 20 PCs | — |
| PPM021872 | PGS005080 (Phe_428_1_prscs_EURss_eurld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.44 [1.37, 1.52] | C-index: 0.75317 | — | age, sex, 20 PCs | — |
| PPM021873 | PGS005085 (Phe_428_1_prscsx_METAweight) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.437 [1.36, 1.51] | C-index: 0.7528 | — | age, sex, 20 PCs | — |
| PPM021874 | PGS005082 (Phe_428_1_prscs_METAss_afrld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.317 [1.19, 1.46] | C-index: 0.7165 | — | age, sex, 20 PCs | — |
| PPM021875 | PGS005083 (Phe_428_1_prscs_METAss_amrld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.314 [1.18, 1.46] | C-index: 0.71674 | — | age, sex, 20 PCs | — |
| PPM021876 | PGS005084 (Phe_428_1_prscs_METAss_eurld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.385 [1.24, 1.54] | C-index: 0.71868 | — | age, sex, 20 PCs | — |
| PPM021877 | PGS005079 (Phe_428_1_prscs_AFRss_afrld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.24 [1.13, 1.36] | C-index: 0.71475 | — | age, sex, 20 PCs | — |
| PPM021878 | PGS005081 (Phe_428_1_prscs_HISss_amrld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.07 [0.98, 1.17] | C-index: 0.70939 | — | age, sex, 20 PCs | — |
| PPM021880 | PGS005085 (Phe_428_1_prscsx_METAweight) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.333 [1.21, 1.47] | C-index: 0.71878 | — | age, sex, 20 PCs | — |
| PPM021899 | PGS005037 (Phe_411_2_ldpred_METAss_afrld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.338 [1.18, 1.51] | C-index: 0.82493 | — | age, sex, 20 PCs | — |
| PPM021900 | PGS005038 (Phe_411_2_ldpred_METAss_amrld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.378 [1.22, 1.56] | C-index: 0.82508 | — | age, sex, 20 PCs | — |
| PPM021902 | PGS005034 (Phe_411_2_ldpred_AFRss_afrld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.227 [1.06, 1.42] | C-index: 0.82275 | — | age, sex, 20 PCs | — |
| PPM021903 | PGS005036 (Phe_411_2_ldpred_HISss_amrld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.159 [1.0, 1.34] | C-index: 0.82048 | — | age, sex, 20 PCs | — |
| PPM021904 | PGS005035 (Phe_411_2_ldpred_EURss_eurld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.315 [1.15, 1.5] | C-index: 0.82355 | — | age, sex, 20 PCs | — |
| PPM021905 | PGS005037 (Phe_411_2_ldpred_METAss_afrld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.5 [1.42, 1.58] | C-index: 0.78205 | — | age, sex, 20 PCs | — |
| PPM021906 | PGS005038 (Phe_411_2_ldpred_METAss_amrld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.53 [1.45, 1.61] | C-index: 0.78309 | — | age, sex, 20 PCs | — |
| PPM021907 | PGS005039 (Phe_411_2_ldpred_METAss_eurld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.578 [1.5, 1.67] | C-index: 0.78484 | — | age, sex, 20 PCs | — |
| PPM021908 | PGS005034 (Phe_411_2_ldpred_AFRss_afrld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.099 [1.05, 1.16] | C-index: 0.76899 | — | age, sex, 20 PCs | — |
| PPM021909 | PGS005036 (Phe_411_2_ldpred_HISss_amrld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.124 [1.07, 1.18] | C-index: 0.76923 | — | age, sex, 20 PCs | — |
| PPM021910 | PGS005035 (Phe_411_2_ldpred_EURss_eurld) |
PSS011818| European Ancestry| 30,379 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.541 [1.46, 1.63] | C-index: 0.78336 | — | age, sex, 20 PCs | — |
| PPM021911 | PGS005037 (Phe_411_2_ldpred_METAss_afrld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.379 [1.25, 1.52] | C-index: 0.74391 | — | age, sex, 20 PCs | — |
| PPM021912 | PGS005038 (Phe_411_2_ldpred_METAss_amrld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.367 [1.24, 1.5] | C-index: 0.74356 | — | age, sex, 20 PCs | — |
| PPM021913 | PGS005039 (Phe_411_2_ldpred_METAss_eurld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.321 [1.2, 1.46] | C-index: 0.74094 | — | age, sex, 20 PCs | — |
| PPM021914 | PGS005034 (Phe_411_2_ldpred_AFRss_afrld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.18 [1.06, 1.31] | C-index: 0.73506 | — | age, sex, 20 PCs | — |
| PPM021915 | PGS005036 (Phe_411_2_ldpred_HISss_amrld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.068 [0.97, 1.18] | C-index: 0.73277 | — | age, sex, 20 PCs | — |
| PPM021916 | PGS005035 (Phe_411_2_ldpred_EURss_eurld) |
PSS011798| African Ancestry| 10,479 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.252 [1.13, 1.39] | C-index: 0.73931 | — | age, sex, 20 PCs | — |
| PPM021935 | PGS005063 (Phe_427_21_ldpred_METAss_afrld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.378 [1.22, 1.56] | C-index: 0.82471 | — | age, sex, 20 PCs | — |
| PPM021936 | PGS005064 (Phe_427_21_ldpred_METAss_amrld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.317 [1.17, 1.48] | C-index: 0.82283 | — | age, sex, 20 PCs | — |
| PPM021937 | PGS005065 (Phe_427_21_ldpred_METAss_eurld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.352 [1.19, 1.54] | C-index: 0.82367 | — | age, sex, 20 PCs | — |
| PPM021938 | PGS005060 (Phe_427_21_ldpred_AFRss_afrld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.231 [1.08, 1.4] | C-index: 0.81914 | — | age, sex, 20 PCs | — |
| PPM021939 | PGS005062 (Phe_427_21_ldpred_HISss_amrld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.232 [1.08, 1.4] | C-index: 0.8194 | — | age, sex, 20 PCs | — |
| PPM021940 | PGS005061 (Phe_427_21_ldpred_EURss_eurld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.223 [1.06, 1.42] | C-index: 0.82015 | — | age, sex, 20 PCs | — |
| PPM021941 | PGS005063 (Phe_427_21_ldpred_METAss_afrld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.619 [1.55, 1.69] | C-index: 0.82332 | — | age, sex, 20 PCs | — |
| PPM021943 | PGS005065 (Phe_427_21_ldpred_METAss_eurld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.67 [1.6, 1.74] | C-index: 0.82526 | — | age, sex, 20 PCs | — |
| PPM021944 | PGS005060 (Phe_427_21_ldpred_AFRss_afrld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.208 [1.16, 1.26] | C-index: 0.80875 | — | age, sex, 20 PCs | — |
| PPM021945 | PGS005062 (Phe_427_21_ldpred_HISss_amrld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.206 [1.16, 1.26] | C-index: 0.80897 | — | age, sex, 20 PCs | — |
| PPM021946 | PGS005061 (Phe_427_21_ldpred_EURss_eurld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.639 [1.57, 1.71] | C-index: 0.82287 | — | age, sex, 20 PCs | — |
| PPM021947 | PGS005063 (Phe_427_21_ldpred_METAss_afrld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.235 [1.12, 1.37] | C-index: 0.74798 | — | age, sex, 20 PCs | — |
| PPM021948 | PGS005064 (Phe_427_21_ldpred_METAss_amrld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.185 [1.08, 1.3] | C-index: 0.74675 | — | age, sex, 20 PCs | — |
| PPM021949 | PGS005065 (Phe_427_21_ldpred_METAss_eurld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.282 [1.16, 1.42] | C-index: 0.74939 | — | age, sex, 20 PCs | — |
| PPM021950 | PGS005060 (Phe_427_21_ldpred_AFRss_afrld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.246 [1.11, 1.39] | C-index: 0.74621 | — | age, sex, 20 PCs | — |
| PPM021952 | PGS005061 (Phe_427_21_ldpred_EURss_eurld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.13 [1.03, 1.24] | C-index: 0.74445 | — | age, sex, 20 PCs | — |
| PPM021953 | PGS005076 (Phe_428_1_ldpred_METAss_afrld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.354 [1.17, 1.57] | C-index: 0.79231 | — | age, sex, 20 PCs | — |
| PPM021954 | PGS005077 (Phe_428_1_ldpred_METAss_amrld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.315 [1.14, 1.52] | C-index: 0.7917 | — | age, sex, 20 PCs | — |
| PPM021955 | PGS005078 (Phe_428_1_ldpred_METAss_eurld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.371 [1.18, 1.59] | C-index: 0.79286 | — | age, sex, 20 PCs | — |
| PPM021956 | PGS005073 (Phe_428_1_ldpred_AFRss_afrld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.139 [1.01, 1.29] | C-index: 0.79007 | — | age, sex, 20 PCs | — |
| PPM021957 | PGS005075 (Phe_428_1_ldpred_HISss_amrld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.052 [0.92, 1.2] | C-index: 0.78786 | — | age, sex, 20 PCs | — |
| PPM021958 | PGS005074 (Phe_428_1_ldpred_EURss_eurld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.386 [1.14, 1.68] | C-index: 0.79052 | — | age, sex, 20 PCs | — |
| PPM021960 | PGS005077 (Phe_428_1_ldpred_METAss_amrld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.452 [1.38, 1.53] | C-index: 0.75358 | — | age, sex, 20 PCs | — |
| PPM021961 | PGS005078 (Phe_428_1_ldpred_METAss_eurld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.442 [1.37, 1.52] | C-index: 0.75253 | — | age, sex, 20 PCs | — |
| PPM021962 | PGS005073 (Phe_428_1_ldpred_AFRss_afrld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.128 [1.07, 1.19] | C-index: 0.74096 | — | age, sex, 20 PCs | — |
| PPM021963 | PGS005075 (Phe_428_1_ldpred_HISss_amrld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.095 [1.04, 1.15] | C-index: 0.73981 | — | age, sex, 20 PCs | — |
| PPM021964 | PGS005074 (Phe_428_1_ldpred_EURss_eurld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.427 [1.35, 1.51] | C-index: 0.75177 | — | age, sex, 20 PCs | — |
| PPM021965 | PGS005076 (Phe_428_1_ldpred_METAss_afrld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.369 [1.23, 1.52] | C-index: 0.71935 | — | age, sex, 20 PCs | — |
| PPM021966 | PGS005077 (Phe_428_1_ldpred_METAss_amrld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.37 [1.24, 1.52] | C-index: 0.7197 | — | age, sex, 20 PCs | — |
| PPM021967 | PGS005078 (Phe_428_1_ldpred_METAss_eurld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.38 [1.24, 1.54] | C-index: 0.71824 | — | age, sex, 20 PCs | — |
| PPM021968 | PGS005073 (Phe_428_1_ldpred_AFRss_afrld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.22 [1.12, 1.33] | C-index: 0.71526 | — | age, sex, 20 PCs | — |
| PPM021970 | PGS005074 (Phe_428_1_ldpred_EURss_eurld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.291 [1.11, 1.5] | C-index: 0.71208 | — | age, sex, 20 PCs | — |
| PPM021849 | PGS005066 (Phe_427_21_prscs_AFRss_afrld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.164 [1.12, 1.21] | C-index: 0.8076 | — | age, sex, 20 PCs | — |
| PPM021850 | PGS005068 (Phe_427_21_prscs_HISss_amrld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.146 [1.1, 1.2] | C-index: 0.80732 | — | age, sex, 20 PCs | — |
| PPM021851 | PGS005067 (Phe_427_21_prscs_EURss_eurld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.734 [1.66, 1.81] | C-index: 0.82758 | — | age, sex, 20 PCs | — |
| PPM021802 | PGS005041 (Phe_411_2_prscs_EURss_eurld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.345 [1.19, 1.53] | C-index: 0.82428 | — | age, sex, 20 PCs | — |
| PPM021840 | PGS005070 (Phe_427_21_prscs_METAss_amrld) |
PSS011810| Hispanic or Latin American Ancestry| 6,775 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.396 [1.23, 1.58] | C-index: 0.82598 | — | age, sex, 20 PCs | — |
| PPM021852 | PGS005072 (Phe_427_21_prscsx_METAweight) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.684 [1.61, 1.76] | C-index: 0.82639 | — | age, sex, 20 PCs | — |
| PPM021860 | PGS005082 (Phe_428_1_prscs_METAss_afrld) |
PSS011811| Hispanic or Latin American Ancestry| 8,119 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.31 [1.14, 1.5] | C-index: 0.79176 | — | age, sex, 20 PCs | — |
| PPM022174 | PGS003332 (PRS_VTE_EUR_GHOUSE) |
PSS011827| Multi-ancestry (including European)| 8,210 individuals |
PGP000681 | Rifkin AS et al. World J Gastroenterol (2023) |Ext. |
Reported Trait: Incident venous thromboembolism in individuals with inflammatory bowel disease | — | AUROC: 0.68 [0.65, 0.71] | Hazard ratio (HR, PGS in top 10% vs middle 80%): 1.98 [1.52, 2.57] | Sex, body mass index, 10 PCs | 1,515 SNPs from F2 and F5 genes excluded |
| PPM021869 | PGS005084 (Phe_428_1_prscs_METAss_eurld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.45 [1.37, 1.53] | C-index: 0.75272 | — | age, sex, 20 PCs | — |
| PPM021879 | PGS005080 (Phe_428_1_prscs_EURss_eurld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.287 [1.13, 1.47] | C-index: 0.71297 | — | age, sex, 20 PCs | — |
| PPM021901 | PGS005039 (Phe_411_2_ldpred_METAss_eurld) |
PSS011808| Hispanic or Latin American Ancestry| 8,047 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Myocardial infarction | OR: 1.42 [1.25, 1.61] | C-index: 0.82713 | — | age, sex, 20 PCs | — |
| PPM021942 | PGS005064 (Phe_427_21_ldpred_METAss_amrld) |
PSS011820| European Ancestry| 25,409 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.497 [1.44, 1.56] | C-index: 0.81963 | — | age, sex, 20 PCs | — |
| PPM021951 | PGS005062 (Phe_427_21_ldpred_HISss_amrld) |
PSS011800| African Ancestry| 8,952 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Atrial fibrillation | OR: 1.069 [0.96, 1.19] | C-index: 0.7432 | — | age, sex, 20 PCs | — |
| PPM021959 | PGS005076 (Phe_428_1_ldpred_METAss_afrld) |
PSS011821| European Ancestry| 31,804 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.443 [1.37, 1.52] | C-index: 0.75325 | — | age, sex, 20 PCs | — |
| PPM021969 | PGS005075 (Phe_428_1_ldpred_HISss_amrld) |
PSS011801| African Ancestry| 10,682 individuals |
PGP000679 | Gunn S et al. HGG Adv (2024) |
Reported Trait: Congestive heart failure (CHF), NOS | OR: 1.089 [1.0, 1.19] | C-index: 0.70971 | — | age, sex, 20 PCs | — |
| PPM022178 | PGS005091 (PGS_LDP2Auto) |
PSS011830| Multi-ancestry (including European)| 171,095 individuals |
PGP000684 | Abramowitz SA et al. JAMA (2024) |
Reported Trait: Prevalent coronary heart disease | OR: 1.452 [1.427, 1.477] | AUROC: 0.776 | Brier score: 0.0825 | Age, sex | Scores in model are PCA-normalized |
| PPM022179 | PGS005091 (PGS_LDP2Auto) |
PSS011832| Multi-ancestry (including European)| 53,092 individuals |
PGP000684 | Abramowitz SA et al. JAMA (2024) |
Reported Trait: Prevalent coronary heart disease | OR: 1.374 [1.343, 1.406] | AUROC: 0.8 | Brier score: 0.143 | Age, sex, first 5 PCs | Scores in model are PCA-normalized |
| PPM022180 | PGS005091 (PGS_LDP2Auto) |
PSS011831| Multi-ancestry (including European)| 41,193 individuals |
PGP000684 | Abramowitz SA et al. JAMA (2024) |
Reported Trait: Prevalent coronary heart disease | OR: 1.547 [1.506, 1.59] | AUROC: 0.791 | Brier score: 0.1405 | Age, sex | Scores in model are PCA-normalized |
| PPM022181 | PGS005092 (PGS_prscsx) |
PSS011830| Multi-ancestry (including European)| 171,095 individuals |
PGP000684 | Abramowitz SA et al. JAMA (2024) |
Reported Trait: Prevalent coronary heart disease | OR: 1.407 [1.384, 1.43] | AUROC: 0.774 | Brier score: 0.0828 | Age, sex | Scores in model are PCA-normalized |
| PPM022182 | PGS005092 (PGS_prscsx) |
PSS011832| Multi-ancestry (including European)| 53,092 individuals |
PGP000684 | Abramowitz SA et al. JAMA (2024) |
Reported Trait: Prevalent coronary heart disease | OR: 1.384 [1.353, 1.416] | AUROC: 0.801 | Brier score: 0.1425 | Age, sex, first 5 PCs | Scores in model are PCA-normalized |
| PPM022183 | PGS005092 (PGS_prscsx) |
PSS011831| Multi-ancestry (including European)| 41,193 individuals |
PGP000684 | Abramowitz SA et al. JAMA (2024) |
Reported Trait: Prevalent coronary heart disease | OR: 1.562 [1.522, 1.604] | AUROC: 0.793 | Brier score: 0.1402 | Age, sex | Scores in model are PCA-normalized |
| PPM022207 | PGS005097 (prscsx_meta_HF) |
PSS011843| Multi-ancestry (including European)| 40,989 individuals |
PGP000691 | Lee DSM et al. Nat Genet (2025) |
Reported Trait: Prevalent heart failure | — | AUROC: 0.72 [0.72, 0.73] | Brier skill score: 0.065 [0.063, 0.068] | Age, sex, 5 genetic principal components | — |
| PPM022185 | PGS005094 (ProPRS) |
PSS011833| Multi-ancestry (including European)| 34,177 individuals |
PGP000685 | Yang X et al. Nat Commun (2026) |
Reported Trait: coronary artery disease | HR: 1.05 [1.03, 1.07] OR: 1.07 [1.04, 1.1] |
— | — | age, sex, PC1-10 | — |
| PPM022291 | PGS003727 (GPS_CADEUR) |
PSS011903| Multi-ancestry (including European)| 429 individuals |
PGP000695 | Reeskamp LF et al. JACC Adv (2023) |Ext. |
Reported Trait: Incident coronary artery disease among heterozygous familial hypercholesterolemia variant carriers | HR: 1.31 [0.97, 1.77] | — | — | Age, sex, 5 PCs | — |
| PPM021753 | PGS004946 (DCM_GWAS_exclMGBB) |
PSS011781| Multi-ancestry (including European)| 96,016 individuals |
PGP000672 | Jurgens SJ et al. Nat Genet (2024) |
Reported Trait: Non-ischemic dilated cardiomyopathy | OR: 1.65762 β: 0.5 (0.04) |
— | Univariate (PRS only) AUPRC: 0.0095 Nagelkerke pseudo-R^2 full model: 0.064 Nagelkerke pseudo-R^2 delta PRS/residual: 0.023 Liability-scale R^2 (assuming 0.4% prev) full model: 0.227 Liability-scale R^2 (assuming 0.4% prev) delta PRS/residual: 0.066 Univariate (PRS only) AUC: 0.65 [0.62, 0.67] |
Age, age^2, sex, PC1-12 | beta represents log(OR) per SD of PRS |
| PPM022290 | PGS003727 (GPS_CADEUR) |
PSS011902| European Ancestry| 1,315 individuals |
PGP000695 | Reeskamp LF et al. JACC Adv (2023) |Ext. |
Reported Trait: Incident coronary artery disease among heterozygous familial hypercholesterolemia variant carriers | HR: 1.35 [1.07, 1.7] | — | — | Age, sex, 5 PCs | — |
| PPM022303 | PGS005112 (PGS_CAD) |
PSS011911| Multi-ancestry (including European)| 48,603 individuals |
PGP000701 | Loesch DP et al. Nat Commun (2025) |
Reported Trait: coronary artery disease | OR: 1.45 [1.41, 1.49] | — | — | age, age^2, sex, UKB centre, array, genetic PCS 1-20 | — |
| PPM022314 | PGS005112 (PGS_CAD) |
PSS011912| European Ancestry| 45,356 individuals |
PGP000701 | Loesch DP et al. Nat Commun (2025) |
Reported Trait: coronary artery disease | OR: 1.46 [1.42, 1.5] | — | — | age, age^2, sex, UKB centre, array, genetic PCS 1-20 | — |
| PPM022379 | PGS005158 (PRS19_PAD) |
PSS011930| European Ancestry| 10,836 individuals |
PGP000705 | Zhu K et al. Diabetes Care (2024) |
Reported Trait: Peripheral artery disease in type 2 diabetes x lifestyle interaction | — | — | Hazard ratio (HR, unfavorable lifestyle and high PRS vs. favorable life style and low PRS): 5.03 [2.74, 9.22] | age (continuous, years), sex (male, female), education attainment (college or university degree, A/AS levels or equivalent or O levels/ GCSEs or equivalent or other professional qualifications, or none of the above), Townsend Deprivation Index (continuous), family history of CVD (yes, no), prevalence of hypertension (yes, no), use of antihypertensive medication (yes, no), use of lipid-lowing medication (yes, no), aspirin use (yes, no), diabetes duration (continuous, years), HbA1c (continuous, %), use of diabetes medication (none, only oral medication pills, only insulin, or combination of oral medications and insulin), genotype measurement batch, and the first 10 principal components of ancestry | fig 1 |
| PPM022385 | PGS005159 (GRS142_AF) |
PSS011934| European Ancestry| 3,094 individuals |
PGP000709 | Frederiksen TC et al. Heart (2024) |
Reported Trait: Atrial fibrillation | — | — | Hazard ratio (HR, high vs low tertile): 4.27 [3.61, 5.06] | age, sex, educational level, heart failure, stroke, diabetes mellitus, and myocardial infarction at baseline | — |
| PPM022386 | PGS005159 (GRS142_AF) |
PSS011934| European Ancestry| 3,094 individuals |
PGP000709 | Frederiksen TC et al. Heart (2024) |
Reported Trait: Atrial fibrillation x lifestyle status interaction | — | — | Hazard ratio (HR, poor lifestyle and high PRS vs. ideal lifestyle and low PRS): 11.33 [6.15, 20.85] | age, sex, educational level, heart failure, stroke, diabetes mellitus, myocardial infarction and for competing risk of death | — |
| PPM022363 | PGS005143 (Coronary artery disease (PRS-CS; EAS)) |
PSS011925| East Asian Ancestry| 58,625 individuals |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Reported Trait: Coronary artery disease | β: 1.27561 | — | — | age, sex | — |
| PPM022364 | PGS005144 (Hypertension (PRS-CS; EAS)) |
PSS011921| East Asian Ancestry| 37,185 individuals |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Reported Trait: Hypertension | β: 1.71261 | — | — | age, sex | — |
| PPM022372 | PGS005152 (Coronary artery disease (PRS-CSx; EAS+EUR)) |
PSS011925| East Asian Ancestry| 58,625 individuals |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Reported Trait: Coronary artery disease | β: 1.30833 | — | — | age, sex | — |
| PPM022373 | PGS005153 (Hypertension (CT-SLEB; EAS+EUR)) |
PSS011921| East Asian Ancestry| 37,185 individuals |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Reported Trait: Hypertension | β: 2.03809 | — | — | age, sex | — |
| PPM022376 | PGS005156 (Stroke (PRS-CSx; EAS+EUR)) |
PSS011929| East Asian Ancestry| 58,633 individuals |
PGP000704 | Jung HU et al. Commun Biol (2025) |
Reported Trait: Stroke | β: 1.17852 | — | — | age, sex | — |
| PPM022378 | PGS005158 (PRS19_PAD) |
PSS011930| European Ancestry| 10,836 individuals |
PGP000705 | Zhu K et al. Diabetes Care (2024) |
Reported Trait: Peripheral artery disease in type 2 diabetes | HR: 1.13 [1.03, 1.23] | — | — | age (continuous, years), sex (male, female), Townsend Deprivation Index (continuous), race/ethnicity (White, others), education attainment (college or university degree, A/AS levels or equivalent or O levels/GCSEs or equivalent or other professional qualifications, or none of the above), family history of CVD (yes, no), prevalence of hypertension (yes, no), use of antihypertensive medication (yes, no), use of lipidlowing medication (yes, no), use of aspirin (yes, no), diabetes duration (continuous, years), HbA1c (continuous, %), use of diabetes medication (none, only oral medication pills, or only insulin or combination of oral medications and insulin), genotype measurement batch, the first 10 principal components of ancestry, weighted healthy lifestyle scores (continuous) | ST3 |
| PPM021366 | PGS004910 (hcm.gwama) |
PSS011704| European Ancestry| 343,182 individuals |
PGP000642 | Zheng SL et al. Nat Genet (2025) |
Reported Trait: Hypertrophic cardiomyopathy | HR: 1.97 OR: 1.26 |
AUROC: 0.73 | R²: 0.031 Odds ratio (OR, high vs median tertile): 5.5 |
age, age^2, sex, PC1-10 | — |
| PPM022406 | PGS005168 (PRSAF) |
PSS011945| European Ancestry| 52,757 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Atrial fibrillation | HR: 1.6663 β: 0.5106 (0.0206) |
C-index: 0.8718 [0.8657, 0.878] | — | age, age^2, sex, geno_array, CHARGE-AF | — |
| PPM022407 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Atrial fibrillation | HR: 1.6005 β: 0.4703 (0.0096) |
C-index: 0.7895 [0.7855, 0.7936] | — | age, age^2, sex, geno_array, CHARGE-AF | — |
| PPM022408 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Heart Failure | β: 0.173 (0.0094) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022409 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Dilated cardiomyopathy | β: 0.2 (0.0349) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022410 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Atrial fibrillation or flutter | β: 0.5568 (0.0068) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022411 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Supraventricular arrhythmia | β: 0.3159 (0.0152) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022412 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Ventricular arrhythmia | β: 0.112 (0.015) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022413 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Ventricular arrhythmia Sudden cardiac death | β: 0.0748 (0.0214) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022414 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Bradyarrhythmia | β: 0.0937 (0.0084) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022415 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Bradyarrhythmia AV block or distal conduction disease | β: 0.0628 (0.0099) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022416 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Bradyarrhythmia Pacemaker | β: 0.1296 (0.0116) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022417 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Aortic valve disease | β: 0.0619 (0.0123) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022418 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Mitral valve disease | β: 0.1804 (0.0113) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022419 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Tricuspid valve disease | β: 0.2134 (0.0155) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022420 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Peripheral vascular disease | β: 0.0608 (0.0122) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022421 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Venous thromboembolism | β: 0.0395 (0.008) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022422 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Ischemic stroke | β: 0.1436 (0.0147) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022423 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Stroke | β: 0.0901 (0.0101) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022424 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Coronary Artery Disease | β: 0.0373 (0.0069) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022425 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Myocardial Infarction | β: 0.0449 (0.0083) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022427 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Hypertension | β: 0.0474 (0.0035) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022428 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Diabetes Type 2 | β: 0.0278 (0.0062) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022429 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Hyperthyroidism | β: 0.0746 (0.0137) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022430 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Hypothyroidism | β: 0.0341 (0.0063) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022431 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Gout | β: 0.0457 (0.0103) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022432 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Asthma | β: 0.0172 (0.0046) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022433 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Diverticular disease | β: 0.0286 (0.0051) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022434 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Chronic kidney disease | β: 0.0701 (0.009) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022435 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Osteoarthritis | β: 0.02 (0.004) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022436 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Sleep apnea | β: 0.0579 (0.0116) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022437 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Pneumonia | β: 0.0447 (0.0067) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022438 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Height | β: 0.2656 (0.0101) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022440 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Body mass index | β: 0.0928 (0.0076) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022426 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Hypercholesterolemia | β: 0.0302 (0.0041) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022439 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Weight | β: 0.5037 (0.0225) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022441 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Diastolic blood pressure | β: 0.0823 (0.016) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022442 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: High density lipoprotein | β: -0.0041 (0.0006) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022443 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Low density lipoprotein | β: -0.0103 (0.0014) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022444 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Triglycerides | β: -0.0064 (0.0016) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022445 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: P-wave duration | β: -0.4988 (0.0918) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022446 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: QRS-duration | β: -0.3295 (0.0736) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022447 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Left ventricular end-diastolic volume | β: 0.5077 (0.1366) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022448 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Left ventricular end-systolic volume | β: 0.4055 (0.0814) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022449 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Left ventricular ejection fraction | β: -0.0016 (0.0003) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022450 | PGS005168 (PRSAF) |
PSS011946| European Ancestry| 246,683 individuals |
PGP000712 | Roselli C et al. Nat Genet (2025) |
Reported Trait: Descending Aorta Diameter | β: 0.0046 (0.001) | — | — | age, sex, genotyping array, PCs 1-5 | — |
| PPM022493 | PGS005171 (PRS142_AF) |
PSS011973| Multi-ancestry (including European)| 457,151 individuals |
PGP000719 | Dai L et al. Diabetes Metab Syndr (2024) |
Reported Trait: Atrial fibrillation | — | — | Hazard ratio (HR, high vs low tertile): 2.56 [2.47, 2.65] | age, sex, genotyping array, and the first 10 principal components of ancestry | — |
| PPM022494 | PGS005171 (PRS142_AF) |
PSS011973| Multi-ancestry (including European)| 457,151 individuals |
PGP000719 | Dai L et al. Diabetes Metab Syndr (2024) |
Reported Trait: Atrial fibrillation x diabetes status interaction | — | — | Hazard ratio (HR, with diabetes and high PRS vs. without diabetes and low PRS): 3.04 [2.81, 3.28] | age at baseline, sex, Townsend deprivation index, assessment centers, smoking status, alcohol consumption frequency, physical activity, BMI, hypertension, dyslipidemia, sleep apnea, genotyping array, and the first 10 principal components of ancestry | — |
| PPM022599 | PGS005217 (PRS_PAD) |
PSS012034| African Ancestry| 6,939 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.26 [1.01, 1.59] | — | R²: 0.051 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022600 | PGS005217 (PRS_PAD) |
PSS012035| East Asian Ancestry| 1,761 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.6 [1.01, 2.53] | — | R²: 0.11217 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022601 | PGS005217 (PRS_PAD) |
PSS012036| South Asian Ancestry| 7,680 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.25 [1.07, 1.46] | — | R²: 0.07629 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022603 | PGS005217 (PRS_PAD) |
PSS012038| African Ancestry| 51,691 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.11 [1.06, 1.16] | — | R²: 0.10751 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022604 | PGS005217 (PRS_PAD) |
PSS012039| East Asian Ancestry| 5,268 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 0.98 [0.78, 1.22] | — | R²: 0.16129 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022605 | PGS005217 (PRS_PAD) |
PSS012040| European Ancestry| 119,167 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.25 [1.22, 1.27] | — | R²: 0.12104 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022606 | PGS005217 (PRS_PAD) |
PSS012041| Hispanic or Latin American Ancestry| 39,576 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.19 [1.13, 1.25] | — | R²: 0.15203 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022607 | PGS005217 (PRS_PAD) |
PSS012028| Greater Middle Eastern Ancestry| 509 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.04 [0.62, 1.75] | — | R²: 0.31662 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022608 | PGS005217 (PRS_PAD) |
PSS012029| South Asian Ancestry| 2,289 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.34 [1.02, 1.74] | — | R²: 0.29674 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022609 | PGS005217 (PRS_PAD) |
PSS012030| African Ancestry| 1,945 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.24 [0.94, 1.63] | — | R²: 0.11198 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022610 | PGS005217 (PRS_PAD) |
PSS012031| European Ancestry| 32,139 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.26 [1.17, 1.34] | — | R²: 0.11467 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022611 | PGS005217 (PRS_PAD) |
PSS012032| Hispanic or Latin American Ancestry| 2,933 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.22 [0.89, 1.67] | — | R²: 0.19935 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022612 | PGS005217 (PRS_PAD) |
PSS012033| Multi-ancestry (including European)| 304,294 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident peripheral artery disease | HR: 1.66 [1.61, 1.71] | C-index: 0.731 | — | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022648 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Incident stroke | HR: 1.09 [1.07, 1.11] | — | — | age, sex, genotyping batch, and the first ten genetic principal components | — |
| PPM022649 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Incident Ischemic stroke | HR: 1.12 [1.09, 1.15] | — | — | age, sex, genotyping batch, and the first ten genetic principal components | — |
| PPM022652 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Stroke onset x air pollution PM10 exposure interaction | — | — | Hazard ratio (HR, high PM2.5 and high PRS vs. low PM2.5 and low PRS): 1.48 [1.33, 1.65] | sex, ethnicity, household income, educational background, alcohol consumption status, smoking status, healthy diet score, physical activity, body mass index, hypertension, hyperlipidemia, diabetes, asthma, chronic obstructive pulmonary disease, genotyping batch, and the first 10 genetic principal components | — |
| PPM022653 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Stroke onset x air pollution NO2 exposure interaction | — | — | Hazard ratio (HR, high PM2.5 and high PRS vs. low PM2.5 and low PRS): 1.51 [1.35, 1.69] | sex, ethnicity, household income, educational background, alcohol consumption status, smoking status, healthy diet score, physical activity, body mass index, hypertension, hyperlipidemia, diabetes, asthma, chronic obstructive pulmonary disease, genotyping batch, and the first 10 genetic principal components | — |
| PPM022654 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Stroke onset x air pollution NOx exposure interaction | — | — | Hazard ratio (HR, high PM2.5 and high PRS vs. low PM2.5 and low PRS): 1.39 [1.25, 1.55] | sex, ethnicity, household income, educational background, alcohol consumption status, smoking status, healthy diet score, physical activity, body mass index, hypertension, hyperlipidemia, diabetes, asthma, chronic obstructive pulmonary disease, genotyping batch, and the first 10 genetic principal components | — |
| PPM022655 | PGS000035 (PRS_AF) |
PSS012048| Multi-ancestry (excluding European)| 14,259 individuals |
PGP000737 | Qafoud F et al. J Clin Med (2024) |Ext. |
Reported Trait: Atrial fibrillation | OR: 1.29 [1.02, 1.65] | AUROC: 0.58 | — | sex, age, and 5 PCs | — |
| PPM022656 | PGS000331 (PRS_AF) |
PSS012048| Multi-ancestry (excluding European)| 14,259 individuals |
PGP000737 | Qafoud F et al. J Clin Med (2024) |Ext. |
Reported Trait: Atrial fibrillation | OR: 1.33 [1.02, 1.73] | AUROC: 0.56 | — | sex, age, and 5 PCs | — |
| PPM022657 | PGS000727 (AF_PGS) |
PSS012048| Multi-ancestry (excluding European)| 14,259 individuals |
PGP000737 | Qafoud F et al. J Clin Med (2024) |Ext. |
Reported Trait: Atrial fibrillation | OR: 1.43 [1.03, 1.97] | AUROC: 0.55 | — | sex, age, and 5 PCs | — |
| PPM022658 | PGS001339 (GBE_HC964) |
PSS012048| Multi-ancestry (excluding European)| 14,259 individuals |
PGP000737 | Qafoud F et al. J Clin Med (2024) |Ext. |
Reported Trait: Atrial fibrillation | OR: 1.32 [1.04, 1.68] | AUROC: 0.56 | — | sex, age, and 5 PCs | — |
| PPM022659 | PGS001340 (GBE_HC281) |
PSS012048| Multi-ancestry (excluding European)| 14,259 individuals |
PGP000737 | Qafoud F et al. J Clin Med (2024) |Ext. |
Reported Trait: Atrial fibrillation | OR: 1.31 [1.02, 1.67] | AUROC: 0.56 | — | sex, age, and 5 PCs | — |
| PPM022660 | PGS005231 (GRS142_CAD) |
PSS012050| Multi-ancestry (including European)| 8,587 individuals |
PGP000738 | Severance LM et al. JACC Cardiovasc Imaging (2021) |
Reported Trait: coronary artery calcium | OR: 1.33 [1.26, 1.4] | — | — | age, sex | — |
| PPM022661 | PGS005231 (GRS142_CAD) |
PSS012049| Multi-ancestry (including European)| 6,660 individuals |
PGP000738 | Severance LM et al. JACC Cardiovasc Imaging (2021) |
Reported Trait: coronary artery calcium | — | — | Odds ratio (OR, high vs low tertile): 2.68 | age, sex, number of traditional risk factors, family history | — |
| PPM022662 | PGS005231 (GRS142_CAD) |
PSS012049| Multi-ancestry (including European)| 6,660 individuals |
PGP000738 | Severance LM et al. JACC Cardiovasc Imaging (2021) |
Reported Trait: coronary artery calcium with family history of an event | — | — | Odds ratio (OR, high vs low tertile): 2.44 | age, sex, number of traditional risk factors | — |
| PPM022663 | PGS005231 (GRS142_CAD) |
PSS012049| Multi-ancestry (including European)| 6,660 individuals |
PGP000738 | Severance LM et al. JACC Cardiovasc Imaging (2021) |
Reported Trait: coronary artery calcium without family history of an event | — | — | Odds ratio (OR, high vs low tertile): 2.89 | age, sex, number of traditional risk factors | — |
| PPM022598 | PGS005217 (PRS_PAD) |
PSS012027| European Ancestry| 286,356 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.66 [1.62, 1.71] | — | R²: 0.0888 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022602 | PGS005217 (PRS_PAD) |
PSS012037| Greater Middle Eastern Ancestry| 7,680 individuals |
PGP000732 | Flores AM et al. JAMA Cardiol (2025) |
Reported Trait: Incident and prevelant peripheral artery disease | OR: 1.62 [1.1, 2.44] | — | R²: 0.0826 | age, sex and the first ten principal components of genetic ancestry | — |
| PPM022650 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Incident Hemorrhagic stroke | HR: 1.05 [1.0, 1.1] | — | — | age, sex, genotyping batch, and the first ten genetic principal components | — |
| PPM022651 | PGS005230 (PRS71_STROKE) |
PSS012047| European Ancestry| 452,196 individuals |
PGP000736 | Ma Y et al. Stroke (2023) |
Reported Trait: Stroke onset x air pollution PM2.5 exposure interaction | — | — | Hazard ratio (HR, high PM2.5 and high PRS vs. low PM2.5 and low PRS): 1.45 [1.31, 1.61] | sex, ethnicity, household income, educational background, alcohol consumption status, smoking status, healthy diet score, physical activity, body mass index, hypertension, hyperlipidemia, diabetes, asthma, chronic obstructive pulmonary disease, genotyping batch, and the first 10 genetic principal components | — |
| PPM022669 | PGS005236 (CAD_AnnoPred) |
PSS012052| European Ancestry| 407,903 individuals |
PGP000740 | Hu J et al. PLoS Comput Biol (2025) |
Reported Trait: Coronary artery disease | HR: 1.72 | — | — | — | — |
| PPM021385 | PGS000011 (GRS50) |
PSS011720| Ancestry Not Reported| 23,594 individuals |
PGP000650 | Sjögren M et al. Int J Cardiol Heart Vasc (2019) |Ext. |
Reported Trait: Number of hospitilizations for any cause | — | — | Incidence Rate Ratio (IRR, top vs bottom PGS quintiles): 1.1 [1.04, 1.16] | Age, sex, follow up time, hypertension, prevalent diabetes, smoking, ApoA1, ApoB | — |
| PPM022736 | PGS005253 (CVD_MetaPRS) |
PSS012067| East Asian Ancestry| 72,149 individuals |
PGP000746 | Sun D et al. Genome Med (2025) |
Reported Trait: Incident cardiovascular disease | HR: 1.2 [1.19, 1.22] | — | — | age, sex, highest education, marital status, top 10 genetic principal components, and genotyping arrays | — |
| PPM022733 | PGS005252 (IAVGC_AS_PRS) |
PSS012066| European Ancestry| 446,895 individuals |
PGP000745 | Small AM et al. Nat Genet (2025) |
Reported Trait: Incident aortic stenosis cases | HR: 1.92 | C-index: 0.87 | — | age, sex, genetic ancestry principal components 1-5, type 2 diabetes, hypertension, coronary artery disease, hyperlipidemia, body mass index, current smoking, renal failure. | — |
| PPM022734 | PGS005252 (IAVGC_AS_PRS) |
PSS012065| European Ancestry| 34,024 individuals |
PGP000745 | Small AM et al. Nat Genet (2025) |
Reported Trait: Any aortic stenosis | OR: 1.43 | — | — | age, sex, genetic ancestry principal components 1-5, type 2 diabetes, hypertension, coronary artery disease, hyperlipidemia, body mass index, current smoking, renal failure. | — |
| PPM022735 | PGS005252 (IAVGC_AS_PRS) |
PSS012064| European Ancestry| 59,866 individuals |
PGP000745 | Small AM et al. Nat Genet (2025) |
