| Publication Information (EuropePMC) | |
| Title | Evaluation of polygenic scoring methods in five biobanks reveals greater variability between biobanks than between methods and highlights benefits of ensemble learning |
| doi | 10.1101/2023.11.20.23298215 |
| Publication Date | Nov. 16, 2023 |
| Journal | medRxiv Preprint |
| Author(s) | Monti R, Eick L, Hudjashov G, Läll K, Kanoni S, Wolford BN, Wingfield B, Pain O, Wharrie S, Jermy B, McMahon A, Hartonen T, Heyne H, Mars N, Hveem K, Inouye M, van Heel DA, Mägi R, Marttinen P, Ripatti S, Ganna A, Lippert C. |
| Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants |
Ancestry distribution GWAS Dev Eval |
Scoring File (FTP Link) |
|---|---|---|---|---|---|---|
| PGS004139 (sbayesr.auto.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 945,385 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004139/ScoringFiles/PGS004139.txt.gz | |
| PGS004141 (sbayesr.auto.GCST007954.HbA1c) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HbA1c | HbA1c measurement | 683,029 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004141/ScoringFiles/PGS004141.txt.gz | |
| PGS004142 (sbayesr.auto.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 804,867 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004142/ScoringFiles/PGS004142.txt.gz |
| PGS004144 (sbayesr.auto.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 822,407 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004144/ScoringFiles/PGS004144.txt.gz |
| PGS004145 (sbayesr.auto.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 822,407 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004145/ScoringFiles/PGS004145.txt.gz | |
| PGS004149 (sbayesr.auto.GCST90018959.Height) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Height | body height | 962,278 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004149/ScoringFiles/PGS004149.txt.gz |
| PGS004146 (sbayesr.auto.GCST90012877.AD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Alzheimer's disease | Alzheimer disease | 915,771 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004146/ScoringFiles/PGS004146.txt.gz |
| PGS004135 (sbayesr.auto.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 912,746 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004135/ScoringFiles/PGS004135.txt.gz | |
| PGS004140 (sbayesr.auto.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 875,144 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004140/ScoringFiles/PGS004140.txt.gz | |
| PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 45,996 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004147/ScoringFiles/PGS004147.txt.gz | |
| PGS004148 (sbayesr.auto.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 671,211 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004148/ScoringFiles/PGS004148.txt.gz | |
| PGS004136 (sbayesr.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 930,497 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004136/ScoringFiles/PGS004136.txt.gz | |
| PGS004096 (prscs.CV.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 1,011,571 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004096/ScoringFiles/PGS004096.txt.gz | |
| PGS004045 (ldpred2.CV.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 1,050,295 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004045/ScoringFiles/PGS004045.txt.gz |
| PGS003981 (dbslmm.auto.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 1,103,311 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003981/ScoringFiles/PGS003981.txt.gz | |
| PGS004039 (ldpred2.CV.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 958,046 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004039/ScoringFiles/PGS004039.txt.gz | |
| PGS004102 (prscs.CV.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 61,651 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004102/ScoringFiles/PGS004102.txt.gz | |
| PGS003982 (dbslmm.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,071,764 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003982/ScoringFiles/PGS003982.txt.gz | |
| PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 63,182 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003993/ScoringFiles/PGS003993.txt.gz | |
| PGS003994 (dbslmm.auto.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 778,205 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003994/ScoringFiles/PGS003994.txt.gz | |
| PGS003989 (dbslmm.auto.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 1,141,637 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003989/ScoringFiles/PGS003989.txt.gz | |
| PGS003988 (dbslmm.auto.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 1,141,637 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003988/ScoringFiles/PGS003988.txt.gz |
| PGS003990 (dbslmm.auto.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 1,005,456 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003990/ScoringFiles/PGS003990.txt.gz |
| PGS003986 (dbslmm.auto.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 1,138,429 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003986/ScoringFiles/PGS003986.txt.gz | |
| PGS003980 (dbslmm.auto.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 1,039,020 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003980/ScoringFiles/PGS003980.txt.gz | |
| PGS004106 (pt_clump.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 35 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004106/ScoringFiles/PGS004106.txt.gz | |
| PGS004087 (prscs.auto.GCST007954.HbA1c) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HbA1c | HbA1c measurement | 989,845 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004087/ScoringFiles/PGS004087.txt.gz | |
| PGS004021 (lassosum.CV.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 315,740 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004021/ScoringFiles/PGS004021.txt.gz | |
| PGS004095 (prscs.auto.GCST90018959.Height) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Height | body height | 1,088,125 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004095/ScoringFiles/PGS004095.txt.gz |
| PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 1,011,468 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004041/ScoringFiles/PGS004041.txt.gz | |
| PGS003983 (dbslmm.auto.GCST004988.Breast_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Breast cancer | breast carcinoma | 1,137,459 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003983/ScoringFiles/PGS003983.txt.gz | |
