| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0004264 |
| Description | A general term used to describe any disease affecting blood vessels]. It includes vascular abnormalities caused by degenerative, metabolic and inflammatory conditions, embolic diseases, coagulative disorders, and functional disorders such as posteri or reversible encephalopathy syndrome. | Trait category |
Cardiovascular disease
|
| Synonyms |
9 synonyms
|
| Mapped terms |
14 mapped terms
|
| Child trait(s) |
22 child traits
|
| 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 disease | 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 disease | 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 disease | 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 disease | 6,630,150 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000013/ScoringFiles/PGS000013.txt.gz | |
| PGS000018 (metaGRS_CAD) |
PGP000007 | Inouye M et al. J Am Coll Cardiol (2018) |
Coronary artery disease | coronary artery disease | 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 disease | 192 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000019/ScoringFiles/PGS000019.txt.gz |
| PGS000038 (PRS90) |
PGP000026 | Rutten-Jacobs LC et al. BMJ (2018) |
Stroke | stroke | 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 | stroke, Ischemic stroke |
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 disease | 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 disease | 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 disease | 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 disease | 40,079 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000116/ScoringFiles/PGS000116.txt.gz | |
| PGS000200 (GRS28) |
PGP000082 | Tikkanen E et al. Arterioscler Thromb Vasc Biol (2013) |
Coronary heart disease | coronary artery disease | 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 disease | 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 disease | 6,423,165 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000329/ScoringFiles/PGS000329.txt.gz | |
| PGS000337 (MetaPRS_CAD) |
PGP000104 | Koyama S et al. Nat Genet (2020) |
Coronary artery disease | coronary artery disease | 75,028 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000337/ScoringFiles/PGS000337.txt.gz |
| PGS000349 (PRS70_CAD) |
PGP000114 | Pechlivanis S et al. BMC Med Genet (2020) |
Coronary artery disease | coronary artery disease | 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 | stroke, Ischemic stroke |
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 | hypertension | 186,726 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000706/ScoringFiles/PGS000706.txt.gz |
| PGS000746 (PRS_UKB) |
PGP000152 | Gola D et al. Circ Genom Precis Med (2020) |
Coronary artery disease | coronary artery disease | 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 disease | 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 disease | 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 disease | 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 | |
| PGS000798 (157SNP_GRS) |
PGP000187 | Severance LM et al. J Cardiovasc Comput Tomogr (2019) |
Coronary heart disease | coronary artery disease | 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 disease | 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 |
| PGS000899 (PRS176_CHD) |
PGP000232 | Feitosa MF et al. Circ Genom Precis Med (2021) |
Coronary heart disease | coronary artery disease | 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 | stroke, Ischemic stroke |
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) | Phlebitis, Thrombophlebitis |
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 disease | 36 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001025/ScoringFiles/PGS001025.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 |
| PGS001277 (GBE_HC203) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
PE +/- DVT | pulmonary embolism, deep vein thrombosis |
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 | pulmonary embolism, deep vein thrombosis |
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 | pulmonary embolism, deep vein thrombosis |
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 |
| PGS001320 (GBE_HC215) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Hypertension | hypertension | 13,791 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001320/ScoringFiles/PGS001320.txt.gz |
| PGS001355 (CAD_AnnoPred_PRS) |
PGP000252 | Ye Y et al. Circ Genom Precis Med (2021) |
Coronary artery disease | coronary artery disease | 2,994,055 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001355/ScoringFiles/PGS001355.txt.gz | |
| PGS001780 (CHD_PRSCS) |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Coronary heart disease | coronary artery disease | 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 |
| PGS001793 (1kgeur_gbmi_leaveUKBBout_Stroke_pst_eff_a1_b0.5_phiauto) |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Stroke | stroke | 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 | 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 | hypertension | 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 |
| 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 | Phlebitis, Thrombophlebitis |
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 disease | 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 | hypertension | 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 |
| 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 | Phlebitis, Thrombophlebitis |
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 disease | 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 disease | 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 | 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 disease | 540 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002262/ScoringFiles/PGS002262.txt.gz | |
| PGS002296 (PRS2166_HT) |
PGP000326 | Maj C et al. Front Cardiovasc Med (2022) |
Hypertension | hypertension | 2,166 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002296/ScoringFiles/PGS002296.txt.gz | |
| PGS002335 (disease_HYPERTENSION_DIAGNOSED.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertension | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002335/ScoringFiles/PGS002335.txt.gz |
| PGS002407 (disease_HYPERTENSION_DIAGNOSED.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertension | 6,693 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002407/ScoringFiles/PGS002407.txt.gz |
| PGS002456 (disease_HYPERTENSION_DIAGNOSED.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertension | 22,539 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002456/ScoringFiles/PGS002456.txt.gz |
| PGS002505 (disease_HYPERTENSION_DIAGNOSED.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertension | 115,656 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002505/ScoringFiles/PGS002505.txt.gz |
| PGS002554 (disease_HYPERTENSION_DIAGNOSED.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertension | 1,715 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002554/ScoringFiles/PGS002554.txt.gz |
| PGS002603 (disease_HYPERTENSION_DIAGNOSED.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertension | 949 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002603/ScoringFiles/PGS002603.txt.gz |
| PGS002652 (disease_HYPERTENSION_DIAGNOSED.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertension | 385,766 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002652/ScoringFiles/PGS002652.txt.gz |
| PGS002701 (disease_HYPERTENSION_DIAGNOSED.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Hypertension | hypertension | 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 | stroke, Ischemic stroke |
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 | stroke, Ischemic stroke |
