Trait: vascular disease

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
  • disease of vasculature
  • disease or disorder of vasculature
  • disorder of vasculature
  • vascular disease
  • vascular diseases
  • vascular disorder
  • vascular tissue disease
  • vasculature disease
  • vasculature disease or disorder
Mapped terms 13 mapped terms
  • DOID:178
  • ICD10:I72.9
  • ICD10:I77
  • ICD10:I78
  • ICD10:I87
  • ICD10:K55
  • ICD9:442.9
  • MESH:D014652
  • MONDO:0005385
  • MeSH:D014652
  • NCIT:C35117
  • SCTID:27550009
  • UMLS:C0042373
Child trait(s) 19 child traits

Associated Polygenic Score(s)

Filter PGS by Participant Ancestry
Individuals included in:
G - Source of Variant Associations (GWAS)
D - Score Development/Training
E - PGS Evaluation
List of ancestries includes:
Display options:
Ancestry legend
Multi-ancestry (including European)
Multi-ancestry (excluding European)
African
East Asian
South Asian
Additional Asian Ancestries
European
Greater Middle Eastern
Hispanic or Latin American
Additional Diverse Ancestries
Not Reported
Note: This table shows all PGS for "vascular disease" and any child terms of this trait in the EFO hierarchy by default.
Polygenic Score ID & Name PGS Publication ID (PGP) Reported Trait Mapped Trait(s) (Ontology) Number of Variants Ancestry distribution 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 - Check Terms/Licenses
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)
Ischaemic 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 - Check Terms/Licenses
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 - Check Terms/Licenses
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 - Check Terms/Licenses
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 - Check Terms/Licenses
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
Essential (primary hypertension) (time-to-event) primary 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. medRxiv (2021)
|Pre
Essential hypertension primary 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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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
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

Performance Metrics

Disclaimer: The performance metrics are displayed as reported by the source studies. It is important to note that metrics are not necessarily comparable with each other. For example, metrics depend on the sample characteristics (described by the PGS Catalog Sample Set [PSS] ID), phenotyping, and statistical modelling. Please refer to the source publication for additional guidance on performance.