| PGS003995 (dbslmm.auto.GCST90018959.Height) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Height | body height | 1,119,867 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003995/ScoringFiles/PGS003995.txt.gz |
| PGS004130 (pt_clump_nested.CV.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 7,279 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004130/ScoringFiles/PGS004130.txt.gz |
| PGS003999 (lassosum.auto.GCST004988.Breast_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Breast cancer | breast carcinoma | 13,086 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003999/ScoringFiles/PGS003999.txt.gz | |
| PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 1,121,845 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003984/ScoringFiles/PGS003984.txt.gz | |
| PGS004019 (lassosum.CV.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 56,575 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004019/ScoringFiles/PGS004019.txt.gz | |
| PGS004111 (pt_clump.auto.GCST007954.HbA1c) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HbA1c | HbA1c measurement | 51 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004111/ScoringFiles/PGS004111.txt.gz | |
| PGS004113 (pt_clump.auto.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 301 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004113/ScoringFiles/PGS004113.txt.gz | |
| PGS004114 (pt_clump.auto.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 248 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004114/ScoringFiles/PGS004114.txt.gz |
| PGS004018 (lassosum.CV.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 100,595 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004018/ScoringFiles/PGS004018.txt.gz |
| PGS003985 (dbslmm.auto.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 1,139,671 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003985/ScoringFiles/PGS003985.txt.gz | |
| PGS003987 (dbslmm.auto.GCST007954.HbA1c) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HbA1c | HbA1c measurement | 1,009,642 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003987/ScoringFiles/PGS003987.txt.gz | |
| PGS003991 (dbslmm.auto.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 1,005,456 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003991/ScoringFiles/PGS003991.txt.gz | |
| PGS003997 (lassosum.auto.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 8,406 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003997/ScoringFiles/PGS003997.txt.gz | |
| PGS004040 (ldpred2.CV.GCST004988.Breast_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Breast cancer | breast carcinoma | 1,041,298 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004040/ScoringFiles/PGS004040.txt.gz | |
| PGS004001 (lassosum.auto.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 26,873 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004001/ScoringFiles/PGS004001.txt.gz | |
| PGS004002 (lassosum.auto.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 7,708 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004002/ScoringFiles/PGS004002.txt.gz | |
| PGS004004 (lassosum.auto.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 15,373 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004004/ScoringFiles/PGS004004.txt.gz |
| PGS004007 (lassosum.auto.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 19,101 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004007/ScoringFiles/PGS004007.txt.gz | |
| PGS004009 (lassosum.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 4,031 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004009/ScoringFiles/PGS004009.txt.gz | |
| PGS004010 (lassosum.auto.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 27,045 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004010/ScoringFiles/PGS004010.txt.gz | |
| PGS004014 (lassosum.CV.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 95,649 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004014/ScoringFiles/PGS004014.txt.gz | |
| PGS004022 (ldpred2.auto.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 919,377 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004022/ScoringFiles/PGS004022.txt.gz | |
| PGS004023 (ldpred2.auto.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 1,018,068 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004023/ScoringFiles/PGS004023.txt.gz | |
| PGS004024 (ldpred2.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 958,046 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004024/ScoringFiles/PGS004024.txt.gz | |
| PGS004027 (ldpred2.auto.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 1,045,276 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004027/ScoringFiles/PGS004027.txt.gz | |
| PGS004029 (ldpred2.auto.GCST007954.HbA1c) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HbA1c | HbA1c measurement | 907,906 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004029/ScoringFiles/PGS004029.txt.gz | |
| PGS004031 (ldpred2.auto.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 1,050,295 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004031/ScoringFiles/PGS004031.txt.gz | |
| PGS004033 (ldpred2.auto.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 865,644 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004033/ScoringFiles/PGS004033.txt.gz | |
| PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 56,562 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004035/ScoringFiles/PGS004035.txt.gz | |
| PGS004038 (ldpred2.CV.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 1,018,068 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004038/ScoringFiles/PGS004038.txt.gz | |
| PGS004042 (ldpred2.CV.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 1,045,276 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004042/ScoringFiles/PGS004042.txt.gz | |
| PGS004043 (ldpred2.CV.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 578,264 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004043/ScoringFiles/PGS004043.txt.gz | |
| PGS004044 (ldpred2.CV.GCST007954.HbA1c) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HbA1c | HbA1c measurement | 907,906 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004044/ScoringFiles/PGS004044.txt.gz | |
| PGS004046 (ldpred2.CV.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 1,050,295 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004046/ScoringFiles/PGS004046.txt.gz | |
| PGS004047 (ldpred2.CV.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 865,644 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004047/ScoringFiles/PGS004047.txt.gz |