6,010,730 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002725/ScoringFiles/PGS002725.txt.gz | |
| PGS002765 (SBP_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Hypertension | hypertension | 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 | 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 |
| PGS002775 (GTG_CAD_maxCT) |
PGP000365 | Wong CK et al. PLoS One (2022) |
Incident coronary artery disease | coronary artery disease | 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 disease | 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 | hypertension | 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 | hypertension | 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 disease | 205 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002809/ScoringFiles/PGS002809.txt.gz |
| PGS002994 (ExPRSweb_Hypertension_20002-1065_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Hypertension | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 disease | 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 disease | 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 K et al. medRxiv (2023) |Pre |
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 disease | 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 disease | 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 | |
| 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 disease | 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 disease | 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 disease | 1,125,113 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003727/ScoringFiles/PGS003727.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 disease | 10,440 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003866/ScoringFiles/PGS003866.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 M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 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 M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 2,371 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004000/ScoringFiles/PGS004000.txt.gz | |
| PGS004015 (lassosum.CV.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 65,138 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004015/ScoringFiles/PGS004015.txt.gz | |
| PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 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 M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 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 M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 852,173 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004054/ScoringFiles/PGS004054.txt.gz | |
| PGS004070 (megaprs.CV.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 852,173 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004070/ScoringFiles/PGS004070.txt.gz | |
| PGS004084 (prscs.auto.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 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 M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 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 M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 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 M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 5,808 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004124/ScoringFiles/PGS004124.txt.gz | |
| PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 888,649 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004138/ScoringFiles/PGS004138.txt.gz | |
| PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 1,116,976 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004154/ScoringFiles/PGS004154.txt.gz | |
| PGS004191 (hyper_1) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Hypertension | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 disease | 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 disease | 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 disease | 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 disease | 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 disease | 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 | hypertension | 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 | hypertension | 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 disease | 1,146,511 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004237/ScoringFiles/PGS004237.txt.gz | |
| PGS004321 (PRS27_CAD) |
PGP000554 | Marston NA et al. Circulation (2019) |
Coronary heart disease | coronary artery disease | 27 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004321/ScoringFiles/PGS004321.txt.gz |
| PGS004443 (disease.CAD.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Coronary artery disease (CAD) | coronary artery disease | 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 disease | 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 | hypertension | 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 |
| 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 |
| 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 |
| PGS004513 (meta.CAD.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Coronary artery disease (CAD) | coronary artery disease | 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 disease | 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 | hypertension | 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 |
| 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 |
| 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 disease | 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 disease | 64 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004596/ScoringFiles/PGS004596.txt.gz |
| PGS004696 (multi_anc_hg37CSx) |
PGP000602 | Smith JL et al. Circ Genom Precis Med (2024) |
Coronary heart disease | coronary artery disease | 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 disease | 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 disease | 542,218 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004698/ScoringFiles/PGS004698.txt.gz | |
| PGS004743 (cad_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Coronary artery disease | coronary artery disease | 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 disease | 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 disease | 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 disease | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | hypertension | 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 | 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 | 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 |
|
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 |
| 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 | — |
| 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] | — | — | — | — |
| 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 |
| 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 | — |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 | — |
| 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 | — |
| 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] |
— | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 |
| 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) |
| 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 | — |
| 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) | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — | — | — |
| 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 | — |
| 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 |
| 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 | — |
| 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 | — |
| 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 | — |
| 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) | — |
| 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) | — |