Reported Trait: Incident aortic stenosis cases | HR: 1.8 | C-index: 0.76 | — | age, sex, genetic ancestry principal components 1-5, type 2 diabetes, hypertension, coronary artery disease, hyperlipidemia, body mass index, current smoking, renal failure. | — |
| PPM022737 | PGS005254 (aortic_stenosis) |
PSS012068| European Ancestry| 244,450 individuals |
PGP000747 | Kany S et al. Nat Genet (2025) |
Reported Trait: incident aortic stenosis | HR: 1.64 [1.5, 1.78] | — | — | self-reported sex, age at DNA collection, age2 at DNA collection, and the first five principal components of genetic ancestry. | — |
| PPM022738 | PGS005255 (mean_gradient) |
PSS012068| European Ancestry| 244,450 individuals |
PGP000747 | Kany S et al. Nat Genet (2025) |
Reported Trait: incident aortic stenosis | HR: 1.53 [1.4, 1.66] | — | — | self-reported sex, age at DNA collection, age2 at DNA collection, and the first five principal components of genetic ancestry. | — |
| PPM022739 | PGS005256 (peak_velocity) |
PSS012068| European Ancestry| 244,450 individuals |
PGP000747 | Kany S et al. Nat Genet (2025) |
Reported Trait: incident aortic stenosis | HR: 1.53 [1.41, 1.67] | — | — | self-reported sex, age at DNA collection, age2 at DNA collection, and the first five principal components of genetic ancestry. | — |
| PPM022979 | PGS000018 (metaGRS_CAD) |
PSS012083| European Ancestry| 5,093 individuals |
PGP000754 | Liu Y et al. Nat Aging (2024) |Ext. |
Reported Trait: Incident coronary artery disease | HR: 1.68 [1.5, 1.88] β: 0.51613 |
— | — | Baseline age, BMI, systolic BP, total cholesterol, HDL, smoking, exercise, prevelant diabetes, family history, gut microbiome score | — |
| PPM022992 | PGS005285 (BBJ_HF_PRS_HG19) |
PSS012088| East Asian Ancestry| 13,157 individuals |
PGP000757 | Enzan N et al. Nat Commun (2025) |
Reported Trait: incident all-cause heart failure cases | — | — | R²: 0.0737 | — | — |
| PPM022996 | PGS005288 (Jorda_AF_MTAG-PGS_females_2024) |
PSS012091| European Ancestry| 5,152 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent atrial fibrillation or flutter | — | AUROC: 0.68996 | R²: 0.11543 | age, sex, four first principal components of genetic ancestry | — |
| PPM022997 | PGS005289 (Jorda_AF_MTAG-PGS_males_2024) |
PSS012092| European Ancestry| 7,525 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent atrial fibrillation or flutter | — | AUROC: 0.6813 | R²: 0.12547 | age, sex, four first principal components of genetic ancestry | — |
| PPM022998 | PGS005290 (Jorda_AF_SingleTrait-PGS_2024) |
PSS012090| European Ancestry| 12,677 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent atrial fibrillation or flutter | — | AUROC: 0.703 | R²: 0.14556 | age, sex, four first principal components of genetic ancestry | — |
| PPM022999 | PGS005291 (Jorda_AF_SingleTrait-PGS_females_2024) |
PSS012091| European Ancestry| 5,152 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent atrial fibrillation or flutter | — | AUROC: 0.69331 | R²: 0.11768 | age, sex, four first principal components of genetic ancestry | — |
| PPM023000 | PGS005292 (Jorda_AF_SingleTrait-PGS_males_2024) |
PSS012092| European Ancestry| 7,525 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent atrial fibrillation or flutter | — | AUROC: 0.68445 | R²: 0.12821 | age, sex, four first principal components of genetic ancestry | — |
| PPM023035 | PGS005313 (AF_PGS_YuanS) |
PSS012099| Multi-ancestry (including European)| 37,161 individuals |
PGP000761 | Yuan S et al. Nat Commun (2025) |
Reported Trait: atrial fibrillation | OR: 1.82 [1.79, 1.85] | AUROC: 0.78 [0.778, 0.783] | — | age, sex | Tested in Penn Medicine Biobank (4401 individuals with AF and 32,760 individuals without AF) |
| PPM023040 | PGS003725 (GPS_Mult) |
PSS012103| Multi-ancestry (including European)| 663 individuals |
PGP000763 | Zou RS et al. J Am Heart Assoc (2024) |Ext. |
Reported Trait: Stenosis over 50% | OR: 2.39 [1.48, 3.85] | — | — | age, sex, and the first 10 principal components of ancestry | — |
| PPM023041 | PGS003725 (GPS_Mult) |
PSS012103| Multi-ancestry (including European)| 663 individuals |
PGP000763 | Zou RS et al. J Am Heart Assoc (2024) |Ext. |
Reported Trait: Visible non calcified plaque or with vulnerable features | OR: 1.45 [1.23, 1.72] | — | — | age, sex, and the first 10 principal components of ancestry | — |
| PPM023003 | PGS005295 (Jorda_CAD_MTAG-PGS_males_2024) |
PSS012092| European Ancestry| 7,525 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent coronary artery disease defined as myocardial infarction, percutaneous transluminal coronary angioplasty, coronary artery bypass grafting, unstable angina and chronic ischemic heart disease. | — | AUROC: 0.69218 | R²: 0.15544 | age, sex, four first principal components of genetic ancestry | — |
| PPM023004 | PGS005296 (Jorda_CAD_SingleTrait-PGS_2024) |
PSS012090| European Ancestry| 12,677 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent coronary artery disease defined as myocardial infarction, percutaneous transluminal coronary angioplasty, coronary artery bypass grafting, unstable angina and chronic ischemic heart disease. | — | AUROC: 0.772 | R²: 0.27809 | age, sex, four first principal components of genetic ancestry | — |
| PPM023005 | PGS005297 (Jorda_CAD_SingleTrait-PGS_females_2024) |
PSS012091| European Ancestry| 5,152 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent coronary artery disease defined as myocardial infarction, percutaneous transluminal coronary angioplasty, coronary artery bypass grafting, unstable angina and chronic ischemic heart disease. | — | AUROC: 0.68603 | R²: 0.10575 | age, sex, four first principal components of genetic ancestry | — |
| PPM023007 | PGS005299 (Jorda_HF_MTAG-PGS-inf_2024) |
PSS012090| European Ancestry| 12,677 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent heart failure | — | AUROC: 0.616 | R²: 0.03455 | age, sex, four first principal components of genetic ancestry | — |
| PPM023008 | PGS005300 (Jorda_HF_MTAG-PGS_2024) |
PSS012090| European Ancestry| 12,677 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent heart failure | — | AUROC: 0.612 | R²: 0.03182 | age, sex, four first principal components of genetic ancestry | — |
| PPM023009 | PGS005301 (Jorda_HF_MTAG-PGS_females_2024) |
PSS012091| European Ancestry| 5,152 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent heart failure | — | AUROC: 0.62709 | R²: 0.03046 | age, sex, four first principal components of genetic ancestry | — |
| PPM023010 | PGS005302 (Jorda_HF_MTAG-PGS_males_2024) |
PSS012092| European Ancestry| 7,525 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent heart failure | — | AUROC: 0.57482 | R²: 0.01618 | age, sex, four first principal components of genetic ancestry | — |
| PPM023011 | PGS005303 (Jorda_HF_SingleTrait-PGS-inf_2024) |
PSS012090| European Ancestry| 12,677 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent heart failure | — | AUROC: 0.613 | R²: 0.03272 | age, sex, four first principal components of genetic ancestry | — |
| PPM023012 | PGS005304 (Jorda_HF_SingleTrait-PGS_2024) |
PSS012090| European Ancestry| 12,677 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent heart failure | — | AUROC: 0.611 | R²: 0.03107 | age, sex, four first principal components of genetic ancestry | — |
| PPM023013 | PGS005305 (Jorda_HF_SingleTrait-PGS_females_2024) |
PSS012091| European Ancestry| 5,152 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent heart failure | — | AUROC: 0.628 | R²: 0.03192 | age, sex, four first principal components of genetic ancestry | — |
| PPM023014 | PGS005306 (Jorda_HF_SingleTrait-PGS_males_2024) |
PSS012092| European Ancestry| 7,525 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent heart failure | — | AUROC: 0.57178 | R²: 0.01529 | age, sex, four first principal components of genetic ancestry | — |
| PPM023066 | PGS005319 (HF_PRS) |
PSS012106| European Ancestry| 32,360 individuals |
PGP000766 | Türkmen D et al. Pharmacogenomics J (2024) |
Reported Trait: Incident heart failure | HR: 1.14 [1.09, 1.19] | — | — | sex, age at first prescription and genetic principal components 1 to 10 | — |
| PPM023069 | PGS005322 (PRS_EC) |
PSS012110| European Ancestry| 348,967 individuals |
PGP000768 | Marston NA et al. Nat Med (2025) |
Reported Trait: Incident CAD | HR: 1.23 [1.21, 1.26] | — | — | age, sex, population structure (by principal components 1-5), smoking, LDL-C, systolic blood pressure, HbA1c and hsCRP | — |
| PPM023070 | PGS005322 (PRS_EC) |
PSS012110| European Ancestry| 348,967 individuals |
PGP000768 | Marston NA et al. Nat Med (2025) |
Reported Trait: Incident CAD x LDL-C (150 mg/dl) interaction | HR: 1.26 [1.22, 1.3] | — | — | — | — |
| PPM023071 | PGS005322 (PRS_EC) |
PSS012109| European Ancestry| 8,749 individuals |
PGP000768 | Marston NA et al. Nat Med (2025) |
Reported Trait: Incident CAD in placebo arm | HR: 1.3 [1.1, 1.53] | — | — | — | — |
| PPM023072 | PGS005322 (PRS_EC) |
PSS012109| European Ancestry| 8,749 individuals |
PGP000768 | Marston NA et al. Nat Med (2025) |
Reported Trait: myocardial infarction or coronary revascularization in placebo arm | — | — | Hazard ratio (HR, high vs low tertile): 2.51 [1.27, 4.93] | — | — |
| PPM023073 | PGS005322 (PRS_EC) |
PSS012108| European Ancestry| 14,298 individuals |
PGP000768 | Marston NA et al. Nat Med (2025) |
Reported Trait: major vascular events in placebo arm | HR: 1.16 [1.08, 1.25] | — | — | — | — |
| PPM023039 | PGS003725 (GPS_Mult) |
PSS012103| Multi-ancestry (including European)| 663 individuals |
PGP000763 | Zou RS et al. J Am Heart Assoc (2024) |Ext. |
Reported Trait: Plaque presence (on coronary computed tomography angiography) | OR: 1.42 [1.2, 1.68] | — | — | age, sex, and the first 10 principal components of ancestry | — |
| PPM022995 | PGS005287 (Jorda_AF_MTAG-PGS_2024) |
PSS012090| European Ancestry| 12,677 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent atrial fibrillation or flutter | — | AUROC: 0.703 | R²: 0.14693 | age, sex, four first principal components of genetic ancestry | — |
| PPM023001 | PGS005293 (Jorda_CAD_MTAG-PGS_2024) |
PSS012090| European Ancestry| 12,677 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent coronary artery disease defined as myocardial infarction, percutaneous transluminal coronary angioplasty, coronary artery bypass grafting, unstable angina and chronic ischemic heart disease. | — | AUROC: 0.772 | R²: 0.27974 | age, sex, four first principal components of genetic ancestry | — |
| PPM023002 | PGS005294 (Jorda_CAD_MTAG-PGS_females_2024) |
PSS012091| European Ancestry| 5,152 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent coronary artery disease defined as myocardial infarction, percutaneous transluminal coronary angioplasty, coronary artery bypass grafting, unstable angina and chronic ischemic heart disease. | — | AUROC: 0.7 | R²: 0.12154 | age, sex, four first principal components of genetic ancestry | — |
| PPM023006 | PGS005298 (Jorda_CAD_SingleTrait-PGS_males_2024) |
PSS012092| European Ancestry| 7,525 individuals |
PGP000759 | Jordà P et al. NPJ Genom Med (2025) |
Reported Trait: Prevalent coronary artery disease defined as myocardial infarction, percutaneous transluminal coronary angioplasty, coronary artery bypass grafting, unstable angina and chronic ischemic heart disease. | — | AUROC: 0.69191 | R²: 0.15574 | age, sex, four first principal components of genetic ancestry | — |
| PPM030586 | PGS012519 (VTE) |
PSS012201| Multi-ancestry (including European)| 9,115 individuals |
PGP000786 | Huang YJ et al. Nat Commun (2026) |
Reported Trait: Venous thromboembolism risk | β: 0.36 (0.027) | — | — | sex, age, age^2, BMI, 11 genetic PCs | Effect estimate corresponds to PRS per SD adjusted for genetic PCs. |
| PPM030587 | PGS012519 (VTE) |
PSS012201| Multi-ancestry (including European)| 9,115 individuals |
PGP000786 | Huang YJ et al. Nat Commun (2026) |
Reported Trait: Venous thromboembolism risk | β: 0.35 (0.026) | — | — | sex, age, age^2, BMI, global ancestry proportions | Effect estimate corresponds to PRS per SD adjusted for global ancestry proportions. |
| PPM030588 | PGS012519 (VTE) |
PSS012201| Multi-ancestry (including European)| 9,115 individuals |
PGP000786 | Huang YJ et al. Nat Commun (2026) |
Reported Trait: Venous thromboembolism risk | β: 0.355 (0.026) | — | — | sex, age, age^2, BMI, global ePRS | Effect estimate corresponds to residual PRS (rPRS) adjusted for global expected PRS (gePRS). |
| PPM030617 | PGS012531 (ALLmeta) |
PSS012204| European Ancestry| 124,367 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.82 β: 0.597 |
— | R²: 0.098 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030618 | PGS012532 (Mult-t-EUR) |
PSS012204| European Ancestry| 124,367 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.89 β: 0.635 |
— | R²: 0.11 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030619 | PGS005168 (PRSAF) |
PSS012206| Hispanic or Latin American Ancestry| 40,219 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |Ext. |
Reported Trait: Atrial Fibrillation | OR: 1.34 β: 0.29 |
— | R²: 0.024 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030620 | PGS012531 (ALLmeta) |
PSS012206| Hispanic or Latin American Ancestry| 40,219 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.39 β: 0.332 |
— | R²: 0.032 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030621 | PGS012533 (Mult-t-AMR) |
PSS012206| Hispanic or Latin American Ancestry| 40,219 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.45 β: 0.373 |
— | R²: 0.043 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030622 | PGS005168 (PRSAF) |
PSS012207| African Ancestry| 44,692 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |Ext. |
Reported Trait: Atrial Fibrillation | OR: 1.21 β: 0.189 |
— | R²: 0.008 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030623 | PGS012531 (ALLmeta) |
PSS012207| African Ancestry| 44,692 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.32 β: 0.274 |
— | R²: 0.018 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030624 | PGS012534 (Mult-t-AFR) |
PSS012207| African Ancestry| 44,692 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.39 β: 0.328 |
— | R²: 0.028 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030625 | PGS005168 (PRSAF) |
PSS012208| South Asian Ancestry| 3,806 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |Ext. |
Reported Trait: Atrial Fibrillation | OR: 1.28 β: 0.247 |
— | R²: 0.014 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030626 | PGS012531 (ALLmeta) |
PSS012208| South Asian Ancestry| 3,806 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.31 β: 0.27 |
— | R²: 0.02 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030627 | PGS012535 (Mult-t-SAS) |
PSS012208| South Asian Ancestry| 3,806 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.45 β: 0.369 |
— | R²: 0.038 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030628 | PGS005168 (PRSAF) |
PSS012209| East Asian Ancestry| 6,832 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |Ext. |
Reported Trait: Atrial Fibrillation | OR: 1.64 β: 0.492 |
— | R²: 0.061 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030629 | PGS012531 (ALLmeta) |
PSS012209| East Asian Ancestry| 6,832 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.79 β: 0.582 |
— | R²: 0.075 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030630 | PGS012536 (Mult-t-EAS) |
PSS012209| East Asian Ancestry| 6,832 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.82 β: 0.599 |
— | R²: 0.079 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030631 | PGS005168 (PRSAF) |
PSS012210| East Asian Ancestry| 45,404 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |Ext. |
Reported Trait: Atrial Fibrillation | OR: 2.0 β: 0.692 |
— | R²: 0.125 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030589 | PGS012519 (VTE) |
PSS012201| Multi-ancestry (including European)| 9,115 individuals |
PGP000786 | Huang YJ et al. Nat Commun (2026) |
Reported Trait: Venous thromboembolism risk | β: 0.354 (0.026) | — | — | sex, age, age^2, BMI, local ePRS | Effect estimate corresponds to residual PRS (rPRS) adjusted for local expected PRS (lePRS). |
| PPM030614 | PGS012530 (PRSCAD+) |
PSS012202| East Asian Ancestry| 12,127 individuals |
PGP000787 | Wang H et al. Genomics Proteomics Bioinformatics (2026) |
Reported Trait: coronary artery disease | HR: 1.26 | C-index: 0.649 | — | age, sex, and the first four PCs | — |
| PPM030615 | PGS012530 (PRSCAD+) |
PSS012203| East Asian Ancestry| 5,243 individuals |
PGP000787 | Wang H et al. Genomics Proteomics Bioinformatics (2026) |
Reported Trait: coronary artery disease | OR: 2.23 | AUROC: 0.786 | — | age, sex, and the first four PCs | — |
| PPM030611 | PGS012527 (VTE_LD) |
PSS012201| Multi-ancestry (including European)| 9,115 individuals |
PGP000786 | Huang YJ et al. Nat Commun (2026) |
Reported Trait: Venous thromboembolism risk | β: 0.162 (0.028) | — | — | sex, age, age^2, BMI, 11 genetic PCs | Effect estimate corresponds to PRS per SD adjusted for genetic PCs. |
| PPM030612 | PGS012527 (VTE_LD) |
PSS012201| Multi-ancestry (including European)| 9,115 individuals |
PGP000786 | Huang YJ et al. Nat Commun (2026) |
Reported Trait: Venous thromboembolism risk | β: 0.163 (0.028) | — | — | sex, age, age^2, BMI, global ancestry proportions | Effect estimate corresponds to PRS per SD adjusted for global ancestry proportions. |
| PPM030613 | PGS012527 (VTE_LD) |
PSS012201| Multi-ancestry (including European)| 9,115 individuals |
PGP000786 | Huang YJ et al. Nat Commun (2026) |
Reported Trait: Venous thromboembolism risk | β: 0.161 (0.028) | — | — | sex, age, age^2, BMI, global ePRS | Effect estimate corresponds to residual PRS (rPRS) adjusted for global expected PRS (gePRS). |
| PPM030648 | PGS012542 (EN_model_CAD) |
PSS012216| European Ancestry| 122,892 individuals |
PGP000790 | Hu J et al. Genet Med (2026) |
Reported Trait: Coronary artery disease | OR: 1.85 [1.81, 1.9] | AUROC: 0.65 [0.65, 0.66] | — | — | — |
| PPM030650 | PGS012544 (EN_model_HF) |
PSS012218| European Ancestry| 122,892 individuals |
PGP000790 | Hu J et al. Genet Med (2026) |
Reported Trait: Heart failure | OR: 1.55 [1.49, 1.62] | AUROC: 0.62 [0.61, 0.63] | — | — | — |
| PPM030652 | PGS012546 (EN_model_PAD) |
PSS012220| European Ancestry| 122,892 individuals |
PGP000790 | Hu J et al. Genet Med (2026) |
Reported Trait: Peripheral arterial disease | OR: 1.57 [1.51, 1.64] | AUROC: 0.62 [0.61, 0.63] | — | — | — |
| PPM030660 | PGS012551 (PRS_stroke) |
PSS012229| European Ancestry| 21,092 individuals |
PGP000794 | Ye Y et al. Front Bioinform (2024) |
Reported Trait: Stroke | — | AUROC: 0.542 [0.499, 0.585] | AUROC of meta-PRS (PRS_CAD + PRS_IS + PRS_HF) for stroke: 0.523 [0.48, 0.566] | PRS_CAD (PGS Catalog ID: PGS005236) + PRS_IS (this paper) + PRS_HF (this paper) combined to derive meta-PRS | The meta-PRS was constructed by combining PRS_CAD, PRS_IS, and PRS_HF at the PRS level using weights described in the study. Implementation details are available at: https://github.com/JqiHu/meta-PRS-CVD |
| PPM030661 | PGS012552 (PRS_HF) |
PSS012228| European Ancestry| 21,092 individuals |
PGP000794 | Ye Y et al. Front Bioinform (2024) |
Reported Trait: HF | — | AUROC: 0.524 [0.495, 0.554] | AUROC of meta-PRS (PRS_CAD + PRS_IS + PRS_HF) for HF: 0.558 [0.528, 0.588] | PRS_CAD (PGS Catalog ID: PGS005236) + PRS_IS (this paper) + PRS_HF (this paper) combined to derive meta-PRS | The meta-PRS was constructed by combining PRS_CAD, PRS_IS, and PRS_HF at the PRS level using weights described in the study. Implementation details are available at: https://github.com/JqiHu/meta-PRS-CVD |
| PPM030662 | PGS005236 (CAD_AnnoPred) |
PSS012227| European Ancestry| 18,732 individuals |
PGP000794 | Ye Y et al. Front Bioinform (2024) |Ext. |
Reported Trait: CAD | — | AUROC: 0.597 [0.571, 0.623] | AUROC of meta-PRS (PRS_CAD + PRS_IS + PRS_HF) for CAD: 0.598 [0.573, 0.625] | PRS_CAD (PGS Catalog ID: PGS005236) + PRS_IS (this paper) + PRS_HF (this paper) combined to derive meta-PRS | The meta-PRS was constructed by combining PRS_CAD, PRS_IS, and PRS_HF at the PRS level using weights described in the study. Implementation details are available at: https://github.com/JqiHu/meta-PRS-CVD |
| PPM030663 | PGS005236 (CAD_AnnoPred) |
PSS012227| European Ancestry| 18,732 individuals |
PGP000794 | Ye Y et al. Front Bioinform (2024) |Ext. |
Reported Trait: Late CAD | — | AUROC: 0.549 [0.525, 0.573] | AUROC of meta-PRS (PRS_CAD + PRS_IS + PRS_HF) for late CAD: 0.557 [0.532, 0.581] | PRS_CAD (PGS Catalog ID: PGS005236) + PRS_IS (this paper) + PRS_HF (this paper) combined to derive meta-PRS | The meta-PRS was constructed by combining PRS_CAD, PRS_IS, and PRS_HF at the PRS level using weights described in the study. Implementation details are available at: https://github.com/JqiHu/meta-PRS-CVD |
| PPM030664 | PGS005236 (CAD_AnnoPred) |
PSS012227| European Ancestry| 18,732 individuals |
PGP000794 | Ye Y et al. Front Bioinform (2024) |Ext. |
Reported Trait: Early CAD | — | AUROC: 0.604 [0.551, 0.657] | AUROC of meta-PRS (PRS_CAD + PRS_IS + PRS_HF) for early CAD: 0.614 [0.561, 0.665] | PRS_CAD (PGS Catalog ID: PGS005236) + PRS_IS (this paper) + PRS_HF (this paper) combined to derive meta-PRS | The meta-PRS was constructed by combining PRS_CAD, PRS_IS, and PRS_HF at the PRS level using weights described in the study. Implementation details are available at: https://github.com/JqiHu/meta-PRS-CVD |
| PPM030632 | PGS012531 (ALLmeta) |
PSS012210| East Asian Ancestry| 45,404 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 2.1 β: 0.744 |
— | R²: 0.142 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030633 | PGS012536 (Mult-t-EAS) |
PSS012210| East Asian Ancestry| 45,404 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 2.11 β: 0.746 |
— | R²: 0.143 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030634 | PGS005168 (PRSAF) |
PSS012211| European Ancestry| 15,191 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |Ext. |
Reported Trait: Atrial Fibrillation | OR: 1.81 β: 0.593 |
— | R²: 0.083 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030635 | PGS012531 (ALLmeta) |
PSS012211| European Ancestry| 15,191 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 2.19 β: 0.786 |
— | R²: 0.134 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030636 | PGS012532 (Mult-t-EUR) |
PSS012211| European Ancestry| 15,191 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 2.24 β: 0.807 |
— | R²: 0.143 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030637 | PGS004706 (afib_PRSmixPlus_eur) |
PSS012212| European Ancestry| 5,656 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |Ext. |
Reported Trait: Atrial Fibrillation | OR: 1.38 β: 0.323 |
— | R²: 0.029 | age, sex and first 6 principal components | Beta = log(OR) |
| PPM030638 | PGS005168 (PRSAF) |
PSS012212| European Ancestry| 5,656 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |Ext. |
Reported Trait: Atrial Fibrillation | OR: 1.43 β: 0.356 |
— | R²: 0.037 | age, sex and first 6 principal components | Beta = log(OR) |
| PPM030639 | PGS012532 (Mult-t-EUR) |
PSS012212| European Ancestry| 5,656 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.54 β: 0.429 |
— | R²: 0.052 | age, sex and first 6 principal components | Beta = log(OR) |
| PPM030640 | PGS005168 (PRSAF) |
PSS012213| African Ancestry| 7,382 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |Ext. |
Reported Trait: Atrial Fibrillation | OR: 1.31 β: 0.271 |
— | R²: 0.015 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030641 | PGS012534 (Mult-t-AFR) |
PSS012213| African Ancestry| 7,382 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.37 β: 0.313 |
— | R²: 0.019 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030642 | PGS005168 (PRSAF) |
PSS012205| South Asian Ancestry| 4,439 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |Ext. |
Reported Trait: Atrial Fibrillation | OR: 1.44 β: 0.364 |
— | R²: 0.033 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030643 | PGS012535 (Mult-t-SAS) |
PSS012205| South Asian Ancestry| 4,439 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |
Reported Trait: Atrial Fibrillation | OR: 1.75 β: 0.559 |
— | R²: 0.071 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM022184 | PGS005093 (MetPRS) |
PSS011833| Multi-ancestry (including European)| 34,177 individuals |
PGP000685 | Yang X et al. Nat Commun (2026) |
Reported Trait: coronary artery disease | HR: 1.1 [1.09, 1.12] OR: 1.14 [1.11, 1.17] |
— | — | age, sex, PC1-10 | — |
| PPM030687 | PGS012558 (CAD_EAS_MIXPRSplus) |
PSS012247| East Asian Ancestry| 2,090 individuals |
PGP000799 | Xu L et al. Nat Genet (2026) |
Reported Trait: Coronary artery disease | OR: 1.751 | AUROC: 0.669 | — | — | — |
| PPM030698 | PGS012563 (PRS31_AAA) |
PSS012254| European Ancestry| 449,463 individuals |
PGP000803 | Ma Y et al. Eur Heart J (2024) |
Reported Trait: Incident Abdominal aortic aneurysm | HR: 1.25 [1.19, 1.31] | — | — | age, sex, family income, TDI, education, employment, alcohol consumption status, tobacco consumption status, healthy diet score, physical activity, BMI, eGFR, SBP, HbA1c, lipid profile, anti-hypertensive medication, anti-hyperglycemic medication, lipid-lowering medication, genotyping batch, and the first 10 genetic principal components | — |
| PPM030699 | PGS012563 (PRS31_AAA) |
PSS012254| European Ancestry| 449,463 individuals |
PGP000803 | Ma Y et al. Eur Heart J (2024) |
Reported Trait: Incident Abdominal aortic aneurysm x PM2.5 pollution exposure interaction | — | — | Hazard ratio (HR, high air pollutants exposure and high PRS vs. low air pollutants exposure and low PRS): 3.18 [2.46, 4.12] | age, sex, family income, Townsend deprivation index, education, employment, alcohol consumption status, tobacco consumption status, healthy diet score, physical activity, body mass index, estimated glomerular filtration rate, systolic blood pressure, glycated haemoglobin, lipid profile, anti-hypertensive medication, anti-hyperglycaemic medication, and lipid-lowering medication, genotyping batch, the first 10 genetic principal components | — |
| PPM030700 | PGS012563 (PRS31_AAA) |
PSS012254| European Ancestry| 449,463 individuals |
PGP000803 | Ma Y et al. Eur Heart J (2024) |
Reported Trait: Incident Abdominal aortic aneurysm x PM10 pollution exposure interaction | — | — | Hazard ratio (HR, high air pollutants exposure and high PRS vs. low air pollutants exposure and low PRS): 3.09 [2.39, 4.0] | age, sex, family income, Townsend deprivation index, education, employment, alcohol consumption status, tobacco consumption status, healthy diet score, physical activity, body mass index, estimated glomerular filtration rate, systolic blood pressure, glycated haemoglobin, lipid profile, anti-hypertensive medication, anti-hyperglycaemic medication, and lipid-lowering medication, genotyping batch, the first 10 genetic principal components | — |
| PPM030701 | PGS012563 (PRS31_AAA) |
PSS012254| European Ancestry| 449,463 individuals |
PGP000803 | Ma Y et al. Eur Heart J (2024) |
Reported Trait: Incident Abdominal aortic aneurysm x NO2 pollution exposure interaction | — | — | Hazard ratio (HR, high air pollutants exposure and high PRS vs. low air pollutants exposure and low PRS): 2.41 [1.86, 3.13] | age, sex, family income, Townsend deprivation index, education, employment, alcohol consumption status, tobacco consumption status, healthy diet score, physical activity, body mass index, estimated glomerular filtration rate, systolic blood pressure, glycated haemoglobin, lipid profile, anti-hypertensive medication, anti-hyperglycaemic medication, and lipid-lowering medication, genotyping batch, the first 10 genetic principal components | — |
| PPM030702 | PGS012563 (PRS31_AAA) |
PSS012254| European Ancestry| 449,463 individuals |
PGP000803 | Ma Y et al. Eur Heart J (2024) |
Reported Trait: Incident Abdominal aortic aneurysm x NOx pollution exposure interaction | — | — | Hazard ratio (HR, high air pollutants exposure and high PRS vs. low air pollutants exposure and low PRS): 2.01 [1.55, 2.61] | age, sex, family income, Townsend deprivation index, education, employment, alcohol consumption status, tobacco consumption status, healthy diet score, physical activity, body mass index, estimated glomerular filtration rate, systolic blood pressure, glycated haemoglobin, lipid profile, anti-hypertensive medication, anti-hyperglycaemic medication, and lipid-lowering medication, genotyping batch, the first 10 genetic principal components | — |
| PPM030728 | PGS012577 (GRS134_AF) |
PSS012268| European Ancestry| 151,741 individuals |
PGP000812 | Chen Y et al. Eur J Psychotraumatol (2024) |
Reported Trait: Incident atrial fibrillation | — | — | Hazard ratio (HR, high vs low tertile): 3.56 [3.26, 3.88] | age, sex, ethnicity, assessment center, employment status, education level,Townsend Deprivation Index, smoking status, alcohol consumption status, physical activity, and healthy diet score | — |
| PPM030734 | PGS012580 (PRS25_AF) |
PSS012270| Multi-ancestry (including European)| 453,102 individuals |
PGP000814 | Zheng J et al. J Intern Med (2024) |
Reported Trait: Atrial fibrillation | — | — | Hazard ratio (HR, high vs low tertile): 1.83 [1.66, 2.0] | major cardiovascular risk factors: Age, sex, ethnicity, the TDI, level of education, annual household income, BMI, smoking status, alcohol intake, physical activity (weekly metabolic equivalent minutes ≥600), vitamin supplementation, and comorbidities that may increase the risk of infections (i.e., hypertension, diabetes, high cholesterol, liver disease, kidney disease, and digestive disease) | — |
| PPM030735 | PGS012581 (PRS169_CAD) |
PSS012270| Multi-ancestry (including European)| 453,102 individuals |
PGP000814 | Zheng J et al. J Intern Med (2024) |
Reported Trait: Coronary artery disease | — | — | Hazard ratio (HR, high vs low tertile): 1.79 [1.72, 1.86] | major cardiovascular risk factors: Age, sex, ethnicity, the TDI, level of education, annual household income, BMI, smoking status, alcohol intake, physical activity (weekly metabolic equivalent minutes ≥600), vitamin supplementation, and comorbidities that may increase the risk of infections (i.e., hypertension, diabetes, high cholesterol, liver disease, kidney disease, and digestive disease) | — |
| PPM030736 | PGS012581 (PRS169_CAD) |
PSS012271| Multi-ancestry (excluding European)| 27,426 individuals |
PGP000814 | Zheng J et al. J Intern Med (2024) |
Reported Trait: Coronary artery disease x infectious disease interaction | — | — | Hazard ratio (HR, with high infection and high PRS vs. no infection and low PRS): 3.41 [1.67, 5.28] | sex, age (timescale), the Townsend Deprivation Index, level of education, annual household income, body mass index, smoking status, alcohol intake, physical activity, vitamin supplementation, hypertension, diabetes, high cholesterol, liver disease, kidney disease, and digestive disease | — |
| PPM030616 | PGS005168 (PRSAF) |
PSS012204| European Ancestry| 124,367 individuals |
PGP000788 | Haydarlou P et al. Nat Commun (2026) |Ext. |
Reported Trait: Atrial Fibrillation | OR: 1.59 β: 0.463 |
— | R²: 0.059 | age, sex and first 20 principal components | Beta = log(OR) |
| PPM030727 | PGS012577 (GRS134_AF) |
PSS012268| European Ancestry| 151,741 individuals |
PGP000812 | Chen Y et al. Eur J Psychotraumatol (2024) |
Reported Trait: Incident atrial fibrillation x childhood maltreatment interaction | — | — | Hazard ratio (HR, 3-5 childhood maltreatment and high PRS vs. no childhood maltreatment and low PRS): 5.31 [4.36, 6.48] | age, sex, ethnicity, assessment centre, employment status, education level, Townsend Deprivation Index, smoking status, alcohol consumption status, physical activity, and healthy diet score | — |
| PPM030733 | PGS012579 (PRS11_stroke) |
PSS012270| Multi-ancestry (including European)| 453,102 individuals |
PGP000814 | Zheng J et al. J Intern Med (2024) |
Reported Trait: Stroke | — | — | Hazard ratio (HR, high vs low tertile): 1.61 [1.41, 1.82] | major cardiovascular risk factors: Age, sex, ethnicity, the TDI, level of education, annual household income, BMI, smoking status, alcohol intake, physical activity (weekly metabolic equivalent minutes ≥600), vitamin supplementation, and comorbidities that may increase the risk of infections (i.e., hypertension, diabetes, high cholesterol, liver disease, kidney disease, and digestive disease) | — |
| PPM036556 | PGS000329 (PRS_CHD) |
PSS012311| European Ancestry| 943 individuals |
PGP000828 | Kujala I et al. J Atheroscler Thromb (2024) |Ext. |
Reported Trait: Coronary atherosclerosis | OR: 1.4 [1.21, 1.62] | — | — | age, sex, hypertension, diabetes, smoking, dyslipidemia, family history of premature CAD and symptoms | — |
| PPM036559 | PGS000329 (PRS_CHD) |
PSS012311| European Ancestry| 943 individuals |
PGP000828 | Kujala I et al. J Atheroscler Thromb (2024) |Ext. |
Reported Trait: Obstructive CAD | OR: 1.25 [1.07, 1.46] | AUROC: 0.561 | — | age, sex, hypertension, diabetes, smoking, dyslipidemia, family history of premature CAD and symptoms | — |
| PPM036562 | PGS000329 (PRS_CHD) |
PSS012311| European Ancestry| 943 individuals |
PGP000828 | Kujala I et al. J Atheroscler Thromb (2024) |Ext. |
Reported Trait: coronary atherosclerosis | OR: 1.25 [1.07, 1.46] | AUROC: 0.589 | — | — | — |
| PPM036563 | PGS000018 (metaGRS_CAD) |
PSS012311| European Ancestry| 943 individuals |
PGP000828 | Kujala I et al. J Atheroscler Thromb (2024) |Ext. |
Reported Trait: coronary atherosclerosis | OR: 1.68 [1.42, 1.97] | AUROC: 0.635 | — | — | — |
| PPM036548 | PGS018412 (MultiPRS_myocardial-infarction) |
PSS012304| European Ancestry| 7,838 individuals |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Reported Trait: Prevalent Myocardial infarction | OR: 3.38 | AUROC: 0.7132 | — | age, sex, body surface area, PC1-PC20 | Multi-PRS + baseline (diagnostic). OR per 1 SD of PRS (logOR=1.2168); DeLong p=0.9822239038128628. Sex='Both' (male/female strata also in Suppl. Data 27). |
| PPM036549 | PGS018412 (MultiPRS_myocardial-infarction) |
PSS012305| European Ancestry| 5,984 individuals |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Reported Trait: Incident Myocardial infarction (1-10 yr) | HR: 0.95 [0.92, 0.97] OR: 2.46 |
AUROC: 0.6571 | — | age, sex, body surface area, PC1-PC20 | Multi-PRS + baseline (prognostic, 1-10 yr). OR per 1 SD (logOR=0.899); HR per SD of PRS from Cox model (col D); DeLong p=0.9361436146977564. Sex='Both'. |
| PPM036550 | PGS018412 (MultiPRS_myocardial-infarction) |
PSS012306| European Ancestry| 16,433 individuals |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Reported Trait: Myocardial infarction | OR: 2.77 | AUROC: 0.6778 | — | age, sex, body surface area, PC1-PC20 | Multi-PRS + baseline (whole cohort). OR per 1 SD (logOR=1.0191); DeLong p=0.9610599661066996. Sex='Both'. |
| PPM036823 | PGS018641 (TPMI_228_LDpred2) |
PSS012542| East Asian Ancestry| 19,931 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hemangioma and lymphangioma any site | — | AUROC: 0.69822 | R²: 0.01417 | sex, age, array, PCs 1-10 | — |
| PPM036825 | PGS018643 (TPMI_228_PRS-CS) |
PSS012545| East Asian Ancestry| 19,931 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hemangioma and lymphangioma any site | — | AUROC: 0.69929 | R²: 0.01429 | sex, age, array, PCs 1-10 | — |
| PPM036565 | PGS000058 (CAD_GRS_204) |
PSS012312| Multi-ancestry (including European)| 49,230 individuals |
PGP000829 | Kwak SH et al. Diabetes Care (2024) |Ext. |
Reported Trait: Incident cardiovascular disease in type 2 diabetes | HR: 1.14 [1.12, 1.16] | — | — | age at diagnosis of T2D, sex, principal components | — |
| PPM036566 | PGS000011 (GRS50) |
PSS012313| Hispanic or Latin American Ancestry| 133,207 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.05 [1.03, 1.08] | AUROC: 0.745 [0.739, 0.752] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036567 | PGS004595 (PRS_CHD) |
PSS012313| Hispanic or Latin American Ancestry| 133,207 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.09 [1.06, 1.13] | AUROC: 0.746 [0.739, 0.752] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036568 | PGS000337 (MetaPRS_CAD) |
PSS012313| Hispanic or Latin American Ancestry| 133,207 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.2 [1.17, 1.23] | AUROC: 0.748 [0.742, 0.754] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036569 | PGS003446 (TEM_CAD_PRS) |
PSS012313| Hispanic or Latin American Ancestry| 133,207 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.16 [1.12, 1.2] | AUROC: 0.746 [0.74, 0.753] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036570 | PGS001780 (CHD_PRSCS) |
PSS012313| Hispanic or Latin American Ancestry| 133,207 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.2 [1.16, 1.23] | AUROC: 0.748 [0.741, 0.754] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036571 | PGS003725 (GPS_Mult) |
PSS012313| Hispanic or Latin American Ancestry| 133,207 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.24 [1.2, 1.28] | AUROC: 0.749 [0.743, 0.755] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036574 | PGS000011 (GRS50) |
PSS012314| Hispanic or Latin American Ancestry| 43,338 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.05 [1.01, 1.1] | AUROC: 0.719 [0.709, 0.729] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036575 | PGS004595 (PRS_CHD) |
PSS012314| Hispanic or Latin American Ancestry| 43,338 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.12 [1.07, 1.16] | AUROC: 0.72 [0.71, 0.73] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036576 | PGS000337 (MetaPRS_CAD) |
PSS012314| Hispanic or Latin American Ancestry| 43,338 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.27 [1.22, 1.33] | AUROC: 0.726 [0.716, 0.736] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036577 | PGS003446 (TEM_CAD_PRS) |
PSS012314| Hispanic or Latin American Ancestry| 43,338 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.28 [1.21, 1.34] | AUROC: 0.724 [0.714, 0.734] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036578 | PGS001780 (CHD_PRSCS) |
PSS012314| Hispanic or Latin American Ancestry| 43,338 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.26 [1.21, 1.32] | AUROC: 0.725 [0.715, 0.735] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036579 | PGS003725 (GPS_Mult) |
PSS012314| Hispanic or Latin American Ancestry| 43,338 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.33 [1.27, 1.39] | AUROC: 0.729 [0.719, 0.738] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036582 | PGS000011 (GRS50) |
PSS012315| Hispanic or Latin American Ancestry| 89,869 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.05 [1.01, 1.09] | AUROC: 0.746 [0.737, 0.755] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036583 | PGS004595 (PRS_CHD) |
PSS012315| Hispanic or Latin American Ancestry| 89,869 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.08 [1.03, 1.12] | AUROC: 0.746 [0.738, 0.755] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036584 | PGS000337 (MetaPRS_CAD) |
PSS012315| Hispanic or Latin American Ancestry| 89,869 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.14 [1.1, 1.19] | AUROC: 0.747 [0.738, 0.756] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036585 | PGS003446 (TEM_CAD_PRS) |
PSS012315| Hispanic or Latin American Ancestry| 89,869 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.07 [1.02, 1.12] | AUROC: 0.746 [0.737, 0.754] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036586 | PGS001780 (CHD_PRSCS) |
PSS012315| Hispanic or Latin American Ancestry| 89,869 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.15 [1.1, 1.19] | AUROC: 0.747 [0.738, 0.756] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036587 | PGS003725 (GPS_Mult) |
PSS012315| Hispanic or Latin American Ancestry| 89,869 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.17 [1.13, 1.22] | AUROC: 0.747 [0.739, 0.756] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036557 | PGS000018 (metaGRS_CAD) |
PSS012311| European Ancestry| 943 individuals |
PGP000828 | Kujala I et al. J Atheroscler Thromb (2024) |Ext. |
Reported Trait: Coronary atherosclerosis | OR: 1.62 [1.39, 1.89] | — | — | age, sex, hypertension, diabetes, smoking, dyslipidemia, family history of premature CAD and symptoms | — |
| PPM036558 | PGS000013 (GPS_CAD) |
PSS012311| European Ancestry| 943 individuals |
PGP000828 | Kujala I et al. J Atheroscler Thromb (2024) |Ext. |
Reported Trait: Coronary atherosclerosis | OR: 1.62 [1.39, 1.88] | — | — | age, sex, hypertension, diabetes, smoking, dyslipidemia, family history of premature CAD and symptoms | — |
| PPM036560 | PGS000018 (metaGRS_CAD) |
PSS012311| European Ancestry| 943 individuals |
PGP000828 | Kujala I et al. J Atheroscler Thromb (2024) |Ext. |