| PGS004048 (ldpred2.CV.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 865,644 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004048/ScoringFiles/PGS004048.txt.gz | |
| PGS004050 (megaprs.auto.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 609,706 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004050/ScoringFiles/PGS004050.txt.gz | |
| PGS004052 (megaprs.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 800,598 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004052/ScoringFiles/PGS004052.txt.gz | |
| PGS004054 (megaprs.auto.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 852,173 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004054/ScoringFiles/PGS004054.txt.gz | |
| PGS004056 (megaprs.auto.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 791,965 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004056/ScoringFiles/PGS004056.txt.gz | |
| PGS004037 (ldpred2.CV.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 919,377 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004037/ScoringFiles/PGS004037.txt.gz | |
| PGS004061 (megaprs.auto.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 677,631 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004061/ScoringFiles/PGS004061.txt.gz | |
| PGS004063 (megaprs.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 56,288 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004063/ScoringFiles/PGS004063.txt.gz | |
| PGS004064 (megaprs.auto.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 402,214 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004064/ScoringFiles/PGS004064.txt.gz | |
| PGS004066 (megaprs.CV.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 602,445 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004066/ScoringFiles/PGS004066.txt.gz | |
| PGS004070 (megaprs.CV.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 852,173 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004070/ScoringFiles/PGS004070.txt.gz | |
| PGS004072 (megaprs.CV.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 791,965 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004072/ScoringFiles/PGS004072.txt.gz | |
| PGS004075 (megaprs.CV.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 846,995 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004075/ScoringFiles/PGS004075.txt.gz | |
| PGS004077 (megaprs.CV.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 677,631 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004077/ScoringFiles/PGS004077.txt.gz | |
| PGS004080 (prscs.auto.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 1,011,571 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004080/ScoringFiles/PGS004080.txt.gz | |
| PGS004086 (prscs.auto.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 1,103,534 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004086/ScoringFiles/PGS004086.txt.gz | |
| PGS004092 (prscs.auto.GCST90012877.AD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Alzheimer's disease | Alzheimer disease | 1,109,233 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004092/ScoringFiles/PGS004092.txt.gz |
| PGS004093 (prscs.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 61,651 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004093/ScoringFiles/PGS004093.txt.gz | |
| PGS004097 (prscs.CV.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 1,073,268 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004097/ScoringFiles/PGS004097.txt.gz | |
| PGS004098 (prscs.CV.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 1,091,747 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004098/ScoringFiles/PGS004098.txt.gz | |
| PGS004100 (prscs.CV.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 1,103,534 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004100/ScoringFiles/PGS004100.txt.gz | |
| PGS004103 (prscs.CV.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 755,048 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004103/ScoringFiles/PGS004103.txt.gz | |
| PGS004107 (pt_clump.auto.GCST004988.Breast_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Breast cancer | breast carcinoma | 209 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004107/ScoringFiles/PGS004107.txt.gz | |
| PGS004112 (pt_clump.auto.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 301 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004112/ScoringFiles/PGS004112.txt.gz |
| PGS004115 (pt_clump.auto.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 248 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004115/ScoringFiles/PGS004115.txt.gz | |
| PGS004118 (pt_clump.auto.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 91 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004118/ScoringFiles/PGS004118.txt.gz | |
| PGS004119 (pt_clump.auto.GCST90018959.Height) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Height | body height | 2,632 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004119/ScoringFiles/PGS004119.txt.gz |
| PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 297 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004122/ScoringFiles/PGS004122.txt.gz | |
| PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 13 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004108/ScoringFiles/PGS004108.txt.gz | |
| PGS004109 (pt_clump.auto.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 200 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004109/ScoringFiles/PGS004109.txt.gz | |
| PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 5,808 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004124/ScoringFiles/PGS004124.txt.gz | |
| PGS004126 (pt_clump_nested.CV.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 579 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004126/ScoringFiles/PGS004126.txt.gz | |
| PGS004129 (pt_clump_nested.CV.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 8,543 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004129/ScoringFiles/PGS004129.txt.gz | |
| PGS004131 (pt_clump_nested.CV.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 7,279 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004131/ScoringFiles/PGS004131.txt.gz | |
| PGS004133 (pt_clump_nested.CV.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 155 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004133/ScoringFiles/PGS004133.txt.gz | |
| PGS004134 (sbayesr.auto.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 782,021 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004134/ScoringFiles/PGS004134.txt.gz | |
| PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 888,649 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004138/ScoringFiles/PGS004138.txt.gz | |
| PGS004143 (sbayesr.auto.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 804,867 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004143/ScoringFiles/PGS004143.txt.gz | |
| PGS004104 (pt_clump.auto.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 83 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004104/ScoringFiles/PGS004104.txt.gz | |
| PGS004151 (UKBB_EnsPGS.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 1,102,205 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004151/ScoringFiles/PGS004151.txt.gz | |
| PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 1,116,976 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004154/ScoringFiles/PGS004154.txt.gz | |
| PGS004157 (UKBB_EnsPGS.GCST007954.HbA1c) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HbA1c | HbA1c measurement | 1,009,664 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004157/ScoringFiles/PGS004157.txt.gz | |
| PGS004160 (UKBB_EnsPGS.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 976,174 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004160/ScoringFiles/PGS004160.txt.gz |
| PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 62,645 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004162/ScoringFiles/PGS004162.txt.gz | |
| PGS004105 (pt_clump.auto.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 139 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004105/ScoringFiles/PGS004105.txt.gz | |
| PGS004101 (prscs.CV.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 1,109,217 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004101/ScoringFiles/PGS004101.txt.gz |
| PGS004116 (pt_clump.auto.GCST90012877.AD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Alzheimer's disease | Alzheimer disease | 58 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004116/ScoringFiles/PGS004116.txt.gz |
| PGS003998 (lassosum.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 5,548 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003998/ScoringFiles/PGS003998.txt.gz | |
| PGS004003 (lassosum.auto.GCST007954.HbA1c) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HbA1c | HbA1c measurement | 4,697 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004003/ScoringFiles/PGS004003.txt.gz | |
| PGS004006 (lassosum.auto.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 19,101 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004006/ScoringFiles/PGS004006.txt.gz |
| PGS004008 (lassosum.auto.GCST90012877.AD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Alzheimer's disease | Alzheimer disease | 5,663 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004008/ScoringFiles/PGS004008.txt.gz |
| PGS004011 (lassosum.auto.GCST90018959.Height) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Height | body height | 315,596 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004011/ScoringFiles/PGS004011.txt.gz |
| PGS004013 (lassosum.CV.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 22,690 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004013/ScoringFiles/PGS004013.txt.gz | |
| PGS004016 (lassosum.CV.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 88,605 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004016/ScoringFiles/PGS004016.txt.gz |
| PGS004017 (lassosum.CV.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 88,605 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004017/ScoringFiles/PGS004017.txt.gz | |
| PGS004020 (lassosum.CV.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 6,682 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004020/ScoringFiles/PGS004020.txt.gz | |
| PGS004051 (megaprs.auto.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 784,928 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004051/ScoringFiles/PGS004051.txt.gz | |
| PGS004091 (prscs.auto.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 976,777 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004091/ScoringFiles/PGS004091.txt.gz | |
| PGS004055 (megaprs.auto.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 777,255 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004055/ScoringFiles/PGS004055.txt.gz | |
| PGS004057 (megaprs.auto.GCST007954.HbA1c) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HbA1c | HbA1c measurement | 514,367 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004057/ScoringFiles/PGS004057.txt.gz | |
| PGS004059 (megaprs.auto.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 846,995 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004059/ScoringFiles/PGS004059.txt.gz | |
| PGS004060 (megaprs.auto.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 677,631 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004060/ScoringFiles/PGS004060.txt.gz |
| PGS004062 (megaprs.auto.GCST90012877.AD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Alzheimer's disease | Alzheimer disease | 691,136 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004062/ScoringFiles/PGS004062.txt.gz |
| PGS004065 (megaprs.auto.GCST90018959.Height) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Height | body height | 980,499 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004065/ScoringFiles/PGS004065.txt.gz |
| PGS004067 (megaprs.CV.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 784,928 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004067/ScoringFiles/PGS004067.txt.gz | |
| PGS004069 (megaprs.CV.GCST004988.Breast_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Breast cancer | breast carcinoma | 869,407 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004069/ScoringFiles/PGS004069.txt.gz | |
| PGS004071 (megaprs.CV.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 777,255 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004071/ScoringFiles/PGS004071.txt.gz | |
| PGS004074 (megaprs.CV.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 846,995 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004074/ScoringFiles/PGS004074.txt.gz |
| PGS004076 (megaprs.CV.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 677,631 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004076/ScoringFiles/PGS004076.txt.gz |
| PGS004078 (megaprs.CV.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 56,288 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004078/ScoringFiles/PGS004078.txt.gz | |