| 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 | — |
| 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) | — |
| 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) | — |
| 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 |
| 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 |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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] | — | — |
| 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] | — | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 |
| 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 | — |
| 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 | — |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 | — |
| 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] | — | — |
| 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 | — |
| PPM000518 | PGS000018 (metaGRS_CAD) |
PSS000287| European Ancestry| 1,319 individuals |
PGP000077 | Timmerman N et al. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
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. medRxiv (2019) |Ext.|Pre |
Reported Trait: Secondary cardiovascular events | HR: 1.15 [1.02, 1.29] | — | — | Age, sex, diabetes, BMI, smoking, hypercholesterolemia, array, 4 genetics PCs | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 |
| 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. |
| 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] | — | — | — | — |
| 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] | — | — | — | — |
| 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] | — | — | — | — |
| 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] | — | — | — | — |
| 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 | — |
| 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] | — | — | — | — |
| 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] | — | — | — | — |
| 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] | — | — | — | — |
| 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 | — |
| 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 |
| 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] | — | — | — |
| 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 | — |
| 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] | — | — | — | — |
| 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) |
| 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. |
| 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 | — |
| 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 | — |
| 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. |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 |
| 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 | — |
| 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 | — |
| 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 |
| 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. |
| 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 | — |
| 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 | — |
| 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) | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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] | — | — | — |
| 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 | — |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 |
| 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 | — |
| 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 | — |
| 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 | — |
| 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] | — | — | — |
| 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 |
| 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 |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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] | — | — |
| 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] | — | — | — |
| 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 | — |
| 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). | — |
| 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 | — |
| 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) | — |
| 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] | — | — |
| 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] | — | — |
| 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] | — | — |
| 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] | — | — |
| 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] | — | — |
| 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] | — | — |
| 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] | — | — |
| 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] | — | — |
| 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] | — | — | — |
| 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. | — |
| 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 | — |
| 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 | — |
| 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) | — |
| 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] | — | — | — | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 |
| 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 |
| 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] | PGS R2 (no covariates): 0.00898 R²: 0.04621 Incremental AUROC (full-covars): 0.02759 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] | PGS R2 (no covariates): 0.00527 R²: 0.03299 Incremental AUROC (full-covars): 0.00984 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 |
| 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 |
| 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) | — |
| 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] | — | — | — | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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] | — | — |
| 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) | — |
| 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) | — |
| 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 | — |
| 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 | — |
| 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 |
| 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 | — |
| 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] | — | — | — | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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] | — | — | — |
| 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 | — |
| 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] | — | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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) | — |
| 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) | — |
| 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) | — |
| 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) | — |
| 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) | — |
| 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] | — | — | — | — |
| 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 | — |
| 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 | — | — | — |
| 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 | — |
| 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 | — | — | — |
| 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 | — |
| 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 | — | — | — |
| 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 | — |
| 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 | — | — | — |
| 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 | — |
| 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 | — | — | — |
| 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 | — |
| 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 | — | — | — |
| PPM017103 | PGS003429 (AAA) |
PSS010126| European Ancestry| 91,731 individuals |