Reported Trait: Obstructive CAD | OR: 1.68 [1.42, 1.97] | AUROC: 0.63 | — | age, sex, hypertension, diabetes, smoking, dyslipidemia, family history of premature CAD and symptoms | — |
| PPM036561 | PGS000013 (GPS_CAD) |
PSS012311| European Ancestry| 943 individuals |
PGP000828 | Kujala I et al. J Atheroscler Thromb (2024) |Ext. |
Reported Trait: Obstructive CAD | OR: 1.7 [1.44, 2.01] | AUROC: 0.64 | — | age, sex, hypertension, diabetes, smoking, dyslipidemia, family history of premature CAD and symptoms | — |
| PPM036564 | PGS000013 (GPS_CAD) |
PSS012311| European Ancestry| 943 individuals |
PGP000828 | Kujala I et al. J Atheroscler Thromb (2024) |Ext. |
Reported Trait: coronary atherosclerosis | OR: 1.7 [1.44, 2.01] | AUROC: 0.63 | — | — | — |
| PPM036572 | PGS000018 (metaGRS_CAD) |
PSS012313| Hispanic or Latin American Ancestry| 133,207 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.19 [1.15, 1.23] | AUROC: 0.747 [0.741, 0.753] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036573 | PGS000013 (GPS_CAD) |
PSS012313| Hispanic or Latin American Ancestry| 133,207 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.17 [1.14, 1.2] | AUROC: 0.747 [0.741, 0.754] C-index: 0.749 [0.743, 0.755] |
— | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036580 | PGS000018 (metaGRS_CAD) |
PSS012314| Hispanic or Latin American Ancestry| 43,338 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.27 [1.21, 1.34] | AUROC: 0.724 [0.714, 0.734] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036581 | PGS000013 (GPS_CAD) |
PSS012314| Hispanic or Latin American Ancestry| 43,338 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.24 [1.19, 1.29] | AUROC: 0.724 [0.715, 0.734] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036588 | PGS000018 (metaGRS_CAD) |
PSS012315| Hispanic or Latin American Ancestry| 89,869 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.13 [1.08, 1.16] | AUROC: 0.747 [0.738, 0.755] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036589 | PGS000013 (GPS_CAD) |
PSS012315| Hispanic or Latin American Ancestry| 89,869 individuals |
PGP000830 | Liu T et al. Eur J Prev Cardiol (2026) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.12 [1.08, 1.16] | AUROC: 0.747 [0.738, 0.755] | — | age, sex, PC1-PC7, baseline waist-to-hip ratio, systolic and diastolic blood pressure, smoking status, level of education, and diabetes | — |
| PPM036536 | PGS018408 (MultiPRS_coronary-heart-disease) |
PSS012292| European Ancestry| 10,135 individuals |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Reported Trait: Prevalent Coronary heart disease | OR: 3.14 | AUROC: 0.6996 | — | age, sex, body surface area, PC1-PC20 | Multi-PRS + baseline (diagnostic). OR per 1 SD of PRS (logOR=1.1441); DeLong p=0.4525863322595239. Sex='Both' (male/female strata also in Suppl. Data 27). |
| PPM036537 | PGS018408 (MultiPRS_coronary-heart-disease) |
PSS012293| European Ancestry| 12,832 individuals |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Reported Trait: Incident Coronary heart disease (1-10 yr) | HR: 1.07 [1.05, 1.08] OR: 2.5 |
AUROC: 0.6568 | — | age, sex, body surface area, PC1-PC20 | Multi-PRS + baseline (prognostic, 1-10 yr). OR per 1 SD (logOR=0.9148); HR per SD of PRS from Cox model (col D); DeLong p=0.3953316390827512. Sex='Both'. |
| PPM036538 | PGS018408 (MultiPRS_coronary-heart-disease) |
PSS012294| European Ancestry| 27,939 individuals |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Reported Trait: Coronary heart disease | OR: 2.66 | AUROC: 0.6669 | — | age, sex, body surface area, PC1-PC20 | Multi-PRS + baseline (whole cohort). OR per 1 SD (logOR=0.9788); DeLong p=0.0328749776164314. Sex='Both'. |
| PPM036539 | PGS018409 (MultiPRS_heart-failure) |
PSS012295| European Ancestry| 2,553 individuals |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Reported Trait: Prevalent Heart failure | OR: 3.1 | AUROC: 0.6913 | — | age, sex, body surface area, PC1-PC20 | Multi-PRS + baseline (diagnostic). OR per 1 SD of PRS (logOR=1.1328); DeLong p=0.183869673873534. Sex='Both' (male/female strata also in Suppl. Data 27). |
| PPM036540 | PGS018409 (MultiPRS_heart-failure) |
PSS012296| European Ancestry| 8,142 individuals |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Reported Trait: Incident Heart failure (1-10 yr) | HR: 0.96 [0.94, 0.97] OR: 3.16 |
AUROC: 0.6932 | — | age, sex, body surface area, PC1-PC20 | Multi-PRS + baseline (prognostic, 1-10 yr). OR per 1 SD (logOR=1.1508); HR per SD of PRS from Cox model (col D); DeLong p=0.6353568793886567. Sex='Both'. |
| PPM036541 | PGS018409 (MultiPRS_heart-failure) |
PSS012297| European Ancestry| 14,172 individuals |
PGP000826 | Ometto S et al. Nat Commun (2026) |
Reported Trait: Heart failure | OR: 3.01 | AUROC: 0.6836 | — | age, sex, body surface area, PC1-PC20 | Multi-PRS + baseline (whole cohort). OR per 1 SD (logOR=1.102); DeLong p=0.7920128596259659. Sex='Both'. |
| PPM037168 | PGS018986 (TPMI_340_Lassosum2) |
PSS012889| East Asian Ancestry| 18,664 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Migraine | — | AUROC: 0.76375 | R²: 0.11662 | sex, age, array, PCs 1-10 | — |
| PPM037169 | PGS018987 (TPMI_340_LDpred2) |
PSS012888| East Asian Ancestry| 18,664 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Migraine | — | AUROC: 0.76372 | R²: 0.11649 | sex, age, array, PCs 1-10 | — |
| PPM037170 | PGS018988 (TPMI_340_MegaPRS) |
PSS012890| East Asian Ancestry| 18,664 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Migraine | — | AUROC: 0.76013 | R²: 0.11377 | sex, age, array, PCs 1-10 | — |
| PPM037171 | PGS018989 (TPMI_340_PRS-CS) |
PSS012891| East Asian Ancestry| 18,664 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Migraine | — | AUROC: 0.76286 | R²: 0.11567 | sex, age, array, PCs 1-10 | — |
| PPM037172 | PGS018990 (TPMI_340_SBayesR) |
PSS012892| East Asian Ancestry| 18,664 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Migraine | — | AUROC: 0.76335 | R²: 0.11547 | sex, age, array, PCs 1-10 | — |
| PPM037314 | PGS019132 (TPMI_401.1_Lassosum2) |
PSS013029| East Asian Ancestry| 18,140 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Essential hypertension | — | AUROC: 0.64517 | R²: 0.08407 | sex, age, array, PCs 1-10 | — |
| PPM037315 | PGS019133 (TPMI_401.1_LDpred2) |
PSS013028| East Asian Ancestry| 18,140 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Essential hypertension | — | AUROC: 0.6541 | R²: 0.09525 | sex, age, array, PCs 1-10 | — |
| PPM037316 | PGS019134 (TPMI_401.1_MegaPRS) |
PSS013030| East Asian Ancestry| 18,140 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Essential hypertension | — | AUROC: 0.64663 | R²: 0.08712 | sex, age, array, PCs 1-10 | — |
| PPM037318 | PGS019136 (TPMI_401.1_PRSmix+) |
PSS013032| East Asian Ancestry| 18,140 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Essential hypertension | — | AUROC: 0.67044 | R²: 0.11574 | sex, age, array, PCs 1-10 | — |
| PPM037319 | PGS019137 (TPMI_401.1_SBayesR) |
PSS013033| East Asian Ancestry| 18,140 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Essential hypertension | — | AUROC: 0.63722 | R²: 0.0764 | sex, age, array, PCs 1-10 | — |
| PPM037320 | PGS019138 (TPMI_401.2_Lassosum2) |
PSS013041| East Asian Ancestry| 15,062 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart and or renal disease | — | AUROC: 0.63849 | R²: 0.05806 | sex, age, array, PCs 1-10 | — |
| PPM037321 | PGS019139 (TPMI_401.2_LDpred2) |
PSS013040| East Asian Ancestry| 15,062 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart and or renal disease | — | AUROC: 0.64308 | R²: 0.06165 | sex, age, array, PCs 1-10 | — |
| PPM037322 | PGS019140 (TPMI_401.2_MegaPRS) |
PSS013042| East Asian Ancestry| 15,062 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart and or renal disease | — | AUROC: 0.63399 | R²: 0.05569 | sex, age, array, PCs 1-10 | — |
| PPM037323 | PGS019141 (TPMI_401.2_PRS-CS) |
PSS013043| East Asian Ancestry| 15,062 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart and or renal disease | — | AUROC: 0.63921 | R²: 0.05839 | sex, age, array, PCs 1-10 | — |
| PPM037324 | PGS019142 (TPMI_401.2_PRSmix+) |
PSS013044| East Asian Ancestry| 15,062 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart and or renal disease | — | AUROC: 0.66636 | R²: 0.08306 | sex, age, array, PCs 1-10 | — |
| PPM037325 | PGS019143 (TPMI_401.2_SBayesR) |
PSS013045| East Asian Ancestry| 15,062 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart and or renal disease | — | AUROC: 0.63493 | R²: 0.05432 | sex, age, array, PCs 1-10 | — |
| PPM037327 | PGS019145 (TPMI_401.3_LDpred2) |
PSS013046| East Asian Ancestry| 17,975 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other hypertensive complications | — | AUROC: 0.64963 | R²: 0.03411 | sex, age, array, PCs 1-10 | — |
| PPM037328 | PGS019146 (TPMI_401.3_MegaPRS) |
PSS013048| East Asian Ancestry| 17,975 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other hypertensive complications | — | AUROC: 0.64084 | R²: 0.03018 | sex, age, array, PCs 1-10 | — |
| PPM037329 | PGS019147 (TPMI_401.3_PRS-CS) |
PSS013049| East Asian Ancestry| 17,975 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other hypertensive complications | — | AUROC: 0.64609 | R²: 0.03227 | sex, age, array, PCs 1-10 | — |
| PPM037330 | PGS019148 (TPMI_401.3_SBayesR) |
PSS013050| East Asian Ancestry| 17,975 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other hypertensive complications | — | AUROC: 0.62768 | R²: 0.02473 | sex, age, array, PCs 1-10 | — |
| PPM037331 | PGS019149 (TPMI_401.21_Lassosum2) |
PSS013035| East Asian Ancestry| 14,851 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart disease | — | AUROC: 0.6402 | R²: 0.05744 | sex, age, array, PCs 1-10 | — |
| PPM037332 | PGS019150 (TPMI_401.21_LDpred2) |
PSS013034| East Asian Ancestry| 14,851 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart disease | — | AUROC: 0.64356 | R²: 0.06085 | sex, age, array, PCs 1-10 | — |
| PPM037333 | PGS019151 (TPMI_401.21_MegaPRS) |
PSS013036| East Asian Ancestry| 14,851 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart disease | — | AUROC: 0.63342 | R²: 0.05337 | sex, age, array, PCs 1-10 | — |
| PPM037334 | PGS019152 (TPMI_401.21_PRS-CS) |
PSS013037| East Asian Ancestry| 14,851 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart disease | — | AUROC: 0.6376 | R²: 0.056 | sex, age, array, PCs 1-10 | — |
| PPM037335 | PGS019153 (TPMI_401.21_PRSmix+) |
PSS013038| East Asian Ancestry| 14,851 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart disease | — | AUROC: 0.66644 | R²: 0.08093 | sex, age, array, PCs 1-10 | — |
| PPM037336 | PGS019154 (TPMI_401.21_SBayesR) |
PSS013039| East Asian Ancestry| 14,851 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hypertensive heart disease | — | AUROC: 0.63323 | R²: 0.0517 | sex, age, array, PCs 1-10 | — |
| PPM037337 | PGS019155 (TPMI_411_Lassosum2) |
PSS013073| East Asian Ancestry| 19,485 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Ischemic Heart Disease | — | AUROC: 0.63122 | R²: 0.05223 | sex, age, array, PCs 1-10 | — |
| PPM037339 | PGS019157 (TPMI_411_MegaPRS) |
PSS013074| East Asian Ancestry| 19,485 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Ischemic Heart Disease | — | AUROC: 0.63233 | R²: 0.05304 | sex, age, array, PCs 1-10 | — |
| PPM037340 | PGS019158 (TPMI_411_PRS-CS) |
PSS013075| East Asian Ancestry| 19,485 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Ischemic Heart Disease | — | AUROC: 0.63294 | R²: 0.0532 | sex, age, array, PCs 1-10 | — |
| PPM037341 | PGS019159 (TPMI_411_SBayesR) |
PSS013076| East Asian Ancestry| 19,485 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Ischemic Heart Disease | — | AUROC: 0.63311 | R²: 0.05304 | sex, age, array, PCs 1-10 | — |
| PPM037342 | PGS019160 (TPMI_411.2_Lassosum2) |
PSS013058| East Asian Ancestry| 17,017 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Myocardial infarction | — | AUROC: 0.75539 | R²: 0.05815 | sex, age, array, PCs 1-10 | — |
| PPM037343 | PGS019161 (TPMI_411.2_LDpred2) |
PSS013057| East Asian Ancestry| 17,017 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Myocardial infarction | — | AUROC: 0.76653 | R²: 0.06279 | sex, age, array, PCs 1-10 | — |
| PPM037344 | PGS019162 (TPMI_411.2_MegaPRS) |
PSS013059| East Asian Ancestry| 17,017 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Myocardial infarction | — | AUROC: 0.75987 | R²: 0.06003 | sex, age, array, PCs 1-10 | — |
| PPM037345 | PGS019163 (TPMI_411.2_PRS-CS) |
PSS013060| East Asian Ancestry| 17,017 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Myocardial infarction | — | AUROC: 0.75958 | R²: 0.06009 | sex, age, array, PCs 1-10 | — |
| PPM037346 | PGS019164 (TPMI_411.2_SBayesR) |
PSS013061| East Asian Ancestry| 17,017 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Myocardial infarction | — | AUROC: 0.75693 | R²: 0.05893 | sex, age, array, PCs 1-10 | — |
| PPM037347 | PGS019165 (TPMI_411.4_Lassosum2) |
PSS013063| East Asian Ancestry| 18,061 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Coronary atherosclerosis | — | AUROC: 0.65583 | R²: 0.05877 | sex, age, array, PCs 1-10 | — |
| PPM037349 | PGS019167 (TPMI_411.4_MegaPRS) |
PSS013064| East Asian Ancestry| 18,061 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Coronary atherosclerosis | — | AUROC: 0.6572 | R²: 0.05946 | sex, age, array, PCs 1-10 | — |
| PPM037350 | PGS019168 (TPMI_411.4_PRS-CS) |
PSS013065| East Asian Ancestry| 18,061 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Coronary atherosclerosis | — | AUROC: 0.65935 | R²: 0.06076 | sex, age, array, PCs 1-10 | — |
| PPM037351 | PGS019169 (TPMI_411.4_SBayesR) |
PSS013066| East Asian Ancestry| 18,061 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Coronary atherosclerosis | — | AUROC: 0.65377 | R²: 0.05819 | sex, age, array, PCs 1-10 | — |
| PPM037352 | PGS019170 (TPMI_411.8_Lassosum2) |
PSS013068| East Asian Ancestry| 18,717 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other chronic ischemic heart disease unspecified | — | AUROC: 0.64399 | R²: 0.05893 | sex, age, array, PCs 1-10 | — |
| PPM037353 | PGS019171 (TPMI_411.8_LDpred2) |
PSS013067| East Asian Ancestry| 18,717 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other chronic ischemic heart disease unspecified | — | AUROC: 0.6462 | R²: 0.06032 | sex, age, array, PCs 1-10 | — |
| PPM037354 | PGS019172 (TPMI_411.8_MegaPRS) |
PSS013069| East Asian Ancestry| 18,717 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other chronic ischemic heart disease unspecified | — | AUROC: 0.64462 | R²: 0.05974 | sex, age, array, PCs 1-10 | — |
| PPM037355 | PGS019173 (TPMI_411.8_PRS-CS) |
PSS013070| East Asian Ancestry| 18,717 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other chronic ischemic heart disease unspecified | — | AUROC: 0.64634 | R²: 0.06059 | sex, age, array, PCs 1-10 | — |
| PPM037356 | PGS019174 (TPMI_411.8_SBayesR) |
PSS013071| East Asian Ancestry| 18,717 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other chronic ischemic heart disease unspecified | — | AUROC: 0.64553 | R²: 0.05976 | sex, age, array, PCs 1-10 | — |
| PPM037357 | PGS019175 (TPMI_414_Lassosum2) |
PSS013083| East Asian Ancestry| 17,594 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other forms of chronic heart disease | — | AUROC: 0.66792 | R²: 0.06004 | sex, age, array, PCs 1-10 | — |
| PPM037358 | PGS019176 (TPMI_414_LDpred2) |
PSS013082| East Asian Ancestry| 17,594 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other forms of chronic heart disease | — | AUROC: 0.66784 | R²: 0.05974 | sex, age, array, PCs 1-10 | — |
| PPM037360 | PGS019178 (TPMI_414_PRS-CS) |
PSS013085| East Asian Ancestry| 17,594 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other forms of chronic heart disease | — | AUROC: 0.66862 | R²: 0.06079 | sex, age, array, PCs 1-10 | — |
| PPM037361 | PGS019179 (TPMI_414_SBayesR) |
PSS013086| East Asian Ancestry| 17,594 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other forms of chronic heart disease | — | AUROC: 0.66786 | R²: 0.05991 | sex, age, array, PCs 1-10 | — |
| PPM037362 | PGS019180 (TPMI_414.2_Lassosum2) |
PSS013078| East Asian Ancestry| 17,519 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: ASCVD | — | AUROC: 0.68136 | R²: 0.04367 | sex, age, array, PCs 1-10 | — |
| PPM037363 | PGS019181 (TPMI_414.2_LDpred2) |
PSS013077| East Asian Ancestry| 17,519 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: ASCVD | — | AUROC: 0.68178 | R²: 0.04395 | sex, age, array, PCs 1-10 | — |
| PPM037364 | PGS019182 (TPMI_414.2_MegaPRS) |
PSS013079| East Asian Ancestry| 17,519 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: ASCVD | — | AUROC: 0.68306 | R²: 0.04501 | sex, age, array, PCs 1-10 | — |
| PPM037365 | PGS019183 (TPMI_414.2_PRS-CS) |
PSS013080| East Asian Ancestry| 17,519 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: ASCVD | — | AUROC: 0.68205 | R²: 0.04423 | sex, age, array, PCs 1-10 | — |
| PPM037366 | PGS019184 (TPMI_414.2_SBayesR) |
PSS013081| East Asian Ancestry| 17,519 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: ASCVD | — | AUROC: 0.68215 | R²: 0.04424 | sex, age, array, PCs 1-10 | — |
| PPM037367 | PGS019185 (TPMI_427_Lassosum2) |
PSS013113| East Asian Ancestry| 19,465 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cardiac dysrhythmias | — | AUROC: 0.59771 | R²: 0.03055 | sex, age, array, PCs 1-10 | — |
| PPM037368 | PGS019186 (TPMI_427_LDpred2) |
PSS013112| East Asian Ancestry| 19,465 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cardiac dysrhythmias | — | AUROC: 0.60028 | R²: 0.03211 | sex, age, array, PCs 1-10 | — |
| PPM037370 | PGS019188 (TPMI_427_PRS-CS) |
PSS013115| East Asian Ancestry| 19,465 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cardiac dysrhythmias | — | AUROC: 0.59933 | R²: 0.03192 | sex, age, array, PCs 1-10 | — |
| PPM037371 | PGS019189 (TPMI_427_SBayesR) |
PSS013116| East Asian Ancestry| 19,465 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cardiac dysrhythmias | — | AUROC: 0.5964 | R²: 0.02941 | sex, age, array, PCs 1-10 | — |
| PPM037372 | PGS019190 (TPMI_427.1_Lassosum2) |
PSS013088| East Asian Ancestry| 17,754 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Paroxysmal tachycardia unspecified | — | AUROC: 0.60796 | R²: 0.00608 | sex, age, array, PCs 1-10 | — |
| PPM037373 | PGS019191 (TPMI_427.1_LDpred2) |
PSS013087| East Asian Ancestry| 17,754 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Paroxysmal tachycardia unspecified | — | AUROC: 0.60822 | R²: 0.00609 | sex, age, array, PCs 1-10 | — |
| PPM037374 | PGS019192 (TPMI_427.1_MegaPRS) |
PSS013089| East Asian Ancestry| 17,754 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Paroxysmal tachycardia unspecified | — | AUROC: 0.6094 | R²: 0.00622 | sex, age, array, PCs 1-10 | — |
| PPM037376 | PGS019194 (TPMI_427.1_SBayesR) |
PSS013091| East Asian Ancestry| 17,754 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Paroxysmal tachycardia unspecified | — | AUROC: 0.60875 | R²: 0.00611 | sex, age, array, PCs 1-10 | — |
| PPM037377 | PGS019195 (TPMI_427.2_Lassosum2) |
PSS013098| East Asian Ancestry| 17,965 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Atrial fibrillation and flutter | — | AUROC: 0.73292 | R²: 0.05767 | sex, age, array, PCs 1-10 | — |
| PPM037378 | PGS019196 (TPMI_427.2_LDpred2) |
PSS013097| East Asian Ancestry| 17,965 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Atrial fibrillation and flutter | — | AUROC: 0.7427 | R²: 0.06297 | sex, age, array, PCs 1-10 | — |
| PPM037379 | PGS019197 (TPMI_427.2_MegaPRS) |
PSS013099| East Asian Ancestry| 17,965 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Atrial fibrillation and flutter | — | AUROC: 0.70596 | R²: 0.04182 | sex, age, array, PCs 1-10 | — |
| PPM037380 | PGS019198 (TPMI_427.2_PRS-CS) |
PSS013100| East Asian Ancestry| 17,965 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Atrial fibrillation and flutter | — | AUROC: 0.7416 | R²: 0.0615 | sex, age, array, PCs 1-10 | — |
| PPM037381 | PGS019199 (TPMI_427.2_SBayesR) |
PSS013101| East Asian Ancestry| 17,965 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Atrial fibrillation and flutter | — | AUROC: 0.71659 | R²: 0.04767 | sex, age, array, PCs 1-10 | — |
| PPM037382 | PGS019200 (TPMI_427.5_Lassosum2) |
PSS013103| East Asian Ancestry| 18,201 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Arrhythmia cardiac NOS | — | AUROC: 0.63874 | R²: 0.03526 | sex, age, array, PCs 1-10 | — |
| PPM037383 | PGS019201 (TPMI_427.5_LDpred2) |
PSS013102| East Asian Ancestry| 18,201 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Arrhythmia cardiac NOS | — | AUROC: 0.63859 | R²: 0.03539 | sex, age, array, PCs 1-10 | — |
| PPM037384 | PGS019202 (TPMI_427.5_MegaPRS) |
PSS013104| East Asian Ancestry| 18,201 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Arrhythmia cardiac NOS | — | AUROC: 0.64042 | R²: 0.03586 | sex, age, array, PCs 1-10 | — |
| PPM037385 | PGS019203 (TPMI_427.5_PRS-CS) |
PSS013105| East Asian Ancestry| 18,201 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Arrhythmia cardiac NOS | — | AUROC: 0.6374 | R²: 0.03475 | sex, age, array, PCs 1-10 | — |
| PPM037386 | PGS019204 (TPMI_427.5_SBayesR) |
PSS013106| East Asian Ancestry| 18,201 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Arrhythmia cardiac NOS | — | AUROC: 0.63709 | R²: 0.03468 | sex, age, array, PCs 1-10 | — |
| PPM037392 | PGS019210 (TPMI_427.21_Lassosum2) |
PSS013093| East Asian Ancestry| 17,941 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.73468 | R²: 0.05521 | sex, age, array, PCs 1-10 | — |
| PPM037393 | PGS019211 (TPMI_427.21_LDpred2) |
PSS013092| East Asian Ancestry| 17,941 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.74419 | R²: 0.06018 | sex, age, array, PCs 1-10 | — |
| PPM037394 | PGS019212 (TPMI_427.21_MegaPRS) |
PSS013094| East Asian Ancestry| 17,941 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.70516 | R²: 0.03926 | sex, age, array, PCs 1-10 | — |
| PPM037395 | PGS019213 (TPMI_427.21_PRS-CS) |
PSS013095| East Asian Ancestry| 17,941 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.73805 | R²: 0.05678 | sex, age, array, PCs 1-10 | — |
| PPM037396 | PGS019214 (TPMI_427.21_SBayesR) |
PSS013096| East Asian Ancestry| 17,941 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Atrial fibrillation | — | AUROC: 0.718 | R²: 0.04525 | sex, age, array, PCs 1-10 | — |
| PPM037397 | PGS019215 (TPMI_430_Lassosum2) |
PSS013123| East Asian Ancestry| 17,552 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracranial hemorrhage | — | AUROC: 0.66064 | R²: 0.01278 | sex, age, array, PCs 1-10 | — |
| PPM037398 | PGS019216 (TPMI_430_LDpred2) |
PSS013122| East Asian Ancestry| 17,552 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracranial hemorrhage | — | AUROC: 0.66428 | R²: 0.01316 | sex, age, array, PCs 1-10 | — |
| PPM037399 | PGS019217 (TPMI_430_MegaPRS) |
PSS013124| East Asian Ancestry| 17,552 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracranial hemorrhage | — | AUROC: 0.65946 | R²: 0.01257 | sex, age, array, PCs 1-10 | — |
| PPM037401 | PGS019219 (TPMI_430_SBayesR) |
PSS013126| East Asian Ancestry| 17,552 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracranial hemorrhage | — | AUROC: 0.65968 | R²: 0.01263 | sex, age, array, PCs 1-10 | — |
| PPM037402 | PGS019220 (TPMI_430.2_Lassosum2) |
PSS013118| East Asian Ancestry| 17,486 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracerebral hemorrhage | — | AUROC: 0.66204 | R²: 0.00902 | sex, age, array, PCs 1-10 | — |
| PPM037403 | PGS019221 (TPMI_430.2_LDpred2) |
PSS013117| East Asian Ancestry| 17,486 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracerebral hemorrhage | — | AUROC: 0.66451 | R²: 0.00928 | sex, age, array, PCs 1-10 | — |
| PPM037404 | PGS019222 (TPMI_430.2_MegaPRS) |
PSS013119| East Asian Ancestry| 17,486 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracerebral hemorrhage | — | AUROC: 0.66942 | R²: 0.01012 | sex, age, array, PCs 1-10 | — |
| PPM037405 | PGS019223 (TPMI_430.2_PRS-CS) |
PSS013120| East Asian Ancestry| 17,486 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracerebral hemorrhage | — | AUROC: 0.66267 | R²: 0.00903 | sex, age, array, PCs 1-10 | — |
| PPM037406 | PGS019224 (TPMI_430.2_SBayesR) |
PSS013121| East Asian Ancestry| 17,486 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracerebral hemorrhage | — | AUROC: 0.66098 | R²: 0.00882 | sex, age, array, PCs 1-10 | — |
| PPM037407 | PGS019225 (TPMI_433_Lassosum2) |
PSS013153| East Asian Ancestry| 19,528 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebrovascular disease | — | AUROC: 0.58403 | R²: 0.0205 | sex, age, array, PCs 1-10 | — |
| PPM037408 | PGS019226 (TPMI_433_LDpred2) |
PSS013152| East Asian Ancestry| 19,528 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebrovascular disease | — | AUROC: 0.58583 | R²: 0.0211 | sex, age, array, PCs 1-10 | — |
| PPM037409 | PGS019227 (TPMI_433_MegaPRS) |
PSS013154| East Asian Ancestry| 19,528 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebrovascular disease | — | AUROC: 0.58307 | R²: 0.02029 | sex, age, array, PCs 1-10 | — |
| PPM037411 | PGS019229 (TPMI_433_SBayesR) |
PSS013156| East Asian Ancestry| 19,528 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebrovascular disease | — | AUROC: 0.58559 | R²: 0.02111 | sex, age, array, PCs 1-10 | — |
| PPM037412 | PGS019230 (TPMI_433.2_Lassosum2) |
PSS013133| East Asian Ancestry| 18,165 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Occlusion of cerebral arteries | — | AUROC: 0.64904 | R²: 0.05282 | sex, age, array, PCs 1-10 | — |
| PPM037413 | PGS019231 (TPMI_433.2_LDpred2) |
PSS013132| East Asian Ancestry| 18,165 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Occlusion of cerebral arteries | — | AUROC: 0.64962 | R²: 0.0533 | sex, age, array, PCs 1-10 | — |
| PPM037414 | PGS019232 (TPMI_433.2_MegaPRS) |
PSS013134| East Asian Ancestry| 18,165 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Occlusion of cerebral arteries | — | AUROC: 0.64321 | R²: 0.04993 | sex, age, array, PCs 1-10 | — |
| PPM037415 | PGS019233 (TPMI_433.2_PRS-CS) |
PSS013135| East Asian Ancestry| 18,165 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Occlusion of cerebral arteries | — | AUROC: 0.65154 | R²: 0.05411 | sex, age, array, PCs 1-10 | — |
| PPM037416 | PGS019234 (TPMI_433.2_SBayesR) |
PSS013136| East Asian Ancestry| 18,165 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Occlusion of cerebral arteries | — | AUROC: 0.64638 | R²: 0.05144 | sex, age, array, PCs 1-10 | — |
| PPM037422 | PGS019240 (TPMI_433.6_Lassosum2) |
PSS013143| East Asian Ancestry| 17,584 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Acute but ill defined cerebrovascular disease | — | AUROC: 0.67118 | R²: 0.01491 | sex, age, array, PCs 1-10 | — |
| PPM037423 | PGS019241 (TPMI_433.6_LDpred2) |
PSS013142| East Asian Ancestry| 17,584 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Acute but ill defined cerebrovascular disease | — | AUROC: 0.67222 | R²: 0.01499 | sex, age, array, PCs 1-10 | — |
| PPM037424 | PGS019242 (TPMI_433.6_MegaPRS) |
PSS013144| East Asian Ancestry| 17,584 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Acute but ill defined cerebrovascular disease | — | AUROC: 0.6716 | R²: 0.01494 | sex, age, array, PCs 1-10 | — |
| PPM037425 | PGS019243 (TPMI_433.6_PRS-CS) |
PSS013145| East Asian Ancestry| 17,584 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Acute but ill defined cerebrovascular disease | — | AUROC: 0.67259 | R²: 0.01516 | sex, age, array, PCs 1-10 | — |
| PPM037426 | PGS019244 (TPMI_433.6_SBayesR) |
PSS013146| East Asian Ancestry| 17,584 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Acute but ill defined cerebrovascular disease | — | AUROC: 0.672 | R²: 0.01494 | sex, age, array, PCs 1-10 | — |
| PPM037427 | PGS019245 (TPMI_433.8_Lassosum2) |
PSS013148| East Asian Ancestry| 17,534 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Late effects of cerebrovascular disease | — | AUROC: 0.63759 | R²: 0.01205 | sex, age, array, PCs 1-10 | — |
| PPM037428 | PGS019246 (TPMI_433.8_LDpred2) |
PSS013147| East Asian Ancestry| 17,534 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Late effects of cerebrovascular disease | — | AUROC: 0.63716 | R²: 0.01173 | sex, age, array, PCs 1-10 | — |
| PPM037430 | PGS019248 (TPMI_433.8_PRS-CS) |
PSS013150| East Asian Ancestry| 17,534 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Late effects of cerebrovascular disease | — | AUROC: 0.63925 | R²: 0.01237 | sex, age, array, PCs 1-10 | — |
| PPM037431 | PGS019249 (TPMI_433.8_SBayesR) |
PSS013151| East Asian Ancestry| 17,534 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Late effects of cerebrovascular disease | — | AUROC: 0.63585 | R²: 0.01168 | sex, age, array, PCs 1-10 | — |
| PPM037432 | PGS019250 (TPMI_433.21_Lassosum2) |
PSS013128| East Asian Ancestry| 17,922 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebral artery occlusion with cerebral infarction | — | AUROC: 0.66398 | R²: 0.03769 | sex, age, array, PCs 1-10 | — |
| PPM037433 | PGS019251 (TPMI_433.21_LDpred2) |
PSS013127| East Asian Ancestry| 17,922 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebral artery occlusion with cerebral infarction | — | AUROC: 0.66506 | R²: 0.03875 | sex, age, array, PCs 1-10 | — |
| PPM037434 | PGS019252 (TPMI_433.21_MegaPRS) |
PSS013129| East Asian Ancestry| 17,922 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebral artery occlusion with cerebral infarction | — | AUROC: 0.66288 | R²: 0.03706 | sex, age, array, PCs 1-10 | — |
| PPM037435 | PGS019253 (TPMI_433.21_PRS-CS) |
PSS013130| East Asian Ancestry| 17,922 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebral artery occlusion with cerebral infarction | — | AUROC: 0.67066 | R²: 0.04063 | sex, age, array, PCs 1-10 | — |
| PPM036822 | PGS018640 (TPMI_228_Lassosum2) |
PSS012543| East Asian Ancestry| 19,931 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hemangioma and lymphangioma any site | — | AUROC: 0.69821 | R²: 0.01403 | sex, age, array, PCs 1-10 | — |
| PPM036824 | PGS018642 (TPMI_228_MegaPRS) |
PSS012544| East Asian Ancestry| 19,931 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hemangioma and lymphangioma any site | — | AUROC: 0.69622 | R²: 0.0139 | sex, age, array, PCs 1-10 | — |
| PPM036826 | PGS018644 (TPMI_228_SBayesR) |
PSS012546| East Asian Ancestry| 19,931 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Hemangioma and lymphangioma any site | — | AUROC: 0.69698 | R²: 0.01388 | sex, age, array, PCs 1-10 | — |
| PPM036922 | PGS018740 (TPMI_250.7_Lassosum2) |
PSS012672| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.62187 | R²: 0.01769 | sex, age, array, PCs 1-10 | — |
| PPM036923 | PGS018741 (TPMI_250.7_LDpred2) |
PSS012671| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.63759 | R²: 0.02299 | sex, age, array, PCs 1-10 | — |
| PPM036924 | PGS018742 (TPMI_250.7_MegaPRS) |
PSS012673| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.6363 | R²: 0.02173 | sex, age, array, PCs 1-10 | — |
| PPM036925 | PGS018743 (TPMI_250.7_PRS-CS) |
PSS012674| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.64129 | R²: 0.02379 | sex, age, array, PCs 1-10 | — |
| PPM036926 | PGS018744 (TPMI_250.7_PRSmix+) |
PSS012675| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.69783 | R²: 0.04794 | sex, age, array, PCs 1-10 | — |
| PPM036927 | PGS018745 (TPMI_250.7_SBayesR) |
PSS012676| East Asian Ancestry| 17,858 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Diabetic retinopathy | — | AUROC: 0.63067 | R²: 0.0204 | sex, age, array, PCs 1-10 | — |
| PPM037317 | PGS019135 (TPMI_401.1_PRS-CS) |
PSS013031| East Asian Ancestry| 18,140 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Essential hypertension | — | AUROC: 0.65139 | R²: 0.09149 | sex, age, array, PCs 1-10 | — |
| PPM037326 | PGS019144 (TPMI_401.3_Lassosum2) |
PSS013047| East Asian Ancestry| 17,975 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other hypertensive complications | — | AUROC: 0.64011 | R²: 0.02989 | sex, age, array, PCs 1-10 | — |
| PPM037338 | PGS019156 (TPMI_411_LDpred2) |
PSS013072| East Asian Ancestry| 19,485 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Ischemic Heart Disease | — | AUROC: 0.63411 | R²: 0.05386 | sex, age, array, PCs 1-10 | — |
| PPM037348 | PGS019166 (TPMI_411.4_LDpred2) |
PSS013062| East Asian Ancestry| 18,061 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Coronary atherosclerosis | — | AUROC: 0.65898 | R²: 0.06045 | sex, age, array, PCs 1-10 | — |
| PPM037359 | PGS019177 (TPMI_414_MegaPRS) |
PSS013084| East Asian Ancestry| 17,594 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Other forms of chronic heart disease | — | AUROC: 0.66895 | R²: 0.06063 | sex, age, array, PCs 1-10 | — |
| PPM037369 | PGS019187 (TPMI_427_MegaPRS) |
PSS013114| East Asian Ancestry| 19,465 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cardiac dysrhythmias | — | AUROC: 0.59639 | R²: 0.02961 | sex, age, array, PCs 1-10 | — |
| PPM037375 | PGS019193 (TPMI_427.1_PRS-CS) |
PSS013090| East Asian Ancestry| 17,754 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Paroxysmal tachycardia unspecified | — | AUROC: 0.60689 | R²: 0.00598 | sex, age, array, PCs 1-10 | — |
| PPM037400 | PGS019218 (TPMI_430_PRS-CS) |
PSS013125| East Asian Ancestry| 17,552 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Intracranial hemorrhage | — | AUROC: 0.66105 | R²: 0.01285 | sex, age, array, PCs 1-10 | — |
| PPM037410 | PGS019228 (TPMI_433_PRS-CS) |
PSS013155| East Asian Ancestry| 19,528 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebrovascular disease | — | AUROC: 0.58466 | R²: 0.02084 | sex, age, array, PCs 1-10 | — |
| PPM037429 | PGS019247 (TPMI_433.8_MegaPRS) |
PSS013149| East Asian Ancestry| 17,534 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Late effects of cerebrovascular disease | — | AUROC: 0.63781 | R²: 0.012 | sex, age, array, PCs 1-10 | — |
| PPM037436 | PGS019254 (TPMI_433.21_SBayesR) |
PSS013131| East Asian Ancestry| 17,922 individuals |
PGP000835 | Chen HH et al. Nature (2025) |
Reported Trait: Cerebral artery occlusion with cerebral infarction | — | AUROC: 0.66335 | R²: 0.03789 | sex, age, array, PCs 1-10 | — |
| PPM038245 | PGS002486 (disease_CARDIOVASCULAR.P+T.0.01) |
PSS013888| European Ancestry| 924 individuals |
PGP000855 | Dimitriou M et al. J Pers Med (2024) |Ext. |
Reported Trait: Overall coronary artery disease | OR: 1.004 | — | R²: 0.222 | — | — |
| PPM038246 | PGS002535 (disease_CARDIOVASCULAR.P+T.1e-06) |
PSS013888| European Ancestry| 924 individuals |
PGP000855 | Dimitriou M et al. J Pers Med (2024) |Ext. |
Reported Trait: Overall coronary artery disease | OR: 1.442 | — | R²: 0.227 | — | — |
| PPM038247 | PGS002584 (disease_CARDIOVASCULAR.P+T.5e-08) |
PSS013888| European Ancestry| 924 individuals |
PGP000855 | Dimitriou M et al. J Pers Med (2024) |Ext. |
Reported Trait: Overall coronary artery disease | OR: 1.483 | — | R²: 0.225 | — | — |
| PPM038248 | PGS002633 (disease_CARDIOVASCULAR.PolyFun-pred) |
PSS013888| European Ancestry| 924 individuals |
PGP000855 | Dimitriou M et al. J Pers Med (2024) |Ext. |
Reported Trait: Overall coronary artery disease | OR: 4.084 | — | R²: 0.229 | — | — |
| PPM038249 | PGS000012 (GRS49K) |
PSS013888| European Ancestry| 924 individuals |
PGP000855 | Dimitriou M et al. J Pers Med (2024) |Ext. |
Reported Trait: Overall coronary artery disease | OR: 1.153 | — | R²: 0.414 | HellenicSCORE | — |
| PPM038250 | PGS000116 (CAD_EJ2020) |
PSS013888| European Ancestry| 924 individuals |
PGP000855 | Dimitriou M et al. J Pers Med (2024) |Ext. |
Reported Trait: Overall coronary artery disease | OR: 0.063 | — | R²: 0.245 | — | — |
| PPM038251 | PGS000337 (MetaPRS_CAD) |
PSS013888| European Ancestry| 924 individuals |
PGP000855 | Dimitriou M et al. J Pers Med (2024) |Ext. |
Reported Trait: Overall coronary artery disease | OR: 1.095 | — | R²: 0.252 | — | — |
| PPM038252 | PGS000747 (PRS_EB) |
PSS013888| European Ancestry| 924 individuals |
PGP000855 | Dimitriou M et al. J Pers Med (2024) |Ext. |
Reported Trait: Overall coronary artery disease | OR: 1.095 | — | R²: 0.608 | HellenicSCORE | — |
| PPM038305 | PGS020005 (eMERGE_AF_PRS) |
PSS013914| European Ancestry| 26,900 individuals |
PGP000864 | Lennon NJ et al. Nat Med (2024) |
Reported Trait: Atrial fibrillation | OR: 1.44 | AUROC: 0.66 | — | Age, sex, first 4 PCs | — |
| PPM038306 | PGS020005 (eMERGE_AF_PRS) |
PSS013911| African Ancestry| 2,392 individuals |
PGP000864 | Lennon NJ et al. Nat Med (2024) |
Reported Trait: Atrial fibrillation | OR: 1.29 | AUROC: 0.65 | — | Age, sex, first 4 PCs | — |
| PPM038307 | PGS020005 (eMERGE_AF_PRS) |
PSS013912| African Ancestry| 3,408 individuals |
PGP000864 | Lennon NJ et al. Nat Med (2024) |
Reported Trait: Atrial fibrillation | OR: 1.25 | AUROC: 0.67 | — | Age, sex, first 4 PCs | — |
| PPM038308 | PGS020005 (eMERGE_AF_PRS) |
PSS013915| Hispanic or Latin American Ancestry| 933 individuals |
PGP000864 | Lennon NJ et al. Nat Med (2024) |
Reported Trait: Atrial fibrillation | OR: 1.39 | AUROC: 0.67 | — | Age, sex, first 4 PCs | — |
| PPM038309 | PGS020005 (eMERGE_AF_PRS) |
PSS013913| Additional Asian Ancestries| 400 individuals |
PGP000864 | Lennon NJ et al. Nat Med (2024) |
Reported Trait: Atrial fibrillation | OR: 1.64 | AUROC: 0.68 | — | Age, sex, first 4 PCs | — |
| PPM038302 | PGS020004 (PRS22_AAA) |
PSS013909| European Ancestry| 334,855 individuals |
PGP000862 | Zhu D et al. JACC Adv (2024) |
Reported Trait: Incident Abdominal aortic aneurysm | — | — | Hazard ratio (HR, high vs low tertile): 2.15 [1.89, 2.44] | age, sex, Townsend Deprivation Index, history of hypertension, family history of heart disease, lifestyle factors (body mass index, smoking status, alcohol intake, and physical activity) | — |
| PPM038303 | PGS020004 (PRS22_AAA) |
PSS013909| European Ancestry| 334,855 individuals |
PGP000862 | Zhu D et al. JACC Adv (2024) |
Reported Trait: Incident Abdominal aortic aneurysm x sleep pattern interaction | — | — | Hazard ratio (HR, poor sleep pattern and high PRS vs. low sleep pattern and low PRS): 2.56 [1.78, 3.69] | age, sex, Townsend Deprivation Index, history of hypertension, family history of heart disease, lifestyle factors (body mass index, smoking status, alcohol intake, and physical activity) | — |
| PPM038424 | PGS002047 (portability-ldpred2_401) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.04303 | — | — | — | — |
| PPM038458 | PGS000329 (PRS_CHD) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.03746 | — | — | — | — |
| PPM038516 | PGS002053 (portability-ldpred2_433) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.0298 | — | — | — | — |
| PPM038536 | PGS000337 (MetaPRS_CAD) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.02886 | — | — | — | — |
| PPM038547 | PGS002486 (disease_CARDIOVASCULAR.P+T.0.01) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.22882 | — | — | — | — |
| PPM038549 | PGS000709 (HC299) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.02846 | — | — | — | — |
| PPM038550 | PGS002682 (disease_CARDIOVASCULAR.SBayesR) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.02771 | — | — | — | — |
| PPM038563 | PGS000958 (GBE_HC273) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.02716 | — | — | — | — |
| PPM038572 | PGS002316 (disease_CARDIOVASCULAR.BOLT-LMM) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.02622 | — | — | — | — |
| PPM038593 | PGS000957 (GBE_HC932) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.02596 | — | — | — | — |
| PPM038626 | PGS000706 (HC215) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.02417 | — | — | — | — |
| PPM038648 | PGS002505 (disease_HYPERTENSION_DIAGNOSED.P+T.0.01) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.25353 | — | — | — | — |
| PPM038671 | PGS001790 (1kgeur_gbmi_leaveUKBBout_HF_pst_eff_a1_b0.5_phiauto) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: -0.02273 | — | — | — | — |
| PPM038682 | PGS002701 (disease_HYPERTENSION_DIAGNOSED.SBayesR) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.02171 | — | — | — | — |
| PPM038744 | PGS002335 (disease_HYPERTENSION_DIAGNOSED.BOLT-LMM) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01849 | — | — | — | — |
| PPM038755 | PGS000727 (AF_PGS) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.02118 | — | — | — | — |
| PPM038772 | PGS002048 (portability-ldpred2_411.4) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01743 | — | — | — | — |
| PPM038773 | PGS000710 (HC326) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01759 | — | — | — | — |
| PPM038774 | PGS002059 (portability-ldpred2_459.9) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.0175 | — | — | — | — |
