| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0004611 |
| Description | The measurement of LDL cholesterol in blood used as a risk indicator for heart disease. | Trait categories |
Cardiovascular measurement
Lipid or lipoprotein measurement
|
| Synonym | LDL measurement |
| Mapped terms |
2 mapped terms
|
| Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants | Ancestry distribution | Scoring File (FTP Link) |
|---|---|---|---|---|---|---|
| PGS000061 (GRS_LDL) |
PGP000045 | Johnson L et al. PLoS One (2015) |
low-density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 37 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000061/ScoringFiles/PGS000061.txt.gz |
| PGS000065 (GLGC2017_LDL) |
PGP000046 | Kuchenbaecker K et al. Nat Commun (2019) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 103 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000065/ScoringFiles/PGS000065.txt.gz |
| PGS000115 (LDL-C_20) |
PGP000053 | Trinder M et al. JAMA Cardiol (2020) |
low density lipoprotein cholesterol | low density lipoprotein cholesterol measurement | 223 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000115/ScoringFiles/PGS000115.txt.gz |
| PGS000192 (GS9) |
PGP000079 | Kathiresan S et al. N Engl J Med (2008) |
Cholesterol | low density lipoprotein cholesterol measurement, high density lipoprotein cholesterol measurement |
9 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000192/ScoringFiles/PGS000192.txt.gz |
| PGS000310 (GRS194_LDL) |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Low-density lipoprotein | low density lipoprotein cholesterol measurement | 194 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000310/ScoringFiles/PGS000310.txt.gz |
| PGS000340 (LDL-Cpsp) |
PGP000107 | Trinder M et al. Circ Genom Precis Med (2020) |
Low-density lipoprotein cholesterol levels | low density lipoprotein cholesterol measurement | 28 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000340/ScoringFiles/PGS000340.txt.gz |
| PGS000661 (PRS-LDL) |
PGP000121 | Tam CHT et al. Genome Med (2021) |
LDL cholesterol | low density lipoprotein cholesterol measurement | 84 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000661/ScoringFiles/PGS000661.txt.gz | |
| PGS000688 (snpnet.LDL_direct_adjstatins) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
LDL cholesterol [mmol/L] (statin adjusted) | low density lipoprotein cholesterol measurement | 16,184 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000688/ScoringFiles/PGS000688.txt.gz |
| PGS000814 (GRS12_LDLc) |
PGP000200 | Talmud PJ et al. Lancet (2013) |
Low-density lipoprotein cholesterol | low density lipoprotein cholesterol measurement | 12 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000814/ScoringFiles/PGS000814.txt.gz |
| PGS000824 (LDL-C_PGS) |
PGP000210 | Zubair N et al. Sci Rep (2019) |
Low-density lipoprotein cholesterol | low density lipoprotein cholesterol measurement | 809 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000824/ScoringFiles/PGS000824.txt.gz |
| PGS000846 (LDL) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Low density lipoprotein (LDL) | low density lipoprotein cholesterol measurement | 275 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000846/ScoringFiles/PGS000846.txt.gz |
| PGS000875 (PGS36_LDLc) |
PGP000221 | Leal LG et al. Mol Genet Genomic Med (2020) |
Low-density lipoprotein cholesterol | low density lipoprotein cholesterol measurement | 36 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000875/ScoringFiles/PGS000875.txt.gz | |
| PGS000886 (GLGC_2021_AFR_LDL_PRS_weights_PRS-CS) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 1,222,318 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000886/ScoringFiles/PGS000886.txt.gz |
| PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 295 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000887/ScoringFiles/PGS000887.txt.gz |
| PGS000888 (GLGC_2021_ALL_LDL_PRS_weights_PRS-CS) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 1,239,184 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000888/ScoringFiles/PGS000888.txt.gz |
| PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 9,009 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000889/ScoringFiles/PGS000889.txt.gz |
| PGS000890 (GLGC_2021_EAS_LDL_PRS_weights_PRS-CS) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 1,029,158 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000890/ScoringFiles/PGS000890.txt.gz |
| PGS000891 (GLGC_2021_EAS_LDL_PRS_weights_PT) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 66 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000891/ScoringFiles/PGS000891.txt.gz |
| PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 1,119,211 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000892/ScoringFiles/PGS000892.txt.gz |
| PGS000893 (GLGC_2021_EUR_LDL_PRS_weights_PT) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 5,427 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000893/ScoringFiles/PGS000893.txt.gz |
| PGS000894 (GLGC_2021_HIS_LDL_PRS_weights_PRS-CS) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 1,175,595 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000894/ScoringFiles/PGS000894.txt.gz |
| PGS000895 (GLGC_2021_HIS_LDL_PRS_weights_PT) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 76 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000895/ScoringFiles/PGS000895.txt.gz |
| PGS000896 (GLGC_2021_SAS_LDL_PRS_weights_PRS-CS) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 1,100,062 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000896/ScoringFiles/PGS000896.txt.gz |
| PGS000897 (GLGC_2021_SAS_LDL_PRS_weights_PT) |
PGP000230 | Graham SE et al. Nature (2021) |
Low density lipoprotein (LDL) cholesterol | low density lipoprotein cholesterol measurement | 13 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000897/ScoringFiles/PGS000897.txt.gz |
| PGS001933 (portability-PLR_LDL) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
LDL direct | low density lipoprotein cholesterol measurement | 25,604 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001933/ScoringFiles/PGS001933.txt.gz |
| PGS002150 (portability-ldpred2_LDL) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
LDL direct | low density lipoprotein cholesterol measurement | 360,007 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002150/ScoringFiles/PGS002150.txt.gz |
| PGS002274 (LDL-PRS) |
PGP000303 | Groenland EH et al. Atherosclerosis (2022) |
Low-density lipoprotein cholesterol | low density lipoprotein cholesterol measurement | 279 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002274/ScoringFiles/PGS002274.txt.gz |
| PGS002285 (GRS_286_LDL) |
PGP000313 | Kamiza AB et al. Nat Med (2022) |
Low density lipoprotein cholesterol | low density lipoprotein cholesterol measurement | 286 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002285/ScoringFiles/PGS002285.txt.gz | |
| PGS002337 (biochemistry_LDLdirect.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
LDL Cholesterol | low density lipoprotein cholesterol measurement | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002337/ScoringFiles/PGS002337.txt.gz |
| PGS002369 (biochemistry_LDLdirect.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
LDL Cholesterol | low density lipoprotein cholesterol measurement | 920,930 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002369/ScoringFiles/PGS002369.txt.gz |
| PGS002409 (biochemistry_LDLdirect.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
LDL Cholesterol | low density lipoprotein cholesterol measurement | 7,626 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002409/ScoringFiles/PGS002409.txt.gz |
| PGS002458 (biochemistry_LDLdirect.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
LDL Cholesterol | low density lipoprotein cholesterol measurement | 20,708 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002458/ScoringFiles/PGS002458.txt.gz |
| PGS002507 (biochemistry_LDLdirect.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
LDL Cholesterol | low density lipoprotein cholesterol measurement | 105,053 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002507/ScoringFiles/PGS002507.txt.gz |
| PGS002556 (biochemistry_LDLdirect.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
LDL Cholesterol | low density lipoprotein cholesterol measurement | 3,244 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002556/ScoringFiles/PGS002556.txt.gz |
| PGS002605 (biochemistry_LDLdirect.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
LDL Cholesterol | low density lipoprotein cholesterol measurement | 2,337 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002605/ScoringFiles/PGS002605.txt.gz |
| PGS002654 (biochemistry_LDLdirect.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
LDL Cholesterol | low density lipoprotein cholesterol measurement | 274,585 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002654/ScoringFiles/PGS002654.txt.gz |
| PGS002703 (biochemistry_LDLdirect.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
LDL Cholesterol | low density lipoprotein cholesterol measurement | 970,081 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002703/ScoringFiles/PGS002703.txt.gz |
| PGS002730 (GRSlipid_35) |
PGP000337 | Mayerhofer E et al. Brain (2022) |
LDL lowering in response to statin | low density lipoprotein cholesterol measurement, response to statin |
35 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002730/ScoringFiles/PGS002730.txt.gz |
| PGS003029 (ExPRSweb_LDL_30780-irnt_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
LDL | low density lipoprotein cholesterol measurement | 549,112 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003029/ScoringFiles/PGS003029.txt.gz | |
| PGS003030 (ExPRSweb_LDL_30780-irnt_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
LDL | low density lipoprotein cholesterol measurement | 2,066 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003030/ScoringFiles/PGS003030.txt.gz | |
| PGS003031 (ExPRSweb_LDL_30780-irnt_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
LDL | low density lipoprotein cholesterol measurement | 2,609 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003031/ScoringFiles/PGS003031.txt.gz | |
| PGS003032 (ExPRSweb_LDL_30780-irnt_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
LDL | low density lipoprotein cholesterol measurement | 7,457,930 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003032/ScoringFiles/PGS003032.txt.gz | |
| PGS003033 (ExPRSweb_LDL_30780-irnt_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
LDL | low density lipoprotein cholesterol measurement | 1,113,830 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003033/ScoringFiles/PGS003033.txt.gz | |
| PGS003034 (ExPRSweb_LDL_30780-raw_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
LDL | low density lipoprotein cholesterol measurement | 552,845 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003034/ScoringFiles/PGS003034.txt.gz | |
| PGS003035 (ExPRSweb_LDL_30780-raw_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
LDL | low density lipoprotein cholesterol measurement | 2,288 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003035/ScoringFiles/PGS003035.txt.gz | |
| PGS003036 (ExPRSweb_LDL_30780-raw_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