PGP000436 | Kelemen M K et al. medRxiv (2023) |Pre |
Reported Trait: Abdominal aortic aneurysm | — | AUROC: 0.708 [0.691, 0.725] | R²: 0.00547 | — | — |
| 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] | — | — | — |
| 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] | — | — | — | — |
| 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] | — | — | — | — |
| 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) | — |
| 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) | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| PPM019449 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12083 β: 0.11407 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019450 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15341 β: 0.14273 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019451 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09189 β: 0.08791 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019452 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12141 β: 0.11459 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019453 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18126 β: 0.16658 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019454 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20912 β: 0.1899 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019497 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09992 β: 0.09524 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019499 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.03582 β: 0.0352 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019500 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12602 β: 0.11869 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019501 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.05895 β: 0.05728 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019502 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12993 β: 0.12215 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019498 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12015 β: 0.11346 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019503 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10789 β: 0.10246 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019504 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14267 β: 0.13337 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019505 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10577 β: 0.10054 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019506 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12027 β: 0.11357 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019507 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18187 β: 0.1671 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019508 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17792 β: 0.16375 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019467 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10756 β: 0.10216 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019468 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16199 β: 0.15013 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019469 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13492 β: 0.12656 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019470 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1247 β: 0.11752 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019471 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23606 β: 0.21193 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019472 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21946 β: 0.19841 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019431 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.11588 β: 0.10965 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019432 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16332 β: 0.15128 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019433 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1116 β: 0.1058 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019434 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13921 β: 0.13033 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019435 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21092 β: 0.19138 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019436 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20936 β: 0.19009 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019473 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12005 β: 0.11337 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019474 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16971 β: 0.15675 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019475 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09218 β: 0.08817 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019476 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1469 β: 0.13706 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019477 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23492 β: 0.211 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019478 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21483 β: 0.1946 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019479 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12262 β: 0.11566 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019480 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17236 β: 0.15902 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019481 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09524 β: 0.09097 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019482 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14508 β: 0.13548 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019483 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.24252 β: 0.21714 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019484 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.22477 β: 0.20275 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019491 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10161 β: 0.09677 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019492 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15354 β: 0.14283 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019493 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1249 β: 0.1177 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019494 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10581 β: 0.10058 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019495 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23758 β: 0.21316 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019496 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20497 β: 0.18646 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019485 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10211 β: 0.09723 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019486 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15335 β: 0.14267 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019487 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14227 β: 0.13302 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019488 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.11617 β: 0.1099 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019489 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23173 β: 0.20842 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019490 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.19231 β: 0.17589 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019437 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08291 β: 0.07965 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019438 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06579 β: 0.06372 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019439 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 0.97393 β: -0.02642 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019440 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06709 β: 0.06493 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019441 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 0.99729 β: -0.00271 |