| PPM038782 | PGS001846 (portability-PLR_455) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01731 | — | — | — | — |
| PPM038783 | PGS000748 (PRS_DE) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01742 | — | — | — | — |
| PPM038794 | PGS001320 (GBE_HC215) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01699 | — | — | — | — |
| PPM038800 | PGS000749 (PRS_COMBINED) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01687 | — | — | — | — |
| PPM038823 | PGS001839 (portability-PLR_411.4) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01603 | — | — | — | — |
| PPM038834 | PGS001335 (GBE_BIN_FC4006150) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01575 | — | — | — | — |
| PPM038860 | PGS002055 (portability-ldpred2_443.9) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01533 | — | — | — | — |
| PPM038883 | PGS002437 (disease_CARDIOVASCULAR.P+T.0.001) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.06289 | — | — | — | — |
| PPM038943 | PGS002456 (disease_HYPERTENSION_DIAGNOSED.P+T.0.001) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.06774 | — | — | — | — |
| PPM038952 | PGS000039 (metaGRS_ischaemicstroke) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01555 | — | — | — | — |
| PPM038991 | PGS002052 (portability-ldpred2_433.1) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01242 | — | — | — | — |
| PPM038994 | PGS000747 (PRS_EB) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01435 | — | — | — | — |
| PPM038996 | PGS001793 (1kgeur_gbmi_leaveUKBBout_Stroke_pst_eff_a1_b0.5_phiauto) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: -0.01235 | — | — | — | — |
| PPM039015 | PGS001798 (1kgeur_gbmi_Stroke_pst_eff_a1_b0.5_phiauto) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01202 | — | — | — | — |
| PPM039042 | PGS000331 (PRS_AF) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01172 | — | — | — | — |
| PPM039077 | PGS000962 (GBE_HC942) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01086 | — | — | — | — |
| PPM039080 | PGS001842 (portability-PLR_428) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01105 | — | — | — | — |
| PPM039113 | PGS000296 (GPS_CAD_SA) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.0105 | — | — | — | — |
| PPM039116 | PGS001780 (CHD_PRSCS) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01064 | — | — | — | — |
| PPM039151 | PGS001024 (GBE_HC61) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.00996 | — | — | — | — |
| PPM039167 | PGS002054 (portability-ldpred2_442.11) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.00956 | — | — | — | — |
| PPM038299 | PGS020002 (PRS12_HF) |
PSS013907| European Ancestry| 340,541 individuals |
PGP000860 | Shi Q et al. JACC Asia (2024) |
Reported Trait: Incident Heart Failure | HR: 1.05 [1.03, 1.06] | — | — | age, sex, ethnicity, the Townsend index, lifestyle factors (smoking status, alcohol intake frequency, a healthy diet score), and body mass index, systolic blood pressure, and baseline cancer, diabetes and use of antihypertensive medicine at baseline | — |
| PPM039225 | PGS002050 (portability-ldpred2_427.2) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.00906 | — | — | — | — |
| PPM039259 | PGS002584 (disease_CARDIOVASCULAR.P+T.5e-08) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: -0.0086 | — | — | — | — |
| PPM038300 | PGS020002 (PRS12_HF) |
PSS013907| European Ancestry| 340,541 individuals |
PGP000860 | Shi Q et al. JACC Asia (2024) |
Reported Trait: Incident Heart Failure x frailty interaction | — | — | Hazard ratio (HR, frail and high PRS vs. non-frail and low PRS): 1.72 [1.36, 2.18] | demographic variables (including age, sex, and ethnicity), the Townsend Deprivation Index, lifestyle factors (smoking status, alcohol intake frequency, and healthy diet score), body mass index, systolic blood pressure, baseline cancer incidence, diabetes incidence, and use of antihypertensive medicine at baseline | — |
| PPM038467 | PGS001838 (portability-PLR_401) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.0361 | — | — | — | — |
| PPM038498 | PGS002058 (portability-ldpred2_455) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.0313 | — | — | — | — |
| PPM038629 | PGS002051 (portability-ldpred2_428) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.02389 | — | — | — | — |
| PPM039196 | PGS000018 (metaGRS_CAD) |
PSS013916| European Ancestry| 425,240 individuals |
PGP000865 | Bhatt IS et al. J Assoc Res Otolaryngol (2024) |Ext. |
Reported Trait: Age-related hearing difficulty | β: 0.01005 | — | — | — | — |
| PPM038244 | PGS002437 (disease_CARDIOVASCULAR.P+T.0.001) |
PSS013888| European Ancestry| 924 individuals |
PGP000855 | Dimitriou M et al. J Pers Med (2024) |Ext. |
Reported Trait: Overall coronary artery disease | OR: 1.016 | — | R²: 0.222 | — | — |
|
PGS Sample Set ID (PSS) |
Phenotype Definitions and Methods | Participant Follow-up Time | Sample Numbers | Age of Study Participants | Sample Ancestry | Additional Ancestry Description | Cohort(s) | Additional Sample/Cohort Information |
|---|---|---|---|---|---|---|---|---|
| PSS012202 | I20-I25 | — | [ ,
43.33 % Male samples |
Mean = 60.0 years | East Asian (Chinese) |
— | DFTJ | — |
| PSS012203 | CAD was defined by coronary angiography as ≥50% stenosis in ≥1 major coronary artery, which manifested as occult CAD | — | [ ,
64.3 % Male samples |
Mean = 58.0 years | East Asian (Chinese) |
— | GRAND | — |
| PSS011439 | — | — | 68,709 individuals, 52.59 % Male samples |
Mean = 60.42 years Ci = [60.37, 60.48] years |
European | — | UKB | — |
| PSS011439 | — | — | 105 individuals, 52.38 % Male samples |
Mean = 55.61 years Ci = [54.11, 57.11] years |
African unspecified | — | UKB | — |
| PSS000008 | Coronary heart disease represented a composite of fatal or non-fatal myocardial infarction, coronary artery bypass grafting, or percutaneous coronary intervention | — | 27,271 individuals, 38.7 % Male samples |
— | European (Swedish) |
— | MDC | Primary prevention cohorts |
| PSS000008 | Coronary heart disease represented a composite of fatal or non-fatal myocardial infarction, coronary artery bypass grafting, or percutaneous coronary intervention | — | [ ,
67.8 % Male samples |
— | European | — | JUPITER | Primary prevention cohorts |
| PSS000008 | Coronary heart disease represented a composite of fatal or non-fatal myocardial infarction, coronary artery bypass grafting, or percutaneous coronary intervention | — | [ ,
79.7 % Male samples |
— | European | — | ASCOT | Primary prevention cohorts |
| PSS000009 | Coronary heart disease represented a composite of fatal or non-fatal myocardial infarction, coronary artery bypass grafting, or percutaneous coronary intervention | — | [ ,
86.1 % Male samples |
— | European | — | CARE_b | Secondary prevention cohorts |
| PSS000009 | Coronary heart disease represented a composite of fatal or non-fatal myocardial infarction, coronary artery bypass grafting, or percutaneous coronary intervention | — | [ ,
77.5 % Male samples |
— | European | — | PROVEIT | Secondary prevention cohorts |
| PSS011442 | — | — | [ ,
77.0 % Male samples |
Mean = 26.7 years | European | — | PDAY | — |
| PSS011441 | — | — | [ ,
82.0 % Male samples |
Mean = 27.5 years | African unspecified | — | PDAY | — |
| PSS011439 | — | — | 862 individuals, 51.86 % Male samples |
Mean = 57.82 years Ci = [57.28, 58.36] years |
Not reported | — | UKB | — |
| PSS011439 | — | — | 730 individuals, 49.18 % Male samples |
Mean = 57.46 years Ci = [56.89, 58.03] years |
Asian unspecified | — | UKB | — |
| PSS000010 | Incident CHD was defined as coronary revascularization, fatal or nonfatal myocardial infarction, or death due to ischemic heart disease. | — | [ ,
38.03 % Male samples |
— | European (Swedish) |
— | MDC | Prospective study |
| PSS000011 | The main outcome of interest was incident CHD event before age 75y. We used the definition of CHD as employed by the Framingham study, namely, one of • MI recognized, with diagnostic ECG (FHS event code #1) • MI recognized, without diagnostic ECG, with enzymes and history (#2) • MI recognized, without diagnostic ECG, with autopsy evidence (new event) (#3) • MI unrecognized, silent (#4) • MI unrecognized, not silent (#5) • Angina pectoris (AP), first episode only (#6) • Coronary insufficiency (CI), definite by both history and ECG (#7) • Questionable MI at exam 1 (#8) • Acute MI by autopsy, previously coded as 1 or 2 (#9) • Death, CHD sudden, with 1 hour (#21) • Death, CHD 1–23 hours, non sudden (#22) • Death, CHD 24-47 hours, non sudden (#23) • Death, CHD, 48 hours or more, non sudden (#24) | — | [ ,
45.0 % Male samples |
— | European | — | FHS | FHS Original, FHS Offspring |
| PSS000012 | Coronary heart disease (CHD) was defined as falling into any of the following categories: • I21 or I22 (ICD-10) / 410 (ICD-8/9) as the direct or as a contributing cause of death or I20-I25 (ICD-10) /410-414 (ICD-9) as the underlying cause of death • I21 or I22 (ICD-10) / 410 (ICD-8/9) as the main or secondary diagnosis at hospital discharge. • Coronary bypass surgery or coronary angioplasty at hospital discharge or identified from the Finnish registry of invasive cardiac procedures. | — | [ ,
46.0 % Male samples |
— | European (Finnish) |
— | FINRISK | FR92, FR97, FR02 |
| PSS011446 | — | — | [
|
— | African unspecified | — | ARIC, CHS, MESA, WHI, eMERGE | — |
| PSS011447 | — | — | [
|
— | East Asian | — | BBJ, OACIS, TaiChi | — |
| PSS011448 | — | — | [
|
— | European | — | ARIC, CHS, MESA, WHI, eMERGE | — |
| PSS011449 | — | — | [
|
— | Hispanic or Latin American | — | MESA, WHI, eMERGE | — |
| PSS011450 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS000013 | Atrial fibrillation ascertainment was based on self-report of atrial fibrillation, atrial flutter, or cardioversion in an interview with a trained nurse, an ICD-9 code of 427.3 or ICD-10 code of I48.X in hospitalization records, or a history of a percutaneous ablation or cardioversion based on the OPCS-4 coded procedure (K57.1, K62.1, K62.2, K62.3, or K 62.4), as performed previously | — | [
|
— | European | — | UKB | UKB Phase 2 |
| PSS000015 | CAD ascertainment was based on a composite of myocardial infarction or coronary revascularization. Myocardial infarction was based on self-report or hospital admission diagnosis, as performed centrally. This included individuals with ICD-9 codes of 410.X, 411.0, 412.X, or 429.79, or ICD-10 codes of I21.X, I22.X, I23.X, I24.1, or I25.2 in hospitalization records. Coronary revascularization was assessed based on an OPCS-4 coded procedure for coronary artery bypass grafting (K40.1–40.4, K41.1–41.4, or K45.1–45.5), or coronary angioplasty with or without stenting (K49.1–49.2, K49.8–49.9, K50.2, K75.1–75.4, or K75.8–75.9). | — | [
|
— | European | — | UKB | UKB Phase 2 |
| PSS000018 | CAD was defined as fatal or nonfatal myocardial infarction (MI) cases, percutaneous transluminal coronary angioplasty (PTCA), or coronary artery bypass grafting (CABG). Prevalent versus incident status was relative to the UKB enrollment assessment. In UKB self-reported data, cases were defined as having had a heart attack diagnosed by a doctor (data field #6150); “non-cancer illnesses that self-reported as heart attack” (data field #20002); or self-reported operation including PTCA, CABG, or triple heart bypass (data field #20004). In HES hospital episodes data and death registry data, MI was defined as hospital admission or cause of death due to ICD-9 410 to 412, or ICD-10 I21 to I24 or I25.2; CABG and PTCA were defined as hospital admission OPCS-4 K40 to K46, K49, K50.1,or K75. | — | [ ,
45.6 % Male samples |
— | European, NR | ~95% European ancestry samples, <5% non-European ancestry | UKB | — |
| PSS000019 | Prevalent Coronary artery disease (CAD), where CAD is defined as previous diagnosis of myocardial infarction or revascularization procedures (percutaneous coronary intervention or coronary artery bypass grafting). | — | [ ,
41.29 % Male samples |
— | European (French Canadian) |
— | CARTaGENE | — |
| PSS000020 | Recurrent CAD event during the follow- up period (median follow-up time =3.9 years [range =1.1–7), where CAD is defined as previous diagnosis of myocardial infarction or revascularization procedures (percutaneous coronary intervention or coronary artery bypass grafting). | — | [
|
— | European (French Canadian) |
— | MHI | Phase 1 |
| PSS000020 | Recurrent CAD event during the follow- up period (median follow-up time =3.9 years [range =1.1–7), where CAD is defined as previous diagnosis of myocardial infarction or revascularization procedures (percutaneous coronary intervention or coronary artery bypass grafting). | — | [
|
— | European (French Canadian) |
— | MHI | Phase 2 |
| PSS000021 | Prevalent Coronary artery disease (CAD), where CAD is defined as previous diagnosis of myocardial infarction or revascularization procedures (percutaneous coronary intervention or coronary artery bypass grafting). | — | [ ,
72.7 % Male samples |
— | European (French Canadian) |
— | MHI | Phase 1 |
| PSS000022 | Prevalent Coronary artery disease (CAD), where CAD is defined as previous diagnosis of myocardial infarction or revascularization procedures (percutaneous coronary intervention or coronary artery bypass grafting). | — | [ ,
72.38 % Male samples |
— | European (French Canadian) |
— | MHI | Phase 2 |
| PSS013888 | — | — | [ ,
63.9 % Male samples |
Mean = 57.7 years Sd = 12.4 years |
European (Greek) |
— | THISEAS | — |
| PSS012204 | OMOP.Ids: 313217 and 314665 | — | [
|
— | European | — | AllofUs | — |
| PSS012205 | I48, I48.0, I48.1, I48.2, I48.3, I48.4, I48.9, 427.3. | — | [
|
— | South Asian | — | UKB | — |
| PSS012206 | OMOP.Ids: 313217 and 314665 | — | [
|
— | Hispanic or Latin American | — | AllofUs | — |
| PSS012207 | OMOP.Ids: 313217 and 314665 | — | [
|
— | African American or Afro-Caribbean | — | AllofUs | — |
| PSS012208 | OMOP.Ids: 313217 and 314665 | — | [
|
— | South Asian | — | AllofUs | — |
| PSS000023 | CAD case endpoints were defined as: angina, myocardial infarction, coronary angioplasty, and coronary bypass surgery. Participants are described as Caucasian with diagnosed Familial hypercholesterolemia(FH; Dutch Lipid Criteria score >= 3 [possible, probable, or definite FH]) and carriers of classical French Canadian mutations in the LDLR gene including del .15 kb of the promoter and exon 1, del .5 kb of exons 2 and 3, W66G (exon 3), E207K (exon 4), Y468X (exon 10), and C646Y (exon 14). | — | [ ,
42.8 % Male samples |
— | European | CNMA | Nutrition, Metabolism and Atherosclerosis Clinic (CNMA) of Institut de recherches cliniques de Montréal | |
| PSS000024 | Cerebrovascular disease (CVD) case endpoints were defined as: transient ischemic attack, stroke, and carotid endarterectomy. Participants are described as Caucasian with diagnosed Familial hypercholesterolemia(FH; Dutch Lipid Criteria score >= 3 [possible, probable, or definite FH]) and carriers of classical French Canadian mutations in the LDLR gene including del .15 kb of the promoter and exon 1, del .5 kb of exons 2 and 3, W66G (exon 3), E207K (exon 4), Y468X (exon 10), and C646Y (exon 14). | — | [ ,
42.8 % Male samples |
— | European | — | CNMA | Nutrition, Metabolism and Atherosclerosis Clinic (CNMA) of Institut de recherches cliniques de Montréal |
| PSS012209 | OMOP.Ids: 313217 and 314665 | — | [
|
— | East Asian | — | AllofUs | — |
| PSS012210 | physician's diagnosis or electrocardiogram records | — | [
|
— | East Asian (Japanese) |
— | BBJ | Biobank Japan 2nd cohort |
| PSS012211 | I48, I48.0, I48.1, I48.2, I48.3, I48.4, I48.9, 427.3. | — | [
|
— | European (Norwegian) |
— | HUNT | — |
| PSS012212 | - | — | [
|
— | European (Danish) |
— | LOOP | — |
| PSS012213 | I48, I48.0, I48.1, I48.2, I48.3, I48.4, I48.9, 427.3. | — | [
|
— | African unspecified | — | UKB | — |
| PSS013907 | — | — | 340,541 individuals, 45.7 % Male samples |
Mean = 55.9 years Sd = 8.1 years |
European | — | UKB | — |
| PSS012216 | — | — | [
|
— | European | — | UKB | — |
| PSS013909 | — | — | [
|
Mean = 63.49 years Sd = 4.84 years |
European | — | UKB | — |
| PSS012218 | — | — | [
|
— | European | — | UKB | — |
| PSS013911 | — | — | [
|
— | African unspecified | — | eMERGE | — |
| PSS012220 | — | — | [
|
— | European | — | UKB | — |
| PSS013912 | — | — | [
|
— | African unspecified | — | eMERGE | — |
| PSS013914 | — | — | [
|
— | European | — | eMERGE | — |
| PSS013915 | — | — | [
|
— | Hispanic or Latin American | — | eMERGE | — |
| PSS013913 | — | — | [
|
— | Asian unspecified | — | eMERGE | — |
| PSS013916 | — | — | [ ,
46.21 % Male samples |
— | European (British, Irish) |
— | UKB | — |
| PSS009289 | — | — | 19,330 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS012227 | — | — | [
|
— | European (British) |
— | UKB | — |
| PSS012228 | — | — | [
|
— | European (British) |
— | UKB | — |
| PSS012229 | — | — | [
|
— | European (British) |
— | UKB | — |
| PSS011465 | — | — | 9,462 individuals | — | European | — | AllofUs | — |
| PSS009310 | — | — | 20,000 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009311 | — | — | 19,308 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009312 | — | — | 19,808 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009313 | — | — | 19,230 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009314 | — | — | 19,961 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009315 | — | — | 19,915 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009316 | — | — | 19,445 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009317 | — | — | 19,545 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009318 | — | — | 19,668 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009319 | — | — | 18,164 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS011474 | — | — | 8,837 individuals | — | South Asian | — | G&H | — |
| PSS009321 | — | — | 19,218 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009322 | — | — | 19,705 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS000053 | Participants were classified as having AF if an arrhythmia was present on an ECG obtained at a study visit or encounter with external clinicians, Holter monitoring, or noted in hospital records during a median 9.4 years of follow-up. | — | [ ,
45.9 % Male samples |
— | European, NR | FHS is principally composed of individuals of European ancestry | FHS | Samples were obtained from the following FHS cohorts: Original, Offspring, and Third Generation. Participants were eligible for inclusion if they were AF free at an average age of 55. |
| PSS011487 | — | — | 7,465 individuals | — | European | — | AllofUs | — |
| PSS000057 | Incident stroke in was defined based on the UK Biobank (UKB) algorithm, based on medical history and linkage to data on hospital admissions and mortality. The authors also subtyped ischaemic stroke, intracerebral haemorrhage, or subarachnoid haemorrhage. UKB Participants with genetic data were excluded from the analysis based on the following criteria: failing genetic quality control (missingness > 5%, sex mismatch, excessive heterozygosity), having a history of stroke or myocardial infarction (MI), self-report of stroke or MI, missing lifestyle information. | Median = 7.1 years | [ ,
44.59 % Male samples |
Mean = 56.7 years Sd = 7.9 years |
European | Unrelated White British subset of UKB participants | UKB | — |
| PSS012247 | Self-report disease: 1075; ICD9: 4109, 4119, 4129, 4299; ICD10: I21-I23, I24.1, I25.2 | — | [
|
— | East Asian | — | UKB | — |
| PSS011506 | — | — | 7,889 individuals | — | European | — | AllofUs | — |
| PSS000058 | Prevalent and incident Ischaemic stroke; defined in http://biobank.ndph.ox.ac.uk/showcase/docs/alg_outcome_stroke.pdf | Mean = 6.3 years Sd = 1.9 years |
[ ,
45.7 % Male samples |
Mean = 54.3 years | European | — | UKB | Validation set |
| PSS012254 | — | Median = 12.66 years | [ ,
44.39 % Male samples |
Mean = 56.22 years Sd = 8.09 years |
European | — | UKB | — |
| PSS011930 | — | — | 10,836 individuals | — | European (British) |
— | UKB | — |
| PSS011521 | — | — | [ ,
45.8 % Male samples |
Mean = 69.8 years | European | — | UKB | — |
| PSS000066 | VTE was defined in the MVP cohort using the following diagnosis codes for: - Deep Venous Thrombosis ICD-10 codes: {I80.1, I80.2, I82.22, I82.4, I82.5} and ICD-9 codes: {451.11, 451.19, 453.2, 453.4} - Pulmonary Embolism ICD-10 codes: {I26.0, I26.9} and ICD-9 code {415.1} | — | [
|
— | European | — | MVP | MVP Cohort = 3.0 |
| PSS000067 | — | — | [ ,
0.0 % Male samples |
Mean = 65.0 years | European | — | WHI, WHI-GARNET, WHI-HT, WHI-LLS, WHI-MS | — |
| PSS011404 | Cases were individuals with atrial fibrillation (AF). Cases were identified using ICD-10 code: I48 and ICD-9 code: 427.3. | — | [ ,
47.7 % Male samples |
Mean = 57.0 years Sd = 7.4 years |
European | — | FINRISK | — |
| PSS011405 | Cases were individuals with atrial fibrillation (AF). AF was defined as a clinically reported finding of AF or atrial flutter from a 12- lead ECG or a diagnosis of AF or atrial flutter applied to two or more inpatient or outpatient encounters or on the patient problem list from the institutional electronic health record. Diagnosis codes used to define AF included ICD10: I48.0, I48.1, I48.2, I48.3 and I48.91); ICD9: 427.31; and 92 separate internal codes. | — | [ ,
34.2 % Male samples |
Mean = 47.3 years Sd = 15.2 years |
European, Not reported | — | MyCode | — |
| PSS011800 | — | — | [
|
— | African American or Afro-Caribbean | — | AllofUs | — |
| PSS012268 | — | — | 151,741 individuals, 43.4 % Male samples |
Mean = 55.8 years Sd = 7.7 years |
European | — | UKB | — |
| PSS010008 | PheCode 401.1 (http://phewascatalog.org/); Binary | — | [
|
— | European | — | MGI | — |
| PSS012270 | — | — | 425,676 individuals | — | European | — | UKB | — |
| PSS011801 | — | — | [
|
— | African American or Afro-Caribbean | — | AllofUs | — |
| PSS012270 | — | — | 8,639 individuals | — | South Asian | — | UKB | — |
| PSS012270 | — | — | 7,345 individuals | — | African American or Afro-Caribbean | — | UKB | — |
| PSS012270 | — | — | 1,462 individuals | — | East Asian (Chinese) |
— | UKB | — |
| PSS012270 | — | — | 9,980 individuals | — | Not reported | — | UKB | — |
| PSS012271 | — | — | 8,639 individuals | — | South Asian | — | UKB | — |
| PSS012271 | — | — | 7,345 individuals | — | African American or Afro-Caribbean | — | UKB | — |
| PSS012271 | — | — | 1,462 individuals | — | East Asian (Chinese) |
— | UKB | — |
| PSS012271 | — | — | 9,980 individuals | — | Not reported | — | UKB | — |
| PSS000089 | Total carotid plaque burden (mm2) | — | 4,392 individuals | Range = [55.0, 80.0] years | NR | — | BioImage | — |
| PSS000090 | Total coronary arterial clacification (CAC) was coded as a a dichotomous outcome variable (CAC>0 versus CAC=0), and quantified by the Agatston method | Mean = 15.0 years | 1,154 individuals | Range = [32.0, 47.0] years | NR | — | CARDIA | — |
| PSS000091 | Nonfatal myocardial infarction or death from CHD | Mean = 13.5 years Sd = 2.8 years |
2,440 individuals, 100.0 % Male samples |
Mean = 55.1 years Sd = 5.5 years |
NR | — | NR | Participants were all men hypercholesterolemia but without a history of myocardial infarction, allocated to the placebo group |
| PSS000092 | Incident Major coronary events (MCE) are defined as: fatal or nonfatal coronary artery disease (CAD) events, nonfatal myocardial infarction, or unstable angina | Median = 4.7 years | [ ,
64.8 % Male samples |
Mean = 62.8 years | European | Self reported white | ACCORD | Type 2 Diabetes patients |
| PSS000093 | Incident Major coronary events (MCE) are defined as: fatal or nonfatal coronary artery disease (CAD) events, nonfatal myocardial infarction, or unstable angina | Median = 6.2 years | [
|
— | European | Self reported white | ORIGIN | Participants are from the Outcome Reduction With Initial Glargine Intervention (ORIGIN) trial and were enrolled based on having some combination of impaired fasting glucose, impaired glucose tolerance or type 2 diabetes, and high cardiovascular risk |
| PSS011539 | — | — | [
|
— | European | — | FinnGen | — |
| PSS011540 | — | — | [
|
— | European | — | G&H | — |
| PSS011541 | — | — | [
|
— | European | — | GS:SFHS | — |
| PSS011542 | — | — | [
|
— | European | — | GEL | — |
| PSS011543 | — | — | [
|
— | European | — | HUNT | — |
| PSS011544 | — | — | [
|
— | European | — | MGBB | — |
| PSS011538 | — | — | [
|
— | European | — | EB | — |
| PSS013031 | 401,I10 | — | [ ,
44.97 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013034 | 402,I11 | — | [ ,
42.22 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS000094 | Incident CHD was defined as myocardial infarction (MI), resuscitated cardiac arrest, definite or probable angina if followed by a revascularization and CHD death | — | [
|
Mean = 62.6 years | European | Analysis restricted to "White participants" | MESA | — |
| PSS000095 | Incident CHD was defined as myocardial infarction (MI), resuscitated cardiac arrest, definite or probable angina if followed by a revascularization and CHD death | — | [
|
Mean = 62.7 years | European | Analysis restricted to "White participants" | MESA | — |
| PSS013035 | 402,I11 | — | [ ,
42.22 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013036 | 402,I11 | — | [ ,
42.22 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011567 | — | — | [
|
— | European | — | EB | — |
| PSS011568 | — | — | [
|
— | European | — | FinnGen | — |
| PSS011569 | — | — | [
|
— | European | — | G&H | — |
| PSS011570 | — | — | [
|
— | European | — | GS:SFHS | — |
| PSS011571 | — | — | [
|
— | European | — | GEL | — |
| PSS011572 | — | — | [
|
— | European | — | HUNT | — |
| PSS011573 | — | — | [
|
— | European | — | MGBB | — |
| PSS013037 | 402,I11 | — | [ ,
42.22 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013038 | 402,I11 | — | [ ,
42.22 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013145 | 346.6, 436,G43.6 | — | [ ,
44.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013039 | 402,I11 | — | [ ,
42.22 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS000601 | All patients with atrial fibrillation and CHADS2 score of 2 or higher who were treated with anticoagulation. The endpoint of interest was ischemic stroke. In each trial, ischemic stroke was formally adjudicated by an independent clinical endpoint committee blinded to treatment assignment. | Median = 2.8 years | [ ,
60.78 % Male samples |
Mean = 70.8 years Sd = 9.1 years |
European | — | ENGAGE_AF-TIMI_48 | — |
| PSS000602 | The endpoint of interest was ischemic stroke. In each trial, ischemic stroke was formally adjudicated by an independent clinical endpoint committee blinded to treatment assignment. | Median = 2.5 years | [ ,
71.7 % Male samples |
Mean = 65.9 years Sd = 9.2 years |
European | — | ENGAGE_AF-TIMI_48, FOURIER, PEGASUS-TIMI_54, SAVOR-TIMI_53, SOLID-TIMI_52 | — |
| PSS009500 | — | — | [
|
— | European (British) |
— | UKB | — |
| PSS003596 | All individuals had breast cancer. Cases were individuals who suffered incident coronary artery disease (CAD) events. Incident CAD events were defined as a composite endpoint of unstable angina, myocardial infarction, or death due to complications following myocardial infarction according to the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10 codes): I21, I22, I23, I25 and I25. | — | [ ,
0.0 % Male samples |
— | European | — | SEARCH | — |
| PSS003597 | All individuals had breast cancer. Cases were individuals who suffered incident coronary artery disease (CAD) events. Incident CAD events were defined as a composite endpoint of unstable angina, myocardial infarction, or death due to complications following myocardial infarction according to the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10 codes): I21, I22, I23, I25 and I25. | Median = 10.3 years | [ ,
0.0 % Male samples |
— | European, African unspecified, Asian unspecified, Not reported | European = 11,995, African unspecified = 1, Asian unspecified = 2, Not reported = 413 | SEARCH | — |
| PSS012038 | ICD-9 Diagnosis: 4400, 44020, 44021, 44022, 44023, 44024, 44029, 44030, 44031, 44032, 4404, 4408, 4439, 4471 ICD-10 Diagnosis: I700, I70201, I70202, I70203, I70209, I70211, I70212, I70213, I70219, I70221, I70222, I70223, I7025, I70229, I70231, I70232, I70233, I70234, I70235, I70238, I70239, I70241, I70242, I70243, I70244, I70245, I70248, I70249, I70261, I70262, I70263, I70269, I70291, I70292, I70293, I70299, I70301, I70302, I70303, I70309, I70311, I70312, I70313, I70319, I70321, I70322, I70323, I70329, I70331, I70332, I70333, I70334, I70335, I70338, I70339, I70341, I70342, I70343, I70344, I70345, I70348, I70349, I70361, I70362, I70363, I70369, I70391, I70392, I70393, I70399, I70401, I70402, I70403, I70409, I70411, I70412, I70413, I70419, I70421, I70422, I70423, I70429, I70431, I70432, I70433, I70434, I70435, I70438, I70439, I70441, I70442, I70443, I70444, I70445, I70448, I70449, I70461, I70462, I70463, I70469, I70491, I70492, I70493, I70499, I70501, I70502, I70503, I70509, I70511, I70512, I70513, I70519, I70521, I70522, I70523, I70529, I70531, I70532, I70533, I70534, I70535, I70538, I70539, I70541, I70542, I70543, I70544, I70545, I70548, I70549, I70561, I70562, I70563, I70569, I70591, I70592, I70593, I70599, I70601, I70602, I70603, I70609, I70611, I70612, I70613, I70619, I70621, I70622, I70623, I70629, I70631, I70632, I70633, I70634, I70635, I70638, I70639, I70641, I70642, I70643, I70644, I70645, I70648, I70649, I70661, I70662, I70663, I70669, I70691, I70692, I70693, I70699, I70701, I70702, I70703, I70709, I70711, I70712, I70713, I70719, I70721, I70722, I70723, I70729, I70731, I70732, I70733, I70734, I70735, I70738, I70739, I70741, I70742, I70743, I70744, I70745, I70748, I70749, I70761, I70762, I70763, I70769, I70791, I70792, I70793, I70799, I7092, I739, I771 CPT: 93668, 27290, 27295, 27590, 27592, 27594, 27596, 27598, 27880, 27881, 27882, 27884, 27886, 27888, 35302, 35303, 35304, 35305, 35306, 35331, 35351, 35355, 35361, 35363, 35371, 35372, 35452, 35454, 35456, 35459, 35470, 35472, 35473, 35474, 35481, 35482, 35483, 35485, 35491, 35492, 35493, 35495, 35521, 35533, 35537, 35538, 35539, 35540, 35548, 35549, 35551, 35556, 35558, 35563, 35565, 35566, 35571, 35583, 35585, 35587, 35621, 35623, 35637, 35638, 35646, 35647, 35654, 35656, 35661, 35663, 35665, 35666, 35671, 35876, 35879, 35881, 35883, 35884, 37220, 37221, 37222, 37223, 37224, 37225, 37226, 37227, 37228, 37229, 37230, 37231, 37232, 37233, 37234, 37235, 35381, 35541, 35546, 35582, 35651, 35641 ICD-9 Procedure: 38.18, 39.25, 39.29, 39.5, 39.9, 84.1, 84.12, 84.13, 84.14, 84.15, 84.16, 84.17, 84.18, 84.19, 84.3 ICD-10 Procedure: 041C***, 041D***, 041F***, 041H***, 041J***, 041K***, 041L***, 041M***, 041N***, 041U***, 0470***, 047C***, 047D***, 047E***, 047F***, 047H***, 047J***, 047K***, 047L***, 047M***, 047N***, 047P***, 047Q***, 047R***, 047S***, 047T***, 047U***, 047V***, 047W***, 047Y***, 04C0***, 04CC***, 04CD***, 04CE***, 04CF***, 04CH***, 04CJ***, 04CK***, 04CL***, 04CM***, 04CN***, 04CP***, 04CQ***, 04CR***, 04CS***, 04CT***, 04CU***, 04CV***, 04CW***, 04CY***, 0Y62***, 0Y63***, 0Y68***, 0Y6C***, 0Y6D***, 0Y6F***, 0Y6G***, 0Y6H***, 0Y6J***, 0Y6M***, 0Y6N*** | Median = 2.32 years | [
|
— | African American or Afro-Caribbean | — | AllofUs | — |
| PSS013047 | 401.0, 405, 437.2,I15, I16, I67.4, N26.2 | — | [ ,
44.87 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS009513 | — | — | [
|
— | East Asian (Japanese) |
— | BBJ | — |
| PSS011775 | — | — | 190,489 individuals | — | European | — | UKB | — |
| PSS013048 | 401.0, 405, 437.2,I15, I16, I67.4, N26.2 | — | [ ,
44.87 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS009517 | — | — | [
|
— | European (Estonian) |
— | EB | — |
| PSS013049 | 401.0, 405, 437.2,I15, I16, I67.4, N26.2 | — | [ ,
44.87 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS003604 | — | — | [
|
Mean = 56.81 years | European | — | UKB | — |
| PSS003605 | — | — | [
|
Mean = 56.81 years | European | — | UKB | — |
| PSS009521 | — | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS013050 | 401.0, 405, 437.2,I15, I16, I67.4, N26.2 | — | [ ,
44.87 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS009525 | — | — | [
|
— | European | Norwegian | HUNT | — |
| PSS009529 | — | — | [
|
— | African American or Afro-Caribbean | — | MGBB | — |
| PSS009533 | — | — | [
|
— | European | — | MGBB | — |
| PSS011775 | — | — | 71 individuals | — | Not reported | — | UKB | — |
| PSS009537 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS009541 | — | — | [
|
— | European | British | UKB | — |
| PSS009545 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS011669 | Inclusion: MGH encounter AND ICD-9 code for diabetes AND Problem list term for diabetes OR HbA1C >6.5 in prior 3 years Exclusion: Problem list term not associated with diabetes; Inclusion problem list terms: DM, Diabetes Mellitus, Diabetic Nephropathy, Diabetic Neuropathy, Diabetic Retinopathy, Diabetic foot care, Diabetic foot infection, Diabetes Mellitus without complication, Insulin dependent diabetes mellitus, Insulin dependent diabetes without complications, Type 1, Diabetes mellitus I, DM type I, Juvenile, DM type i, Type I DM, Diabetes Mellitus type 1, Juvenile onset diabetes mellitus, Type 1 diabetes mellitus uncontrolled, Type 1 diabetes mellitus well controlled, DM1, Adult onset, AODM, Type 2, DM type ii, Diabetes mellitus ii, DMii, Type 2 DM, Type ii DM, Diabetes mellitus type 2, noninsulin dependent diabetes mellitus, Type 2 diabetes mellitus uncontrolled, Type 2 diabetes mellitus well controlled, Diabetes adult-adult onset, NIDDM.; Inclusion ICD-9 codes: 250.21, 250.23, 250.11, 250.13, 250.61, 250.63, 250.51, 250.53, 250.31, 250.33, 250.81, 250.83, 250.71, 250.73, 250.41, 250.43, 250.91, 250.93, 250.01, 250.03, 250.20, 250.22, 250.10, 250.12, 250.60, 250.62, 250.50, 250.52, 250.30, 250.32, 250.80, 250.82, 250.70, 250.72, 250.40, 250.42, 250.90, 250.92, 250.00, 250.02; Exclusion problem list terms: negative, neg, r/o, risk, rule out, no, consider diabetes, borderline, gestational, maternal, pregnancy, glucose impai, impaired glucose, insipidus, pre diabetes, prediab, family history, PCOS, Polycystic Ovary Syndrome | Median = 13.9 years | 9,909 individuals, 42.32 % Male samples |
Mean = 60.4 years | European | — | MGBB | — |
| PSS007665 | Of the 1,132 individuals, 1,070 had a coronary artery calcium (CAC) score ≤ 20, whilst the remaining 62 had a CAC score >20. To calculate CAC scores, participants underwent two computed tomography scans from the root of the aorta to the apex of the heart at year 15. From these, Agatston scores, adjusted using a standard calcium phantom scanned underneath each participant, were computed for the four major arteries. The CAC Agatston score is the average of two scans. | — | [ ,
48.1 % Male samples |
Mean = 25.6 years Sd = 3.3 years |
European | — | CARDIA | — |
| PSS007666 | Of the 663 individuals, 500 individuals had a coronary artery calcium (CAC) score ≤ 300, whilst the remaining 93 had a CAC score > 300. To calculate CAC scores, participants underwent two computed tomography scans from the root of the aorta to the apex of the heart at year 30. From these, Agatston scores, adjusted using a standard calcium phantom scanned underneath each participant, were computed for the four major arteries. The CAC Agatston score is the average of two scans. | — | [ ,
46.5 % Male samples |
Mean = 27.8 years Sd = 4.7 years |
European | — | FOS | — |
| PSS011669 | Inclusion: MGH encounter AND ICD-9 code for diabetes AND Problem list term for diabetes OR HbA1C >6.5 in prior 3 years Exclusion: Problem list term not associated with diabetes; Inclusion problem list terms: DM, Diabetes Mellitus, Diabetic Nephropathy, Diabetic Neuropathy, Diabetic Retinopathy, Diabetic foot care, Diabetic foot infection, Diabetes Mellitus without complication, Insulin dependent diabetes mellitus, Insulin dependent diabetes without complications, Type 1, Diabetes mellitus I, DM type I, Juvenile, DM type i, Type I DM, Diabetes Mellitus type 1, Juvenile onset diabetes mellitus, Type 1 diabetes mellitus uncontrolled, Type 1 diabetes mellitus well controlled, DM1, Adult onset, AODM, Type 2, DM type ii, Diabetes mellitus ii, DMii, Type 2 DM, Type ii DM, Diabetes mellitus type 2, noninsulin dependent diabetes mellitus, Type 2 diabetes mellitus uncontrolled, Type 2 diabetes mellitus well controlled, Diabetes adult-adult onset, NIDDM.; Inclusion ICD-9 codes: 250.21, 250.23, 250.11, 250.13, 250.61, 250.63, 250.51, 250.53, 250.31, 250.33, 250.81, 250.83, 250.71, 250.73, 250.41, 250.43, 250.91, 250.93, 250.01, 250.03, 250.20, 250.22, 250.10, 250.12, 250.60, 250.62, 250.50, 250.52, 250.30, 250.32, 250.80, 250.82, 250.70, 250.72, 250.40, 250.42, 250.90, 250.92, 250.00, 250.02; Exclusion problem list terms: negative, neg, r/o, risk, rule out, no, consider diabetes, borderline, gestational, maternal, pregnancy, glucose impai, impaired glucose, insipidus, pre diabetes, prediab, family history, PCOS, Polycystic Ovary Syndrome | Median = 13.9 years | 757 individuals, 42.32 % Male samples |
Mean = 60.4 years | Hispanic or Latin American | — | MGBB | — |
| PSS011669 | Inclusion: MGH encounter AND ICD-9 code for diabetes AND Problem list term for diabetes OR HbA1C >6.5 in prior 3 years Exclusion: Problem list term not associated with diabetes; Inclusion problem list terms: DM, Diabetes Mellitus, Diabetic Nephropathy, Diabetic Neuropathy, Diabetic Retinopathy, Diabetic foot care, Diabetic foot infection, Diabetes Mellitus without complication, Insulin dependent diabetes mellitus, Insulin dependent diabetes without complications, Type 1, Diabetes mellitus I, DM type I, Juvenile, DM type i, Type I DM, Diabetes Mellitus type 1, Juvenile onset diabetes mellitus, Type 1 diabetes mellitus uncontrolled, Type 1 diabetes mellitus well controlled, DM1, Adult onset, AODM, Type 2, DM type ii, Diabetes mellitus ii, DMii, Type 2 DM, Type ii DM, Diabetes mellitus type 2, noninsulin dependent diabetes mellitus, Type 2 diabetes mellitus uncontrolled, Type 2 diabetes mellitus well controlled, Diabetes adult-adult onset, NIDDM.; Inclusion ICD-9 codes: 250.21, 250.23, 250.11, 250.13, 250.61, 250.63, 250.51, 250.53, 250.31, 250.33, 250.81, 250.83, 250.71, 250.73, 250.41, 250.43, 250.91, 250.93, 250.01, 250.03, 250.20, 250.22, 250.10, 250.12, 250.60, 250.62, 250.50, 250.52, 250.30, 250.32, 250.80, 250.82, 250.70, 250.72, 250.40, 250.42, 250.90, 250.92, 250.00, 250.02; Exclusion problem list terms: negative, neg, r/o, risk, rule out, no, consider diabetes, borderline, gestational, maternal, pregnancy, glucose impai, impaired glucose, insipidus, pre diabetes, prediab, family history, PCOS, Polycystic Ovary Syndrome | Median = 13.9 years | 347 individuals, 42.32 % Male samples |
Mean = 60.4 years | African unspecified | — | MGBB | — |
| PSS011669 | Inclusion: MGH encounter AND ICD-9 code for diabetes AND Problem list term for diabetes OR HbA1C >6.5 in prior 3 years Exclusion: Problem list term not associated with diabetes; Inclusion problem list terms: DM, Diabetes Mellitus, Diabetic Nephropathy, Diabetic Neuropathy, Diabetic Retinopathy, Diabetic foot care, Diabetic foot infection, Diabetes Mellitus without complication, Insulin dependent diabetes mellitus, Insulin dependent diabetes without complications, Type 1, Diabetes mellitus I, DM type I, Juvenile, DM type i, Type I DM, Diabetes Mellitus type 1, Juvenile onset diabetes mellitus, Type 1 diabetes mellitus uncontrolled, Type 1 diabetes mellitus well controlled, DM1, Adult onset, AODM, Type 2, DM type ii, Diabetes mellitus ii, DMii, Type 2 DM, Type ii DM, Diabetes mellitus type 2, noninsulin dependent diabetes mellitus, Type 2 diabetes mellitus uncontrolled, Type 2 diabetes mellitus well controlled, Diabetes adult-adult onset, NIDDM.; Inclusion ICD-9 codes: 250.21, 250.23, 250.11, 250.13, 250.61, 250.63, 250.51, 250.53, 250.31, 250.33, 250.81, 250.83, 250.71, 250.73, 250.41, 250.43, 250.91, 250.93, 250.01, 250.03, 250.20, 250.22, 250.10, 250.12, 250.60, 250.62, 250.50, 250.52, 250.30, 250.32, 250.80, 250.82, 250.70, 250.72, 250.40, 250.42, 250.90, 250.92, 250.00, 250.02; Exclusion problem list terms: negative, neg, r/o, risk, rule out, no, consider diabetes, borderline, gestational, maternal, pregnancy, glucose impai, impaired glucose, insipidus, pre diabetes, prediab, family history, PCOS, Polycystic Ovary Syndrome | Median = 13.9 years | 183 individuals, 42.32 % Male samples |
Mean = 60.4 years | East Asian | — | MGBB | — |