LDL | low density lipoprotein cholesterol measurement | 2,935 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003036/ScoringFiles/PGS003036.txt.gz | |
| PGS003037 (ExPRSweb_LDL_30780-raw_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
LDL | low density lipoprotein cholesterol measurement | 8,918,470 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003037/ScoringFiles/PGS003037.txt.gz | |
| PGS003038 (ExPRSweb_LDL_30780-raw_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
LDL | low density lipoprotein cholesterol measurement | 1,113,830 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003038/ScoringFiles/PGS003038.txt.gz | |
| PGS003339 (CVGRS_LDL) |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
LDL cholesterol level | low density lipoprotein cholesterol measurement | 65 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003339/ScoringFiles/PGS003339.txt.gz |
| PGS003348 (ALLGRS_LDL) |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
LDL cholesterol level | low density lipoprotein cholesterol measurement | 78 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003348/ScoringFiles/PGS003348.txt.gz |
| PGS003403 (PRS28_LDL) |
PGP000420 | Trinder M et al. J Am Coll Cardiol (2019) |
LDL cholesterol | low density lipoprotein cholesterol measurement | 28 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003403/ScoringFiles/PGS003403.txt.gz |
| PGS003404 (wGRS) |
PGP000421 | Wang J et al. Arterioscler Thromb Vasc Biol (2016) |
LDL cholesterol | low density lipoprotein cholesterol measurement | 10 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003404/ScoringFiles/PGS003404.txt.gz |
| PGS003405 (165SNP_PRS) |
PGP000422 | Vanhoye X et al. Transl Res (2022) |
LDL-c blood concentration | low density lipoprotein cholesterol measurement | 165 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003405/ScoringFiles/PGS003405.txt.gz |
|
PGS Performance Metric ID (PPM) |
Evaluated Score |
PGS Sample Set ID (PSS) |
Performance Source | Trait |
PGS Effect Sizes (per SD change) |
Classification Metrics | Other Metrics | Covariates Included in the Model |
PGS Performance: Other Relevant Information |
|---|---|---|---|---|---|---|---|---|---|
| PPM000155 | PGS000061 (GRS_LDL) |
PSS000098| European Ancestry| 2,063 individuals |
PGP000045 | Johnson L et al. PLoS One (2015) |
Reported Trait: Serum low-density lipoprotein (LDL) levels | β: 15.0 | — | Beta (p-value): 0.0352 | age, age^2, sex, GRS_HDL, GRS_TC, GRS_TG | Association (p-value; unadjusted for covariates) < 0.001 |
| PPM000156 | PGS000061 (GRS_LDL) |
PSS000097| East Asian Ancestry| 666 individuals |
PGP000045 | Johnson L et al. PLoS One (2015) |
Reported Trait: Serum low-density lipoprotein (LDL) levels | β: 5.58 | — | Beta (p-value): 0.697 | age, age^2, sex, GRS_HDL, GRS_TC, GRS_TG | Association (p-value; unadjusted for covariates) < 0.001 |
| PPM000157 | PGS000061 (GRS_LDL) |
PSS000096| African Ancestry| 1,355 individuals |
PGP000045 | Johnson L et al. PLoS One (2015) |
Reported Trait: Serum low-density lipoprotein (LDL) levels | β: 30.04 | — | Beta (p-value): 0.00282 | age, age^2, sex, GRS_HDL, GRS_TC, GRS_TG | Association (p-value; unadjusted for covariates) < 0.001 |
| PPM000158 | PGS000061 (GRS_LDL) |
PSS000099| Hispanic or Latin American Ancestry| 1,256 individuals |
PGP000045 | Johnson L et al. PLoS One (2015) |
Reported Trait: Serum low-density lipoprotein (LDL) levels | β: 42.86 | — | Beta (p-value): 2e-05 | age, age^2, sex, GRS_HDL, GRS_TC, GRS_TG | Association (p-value; unadjusted for covariates) < 0.001 |
| PPM000168 | PGS000065 (GLGC2017_LDL) |
PSS000104| European Ancestry| 9,962 individuals |
PGP000046 | Kuchenbaecker K et al. Nat Commun (2019) |
Reported Trait: Serum low-density lipoprotein (LDL) levels | — | — | correlation (r): 0.274 [0.254, 0.294] | age, sex | Relatedness and population structure were accounted for using a linear mixed model with random polygenic effect implemented in GEMMA |
| PPM000171 | PGS000065 (GLGC2017_LDL) |
PSS000102| European Ancestry| 1,641 individuals |
PGP000046 | Kuchenbaecker K et al. Nat Commun (2019) |
Reported Trait: Serum low-density lipoprotein (LDL) levels | — | — | correlation (r): 0.229 [0.172, 0.286] | age, sex | Relatedness and population structure were accounted for using a linear mixed model with random polygenic effect implemented in GEMMA |
| PPM000174 | PGS000065 (GLGC2017_LDL) |
PSS000103| European Ancestry| 1,945 individuals |
PGP000046 | Kuchenbaecker K et al. Nat Commun (2019) |
Reported Trait: Serum low-density lipoprotein (LDL) levels | — | — | correlation (r): 0.29 [0.231, 0.349] | age, sex | Relatedness and population structure were accounted for using a linear mixed model with random polygenic effect implemented in GEMMA |
| PPM000177 | PGS000065 (GLGC2017_LDL) |
PSS000100| African Ancestry| 6,407 individuals |
PGP000046 | Kuchenbaecker K et al. Nat Commun (2019) |
Reported Trait: Serum low-density lipoprotein (LDL) levels | — | — | correlation (r): 0.28 [0.257, 0.304] | age, sex | Relatedness and population structure were accounted for using a linear mixed model with random polygenic effect implemented in GEMMA |
| PPM000180 | PGS000065 (GLGC2017_LDL) |
PSS000101| East Asian Ancestry| 21,295 individuals |
PGP000046 | Kuchenbaecker K et al. Nat Commun (2019) |
Reported Trait: Serum low-density lipoprotein (LDL) levels | — | — | correlation (r): 0.198 [0.161, 0.235] | age, sex, region, 20 PCs of genetic ancestry | Relatedness and population structure were accounted for using a linear mixed model with random polygenic effect implemented in GEMMA |
| PPM000780 | PGS000310 (GRS194_LDL) |
PSS000376| European Ancestry| 1,354 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: Low-density lipoprotein (mmol/l) | — | — | R²: 0.1849 | Sex, age, age^2 | — |
| PPM000563 | PGS000192 (GS9) |
PSS000292| European Ancestry| 4,232 individuals |
PGP000079 | Kathiresan S et al. N Engl J Med (2008) |
Reported Trait: Incident cardiovascular event | — | AUROC: 0.8 | Hazard Ratio (HR; per allele): 1.15 [1.07, 1.24] | age, sex, family history of MI, LDL cholesterol, HDL cholesterol, triglycerides, blood pressure, body mass index, diabetes status, smoking status, CRP, lipid lowering medication | — |
| PPM000264 | PGS000115 (LDL-C_20) |
PSS000184| European Ancestry| 439,871 individuals |
PGP000053 | Trinder M et al. JAMA Cardiol (2020) |
Reported Trait: Serum low density lipoprotein cholesterol (LDL-C) levels | β: 28.01 (0.18) | — | R²: 0.09 | age, sex, 4 PCs of genetic ancestry, genotyping method (array and batch) | — |
| PPM000265 | PGS000115 (LDL-C_20) |
PSS000183| East Asian Ancestry| 10,640 individuals |
PGP000053 | Trinder M et al. JAMA Cardiol (2020) |
Reported Trait: Serum low density lipoprotein cholesterol (LDL-C) levels | β: 21.73 (1.25) | — | R²: 0.06 | age, sex, 4 PCs of genetic ancestry, genotyping method (array and batch) | — |
| PPM000266 | PGS000115 (LDL-C_20) |
PSS000181| African Ancestry| 4,680 individuals |
PGP000053 | Trinder M et al. JAMA Cardiol (2020) |
Reported Trait: Serum low density lipoprotein cholesterol (LDL-C) levels | β: 17.4 (1.91) | — | R²: 0.04 | age, sex, 4 PCs of genetic ancestry, genotyping method (array and batch) | — |
| PPM000267 | PGS000115 (LDL-C_20) |
PSS000185| Multi-ancestry (including European)| 455,191 individuals |
PGP000053 | Trinder M et al. JAMA Cardiol (2020) |
Reported Trait: Serum low density lipoprotein cholesterol (LDL-C) levels | β: 27.78 (0.18) | — | R²: 0.09 | age, sex, 4 PCs of genetic ancestry, genotyping method (array and batch) | — |
| PPM000268 | PGS000115 (LDL-C_20) |
PSS000182| Multi-ancestry (including European)| 47,845 individuals |
PGP000053 | Trinder M et al. JAMA Cardiol (2020) |
Reported Trait: Cardiovascular disease events | — | — | Hazard Ratio (HR; top vs. bottom decile of risk): 1.35 [1.3, 1.4] | age, sex, 4 PCs of genetic ancestry, genotyping method (array and batch) | — |
| PPM000562 | PGS000192 (GS9) |
PSS000292| European Ancestry| 4,232 individuals |
PGP000079 | Kathiresan S et al. N Engl J Med (2008) |
Reported Trait: High-density lipoprotein (HDL) levels | — | — | Association p-value: 2.00e-18 | — | — |
| PPM000561 | PGS000192 (GS9) |
PSS000292| European Ancestry| 4,232 individuals |
PGP000079 | Kathiresan S et al. N Engl J Med (2008) |
Reported Trait: Low-density lipoprotein (LDL) levels | — | — | Association p-value: 3.00e-24 | — | — |
| PPM000924 | PGS000340 (LDL-Cpsp) |
PSS000466| European Ancestry| 389,127 individuals |
PGP000107 | Trinder M et al. Circ Genom Precis Med (2020) |
Reported Trait: Low-density lipoprotein cholesterol levels | β: 0.82 (0.006) | — | R²: 0.074 | Age, sex | — |
| PPM000923 | PGS000340 (LDL-Cpsp) |
PSS000465| Multi-ancestry (including European)| 1,120 individuals |
PGP000107 | Trinder M et al. Circ Genom Precis Med (2020) |
Reported Trait: Low-density lipoprotein cholesterol levels in familial hypercholesterolemia mutation carriers | — | — | Beta (per 20% increase in PGS): 0.13 [0.072, 0.19] | — | — |
| PPM000925 | PGS000340 (LDL-Cpsp) |
PSS000465| Multi-ancestry (including European)| 1,120 individuals |
PGP000107 | Trinder M et al. Circ Genom Precis Med (2020) |
Reported Trait: Atherosclerotic cardiovascular disease in familial hypercholesterolemia mutation carriers | — | — | Odds Ratio (OR; top 20% vs. rest): 1.48 [1.02, 2.14] | sex | — |
| PPM001361 | PGS000661 (PRS-LDL) |
PSS000588| East Asian Ancestry| 426 individuals |
PGP000121 | Tam CHT et al. Genome Med (2021) |
Reported Trait: LDL choldesterol at baseline (log transformed) | β: 0.072 (0.012) | — | Pearson Correlation Coefficient (r): 0.255 Incremental R² (PRS and covariates vs. covariates-alone): 0.0672 |
age, sex, BMI, PCs | — |
| PPM001362 | PGS000661 (PRS-LDL) |
PSS000594| East Asian Ancestry| 4,917 individuals |
PGP000121 | Tam CHT et al. Genome Med (2021) |
Reported Trait: LDL choldesterol at baseline (log transformed) | β: 0.059 (0.004) | — | Pearson Correlation Coefficient (r): 0.178 Incremental R² (PRS and covariates vs. covariates-alone): 0.0351 |
age, sex, BMI, PCs | — |
| PPM001363 | PGS000661 (PRS-LDL) |
PSS000590| East Asian Ancestry| 1,941 individuals |
PGP000121 | Tam CHT et al. Genome Med (2021) |
Reported Trait: LDL choldesterol at baseline (log transformed) | β: 0.054 (0.006) | — | Pearson Correlation Coefficient (r): 0.19 Incremental R² (PRS and covariates vs. covariates-alone): 0.036 |
age, sex, BMI, PCs | — |
| PPM001364 | PGS000661 (PRS-LDL) |
PSS000592| East Asian Ancestry| 865 individuals |
PGP000121 | Tam CHT et al. Genome Med (2021) |
Reported Trait: LDL choldesterol at baseline (log transformed) | β: 0.058 (0.01) | — | Pearson Correlation Coefficient (r): 0.195 Incremental R² (PRS and covariates vs. covariates-alone): 0.0374 |
age, sex, BMI, PCs | — |
| PPM001416 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS000714| African Ancestry| 6,003 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) | — | — | R²: 0.13357 Spearman's ρ: 0.289 |
Age, sex, PCs(1-40) | — |
| PPM001451 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS000715| East Asian Ancestry| 1,082 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) | — | — | R²: 0.13985 Spearman's ρ: 0.301 |
Age, sex, PCs(1-40) | — |
| PPM001486 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS000716| European Ancestry| 23,535 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) | — | — | R²: 0.26408 Spearman's ρ: 0.436 |