AUROC: 0.5 | — | 0 | beta = log(or)/sd_pgs |
| PPM019442 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08405 β: 0.0807 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019443 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06894 β: 0.06667 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019444 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10078 β: 0.09602 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019445 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12773 β: 0.12021 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019446 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10772 β: 0.1023 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019447 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14403 β: 0.13455 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019448 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13266 β: 0.12457 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019455 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08855 β: 0.08485 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019456 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14381 β: 0.13436 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019457 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09703 β: 0.09261 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019458 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09561 β: 0.09131 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019459 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15035 β: 0.14007 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019460 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20185 β: 0.18386 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019462 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17327 β: 0.15979 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019463 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08287 β: 0.07961 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019464 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14197 β: 0.13276 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019466 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23115 β: 0.20795 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019461 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12873 β: 0.1211 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019465 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18096 β: 0.16632 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| 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 | — |
| 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 | — |
| 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 | — |
| 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) | — |
| 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 | — | — |
| 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 | — | — | — | — |
| 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 | — | — | — | — |
| 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 | — | — | — | — |
| 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 | — | — | — | — |
| 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 | — | — | — | — |
| 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 | — | — | — | — |
| 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 | — | — | — | — |
| 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 | — | — | — | — |
| 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 | — | — | — | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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) |
| 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) |
| 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) |
| 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) |
|
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 |
|---|---|---|---|---|---|---|---|---|
| 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 |
| 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 | — |
| PSS011442 | — | — | [ ,
77.0 % Male samples |
Mean = 26.7 years | European | — | PDAY | — |
| PSS011441 | — | — | [ ,
82.0 % Male samples |
Mean = 27.5 years | African unspecified | — | PDAY | — |
| 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 | — |
| 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 |
| 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 |
| PSS009289 | — | — | 19,330 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS011465 | — | — | 9,462 individuals | — | European | — | AllofUs | — |
| PSS009310 | — | — | 20,000 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009311 | — | — | 19,308 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 | — |
| 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 | — |
| 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 |
| 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 | — |
| 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 |
| 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 | — |
| 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 | — |
| PSS009513 | — | — | [
|
— | East Asian (Japanese) |
— | BBJ | — |
| PSS009517 | — | — | [
|
— | European (Estonian) |
— | EB | — |
| PSS003605 | — | — | [
|
Mean = 56.81 years | European | — | UKB | — |
| PSS009521 | — | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS009525 | — | — | [
|
— | European | Norwegian | HUNT | — |
| PSS009529 | — | — | [
|
— | African American or Afro-Caribbean | — | MGBB | — |
| PSS009533 | — | — | [
|
— | European | — | MGBB | — |
| PSS009537 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS009541 | — | — | [
|
— | European | British | UKB | — |
| PSS009545 | — | — | [
|
— | South Asian | — | UKB | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| PSS007700 | — | — | [
|
— | African unspecified | Africa or admixed-ancestry diaspora | UKB | — |
| PSS007705 | — | — | [
|
— | Asian unspecified | Central and South Asian | UKB | — |
| PSS007707 | — | — | [
|
— | European | — | UKB | — |
| PSS007716 | — | — | [
|
— | European | — | UKB | — |
| PSS007719 | — | — | [
|
— | European | — | UKB | — |
| PSS007739 | — | — | 2,385 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007757 | — | — | 2,484 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007758 | — | — | 2,396 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007762 | — | — | 2,470 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS000822 | — | — | 87,413 individuals | — | European | — | UKB | — |
| PSS007763 | — | — | 2,407 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007765 | — | — | 2,444 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS003790 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS003791 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS003792 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS003793 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS003794 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| 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 |
| PSS003795 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS003796 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS003797 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS003798 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS003799 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS007768 | — | — | 2,423 individuals | — | African American or Afro-Caribbean | Carribean | 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 | — |
| 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 | — |