| PGS004083 (prscs.auto.GCST004988.Breast_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Breast cancer | breast carcinoma | 1,103,877 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004083/ScoringFiles/PGS004083.txt.gz | |
| PGS004090 (prscs.auto.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 976,777 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004090/ScoringFiles/PGS004090.txt.gz |
| PGS004099 (prscs.CV.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 1,105,199 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004099/ScoringFiles/PGS004099.txt.gz | |
| PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 131 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004117/ScoringFiles/PGS004117.txt.gz | |
| PGS004120 (pt_clump_nested.CV.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 23,190 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004120/ScoringFiles/PGS004120.txt.gz | |
| PGS004121 (pt_clump_nested.CV.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 774 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004121/ScoringFiles/PGS004121.txt.gz | |
| PGS004123 (pt_clump_nested.CV.GCST004988.Breast_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Breast cancer | breast carcinoma | 982 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004123/ScoringFiles/PGS004123.txt.gz | |
| PGS004125 (pt_clump_nested.CV.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 765 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004125/ScoringFiles/PGS004125.txt.gz | |
| PGS004127 (pt_clump_nested.CV.GCST007954.HbA1c) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HbA1c | HbA1c measurement | 246 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004127/ScoringFiles/PGS004127.txt.gz | |
| PGS004128 (pt_clump_nested.CV.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 8,543 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004128/ScoringFiles/PGS004128.txt.gz |
| PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 354 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004132/ScoringFiles/PGS004132.txt.gz | |
| PGS004137 (sbayesr.auto.GCST004988.Breast_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Breast cancer | breast carcinoma | 950,524 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004137/ScoringFiles/PGS004137.txt.gz | |
| PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,071,786 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004152/ScoringFiles/PGS004152.txt.gz | |
| PGS004155 (UKBB_EnsPGS.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 1,139,693 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004155/ScoringFiles/PGS004155.txt.gz | |
| PGS004156 (UKBB_EnsPGS.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 1,138,452 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004156/ScoringFiles/PGS004156.txt.gz | |
| PGS004158 (UKBB_EnsPGS.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 1,135,455 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004158/ScoringFiles/PGS004158.txt.gz |
| PGS004159 (UKBB_EnsPGS.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 1,141,659 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004159/ScoringFiles/PGS004159.txt.gz | |
| PGS004161 (UKBB_EnsPGS.GCST008972.Urate) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Urate | urate measurement | 1,005,478 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004161/ScoringFiles/PGS004161.txt.gz | |
| PGS004163 (UKBB_EnsPGS.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 778,275 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004163/ScoringFiles/PGS004163.txt.gz | |
| PGS004025 (ldpred2.auto.GCST004988.Breast_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Breast cancer | breast carcinoma | 1,041,298 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004025/ScoringFiles/PGS004025.txt.gz | |
| PGS003992 (dbslmm.auto.GCST90012877.AD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Alzheimer's disease | Alzheimer disease | 1,136,212 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003992/ScoringFiles/PGS003992.txt.gz |
| PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 1,011,468 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004026/ScoringFiles/PGS004026.txt.gz | |
| PGS004049 (ldpred2.CV.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 373,627 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004049/ScoringFiles/PGS004049.txt.gz | |
| PGS004058 (megaprs.auto.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 846,995 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004058/ScoringFiles/PGS004058.txt.gz |
| PGS004068 (megaprs.CV.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 800,598 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004068/ScoringFiles/PGS004068.txt.gz | |
| PGS004085 (prscs.auto.GCST006085.Prostate_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Prostate cancer | prostate carcinoma | 1,105,199 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004085/ScoringFiles/PGS004085.txt.gz | |
| PGS004110 (pt_clump.auto.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 161 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004110/ScoringFiles/PGS004110.txt.gz | |
| PGS004153 (UKBB_EnsPGS.GCST004988.Breast_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Breast cancer | breast carcinoma | 1,133,268 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004153/ScoringFiles/PGS004153.txt.gz | |
| PGS003996 (lassosum.auto.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 16,785 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003996/ScoringFiles/PGS003996.txt.gz | |
| PGS004012 (lassosum.CV.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 437,695 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004012/ScoringFiles/PGS004012.txt.gz | |
| PGS004150 (UKBB_EnsPGS.GCST002783.BMI) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Body mass index (BMI) | body mass index | 1,039,042 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004150/ScoringFiles/PGS004150.txt.gz | |
| PGS004079 (megaprs.CV.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 402,214 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004079/ScoringFiles/PGS004079.txt.gz | |
| PGS004030 (ldpred2.auto.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 1,050,295 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004030/ScoringFiles/PGS004030.txt.gz |