Age, sex, PCs(1-40) | — |
| PPM001521 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS000717| South Asian Ancestry| 7,319 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) | — | — | R²: 0.11217 Spearman's ρ: 0.289 |
Age, sex, PCs(1-40) | — |
| PPM001556 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS000718| European Ancestry| 63,675 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) | — | — | R²: 0.26409 Spearman's ρ: 0.446 |
Age, sex, PCs(1-40) | — |
| PPM001575 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS000824| European Ancestry| 2,097 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) | — | — | Spearman's ρ: 0.159 | Age, sex | — |
| PPM001576 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS000825| European Ancestry| 1,987 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: LDL cholesterol [mmol/L] (statin adjusted) | — | — | Spearman's ρ: 0.138 | Age, sex | — |
| PPM012972 | PGS000814 (GRS12_LDLc) |
PSS009637| Ancestry Not Reported| 1,519 individuals |
PGP000311 | Olmastroni E et al. J Am Heart Assoc (2022) |Ext. |
Reported Trait: Polygenic hypercholesterolemia | — | AUROC: 0.59 [0.56, 0.62] | Sensitivity (%, cutoff of 0.905): 78.0 Specificity (%, cutoff of 0.905): 36.0 |
— | — |
| PPM002202 | PGS000814 (GRS12_LDLc) |
PSS001072| Ancestry Not Reported| 967 individuals |
PGP000205 | Rimbert A et al. Arterioscler Thromb Vasc Biol (2020) |Ext. |
Reported Trait: Liver steatosis | — | — | Odds Ratio (OR, polygenic vs monogenic hypobetalipoproteinemia cases): 0.13 [0.1, 1.16] | Age, sex | — |
| PPM002201 | PGS000814 (GRS12_LDLc) |
PSS001072| Ancestry Not Reported| 967 individuals |
PGP000205 | Rimbert A et al. Arterioscler Thromb Vasc Biol (2020) |Ext. |
Reported Trait: Hypobetalipoproteinemia | — | — | Percentage of cases with polygenic etiology (%): 34.0 | — | Polygenic etiology = PRS<10th percentile |
| PPM002170 | PGS000814 (GRS12_LDLc) |
PSS001058| European Ancestry| 3,020 individuals |
PGP000200 | Talmud PJ et al. Lancet (2013) |
Reported Trait: Low-density lipoprotein cholesterol level >4.9mmol/L | — | — | Risk Ratio (RR, top 10% vs bottom 10%): 4.17 [3.01, 5.78] | — | — |
| PPM002171 | PGS000814 (GRS12_LDLc) |
PSS001059| European Ancestry| 3,660 individuals |
PGP000200 | Talmud PJ et al. Lancet (2013) |
Reported Trait: Low-density lipoprotein cholesterol level >4.9mmol/L in individuals who have familial hypercholestrolaemia and no known mutation | — | AUROC: 0.65 [0.62, 0.68] | — | — | — |
| PPM002168 | PGS000814 (GRS12_LDLc) |
PSS001058| European Ancestry| 3,020 individuals |
PGP000200 | Talmud PJ et al. Lancet (2013) |
Reported Trait: Low-density lipoprotein (LDL) cholesterol | β: 0.33 [0.3, 0.37] | — | R²: 0.11 | — | — |
| PPM002169 | PGS000814 (GRS12_LDLc) |
PSS001058| European Ancestry| 3,020 individuals |
PGP000200 | Talmud PJ et al. Lancet (2013) |
Reported Trait: Low-density lipoprotein (LDL) cholesterol | β: 0.34 [0.31, 0.38] | — | — | Sex, age, lipid-lowering drug use, body-mass index, diabetes status, smoking status, blood pressure | — |
| PPM002230 | PGS000824 (LDL-C_PGS) |
PSS001083| Multi-ancestry (including European)| 2,531 individuals |
PGP000210 | Zubair N et al. Sci Rep (2019) |
Reported Trait: Low density lipoprotein cholesterol | — | — | R²: 0.111 | Age at baseline, sex, enrollment channel, PCs(1-7), observation season, observation vendor | — |
| PPM002313 | PGS000846 (LDL) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.02 [0.92, 1.13] | — | — | PC1-10 | — |
| PPM002588 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001156| African Ancestry| 18,251 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.162 | sex, PC1-4, birth year, and mean age | — |
| PPM002589 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001157| Additional Asian Ancestries| 4,155 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.1 | sex, PC1-4, birth year, and mean age | — |
| PPM002500 | PGS000875 (PGS36_LDLc) |
PSS001124| European Ancestry| 4,787 individuals |
PGP000221 | Leal LG et al. Mol Genet Genomic Med (2020) |
Reported Trait: Low-density lipoprotein cholesterol | — | — | R²: 0.08 | Age, gender, body mass index, ancestry differences captured by the first two components from multidimensional scaling | — |
| PPM002501 | PGS000875 (PGS36_LDLc) |
PSS001124| European Ancestry| 4,787 individuals |
PGP000221 | Leal LG et al. Mol Genet Genomic Med (2020) |
Reported Trait: Severe hypercholesterolemia | — | — | Risk Ratio (RR, top 30% vs bottom 30%): 4.8 [2.6, 8.9] | — | — |
| PPM002502 | PGS000875 (PGS36_LDLc) |
PSS001124| European Ancestry| 4,787 individuals |
PGP000221 | Leal LG et al. Mol Genet Genomic Med (2020) |
Reported Trait: Low-density lipoprotein cholesterol | — | AUROC: 0.67 | — | — | — |
| PPM002503 | PGS000814 (GRS12_LDLc) |
PSS001124| European Ancestry| 4,787 individuals |
PGP000221 | Leal LG et al. Mol Genet Genomic Med (2020) |Ext. |
Reported Trait: Low-density lipoprotein cholesterol | — | AUROC: 0.65 | — | — | — |
| PPM002590 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001158| European Ancestry| 68,381 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.158 | sex, PC1-4, birth year, and mean age | — |
| PPM002545 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001146| African Ancestry| 3,566 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.125 | age, sex, PC1-3 | — |
| PPM002546 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001144| African Ancestry| 4,273 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.114 | age, sex, PC1-3 | — |
| PPM002547 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001145| African Ancestry| 707 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.067 | age, sex, PC1-3 | — |
| PPM002548 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001146| African Ancestry| 3,566 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.123 | age, sex, PC1-3 | — |
| PPM002549 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001144| African Ancestry| 4,273 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.052 | age, sex, PC1-3 | — |
| PPM002550 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001145| African Ancestry| 707 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.063 | age, sex, PC1-3 | — |
| PPM002551 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001146| African Ancestry| 3,566 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.055 | age, sex, PC1-3 | — |
| PPM002552 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001147| African Ancestry| 10,460 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.173 | age, sex, PC1-6 | — |
| PPM002553 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001147| African Ancestry| 10,460 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.122 | age, sex, PC1-6 | — |
| PPM002555 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001148| African Ancestry| 1,745 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.069 | age, sex, PC1-6 | — |
| PPM002556 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001148| African Ancestry| 1,745 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.041 | age, sex, PC1-6 | — |
| PPM002557 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001149| African Ancestry| 4,972 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.128 | age, sex, PC1-6 | — |
| PPM002558 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001149| African Ancestry| 4,972 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.108 | age, sex, PC1-6 | — |
| PPM002559 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001149| African Ancestry| 4,972 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.04 | age, sex, PC1-6 | — |
| PPM002560 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001150| African Ancestry| 3,743 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.076 | age, sex, and PC1-4 | — |
| PPM002561 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001150| African Ancestry| 3,743 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.075 | age, sex, and PC1-4 | — |
| PPM002562 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001150| African Ancestry| 3,743 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.022 | age, sex, and PC1-4 | — |
| PPM002563 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001151| South Asian Ancestry| 15,242 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Max LDL cholesterol | — | — | R²: 0.069 | age, sex, and PC1-10 | — |
| PPM002565 | PGS000893 (GLGC_2021_EUR_LDL_PRS_weights_PT) |
PSS001151| South Asian Ancestry| 15,242 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Max LDL cholesterol | — | — | R²: 0.096 | age, sex, and PC1-10 | — |
| PPM002566 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001151| South Asian Ancestry| 15,242 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Max LDL cholesterol | — | — | R²: 0.088 | age, sex, and PC1-10 | — |
| PPM002567 | PGS000897 (GLGC_2021_SAS_LDL_PRS_weights_PT) |
PSS001151| South Asian Ancestry| 15,242 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Max LDL cholesterol | — | — | R²: 0.077 | age, sex, and PC1-10 | — |
| PPM002568 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001152| East Asian Ancestry| 118,260 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.051 | age, sex, and recruitment area | — |
| PPM002569 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001152| East Asian Ancestry| 118,260 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.095 | age, sex, and recruitment area | — |
| PPM002570 | PGS000891 (GLGC_2021_EAS_LDL_PRS_weights_PT) |
PSS001152| East Asian Ancestry| 118,260 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.098 | age, sex, and recruitment area | — |
| PPM002571 | PGS000890 (GLGC_2021_EAS_LDL_PRS_weights_PRS-CS) |
PSS001152| East Asian Ancestry| 118,260 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.094 | age, sex, and recruitment area | — |
| PPM002573 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001152| East Asian Ancestry| 118,260 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.064 | age, sex, and recruitment area | — |
| PPM002574 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001153| African Ancestry| 1,341 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.115 | sex, batch, PC1-4, and birth year | — |
| PPM002575 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001154| European Ancestry| 17,190 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.074 | sex, batch, PC1-4, and birth year | — |
| PPM002576 | PGS000886 (GLGC_2021_AFR_LDL_PRS_weights_PRS-CS) |
PSS001153| African Ancestry| 1,341 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.064 | sex, batch, PC1-4, and birth year | — |
| PPM002578 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001153| African Ancestry| 1,341 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.122 | sex, batch, PC1-4, and birth year | — |
| PPM002579 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001154| European Ancestry| 17,190 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.13 | sex, batch, PC1-4, and birth year | — |
| PPM002580 | PGS000893 (GLGC_2021_EUR_LDL_PRS_weights_PT) |
PSS001153| African Ancestry| 1,341 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.058 | sex, batch, PC1-4, and birth year | — |