| PSS011669 | Inclusion: MGH encounter AND ICD-9 code for diabetes AND Problem list term for diabetes OR HbA1C >6.5 in prior 3 years Exclusion: Problem list term not associated with diabetes; Inclusion problem list terms: DM, Diabetes Mellitus, Diabetic Nephropathy, Diabetic Neuropathy, Diabetic Retinopathy, Diabetic foot care, Diabetic foot infection, Diabetes Mellitus without complication, Insulin dependent diabetes mellitus, Insulin dependent diabetes without complications, Type 1, Diabetes mellitus I, DM type I, Juvenile, DM type i, Type I DM, Diabetes Mellitus type 1, Juvenile onset diabetes mellitus, Type 1 diabetes mellitus uncontrolled, Type 1 diabetes mellitus well controlled, DM1, Adult onset, AODM, Type 2, DM type ii, Diabetes mellitus ii, DMii, Type 2 DM, Type ii DM, Diabetes mellitus type 2, noninsulin dependent diabetes mellitus, Type 2 diabetes mellitus uncontrolled, Type 2 diabetes mellitus well controlled, Diabetes adult-adult onset, NIDDM.; Inclusion ICD-9 codes: 250.21, 250.23, 250.11, 250.13, 250.61, 250.63, 250.51, 250.53, 250.31, 250.33, 250.81, 250.83, 250.71, 250.73, 250.41, 250.43, 250.91, 250.93, 250.01, 250.03, 250.20, 250.22, 250.10, 250.12, 250.60, 250.62, 250.50, 250.52, 250.30, 250.32, 250.80, 250.82, 250.70, 250.72, 250.40, 250.42, 250.90, 250.92, 250.00, 250.02; Exclusion problem list terms: negative, neg, r/o, risk, rule out, no, consider diabetes, borderline, gestational, maternal, pregnancy, glucose impai, impaired glucose, insipidus, pre diabetes, prediab, family history, PCOS, Polycystic Ovary Syndrome | Median = 13.9 years | 82 individuals, 42.32 % Male samples |
Mean = 60.4 years | South Asian | — | MGBB | — |
| PSS011669 | Inclusion: MGH encounter AND ICD-9 code for diabetes AND Problem list term for diabetes OR HbA1C >6.5 in prior 3 years Exclusion: Problem list term not associated with diabetes; Inclusion problem list terms: DM, Diabetes Mellitus, Diabetic Nephropathy, Diabetic Neuropathy, Diabetic Retinopathy, Diabetic foot care, Diabetic foot infection, Diabetes Mellitus without complication, Insulin dependent diabetes mellitus, Insulin dependent diabetes without complications, Type 1, Diabetes mellitus I, DM type I, Juvenile, DM type i, Type I DM, Diabetes Mellitus type 1, Juvenile onset diabetes mellitus, Type 1 diabetes mellitus uncontrolled, Type 1 diabetes mellitus well controlled, DM1, Adult onset, AODM, Type 2, DM type ii, Diabetes mellitus ii, DMii, Type 2 DM, Type ii DM, Diabetes mellitus type 2, noninsulin dependent diabetes mellitus, Type 2 diabetes mellitus uncontrolled, Type 2 diabetes mellitus well controlled, Diabetes adult-adult onset, NIDDM.; Inclusion ICD-9 codes: 250.21, 250.23, 250.11, 250.13, 250.61, 250.63, 250.51, 250.53, 250.31, 250.33, 250.81, 250.83, 250.71, 250.73, 250.41, 250.43, 250.91, 250.93, 250.01, 250.03, 250.20, 250.22, 250.10, 250.12, 250.60, 250.62, 250.50, 250.52, 250.30, 250.32, 250.80, 250.82, 250.70, 250.72, 250.40, 250.42, 250.90, 250.92, 250.00, 250.02; Exclusion problem list terms: negative, neg, r/o, risk, rule out, no, consider diabetes, borderline, gestational, maternal, pregnancy, glucose impai, impaired glucose, insipidus, pre diabetes, prediab, family history, PCOS, Polycystic Ovary Syndrome | Median = 13.9 years | 83 individuals, 42.32 % Male samples |
Mean = 60.4 years | Greater Middle Eastern (Middle Eastern, North African or Persian) | — | MGBB | — |
| PSS011669 | Inclusion: MGH encounter AND ICD-9 code for diabetes AND Problem list term for diabetes OR HbA1C >6.5 in prior 3 years Exclusion: Problem list term not associated with diabetes; Inclusion problem list terms: DM, Diabetes Mellitus, Diabetic Nephropathy, Diabetic Neuropathy, Diabetic Retinopathy, Diabetic foot care, Diabetic foot infection, Diabetes Mellitus without complication, Insulin dependent diabetes mellitus, Insulin dependent diabetes without complications, Type 1, Diabetes mellitus I, DM type I, Juvenile, DM type i, Type I DM, Diabetes Mellitus type 1, Juvenile onset diabetes mellitus, Type 1 diabetes mellitus uncontrolled, Type 1 diabetes mellitus well controlled, DM1, Adult onset, AODM, Type 2, DM type ii, Diabetes mellitus ii, DMii, Type 2 DM, Type ii DM, Diabetes mellitus type 2, noninsulin dependent diabetes mellitus, Type 2 diabetes mellitus uncontrolled, Type 2 diabetes mellitus well controlled, Diabetes adult-adult onset, NIDDM.; Inclusion ICD-9 codes: 250.21, 250.23, 250.11, 250.13, 250.61, 250.63, 250.51, 250.53, 250.31, 250.33, 250.81, 250.83, 250.71, 250.73, 250.41, 250.43, 250.91, 250.93, 250.01, 250.03, 250.20, 250.22, 250.10, 250.12, 250.60, 250.62, 250.50, 250.52, 250.30, 250.32, 250.80, 250.82, 250.70, 250.72, 250.40, 250.42, 250.90, 250.92, 250.00, 250.02; Exclusion problem list terms: negative, neg, r/o, risk, rule out, no, consider diabetes, borderline, gestational, maternal, pregnancy, glucose impai, impaired glucose, insipidus, pre diabetes, prediab, family history, PCOS, Polycystic Ovary Syndrome | Median = 13.9 years | 154 individuals, 42.32 % Male samples |
Mean = 60.4 years | Not reported | — | MGBB | — |
| PSS013062 | 411.81, 414.0, 414.1, 414.2, 414.3, 414.4, 996.03, V45.81, V45.82,I24.0, I25.1, I25.3, I25.4, I25.700, I25.701, I25.708, I25.709, I25.710, I25.711, I25.718, I25.719, I25.720, I25.721, I25.728, I25.729, I25.730, I25.731, I25.738, I25.739, I25.790, I25.791, I25.798, I25.799, I25.810, I25.82, I25.83, I25.84, Z95.1, Z95.5, Z98.6 | — | [ ,
44.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007671 | An atrial tachyarrhythmia characterised by rapid (usually faster than 300 bpm), irregular and uncoordinated atrial impulse generation, usually manifesting on ECG with indistinct P-waves and an irregularly irregular ventricular response. | — | [
|
— | European | British | UKB | — |
| PSS007672 | Disorder of the atrioventricular conduction system in which there is failure of all atrial impulses to propagate to the ventricle | — | [
|
— | European | British | UKB | — |
| PSS007673 | Pathogenicity of rare variants in SCN5A identified in included BrS cases was centrally assessed using the American College of Medical Genetics and Genomics and Association of Molecular Pathology (ACMG/AMP) guidelines, using an adapted version of CardioClassifier incorporating a quantitative approach based on case-control analyses, as performed previously in hypertrophic cardiomyopathy genes, as well as a curated compendium of functional data. | — | [
|
— | European | Dutch, Belgian, German, British, Turkish, Italian, Spanish, Danish, French, Irish | NR | These samples overlap with the cases used in the score development |
| PSS007674 | A type 1 Brugada Syndrome ECG was defined as a coved type ST elevation at baseline (spontaneous) or after a drug challenge test, in one or more leads in the right precordial leads V1 and/or V2 in the standard position (4th intercostal space) or in high positions (2nd or 3rd intercostal spaces). | — | [
|
— | European | Dutch, Belgian, German, British, Turkish, Italian, Spanish, Danish, French, Irish | NR | These samples overlap with the cases used in the score development |
| PSS007675 | Disorder of the atrioventricular conduction system in which there is failure of all atrial impulses to propagate to the ventricle or Any of a number of possible arrhythmias originating from at or above the level of bundle of His in which the heart beats slower than the age-dependent lower limits of normal. | — | [
|
— | European | British | UKB | — |
| PSS007676 | Electrocardiogram PQ interval | — | 11,942 individuals | — | European | British | UKB | — |
| PSS007677 | Electrocardiogram P-wave duration | — | 11,566 individuals | — | European | British | UKB | — |
| PSS007678 | Electrocardiogram QRS duration | — | 11,877 individuals | — | European | British | UKB | — |
| PSS007679 | Electrocardiogram QT interval | — | 11,893 individuals | — | European | British | UKB | — |
| PSS007680 | associated with episodes of atrial tachycardia | — | [
|
— | European | British | UKB | — |
| PSS007681 | Coronary heart disease was defined as Myocardial infarction | Coronary angioplasty | Coronary artery bypass grafting. ICD 8/9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2019, whichever came first. | Median = 15.3 years IQR = [7.8, 22.6] years |
[ ,
43.8 % Male samples |
Mean (Age At Baseline) = 53.2 years Sd = 17.4 years |
European (Finnish) |
— | FinnGen | — |
| PSS007682 | Coronary heart disease was defined as Myocardial infarction | Coronary angioplasty | Coronary artery bypass grafting. ICD 8/9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2019, whichever came first. | — | [ ,
42.2 % Male samples |
Mean (Age At Baseline) = 52.2 years Sd = 17.3 years |
European (Finnish) |
— | FinnGen | — |
| PSS007683 | Coronary heart disease was defined as Myocardial infarction | Coronary angioplasty | Coronary artery bypass grafting. ICD 8/9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2019, whichever came first. | — | [ ,
43.8 % Male samples |
Mean (Age At Baseline) = 53.2 years Sd = 17.4 years |
European (Finnish) |
— | FinnGen | — |
| PSS007687 | Coronary heart disease was defined as Myocardial infarction | Coronary angioplasty | Coronary artery bypass grafting. ICD 9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the censoring date of hospital inpatient data (UK Biobank; English hospital inpatient records up to May 2020, Scottish up to November 2016, Welsh up to March 2016), whichever came first. | Median = 10.7 years IQR = [8.6, 11.6] years |
[ ,
46.3 % Male samples |
Mean (Age At Baseline) = 57.4 years Sd = 8.0 years |
European (British) |
UK Biobank participants with non-British ancestry were excluded based on genetically inferred ancestry. | UKB | — |
| PSS007688 | Coronary heart disease was defined as Myocardial infarction | Coronary angioplasty | Coronary artery bypass grafting. ICD 9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the censoring date of hospital inpatient data (UK Biobank; English hospital inpatient records up to May 2020, Scottish up to November 2016, Welsh up to March 2016), whichever came first. | — | [ ,
45.1 % Male samples |
Mean (Age At Baseline) = 57.2 years Sd = 8.0 years |
European (British) |
UK Biobank participants with non-British ancestry were excluded based on genetically inferred ancestry. | UKB | — |
| PSS007689 | Coronary heart disease was defined as Myocardial infarction | Coronary angioplasty | Coronary artery bypass grafting. ICD 9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the censoring date of hospital inpatient data (UK Biobank; English hospital inpatient records up to May 2020, Scottish up to November 2016, Welsh up to March 2016), whichever came first. | — | [ ,
46.3 % Male samples |
Mean (Age At Baseline) = 57.4 years Sd = 8.0 years |
European (British) |
UK Biobank participants with non-British ancestry were excluded based on genetically inferred ancestry. | UKB | — |
| PSS011679 | Cases were individuals who had experienced mycoardial injury after non-cardiac surgery (MINS). MINS was defined as a new troponin elevation (≥ 0.1 ng/mL, institutional laboratory's upper threshold for normal) occurring within the first 30 days after surgery. If a patient underwent a subsequent surgery within the 30-day postoperative window, the later procedure was presumed to have greater influence on the subsequent postoperative course, therefore, the post-operative window for the initial procedure was censored at the start of a subsequent procedure. Patients with a troponin elevation in the two years before surgery were excluded from analysis for that particular surgery. If a patient had a postoperative troponin elevation, all subsequent surgeries were excluded from evaluation. | — | [
|
— | European | — | MGI | — |
| PSS011679 | Cases were individuals who had experienced mycoardial injury after non-cardiac surgery (MINS). MINS was defined as a new troponin elevation (≥ 0.1 ng/mL, institutional laboratory's upper threshold for normal) occurring within the first 30 days after surgery. If a patient underwent a subsequent surgery within the 30-day postoperative window, the later procedure was presumed to have greater influence on the subsequent postoperative course, therefore, the post-operative window for the initial procedure was censored at the start of a subsequent procedure. Patients with a troponin elevation in the two years before surgery were excluded from analysis for that particular surgery. If a patient had a postoperative troponin elevation, all subsequent surgeries were excluded from evaluation. | — | [
|
— | African unspecified | — | MGI | — |
| PSS011679 | Cases were individuals who had experienced mycoardial injury after non-cardiac surgery (MINS). MINS was defined as a new troponin elevation (≥ 0.1 ng/mL, institutional laboratory's upper threshold for normal) occurring within the first 30 days after surgery. If a patient underwent a subsequent surgery within the 30-day postoperative window, the later procedure was presumed to have greater influence on the subsequent postoperative course, therefore, the post-operative window for the initial procedure was censored at the start of a subsequent procedure. Patients with a troponin elevation in the two years before surgery were excluded from analysis for that particular surgery. If a patient had a postoperative troponin elevation, all subsequent surgeries were excluded from evaluation. | — | [
|
— | Asian unspecified, Oceanian | — | MGI | — |
| PSS011679 | Cases were individuals who had experienced mycoardial injury after non-cardiac surgery (MINS). MINS was defined as a new troponin elevation (≥ 0.1 ng/mL, institutional laboratory's upper threshold for normal) occurring within the first 30 days after surgery. If a patient underwent a subsequent surgery within the 30-day postoperative window, the later procedure was presumed to have greater influence on the subsequent postoperative course, therefore, the post-operative window for the initial procedure was censored at the start of a subsequent procedure. Patients with a troponin elevation in the two years before surgery were excluded from analysis for that particular surgery. If a patient had a postoperative troponin elevation, all subsequent surgeries were excluded from evaluation. | — | [
|
— | Native American | — | MGI | — |
| PSS011679 | Cases were individuals who had experienced mycoardial injury after non-cardiac surgery (MINS). MINS was defined as a new troponin elevation (≥ 0.1 ng/mL, institutional laboratory's upper threshold for normal) occurring within the first 30 days after surgery. If a patient underwent a subsequent surgery within the 30-day postoperative window, the later procedure was presumed to have greater influence on the subsequent postoperative course, therefore, the post-operative window for the initial procedure was censored at the start of a subsequent procedure. Patients with a troponin elevation in the two years before surgery were excluded from analysis for that particular surgery. If a patient had a postoperative troponin elevation, all subsequent surgeries were excluded from evaluation. | — | [
|
— | Not reported | — | MGI | — |
| PSS011680 | At baseline, all individuals were free from coronary heart disease (CHD). Cases included individuals who were hospitalised due to CHD or suffered a fatal CHD event. CHD events were defined for non-fatal cases as the International Classification of Diseases ninth revision (ICD-9) codes 410 and 4110 (years 1992-1995) and ICD-10 codes I200, I21 or I22 (1996-2015) and Nordic Medico-Statistical Committee codes for coronary artery bypass graft or percutaneous coronary intervention in the hospital discharge register, and for fatal cases as ICD-9 codes 410-414 and 798 (not 7980A) and ICD-10 codes I20-25, I46, R96 and R98 in the causes of death register. | Mean = 13.8 years | [ ,
46.74 % Male samples |
Mean = 48.0 years | European (Finnish) |
— | FINRISK | — |
| PSS011681 | The primary outcome was a first-onset cardiovascular disease event, defined as the composite of CHD (i.e., myocardial infarction or fatal CHD) or any stroke. Secondary outcomes included each of CHD and stroke separately, and a combination of CHD, stroke, and cardiac revascularisation procedures (i.e., percutaneous transluminal cor- onary angioplasty [PTCA] and coronary artery bypass grafting [CABG]). 3333 Cases are CHD events and 2347 are stroke events | Median = 8.1 years | [ ,
43.01 % Male samples |
Mean = 56.0 years Sd = 8.0 years |
European | — | UKB | — |
| PSS013067 | 414,I25 | — | [ ,
45.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011682 | All individuals had multifocal FMD. Cases show those with spontaneous coronary artery dissection. | — | [
|
— | Not reported | — | CCGB | Cases from Cleveland Clinic FMD Biorepository |
| PSS011683 | An individual was classified as a case if he or she had ≥1 admission to a VA hospital with discharge diagnosis of acute myocardial infarction (AMI) or ≥1 procedure code for revascularization of the coronary arteries or ≥2 ICD codes for CAD (410-414) on ≥2 dates. | — | [
|
— | European | — | MVP | — |
| PSS011684 | Cases are individuals with evidence of hospitilisation for myocardial infarction. | — | [
|
— | European | — | MVP | — |
| PSS011685 | MI events were defined pre- enrollment by self-reported medical history and post-enrollment by hospital epi- sode statistics using ICD, Version 10 diagnosis codes (I21, I22, I23, or I24). Events were censored on the date of loss to follow-up, death, or if individuals remained event free up to March 31, 2017. | — | [ ,
45.86 % Male samples |
— | European | — | UKB | — |
| PSS011689 | — | Mean = 14.2 years | [ ,
42.3 % Male samples |
Mean = 63.0 years Sd = 5.7 years |
European | — | ARIC | — |
| PSS011690 | — | Mean = 18.5 years | [ ,
44.2 % Male samples |
Mean = 56.7 years Sd = 9.2 years |
European | — | FOS | — |
| PSS013072 | 410, 411, 412, 413, 414, 429.7, 996.03, V45.81, V45.82,I20, I21, I22, I23.0, I23.1, I23.2, I23.3, I23.6, I23.7, I23.8, I24.0, I24.1, I24.8, I24.9, I25, I51.0, I51.3, Z95.1, Z95.5, Z98.6 | — | [ ,
45.93 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011698 | — | — | 1,567 individuals | — | European | — | EAST-AFNET4 | — |
| PSS011699 | — | — | 407,311 individuals | — | European | — | UKB | — |
| PSS011700 | — | Median = 11.9 years | [
|
— | European | — | UKB | — |
| PSS011700 | — | Median = 11.9 years | [
|
— | Not reported | — | UKB | — |
| PSS011700 | — | Median = 11.9 years | [
|
— | Asian unspecified | — | UKB | — |
| PSS011700 | — | Median = 11.9 years | [
|
— | African unspecified | — | UKB | — |
| PSS009585 | Incident stroke as a confirmed diagnosis of first-ever fatal or nonfatal stroke event during follow-up (I60-I69) | — | 41,006 individuals, 43.1 % Male samples |
Mean = 51.9 years | East Asian | — | NR | — |
| PSS011704 | — | — | [
|
— | European | — | UKB | — |
| PSS009589 | — | Mean = 13.0 years | [ ,
42.5 % Male samples |
Mean = 52.3 years Sd = 10.6 years |
East Asian | — | CIMIC, ChinaMUCA-1998, InterASIA | — |
| PSS009590 | individuals with type 2 diabetes. Events consist of 794 CV deaths (15.4%), 274 non-fatal MI (5.3%) and 151 non-fatal stroke (2.9%) | Median = 9.8 years | [ ,
56.1 % Male samples |
Mean = 65.2 years | European, NR | — | GoDARTS | — |
| PSS007696 | — | — | [
|
— | European | — | CanPath | — |
| PSS012676 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007700 | — | — | [
|
— | African unspecified | Africa or admixed-ancestry diaspora | UKB | — |
| PSS013084 | 429,B33.2, I23.4, I23.5, I51.1, I51.2, I51.5, I51.8, I51.9, I52 | — | [ ,
44.23 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007705 | — | — | [
|
— | Asian unspecified | Central and South Asian | UKB | — |
| PSS007707 | — | — | [
|
— | European | — | UKB | — |
| PSS007713 | — | — | [
|
— | European | — | UKB | — |
| PSS007716 | — | — | [
|
— | European | — | UKB | — |
| PSS007719 | — | — | [
|
— | European | — | UKB | — |
| PSS011720 | Cases are individuals that were hospitilized at least once for any cause. | Mean = 17.8 years Sd = 4.4 years |
[ ,
38.0 % Male samples |
Mean = 58.0 years Sd = 7.7 years |
Not reported | — | MDC | — |
| PSS011721 | Cases are individuals that were hospitilized at least once for a CVD event. The causes of hospitilization were classified according to ICD code as the main diagnosis at discharge. The most common causes of CVD hospitalizations were ischeamic heart disease (33%), stroke (23%), arterial fibrillation (15%) and congestive heart failure (3%) as estimated from the causes of the first hospitalization event | Mean = 17.8 years Sd = 4.4 years |
23,594 individuals, 38.0 % Male samples |
Mean = 58.0 years Sd = 7.7 years |
Not reported | — | MDC | — |
| PSS011722 | — | — | 23,594 individuals, 38.0 % Male samples |
Mean = 58.0 years Sd = 7.7 years |
Not reported | — | MDC | — |
| PSS011724 | — | — | [
|
— | European | — | UKB | — |
| PSS013090 | 427.0, 427.1, 427.2,I47, I49.2 | — | [ ,
45.96 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011727 | A participant was defined as a CAD case if he/she had at least one occurrence of International Classification of Diseases, 10th edition (ICD-10) codes I21-I25 (covering ischemic heart diseases) or at least one occurrence of the following codes in Office of Population Censuses and Surveys Classification of Interventions and Procedures, version 4 (OPCS-4): K40- K46, K49, K50 or K75, which include replacement, transluminal balloon angioplasty, and other therapeutic transluminal operations on coronary artery, and percutaneous transluminal balloon angioplasty and insertion of stents. Death because of CAD was defined as an occurrence of any of the ICD-10 codes stated above as the primary cause of death. Primary incident CAD events were either captured on the earliest date of CAD event/CAD death after enrollment, or censored at the end of HES-based follow-up or at time of competing death, whichever occurred first. Those who have had CAD diagnosis before enrollment were excluded from the incident CAD analysis. 10358 CAD cases were prevalent and 9847 were incident. | Median = [0.0, 8.4] years | [ ,
46.1 % Male samples |
Mean = 57.4 years Sd = 8.0 years |
European | — | UKB | — |
| PSS011728 | A participant was defined as a CAD case if he/she had at least one occurrence of International Classification of Diseases, 10th edition (ICD-10) codes I21-I25 (covering ischemic heart diseases) or at least one occurrence of the following codes in Office of Population Censuses and Surveys Classification of Interventions and Procedures, version 4 (OPCS-4): K40- K46, K49, K50 or K75, which include replacement, transluminal balloon angioplasty, and other therapeutic transluminal operations on coronary artery, and percutaneous transluminal balloon angioplasty and insertion of stents. Death because of CAD was defined as an occurrence of any of the ICD-10 codes stated above as the primary cause of death. Primary incident CAD events were either captured on the earliest date of CAD event/CAD death after enrollment, or censored at the end of HES-based follow-up or at time of competing death, whichever occurred first. Those who have had CAD diagnosis before enrollment were excluded from the incident CAD analysis. 7976 CAD cases were prevalent and 6774 were incident. | Median = [0.0, 8.4] years | [ ,
100.0 % Male samples |
Mean = 57.6 years Sd = 8.1 years |
European | — | UKB | — |
| PSS011729 | A participant was defined as a CAD case if he/she had at least one occurrence of International Classification of Diseases, 10th edition (ICD-10) codes I21-I25 (covering ischemic heart diseases) or at least one occurrence of the following codes in Office of Population Censuses and Surveys Classification of Interventions and Procedures, version 4 (OPCS-4): K40- K46, K49, K50 or K75, which include replacement, transluminal balloon angioplasty, and other therapeutic transluminal operations on coronary artery, and percutaneous transluminal balloon angioplasty and insertion of stents. Death because of CAD was defined as an occurrence of any of the ICD-10 codes stated above as the primary cause of death. Primary incident CAD events were either captured on the earliest date of CAD event/CAD death after enrollment, or censored at the end of HES-based follow-up or at time of competing death, whichever occurred first. Those who have had CAD diagnosis before enrollment were excluded from the incident CAD analysis. 2382 CAD cases were prevalent and 3073 were incident. | Median = [0.0, 8.4] years | [ ,
0.0 % Male samples |
Mean = 57.2 years Sd = 7.9 years |
European | — | UKB | — |
| PSS011730 | A participant was defined as a CAD case if he/she had at least one occurrence of International Classification of Diseases, 10th edition (ICD-10) codes I21-I25 (covering ischemic heart diseases) or at least one occurrence of the following codes in Office of Population Censuses and Surveys Classification of Interventions and Procedures, version 4 (OPCS-4): K40- K46, K49, K50 or K75, which include replacement, transluminal balloon angioplasty, and other therapeutic transluminal operations on coronary artery, and percutaneous transluminal balloon angioplasty and insertion of stents. Death because of CAD was defined as an occurrence of any of the ICD-10 codes stated above as the primary cause of death. Primary incident CAD events were either captured on the earliest date of CAD event/CAD death after enrollment, or censored at the end of HES-based follow-up or at time of competing death, whichever occurred first. Those who have had CAD diagnosis before enrollment were excluded from the incident CAD analysis. 10358 CAD cases were prevalent and 9847 were incident. | Median = [0.0, 8.4] years | [ ,
46.1 % Male samples |
Mean = 57.4 years Sd = 8.0 years |
European | — | UKB | — |
| PSS011731 | A participant was defined as a CAD case if he/she had at least one occurrence of International Classification of Diseases, 10th edition (ICD-10) codes I21-I25 (covering ischemic heart diseases) or at least one occurrence of the following codes in Office of Population Censuses and Surveys Classification of Interventions and Procedures, version 4 (OPCS-4): K40- K46, K49, K50 or K75, which include replacement, transluminal balloon angioplasty, and other therapeutic transluminal operations on coronary artery, and percutaneous transluminal balloon angioplasty and insertion of stents. Death because of CAD was defined as an occurrence of any of the ICD-10 codes stated above as the primary cause of death. Primary incident CAD events were either captured on the earliest date of CAD event/CAD death after enrollment, or censored at the end of HES-based follow-up or at time of competing death, whichever occurred first. Those who have had CAD diagnosis before enrollment were excluded from the incident CAD analysis. 7976 CAD cases were prevalent and 6774 were incident. | Median = [0.0, 8.4] years | [ ,
100.0 % Male samples |
Mean = 57.6 years Sd = 8.1 years |
European | — | UKB | — |
| PSS011732 | A participant was defined as a CAD case if he/she had at least one occurrence of International Classification of Diseases, 10th edition (ICD-10) codes I21-I25 (covering ischemic heart diseases) or at least one occurrence of the following codes in Office of Population Censuses and Surveys Classification of Interventions and Procedures, version 4 (OPCS-4): K40- K46, K49, K50 or K75, which include replacement, transluminal balloon angioplasty, and other therapeutic transluminal operations on coronary artery, and percutaneous transluminal balloon angioplasty and insertion of stents. Death because of CAD was defined as an occurrence of any of the ICD-10 codes stated above as the primary cause of death. Primary incident CAD events were either captured on the earliest date of CAD event/CAD death after enrollment, or censored at the end of HES-based follow-up or at time of competing death, whichever occurred first. Those who have had CAD diagnosis before enrollment were excluded from the incident CAD analysis. 2382 CAD cases were prevalent and 3073 were incident. | Median = [0.0, 8.4] years | [ ,
0.0 % Male samples |
Mean = 57.2 years Sd = 7.9 years |
European | — | UKB | — |
| PSS007739 | — | — | 2,385 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS009620 | MVP was defined according to contemporary echocardiographic society guidelines as leaflet displacement ≥2 mm beyond the mitral annulus in a long-axis view at end-systole involving one or both MV leaflets when raw imaging data were available for review or via electronic medical record search for MVP diagnosis using ICD and procedure codes or natural language processing | — | [
|
— | European | — | UKB | — |
| PSS013096 | 427.31,I48.0, I48.2, I48.91 | — | [ ,
46.47 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012542 | 228,D18 | — | [ ,
46.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012543 | 228,D18 | — | [ ,
46.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS003775 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS003776 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS003777 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS003778 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS003779 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS012545 | 228,D18 | — | [ ,
46.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007757 | — | — | 2,484 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007758 | — | — | 2,396 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007759 | — | — | 2,457 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007760 | — | — | 2,381 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS000820 | — | — | 87,413 individuals | — | European | — | UKB | — |
| PSS000821 | ICD-10 I50, I11.0, I13.0 | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS000822 | — | — | 87,413 individuals | — | European | — | UKB | — |
| PSS007761 | — | — | 2,472 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007765 | — | — | 2,444 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS003790 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS000826 | — | — | 87,413 individuals | — | European | — | UKB | — |
| PSS000827 | ICD-10 I21|I22 | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS003791 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS003794 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS003795 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS003792 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS003796 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS003797 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS003799 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS003798 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS003793 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS000837 | Incident CHD cases were defined as having incident myocardial infarction (MI), fatal coronary event, or silent infarction or having undergone a revasclarization procedure. | Median = 15.5 years | [ ,
43.6 % Male samples |
Mean = 62.9 years | European | — | ARIC | — |
| PSS000838 | Incident CHD cases were defined as MI, resuscitated cardiac arrest, definite or probable angina if followed by a revascularization, and CHD dead occuring by visit 5. | Median = 14.2 years | [ ,
47.8 % Male samples |
Mean = 61.8 years | European | — | MESA | — |
| PSS000839 | Incident CHD cases were defined as having incident myocardial infarction (MI), fatal coronary event, or silent infarction or having undergone a revasclarization procedure. Prevalent CHD cases were participants with a reported history of MI, heart or arterial surgery, coronary artery bypass graft surgery, or angioplasty; or evidence of having had an MI based on electrocardiogram taken at their visit 1 examination. | — | [ ,
43.6 % Male samples |
Mean = 62.9 years | European | — | ARIC | — |
| PSS000850 | All individuals had inflammatory bowel disease, defined on the basis of clinical symptoms as well as standard endoscopic, radiographic and histologic findings. Cases are individuals with a thromboembolic disease (TED) event. Disease activity at the time of TED for Chron's disease was measured by the Harvey-Bradshaw Index and colonoscopy report at the time of clotting event (when available). Patients were considered to have active disease if they had Harvey-Bradshaw Index scores !5 and/or endoscopy showed active disease, Disease activity at the time of TED for Ulcerative Colitis was evaluated by the full Mayo score. A full Mayo score >2 was considered as active disease. | — | [ ,
53.3 % Male samples |
— | European | — | CSMC | — |
| PSS000217 | Phenotypic information was self-reported by the individual through an online, interactive health history tool | — | [ ,
17.1 % Male samples |
— | European | — | CG | Samples are individuals whose healthcare provider had ordered a Color Genomics multi-gene panel test |
| PSS000219 | Phenotypic information was self-reported by the individual through an online, interactive health history tool | — | [ ,
17.1 % Male samples |
— | European | — | CG | Samples are individuals whose healthcare provider had ordered a Color Genomics multi-gene panel test |
| PSS009641 | A stroke event was defined as hospitalization due to stroke which was self-reported in a structured and standardized inter- view performed by certified and supervised personnel. | — | 3,071 individuals, 49.0 % Male samples |
Mean = 57.4 years Sd = 12.9 years |
European | — | KORA | — |
| PSS011752 | — | Median = 11.6 years | 39,164 individuals, 42.4 % Male samples |
Mean = 53.9 years Sd = 10.5 years |
East Asian (Chinese) |
— | CIMIC, ChinaMUCA-1998, InterASIA | — |
| PSS011755 | — | — | 77,500 individuals, 43.2 % Male samples |
Mean = 56.3 years Sd = 7.7 years |
European (British) |
— | UKB | — |
| PSS000227 | — | — | [
|
— | Asian unspecified | — | MESA, VIRGO | Cases are from VIRGO, controls are from MESA |
| PSS000228 | — | — | [
|
— | African American or Afro-Caribbean | — | MESA, VIRGO | Cases are from VIRGO, controls are from MESA |
| PSS000229 | — | — | [
|
— | Hispanic or Latin American | — | MESA, VIRGO | Cases are from VIRGO, controls are from MESA |
| PSS000230 | — | — | [
|
— | European | — | MESA, VIRGO | Cases are from VIRGO, controls are from MESA |
| PSS009709 | — | — | 43,505 individuals | — | European | Non-British European | UKB | — |
| PSS009710 | — | — | 8,098 individuals | — | South Asian | — | UKB | — |
| PSS011758 | — | Median = 11.7 years | 34,111 individuals, 41.8 % Male samples |
Mean = 52.3 years Sd = 10.5 years |
East Asian (Chinese) |
— | CIMIC, ChinaMUCA-1998, InterASIA | — |
| PSS013113 | 427, 785.0, 785.1, V12.53,I46, I47, I48, I49.0, I49.1, I49.2, I49.3, I49.4, I49.5, I49.8, I49.9, R00.0, R00.1, R00.2, Z86.74 | — | [ ,
46.01 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011762 | — | — | 8,417 individuals | — | European | — | BBofA | — |
| PSS009654 | — | — | [ ,
61.0 % Male samples |
— | European | — | NR | — |
| PSS013114 | 427, 785.0, 785.1, V12.53,I46, I47, I48, I49.0, I49.1, I49.2, I49.3, I49.4, I49.5, I49.8, I49.9, R00.0, R00.1, R00.2, Z86.74 | — | [ ,
46.01 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS000867 | CALIBER rule-based phenotyping algorithms (https://www.caliberresearch.org/portal). ICD-10: I48 | Median = 6.9 years | [ ,
51.0 % Male samples |
Median = 44.0 years IQR = [30.5, 54.7] years |
European | — | INTERVAL | — |
| PSS000868 | CALIBER rule-based phenotyping algorithms (https://www.caliberresearch.org/portal). ICD-10: I21-I23, I24.1, I25.2 | Median = 6.9 years | [ ,
51.0 % Male samples |
Median = 44.0 years IQR = [30.5, 54.7] years |
European | — | INTERVAL | — |
| PSS013117 | 431,I61 | — | [ ,
44.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013118 | 431,I61 | — | [ ,
44.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013119 | 431,I61 | — | [ ,
44.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013120 | 431,I61 | — | [ ,
44.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013121 | 431,I61 | — | [ ,
44.64 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012671 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012672 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012673 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012674 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012675 | 362.0,E08.3, E09.3, E10.3, E11.3, E13.31, E13.32, E13.33, E13.34, E13.35 | — | [ ,
46.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011772 | Including death resulting from ischemic heart disease [ICD10: I20-I25], nonfatal myocardial infarction [ICD10: I21-I23], and coronary revascularization | Median = 12.2 years | 72,149 individuals, 40.2 % Male samples |
Mean = 51.7 years Sd = 10.5 years |
East Asian (Chinese) |
— | CKB | — |
| PSS011773 | ICD10: I61 | Median = 12.2 years | 72,149 individuals, 40.2 % Male samples |
Mean = 51.7 years Sd = 10.5 years |
East Asian (Chinese) |
— | CKB | — |
| PSS000898 | Coronary artery disease was defined as myocardial infarction and/or history of coronary revascularization. | — | [
|
— | African unspecified | — | BioMe, MESA, PHB, UKB, VIRGO | — |
| PSS000899 | Coronary artery disease was defined as myocardial infarction and/or history of coronary revascularization. | — | [
|
— | East Asian | — | TaiChi, UKB | — |
| PSS000900 | Coronary artery disease was defined as myocardial infarction and/or history of coronary revascularization. | — | [
|
— | European | — | BioMe, MESA, PHB, UKB, VIRGO | — |
| PSS000901 | Coronary artery disease was defined as myocardial infarction and/or history of coronary revascularization. | — | [
|
— | Hispanic or Latin American | — | BioMe, MESA, PHB, VIRGO | — |
| PSS000902 | Coronary artery disease was defined as myocardial infarction and/or history of coronary revascularization. | — | [
|
— | South Asian | — | BRAVE, UKB | — |
| PSS003914 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS003915 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS003916 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS003917 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS003918 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS000905 | Intravenous ajmaline was administered at consecutive boluses of 10 mg/min. A 10-s ECG was recorded ∼1 min after each bolus using a GE Healthcare electrocardiograph. The test was stopped when the target dose of 1 mg/kg rounded up to the next 10 mg was reached, if ventricular arrhythmia occurred, or at the manifestation of a Type I BrS pattern, defined as an ST elevation >2 mm with a coved morphology in any lead among V1–V2 in the 2nd to 4th intercostal spaces.15 | — | 1,185 individuals | — | European | — | Amsterdam | — |
| PSS011775 | — | — | 4,412 individuals | — | South Asian | — | UKB | — |
| PSS011775 | — | — | 3,795 individuals | — | African unspecified | — | UKB | — |
| PSS011775 | — | — | 1,230 individuals | — | East Asian | — | UKB | — |
| PSS000908 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | African unspecified | — | GEL, RBH-CRB | — |
| PSS000908 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | Other admixed ancestry | Ad Mixed American | GEL, RBH-CRB | — |
| PSS000908 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | East Asian | — | GEL, RBH-CRB | — |
| PSS000908 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | European | — | GEL, RBH-CRB | — |
| PSS000908 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | South Asian | — | GEL, RBH-CRB | — |
| PSS000908 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | Not reported | — | GEL, RBH-CRB | — |
| PSS000909 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | African unspecified | — | GEL, RBH-CRB | — |
| PSS000909 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | Other admixed ancestry | Ad Mixed American | GEL, RBH-CRB | — |
| PSS000909 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | East Asian | — | GEL, RBH-CRB | — |
| PSS000909 | Cases were individuals with hypertrophic cardiomyopathy. In the individuals recruited from the Netherlands, this was identified using current diagnostic criteria(eft ventricular wall thickness ≥15mm or ≥13mm in presence of family history) | — | [
|
— | European | — | GEL, RBH-CRB | — |
| PSS000909 | Cases were individuals with hypertrophic Cardiomyopathy. | — | [
|
— | South Asian | — | GEL, RBH-CRB | — |
| PSS000909 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | Not reported | — | GEL, RBH-CRB | — |
| PSS000910 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | African unspecified | — | GEL, RBH-CRB | — |
| PSS000910 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | Other admixed ancestry | Ad Mixed American | GEL, RBH-CRB | — |
| PSS000910 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | East Asian | — | GEL, RBH-CRB | — |