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]
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
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
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
PPM000383 PGS000013
(GPS_CAD)
PSS000219|
European Ancestry|
11,010 individuals
PGP000057 |
Homburger JR et al. Genome Med (2019)
|Ext.
Reported Trait: Coronary artery disease (personal history) OR: 1.589 [1.32, 1.92] AUROC: 0.86 age, sex
PPM000402 PGS000013
(GPS_CAD)
PSS000227|
Additional Asian Ancestries|
544 individuals
PGP000060 |
Khera AV et al. Circulation (2019)
|Ext.
Reported Trait: Early-onset mycardial infarction (age ≤55 years) OR: 2.16 [1.35, 1.59] Odds Ratio (OR; top 5% vs. rest): 3.33 [0.82, 13.51] 4 genetic PCs
PPM000401 PGS000013
(GPS_CAD)
PSS000229|
Hispanic or Latin American Ancestry|
919 individuals
PGP000060 |
Khera AV et al. Circulation (2019)
|Ext.
Reported Trait: Early-onset mycardial infarction (age ≤55 years) OR: 1.56 [1.29, 1.88] Odds Ratio (OR; top 5% vs. rest): 3.38 [2.03, 5.64] 4 genetic PCs
PPM000400 PGS000013
(GPS_CAD)
PSS000228|
African Ancestry|
1,298 individuals
PGP000060 |
Khera AV et al. Circulation (2019)
|Ext.
Reported Trait: Early-onset mycardial infarction (age ≤55 years) OR: 1.46 [1.28, 1.66] Odds Ratio (OR; top 5% vs. rest): 2.02 [1.29, 3.16] 4 genetic PCs
PPM000399 PGS000013
(GPS_CAD)
PSS000230|
European Ancestry|
3,081 individuals
PGP000060 |
Khera AV et al. Circulation (2019)
|Ext.
Reported Trait: Early-onset mycardial infarction (age ≤55 years) OR: 2.06 [1.89, 2.25] Odds Ratio (OR; top 5% vs. rest): 5.09 [3.82, 6.78] 4 genetic PCs
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
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.
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.
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.
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]
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
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
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
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
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
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
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
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
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] : 0.087 [0.074, 0.101]
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]
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. medRxiv (2021)
|Pre
Reported Trait: Blood clot diagnosed by doctor AUROC: 0.64618 [0.56748, 0.72489] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot diagnosed by doctor AUROC: 0.83468 [0.6451, 1.0] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot diagnosed by doctor AUROC: 0.62906 [0.59189, 0.66622] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot diagnosed by doctor AUROC: 0.71068 [0.63185, 0.78951] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot diagnosed by doctor AUROC: 0.6205 [0.59778, 0.64322] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot or DVT diagnosed by doctor AUROC: 0.61925 [0.57619, 0.6623] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot or DVT diagnosed by doctor AUROC: 0.68652 [0.54244, 0.83061] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot or DVT diagnosed by doctor AUROC: 0.64786 [0.62647, 0.66925] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot or DVT diagnosed by doctor AUROC: 0.63964 [0.59263, 0.68666] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot or DVT diagnosed by doctor AUROC: 0.62837 [0.61546, 0.64128] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE essential (primary hypertension) AUROC: 0.71865 [0.70527, 0.73203] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE essential (primary hypertension) AUROC: 0.7519 [0.72118, 0.78262] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE essential (primary hypertension) AUROC: 0.74724 [0.74015, 0.75433] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE essential (primary hypertension) AUROC: 0.73072 [0.71892, 0.74253] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE essential (primary hypertension) AUROC: 0.72352 [0.71925, 0.72779] : 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. medRxiv (2021)
|Pre
Reported Trait: Essential hypertension AUROC: 0.72155 [0.708, 0.7351] : 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. medRxiv (2021)
|Pre
Reported Trait: Essential hypertension AUROC: 0.74478 [0.71204, 0.77751] : 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. medRxiv (2021)
|Pre
Reported Trait: Essential hypertension AUROC: 0.74583 [0.73846, 0.75319] : 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. medRxiv (2021)
|Pre
Reported Trait: Essential hypertension AUROC: 0.73161 [0.71966, 0.74357] : 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. medRxiv (2021)
|Pre
Reported Trait: Essential hypertension AUROC: 0.72364 [0.71923, 0.72805] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE phlebitis and thrombophlebitis AUROC: 0.63235 [0.59259, 0.67211] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE phlebitis and thrombophlebitis AUROC: 0.66631 [0.52571, 0.80691] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE phlebitis and thrombophlebitis AUROC: 0.66949 [0.64981, 0.68916] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE phlebitis and thrombophlebitis AUROC: 0.63064 [0.58623, 0.67504] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE phlebitis and thrombophlebitis AUROC: 0.64191 [0.63056, 0.65326] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE chronic ischaemic heart disease AUROC: 0.7358 [0.70724, 0.76436] PGS R2 (no covariates): 0.00275
Incremental AUROC (full-covars): 0.00137
: 0.09751
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. medRxiv (2021)
|Pre
Reported Trait: TTE chronic ischaemic heart disease AUROC: 0.76843 [0.69891, 0.83795] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE chronic ischaemic heart disease AUROC: 0.77959 [0.76878, 0.7904] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE chronic ischaemic heart disease AUROC: 0.76819 [0.75382, 0.78257] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE chronic ischaemic heart disease AUROC: 0.76113 [0.75467, 0.7676] : 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. medRxiv (2021)
|Pre
Reported Trait: Haemorrhoids / piles AUROC: 0.57317 [0.5447, 0.60164] : 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. medRxiv (2021)
|Pre