| PGS004032 (ldpred2.auto.GCST008972.Gout) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Gout | gout | 865,644 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004032/ScoringFiles/PGS004032.txt.gz |
| PGS004034 (ldpred2.auto.GCST90012877.AD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Alzheimer's disease | Alzheimer disease | 1,046,908 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004034/ScoringFiles/PGS004034.txt.gz |
| PGS004036 (ldpred2.auto.GCST90018959.Height) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Height | body height | 929,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004036/ScoringFiles/PGS004036.txt.gz |
| PGS004084 (prscs.auto.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 1,091,747 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004084/ScoringFiles/PGS004084.txt.gz | |
| PGS004089 (prscs.auto.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 1,109,217 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004089/ScoringFiles/PGS004089.txt.gz | |
| PGS004082 (prscs.auto.GCST004773.T2D) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,043,329 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004082/ScoringFiles/PGS004082.txt.gz | |
| PGS004088 (prscs.auto.GCST008059.CKD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Chronic kidney disease (CKD) | chronic kidney disease | 1,109,217 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004088/ScoringFiles/PGS004088.txt.gz |
| PGS004094 (prscs.auto.GCST90013534.RA) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Rheumatoid arthritis | rheumatoid arthritis | 755,048 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004094/ScoringFiles/PGS004094.txt.gz | |
| PGS004000 (lassosum.auto.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 2,371 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004000/ScoringFiles/PGS004000.txt.gz | |
| PGS004005 (lassosum.auto.GCST008059.eGFR) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
eGFR | glomerular filtration rate | 15,373 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004005/ScoringFiles/PGS004005.txt.gz | |
| PGS004015 (lassosum.CV.GCST005838.Stroke) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Stroke | stroke | 65,138 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004015/ScoringFiles/PGS004015.txt.gz | |
| PGS004028 (ldpred2.auto.GCST007140.HDL) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HDL cholesterol | high density lipoprotein cholesterol measurement | 992,696 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004028/ScoringFiles/PGS004028.txt.gz | |
| PGS004053 (megaprs.auto.GCST004988.Breast_cancer) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Breast cancer | breast carcinoma | 869,407 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004053/ScoringFiles/PGS004053.txt.gz | |
| PGS004073 (megaprs.CV.GCST007954.HbA1c) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
HbA1c | HbA1c measurement | 514,367 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004073/ScoringFiles/PGS004073.txt.gz | |
| PGS004081 (prscs.auto.GCST004131.IBD) |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Inflammatory bowel disease (IBD) | inflammatory bowel disease | 1,073,268 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004081/ScoringFiles/PGS004081.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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM019425 | PGS003999 (lassosum.auto.GCST004988.Breast_cancer) |
PSS011215| European Ancestry| 130,758 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.65454 β: 0.50352 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019426 | PGS003999 (lassosum.auto.GCST004988.Breast_cancer) |
PSS011227| European Ancestry| 217,530 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.7112 β: 0.5372 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019912 | PGS004018 (lassosum.CV.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.79341 β: 0.58412 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019198 | PGS004096 (prscs.CV.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.21196 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019193 | PGS004050 (megaprs.auto.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.20292 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019194 | PGS004050 (megaprs.auto.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.23169 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019150 | PGS004120 (pt_clump_nested.CV.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.22681 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019151 | PGS004120 (pt_clump_nested.CV.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.13234 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019152 | PGS004120 (pt_clump_nested.CV.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.23703 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019153 | PGS004120 (pt_clump_nested.CV.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.18732 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019154 | PGS004120 (pt_clump_nested.CV.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.24564 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019155 | PGS004037 (ldpred2.CV.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.27279 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019156 | PGS004037 (ldpred2.CV.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.17614 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019157 | PGS004037 (ldpred2.CV.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.28307 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019158 | PGS004037 (ldpred2.CV.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.23025 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019159 | PGS004037 (ldpred2.CV.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.29441 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019160 | PGS004104 (pt_clump.auto.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.13262 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019161 | PGS004104 (pt_clump.auto.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.13437 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019162 | PGS004104 (pt_clump.auto.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.13976 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019163 | PGS004104 (pt_clump.auto.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.13361 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019164 | PGS004104 (pt_clump.auto.