| PPM002581 | PGS000893 (GLGC_2021_EUR_LDL_PRS_weights_PT) |
PSS001154| European Ancestry| 17,190 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.123 | sex, batch, PC1-4, and birth year | — |
| PPM002582 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001153| African Ancestry| 1,341 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.062 | sex, batch, PC1-4, and birth year | — |
| PPM002583 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001154| European Ancestry| 17,190 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.129 | sex, batch, PC1-4, and birth year | — |
| PPM002584 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001156| African Ancestry| 18,251 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.148 | sex, PC1-4, birth year, and mean age | — |
| PPM002585 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001157| Additional Asian Ancestries| 4,155 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.063 | sex, PC1-4, birth year, and mean age | — |
| PPM002587 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001159| Hispanic or Latin American Ancestry| 7,669 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.071 | sex, PC1-4, birth year, and mean age | — |
| PPM002591 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001159| Hispanic or Latin American Ancestry| 7,669 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.134 | sex, PC1-4, birth year, and mean age | — |
| PPM002592 | PGS000891 (GLGC_2021_EAS_LDL_PRS_weights_PT) |
PSS001156| African Ancestry| 18,251 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.056 | sex, PC1-4, birth year, and mean age | — |
| PPM002593 | PGS000891 (GLGC_2021_EAS_LDL_PRS_weights_PT) |
PSS001157| Additional Asian Ancestries| 4,155 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.098 | sex, PC1-4, birth year, and mean age | — |
| PPM002594 | PGS000891 (GLGC_2021_EAS_LDL_PRS_weights_PT) |
PSS001158| European Ancestry| 68,381 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.083 | sex, PC1-4, birth year, and mean age | — |
| PPM002595 | PGS000891 (GLGC_2021_EAS_LDL_PRS_weights_PT) |
PSS001159| Hispanic or Latin American Ancestry| 7,669 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.057 | sex, PC1-4, birth year, and mean age | — |
| PPM002596 | PGS000890 (GLGC_2021_EAS_LDL_PRS_weights_PRS-CS) |
PSS001156| African Ancestry| 18,251 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.041 | sex, PC1-4, birth year, and mean age | — |
| PPM002598 | PGS000890 (GLGC_2021_EAS_LDL_PRS_weights_PRS-CS) |
PSS001158| European Ancestry| 68,381 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.083 | sex, PC1-4, birth year, and mean age | — |
| PPM002599 | PGS000890 (GLGC_2021_EAS_LDL_PRS_weights_PRS-CS) |
PSS001159| Hispanic or Latin American Ancestry| 7,669 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.063 | sex, PC1-4, birth year, and mean age | — |
| PPM002600 | PGS000893 (GLGC_2021_EUR_LDL_PRS_weights_PT) |
PSS001156| African Ancestry| 18,251 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.042 | sex, PC1-4, birth year, and mean age | — |
| PPM002601 | PGS000893 (GLGC_2021_EUR_LDL_PRS_weights_PT) |
PSS001157| Additional Asian Ancestries| 4,155 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.066 | sex, PC1-4, birth year, and mean age | — |
| PPM002602 | PGS000893 (GLGC_2021_EUR_LDL_PRS_weights_PT) |
PSS001158| European Ancestry| 68,381 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.152 | sex, PC1-4, birth year, and mean age | — |
| PPM002603 | PGS000893 (GLGC_2021_EUR_LDL_PRS_weights_PT) |
PSS001159| Hispanic or Latin American Ancestry| 7,669 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.106 | sex, PC1-4, birth year, and mean age | — |
| PPM002604 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001156| African Ancestry| 18,251 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.04 | sex, PC1-4, birth year, and mean age | — |
| PPM002605 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001157| Additional Asian Ancestries| 4,155 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.067 | sex, PC1-4, birth year, and mean age | — |
| PPM002606 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001158| European Ancestry| 68,381 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.153 | sex, PC1-4, birth year, and mean age | — |
| PPM002607 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001159| Hispanic or Latin American Ancestry| 7,669 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.114 | sex, PC1-4, birth year, and mean age | — |
| PPM002609 | PGS000895 (GLGC_2021_HIS_LDL_PRS_weights_PT) |
PSS001157| Additional Asian Ancestries| 4,155 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.079 | sex, PC1-4, birth year, and mean age | — |
| PPM002610 | PGS000895 (GLGC_2021_HIS_LDL_PRS_weights_PT) |
PSS001158| European Ancestry| 68,381 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.119 | sex, PC1-4, birth year, and mean age | — |
| PPM002611 | PGS000895 (GLGC_2021_HIS_LDL_PRS_weights_PT) |
PSS001159| Hispanic or Latin American Ancestry| 7,669 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.102 | sex, PC1-4, birth year, and mean age | — |
| PPM002612 | PGS000897 (GLGC_2021_SAS_LDL_PRS_weights_PT) |
PSS001156| African Ancestry| 18,251 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.076 | sex, PC1-4, birth year, and mean age | — |
| PPM002613 | PGS000897 (GLGC_2021_SAS_LDL_PRS_weights_PT) |
PSS001157| Additional Asian Ancestries| 4,155 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.067 | sex, PC1-4, birth year, and mean age | — |
| PPM002614 | PGS000897 (GLGC_2021_SAS_LDL_PRS_weights_PT) |
PSS001158| European Ancestry| 68,381 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.101 | sex, PC1-4, birth year, and mean age | — |
| PPM002615 | PGS000897 (GLGC_2021_SAS_LDL_PRS_weights_PT) |
PSS001159| Hispanic or Latin American Ancestry| 7,669 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.069 | sex, PC1-4, birth year, and mean age | — |
| PPM002616 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001160| African Ancestry| 2,138 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.129 | birth year, sex, and PC1-4 | — |
| PPM002617 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001160| African Ancestry| 2,138 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.132 | birth year, sex, and PC1-4 | — |
| PPM002618 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001160| African Ancestry| 2,138 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.069 | birth year, sex, and PC1-4 | — |
| PPM002620 | PGS000890 (GLGC_2021_EAS_LDL_PRS_weights_PRS-CS) |
PSS001161| East Asian Ancestry| 28,217 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.094 | sex, age, recruitment method, and PC1-20 | — |
| PPM002621 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001161| East Asian Ancestry| 28,217 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.074 | sex, age, recruitment method, and PC1-20 | — |
| PPM002622 | PGS000892 (GLGC_2021_EUR_LDL_PRS_weights_PRS-CS) |
PSS001165| European Ancestry| 389,158 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.182 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM002623 | PGS000893 (GLGC_2021_EUR_LDL_PRS_weights_PT) |
PSS001165| European Ancestry| 389,158 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.176 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM002624 | PGS000888 (GLGC_2021_ALL_LDL_PRS_weights_PRS-CS) |
PSS001162| Multi-ancestry (including European)| 461,918 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.175 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM002625 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001162| Multi-ancestry (including European)| 461,918 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.182 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM002626 | PGS000890 (GLGC_2021_EAS_LDL_PRS_weights_PRS-CS) |
PSS001164| East Asian Ancestry| 1,441 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.113 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM002627 | PGS000891 (GLGC_2021_EAS_LDL_PRS_weights_PT) |
PSS001164| East Asian Ancestry| 1,441 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.1 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM002628 | PGS000886 (GLGC_2021_AFR_LDL_PRS_weights_PRS-CS) |
PSS001163| African Ancestry| 6,863 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.112 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM002629 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001163| African Ancestry| 6,863 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.175 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM002630 | PGS000896 (GLGC_2021_SAS_LDL_PRS_weights_PRS-CS) |
PSS001166| South Asian Ancestry| 6,814 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.04 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM002631 | PGS000897 (GLGC_2021_SAS_LDL_PRS_weights_PT) |
PSS001166| South Asian Ancestry| 6,814 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.058 | sex, batch, age at initial assessment, PCs1-4 | — |
| PPM002632 | PGS000894 (GLGC_2021_HIS_LDL_PRS_weights_PRS-CS) |
PSS001155| Hispanic or Latin American Ancestry| 360 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.023 | sex, batch, PC1-4, and birth year | — |
| PPM002633 | PGS000895 (GLGC_2021_HIS_LDL_PRS_weights_PT) |
PSS001155| Hispanic or Latin American Ancestry| 360 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.088 | sex, batch, PC1-4, and birth year | — |
| PPM002316 | PGS000846 (LDL) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.0 [0.94, 1.07] | — | — | PC1-10 | — |
| PPM002317 | PGS000846 (LDL) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 0.95 [0.9, 1.0] | — | — | PC1-10 | — |
| PPM002315 | PGS000846 (LDL) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 0.92 [0.86, 0.99] | — | — | PC1-10 | — |
| PPM002314 | PGS000846 (LDL) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 0.95 [0.89, 1.02] | — | — | PC1-10 | — |
| PPM007365 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS007171| African Ancestry| 6,086 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: LDL cholesterol | — | — | R²: 0.05912 [0.048, 0.07024] Incremental R2 (full-covars): 0.05479 PGS R2 (no covariates): 0.06663 [0.05492, 0.07834] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007366 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS007172| East Asian Ancestry| 1,615 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: LDL cholesterol | — | — | R²: 0.06107 [0.03908, 0.08305] Incremental R2 (full-covars): 0.0498 PGS R2 (no covariates): 0.07486 [0.05087, 0.09885] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007367 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS007173| European Ancestry| 23,728 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: LDL cholesterol | — | — | R²: 0.10564 [0.09842, 0.11286] Incremental R2 (full-covars): 0.096 PGS R2 (no covariates): 0.11974 [0.11218, 0.12731] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007368 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS007174| South Asian Ancestry| 7,407 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: LDL cholesterol | — | — | R²: 0.05634 [0.04642, 0.06625] Incremental R2 (full-covars): 0.02423 PGS R2 (no covariates): 0.03502 [0.02702, 0.04301] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007369 | PGS000688 (snpnet.LDL_direct_adjstatins) |