| PSS000910 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | European | — | GEL, RBH-CRB | — |
| PSS000910 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | South Asian | — | GEL, RBH-CRB | — |
| PSS000910 | Cases were individuals with hypertrophic cardiomyopathy. | — | [
|
— | Not reported | — | GEL, RBH-CRB | — |
| PSS011781 | ICD10 I42.0; excluding antecedent acute coronary disease and/or revascularization | — | [
|
— | European, Not reported | Mostly European-American | AllofUs | — |
| PSS011782 | ICD10 I42.0; excluding antecedent acute coronary disease and/or revascularization | — | [
|
— | European, Not reported | — | UKB | Please note: UKB samples included in the first 45k MRI tranche were removed from this testing set, since the MTAG data includes GWAS data of cardiac MRI traits from the UKB. |
| PSS011780 | Clinical criteria + imaging | — | [
|
— | European (Dutch) |
— | AUMC_DCM | — |
| PSS013129 | 434.01, 434.11, 434.91,I63.0, I63.3, I63.4, I63.5, I63.6, I63.8, I63.9 | — | [ ,
45.27 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013130 | 434.01, 434.11, 434.91,I63.0, I63.3, I63.4, I63.5, I63.6, I63.8, I63.9 | — | [ ,
45.27 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011789 | — | — | [ ,
0.0 % Male samples |
— | European | — | GEOS | — |
| PSS013131 | 434.01, 434.11, 434.91,I63.0, I63.3, I63.4, I63.5, I63.6, I63.8, I63.9 | — | [ ,
45.27 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS003949 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS003950 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS003951 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS003952 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS003953 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS013132 | 434, 437.6,I63, I66, I67.6 | — | [ ,
45.55 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013133 | 434, 437.6,I63, I66, I67.6 | — | [ ,
45.55 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013134 | 434, 437.6,I63, I66, I67.6 | — | [ ,
45.55 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013135 | 434, 437.6,I63, I66, I67.6 | — | [ ,
45.55 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS010956 | — | — | [
|
— | European | — | HUNT | — |
| PSS013136 | 434, 437.6,I63, I66, I67.6 | — | [ ,
45.55 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007958 | — | — | 1,764 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS010960 | ICD 10: I21,I210,I211,I212,I213,I214,I219,I22,I220,I221,I228,I229,I23,I230,I231,I232,I233,I234,I235,I236,I238,I24,I240,I241,I248,I249,I252; ICD9: 410, 411, 412, 4119,4129,4109; OPCS: K40,K401,K402,K403,K404,K408,K409,K41,K411,K412,K413,K414,K418,K419,K42,K421,K422,K423,K424,K428,K429,K43,K431,K432,K433,K434,K438,K439,K44,K441,K442,K448,K449,K451,K452,K453,K454,K455,K456,K458,K459,K46,K461,K462,K463,K464,K465,K468,K469,K471,K491,K492,K493,K494,K498,K499,K501,K502,K504,K751,K752,K753,K754,K758,K759 | Mean = 12.0 years Range = [11.2, 12.7] years |
[ ,
45.6 % Male samples |
Mean = 57.3 years | European | — | UKB | Excluding first released tranche of genotypes from UKBB |
| PSS010961 | ICD 10: I21,I210,I211,I212,I213,I214,I219,I22,I220,I221,I228,I229,I23,I230,I231,I232,I233,I234,I235,I236,I238,I24,I240,I241,I248,I249,I252; ICD9: 410, 411, 412, 4119,4129,4109; OPCS: K40,K401,K402,K403,K404,K408,K409,K41,K411,K412,K413,K414,K418,K419,K42,K421,K422,K423,K424,K428,K429,K43,K431,K432,K433,K434,K438,K439,K44,K441,K442,K448,K449,K451,K452,K453,K454,K455,K456,K458,K459,K46,K461,K462,K463,K464,K465,K468,K469,K471,K491,K492,K493,K494,K498,K499,K501,K502,K504,K751,K752,K753,K754,K758,K759 | Mean = 12.0 years Range = [11.2, 12.7] years |
[ ,
43.5 % Male samples |
Mean = 52.4 years | African unspecified | — | UKB | — |
| PSS010962 | ICD 10: I21,I210,I211,I212,I213,I214,I219,I22,I220,I221,I228,I229,I23,I230,I231,I232,I233,I234,I235,I236,I238,I24,I240,I241,I248,I249,I252; ICD9: 410, 411, 412, 4119,4129,4109; OPCS: K40,K401,K402,K403,K404,K408,K409,K41,K411,K412,K413,K414,K418,K419,K42,K421,K422,K423,K424,K428,K429,K43,K431,K432,K433,K434,K438,K439,K44,K441,K442,K448,K449,K451,K452,K453,K454,K455,K456,K458,K459,K46,K461,K462,K463,K464,K465,K468,K469,K471,K491,K492,K493,K494,K498,K499,K501,K502,K504,K751,K752,K753,K754,K758,K759 | Mean = 12.0 years Range = [11.2, 12.7] years |
[ ,
37.2 % Male samples |
Mean = 53.0 years | East Asian | — | UKB | — |
| PSS010963 | ICD 10: I21,I210,I211,I212,I213,I214,I219,I22,I220,I221,I228,I229,I23,I230,I231,I232,I233,I234,I235,I236,I238,I24,I240,I241,I248,I249,I252; ICD9: 410, 411, 412, 4119,4129,4109; OPCS: K40,K401,K402,K403,K404,K408,K409,K41,K411,K412,K413,K414,K418,K419,K42,K421,K422,K423,K424,K428,K429,K43,K431,K432,K433,K434,K438,K439,K44,K441,K442,K448,K449,K451,K452,K453,K454,K455,K456,K458,K459,K46,K461,K462,K463,K464,K465,K468,K469,K471,K491,K492,K493,K494,K498,K499,K501,K502,K504,K751,K752,K753,K754,K758,K759 | Mean = 12.0 years Range = [11.2, 12.7] years |
[ ,
54.1 % Male samples |
Mean = 53.8 years | South Asian | — | UKB | — |
| PSS010964 | ICD 10: I21-I25; Z95.1, Z98.61; ICD9: 0.66, 36.X, 99.1, 410, 411.X, 412, 414.X, V45.81, V45.82 | — | [
|
— | African American or Afro-Caribbean | — | MVP | Excluding individuals in published GWAS (GCST90132302) |
| PSS010965 | ICD 10: I21-I25; Z95.1, Z98.61; ICD9: 0.66, 36.X, 99.1, 410, 411.X, 412, 414.X, V45.81, V45.82 | — | [
|
— | European | — | MVP | Excluding individuals in published GWAS (GCST90132302) |
| PSS010966 | ICD 10: I21-I25; Z95.1, Z98.61; ICD9: 0.66, 36.X, 99.1, 410, 411.X, 412, 414.X, V45.81, V45.82 | — | [
|
— | Hispanic or Latin American | — | MVP | Excluding individuals in published GWAS (GCST90132302) |
| PSS010967 | ICD10: I21.X, I22.X, I23.X, I24.1, or I25.2; K40.1-40.4, K41.1-41.4, K45.1-45.5, K49.1-49.2, K49.8-49.9, K50.2, K75.1-75.4, or K75.8-75.9 ICD9: 410.X, 411.0, 412.X, or 429.79 | — | [
|
— | South Asian (Bangladeshi, Pakistani) |
— | G&H | Excluding individuals in published GWAS (GCST90140952) |
| PSS011798 | — | — | [
|
— | African American or Afro-Caribbean | — | AllofUs | — |
| PSS009707 | — | — | 6,503 individuals | — | African unspecified | — | UKB | — |
| PSS009708 | — | — | 922 individuals | — | East Asian | — | UKB | — |
| PSS009960 | — | — | 172,066 individuals, 100.0 % Male samples |
Mean = 57.8 years | Not reported | — | UKB | — |
| PSS007974 | — | — | 1,810 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007975 | — | — | 1,794 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007976 | — | — | 1,805 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007977 | — | — | 1,768 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007978 | — | — | 1,808 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007979 | — | — | 1,804 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007980 | — | — | 1,789 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007981 | — | — | 1,791 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007982 | — | — | 1,794 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007983 | — | — | 1,622 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS009961 | — | — | 208,627 individuals, 0.0 % Male samples |
Mean = 57.4 years | Not reported | — | UKB | — |
| PSS007985 | — | — | 1,785 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007986 | — | — | 1,790 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS010981 | — | — | [ ,
46.0 % Male samples |
Mean = 52.83 years | European | — | CoLaus | — |
| PSS009962 | — | — | 359,310 individuals, 44.6 % Male samples |
Mean = 69.05 years Sd = 8.04 years |
Not reported | — | UKB | — |
| PSS011808 | — | — | [
|
— | Hispanic or Latin American | — | AllofUs | — |
| PSS004014 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004015 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004016 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS000929 | For GERMIFSI and GERMIFSII, CAD was defined as Myocardinal infarction before the age of 60 and 1 or more 1st- degree relative with CAD. In GERMIFSIII CAD was defined as myocardial infarction between the ages of 26 and 74. In GERMIFSIV, cases were based on a CAD diagnosis before age 65 in men or age 70 in women. In Luric, cases were ascertained as >50% angiographic confirmation of vascular obstruction in 1 or more coronary vessel | — | [
|
— | European | — | GerMIFS, LURIC | — |
| PSS004018 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS000930 | CAD ascertainment was based on myocardial infarction diagnosis or death cause using ICD-10 codes I21.X, I22.X, I23.X, I24.1, or I25.2 | — | [
|
— | European | — | EB | — |
| PSS000931 | CAD ascertainment was based on a composite of myocardial infarction or coronary revascularization. Myocardial infarction was based on ICD-9 codes 410.X, 411.X, 412.X, or 429.79, or ICD-10 codes I21.X, I22.X, I23.X, I24.1, or I25.2. Coronary revascularization was assessed based on OPCS-4 coded procedure for coronary artery bypass grafting (K40.1-40-4, K41.1-41.4, or K45.1-45.5), or coronary angioplasty with or without stenting (K49.1-49.2, K49.0-49.9, K50.2, K75.1-75.4, or K75.8-75.9) | — | [
|
— | European | — | UKB | — |
| PSS004017 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS011811 | — | — | [
|
— | Hispanic or Latin American | — | AllofUs | — |
| PSS011818 | — | — | [
|
— | European | — | AllofUs | — |
| PSS011820 | — | — | [
|
— | European | — | AllofUs | — |
| PSS011821 | — | — | [
|
— | European | — | AllofUs | — |
| PSS013146 | 346.6, 436,G43.6 | — | [ ,
44.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013147 | 438,I69 | — | [ ,
44.66 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013148 | 438,I69 | — | [ ,
44.66 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011827 | — | — | [
|
— | European | — | UKB | — |
| PSS011827 | — | — | [
|
— | Not reported | — | UKB | — |
| PSS013149 | 438,I69 | — | [ ,
44.66 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013150 | 438,I69 | — | [ ,
44.66 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011810 | — | — | [
|
— | Hispanic or Latin American | — | AllofUs | — |
| PSS011830 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | European | — | AllofUs | — |
| PSS011830 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | African unspecified | — | AllofUs | — |
| PSS011830 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | Hispanic or Latin American | — | AllofUs | — |
| PSS011830 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | South Asian | — | AllofUs | — |
| PSS011830 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | East Asian | — | AllofUs | — |
| PSS011830 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | Greater Middle Eastern (Middle Eastern, North African or Persian) | — | AllofUs | — |
| PSS011831 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | European | — | PMB | — |
| PSS011831 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | African unspecified | — | PMB | — |
| PSS011831 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | Hispanic or Latin American | — | PMB | — |
| PSS011831 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | South Asian | — | PMB | — |
| PSS000956 | Abdominal aortic aneurysm cases were defined as the presence of 2 instances of any of the following International Classification of Diseases (ICD)–9 or ICD-10 codes in a participant’s EHR: 441.3, 441.4, I71.3, or I71.4. Controls were defined as possessing no occurrences of the aforementioned ICD codes, as well as no occurrences of the ICD-9 codes 440 through 448 or ICD-10 codes I71 through I75, I77 through I79, or K55. | — | [ ,
86.0 % Male samples |
Mean = 56.3 years Sd = 11.8 years |
African unspecified | — | MVP | — |
| PSS000957 | Abdominal aortic aneurysm cases were defined as the presence of 2 instances of any of the following International Classification of Diseases (ICD)–9 or ICD-10 codes in a participant’s EHR: 441.3, 441.4, I71.3, or I71.4. | — | [ ,
48.1 % Male samples |
Mean = 58.3 years Sd = 19.5 years |
European | — | BioMe | — |
| PSS000958 | Abdominal aortic aneurysm cases were defined as the presence of 2 instances of any of the following International Classification of Diseases (ICD)–9 or ICD-10 codes in a participant’s EHR: 441.3, 441.4, I71.3, or I71.4. Controls were defined as possessing no occurrences of the aforementioned ICD codes, as well as no occurrences of the ICD-9 codes 440 through 448 or ICD-10 codes I71 through I75, I77 through I79, or K55. | — | [ ,
92.1 % Male samples |
Mean = 63.8 years Sd = 13.7 years |
European | — | MVP | Sample is independent to the MVP sample used to identify SNPs and determine their weights |
| PSS000959 | Abdominal aortic aneurysm cases were defined as the presence of 2 instances of any of the following International Classification of Diseases (ICD)–9 or ICD-10 codes in a participant’s EHR: 441.3, 441.4, I71.3, or I71.4. | — | [ ,
65.4 % Male samples |
Mean = 71.0 years Sd = 13.7 years |
European | — | PMB | — |
| PSS011832 | Chronic condition warehouse definitions for myocardial infarction and ischemic heart disease | — | [
|
— | European | — | UCLA | — |
| PSS011832 | Chronic condition warehouse definitions for myocardial infarction and ischemic heart disease | — | [
|
— | African unspecified | — | UCLA | — |
| PSS011832 | Chronic condition warehouse definitions for myocardial infarction and ischemic heart disease | — | [
|
— | Hispanic or Latin American | — | UCLA | — |
| PSS011832 | Chronic condition warehouse definitions for myocardial infarction and ischemic heart disease | — | [
|
— | East Asian | — | UCLA | — |
| PSS011832 | Chronic condition warehouse definitions for myocardial infarction and ischemic heart disease | — | [
|
— | South Asian | — | UCLA | — |
| PSS011832 | Chronic condition warehouse definitions for myocardial infarction and ischemic heart disease | — | [
|
— | Not reported | — | UCLA | — |
| PSS011831 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | Greater Middle Eastern (Middle Eastern, North African or Persian) | — | PMB | — |
| PSS011833 | — | Median = 10.5 years | [ ,
34.0 % Male samples |
Mean = 62.6 years Sd = 10.6 years |
European, Asian unspecified, African unspecified, NR (White, Asian, Black, NR) |
— | 10 cohorts
|
— |
| PSS009783 | — | — | 6,438 individuals | — | African unspecified | — | UKB | — |
| PSS009784 | — | — | 913 individuals | — | East Asian | — | UKB | — |
| PSS009785 | — | — | 43,392 individuals | — | European | Non-British European | UKB | — |
| PSS009786 | — | — | 7,948 individuals | — | South Asian | — | UKB | — |
| PSS011007 | HCM was defined as having an ICD-10 code of I42.1 or I42.2, in addition to a mention of “hypertrophic cardiomyopathy,” “hypertrophic obstructive cardiomyopathy,” “HCM,” or “HOCM” | — | 30,716 individuals, 45.37 % Male samples |
Mean = 57.23 years | European | — | MGBB | — |
| PSS011008 | HCM cases were identified by the presence of International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10), billing code I42.1 (hypertrophic obstructive cardiomyopathy) or I42.2 (other hypertrophic cardiomyopathy) | — | 184,511 individuals, 45.35 % Male samples |
Mean = 56.51 years | European | — | UKB | — |
| PSS011843 | HF defined as 2 instances of phecode 428 | — | 29,888 individuals | — | European | — | PMB | — |
| PSS011843 | HF defined as 2 instances of phecode 428 | — | 11,101 individuals | — | African unspecified | — | PMB | — |
| PSS000973 | Cases show venous thromboembolism events, 95 of which were deep vein thrombosis and 79 were pulmonary embolism. 27,189 individuals did not carry a Venous Thromboembolism monogenic mutation. | Median = 2.4 years | [ ,
74.59 % Male samples |
Mean = 64.23 years | European | — | NR | — |
| PSS012888 | 339.0, 346,G43, G44.00, G44.01, G44.02, G44.03, G44.04 | — | [ ,
46.9 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011021 | — | Mean = 9.0 years | 41,006 individuals, 43.1 % Male samples |
Mean = 51.9 years Sd = 10.6 years |
East Asian (Chinese) |
— | InterASIA | China MUCA 1998, CIMIC |
| PSS011022 | — | — | 75,886 individuals | European | — | UKB | — | |
| PSS011022 | — | — | 8,320 individuals | Not reported | — | UKB | — | |
| PSS011023 | — | — | 110,737 individuals | European | — | UKB | — | |
| PSS011023 | — | — | 6,783 individuals | Not reported | — | UKB | — | |
| PSS011024 | — | — | 142,614 individuals | European | — | UKB | — | |
| PSS011024 | — | — | 4,564 individuals | Not reported | — | UKB | — | |
| PSS012889 | 339.0, 346,G43, G44.00, G44.01, G44.02, G44.03, G44.04 | — | [ ,
46.9 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012890 | 339.0, 346,G43, G44.00, G44.01, G44.02, G44.03, G44.04 | — | [ ,
46.9 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS000283 | Composite endpoint of either: myocardial infarction, coronary revascularization, death from coronary causes. | Mean = 18.8 years | [ ,
45.0 % Male samples |
Mean = 54.0 years Sd = 5.7 years |
European | — | ARIC | — |
| PSS000284 | Cross-sectional analysis of baseline scores for coronary artery calcification (Agatston score) | — | 4,260 individuals, 44.0 % Male samples |
Mean = 69.1 years Sd = 6.0 years |
European | — | BioImage | — |
| PSS000285 | Composite endpoint of either: myocardial infarction, coronary revascularization, death from coronary causes. | Mean = 19.4 years | [ ,
38.0 % Male samples |
Mean = 58.0 years Sd = 7.7 years |
European | — | MDC-CC | — |
| PSS000286 | Composite endpoint of either: myocardial infarction, coronary revascularization, death from coronary causes. | Mean = 20.5 years | [ ,
0.0 % Male samples |
Mean = 54.2 years Sd = 7.1 years |
European | — | WGHS | — |
| PSS000287 | (i) Secondary cardiovascular events (sCVE; incl myocardial infarction, stroke, ruptured abdominal aortic aneurysm, fatal cardiac failure, percuteneous of bypass surgery, leg amputation due to cardiovascular causes, cardiovascular death), (ii) atherosclerotic carotid plaque characteristics | Mean = 3.0 years | 1,319 individuals, 69.3 % Male samples |
Mean = 68.8 years Sd = 9.3 years |
European (Dutch) |
— | AEGS1 | — |
| PSS008171 | — | — | 6,081 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS011902 | — | — | 1,315 individuals, 47.1 % Male samples |
Mean = 42.1 years Sd = 14.6 years |
European (Dutch) |
— | Dutch HeFH | — |
| PSS011903 | — | — | 383 individuals | — | European | — | UKB | Independent to UKB cohort used to train the PGS |
| PSS011903 | — | — | 27 individuals | — | Asian unspecified | — | UKB | Independent to UKB cohort used to train the PGS |
| PSS011903 | — | — | 9 individuals | — | African American or Afro-Caribbean | — | UKB | Independent to UKB cohort used to train the PGS |
| PSS011903 | — | — | 10 individuals | — | Not reported | — | UKB | Independent to UKB cohort used to train the PGS |
| PSS008192 | — | — | 6,331 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008193 | — | — | 6,070 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008194 | — | — | 6,283 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008195 | — | — | 6,001 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008196 | — | — | 6,294 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008197 | — | — | 6,308 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008198 | — | — | 6,173 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008199 | — | — | 6,205 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008200 | — | — | 6,258 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008201 | — | — | 5,719 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS009879 | Ischemic stroke | — | [
|
— | European (European) |
— | MVP | — |
| PSS008203 | — | — | 6,161 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008204 | — | — | 6,220 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS009881 | Ischemic stroke | — | [
|
— | East Asian (Taiwanese) |
— | TWB | — |
| PSS009880 | Ischemic stroke | — | [
|
— | Sub-Saharan African (Nigerian) |
— | NR | Stroke Investigative Research & Educational Network (SIREN) |
| PSS011911 | ICD10: E11 for T2D, N18 for CKD, first occurence of I20-125 for CAD. BMI: baseline body mass index | Median = 14.8 years | 48,603 individuals, 46.0 % Male samples |
Mean = 56.8 years Sd = 8.2 years |
European, East Asian, South Asian, Hispanic or Latin American, African unspecified | — | UKB | — |
| PSS011912 | ICD10: E11 for T2D, N18 for CKD, first occurence of I20-125 for CAD, K76.0 for NAFLD. BMI: baseline body mass index | Median = 14.8 years | 45,356 individuals, 46.0 % Male samples |
Mean = 57.1 years Sd = 8.1 years |
European | — | UKB | — |
| PSS000998 | All individuals were carriers of a pathogenic or likely pathogenic variant (MYBPC3 truncating variant, MYBPC3 non-truncating variant, MYH7 variant, MYL2 variant, other genetic variant). Cases included individuals who had experienced atrial fibrillation, defined as: time to atrial fibrillation or flutter. | — | [
|
— | Not reported | — | ERSPC | — |
| PSS000999 | All individuals were carriers of a pathogenic or likely pathogenic variant (MYBPC3 truncating variant, MYBPC3 non-truncating variant, MYH7 variant, MYL2 variant, other genetic variant). Cases included individuals who had experienced a clinical event, defined as: time to septal reduction therapy, cardiac transplantation, sustained ventricular arrhythmia, sudden cardiac death, appropriate ICD therapy or atrial fibrillation/flutter. | — | [
|
— | Not reported | — | ERSPC | — |
| PSS001000 | All individuals were carriers of a pathogenic or likely pathogenic variant (MYBPC3 truncating variant, MYBPC3 non-truncating variant, MYH7 variant, MYL2 variant, other genetic variant). Cases included individuals who had experienced a major ventricular arrhythmia, defined as: time to sustained ventricular arrhythmia, appropriate ICD therapy or sudden cardiac death. | — | [
|
— | Not reported | — | ERSPC | — |
| PSS001001 | All individuals were carriers of a pathogenic or likely pathogenic variant (MYBPC3 truncating variant, MYBPC3 non-truncating variant, MYH7 variant, MYL2 variant, other genetic variant). The primary outcome of maximal left ventricular wall thickness is defined as maxLVWT indexed to body surface area (BSA) on last available CMR or TTE prior to septal reduction therapy and cardiac transplantation. LVWT from CMR used whenever available unless TTE performed more than 5 years after last CMR. | — | 322 individuals | — | Not reported | — | ERSPC | — |
| PSS001002 | All individuals were non-proband carriers of a pathogenic or likely pathogenic variant (MYBPC3 truncating variant, MYBPC3 non-truncating variant, MYH7 variant, MYL2 variant, other genetic variant). Cases included individuals who had experienced a clinical event, defined as: time to septal reduction therapy, cardiac transplantation, sustained ventricular arrhythmia, sudden cardiac death, appropriate ICD therapy or atrial fibrillation/flutter. | — | [
|
— | Not reported | — | ERSPC | — |
| PSS001003 | All individuals were non-proband carriers of a pathogenic or likely pathogenic variant (MYBPC3 truncating variant, MYBPC3 non-truncating variant, MYH7 variant, MYL2 variant, other genetic variant). The primary outcome of maximal left ventricular wall thickness (maxLVWT) is defined as maxLVWT indexed to body surface area (BSA) on last available CMR or TTE prior to septal reduction therapy and cardiac transplantation. LVWT from CMR used whenever available unless TTE performed more than 5 years after last CMR. | — | 194 individuals | — | Not reported | — | ERSPC | — |
| PSS001004 | All individuals were carriers of a pathogenic or likely pathogenic variant (MYBPC3 truncating variant, MYBPC3 non-truncating variant, MYH7 variant, MYL2 variant, other genetic variant). Cases included individuals who had experienced septal reduction therapy, defined as: time to septal myectomy or alcohol septal ablation. | — | [
|
— | Not reported | — | ERSPC | — |
| PSS013029 | 401,I10 | — | [ ,
44.97 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013028 | 401,I10 | — | [ ,
44.97 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013030 | 401,I10 | — | [ ,
44.97 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011090 | — | — | [ ,
46.34 % Male samples |
— | East Asian (Han Chinese) |
— | CURES_China | — |
| PSS013032 | 401,I10 | — | [ ,
44.97 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011921 | — | — | [
|
— | East Asian (Korean) |
— | HEXA | — |
| PSS011831 | 410, 411, 412, 413, 41, V45.81 (ICD-9), I21, I22, I24, Z95.1, Z98.61, I20.0 (ICD-10) | — | [
|
— | East Asian | — | PMB | — |
| PSS013033 | 401,I10 | — | [ ,
44.97 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013041 | 402, 403, 404,I11, I12, I13 | — | [ ,
42.49 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011925 | — | — | [
|
— | East Asian (Korean) |
— | HEXA | — |
| PSS013040 | 402, 403, 404,I11, I12, I13 | — | [ ,
42.49 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013042 | 402, 403, 404,I11, I12, I13 | — | [ ,
42.49 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013043 | 402, 403, 404,I11, I12, I13 | — | [ ,
42.49 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011929 | — | — | [
|
— | East Asian (Korean) |
— | HEXA | — |
| PSS013044 | 402, 403, 404,I11, I12, I13 | — | [ ,
42.49 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013045 | 402, 403, 404,I11, I12, I13 | — | [ ,
42.49 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013046 | 401.0, 405, 437.2,I15, I16, I67.4, N26.2 | — | [ ,
44.87 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS004282 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004283 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004284 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004285 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004286 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004287 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004288 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004289 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004290 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004291 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS011934 | — | — | 3,094 individuals, 64.0 % Male samples |
— | European (Denmark) |
— | DCH | — |
| PSS013058 | 410, 411.0, 412, 429.7,I21, I22, I23.0, I23.1, I23.2, I23.3, I23.6, I23.7, I23.8, I24.1, I25.2, I51.0, I51.3 | — | [ ,
43.7 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013057 | 410, 411.0, 412, 429.7,I21, I22, I23.0, I23.1, I23.2, I23.3, I23.6, I23.7, I23.8, I24.1, I25.2, I51.0, I51.3 | — | [ ,
43.7 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013059 | 410, 411.0, 412, 429.7,I21, I22, I23.0, I23.1, I23.2, I23.3, I23.6, I23.7, I23.8, I24.1, I25.2, I51.0, I51.3 | — | [ ,
43.7 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013060 | 410, 411.0, 412, 429.7,I21, I22, I23.0, I23.1, I23.2, I23.3, I23.6, I23.7, I23.8, I24.1, I25.2, I51.0, I51.3 | — | [ ,
43.7 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013061 | 410, 411.0, 412, 429.7,I21, I22, I23.0, I23.1, I23.2, I23.3, I23.6, I23.7, I23.8, I24.1, I25.2, I51.0, I51.3 | — | [ ,
43.7 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013063 | 411.81, 414.0, 414.1, 414.2, 414.3, 414.4, 996.03, V45.81, V45.82,I24.0, I25.1, I25.3, I25.4, I25.700, I25.701, I25.708, I25.709, I25.710, I25.711, I25.718, I25.719, I25.720, I25.721, I25.728, I25.729, I25.730, I25.731, I25.738, I25.739, I25.790, I25.791, I25.798, I25.799, I25.810, I25.82, I25.83, I25.84, Z95.1, Z95.5, Z98.6 | — | [ ,
44.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013064 | 411.81, 414.0, 414.1, 414.2, 414.3, 414.4, 996.03, V45.81, V45.82,I24.0, I25.1, I25.3, I25.4, I25.700, I25.701, I25.708, I25.709, I25.710, I25.711, I25.718, I25.719, I25.720, I25.721, I25.728, I25.729, I25.730, I25.731, I25.738, I25.739, I25.790, I25.791, I25.798, I25.799, I25.810, I25.82, I25.83, I25.84, Z95.1, Z95.5, Z98.6 | — | [ ,
44.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS009922 | — | — | [
|
— | European | — | NR | — |
| PSS013065 | 411.81, 414.0, 414.1, 414.2, 414.3, 414.4, 996.03, V45.81, V45.82,I24.0, I25.1, I25.3, I25.4, I25.700, I25.701, I25.708, I25.709, I25.710, I25.711, I25.718, I25.719, I25.720, I25.721, I25.728, I25.729, I25.730, I25.731, I25.738, I25.739, I25.790, I25.791, I25.798, I25.799, I25.810, I25.82, I25.83, I25.84, Z95.1, Z95.5, Z98.6 | — | [ ,
44.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013066 | 411.81, 414.0, 414.1, 414.2, 414.3, 414.4, 996.03, V45.81, V45.82,I24.0, I25.1, I25.3, I25.4, I25.700, I25.701, I25.708, I25.709, I25.710, I25.711, I25.718, I25.719, I25.720, I25.721, I25.728, I25.729, I25.730, I25.731, I25.738, I25.739, I25.790, I25.791, I25.798, I25.799, I25.810, I25.82, I25.83, I25.84, Z95.1, Z95.5, Z98.6 | — | [ ,
44.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013068 | 414,I25 | — | [ ,
45.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013073 | 410, 411, 412, 413, 414, 429.7, 996.03, V45.81, V45.82,I20, I21, I22, I23.0, I23.1, I23.2, I23.3, I23.6, I23.7, I23.8, I24.0, I24.1, I24.8, I24.9, I25, I51.0, I51.3, Z95.1, Z95.5, Z98.6 | — | [ ,
45.93 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013074 | 410, 411, 412, 413, 414, 429.7, 996.03, V45.81, V45.82,I20, I21, I22, I23.0, I23.1, I23.2, I23.3, I23.6, I23.7, I23.8, I24.0, I24.1, I24.8, I24.9, I25, I51.0, I51.3, Z95.1, Z95.5, Z98.6 | — | [ ,
45.93 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013075 | 410, 411, 412, 413, 414, 429.7, 996.03, V45.81, V45.82,I20, I21, I22, I23.0, I23.1, I23.2, I23.3, I23.6, I23.7, I23.8, I24.0, I24.1, I24.8, I24.9, I25, I51.0, I51.3, Z95.1, Z95.5, Z98.6 | — | [ ,
45.93 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013076 | 410, 411, 412, 413, 414, 429.7, 996.03, V45.81, V45.82,I20, I21, I22, I23.0, I23.1, I23.2, I23.3, I23.6, I23.7, I23.8, I24.0, I24.1, I24.8, I24.9, I25, I51.0, I51.3, Z95.1, Z95.5, Z98.6 | — | [ ,
45.93 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013069 | 414,I25 | — | [ ,
45.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013070 | 414,I25 | — | [ ,
45.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013071 | 414,I25 | — | [ ,
45.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013078 | 429.2, | — | [ ,
44.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013077 | 429.2, | — | [ ,
44.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013082 | 429,B33.2, I23.4, I23.5, I51.1, I51.2, I51.5, I51.8, I51.9, I52 | — | [ ,
44.23 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013083 | 429,B33.2, I23.4, I23.5, I51.1, I51.2, I51.5, I51.8, I51.9, I52 | — | [ ,
44.23 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013079 | 429.2, | — | [ ,
44.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013085 | 429,B33.2, I23.4, I23.5, I51.1, I51.2, I51.5, I51.8, I51.9, I52 | — | [ ,
44.23 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013086 | 429,B33.2, I23.4, I23.5, I51.1, I51.2, I51.5, I51.8, I51.9, I52 | — | [ ,
44.23 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013080 | 429.2, | — | [ ,
44.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013081 | 429.2, | — | [ ,
44.24 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013088 | 427.0, 427.1, 427.2,I47, I49.2 | — | [ ,
45.96 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013087 | 427.0, 427.1, 427.2,I47, I49.2 | — | [ ,
45.96 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013089 | 427.0, 427.1, 427.2,I47, I49.2 | — | [ ,
45.96 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013091 | 427.0, 427.1, 427.2,I47, I49.2 | — | [ ,
45.96 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013093 | 427.31,I48.0, I48.2, I48.91 | — | [ ,
46.47 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013092 | 427.31,I48.0, I48.2, I48.91 | — | [ ,
46.47 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013094 | 427.31,I48.0, I48.2, I48.91 | — | [ ,
46.47 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013095 | 427.31,I48.0, I48.2, I48.91 | — | [ ,
46.47 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013097 | 427.3,I48 | — | [ ,
46.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011097 | — | — | 2,669 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Arab) |
— | NR | N total after excluding missing values = 2,553 |
| PSS011945 | — | — | [
|
— | European | — | HUNT | — |
| PSS011946 | — | — | [
|
— | European | — | UKB | — |
| PSS013098 | 427.3,I48 | — | [ ,
46.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013099 | 427.3,I48 | — | [ ,
46.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013100 | 427.3,I48 | — | [ ,
46.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013101 | 427.3,I48 | — | [ ,
46.51 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013103 | 427.9,I49.9 | — | [ ,
45.79 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013102 | 427.9,I49.9 | — | [ ,
45.79 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013104 | 427.9,I49.9 | — | [ ,
45.79 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013105 | 427.9,I49.9 | — | [ ,
45.79 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013106 | 427.9,I49.9 | — | [ ,
45.79 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013112 | 427, 785.0, 785.1, V12.53,I46, I47, I48, I49.0, I49.1, I49.2, I49.3, I49.4, I49.5, I49.8, I49.9, R00.0, R00.1, R00.2, Z86.74 | — | [ ,
46.01 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS004344 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004345 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004346 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004347 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004348 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004349 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004350 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004351 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004352 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004353 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS013115 | 427, 785.0, 785.1, V12.53,I46, I47, I48, I49.0, I49.1, I49.2, I49.3, I49.4, I49.5, I49.8, I49.9, R00.0, R00.1, R00.2, Z86.74 | — | [ ,
46.01 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013116 | 427, 785.0, 785.1, V12.53,I46, I47, I48, I49.0, I49.1, I49.2, I49.3, I49.4, I49.5, I49.8, I49.9, R00.0, R00.1, R00.2, Z86.74 | — | [ ,
46.01 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013123 | 430, 431, 432,I60.0, I60.1, I60.2, I60.3, I60.4, I60.5, I60.6, I60.7, I60.8, I60.9, I61, I62.0, I62.1, I62.9 | — | [ ,
44.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013122 | 430, 431, 432,I60.0, I60.1, I60.2, I60.3, I60.4, I60.5, I60.6, I60.7, I60.8, I60.9, I61, I62.0, I62.1, I62.9 | — | [ ,
44.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013124 | 430, 431, 432,I60.0, I60.1, I60.2, I60.3, I60.4, I60.5, I60.6, I60.7, I60.8, I60.9, I61, I62.0, I62.1, I62.9 | — | [ ,
44.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013126 | 430, 431, 432,I60.0, I60.1, I60.2, I60.3, I60.4, I60.5, I60.6, I60.7, I60.8, I60.9, I61, I62.0, I62.1, I62.9 | — | [ ,
44.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS000328 | ACS was defined as MI, unstable angina or death due to CHD. | Mean = 19.0 years | [ ,
44.8 % Male samples |
Mean = 43.9 years Sd = 11.3 years |
European (Finnish) |
— | FINRISK | FINRISK 1992 |
| PSS000328 | ACS was defined as MI, unstable angina or death due to CHD. | Mean = 14.0 years | [ ,
45.8 % Male samples |
Mean = 46.8 years Sd = 12.9 years |
European (Finnish) |
— | FINRISK97 | FINRISK 1997 |
| PSS000328 | ACS was defined as MI, unstable angina or death due to CHD. | Mean = 9.0 years | [ ,
45.0 % Male samples |
Mean = 47.5 years Sd = 13.0 years |
European (Finnish) |
— | FINRISK | FINRISK 2002 |
| PSS000328 | ACS was defined as MI, unstable angina or death due to CHD. | Mean = 8.0 years | [ ,
46.3 % Male samples |
Mean = 50.0 years Sd = 11.7 years |
European (Finnish) |
— | Health2000 | — |
| PSS000329 | CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. | Mean = 19.0 years | [ ,
44.8 % Male samples |
Mean = 43.9 years Sd = 11.3 years |
European (Finnish) |
— | FINRISK | FINRISK 1992 |
| PSS000329 | CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. | Mean = 14.0 years | [ ,
45.8 % Male samples |
Mean = 46.8 years Sd = 12.9 years |
European (Finnish) |
— | FINRISK97 | FINRISK 1997 |
| PSS000329 | CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. | Mean = 9.0 years | [ ,
45.0 % Male samples |
Mean = 47.5 years Sd = 13.0 years |
European (Finnish) |
— | FINRISK | FINRISK 2002 |
| PSS000329 | CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. | Mean = 8.0 years | [ ,
46.3 % Male samples |
Mean = 50.0 years Sd = 11.7 years |
European (Finnish) |
— | Health2000 | — |
| PSS000330 | CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. CVD included CHD and ischemic stroke events. | Mean = 19.0 years | [ ,
44.8 % Male samples |
Mean = 43.9 years Sd = 11.3 years |
European (Finnish) |
— | FINRISK | FINRISK 1992 |
| PSS000330 | CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. CVD included CHD and ischemic stroke events. | Mean = 14.0 years | [ ,
45.8 % Male samples |
Mean = 46.8 years Sd = 12.9 years |
European (Finnish) |
— | FINRISK97 | FINRISK 1997 |
| PSS000330 | CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. CVD included CHD and ischemic stroke events. | Mean = 9.0 years | [ ,
45.0 % Male samples |
Mean = 47.5 years Sd = 13.0 years |
European (Finnish) |
— | FINRISK | FINRISK 2002 |
| PSS000330 | CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. CVD included CHD and ischemic stroke events. | Mean = 8.0 years | [ ,
46.3 % Male samples |
Mean = 50.0 years Sd = 11.7 years |
European (Finnish) |
— | Health2000 | — |
| PSS000331 | CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410 | Median = 9.2 years IQR = [5.5, 13.0] years |
[ ,
31.0 % Male samples |
Mean = 43.6 years Sd = 12.5 years |
African American or Afro-Caribbean | — | 7 cohorts
|
right censored at age 75 years or at the age of last observation (whichever was first) |
| PSS000332 | CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. We identified the first CHD event and classified it as ‘‘incident’’ if the event occurred at least 6 months after the participant’s first record in the EHR and if there were no previous ICD-9-CM or ICD-10-CM codes associated with CHD. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410 | Median = 9.2 years IQR = [5.5, 13.0] years |
[ ,
31.0 % Male samples |
Mean = 43.6 years Sd = 12.5 years |
African American or Afro-Caribbean | — | 7 cohorts
|
right censored at age 75 years or at the age of last observation (whichever was first) |
| PSS000333 | CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410 | Median = 11.7 years IQR = [6.0, 18.5] years |
[ ,
44.6 % Male samples |
Mean = 49.0 years Sd = 14.1 years |
European | — | 11 cohorts
|
right censored at age 75 years or at the age of last observation (whichever was first) |
| PSS000334 | CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. We identified the first CHD event and classified it as ‘‘incident’’ if the event occurred at least 6 months after the participant’s first record in the EHR and if there were no previous ICD-9-CM or ICD-10-CM codes associated with CHD. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410 | Median = 11.7 years IQR = [6.0, 18.5] years |
[ ,
44.6 % Male samples |
Mean = 49.0 years Sd = 14.1 years |
European | — | 11 cohorts
|
right censored at age 75 years or at the age of last observation (whichever was first) |
| PSS000335 | CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410 | Median = 10.4 years IQR = [5.7, 14.7] years |
[ ,
36.2 % Male samples |
Mean = 41.1 years Sd = 13.2 years |
Hispanic or Latin American | — | 8 cohorts
|
right censored at age 75 years or at the age of last observation (whichever was first) |
| PSS000336 | CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. We identified the first CHD event and classified it as ‘‘incident’’ if the event occurred at least 6 months after the participant’s first record in the EHR and if there were no previous ICD-9-CM or ICD-10-CM codes associated with CHD. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410 | Median = 10.4 years IQR = [5.7, 14.7] years |
[ ,
36.2 % Male samples |
Mean = 41.1 years Sd = 13.2 years |
Hispanic or Latin American | — | 8 cohorts
|
right censored at age 75 years or at the age of last observation (whichever was first) |
| PSS009939 | — | — | 39,444 individuals | — | European (Finnish) |
— | FinnGen | — |
| PSS013143 | 346.6, 436,G43.6 | — | [ ,
44.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013142 | 346.6, 436,G43.6 | — | [ ,
44.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013144 | 346.6, 436,G43.6 | — | [ ,