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.12888 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019165 | PGS004150 (UKBB_EnsPGS.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.28774 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019166 | PGS004150 (UKBB_EnsPGS.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.21492 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019167 | PGS004150 (UKBB_EnsPGS.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.2987 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019168 | PGS004150 (UKBB_EnsPGS.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.25738 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019169 | PGS004150 (UKBB_EnsPGS.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.31034 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019170 | PGS003980 (dbslmm.auto.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.26843 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019171 | PGS003980 (dbslmm.auto.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.21006 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019172 | PGS003980 (dbslmm.auto.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.28302 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019173 | PGS003980 (dbslmm.auto.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.23645 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019174 | PGS003980 (dbslmm.auto.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.28337 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019175 | PGS004134 (sbayesr.auto.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.23628 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019176 | PGS004134 (sbayesr.auto.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.18382 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019177 | PGS004134 (sbayesr.auto.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.23811 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019178 | PGS004134 (sbayesr.auto.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.2074 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019182 | PGS004022 (ldpred2.auto.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.22725 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019183 | PGS004022 (ldpred2.auto.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.20804 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019184 | PGS004022 (ldpred2.auto.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.23174 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019185 | PGS004066 (megaprs.CV.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.27372 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019186 | PGS004066 (megaprs.CV.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.19873 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019187 | PGS004066 (megaprs.CV.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.28643 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019188 | PGS004066 (megaprs.CV.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.24111 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019189 | PGS004066 (megaprs.CV.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.29808 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019190 | PGS004050 (megaprs.auto.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.22924 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019191 | PGS004050 (megaprs.auto.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.19661 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019192 | PGS004050 (megaprs.auto.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.236 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019195 | PGS004096 (prscs.CV.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.26769 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019196 | PGS004096 (prscs.CV.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.16504 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019197 | PGS004096 (prscs.CV.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.27794 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019199 | PGS004096 (prscs.CV.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.29179 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019200 | PGS004080 (prscs.auto.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.26849 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019201 | PGS004080 (prscs.auto.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.20035 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019202 | PGS004080 (prscs.auto.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.27952 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019203 | PGS004080 (prscs.auto.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.23887 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019204 | PGS004080 (prscs.auto.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.28279 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019205 | PGS003996 (lassosum.auto.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.24937 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019206 | PGS003996 (lassosum.auto.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.21681 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019207 | PGS003996 (lassosum.auto.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.25672 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019208 | PGS003996 (lassosum.auto.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.2328 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019209 | PGS003996 (lassosum.auto.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.2558 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019210 | PGS004012 (lassosum.CV.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.27473 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019211 | PGS004012 (lassosum.CV.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.20034 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019212 | PGS004012 (lassosum.CV.GCST002783.BMI) |
PSS011253| European Ancestry| 66,663 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.28629 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019213 | PGS004012 (lassosum.CV.GCST002783.BMI) |