Reported Trait: Haemorrhoids / piles AUROC: 0.59643 [0.55346, 0.63941] : 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. medRxiv (2021)
|Pre
Reported Trait: Haemorrhoids / piles AUROC: 0.58423 [0.56992, 0.59855] : 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. medRxiv (2021)
|Pre
Reported Trait: Haemorrhoids / piles AUROC: 0.59907 [0.57631, 0.62183] : 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. medRxiv (2021)
|Pre
Reported Trait: Haemorrhoids / piles AUROC: 0.56311 [0.5545, 0.57173] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE nonrheumatic aortic valve disorders AUROC: 0.82312 [0.77164, 0.87459] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE nonrheumatic aortic valve disorders AUROC: 0.85035 [0.70276, 0.99795] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE nonrheumatic aortic valve disorders AUROC: 0.7688 [0.74115, 0.79645] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE nonrheumatic aortic valve disorders AUROC: 0.7872 [0.73952, 0.83487] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE nonrheumatic aortic valve disorders AUROC: 0.72257 [0.70467, 0.74046] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE vascular dementia AUROC: 0.89609 [0.78011, 1.0] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE vascular dementia AUROC: 0.86436 [0.80883, 0.91989] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE vascular dementia AUROC: 0.83842 [0.72824, 0.9486] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE vascular dementia AUROC: 0.82562 [0.78593, 0.86531] : 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. medRxiv (2021)
|Pre
Reported Trait: PE +/- DVT AUROC: 0.65081 [0.59936, 0.70226] : 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. medRxiv (2021)
|Pre
Reported Trait: PE +/- DVT AUROC: 0.8083 [0.66236, 0.95424] : 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. medRxiv (2021)
|Pre
Reported Trait: PE +/- DVT AUROC: 0.67497 [0.64702, 0.70293] : 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. medRxiv (2021)
|Pre
Reported Trait: PE +/- DVT AUROC: 0.69135 [0.62082, 0.76187] : 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. medRxiv (2021)
|Pre
Reported Trait: PE +/- DVT AUROC: 0.64659 [0.63085, 0.66233] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot in the leg (DVT) or lung AUROC: 0.59279 [0.55016, 0.63542] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot in the leg (DVT) or lung AUROC: 0.66743 [0.52454, 0.81033] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot in the leg (DVT) or lung AUROC: 0.65354 [0.63231, 0.67477] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot in the leg (DVT) or lung AUROC: 0.63523 [0.58822, 0.68224] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot in the leg (DVT) or lung AUROC: 0.63525 [0.6226, 0.64791] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot in the lung AUROC: 0.63917 [0.56071, 0.71763] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot in the lung AUROC: 0.82557 [0.62097, 1.0] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot in the lung AUROC: 0.62994 [0.59262, 0.66726] : 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. medRxiv (2021)
|Pre
Reported Trait: Blood clot in the lung AUROC: 0.71053 [0.63261, 0.78846] : 0.04621
Incremental AUROC (full-covars): 0.02759
PGS R2 (no covariates): 0.00898
PGS AUROC (no covariates): 0.60144 [0.50751, 0.69537]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008897 PGS001279
(GBE_BIN_FC8006152)
PSS004018|
European Ancestry|
67,349 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Blood clot in the lung AUROC: 0.62416 [0.60164, 0.64668] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE PE AUROC: 0.64593 [0.59381, 0.69806] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE PE AUROC: 0.80741 [0.66178, 0.95305] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE PE AUROC: 0.67617 [0.64866, 0.70368] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE PE AUROC: 0.68371 [0.61554, 0.75187] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE PE AUROC: 0.65102 [0.6355, 0.66654] : 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. medRxiv (2021)
|Pre
Reported Trait: Migraine AUROC: 0.68314 [0.64175, 0.72454] : 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. medRxiv (2021)
|Pre
Reported Trait: Migraine AUROC: 0.70929 [0.59332, 0.82526] Incremental AUROC (full-covars): 0.00197
: 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. medRxiv (2021)
|Pre
Reported Trait: Migraine AUROC: 0.65031 [0.63271, 0.66791] : 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. medRxiv (2021)
|Pre
Reported Trait: Migraine AUROC: 0.71746 [0.68326, 0.75166] PGS R2 (no covariates): 0.0051
PGS AUROC (no covariates): 0.55594 [0.51785, 0.59403]
: 0.07262
Incremental AUROC (full-covars): 0.00414
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. medRxiv (2021)
|Pre
Reported Trait: Migraine AUROC: 0.6514 [0.64118, 0.66162] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE migraine AUROC: 0.68512 [0.64613, 0.72411] : 0.04881
Incremental AUROC (full-covars): 0.00144
PGS R2 (no covariates): 0.00032
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. medRxiv (2021)
|Pre
Reported Trait: TTE migraine AUROC: 0.71233 [0.61741, 0.80724] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE migraine AUROC: 0.63835 [0.62244, 0.65426] : 0.03299
Incremental AUROC (full-covars): 0.00984
PGS R2 (no covariates): 0.00527
PGS AUROC (no covariates): 0.55358 [0.53641, 0.57074]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008911 PGS001282
(GBE_HC815)
PSS004645|
South Asian Ancestry|
7,831 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: TTE migraine AUROC: 0.71231 [0.68018, 0.74443] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE migraine AUROC: 0.64859 [0.63934, 0.65784] : 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. medRxiv (2021)
|Pre
Reported Trait: Hypertension AUROC: 0.7113 [0.69875, 0.72385] : 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. medRxiv (2021)
|Pre
Reported Trait: Hypertension AUROC: 0.75955 [0.7336, 0.78551] : 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. medRxiv (2021)
|Pre
Reported Trait: Hypertension AUROC: 0.731 [0.72434, 0.73765] : 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. medRxiv (2021)
|Pre
Reported Trait: Hypertension AUROC: 0.73444 [0.72324, 0.74564] : 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. medRxiv (2021)
|Pre
Reported Trait: Hypertension AUROC: 0.7189 [0.71489, 0.72291] : 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)
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