PSS007175| European Ancestry| 64,356 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: LDL cholesterol | — | — | R²: 0.09533 [0.09111, 0.09955] Incremental R2 (full-covars): 0.08543 PGS R2 (no covariates): 0.10869 [0.10426, 0.11313] |
age, sex, UKB array type, Genotype PCs | — |
| PPM010339 | PGS001933 (portability-PLR_LDL) |
PSS009376| European Ancestry| 18,968 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.3331 [0.3204, 0.3457] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010340 | PGS001933 (portability-PLR_LDL) |
PSS009150| European Ancestry| 3,946 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.3496 [0.3219, 0.3768] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010341 | PGS001933 (portability-PLR_LDL) |
PSS008704| European Ancestry| 6,312 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.3177 [0.2953, 0.3397] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010342 | PGS001933 (portability-PLR_LDL) |
PSS008478| Greater Middle Eastern Ancestry| 1,122 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.297 [0.2422, 0.3499] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010343 | PGS001933 (portability-PLR_LDL) |
PSS008256| South Asian Ancestry| 5,987 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.2086 [0.1842, 0.2327] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010344 | PGS001933 (portability-PLR_LDL) |
PSS008034| East Asian Ancestry| 1,716 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.2593 [0.2144, 0.3032] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010345 | PGS001933 (portability-PLR_LDL) |
PSS007820| African Ancestry| 2,338 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.2864 [0.2486, 0.3234] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012054 | PGS002150 (portability-ldpred2_LDL) |
PSS008924| African Ancestry| 3,651 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.2251 [0.194, 0.2558] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012047 | PGS002150 (portability-ldpred2_LDL) |
PSS009376| European Ancestry| 18,968 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.3346 [0.3219, 0.3472] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012048 | PGS002150 (portability-ldpred2_LDL) |
PSS009150| European Ancestry| 3,946 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.3475 [0.3197, 0.3747] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012049 | PGS002150 (portability-ldpred2_LDL) |
PSS008704| European Ancestry| 6,312 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.3081 [0.2856, 0.3303] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012050 | PGS002150 (portability-ldpred2_LDL) |
PSS008478| Greater Middle Eastern Ancestry| 1,122 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.2975 [0.2427, 0.3504] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012051 | PGS002150 (portability-ldpred2_LDL) |
PSS008256| South Asian Ancestry| 5,987 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.2191 [0.1948, 0.2431] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012052 | PGS002150 (portability-ldpred2_LDL) |
PSS008034| East Asian Ancestry| 1,716 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.2555 [0.2104, 0.2994] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012053 | PGS002150 (portability-ldpred2_LDL) |
PSS007820| African Ancestry| 2,338 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.294 [0.2563, 0.3307] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM002543 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001144| African Ancestry| 4,273 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.118 | age, sex, PC1-3 | — |
| PPM002544 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001145| African Ancestry| 707 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.101 | age, sex, PC1-3 | — |
| PPM002554 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001148| African Ancestry| 1,745 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.085 | age, sex, PC1-6 | — |
| PPM002564 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001151| South Asian Ancestry| 15,242 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Max LDL cholesterol | — | — | R²: 0.105 | age, sex, and PC1-10 | — |
| PPM002572 | PGS000893 (GLGC_2021_EUR_LDL_PRS_weights_PT) |
PSS001152| East Asian Ancestry| 118,260 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.071 | age, sex, and recruitment area | — |
| PPM002577 | PGS000886 (GLGC_2021_AFR_LDL_PRS_weights_PRS-CS) |
PSS001154| European Ancestry| 17,190 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.056 | sex, batch, PC1-4, and birth year | — |
| PPM002586 | PGS000887 (GLGC_2021_AFR_LDL_PRS_weights_PT) |
PSS001158| European Ancestry| 68,381 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.103 | sex, PC1-4, birth year, and mean age | — |
| PPM002597 | PGS000890 (GLGC_2021_EAS_LDL_PRS_weights_PRS-CS) |
PSS001157| Additional Asian Ancestries| 4,155 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.09 | sex, PC1-4, birth year, and mean age | — |
| PPM002608 | PGS000895 (GLGC_2021_HIS_LDL_PRS_weights_PT) |
PSS001156| African Ancestry| 18,251 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Mean LDL cholesterol | — | — | R²: 0.1 | sex, PC1-4, birth year, and mean age | — |
| PPM002619 | PGS000889 (GLGC_2021_ALL_LDL_PRS_weights_PT) |
PSS001161| East Asian Ancestry| 28,217 individuals |
PGP000230 | Graham SE et al. Nature (2021) |
Reported Trait: Baseline LDL cholesterol | — | — | R²: 0.098 | sex, age, recruitment method, and PC1-20 | — |
| PPM010346 | PGS001933 (portability-PLR_LDL) |
PSS008924| African Ancestry| 3,651 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: LDL direct | — | — | Partial Correlation (partial-r): 0.2203 [0.1891, 0.251] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012859 | PGS000115 (LDL-C_20) |
PSS009580| European Ancestry| 33,787 individuals |
PGP000284 | Tapela NM et al. Eur J Prev Cardiol (2021) |Ext. |
Reported Trait: Uncontrolled hypercholesterolaemia | — | — | Odds Ratio (OR, top vs. bottom quintile): 2.78 [2.58, 3.0] | age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), and the first four principal components of genetic ancestry, genotyping array and systolic blood pressure at baseline | 218 SNPs remained after QC |
| PPM012860 | PGS000115 (LDL-C_20) |
PSS009577| European Ancestry| 33,787 individuals |
PGP000284 | Tapela NM et al. Eur J Prev Cardiol (2021) |Ext. |
Reported Trait: Incident major adverse cardiovascular events in statin treatment | — | — | Hazard Ratio (HR, top vs. bottom quintile): 1.03 [0.92, 1.14] | age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), and the first four principal components of genetic ancestry, genotyping array and systolic blood pressure at baseline | 218 SNPs remained after QC |
| PPM012861 | PGS000115 (LDL-C_20) |
PSS009578| European Ancestry| 33,787 individuals |
PGP000284 | Tapela NM et al. Eur J Prev Cardiol (2021) |Ext. |
Reported Trait: Incident myocardial infarction in statin treatment | — | — | Hazard Ratio (HR, top vs. bottom quintile): 1.08 [0.95, 1.23] | age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), and the first four principal components of genetic ancestry, genotyping array and systolic blood pressure at baseline | 218 SNPs remained after QC |
| PPM012862 | PGS000115 (LDL-C_20) |
PSS009579| European Ancestry| 33,787 individuals |
PGP000284 | Tapela NM et al. Eur J Prev Cardiol (2021) |Ext. |
Reported Trait: Incident stroke in statin treatment | — | — | Hazard Ratio (HR, top vs. bottom quintile): 0.93 [0.77, 1.12] | age, sex, socioeconomic characteristics (education, occupation, Townsend deprivation score, and country of residence), metabolic and lifestyle CVD risk factors (smoking status, body mass index, physical activity in METS, and weekly alcohol consumption), family history of CVD (diagnosis at any age), and the first four principal components of genetic ancestry, genotyping array and systolic blood pressure at baseline | 218 SNPs remained after QC |
| PPM012944 | PGS002274 (LDL-PRS) |
PSS009627| European Ancestry| 4,416 individuals |
PGP000303 | Groenland EH et al. Atherosclerosis (2022) |
Reported Trait: Low-density lipoprotein cholesterol | β: 0.18 [0.15, 0.21] | — | — | Age, sex, the first 5 principal components, BMI, T2DM, smoking, alcohol use, systolic blood pressure, eGFR, triglycerides, lipid-lowering medication | — |
| PPM012983 | PGS002285 (GRS_286_LDL) |
PSS009639| African Ancestry| 2,569 individuals |
PGP000313 | Kamiza AB et al. Nat Med (2022) |
Reported Trait: Low density lipoprotein cholesterol levels | — | — | R²: 0.0814 | age, sex, type 2 diabetes, PC1, PC2, PC3, PC4, PC5 | Nagelkerke’s R2 (estimate of variance explained by the PGS after covariate adjustment) |
| PPM014797 | PGS002730 (GRSlipid_35) |
PSS009892| European Ancestry| 75,973 individuals |
PGP000337 | Mayerhofer E et al. Brain (2022) |
Reported Trait: On-statin LDL decrease | β: -0.05 [-0.07, -0.02] | — | — | — | — |
| PPM013054 | PGS000814 (GRS12_LDLc) |
PSS009666| South Asian Ancestry| 7,016 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: LDL-C concentration | — | — | R²: 0.049 [0.035, 0.063] | Age, sex | — |
| PPM013055 | PGS000814 (GRS12_LDLc) |
PSS009668| European Ancestry| 353,166 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: LDL-C concentration >4.9 mmol/L | OR: 11.01 [10.08, 12.04] | — | — | — | — |
| PPM013056 | PGS000814 (GRS12_LDLc) |
PSS009667| African Ancestry| 7,082 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: LDL-C concentration >4.9 mmol/L | OR: 10.54 [5.29, 21.67] | — | — | — | — |
| PPM013057 | PGS000814 (GRS12_LDLc) |
PSS009666| South Asian Ancestry| 7,016 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: LDL-C concentration >4.9 mmol/L | OR: 6.64 [2.98, 15.22] | — | — | — | — |
| PPM013058 | PGS000814 (GRS12_LDLc) |
PSS009668| European Ancestry| 353,166 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.76 [1.56, 1.99] | — | — | — | — |
| PPM014798 | PGS002730 (GRSlipid_35) |
PSS009892| European Ancestry| 75,973 individuals |
PGP000337 | Mayerhofer E et al. Brain (2022) |
Reported Trait: Incident intracerebral hemorrhage | HR: 1.16 [1.05, 1.28] | — | — | — | — |
| PPM014799 | PGS002730 (GRSlipid_35) |
PSS009892| European Ancestry| 75,973 individuals |
PGP000337 | Mayerhofer E et al. Brain (2022) |
Reported Trait: Incident myocardial infarction | HR: 0.98 [0.96, 0.99] | — | — | — | — |
| PPM014800 | PGS002730 (GRSlipid_35) |
PSS009892| European Ancestry| 75,973 individuals |
PGP000337 | Mayerhofer E et al. Brain (2022) |
Reported Trait: Incident Peripheral Artery Disease | HR: 0.93 [0.87, 0.99] | — | — | — | — |
| PPM013059 | PGS000814 (GRS12_LDLc) |
PSS009667| African Ancestry| 7,082 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: Coronary heart disease | OR: 2.26 [0.78, 7.22] | — | — | — | — |
| PPM013060 | PGS000814 (GRS12_LDLc) |
PSS009666| South Asian Ancestry| 7,016 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.24 [0.62, 2.53] | — | — | — | — |
| PPM013061 | PGS000814 (GRS12_LDLc) |
PSS009668| European Ancestry| 353,166 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.25 [1.13, 1.39] | — | — | — | — |
| PPM013062 | PGS000814 (GRS12_LDLc) |