| 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 |
| PSS009654 | — | — | [ ,
61.0 % Male samples |
— | European | — | NR | — |
| 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 | — |
| 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) |
| PSS010956 | — | — | [
|
— | European | — | HUNT | — |
| 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) |
| PSS007974 | — | — | 1,810 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007975 | — | — | 1,794 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 | — |
| PSS010981 | — | — | [ ,
46.0 % Male samples |
Mean = 52.83 years | European | — | CoLaus | — |
| PSS007982 | — | — | 1,794 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007983 | — | — | 1,622 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007985 | — | — | 1,785 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007986 | — | — | 1,790 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS004014 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004015 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004016 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004017 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004018 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 | — |
| 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 |
| 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 | — |
| PSS008192 | — | — | 6,331 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008193 | — | — | 6,070 individuals | — | South Asian | India (South Asia) | UKB | — |
| 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 |
| 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 | — |
| PSS009879 | Ischemic stroke | — | [
|
— | European (European) |
— | MVP | — |
| PSS009880 | Ischemic stroke | — | [
|
— | Sub-Saharan African (Nigerian) |
— | NR | Stroke Investigative Research & Educational Network (SIREN) |
| PSS009881 | Ischemic stroke | — | [
|
— | East Asian (Taiwanese) |
— | TWB | — |
| PSS008200 | — | — | 6,258 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008201 | — | — | 5,719 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008203 | — | — | 6,161 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008204 | — | — | 6,220 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008198 | — | — | 6,173 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008197 | — | — | 6,308 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008199 | — | — | 6,205 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS011090 | — | — | [ ,
46.34 % Male samples |
— | East Asian (Han Chinese) |
— | CURES_China | — |
| PSS009922 | — | — | [
|
— | European | — | NR | — |
| PSS011097 | — | — | 2,669 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Arab) |
— | NR | N total after excluding missing values = 2,553 |
| 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) |
| 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 | — |
| 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 | — | |
| 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 | — |
| PSS008393 | — | — | 1,162 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS009958 | — | — | 21,863 individuals, 0.0 % Male samples |
Mean = 65.3 years | European (Non-Hispanic White) |
— | WHI | — |
| PSS009960 | — | — | 172,066 individuals, 100.0 % Male samples |
Mean = 57.8 years | Not reported | — | UKB | — |
| PSS009961 | — | — | 208,627 individuals, 0.0 % Male samples |
Mean = 57.4 years | Not reported | — | UKB | — |
| 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 | — |
| PSS009962 | — | — | 359,310 individuals, 44.6 % Male samples |
Mean = 69.05 years Sd = 8.04 years |
Not reported | — | 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 | — |
| 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 | — |
| 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 | — |
| PSS008419 | — | — | 1,183 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| 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 | — |
| PSS009986 | — | — | [ ,
47.0 % Male samples |
— | Greater Middle Eastern (Middle Eastern, North African or Persian) (Qatari) |
— | QBB | — |
| 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 | — |
| 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 | — |
| 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) |
| 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 | — |
| PSS011200 | — | — | [
|
— | European | — | 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) |
| 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) |
| 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) |
| 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) |
| 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 | — |
| 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) |
| PSS004619 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| 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) |
| PSS004620 | — | — | [
|
— | South Asian | — | UKB | — |
| 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) |
| PSS004621 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| 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) |
| 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) |
| 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) |
| PSS008638 | — | — | 6,660 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008639 | — | — | 6,492 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 | — |
| 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) |
| PSS010008 | PheCode 401.1 (http://phewascatalog.org/); Binary | — | [
|
— | European | — | MGI | — |
| 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) |
| PSS010030 | PheCode 401.1 (http://phewascatalog.org/); Binary | — | [
|
— | European | — | UKB | — |
| PSS011223 | — | — | [
|
— | European | — | EB | — |
| 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 | — |
| 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) |
| PSS011234 | I9_STR, ICD10: I61 | I63 | I64 (exclude I636), ICD9:431|4330A|4331A|4339A|4340A|4341A|4349A|436 | — | [
|
— | European | — | FinnGen | — |
| 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 | — |
| 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 |
| PSS010050 | Participants without history of stroke, coronary heart disease, peripheral vascular disease, or congestive heart failure at recruitment | — | 454,756 individuals | — | Not reported | — | UKB | — |
| 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 | — |
| 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 | — |
| 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 | — |
| PSS008861 | — | — | 3,924 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008862 | — | — | 3,793 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 | — | 6 cohorts
|
— |
| 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 | — | |
| 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 | — |
| 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 | — |
| 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 | — |
| PSS010126 | — | — | [
|
— | European (U.K.) |
— | 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 | — |
| PSS011357 | — | — | 14,298 individuals | — | European | — | FOURIER | — |
| PSS011364 | — | — | 56,192 individuals | — | European | — | UKB | — |
| 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 | — |
| 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 | — |
| 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 | — |
| PSS009084 | — | — | 4,136 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009085 | — | — | 4,021 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 | — |
| PSS009095 | — | — | 3,955 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009096 | — | — | 4,066 individuals | — | European | Poland (NE Europe) | UKB | — |