44.81 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS011973 | — | — | 411,749 individuals, 43.8 % Male samples |
Mean = 56.1 years Sd = 8.1 years |
European | — | UKB | — |
| PSS011973 | — | — | 45,402 individuals, 43.8 % Male samples |
Mean = 56.1 years Sd = 8.1 years |
Not reported | — | UKB | — |
| PSS013153 | 346.6, 433, 434, 435, 436, 437, 438, V12.54,G43.6, G45.0, G45.1, G45.2, G45.4, G45.8, G45.9, G46.0, G46.1, G46.2, G46.3, G46.4, G46.5, G46.6, G46.7, G46.8, I63, I65, I66, I67.1, I67.2, I67.5, I67.6, I67.7, I67.8, I67.9, I68, I69, M47.02, Z86.73 | — | [ ,
45.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013152 | 346.6, 433, 434, 435, 436, 437, 438, V12.54,G43.6, G45.0, G45.1, G45.2, G45.4, G45.8, G45.9, G46.0, G46.1, G46.2, G46.3, G46.4, G46.5, G46.6, G46.7, G46.8, I63, I65, I66, I67.1, I67.2, I67.5, I67.6, I67.7, I67.8, I67.9, I68, I69, M47.02, Z86.73 | — | [ ,
45.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013154 | 346.6, 433, 434, 435, 436, 437, 438, V12.54,G43.6, G45.0, G45.1, G45.2, G45.4, G45.8, G45.9, G46.0, G46.1, G46.2, G46.3, G46.4, G46.5, G46.6, G46.7, G46.8, I63, I65, I66, I67.1, I67.2, I67.5, I67.6, I67.7, I67.8, I67.9, I68, I69, M47.02, Z86.73 | — | [ ,
45.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS009940 | We used the disease definitions described in the supplement of Said et al (2018). PMID: 29955826 | — | [ ,
46.0 % Male samples |
European | — | UKB | — | |
| PSS009941 | We used the disease definitions described in the supplement of Said et al (2018). PMID: 29955826 | — | [ ,
46.0 % Male samples |
European | — | UKB | — | |
| PSS009942 | We used the disease definitions described in the supplement of Said et al (2018). PMID: 29955826 | — | [ ,
42.0 % Male samples |
European | — | UKB | — | |
| PSS013156 | 346.6, 433, 434, 435, 436, 437, 438, V12.54,G43.6, G45.0, G45.1, G45.2, G45.4, G45.8, G45.9, G46.0, G46.1, G46.2, G46.3, G46.4, G46.5, G46.6, G46.7, G46.8, I63, I65, I66, I67.1, I67.2, I67.5, I67.6, I67.7, I67.8, I67.9, I68, I69, M47.02, Z86.73 | — | [ ,
45.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013151 | 438,I69 | — | [ ,
44.66 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013155 | 346.6, 433, 434, 435, 436, 437, 438, V12.54,G43.6, G45.0, G45.1, G45.2, G45.4, G45.8, G45.9, G46.0, G46.1, G46.2, G46.3, G46.4, G46.5, G46.6, G46.7, G46.8, I63, I65, I66, I67.1, I67.2, I67.5, I67.6, I67.7, I67.8, I67.9, I68, I69, M47.02, Z86.73 | — | [ ,
45.85 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS009946 | — | — | 36,662 individuals, 75.0 % Male samples |
Mean = 64.1 years | European | — | FOURIER, PEGASUS, SAVOR-TIMI_53, SOLID-TIMI_52 | — |
| PSS009947 | — | — | 674 individuals | — | Asian unspecified | — | FOURIER, PEGASUS, SAVOR-TIMI_53, SOLID-TIMI_52 | — |
| PSS009947 | — | — | 791 individuals | — | East Asian | — | FOURIER, PEGASUS, SAVOR-TIMI_53, SOLID-TIMI_52 | — |
| PSS009947 | — | — | 687 individuals | — | South Asian | — | FOURIER, PEGASUS, SAVOR-TIMI_53, SOLID-TIMI_52 | — |
| PSS009947 | — | — | 2,721 individuals | — | Hispanic or Latin American (Mixed American) |
— | FOURIER, PEGASUS, SAVOR-TIMI_53, SOLID-TIMI_52 | — |
| PSS009948 | — | — | [
|
— | African unspecified, European, Hispanic or Latin American, African American or Afro-Caribbean, Asian unspecified | Africa, European, Hispanics, Afro-Carribean, Pan-Asian | BBJ, EPIC_CAD, GMC, RACE, UKB | HELSINKI |
| PSS004403 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004404 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004405 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004406 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004407 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS001026 | — | — | 2,647 individuals | — | European | — | MESA | — |
| PSS001026 | — | — | 728 individuals | — | East Asian | — | MESA | — |
| PSS001026 | — | — | 1,834 individuals | — | African American or Afro-Caribbean | — | MESA | — |
| PSS001026 | — | — | 1,451 individuals | — | Hispanic or Latin American | — | MESA | — |
| PSS004413 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004414 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004415 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004416 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004417 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS008393 | — | — | 1,162 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS012037 | ICD10: I70.0, I70.00, I70.01, I70.2, I70.20, I70.21, I70.8, I70.80, I70.81, I70.9, I70.90, I70.91, I73.8, I73.9 ICD9: 4400, 4402, 4408, 4438, 4439, 9976 OPCS4: X09.1, X09.2, X09.3, X09.4, X09.5, X09.8, X09.9, X10.1, X10.8, X10.9, X12.1, X12.3, X12.4, L16.2, L16.3, L21.6, L25.1, L25.2, L26.1, L26.2, L51.1, L51.2, L51.3, L51.4, L51.6, L51.8, L52.1, L52.2, L54.1, L54.4, L54.8, L54.9, L59.1, L59.2, L59.3, L59.4, L59.5, L59.6, L59.7, L59.8, L59.9, L60.1, L60.2, L60.3, L60.4, L60.8, L60.9, L63.1, L63.5, L63.8, L63.9, L66.5, L66.7, L66.8, L66.9, L68.1, L68.2, L71.1, L71.5, L71.7, L71.8, L71.9 OPCS3: 873, 874, 881, 8841 | Median = 12.1 years | [
|
— | Greater Middle Eastern (Middle Eastern, North African or Persian) | — | UKB | — |
| PSS009958 | — | — | 21,863 individuals, 0.0 % Male samples |
Mean = 65.3 years | European (Non-Hispanic White) |
— | WHI | — |
| PSS008412 | — | — | 1,200 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008413 | — | — | 1,158 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008414 | — | — | 1,190 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008415 | — | — | 1,151 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008416 | — | — | 1,197 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008417 | — | — | 1,198 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008418 | — | — | 1,183 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008419 | — | — | 1,183 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008420 | — | — | 1,189 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008421 | — | — | 1,102 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS009965 | CAD events were defined according to the Data Collection on Adverse events of Anti-HIV Drugs (D:A:D) study and the MONICA Project of the World Health Organization, as reported elsewhere | — | [
|
— | European | — | SHCS | — |
| PSS004447 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004448 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004449 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004450 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004451 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS008423 | — | — | 1,179 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008424 | — | — | 1,182 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS009971 | — | — | 30,716 individuals | — | European | — | MGBB | — |
| PSS009971 | — | — | 1,807 individuals | — | African unspecified (Black) |
— | MGBB | — |
| PSS009971 | — | — | 786 individuals | — | Asian unspecified | — | MGBB | — |
| PSS009971 | — | — | 3,113 individuals | — | Other | — | MGBB | — |
| PSS011183 | — | — | [ ,
44.3 % Male samples |
Mean = 56.2 years Sd = 8.05 years |
European (British) |
— | UKB | — |
| PSS004501 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004502 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004503 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004504 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004505 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS009986 | — | — | [ ,
47.0 % Male samples |
— | Greater Middle Eastern (Middle Eastern, North African or Persian) (Qatari) |
— | QBB | — |
| PSS011190 | — | — | [ ,
43.9 % Male samples |
— | European | — | BioVU | — |
| PSS009989 | — | — | 360,098 individuals, 45.1 % Male samples |
Mean = 56.95 years | European | — | UKB | — |
| PSS001063 | Cases were individuals with incident coronary heart disesase (CHD). The outcome CHD was a combined endpoint of nonfatal myocardial infarction as well as coronary death and sudden death (International Classification of Disease 9th Revision: 410–414 and 798). Until December 2000, the diagnosis of a major, nonfatal myocardial infarction and coronary death was based on the MONICA algorithm in which a diagnosis of a major CHD event was based on symptoms, cardiac enzymes (creatine kinase, aspartate aminotransferase, and lactate dehydrogenase), serial changes from 12‐lead electrocardiograms (ECGs) evaluated by Minnesota coding, necropsy results and history of CHD in fatal cases. Since January 1, 2001, the diagnosis of myocardial infarction was based on the European Society of Cardiology and American College of Cardiology criteria. Incident events were identified through follow‐up questionnaires or through the MONICA/KORA myocardial infarction registry, which monitors the occurrence of all in‐ and out of‐hospital fatal and nonfatal myocardial infarctions among the 25–74‐year‐old inhabitants of the study region. Initially identified self‐reported incident cases and the self‐reported date of diagnosis not covered by the MONICA/KORA myocardial infarction registry, were validated by hospital records or by contacting the patient's treating physician. Deaths from myocardial in- farction were validated by death certificates, autopsy reports, chart reviews, or information from the last treating physician. | Median = 14.0 years IQR = [14.0, 14.0] years |
[ ,
48.1 % Male samples |
— | European | — | KORA | — |
| PSS001064 | Cases were individuals with incident coronary heart disesase (CHD). The outcome CHD was a combined endpoint of nonfatal myocardial infarction as well as coronary death and sudden death (International Classification of Disease 9th Revision: 410–414 and 798). Until December 2000, the diagnosis of a major, nonfatal myocardial infarction and coronary death was based on the MONICA algorithm in which a diagnosis of a major CHD event was based on symptoms, cardiac enzymes (creatine kinase, aspartate aminotransferase, and lactate dehydrogenase), serial changes from 12‐lead electrocardiograms (ECGs) evaluated by Minnesota coding, necropsy results and history of CHD in fatal cases. Since January 1, 2001, the diagnosis of myocardial infarction was based on the European Society of Cardiology and American College of Cardiology criteria. Incident events were identified through follow‐up questionnaires or through the MONICA/KORA myocardial infarction registry, which monitors the occurrence of all in‐ and out of‐hospital fatal and nonfatal myocardial infarctions among the 25–74‐year‐old inhabitants of the study region. Initially identified self‐reported incident cases and the self‐reported date of diagnosis not covered by the MONICA/KORA myocardial infarction registry, were validated by hospital records or by contacting the patient's treating physician. Deaths from myocardial in- farction were validated by death certificates, autopsy reports, chart reviews, or information from the last treating physician. | Median = 14.0 years IQR = [10.3, 14.0] years |
[ ,
53.06 % Male samples |
— | European | — | KORA | — |
| PSS012028 | ICD-9 Diagnosis: 4400, 44020, 44021, 44022, 44023, 44024, 44029, 44030, 44031, 44032, 4404, 4408, 4439, 4471 ICD-10 Diagnosis: I700, I70201, I70202, I70203, I70209, I70211, I70212, I70213, I70219, I70221, I70222, I70223, I7025, I70229, I70231, I70232, I70233, I70234, I70235, I70238, I70239, I70241, I70242, I70243, I70244, I70245, I70248, I70249, I70261, I70262, I70263, I70269, I70291, I70292, I70293, I70299, I70301, I70302, I70303, I70309, I70311, I70312, I70313, I70319, I70321, I70322, I70323, I70329, I70331, I70332, I70333, I70334, I70335, I70338, I70339, I70341, I70342, I70343, I70344, I70345, I70348, I70349, I70361, I70362, I70363, I70369, I70391, I70392, I70393, I70399, I70401, I70402, I70403, I70409, I70411, I70412, I70413, I70419, I70421, I70422, I70423, I70429, I70431, I70432, I70433, I70434, I70435, I70438, I70439, I70441, I70442, I70443, I70444, I70445, I70448, I70449, I70461, I70462, I70463, I70469, I70491, I70492, I70493, I70499, I70501, I70502, I70503, I70509, I70511, I70512, I70513, I70519, I70521, I70522, I70523, I70529, I70531, I70532, I70533, I70534, I70535, I70538, I70539, I70541, I70542, I70543, I70544, I70545, I70548, I70549, I70561, I70562, I70563, I70569, I70591, I70592, I70593, I70599, I70601, I70602, I70603, I70609, I70611, I70612, I70613, I70619, I70621, I70622, I70623, I70629, I70631, I70632, I70633, I70634, I70635, I70638, I70639, I70641, I70642, I70643, I70644, I70645, I70648, I70649, I70661, I70662, I70663, I70669, I70691, I70692, I70693, I70699, I70701, I70702, I70703, I70709, I70711, I70712, I70713, I70719, I70721, I70722, I70723, I70729, I70731, I70732, I70733, I70734, I70735, I70738, I70739, I70741, I70742, I70743, I70744, I70745, I70748, I70749, I70761, I70762, I70763, I70769, I70791, I70792, I70793, I70799, I7092, I739, I771 CPT: 93668, 27290, 27295, 27590, 27592, 27594, 27596, 27598, 27880, 27881, 27882, 27884, 27886, 27888, 35302, 35303, 35304, 35305, 35306, 35331, 35351, 35355, 35361, 35363, 35371, 35372, 35452, 35454, 35456, 35459, 35470, 35472, 35473, 35474, 35481, 35482, 35483, 35485, 35491, 35492, 35493, 35495, 35521, 35533, 35537, 35538, 35539, 35540, 35548, 35549, 35551, 35556, 35558, 35563, 35565, 35566, 35571, 35583, 35585, 35587, 35621, 35623, 35637, 35638, 35646, 35647, 35654, 35656, 35661, 35663, 35665, 35666, 35671, 35876, 35879, 35881, 35883, 35884, 37220, 37221, 37222, 37223, 37224, 37225, 37226, 37227, 37228, 37229, 37230, 37231, 37232, 37233, 37234, 37235, 35381, 35541, 35546, 35582, 35651, 35641 ICD-9 Procedure: 38.18, 39.25, 39.29, 39.5, 39.9, 84.1, 84.12, 84.13, 84.14, 84.15, 84.16, 84.17, 84.18, 84.19, 84.3 ICD-10 Procedure: 041C***, 041D***, 041F***, 041H***, 041J***, 041K***, 041L***, 041M***, 041N***, 041U***, 0470***, 047C***, 047D***, 047E***, 047F***, 047H***, 047J***, 047K***, 047L***, 047M***, 047N***, 047P***, 047Q***, 047R***, 047S***, 047T***, 047U***, 047V***, 047W***, 047Y***, 04C0***, 04CC***, 04CD***, 04CE***, 04CF***, 04CH***, 04CJ***, 04CK***, 04CL***, 04CM***, 04CN***, 04CP***, 04CQ***, 04CR***, 04CS***, 04CT***, 04CU***, 04CV***, 04CW***, 04CY***, 0Y62***, 0Y63***, 0Y68***, 0Y6C***, 0Y6D***, 0Y6F***, 0Y6G***, 0Y6H***, 0Y6J***, 0Y6M***, 0Y6N*** | Median = 2.32 years | [
|
— | Greater Middle Eastern (Middle Eastern, North African or Persian) | — | AllofUs | — |
| PSS001065 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | African American or Afro-Caribbean | — | BioMe | — |
| PSS001066 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | European | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | European | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | African American or Afro-Caribbean | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | Hispanic or Latin American | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | Asian unspecified, Native American, NR | — | BioMe | — |
| PSS009995 | ICD48 | — | [
|
— | East Asian (Japanese) |
— | BBJ | — |
| PSS012034 | ICD10: I70.0, I70.00, I70.01, I70.2, I70.20, I70.21, I70.8, I70.80, I70.81, I70.9, I70.90, I70.91, I73.8, I73.9 ICD9: 4400, 4402, 4408, 4438, 4439, 9976 OPCS4: X09.1, X09.2, X09.3, X09.4, X09.5, X09.8, X09.9, X10.1, X10.8, X10.9, X12.1, X12.3, X12.4, L16.2, L16.3, L21.6, L25.1, L25.2, L26.1, L26.2, L51.1, L51.2, L51.3, L51.4, L51.6, L51.8, L52.1, L52.2, L54.1, L54.4, L54.8, L54.9, L59.1, L59.2, L59.3, L59.4, L59.5, L59.6, L59.7, L59.8, L59.9, L60.1, L60.2, L60.3, L60.4, L60.8, L60.9, L63.1, L63.5, L63.8, L63.9, L66.5, L66.7, L66.8, L66.9, L68.1, L68.2, L71.1, L71.5, L71.7, L71.8, L71.9 OPCS3: 873, 874, 881, 8841 | Median = 12.1 years | [
|
— | African unspecified | — | UKB | — |
| PSS012035 | ICD10: I70.0, I70.00, I70.01, I70.2, I70.20, I70.21, I70.8, I70.80, I70.81, I70.9, I70.90, I70.91, I73.8, I73.9 ICD9: 4400, 4402, 4408, 4438, 4439, 9976 OPCS4: X09.1, X09.2, X09.3, X09.4, X09.5, X09.8, X09.9, X10.1, X10.8, X10.9, X12.1, X12.3, X12.4, L16.2, L16.3, L21.6, L25.1, L25.2, L26.1, L26.2, L51.1, L51.2, L51.3, L51.4, L51.6, L51.8, L52.1, L52.2, L54.1, L54.4, L54.8, L54.9, L59.1, L59.2, L59.3, L59.4, L59.5, L59.6, L59.7, L59.8, L59.9, L60.1, L60.2, L60.3, L60.4, L60.8, L60.9, L63.1, L63.5, L63.8, L63.9, L66.5, L66.7, L66.8, L66.9, L68.1, L68.2, L71.1, L71.5, L71.7, L71.8, L71.9 OPCS3: 873, 874, 881, 8841 | Median = 12.1 years | [
|
— | East Asian | — | UKB | — |
| PSS012036 | ICD10: I70.0, I70.00, I70.01, I70.2, I70.20, I70.21, I70.8, I70.80, I70.81, I70.9, I70.90, I70.91, I73.8, I73.9 ICD9: 4400, 4402, 4408, 4438, 4439, 9976 OPCS4: X09.1, X09.2, X09.3, X09.4, X09.5, X09.8, X09.9, X10.1, X10.8, X10.9, X12.1, X12.3, X12.4, L16.2, L16.3, L21.6, L25.1, L25.2, L26.1, L26.2, L51.1, L51.2, L51.3, L51.4, L51.6, L51.8, L52.1, L52.2, L54.1, L54.4, L54.8, L54.9, L59.1, L59.2, L59.3, L59.4, L59.5, L59.6, L59.7, L59.8, L59.9, L60.1, L60.2, L60.3, L60.4, L60.8, L60.9, L63.1, L63.5, L63.8, L63.9, L66.5, L66.7, L66.8, L66.9, L68.1, L68.2, L71.1, L71.5, L71.7, L71.8, L71.9 OPCS3: 873, 874, 881, 8841 | Median = 12.1 years | [
|
— | South Asian | — | UKB | — |
| PSS011197 | — | — | [
|
— | European | — | WTCCC | — |
| PSS011198 | — | — | [
|
— | European | — | UCC-SMART | — |
| PSS011199 | — | — | [
|
— | European | — | OxAAA, UKAGS, UKB, UppsalaAAA, VIVA | — |
| PSS000365 | Case-control study of first-onset acute myocardial infarction | — | [ ,
90.7 % Male samples |
Mean = 34.0 years IQR = [30.0, 35.0] years |
South Asian | — | BRAVE | — |
| PSS000365 | Case-control study of first-onset acute myocardial infarction | — | 244 individuals, 90.2 % Male samples |
Mean = 33.0 years IQR = [30.0, 35.0] years |
South Asian | — | BRAVE | — |
| PSS000366 | Cases composed of men and women diagnosed with coronary artery disease. Controls were selected from consenting men and women without any form of heart disease. | — | [ ,
90.2 % Male samples |
Mean = 54.0 years IQR = [46.0, 60.0] years |
South Asian | — | MedGenome | — |
| PSS000366 | Cases composed of men and women diagnosed with coronary artery disease. Controls were selected from consenting men and women without any form of heart disease. | — | 1,163 individuals, 76.4 % Male samples |
Mean = 55.0 years IQR = [49.0, 62.0] years |
South Asian | — | MedGenome | — |
| PSS000367 | Ascertainment of coronary artery disease was based on self-report or hospital admission diagnosis. This included individuals with ICD-9 codes of 410.X, 411.0, 412.X, or 429.79, or ICD-10 codes of I21.X, I22.X, I23.X, I24.1, or I25.2 in hospitalization records. Coronary revascularization was assessed based on an OPCS-4 coded procedure for coronary artery bypass grafting (K40.1–40.4, K41.1–41.4, or K45.1–45.5), or coronary angioplasty with or without stenting (K49.1–49.2, K49.8–49.9, K50.2, K75.1–75.4, or K75.8–75.9). | — | [ ,
86.7 % Male samples |
Mean = 60.6 years IQR = [54.4, 66.1] years |
South Asian | — | UKB | — |
| PSS000367 | Ascertainment of coronary artery disease was based on self-report or hospital admission diagnosis. This included individuals with ICD-9 codes of 410.X, 411.0, 412.X, or 429.79, or ICD-10 codes of I21.X, I22.X, I23.X, I24.1, or I25.2 in hospitalization records. Coronary revascularization was assessed based on an OPCS-4 coded procedure for coronary artery bypass grafting (K40.1–40.4, K41.1–41.4, or K45.1–45.5), or coronary angioplasty with or without stenting (K49.1–49.2, K49.8–49.9, K50.2, K75.1–75.4, or K75.8–75.9). | — | 6,846 individuals, 52.1 % Male samples |
Mean = 52.8 years IQR = [46.3, 60.2] years |
South Asian | — | UKB | — |
| PSS004541 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004542 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004543 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004544 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004545 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS012027 | ICD10: I70.0, I70.00, I70.01, I70.2, I70.20, I70.21, I70.8, I70.80, I70.81, I70.9, I70.90, I70.91, I73.8, I73.9 ICD9: 4400, 4402, 4408, 4438, 4439, 9976 OPCS4: X09.1, X09.2, X09.3, X09.4, X09.5, X09.8, X09.9, X10.1, X10.8, X10.9, X12.1, X12.3, X12.4, L16.2, L16.3, L21.6, L25.1, L25.2, L26.1, L26.2, L51.1, L51.2, L51.3, L51.4, L51.6, L51.8, L52.1, L52.2, L54.1, L54.4, L54.8, L54.9, L59.1, L59.2, L59.3, L59.4, L59.5, L59.6, L59.7, L59.8, L59.9, L60.1, L60.2, L60.3, L60.4, L60.8, L60.9, L63.1, L63.5, L63.8, L63.9, L66.5, L66.7, L66.8, L66.9, L68.1, L68.2, L71.1, L71.5, L71.7, L71.8, L71.9 OPCS3: 873, 874, 881, 8841 | Median = 12.1 years | [
|
— | European | — | UKB | Independent individuals from training sample |
| PSS001082 | Cases were individuals who had experienced an ischemic stroke (IS) event. IS was defined according to the World Health Organization definition and included imaging by computed tomography or magnetic resonance imaging in the majority of cases. All cases of IS were further divided into subtypes of large vessel (n=49), small vessel (n=43), cardioembolic (n=36), and undetermined. Undetermined strokes had undetermined causes, multiple causes identified, or an incomplete evaluation made. All stroke events were assessed by an adjudication committee, blinded to the identity of participants and study treatment group assignment. | Median = 4.7 years IQR = [3.6, 5.7] years |
[ ,
45.1 % Male samples |
Mean = 75.1 years Sd = 4.2 years |
European | — | ASPREE | — |
| PSS012047 | — | — | [ ,
45.5 % Male samples |
Mean = 56.48 years Sd = 8.1 years |
European | — | UKB | — |
| PSS012048 | — | — | 6,816 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Arabs) |
— | QBB | — |
| PSS012048 | — | — | 2,620 individuals | — | South Asian | — | NR | — |
| PSS012048 | — | — | 655 individuals | — | African unspecified | — | NR | — |
| PSS012048 | — | — | 4,168 individuals | — | Not reported | — | NR | — |
| PSS012049 | — | — | 2,647 individuals | — | European | — | MESA | — |
| PSS012029 | ICD-9 Diagnosis: 4400, 44020, 44021, 44022, 44023, 44024, 44029, 44030, 44031, 44032, 4404, 4408, 4439, 4471 ICD-10 Diagnosis: I700, I70201, I70202, I70203, I70209, I70211, I70212, I70213, I70219, I70221, I70222, I70223, I7025, I70229, I70231, I70232, I70233, I70234, I70235, I70238, I70239, I70241, I70242, I70243, I70244, I70245, I70248, I70249, I70261, I70262, I70263, I70269, I70291, I70292, I70293, I70299, I70301, I70302, I70303, I70309, I70311, I70312, I70313, I70319, I70321, I70322, I70323, I70329, I70331, I70332, I70333, I70334, I70335, I70338, I70339, I70341, I70342, I70343, I70344, I70345, I70348, I70349, I70361, I70362, I70363, I70369, I70391, I70392, I70393, I70399, I70401, I70402, I70403, I70409, I70411, I70412, I70413, I70419, I70421, I70422, I70423, I70429, I70431, I70432, I70433, I70434, I70435, I70438, I70439, I70441, I70442, I70443, I70444, I70445, I70448, I70449, I70461, I70462, I70463, I70469, I70491, I70492, I70493, I70499, I70501, I70502, I70503, I70509, I70511, I70512, I70513, I70519, I70521, I70522, I70523, I70529, I70531, I70532, I70533, I70534, I70535, I70538, I70539, I70541, I70542, I70543, I70544, I70545, I70548, I70549, I70561, I70562, I70563, I70569, I70591, I70592, I70593, I70599, I70601, I70602, I70603, I70609, I70611, I70612, I70613, I70619, I70621, I70622, I70623, I70629, I70631, I70632, I70633, I70634, I70635, I70638, I70639, I70641, I70642, I70643, I70644, I70645, I70648, I70649, I70661, I70662, I70663, I70669, I70691, I70692, I70693, I70699, I70701, I70702, I70703, I70709, I70711, I70712, I70713, I70719, I70721, I70722, I70723, I70729, I70731, I70732, I70733, I70734, I70735, I70738, I70739, I70741, I70742, I70743, I70744, I70745, I70748, I70749, I70761, I70762, I70763, I70769, I70791, I70792, I70793, I70799, I7092, I739, I771 CPT: 93668, 27290, 27295, 27590, 27592, 27594, 27596, 27598, 27880, 27881, 27882, 27884, 27886, 27888, 35302, 35303, 35304, 35305, 35306, 35331, 35351, 35355, 35361, 35363, 35371, 35372, 35452, 35454, 35456, 35459, 35470, 35472, 35473, 35474, 35481, 35482, 35483, 35485, 35491, 35492, 35493, 35495, 35521, 35533, 35537, 35538, 35539, 35540, 35548, 35549, 35551, 35556, 35558, 35563, 35565, 35566, 35571, 35583, 35585, 35587, 35621, 35623, 35637, 35638, 35646, 35647, 35654, 35656, 35661, 35663, 35665, 35666, 35671, 35876, 35879, 35881, 35883, 35884, 37220, 37221, 37222, 37223, 37224, 37225, 37226, 37227, 37228, 37229, 37230, 37231, 37232, 37233, 37234, 37235, 35381, 35541, 35546, 35582, 35651, 35641 ICD-9 Procedure: 38.18, 39.25, 39.29, 39.5, 39.9, 84.1, 84.12, 84.13, 84.14, 84.15, 84.16, 84.17, 84.18, 84.19, 84.3 ICD-10 Procedure: 041C***, 041D***, 041F***, 041H***, 041J***, 041K***, 041L***, 041M***, 041N***, 041U***, 0470***, 047C***, 047D***, 047E***, 047F***, 047H***, 047J***, 047K***, 047L***, 047M***, 047N***, 047P***, 047Q***, 047R***, 047S***, 047T***, 047U***, 047V***, 047W***, 047Y***, 04C0***, 04CC***, 04CD***, 04CE***, 04CF***, 04CH***, 04CJ***, 04CK***, 04CL***, 04CM***, 04CN***, 04CP***, 04CQ***, 04CR***, 04CS***, 04CT***, 04CU***, 04CV***, 04CW***, 04CY***, 0Y62***, 0Y63***, 0Y68***, 0Y6C***, 0Y6D***, 0Y6F***, 0Y6G***, 0Y6H***, 0Y6J***, 0Y6M***, 0Y6N*** | Median = 2.32 years | [
|
— | South Asian | — | AllofUs | — |
| PSS012049 | — | — | 1,834 individuals | — | African American or Afro-Caribbean | — | MESA | — |
| PSS012050 | — | — | 3,898 individuals | — | European | — | CARDIA, MESA | — |
| PSS012050 | — | — | 2,510 individuals | — | African American or Afro-Caribbean | — | CARDIA, MESA | — |
| PSS012050 | — | — | 2,179 individuals | — | East Asian, Hispanic or Latin American | — | MESA | — |
| PSS012030 | Phenotype constructed using NLP applied to unstructured EHR text and ICD10 codes: | Median = 5.19 years | [
|
— | African American or Afro-Caribbean | — | MGBB | — |
| PSS011200 | — | — | [
|
— | European | — | UKB | — |
| PSS012049 | — | — | 2,179 individuals | — | East Asian, Hispanic or Latin American | — | MESA | — |
| PSS012031 | Phenotype constructed using NLP applied to unstructured EHR text and ICD10 codes: | Median = 5.19 years | [
|
— | European | — | MGBB | — |
| PSS012032 | Phenotype constructed using NLP applied to unstructured EHR text and ICD10 codes: | Median = 5.19 years | [
|
— | Hispanic or Latin American | — | MGBB | — |
| PSS012052 | — | — | [
|
— | European | — | UKB | — |
| PSS012033 | ICD10: I70.0, I70.00, I70.01, I70.2, I70.20, I70.21, I70.8, I70.80, I70.81, I70.9, I70.90, I70.91, I73.8, I73.9 ICD9: 4400, 4402, 4408, 4438, 4439, 9976 OPCS4: X09.1, X09.2, X09.3, X09.4, X09.5, X09.8, X09.9, X10.1, X10.8, X10.9, X12.1, X12.3, X12.4, L16.2, L16.3, L21.6, L25.1, L25.2, L26.1, L26.2, L51.1, L51.2, L51.3, L51.4, L51.6, L51.8, L52.1, L52.2, L54.1, L54.4, L54.8, L54.9, L59.1, L59.2, L59.3, L59.4, L59.5, L59.6, L59.7, L59.8, L59.9, L60.1, L60.2, L60.3, L60.4, L60.8, L60.9, L63.1, L63.5, L63.8, L63.9, L66.5, L66.7, L66.8, L66.9, L68.1, L68.2, L71.1, L71.5, L71.7, L71.8, L71.9 OPCS3: 873, 874, 881, 8841 | Median = 12.1 years | [
|
— | African American or Afro-Caribbean, East Asian, European, Greater Middle Eastern (Middle Eastern, North African or Persian), South Asian | — | UKB | — |
| PSS001084 | Moderate Age-Related Diabetes (MARD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001085 | Moderate Obesity-related Diabetes (MOD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001086 | Severe Autoimmune Diabetes (SAID) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001087 | Severe Insulin-Deficient Diabetes (SIDD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001088 | Severe Insulin-Resistant Diabetes (SIRD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS000383 | Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[
|
Range = [40.0, 55.0] years | European, African unspecified, NR | 98.3% White European, 1.7% Black/Other | UKB | PCE Prospective Cohort (lipid-lowering treatment performed) |
| PSS000384 | Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[
|
Range = [40.0, 55.0] years | European, African unspecified, NR | 98.3% White European, 1.7% Black/Other | UKB | PCE Prospective Cohort (lipid-lowering treatment performed) |
| PSS000385 | Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[
|
Range = [40.0, 55.0] years | European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified | 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry | UKB | QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed) |
| PSS000386 | Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[
|
Range = [40.0, 55.0] years | European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified | 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry | UKB | QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed) |
| PSS000387 | Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[
|
Range = [55.0, 69.0] years | European, African unspecified, NR | 98.3% White European, 1.7% Black/Other | UKB | PCE Prospective Cohort (lipid-lowering treatment performed) |
| PSS000388 | Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[
|
Range = [55.0, 69.0] years | European, African unspecified, NR | 98.3% White European, 1.7% Black/Other | UKB | PCE Prospective Cohort (lipid-lowering treatment performed) |
| PSS000389 | Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[
|
Range = [55.0, 69.0] years | European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified | 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry | UKB | QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed) |
| PSS000390 | Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[
|
Range = [55.0, 69.0] years | European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified | 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry | UKB | QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed) |
| PSS000391 | Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
100.0 % Male samples |
Mean = 55.79 years Sd = 8.35 years |
European, African unspecified, NR | 98.3% White European, 1.7% Black/Other | UKB | PCE Prospective Cohort (lipid-lowering treatment performed) |
| PSS004618 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004619 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS000392 | Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
100.0 % Male samples |
Mean = 55.79 years Sd = 8.35 years |
European, African unspecified, NR | 98.3% White European, 1.7% Black/Other | UKB | PCE Prospective Cohort (lipid-lowering treatment performed) |
| PSS000393 | Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
100.0 % Male samples |
Mean = 55.8 years Sd = 8.3 years |
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified | 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry | UKB | QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed) |
| PSS000394 | Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
100.0 % Male samples |
Mean = 55.8 years Sd = 8.3 years |
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified | 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry | UKB | QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed) |
| PSS000395 | Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
0.0 % Male samples |
Mean = 56.0 years Sd = 8.01 years |
European, African unspecified, NR | 98.3% White European, 1.7% Black/Other | UKB | PCE Prospective Cohort (lipid-lowering treatment performed) |
| PSS000396 | Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
0.0 % Male samples |
Mean = 56.0 years Sd = 8.01 years |
European, African unspecified, NR | 98.3% White European, 1.7% Black/Other | UKB | PCE Prospective Cohort (lipid-lowering treatment performed) |
| PSS000397 | Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
0.0 % Male samples |
Mean = 56.0 years Sd = 8.0 years |
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified | 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry | UKB | QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed) |
| PSS000398 | Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
0.0 % Male samples |
Mean = 56.0 years Sd = 8.0 years |
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified | 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry | UKB | QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed) |
| PSS000399 | Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
41.8 % Male samples |
Mean = 55.9 years Range = [40.0, 69.0] years |
European, African unspecified, NR | 98.3% White European, 1.7% Black/Other | UKB | PCE Prospective Cohort (lipid-lowering treatment performed) |
| PSS000400 | Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
41.8 % Male samples |
Mean = 55.9 years Range = [40.0, 69.0] years |
European, African unspecified, NR | 98.3% White European, 1.7% Black/Other | UKB | PCE Prospective Cohort (lipid-lowering treatment performed) |
| PSS000401 | Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
41.0 % Male samples |
Range = [40.0, 69.0] years | European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified | 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry | UKB | QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed) |
| PSS000402 | Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings | Mean = 8.01 years Sd = 1.04 years |
[ ,
41.0 % Male samples |
Range = [40.0, 69.0] years | European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified | 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry | UKB | QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed) |
| PSS012039 | ICD-9 Diagnosis: 4400, 44020, 44021, 44022, 44023, 44024, 44029, 44030, 44031, 44032, 4404, 4408, 4439, 4471 ICD-10 Diagnosis: I700, I70201, I70202, I70203, I70209, I70211, I70212, I70213, I70219, I70221, I70222, I70223, I7025, I70229, I70231, I70232, I70233, I70234, I70235, I70238, I70239, I70241, I70242, I70243, I70244, I70245, I70248, I70249, I70261, I70262, I70263, I70269, I70291, I70292, I70293, I70299, I70301, I70302, I70303, I70309, I70311, I70312, I70313, I70319, I70321, I70322, I70323, I70329, I70331, I70332, I70333, I70334, I70335, I70338, I70339, I70341, I70342, I70343, I70344, I70345, I70348, I70349, I70361, I70362, I70363, I70369, I70391, I70392, I70393, I70399, I70401, I70402, I70403, I70409, I70411, I70412, I70413, I70419, I70421, I70422, I70423, I70429, I70431, I70432, I70433, I70434, I70435, I70438, I70439, I70441, I70442, I70443, I70444, I70445, I70448, I70449, I70461, I70462, I70463, I70469, I70491, I70492, I70493, I70499, I70501, I70502, I70503, I70509, I70511, I70512, I70513, I70519, I70521, I70522, I70523, I70529, I70531, I70532, I70533, I70534, I70535, I70538, I70539, I70541, I70542, I70543, I70544, I70545, I70548, I70549, I70561, I70562, I70563, I70569, I70591, I70592, I70593, I70599, I70601, I70602, I70603, I70609, I70611, I70612, I70613, I70619, I70621, I70622, I70623, I70629, I70631, I70632, I70633, I70634, I70635, I70638, I70639, I70641, I70642, I70643, I70644, I70645, I70648, I70649, I70661, I70662, I70663, I70669, I70691, I70692, I70693, I70699, I70701, I70702, I70703, I70709, I70711, I70712, I70713, I70719, I70721, I70722, I70723, I70729, I70731, I70732, I70733, I70734, I70735, I70738, I70739, I70741, I70742, I70743, I70744, I70745, I70748, I70749, I70761, I70762, I70763, I70769, I70791, I70792, I70793, I70799, I7092, I739, I771 CPT: 93668, 27290, 27295, 27590, 27592, 27594, 27596, 27598, 27880, 27881, 27882, 27884, 27886, 27888, 35302, 35303, 35304, 35305, 35306, 35331, 35351, 35355, 35361, 35363, 35371, 35372, 35452, 35454, 35456, 35459, 35470, 35472, 35473, 35474, 35481, 35482, 35483, 35485, 35491, 35492, 35493, 35495, 35521, 35533, 35537, 35538, 35539, 35540, 35548, 35549, 35551, 35556, 35558, 35563, 35565, 35566, 35571, 35583, 35585, 35587, 35621, 35623, 35637, 35638, 35646, 35647, 35654, 35656, 35661, 35663, 35665, 35666, 35671, 35876, 35879, 35881, 35883, 35884, 37220, 37221, 37222, 37223, 37224, 37225, 37226, 37227, 37228, 37229, 37230, 37231, 37232, 37233, 37234, 37235, 35381, 35541, 35546, 35582, 35651, 35641 ICD-9 Procedure: 38.18, 39.25, 39.29, 39.5, 39.9, 84.1, 84.12, 84.13, 84.14, 84.15, 84.16, 84.17, 84.18, 84.19, 84.3 ICD-10 Procedure: 041C***, 041D***, 041F***, 041H***, 041J***, 041K***, 041L***, 041M***, 041N***, 041U***, 0470***, 047C***, 047D***, 047E***, 047F***, 047H***, 047J***, 047K***, 047L***, 047M***, 047N***, 047P***, 047Q***, 047R***, 047S***, 047T***, 047U***, 047V***, 047W***, 047Y***, 04C0***, 04CC***, 04CD***, 04CE***, 04CF***, 04CH***, 04CJ***, 04CK***, 04CL***, 04CM***, 04CN***, 04CP***, 04CQ***, 04CR***, 04CS***, 04CT***, 04CU***, 04CV***, 04CW***, 04CY***, 0Y62***, 0Y63***, 0Y68***, 0Y6C***, 0Y6D***, 0Y6F***, 0Y6G***, 0Y6H***, 0Y6J***, 0Y6M***, 0Y6N*** | Median = 2.32 years | [
|
— | East Asian | — | AllofUs | — |
| PSS012040 | ICD-9 Diagnosis: 4400, 44020, 44021, 44022, 44023, 44024, 44029, 44030, 44031, 44032, 4404, 4408, 4439, 4471 ICD-10 Diagnosis: I700, I70201, I70202, I70203, I70209, I70211, I70212, I70213, I70219, I70221, I70222, I70223, I7025, I70229, I70231, I70232, I70233, I70234, I70235, I70238, I70239, I70241, I70242, I70243, I70244, I70245, I70248, I70249, I70261, I70262, I70263, I70269, I70291, I70292, I70293, I70299, I70301, I70302, I70303, I70309, I70311, I70312, I70313, I70319, I70321, I70322, I70323, I70329, I70331, I70332, I70333, I70334, I70335, I70338, I70339, I70341, I70342, I70343, I70344, I70345, I70348, I70349, I70361, I70362, I70363, I70369, I70391, I70392, I70393, I70399, I70401, I70402, I70403, I70409, I70411, I70412, I70413, I70419, I70421, I70422, I70423, I70429, I70431, I70432, I70433, I70434, I70435, I70438, I70439, I70441, I70442, I70443, I70444, I70445, I70448, I70449, I70461, I70462, I70463, I70469, I70491, I70492, I70493, I70499, I70501, I70502, I70503, I70509, I70511, I70512, I70513, I70519, I70521, I70522, I70523, I70529, I70531, I70532, I70533, I70534, I70535, I70538, I70539, I70541, I70542, I70543, I70544, I70545, I70548, I70549, I70561, I70562, I70563, I70569, I70591, I70592, I70593, I70599, I70601, I70602, I70603, I70609, I70611, I70612, I70613, I70619, I70621, I70622, I70623, I70629, I70631, I70632, I70633, I70634, I70635, I70638, I70639, I70641, I70642, I70643, I70644, I70645, I70648, I70649, I70661, I70662, I70663, I70669, I70691, I70692, I70693, I70699, I70701, I70702, I70703, I70709, I70711, I70712, I70713, I70719, I70721, I70722, I70723, I70729, I70731, I70732, I70733, I70734, I70735, I70738, I70739, I70741, I70742, I70743, I70744, I70745, I70748, I70749, I70761, I70762, I70763, I70769, I70791, I70792, I70793, I70799, I7092, I739, I771 CPT: 93668, 27290, 27295, 27590, 27592, 27594, 27596, 27598, 27880, 27881, 27882, 27884, 27886, 27888, 35302, 35303, 35304, 35305, 35306, 35331, 35351, 35355, 35361, 35363, 35371, 35372, 35452, 35454, 35456, 35459, 35470, 35472, 35473, 35474, 35481, 35482, 35483, 35485, 35491, 35492, 35493, 35495, 35521, 35533, 35537, 35538, 35539, 35540, 35548, 35549, 35551, 35556, 35558, 35563, 35565, 35566, 35571, 35583, 35585, 35587, 35621, 35623, 35637, 35638, 35646, 35647, 35654, 35656, 35661, 35663, 35665, 35666, 35671, 35876, 35879, 35881, 35883, 35884, 37220, 37221, 37222, 37223, 37224, 37225, 37226, 37227, 37228, 37229, 37230, 37231, 37232, 37233, 37234, 37235, 35381, 35541, 35546, 35582, 35651, 35641 ICD-9 Procedure: 38.18, 39.25, 39.29, 39.5, 39.9, 84.1, 84.12, 84.13, 84.14, 84.15, 84.16, 84.17, 84.18, 84.19, 84.3 ICD-10 Procedure: 041C***, 041D***, 041F***, 041H***, 041J***, 041K***, 041L***, 041M***, 041N***, 041U***, 0470***, 047C***, 047D***, 047E***, 047F***, 047H***, 047J***, 047K***, 047L***, 047M***, 047N***, 047P***, 047Q***, 047R***, 047S***, 047T***, 047U***, 047V***, 047W***, 047Y***, 04C0***, 04CC***, 04CD***, 04CE***, 04CF***, 04CH***, 04CJ***, 04CK***, 04CL***, 04CM***, 04CN***, 04CP***, 04CQ***, 04CR***, 04CS***, 04CT***, 04CU***, 04CV***, 04CW***, 04CY***, 0Y62***, 0Y63***, 0Y68***, 0Y6C***, 0Y6D***, 0Y6F***, 0Y6G***, 0Y6H***, 0Y6J***, 0Y6M***, 0Y6N*** | Median = 2.32 years | [
|
— | European | — | AllofUs | — |