PSS009667| African Ancestry| 7,082 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.09 [0.48, 2.58] | — | — | — | — |
| PPM013063 | PGS000814 (GRS12_LDLc) |
PSS009666| South Asian Ancestry| 7,016 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: Coronary heart disease | OR: 1.98 [0.95, 4.25] | — | — | — | — |
| PPM013052 | PGS000814 (GRS12_LDLc) |
PSS009668| European Ancestry| 353,166 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: LDL-C concentration | — | — | R²: 0.108 [0.105, 0.111] | Age, sex | — |
| PPM013053 | PGS000814 (GRS12_LDLc) |
PSS009667| African Ancestry| 7,082 individuals |
PGP000330 | Gratton J et al. Front Genet (2022) |Ext. |
Reported Trait: LDL-C concentration | — | — | R²: 0.105 [0.086, 0.124] | Age, sex | — |
| PPM015917 | PGS003032 (ExPRSweb_LDL_30780-irnt_DBSLMM_MGI_20211120) |
PSS010010| European Ancestry| 9,288 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: LDL | β: 7.6 (0.282) | — | R²: 0.0687 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015918 | PGS003029 (ExPRSweb_LDL_30780-irnt_LASSOSUM_MGI_20211120) |
PSS010010| European Ancestry| 9,288 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: LDL | β: 7.06 (0.286) | — | R²: 0.0594 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015919 | PGS003031 (ExPRSweb_LDL_30780-irnt_PLINK_MGI_20211120) |
PSS010010| European Ancestry| 9,288 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: LDL | β: 7.23 (0.283) | — | R²: 0.0635 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015920 | PGS003033 (ExPRSweb_LDL_30780-irnt_PRSCS_MGI_20211120) |
PSS010010| European Ancestry| 9,288 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: LDL | β: 7.36 (0.284) | — | R²: 0.0649 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015921 | PGS003030 (ExPRSweb_LDL_30780-irnt_PT_MGI_20211120) |
PSS010010| European Ancestry| 9,288 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: LDL | β: 7.07 (0.283) | — | R²: 0.061 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015922 | PGS003037 (ExPRSweb_LDL_30780-raw_DBSLMM_MGI_20211120) |
PSS010010| European Ancestry| 9,288 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: LDL | β: 7.9 (0.281) | — | R²: 0.0753 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015924 | PGS003036 (ExPRSweb_LDL_30780-raw_PLINK_MGI_20211120) |
PSS010010| European Ancestry| 9,288 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: LDL | β: 7.17 (0.283) | — | R²: 0.0625 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015925 | PGS003038 (ExPRSweb_LDL_30780-raw_PRSCS_MGI_20211120) |
PSS010010| European Ancestry| 9,288 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: LDL | β: 7.42 (0.285) | — | R²: 0.0656 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015926 | PGS003035 (ExPRSweb_LDL_30780-raw_PT_MGI_20211120) |
PSS010010| European Ancestry| 9,288 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: LDL | β: 7.09 (0.283) | — | R²: 0.0612 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015923 | PGS003034 (ExPRSweb_LDL_30780-raw_LASSOSUM_MGI_20211120) |
PSS010010| European Ancestry| 9,288 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: LDL | β: 7.06 (0.286) | — | R²: 0.0593 | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016178 | PGS003339 (CVGRS_LDL) |
PSS010055| East Asian Ancestry| 22,608 individuals |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Reported Trait: LDL cholesterol level | β: 0.31083 | — | — | — | — |
| PPM016187 | PGS003348 (ALLGRS_LDL) |
PSS010055| East Asian Ancestry| 22,608 individuals |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Reported Trait: LDL cholesterol level | β: 0.31961 | — | — | — | — |
| PPM016195 | PGS003339 (CVGRS_LDL) |
PSS010055| East Asian Ancestry| 22,608 individuals |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Reported Trait: Type 2 diabetes | OR: 0.99947 | — | — | — | — |
| PPM016205 | PGS000814 (GRS12_LDLc) |
PSS010056| Greater Middle Eastern Ancestry| 6,140 individuals |
PGP000406 | Gandhi GD et al. J Transl Med (2022) |Ext. |
Reported Trait: Probable vs. unlikely dyslipidemia | — | — | p: 0.0003 | — | — |
| PPM016207 | PGS000814 (GRS12_LDLc) |
PSS010058| Ancestry Not Reported| 237 individuals |
PGP000408 | Borg SÁ et al. Atheroscler Plus (2022) |Ext. |
Reported Trait: Coronary artery calcium score >0 in potential clinical FH cases | — | — | Odds ratio (OR, >80 percentile vs <= 80 percentile): 8.05 [1.65, 39.29] | Smoking, hypertension, waist circumference and lipoprotein(a) | — |
| PPM017043 | PGS003404 (wGRS) |
PSS010103| Multi-ancestry (including European)| 313 individuals |
PGP000421 | Wang J et al. Arterioscler Thromb Vasc Biol (2016) |
Reported Trait: FH mutation-negative with severe hypercholesterolemia | OR: 3.02 [1.61, 5.68] | — | — | — | — |
| PPM017041 | PGS003403 (PRS28_LDL) |
PSS010102| European Ancestry| 626 individuals |
PGP000420 | Trinder M et al. J Am Coll Cardiol (2019) |
Reported Trait: LDL-C levels | — | — | pvalue (High >=80 percentile vs lower <80th percentile): 0.03 | — | — |
| PPM017044 | PGS003405 (165SNP_PRS) |
PSS010104| European Ancestry| 89,528 individuals |
PGP000422 | Vanhoye X et al. Transl Res (2022) |
Reported Trait: LDL-c blood concentration | β: 0.31 [0.3, 0.31] | AUROC: 0.6901 [0.684, 0.696] | R²: 0.1979 | Age, BMI, sex, age | — |
| PPM017045 | PGS000814 (GRS12_LDLc) |
PSS010104| European Ancestry| 89,528 individuals |
PGP000422 | Vanhoye X et al. Transl Res (2022) |Ext. |
Reported Trait: LDL-c blood concentration | β: 0.25 [0.25, 0.26] | AUROC: 0.6503 [0.644, 0.657] | R²: 0.1055 | Age, BMI, sex, age | — |
| PPM017046 | PGS003403 (PRS28_LDL) |
PSS010104| European Ancestry| 89,528 individuals |
PGP000422 | Vanhoye X et al. Transl Res (2022) |Ext. |
Reported Trait: LDL-c blood concentration | β: 0.18 [0.18, 0.18] | AUROC: 0.6233 [0.617, 0.63] | R²: 0.1055 | Age, BMI, sex, age | — |
| PPM017047 | PGS003404 (wGRS) |
PSS010104| European Ancestry| 89,528 individuals |
PGP000422 | Vanhoye X et al. Transl Res (2022) |Ext. |
Reported Trait: LDL-c blood concentration | β: 0.16 [0.15, 0.16] | AUROC: 0.6072 [0.6, 0.614] | R²: 0.09317 | Age, BMI, sex, age | — |
| PPM017042 | PGS003403 (PRS28_LDL) |
PSS010102| European Ancestry| 626 individuals |
PGP000420 | Trinder M et al. J Am Coll Cardiol (2019) |
Reported Trait: Cardiovascular disease events in patients with monogenic familial hypercholesterolemia | — | — | Adjusted Hazard Ratio (aHR; top 20% vs. remaining): 3.06 [1.56, 5.99] | age, sex, LDL-C, diabetes mellitus, and hypertension | — |
| PPM013102 | PGS002337 (biochemistry_LDLdirect.BOLT-LMM) |
PSS009791| African Ancestry| 6,068 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0733 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013151 | PGS002337 (biochemistry_LDLdirect.BOLT-LMM) |
PSS009792| East Asian Ancestry| 875 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0681 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013200 | PGS002337 (biochemistry_LDLdirect.BOLT-LMM) |
PSS009793| European Ancestry| 41,139 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.11 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013249 | PGS002337 (biochemistry_LDLdirect.BOLT-LMM) |
PSS009794| South Asian Ancestry| 7,638 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0479 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013281 | PGS002369 (biochemistry_LDLdirect.BOLT-LMM-BBJ) |
PSS009791| African Ancestry| 6,068 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0314 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013304 | PGS002369 (biochemistry_LDLdirect.BOLT-LMM-BBJ) |
PSS009792| East Asian Ancestry| 875 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.037 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013327 | PGS002369 (biochemistry_LDLdirect.BOLT-LMM-BBJ) |
PSS009793| European Ancestry| 41,139 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0112 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013390 | PGS002409 (biochemistry_LDLdirect.P+T.0.0001) |
PSS009791| African Ancestry| 6,068 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0019 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013439 | PGS002409 (biochemistry_LDLdirect.P+T.0.0001) |
PSS009792| East Asian Ancestry| 875 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0268 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013488 | PGS002409 (biochemistry_LDLdirect.P+T.0.0001) |
PSS009793| European Ancestry| 41,139 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0733 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013586 | PGS002458 (biochemistry_LDLdirect.P+T.0.001) |
PSS009791| African Ancestry| 6,068 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0011 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013635 | PGS002458 (biochemistry_LDLdirect.P+T.0.001) |
PSS009792| East Asian Ancestry| 875 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0162 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013684 | PGS002458 (biochemistry_LDLdirect.P+T.0.001) |
PSS009793| European Ancestry| 41,139 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0672 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013733 | PGS002458 (biochemistry_LDLdirect.P+T.0.001) |
PSS009794| South Asian Ancestry| 7,638 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0065 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013782 | PGS002507 (biochemistry_LDLdirect.P+T.0.01) |
PSS009791| African Ancestry| 6,068 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013831 | PGS002507 (biochemistry_LDLdirect.P+T.0.01) |
PSS009792| East Asian Ancestry| 875 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0016 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013929 | PGS002507 (biochemistry_LDLdirect.P+T.0.01) |
PSS009794| South Asian Ancestry| 7,638 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013978 | PGS002556 (biochemistry_LDLdirect.P+T.1e-06) |
PSS009791| African Ancestry| 6,068 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0407 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014027 | PGS002556 (biochemistry_LDLdirect.P+T.1e-06) |
PSS009792| East Asian Ancestry| 875 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0185 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014076 | PGS002556 (biochemistry_LDLdirect.P+T.1e-06) |
PSS009793| European Ancestry| 41,139 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0705 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014125 | PGS002556 (biochemistry_LDLdirect.P+T.1e-06) |
PSS009794| South Asian Ancestry| 7,638 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0205 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014174 | PGS002605 (biochemistry_LDLdirect.P+T.5e-08) |
PSS009791| African Ancestry| 6,068 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0428 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014223 | PGS002605 (biochemistry_LDLdirect.P+T.5e-08) |
PSS009792| East Asian Ancestry| 875 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0167 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014272 | PGS002605 (biochemistry_LDLdirect.P+T.5e-08) |
PSS009793| European Ancestry| 41,139 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0679 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014321 | PGS002605 (biochemistry_LDLdirect.P+T.5e-08) |
PSS009794| South Asian Ancestry| 7,638 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0195 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014370 | PGS002654 (biochemistry_LDLdirect.PolyFun-pred) |
PSS009791| African Ancestry| 6,068 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1091 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See biochemistry_LDLdirect.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014419 | PGS002654 (biochemistry_LDLdirect.PolyFun-pred) |
PSS009792| East Asian Ancestry| 875 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0724 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See biochemistry_LDLdirect.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014468 | PGS002654 (biochemistry_LDLdirect.PolyFun-pred) |
PSS009793| European Ancestry| 41,139 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1195 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See biochemistry_LDLdirect.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014517 | PGS002654 (biochemistry_LDLdirect.PolyFun-pred) |
PSS009794| South Asian Ancestry| 7,638 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0528 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See biochemistry_LDLdirect.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014566 | PGS002703 (biochemistry_LDLdirect.SBayesR) |
PSS009791| African Ancestry| 6,068 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0612 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014664 | PGS002703 (biochemistry_LDLdirect.SBayesR) |
PSS009793| European Ancestry| 41,139 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.1011 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014713 | PGS002703 (biochemistry_LDLdirect.SBayesR) |
PSS009794| South Asian Ancestry| 7,638 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0377 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013350 | PGS002369 (biochemistry_LDLdirect.BOLT-LMM-BBJ) |
PSS009794| South Asian Ancestry| 7,638 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0091 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013537 | PGS002409 (biochemistry_LDLdirect.P+T.0.0001) |
PSS009794| South Asian Ancestry| 7,638 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0203 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013880 | PGS002507 (biochemistry_LDLdirect.P+T.0.01) |
PSS009793| European Ancestry| 41,139 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0127 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014615 | PGS002703 (biochemistry_LDLdirect.SBayesR) |
PSS009792| East Asian Ancestry| 875 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: LDL Cholesterol | — | — | Incremental R2 (full model vs. covariates alone): 0.0478 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
|
PGS Sample Set ID (PSS) |
Phenotype Definitions and Methods | Participant Follow-up Time | Sample Numbers | Age of Study Participants | Sample Ancestry | Additional Ancestry Description | Cohort(s) | Additional Sample/Cohort Information |
|---|---|---|---|---|---|---|---|---|
| PSS000714 | — | — | 6,003 individuals | — | African unspecified | — | UKB | — |
| PSS000715 | — | — | 1,082 individuals | — | East Asian | — | UKB | — |
| PSS000716 | — | — | 23,535 individuals | — | European | Non-British White | UKB | — |
| PSS000717 | — | — | 7,319 individuals | — | South Asian | — | UKB | — |
| PSS000718 | — | — | 63,675 individuals | — | European (British) |
— | UKB | — |
| PSS001146 | — | — | 3,566 individuals | — | African unspecified | — | AADM | — |
| PSS001144 | — | — | 4,273 individuals | — | African unspecified | — | AADM | — |
| PSS001145 | — | — | 707 individuals | — | African unspecified | — | AADM | — |
| PSS001147 | — | — | 10,460 individuals | — | African unspecified | — | AWI-Gen | — |
| PSS001148 | — | — | 1,745 individuals | — | African unspecified | — | AWI-Gen | — |
| PSS001149 | — | — | 4,972 individuals | — | Sub-Saharan African | — | AWI-Gen | — |
| PSS001150 | — | — | 3,743 individuals | — | African unspecified | — | AWI-Gen | — |
| PSS000292 | Composite end point of cardiovascular events was defined as myocardial infarction, ischemic stroke, and death from coronary heart disease. Death from coronary heart disease was defined on the basis of codes 412 and 414 (ICD-9) or I22–I23 and I25 (ICD-10) in the Swedish Cause of Death Register. Myocardial infarction was defined on the basis of codes 410 and I21 in the International Classification of Diseases, 9th Revision and 10th Revision (ICD-9 and ICD-10), respectively. Ischemic stroke was defined on the basis of codes 434 or 436 (ICD-9) and I63 or I64 (ICD-10). | Median = 10.6 years | [
|
— | European | — | MDC | — |
| PSS001151 | — | — | 15,242 individuals | — | South Asian | — | G&H | — |
| PSS001152 | — | — | 118,260 individuals | — | East Asian | — | KoGES | — |
| PSS001156 | — | — | 18,251 individuals | — | African American or Afro-Caribbean | — | MVP | Subset not used in discovery dataset |
| PSS001157 | — | — | 4,155 individuals | — | Asian unspecified | — | MVP | Subset not used in discovery dataset |
| PSS001158 | — | — | 68,381 individuals | — | European | — | MVP | Subset not used in discovery dataset |
| PSS001153 | — | — | 1,341 individuals | — | African American or Afro-Caribbean | — | MGI | — |
| PSS001159 | — | — | 7,669 individuals | — | Hispanic or Latin American | — | MVP | Subset not used in discovery dataset |
| PSS001160 | — | — | 2,138 individuals | — | African American or Afro-Caribbean | — | PMB | — |
| PSS001161 | — | — | 28,217 individuals | — | East Asian | — | ToMMo | Only participants from Miyagi Prefecture were included |
| PSS001162 | — | — | 461,918 individuals | — | European, African unspecified, East Asian, South Asian | — | UKB | — |
| PSS001164 | — | — | 1,441 individuals | — | East Asian | — | UKB | — |
| PSS001165 | — | — | 389,158 individuals | — | European | — | UKB | — |
| PSS001166 | — | — | 6,814 individuals | — | South Asian | — | UKB | — |
| PSS001163 | — | — | 6,863 individuals | — | African unspecified | — | UKB | — |
| PSS008704 | — | — | 6,312 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS010010 | LOW DENSITY LIPOPROTEIN CHOL (LOINC: 13457-7); Quantitative | — | 9,288 individuals | — | European | — | MGI | — |
| PSS009892 | — | — | 75,973 individuals, 57.2 % Male samples |
Mean = 60.4 years Sd = 6.6 years |
European | — | UKB | — |
| PSS000181 | LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). | — | 4,680 individuals, 45.8 % Male samples |
Mean = 56.6 years Sd = 8.1 years |
African unspecified | — | UKB | Genotyping Array Cohort |
| PSS000182 | Cardiovascular disease events were defined as coronary and carotid revascularization, myocardial infarction, ischemic stroke, and all-cause mortality. The CVD events occurring before and after enrollment were included. Events occurring prior to enrollment were identified by either self-reported medical history and/or previous hospital admission documented in an electronic health record. | — | [ ,
43.36 % Male samples |
Mean = 56.64 years Sd = 7.99 years |
European, East Asian, African unspecified | — | UKB | Genotyping Array & Exome Sequencing Cohort |
| PSS000183 | LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). | — | 10,640 individuals, 45.8 % Male samples |
Mean = 56.6 years Sd = 8.1 years |
East Asian | — | UKB | Genotyping Array Cohort |
| PSS000184 | LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). | — | 439,871 individuals, 45.8 % Male samples |
Mean = 56.6 years Sd = 8.1 years |
European | — | UKB | Genotyping Array Cohort |
| PSS000185 | LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). | — | 439,871 individuals, 45.8 % Male samples |
Mean = 56.6 years Sd = 8.1 years |
European | — | UKB | Genotyping Array Cohort |
| PSS000185 | LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). | — | 10,640 individuals, 45.8 % Male samples |
Mean = 56.6 years Sd = 8.1 years |
East Asian | — | UKB | Genotyping Array Cohort |
| PSS000185 | LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). | — | 4,680 individuals, 45.8 % Male samples |
Mean = 56.6 years Sd = 8.1 years |
African unspecified | — | UKB | Genotyping Array Cohort |
| PSS008256 | — | — | 5,987 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS009627 | — | — | 4,416 individuals, 75.0 % Male samples |
European | — | UCC-SMART | UCC-SMART | |
| PSS000824 | — | — | 2,097 individuals | — | European | Participants self-identifying as white | MESA | — |
| PSS000825 | — | — | 1,987 individuals | — | European | Participants self-identifying as white | MESA | — |
| PSS010055 | — | — | 22,608 individuals | — | East Asian | — | KBA, KoGES | — |
| PSS010056 | — | — | 6,140 individuals, 43.0 % Male samples |
Median = 39.0 years | Greater Middle Eastern (Middle Eastern, North African or Persian) (Middle Eastern Arabs) |
— | QBB | — |
| PSS010058 | Cases are potential clinical FH cases | — | [
|
— | Not reported | — | NR | — |
| PSS000465 | Individuals ≥18 years with clinically diagnosed heterozygous familial hypercholesterolemia (FH) from the BCFH cohort. Individuals who were positive for the common French Canadian variant in the LDLR gene including del.15 kb of the promoter and exon 1, del.5 kb of exons 2 and 3, p.W66G (exon 3), p.E207K (exon 4), p.Y468X (exon 10), or p.C646Y (exon 14) in this study. Fasting clinical lipid profiles were obtained following a 4-week washout of any cholesterol-lowering medications from the CNMA cohort. Individuals who were positive for a LDLR, APOB, or PCSK9 variant that was deemed to cause FH in the UKB cohort.Any atherosclerotic cardiovascular disease (ASCVD) event, which was defined as myocardial infarction, coronary artery disease or carotid revascularization, transient ischemic attack or stroke. For the UK Biobank, retrospecitvie ASCVD was self reported and prospective ASCVD were defined using hospital episode statistics and 10th revision of the International Statistical Classification of Diseases and Related Health Problems diagnosis codes and OPCS Classification of Interventions and Procedures version 4 procedure codes | — | 1,120 individuals, 40.4 % Male samples |
Mean = 41.36 years | European, NR | European (94%), Not reported (6%) | BCFH, CNMA, UKB | — |
| PSS000466 | Any atherosclerotic cardiovascular disease (ASCVD) event, which was defined as myocardial infarction, coronary artery disease or carotid revascularization, transient ischemic attack or stroke. For the UK Biobank, retrospecitvie ASCVD was self reported and prospective ASCVD were defined using hospital episode statistics and 10th revision of the International Statistical Classification of Diseases and Related Health Problems diagnosis codes and OPCS Classification of Interventions and Procedures version 4 procedure codes | — | 389,127 individuals | — | European | — | UKB | — |
| PSS009637 | — | — | [
|
— | Not reported | — | NR | LIPIGEN (Lipid TransPort Disorders italian Genetic Network) database |
| PSS009639 | Non-fasting serum lipid levels were measured using the Cobas Integra 400 Plus Chemistry analyser, an automated analyser that employs four different technologies: absorption photometry, fluorescence polarization immunoassay, immune-turbidimetry, and potentiometry for accurate analysis. LDL-C were measured using the homogeneous enzymatic colorimetric assays | — | 2,569 individuals, 42.9 % Male samples |