| PSS012041 | ICD-9 Diagnosis: 4400, 44020, 44021, 44022, 44023, 44024, 44029, 44030, 44031, 44032, 4404, 4408, 4439, 4471 ICD-10 Diagnosis: I700, I70201, I70202, I70203, I70209, I70211, I70212, I70213, I70219, I70221, I70222, I70223, I7025, I70229, I70231, I70232, I70233, I70234, I70235, I70238, I70239, I70241, I70242, I70243, I70244, I70245, I70248, I70249, I70261, I70262, I70263, I70269, I70291, I70292, I70293, I70299, I70301, I70302, I70303, I70309, I70311, I70312, I70313, I70319, I70321, I70322, I70323, I70329, I70331, I70332, I70333, I70334, I70335, I70338, I70339, I70341, I70342, I70343, I70344, I70345, I70348, I70349, I70361, I70362, I70363, I70369, I70391, I70392, I70393, I70399, I70401, I70402, I70403, I70409, I70411, I70412, I70413, I70419, I70421, I70422, I70423, I70429, I70431, I70432, I70433, I70434, I70435, I70438, I70439, I70441, I70442, I70443, I70444, I70445, I70448, I70449, I70461, I70462, I70463, I70469, I70491, I70492, I70493, I70499, I70501, I70502, I70503, I70509, I70511, I70512, I70513, I70519, I70521, I70522, I70523, I70529, I70531, I70532, I70533, I70534, I70535, I70538, I70539, I70541, I70542, I70543, I70544, I70545, I70548, I70549, I70561, I70562, I70563, I70569, I70591, I70592, I70593, I70599, I70601, I70602, I70603, I70609, I70611, I70612, I70613, I70619, I70621, I70622, I70623, I70629, I70631, I70632, I70633, I70634, I70635, I70638, I70639, I70641, I70642, I70643, I70644, I70645, I70648, I70649, I70661, I70662, I70663, I70669, I70691, I70692, I70693, I70699, I70701, I70702, I70703, I70709, I70711, I70712, I70713, I70719, I70721, I70722, I70723, I70729, I70731, I70732, I70733, I70734, I70735, I70738, I70739, I70741, I70742, I70743, I70744, I70745, I70748, I70749, I70761, I70762, I70763, I70769, I70791, I70792, I70793, I70799, I7092, I739, I771 CPT: 93668, 27290, 27295, 27590, 27592, 27594, 27596, 27598, 27880, 27881, 27882, 27884, 27886, 27888, 35302, 35303, 35304, 35305, 35306, 35331, 35351, 35355, 35361, 35363, 35371, 35372, 35452, 35454, 35456, 35459, 35470, 35472, 35473, 35474, 35481, 35482, 35483, 35485, 35491, 35492, 35493, 35495, 35521, 35533, 35537, 35538, 35539, 35540, 35548, 35549, 35551, 35556, 35558, 35563, 35565, 35566, 35571, 35583, 35585, 35587, 35621, 35623, 35637, 35638, 35646, 35647, 35654, 35656, 35661, 35663, 35665, 35666, 35671, 35876, 35879, 35881, 35883, 35884, 37220, 37221, 37222, 37223, 37224, 37225, 37226, 37227, 37228, 37229, 37230, 37231, 37232, 37233, 37234, 37235, 35381, 35541, 35546, 35582, 35651, 35641 ICD-9 Procedure: 38.18, 39.25, 39.29, 39.5, 39.9, 84.1, 84.12, 84.13, 84.14, 84.15, 84.16, 84.17, 84.18, 84.19, 84.3 ICD-10 Procedure: 041C***, 041D***, 041F***, 041H***, 041J***, 041K***, 041L***, 041M***, 041N***, 041U***, 0470***, 047C***, 047D***, 047E***, 047F***, 047H***, 047J***, 047K***, 047L***, 047M***, 047N***, 047P***, 047Q***, 047R***, 047S***, 047T***, 047U***, 047V***, 047W***, 047Y***, 04C0***, 04CC***, 04CD***, 04CE***, 04CF***, 04CH***, 04CJ***, 04CK***, 04CL***, 04CM***, 04CN***, 04CP***, 04CQ***, 04CR***, 04CS***, 04CT***, 04CU***, 04CV***, 04CW***, 04CY***, 0Y62***, 0Y63***, 0Y68***, 0Y6C***, 0Y6D***, 0Y6F***, 0Y6G***, 0Y6H***, 0Y6J***, 0Y6M***, 0Y6N*** | Median = 2.32 years | [
|
— | Hispanic or Latin American | — | AllofUs | — |
| PSS012067 | ICD-10: I00-I99 | Median = 12.1 years | [
|
— | East Asian | — | CKB | — |
| PSS008617 | — | — | 6,465 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS004642 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004643 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004644 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004645 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004646 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS012068 | incident aortic stenosis (using ICD and CPT codes) | — | [
|
— | European | — | AllofUs | — |
| PSS008638 | — | — | 6,660 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008639 | — | — | 6,492 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008640 | — | — | 6,617 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008641 | — | — | 6,397 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008642 | — | — | 6,648 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008643 | — | — | 6,641 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008644 | — | — | 6,521 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008645 | — | — | 6,542 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008646 | — | — | 6,566 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008647 | — | — | 6,014 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS004672 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004673 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004674 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004675 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004676 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS008649 | — | — | 6,440 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008650 | — | — | 6,570 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS012083 | — | — | [
|
— | European (Finnish) |
— | FINRISK | — |
| PSS012088 | — | — | [ ,
63.8 % Male samples |
Mean = 66.4 years | East Asian (Japanese) |
— | BBJ | — |
| PSS004711 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004712 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004713 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004714 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004715 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS012090 | Atrial fibrillation or flutter | — | 12,677 individuals | — | European | — | MHI | — |
| PSS012091 | Atrial fibrillation or flutter | — | 5,152 individuals, 0.0 % Male samples |
— | European | — | MHI | — |
| PSS012092 | Atrial fibrillation or flutter | — | 7,525 individuals | — | European | — | MHI | — |
| PSS004721 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004722 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004723 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004724 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004725 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004726 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004727 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004728 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004729 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004730 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004731 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004732 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004733 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004734 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004735 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004736 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004737 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004738 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004739 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004740 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004621 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS012099 | — | — | [
|
— | European, African unspecified, South Asian, East Asian, Hispanic or Latin American, Other | — | PMB | — |
| PSS012103 | — | — | 277 individuals | — | African unspecified | — | REPRIEVE | — |
| PSS012103 | — | — | 379 individuals | — | European | — | REPRIEVE | — |
| PSS012103 | — | — | 6 individuals | — | East Asian | — | REPRIEVE | — |
| PSS004746 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004747 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004748 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004749 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004750 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS001168 | Cases were individulas with prevalent CHD was obtained by self-report of a coronary bypass, myocardial infarction, or any of the following: coronary angioplasty, balloon angioplasty, atherectomy, stent, percutaneous transluminal coronary angioplasty, or percutaneous coronary intervention. CHD information was similarly obtained in LLFS and FamHS; however, CHD was only validated by hospital records in FamHS. Age-at-onset was defined as the individual's age at the first report of CHD. | — | [ ,
46.25 % Male samples |
Mean = 60.6 years | European | — | FamHS, LLFS | — |
| PSS010030 | PheCode 401.1 (http://phewascatalog.org/); Binary | — | [
|
— | European | — | UKB | — |
| PSS011223 | — | — | [
|
— | European | — | EB | — |
| PSS012103 | — | — | 1 individuals | — | South Asian | — | REPRIEVE | — |
| PSS004756 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004757 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004758 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004759 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004760 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS007762 | — | — | 2,470 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS011234 | I9_STR, ICD10: I61 | I63 | I64 (exclude I636), ICD9:431|4330A|4331A|4339A|4340A|4341A|4349A|436 | — | [
|
— | European | — | FinnGen | — |
| PSS012106 | — | — | 32,360 individuals, 54.4 % Male samples |
— | European | — | UKB | — |
| PSS007763 | — | — | 2,407 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS012110 | — | — | 348,967 individuals, 42.4 % Male samples |
Mean = 56.36 years Sd = 8.05 years |
European | — | UKB | — |
| PSS012109 | — | — | 8,749 individuals, 67.8 % Male samples |
Mean = 66.1 years Sd = 7.77 years |
European | — | JUPITER | — |
| PSS012108 | — | — | 14,298 individuals, 76.3 % Male samples |
Mean = 62.85 years Sd = 8.82 years |
European | — | FOURIER | — |
| PSS007764 | — | — | 2,435 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS011247 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS010047 | — | — | [
|
— | European | — | UKB | — |
| PSS007766 | — | — | 2,283 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS000439 | National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9. | — | [ ,
47.3 % Male samples |
Mean (Age At Baseline) = 48.0 years | European (Finnish) |
— | FINRISK | FINRISK surveys from 1992, 1997, 2002 and 2007 |
| PSS000440 | Coronary heart disease was defined as Myocardial infarction|Myocardial infarction, strict|Complications following myocardial infarction|Prior myocardial infactrion|Angina pectoris|Other coronary atherosclerosis|Coronary artery bypass graft**|Coronary angioplasty**. ICD9/10 codes are listed in Table S9. National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. | — | [ ,
47.3 % Male samples |
Mean (Age At Baseline) = 48.0 years | European (Finnish) |
— | FINRISK | FINRISK surveys from 1992, 1997, 2002 and 2007 |
| PSS000442 | National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9. | — | [ ,
43.7 % Male samples |
Mean (Age At Baseline) = 59.2 years Sd = 16.6 years |
European (Finnish) |
— | FinnGen | — |
| PSS010050 | Participants without history of stroke, coronary heart disease, peripheral vascular disease, or congestive heart failure at recruitment | — | 454,756 individuals | — | Not reported | — | UKB | — |
| PSS012891 | 339.0, 346,G43, G44.00, G44.01, G44.02, G44.03, G44.04 | — | [ ,
46.9 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS000445 | Coronary heart disease was defined as Myocardial infarction|Myocardial infarction, strict|Complications following myocardial infarction|Prior myocardial infactrion|Angina pectoris|Other coronary atherosclerosis|Coronary artery bypass graft**|Coronary angioplasty**. ICD9/10 codes are listed in Table S9. National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. | — | [ ,
43.7 % Male samples |
Mean (Age At Baseline) = 59.2 years Sd = 16.6 years |
European (Finnish) |
— | FinnGen | — |
| PSS011263 | — | — | [
|
— | European | — | HUNT | — |
| PSS007768 | — | — | 2,423 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS012892 | 339.0, 346,G43, G44.00, G44.01, G44.02, G44.03, G44.04 | — | [ ,
46.9 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS007769 | — | — | 2,467 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS011276 | — | — | [
|
— | European | — | UKB | — |
| PSS000454 | Cause of death under ICD-10 code | Median = 7.7 years | [
|
— | East Asian (Japanese) |
— | BBJ | — |
| PSS000455 | Cause of death under ICD-10.CHF code | Median = 7.7 years | [
|
— | East Asian (Japanese) |
— | BBJ | — |
| PSS000456 | Cause of death under ICD-10.I codes | Median = 7.7 years | [
|
— | East Asian (Japanese) |
— | BBJ | — |
| PSS000457 | Cause of death under ICD-10.IHD code | Median = 7.7 years | [
|
— | East Asian (Japanese) |
— | BBJ | — |
| PSS000458 | Cause of death under ICD-10.J codes | Median = 7.7 years | [
|
— | East Asian (Japanese) |
— | BBJ | — |
| PSS000459 | CAD was defined as a composite of stable angina, unstable angina and myocardial infarction. The disease definitions are dependent on the physician's diagnosis based on general medical practices following relevant guidelines and according to the clinical symptoms and diagnotic tests. | — | [ ,
84.0 % Male samples |
— | East Asian (Japanese) |
— | BBJ | — |
| PSS011290 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS010059 | — | Median = 2.3 years | [
|
— | European | — | FOURIER | — |
| PSS000460 | Atrial fibrillation was defined as a clinical history of AF or atrial flutter (AFL) and/or AF(L) on baseline electrocardiogram. Patients were regarded as having sinus rhythm if they had no history of AF and sinus rhythm on baseline ECG. HFpEF defined as LVEF >/= 50% | — | [
|
— | European | — | BIOSTAT-CHF | BIOSTAT-CHF study included patients from 11 European countries. Patients from Scotland were included in the vaidation cohort between October 2010 and April 2014 |
| PSS000461 | Atrial fibrillation was defined as a clinical history of AF or atrial flutter (AFL) and/or AF(L) on baseline electrocardiogram. Patients were regarded as having sinus rhythm if they had no history of AF and sinus rhythm on baseline ECG.HFrEF defined as LVEF <40% | — | [
|
— | European | — | BIOSTAT-CHF | BIOSTAT-CHF study included patients from 11 European countries. Patients from Scotland were included in the vaidation cohort between October 2010 and April 2014 |
| PSS000462 | Atrial fibrillation was defined as a clinical history of AF or atrial flutter (AFL) and/or AF(L) on baseline electrocardiogram. Patients were regarded as having sinus rhythm if they had no history of AF and sinus rhythm on baseline ECG. | — | [ ,
70.0 % Male samples |
Mean = 72.8 years Sd = 11.5 years |
European | — | BIOSTAT-CHF | BIOSTAT-CHF study included patients from 11 European countries. Patients from Scotland were included in the vaidation cohort between October 2010 and April 2014 |
| PSS010060 | — | [ ,
41.0 % Male samples |
— | Not reported | — | MDC | — | |
| PSS000467 | Individuals were free of CAD at time of enrollment. CAD was defined as (1)fatal or nonfatal myocardial infarction: defined based on either International Classification of Diseases, Ninth Revision (ICD-9) code 410 or Tenth Revision (ICD-10) code I21, (2)coronary artery bypass graft surgery: defined as procedure codes 3065, 3066, 3068, 3080, 3092, 3105, 3127 or 3158 (the Op6 system) or procedure code FN (the KKA97 system), (3)percutaneous coronary intervention, (4)death due to CAD: defined as ICD-9 codes 412 and 414 or ICD-10 codes I22, I23 and I25. | Median = 21.3 years IQR = [16.1, 23.1] years |
[ ,
38.7 % Male samples |
Mean = 57.9 years | European, NR | European=28286, NR=270 | MDC | — |
| PSS000468 | Individuals were free of CAD at time of enrollment. CAD was defined as (1)fatal or nonfatal myocardial infarction: defined based on either International Classification of Diseases, Ninth Revision (ICD-9) code 410 or Tenth Revision (ICD-10) code I21, (2)coronary artery bypass graft surgery: defined as procedure codes 3065, 3066, 3068, 3080, 3092, 3105, 3127 or 3158 (the Op6 system) or procedure code FN (the KKA97 system), (3)percutaneous coronary intervention, (4)death due to CAD: defined as ICD-9 codes 412 and 414 or ICD-10 codes I22, I23 and I25. All individuals included had measured cholesterol concentrations. | Median = 23.2 years IQR = [17.6, 24.2] years |
[ ,
41.16 % Male samples |
— | European, NR | European=5640, NR=45 | MDC-CC | Cardiovascular Cohort |
| PSS000469 | Individuals were free of CAD at time of enrollment. CAD was defined based on hospitalisation with or death due to ICD-10 codes for acute or subsequent myocaridal infarction (I21, I22, I23, I24.1, and I25.2); or hospitalisation with ICD-9 codes for myocaridal. infarction (410, 411, and 412); or hospitalisation with OPCS-4 (Office of Population Censuses and Surveys) codes. for coronary artery bypass grafting (K40, K41, and K45) or coronary angioplasty with or without stenting (K49, K50.2, and K75). | Median = 8.1 years IQR = [7.4, 8.8] years |
[ ,
44.2 % Male samples |
Mean = 56.8 years | European, African unspecified, South Asian, East Asian, NR | European=304270, African unspecified=5760, South Asian=6832, East Asian (Chinese)=1117, NR=7024 | UKB | — |
| PSS011296 | 22,667 sibling pairs | — | 45,334 individuals | — | European | — | UKB | — |
| PSS008842 | — | — | 3,732 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS009630 | Entry to the trial had required a history of acute coronary syndrome 3–36 months previously, and patients were in the trial for a mean of 36 months. 1558 deaths, 898 cardiovascular deaths, 727 CHD deaths and 375 cancer deaths | Mean = 36.0 months | [ ,
84.0 % Male samples |
Mean = 60.2 years Sd = 8.41 years |
European | — | NR | LIPID (Long-term Intervention with Pravastatin in Ischaemic Disease) randomised controlled trial |
| PSS008861 | — | — | 3,924 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008862 | — | — | 3,793 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008863 | — | — | 3,858 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008864 | — | — | 3,769 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008865 | — | — | 3,905 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008866 | — | — | 3,912 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008867 | — | — | 3,806 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008868 | — | — | 3,861 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008869 | — | — | 3,878 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008870 | — | — | 3,611 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008872 | — | — | 3,828 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008873 | — | — | 3,882 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS011312 | — | — | 22,701 individuals, 27.8 % Male samples |
— | European | — | ARIC, CHS, FHS, MESA, WHI | — |
| PSS011312 | — | — | 8,822 individuals, 31.9 % Male samples |
— | African American or Afro-Caribbean | — | 6 cohorts
|
— |
| PSS011312 | — | — | 6,718 individuals, 38.0 % Male samples |
— | Hispanic or Latin American | — | CHS, FHS, HCHS-SOL, MESA, WHI | — |
| PSS011312 | — | — | 794 individuals, 37.9 % Male samples |
— | Asian unspecified | — | MESA, WHI | — |
| PSS011313 | To define prevalent CAD, we selected participants with ICD-10 codes for MI (I21.X, I22.X, I23.X, I24.1, or I25.2), for other acute ischemic heart disease (I24.0, I24.8-9) and for atherosclerotic / chronic ischemic heart disease (I25.0-25.1, I25.5-25.9). Procedure codes for coronary artery bypass grafting (K40.1-40.4, K41.1-41.4, K45.1-45.5), for coronary angioplasty, with or without stenting (K49.1-49.2, K49.8-49.9, K50.2, K75.1-75.4, K75.8-75.9) were also added to the CAD definition. | Mean = 11.0 years | [ ,
46.0 % Male samples |
Mean = 56.93 years | European (White British) |
— | UKB | — |
| PSS011315 | The patients were hospitalized with a diagnosis of and treatment for an ST-segment elevation myocardial infarction or non-ST-segment elevation myocardial infarction; they were ≤50 years old and had undergone PCI at three hospitals. | Median = 43.0 months | [ ,
63.82 % Male samples |
— | East Asian (Korean) |
— | KGP | — |
| PSS011316 | Cases were individuals with repeat revascularizations. The patients were hospitalized with a diagnosis of and treatment for an ST-segment elevation myocardial infarction or non-ST-segment elevation myocardial infarction; they were ≤50 years old and had undergone PCI at three hospitals. | [
|
— | East Asian (Korean) |
— | KGP | — | |
| PSS011317 | The cardiovascular disease patients (cases) were diagnosed by a licensed medical doctor based on events (e.g. angina, myocardial infarction, stroke) and/or interventions (e.g. coronary angioplasty/stenting, coronary artery bypass grafting, carotid endarterectomy). | — | [ ,
51.42 % Male samples |
— | East Asian (Han Chinese) |
— | NR | — |
| PSS011318 | — | — | 18,505 individuals, 81.9 % Male samples |
Mean = 55.4 years Sd = 11.8 years |
African American or Afro-Caribbean | — | MVP | — |
| PSS011319 | — | — | 6,785 individuals, 86.5 % Male samples |
Mean = 52.6 years Sd = 14.8 years |
Hispanic or Latin American | — | MVP | — |
| PSS011320 | — | — | 53,861 individuals, 88.2 % Male samples |
Mean = 59.3 years Sd = 13.8 years |
European | — | MVP | — |
| PSS010105 | ICD codes I67.1 and I60 | — | [
|
— | European (Norwegian) |
— | HUNT2 | — |
| PSS009875 | Ischemic stroke | — | [
|
— | East Asian (Japanese) |
— | BBJ | % Male: 70.0% for cases and 53.1% for controls. Age information: Mean (cases) = 69.2 years, sd (cases) = 10.8; Mean (controls) = 66.5 years, sd (controls) = 12.5 |
| PSS000504 | Participants with no prior Coronary Heart Disease (CHD) at the time of enrollment were included within the present study. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. | Median = 11.6 years Sd = 3.7 years |
[ ,
47.5 % Male samples |
Mean = 58.9 years Sd = 7.6 years |
European | — | HNR | — |
| PSS000505 | — | — | [
|
— | European | — | HNR | — |
| PSS000506 | Male participants with no prior Coronary Heart Disease (CHD) at the time of enrollment were included within the present study. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. | — | [ ,
100.0 % Male samples |
— | European | — | HNR | — |
| PSS000507 | Participants with no prior Coronary Heart Disease (CHD) at the time of enrollment were included within the present study. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. Cardiovascular risk factor data required included smoking status, current use of medication, body mass index, levels of serum triglycerides, low densitity lipoprotein-cholesterol and high densitity lipoprotein-cholesterol and diabetes defined as either of 4 criteria (1) participants reported a history of clinically diagnosed diabetes, (2) participants took glucose-lowering medications, (3) participants had fasting glucose levels of greater than 125mg/dL or (4) participants had non-fasting glucose levels of 200mg/dL or greater. | — | [
|
— | European | — | HNR | — |
| PSS000508 | — | — | [
|
— | European | — | HNR | — |
| PSS000509 | Participants with no prior Coronary Heart Disease (CHD) at the time of enrollment with coronary artery calcification>0 were included. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. Cardiovascular risk factor data required included smoking status, current use of medication, body mass index, levels of serum triglycerides, low densitity lipoprotein-cholesterol and high densitity lipoprotein-cholesterol and diabetes defined as either of 4 criteria (1) participants reported a history of clinically diagnosed diabetes, (2) participants took glucose-lowering medications, (3) participants had fasting glucose levels of greater than 125mg/dL or (4) participants had non-fasting glucose levels of 200mg/dL or greater. | — | [
|
— | European | — | HNR | — |
| PSS000510 | Male participants with no prior Coronary Heart Disease (CHD) at the time of enrollment were included within the present study. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. Cardiovascular risk factor data required included smoking status, current use of medication, body mass index, levels of serum triglycerides, low densitity lipoprotein-cholesterol and high densitity lipoprotein-cholesterol and diabetes defined as either of 4 criteria (1) participants reported a history of clinically diagnosed diabetes, (2) participants took glucose-lowering medications, (3) participants had fasting glucose levels of greater than 125mg/dL or (4) participants had non-fasting glucose levels of 200mg/dL or greater. | — | [ ,
100.0 % Male samples |
— | European | — | HNR | — |
| PSS000511 | Male participants with no prior Coronary Heart Disease (CHD) at the time of enrollment with coronary artery calcification>0 were included. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. Cardiovascular risk factor data required included smoking status, current use of medication, body mass index, levels of serum triglycerides, low densitity lipoprotein-cholesterol and high densitity lipoprotein-cholesterol and diabetes defined as either of 4 criteria (1) participants reported a history of clinically diagnosed diabetes, (2) participants took glucose-lowering medications, (3) participants had fasting glucose levels of greater than 125mg/dL or (4) participants had non-fasting glucose levels of 200mg/dL or greater. | — | [ ,
100.0 % Male samples |
— | European | — | HNR | — |
| PSS009876 | Ischemic stroke | — | [
|
— | European | — | NR | ClinicalTrials_EUR |
| PSS009877 | Ischemic stroke | Mean = 4.6 years Sd = 4.8 years |
[ ,
37.8 % Male samples |
Mean = 44.0 years Sd = 15.7 years |
European (Estonian) |
— | EB | — |
| PSS009878 | Ischemic stroke | — | [
|
— | African American or Afro-Caribbean (African American) |
— | MVP | — |
| PSS010119 | Atherosclerotic cardiovacular disease (ASCVD), comprising non-fatal acute myocardial infarction, death of cardiovascular origin (comprising sudden death, ischemic death) and fatal and non-fatal ischaemic stroke (including transient ischaemic attack) using relevant medical records and ICD codes. All events were adjudicated by two expert. More details in PMID: 33838036 | Median = [10.7, 14.6] years | [ ,
45.0 % Male samples |
Mean = 52.3 years | European | — | CoLaus | right censored was death or latest evidence of good health, participant with statine therapy at baseline were excluded |
| PSS010120 | Atherosclerotic cardiovacular disease (ASCVD), comprising non-fatal acute myocardial infarction, death of cardiovascular origin (comprising sudden death, ischemic death) and fatal and non-fatal ischaemic stroke (including transient ischaemic attack) using relevant medical records and ICD codes. All events were adjudicated by two expert. More details in PMID: 33838036 | Median = [10.6, 14.6] years | [ ,
47.0 % Male samples |
Mean = 53.4 years | European | — | CoLaus | right censored was death or latest evidence of good health |
| PSS010121 | Coronary artery disease (CAD), ccomprising either non-fatal myocardial infarction, death from coronary heart disease or symptomatic stable angina followed by a revascularization procedure, either by percutaneous coronary intervention (PCI), or by coronary artery bypass grafting (CABG) using relevant medical records and ICD codes. All events were adjudicated by two expert. More details in PMID: 33838036 | Median = [10.7, 14.6] years | [ ,
45.0 % Male samples |
Mean = 52.3 years | European | — | CoLaus | right censored was death or latest evidence of good health, participant with statine therapy at baseline were excluded |
| PSS010122 | Coronary artery disease (CAD), ccomprising either non-fatal myocardial infarction, death from coronary heart disease or symptomatic stable angina followed by a revascularization procedure, either by percutaneous coronary intervention (PCI), or by coronary artery bypass grafting (CABG) using relevant medical records and ICD codes. All events were adjudicated by two expert. More details in PMID: 33838036 | Median = [10.6, 14.6] years | [ ,
47.0 % Male samples |
Mean = 53.4 years | European | — | CoLaus | right censored was death or latest evidence of good health |
| PSS000514 | ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x) | — | [ ,
42.7 % Male samples |
Mean = 57.0 years | European, Hispanic or Latin American, African unspecified | African unspecified=6979, European=10344, Hispanic or Latin American=7048 | BioMe | — |
| PSS000515 | ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x) | — | 6,979 individuals | — | African unspecified | — | BioMe | — |
| PSS000516 | ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x) | — | 10,344 individuals | — | European | — | BioMe | — |
| PSS000517 | ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x) | — | 7,048 individuals | — | Hispanic or Latin American | — | BioMe | — |
| PSS000518 | ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x) | — | [ ,
45.0 % Male samples |
Mean = 60.0 years | European, African unspecified, Hispanic or Latin American, East Asian, South Asian | African unspecified=867, East Asian=167, European=11725, Hispanic or Latin American=799, South Asian=109 | PHB | — |
| PSS000519 | ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x) | — | [ ,
59.0 % Male samples |
Mean = 68.0 years | European, African unspecified | African unspecified=1927, European=7143 | PMB | — |
| PSS000520 | ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x) | — | [ ,
46.52 % Male samples |
Mean = 59.6 years | European, African unspecified, Hispanic or Latin American, East Asian, South Asian | African unspecified=9773, East Asian=167, European=29212, Hispanic or Latin America=7847, South Asian=109 | BioMe, PHB, PMB | — |
| PSS011337 | — | — | [ ,
46.0 % Male samples |
— | European (White British) |
— | UKB | — |
| PSS011339 | — | — | [ ,
46.0 % Male samples |
— | European (White British) |
— | UKB | — |
| PSS010126 | — | — | [
|
— | European (U.K.) |
— | UKB | — |
| PSS012292 | Balanced case/control cohort: cases from UK Biobank hospital/EHR & self-report; equal number of super-controls (no cardiac/metabolic disease) matched on age and sex. | — | 10,135 individuals | — | European | — | UKB | — |
| PSS012293 | Balanced case/control cohort: cases from UK Biobank hospital/EHR & self-report; equal number of super-controls (no cardiac/metabolic disease) matched on age and sex. | — | 12,832 individuals | — | European | — | UKB | — |
| PSS012294 | Balanced case/control cohort: cases from UK Biobank hospital/EHR & self-report; equal number of super-controls (no cardiac/metabolic disease) matched on age and sex. | — | 27,939 individuals | — | European | — | UKB | — |
| PSS012295 | Balanced case/control cohort: cases from UK Biobank hospital/EHR & self-report; equal number of super-controls (no cardiac/metabolic disease) matched on age and sex. | — | 2,553 individuals | — | European | — | UKB | — |
| PSS012296 | Balanced case/control cohort: cases from UK Biobank hospital/EHR & self-report; equal number of super-controls (no cardiac/metabolic disease) matched on age and sex. | — | 8,142 individuals | — | European | — | UKB | — |
| PSS012297 | Balanced case/control cohort: cases from UK Biobank hospital/EHR & self-report; equal number of super-controls (no cardiac/metabolic disease) matched on age and sex. | — | 14,172 individuals | — | European | — | UKB | — |
| PSS004620 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS010137 | Incident MI was defined by the general International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10), code I21 and its subcodes I210-I214 and I219. | — | 330,201 individuals, 43.0 % Male samples |
Median = 57.0 years | European | — | UKB | — |
| PSS012304 | Balanced case/control cohort: cases from UK Biobank hospital/EHR & self-report; equal number of super-controls (no cardiac/metabolic disease) matched on age and sex. | — | 7,838 individuals | — | European | — | UKB | — |
| PSS012305 | Balanced case/control cohort: cases from UK Biobank hospital/EHR & self-report; equal number of super-controls (no cardiac/metabolic disease) matched on age and sex. | — | 5,984 individuals | — | European | — | UKB | — |
| PSS012306 | Balanced case/control cohort: cases from UK Biobank hospital/EHR & self-report; equal number of super-controls (no cardiac/metabolic disease) matched on age and sex. | — | 16,433 individuals | — | European | — | UKB | — |
| PSS011357 | — | — | 14,298 individuals | — | European | — | FOURIER | — |
| PSS011358 | ICD-10 codes (I21, I22, I23, I24.1, and I25.2), ICD-9 codes (410, 411, 412, and 429.79) for MI, ICD-10 (I63, I64), ICD-9 (434 and 436) for IS | — | 454,493 individuals | — | European | — | UKB | Mean age of full combined ancestry cohort = 56.9 years |
| PSS012311 | — | — | [ ,
40.3 % Male samples |
Mean = 64.0 years Sd = 8.6 years |
European | — | NR | — |
| PSS012312 | — | — | 31,118 individuals | — | European | — | 14 cohorts
|
— |
| PSS012312 | — | — | 11,124 individuals | — | African American or Afro-Caribbean | — | 8 cohorts
|
— |
| PSS012312 | — | — | 4,325 individuals | — | Hispanic or Latin American | — | BioMe, MESA, WHI | — |
| PSS012312 | — | — | 2,663 individuals | — | East Asian | — | KoGES, MESA, WHI | — |
| PSS012313 | — | Median = 20.3 years Range = [19.4, 21.5] years |
[ ,
33.0 % Male samples |
Mean = 51.2 years Sd = 11.8 years |
Hispanic or Latin American (Mexican) |
— | MCPS | — |
| PSS012064 | The aortic stenosis PRS was tested for its association with aortic stenosis using safety data from the TIMI trials. Aortic stenosis was called for any adverse event referencing aortic stenosis, including new or worsening aortic stenosis. | — | [
|
— | European (European) |
— | ENGAGE_AF-TIMI_48, FOURIER, PEGASUS-TIMI_54, SAVOR-TIMI_53, SOLID-TIMI_52 | These data also include samples from DECLARE-TIMI 58 (not in the cohort refr. List) |
| PSS012314 | — | — | 43,338 individuals, 100.0 % Male samples |
Mean = 52.0 years Sd = 12.1 years |
Hispanic or Latin American (Mexican) |
— | MCPS | — |
| PSS012315 | — | — | 89,869 individuals, 0.0 % Male samples |
Mean = 50.8 years Sd = 11.7 years |
Hispanic or Latin American (Mexican) |
— | MCPS | — |
| PSS011364 | — | — | 56,192 individuals | — | European | — | UKB | — |
| PSS012065 | IAVGC phenotype definition (see detailed description in manuscript) | — | [
|
— | European (European) |
— | UCLA | — |
| PSS012066 | IAVGC phenotype definition (see detailed description in manuscript) | — | [
|
Mean = 62.1 years | European (European) |
— | UKB | — |
| PSS013125 | 430, 431, 432,I60.0, I60.1, I60.2, I60.3, I60.4, I60.5, I60.6, I60.7, I60.8, I60.9, I61, I62.0, I62.1, I62.9 | — | [ ,
44.71 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS010158 | — | — | [
|
— | African American or Afro-Caribbean | — | MVP | — |
| PSS010159 | — | — | [
|
— | Hispanic or Latin American | — | MVP | — |
| PSS010160 | — | — | [
|
— | African American or Afro-Caribbean | — | MVP | — |
| PSS010161 | — | — | [
|
— | Hispanic or Latin American | — | MVP | — |
| PSS010162 | — | — | [
|
— | European | — | MVP | — |
| PSS010163 | — | — | [
|
— | European | — | MVP | — |
| PSS011375 | — | — | 93 individuals | — | European | Admixed European (n=3) | NR | — |
| PSS011375 | — | — | 1 individuals | — | East Asian | — | NR | — |
| PSS011375 | — | — | 1 individuals | — | South Asian | Admixed South Asian (n=1) | NR | — |
| PSS001445 | All individuals had a history of incident atrial fibrillation (AF) following enrollment. 2,310 individuals were taking warfarin. Cases were individuals with ischemic stroke (IS). IS was defined uisng the UKB codes: 131368, 42008. Of the 2,310 individuals taking warfarin, 93 were individuals with ischemic stroke (cases). | Median = 7.0 years | [ ,
66.7 % Male samples |
European | — | UKB | — | |
| PSS011378 | — | — | 5,740 individuals, 46.0 % Male samples |
Median = 52.0 years IQR = [48.0, 56.0] years |
European | — | ARIC | — |
| PSS011379 | — | — | 2,154 individuals, 45.0 % Male samples |
Median = 43.0 years IQR = [41.0, 45.0] years |
European | — | FOS | — |
| PSS011380 | — | — | 1,863 individuals, 46.0 % Male samples |
Median = 30.0 years IQR = [26.0, 34.0] years |
European | — | FOS | — |
| PSS010177 | — | Median = 28.0 years | 2,484 individuals | — | African unspecified | — | ARIC | — |
| PSS010178 | — | Median = 28.0 years | 8,808 individuals | — | European | — | ARIC | — |
| PSS011387 | — | — | [ ,
0.0 % Male samples |
— | European (Finnish) |
— | FinnGen | — |
| PSS010179 | The test cohort consisted of individuals without a history of ICH at baseline and anticoagulant use defined by self-report in the verbal interview at inclusion. Furthermore, individuals were included if they had a diagnosis of the International Classification of Diseases, Tenth Revision code Z92.1 (personal history of long-term (current) use of anticoagulants) or D68.3 (hemorrhagic disorder due to circulating anticoagulants) at baseline or a prescription of an anticoagulant medication between baseline and 6 months thereafter in the primary care data | Mean = 11.9 years | [ ,
69.0 % Male samples |
Mean = 62.0 years | European | — | UKB | — |
| PSS010179 | The test cohort consisted of individuals without a history of ICH at baseline and anticoagulant use defined by self-report in the verbal interview at inclusion. Furthermore, individuals were included if they had a diagnosis of the International Classification of Diseases, Tenth Revision code Z92.1 (personal history of long-term (current) use of anticoagulants) or D68.3 (hemorrhagic disorder due to circulating anticoagulants) at baseline or a prescription of an anticoagulant medication between baseline and 6 months thereafter in the primary care data | Mean = 11.9 years | [ ,
69.0 % Male samples |
Mean = 62.0 years | Not reported | — | UKB | — |
| PSS011388 | — | — | [ ,
0.0 % Male samples |
— | European (Finnish) |
— | FinnGen | — |
| PSS011389 | — | Median = 8.2 years | 21,824 individuals, 43.4 % Male samples |
Median = 63.1 years | European | — | GERA | — |
| PSS013127 | 434.01, 434.11, 434.91,I63.0, I63.3, I63.4, I63.5, I63.6, I63.8, I63.9 | — | [ ,
45.27 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS010183 | Incident AF was defined as International Classification of Diseases (ICD) edition 10 (codes I48, I48.0, I48.1, I48.2, I48.3, I48.4, I48.9) and operative procedures (codes K62.1, K62.2, K62.3, K62.4) | Median = 6.16 years | 62,927 individuals, 43.87 % Male samples |
Mean = 62.48 years | European | — | UKB | — |
| PSS011390 | CVD ICD-10: I20-I25, I60-I64, G45 | — | 12,780 individuals, 0.0 % Male samples |
— | European | — | UKB | Mean age of full combined ancestry cohort = 58.8 years (sd = 7.1) |
| PSS011390 | CVD ICD-10: I20-I25, I60-I64, G45 | — | 568 individuals, 0.0 % Male samples |
— | Not reported | — | UKB | Mean age of full combined ancestry cohort = 58.8 years (sd = 7.1) |
| PSS009063 | — | — | 4,032 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS012544 | 228,D18 | — | [ ,
46.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS012546 | 228,D18 | — | [ ,
46.0 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS013128 | 434.01, 434.11, 434.91,I63.0, I63.3, I63.4, I63.5, I63.6, I63.8, I63.9 | — | [ ,
45.27 % Male samples |
— | East Asian (Han Chinese) |
— | TPMI | — |
| PSS009084 | — | — | 4,136 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009085 | — | — | 4,021 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009086 | — | — | 4,113 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009087 | — | — | 3,980 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009088 | — | — | 4,128 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009089 | — | — | 4,121 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009090 | — | — | 4,046 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009091 | — | — | 4,042 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009092 | — | — | 4,063 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009093 | — | — | 3,734 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS011403 | Cases were individuals with atrial fibrillation (AF). Individuals were classified as having AF if the arrhythmia was present on an ECG obtained at a study visit or encounter with external clinicians, Holter monitoring, or noted in hospital records. Study investigators reviewed all available records to determine dates of AF. Two physicians adjudicated first-detected AF events. | — | [ ,
44.6 % Male samples |
Mean = 59.4 years Sd = 15.5 years |
European, Not reported | — | FHS | — |
| PSS009095 | — | — | 3,955 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009096 | — | — | 4,066 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS011406 | Cases were individuals with atrial fibrillation (AF). Cases were identified using using self-report, ICD 9/10 codes, or cause of death records and where available, codes for specific AF-related procedures (e.g., percutaneous transluminal ablation of pulmonary vein) were also utilized in the AF definition. The complete list of clinical factor definitions is shown in supplemental Table I. | — | [ ,
45.3 % Male samples |
Mean = 56.9 years Sd = 8.1 years |
European, Not reported | — | UKB | Possible sample overlap between this dataset and the dataset used to develop/train PGS000035. |
| PSS011412 | — | — | 370,121 individuals | — | European | — | UKB | — |
| PSS011412 | — | — | 54,290 individuals | — | Not reported | — | UKB | — |
| PSS012201 | — | — | 7,482 individuals | — | European | — | OOA | — |
| PSS012201 | — | — | 1,520 individuals | — | African American or Afro-Caribbean | — | OOA | — |
| PSS012201 | — | — | 113 individuals | — | Hispanic or Latin American | — | OOA | — |