Mean = 33.1 years Ci = [18.0, 48.2] years |
Sub-Saharan African (South Africans) |
— | SAZ | — |
| PSS007820 | — | — | 2,338 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS009376 | — | — | 18,968 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009666 | — | — | 7,016 individuals, 54.3 % Male samples |
Median = 53.0 years IQR = [46.0, 60.0] years |
South Asian | — | UKB | — |
| PSS009667 | — | — | 7,082 individuals, 43.3 % Male samples |
Median = 59.0 years IQR = [45.0, 58.0] years |
African American or Afro-Caribbean | Black/Caribbean | UKB | — |
| PSS009668 | — | — | 353,166 individuals, 46.2 % Male samples |
Median = 58.0 years IQR = [51.0, 63.0] years |
European | White | UKB | — |
| PSS010102 | — | — | 626 individuals, 49.4 % Male samples |
Mean = 46.2 years | European | — | BCFH | — |
| PSS010103 | — | — | 313 individuals, 41.5 % Male samples |
Mean = 51.0 years | South Asian, European, African unspecified, NR | South Asian, European, African, NR | NR | Ontario hypercholesterolemia cohort |
| PSS010104 | — | — | 89,528 individuals | — | European | — | UKB | — |
| PSS008924 | — | — | 3,651 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS000588 | Derived from the Friedewald’s formula | — | 426 individuals, 46.0 % Male samples |
Mean = 43.3 years Sd = 11.4 years |
East Asian (Chinese) |
— | NR | Adults |
| PSS000590 | Derived from the Friedewald’s formula | — | 1,941 individuals, 57.7 % Male samples |
Mean = 58.2 years Sd = 12.34 years |
East Asian (Chinese) |
— | HKDB | — |
| PSS000592 | Derived from the Friedewald’s formula | — | 865 individuals, 57.6 % Male samples |
Mean = 57.0 years Sd = 12.08 years |
East Asian (Chinese) |
— | HKDB | — |
| PSS000594 | Derived from the Friedewald’s formula | — | 4,917 individuals, 44.9 % Male samples |
Mean = 56.3 years Sd = 13.5 years |
East Asian (Chinese) |
— | HKDR | — |
| PSS000096 | Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. | — | 1,355 individuals, 46.2 % Male samples |
Mean = 61.68 years | African American or Afro-Caribbean | — | MESA | MESA Classic Cohort |
| PSS000097 | Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. | — | 666 individuals, 50.15 % Male samples |
Mean = 61.5 years | East Asian | — | MESA | MESA Classic Cohort |
| PSS000098 | Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. | — | 2,063 individuals, 46.78 % Male samples |
Mean = 62.09 years | European | — | MESA | MESA Classic Cohort |
| PSS000099 | Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. | — | 1,256 individuals, 48.89 % Male samples |
Mean = 60.65 years | Hispanic or Latin American | — | MESA | MESA Classic Cohort |
| PSS008478 | — | — | 1,122 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS000100 | Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) | — | 6,407 individuals, 44.0 % Male samples |
Mean = 34.0 years | Sub-Saharan African | — | APCDR | APCDR-Uganda study |
| PSS000101 | Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) | — | 21,295 individuals, 38.0 % Male samples |
Mean = 60.0 years | East Asian (Chinese) |
— | CKB | - 20810 samples had HDL measurements - 17662 samples had LDL measurements - 20222 samples had triglyceride measurements |
| PSS000102 | Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) | — | 1,641 individuals, 58.0 % Male samples |
Mean = 62.0 years | European (Greek) |
Population isolate from the Pomak villages in the North of Greece | HELIC | - 1186 samples had HDL measurements - 1186 samples had LDL measurements - 1176 samples had triglyceride measurements |
| PSS000103 | Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) | — | 1,945 individuals, 66.0 % Male samples |
Mean = 45.0 years | European (Greek) |
Population isolate from the Mylopotamos villages in Crete | HELIC | - 1078 samples had HDL measurements - 1075 samples had LDL measurements - 1066 samples had triglyceride measurements |
| PSS000104 | Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) | — | 9,962 individuals, 56.0 % Male samples |
Mean = 52.0 years | European | — | UKHLS | - 9706 samples had HDL measurements - 9767 samples had LDL measurements - 9635 samples had triglyceride measurements |
| PSS001058 | — | — | 3,020 individuals, 76.0 % Male samples |
Mean = 49.0 years Sd = 6.0 years |
European | — | Whitehall | — |
| PSS001059 | Cases are individuals with familial hypercholesterolaemia (FH). For the Simon Broome British Heart Foundation Study (SBFH), the diagnostic criteria for FH were defined by the Simon Broome Register criteria as an untreated total cholesterol above 7.5mmol/L or an LDL-C above 4.9mmol/L, and a family history of hypercholesterolaemia and/or early coronary heart disease for “possible FH”, and when together with the presence of tendon xanthomas either in the patient or in a first degree relative, as “definite FH”. Of the 640 FH individuals, 321 have FH with no known mutation, whilst 319 have FH with a known mutation. | — | [
|
— | European | — | Whitehall | Cases from the Oxford FH study (OXFH) and the Simon Broome British Heart Foundation Study (SBFH) |
| PSS001072 | Cases were individuals with hypobetalipoproteinemia (HBL). Of the 111 individuals with HBL, 38 had polygenic HBL, 40 had monogenic HBL and 33 had HBL from an unknown cause. Polgenic HBL was defined by a polygenic risk score (PRS) < 10th percentile of controls (PRS < 0.5925). For the 40 monogenic HBL individuals, 38 carried heterozygous APOB loss of fucntion variants and 2 carried heterozygous PCSK9 loss of function variants. In a subset of HBL cases, 7 polygenic cases , 26 monogenic cases and 13 uknown cause cases had liver steatosis. Whilst 17, 6 and 9 individuals did not have liver steatosis, respectively. Liver steatosis was diagnosed by abdominal ultrasonography. Alanine aminotransferase (ALT), aspartate aminotransferase, and gamma-glutamyl transpeptidase were determined by IFCC-standardized enzymatic methods using dedicated commercial kits. Individuals with ALT >1 upper limit of normal (>97.5th percentile) were considered to likely have liver injury. | — | [
|
— | Not reported | — | NR | Cases were obtained from the HYPOCHOL and GENLIP studies. Controls were obtained from the PREGO and GAZEL cohorts and the Finstère area, which are part of the FranceGenRef Consortium. |
| PSS008034 | — | — | 1,716 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS001083 | Of the 2,531 participants, 1,809 had longitudinal observations for total cholesterol (mg/dL), high density lipoprotein cholesterol (mg/dL) and trigycerides (mg/dL), 1,801 had longitudinal observations for low density lipoprotein cholesterol (mg/dL), 1,325 had longitudinal observations for waist circumference (inches), 2,355 had longitudinal observations for body mass index (kg/m^2) and 1,572 had longitudinal observations for homocysteine (μmol/L). | — | 2,531 individuals, 40.0 % Male samples |
Mean = 48.0 years Sd = 12.0 years |
European, Asian unspecified, Hispanic or Latin American, African unspecified, NR | European = 1,999, Asian unspecified = 228, Hispanic or Latin American = 101, African unspecified = 51, Not reported = 152 | NR | Participants were obtained from the Scientific Wellness Program. |
| PSS001154 | — | — | 17,190 individuals | — | European | — | MGI | — |
| PSS001155 | — | — | 360 individuals | — | Hispanic or Latin American | — | MGI | — |
| PSS009791 | — | — | 6,068 individuals | — | African unspecified | — | UKB | — |
| PSS000376 | We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). | — | 1,354 individuals, 47.56 % Male samples |
Mean = 16.22 years Sd = 0.66 years |
European | — | TRAILS | — |
| PSS009792 | — | — | 875 individuals | — | East Asian | — | UKB | — |
| PSS009793 | — | — | 41,139 individuals | — | European | Non-British European | UKB | — |
| PSS001084 | Moderate Age-Related Diabetes (MARD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001085 | Moderate Obesity-related Diabetes (MOD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001086 | Severe Autoimmune Diabetes (SAID) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001087 | Severe Insulin-Deficient Diabetes (SIDD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001088 | Severe Insulin-Resistant Diabetes (SIRD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS009794 | — | — | 7,638 individuals | — | South Asian | — | UKB | — |
| PSS007171 | — | — | 6,086 individuals | — | African unspecified | — | UKB | — |
| PSS007172 | — | — | 1,615 individuals | — | East Asian | — | UKB | — |
| PSS007173 | — | — | 23,728 individuals | — | European | non-white British ancestry | UKB | — |
| PSS007174 | — | — | 7,407 individuals | — | South Asian | — | UKB | — |
| PSS007175 | — | — | 64,356 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS009577 | Self-reported statin-use. Uncontrolled hypercholesterolaemia was defined as having baseline LDL-cholesterol >_3 mmol/L, among individuals in the treated hypercholesterolaemia sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. | Median = 11.4 years | [ ,
58.5 % Male samples |
Mean = 61.7 years | European (white British) |
— | UKB | — |
| PSS009578 | Self-reported statin-use. Uncontrolled hypercholesterolaemia was defined as having baseline LDL-cholesterol >_3 mmol/L, among individuals in the treated hypercholesterolaemia sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. | Median = 11.4 years | [ ,
58.5 % Male samples |
Mean = 61.7 years | European (white British) |
— | UKB | — |
| PSS009579 | Self-reported statin-use. Uncontrolled hypercholesterolaemia was defined as having baseline LDL-cholesterol >_3 mmol/L, among individuals in the treated hypercholesterolaemia sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. | Median = 11.4 years | [ ,
58.5 % Male samples |
Mean = 61.7 years | European (white British) |
— | UKB | — |
| PSS009580 | Self-reported statin-use. Uncontrolled hypercholesterolaemia was defined as having baseline LDL-cholesterol >_3 mmol/L, among individuals in the treated hypercholesterolaemia sub-cohort. We used prospective follow-up data to assess the composite outcome of incident major adverse cardiovascular events (MACE), which we defined as the first non-fatal stroke (ischaemic or haemorrhagic), non-fatal myocardial infarction, or fatal cardiovascular events, or disease-modifying cardiovascular procedures. We identified MACE components using International Classification of Diseases (ICD-9 and ICD-10) and the Office of Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) codes from Hospital Episodes Statistics (HES) data, and death registries data. | Median = 11.4 years | [ ,
58.5 % Male samples |
Mean = 61.7 years | European (white British) |
— | UKB | — |
| PSS001124 | Individuals with severe hypercholesterolemia (HC) had a LDL-C level > 4.9 mmol/L. 124 individuals had severe HC, based on this criteria. Individuals with intermediate HC had a LDL-C level 3.0 ≤ LDL‐C ≤ 4.9 mmol/L. 1927 individuals had intermediate HC, based on this criteria. Individuals classified as having normal LDL-C levels had LDL-C levels < 3.0 mmol/L. 2733 individuals had normal LDL-C levels, based on this criteria. | — | 4,787 individuals, 48.0 % Male samples |
Mean = 31.0 years Sd = 0.2 years |
European | — | NFBC | — |
| PSS009150 | — | — | 3,946 individuals | — | European | Poland (NE Europe) | UKB | — |