PSS011281| South Asian Ancestry| 9,097 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.24618 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019214 | PGS004012 (lassosum.CV.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.29892 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019215 | PGS004038 (ldpred2.CV.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.3661 β: 0.31196 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019216 | PGS004038 (ldpred2.CV.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 2.00709 β: 0.69669 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019217 | PGS004038 (ldpred2.CV.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.946 β: 0.66578 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019218 | PGS004038 (ldpred2.CV.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.55477 β: 0.44133 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019219 | PGS004038 (ldpred2.CV.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.71999 β: 0.54232 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019220 | PGS004038 (ldpred2.CV.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.96885 β: 0.67745 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019221 | PGS004105 (pt_clump.auto.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.24143 β: 0.21627 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019222 | PGS004105 (pt_clump.auto.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.63002 β: 0.48859 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019223 | PGS004105 (pt_clump.auto.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.40101 β: 0.33719 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019224 | PGS004105 (pt_clump.auto.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.35946 β: 0.30709 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019225 | PGS004105 (pt_clump.auto.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.34635 β: 0.29739 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019226 | PGS004105 (pt_clump.auto.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.59062 β: 0.46412 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019227 | PGS004121 (pt_clump_nested.CV.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.27323 β: 0.24156 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019228 | PGS004121 (pt_clump_nested.CV.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.74769 β: 0.55829 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019229 | PGS004121 (pt_clump_nested.CV.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.51461 β: 0.41516 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019230 | PGS004121 (pt_clump_nested.CV.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.38976 β: 0.32913 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019231 | PGS004121 (pt_clump_nested.CV.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.49325 β: 0.40096 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019232 | PGS004121 (pt_clump_nested.CV.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.68525 β: 0.52191 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019233 | PGS003981 (dbslmm.auto.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.33244 β: 0.28701 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019234 | PGS003981 (dbslmm.auto.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.89729 β: 0.64043 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019235 | PGS003981 (dbslmm.auto.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.82983 β: 0.60422 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019236 | PGS003981 (dbslmm.auto.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.51174 β: 0.41326 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019237 | PGS003981 (dbslmm.auto.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.62008 β: 0.48247 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019238 | PGS003981 (dbslmm.auto.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.8704 β: 0.62615 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019239 | PGS004151 (UKBB_EnsPGS.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.39728 β: 0.33453 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019240 | PGS004151 (UKBB_EnsPGS.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 2.06398 β: 0.72464 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019241 | PGS004151 (UKBB_EnsPGS.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.99477 β: 0.69053 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019242 | PGS004151 (UKBB_EnsPGS.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.58122 β: 0.4582 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019243 | PGS004151 (UKBB_EnsPGS.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.76291 β: 0.56697 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019244 | PGS004151 (UKBB_EnsPGS.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 2.04212 β: 0.71399 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019245 | PGS004135 (sbayesr.auto.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.33765 β: 0.29091 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019247 | PGS004135 (sbayesr.auto.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.8584 β: 0.61972 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019248 | PGS004135 (sbayesr.auto.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.53371 β: 0.42769 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019249 | PGS004135 (sbayesr.auto.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.68556 β: 0.5221 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019250 | PGS004135 (sbayesr.auto.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.91118 β: 0.64772 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019252 | PGS004023 (ldpred2.auto.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.98269 β: 0.68445 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019253 | PGS004023 (ldpred2.auto.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.96487 β: 0.67543 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019254 | PGS004023 (ldpred2.auto.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.53961 β: 0.43153 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019255 | PGS004023 (ldpred2.auto.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.7204 β: 0.54256 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019256 | PGS004023 (ldpred2.auto.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.95616 β: 0.67098 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019257 | PGS004051 (megaprs.auto.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.36888 β: 0.314 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019258 | PGS004051 (megaprs.auto.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 2.00653 β: 0.69641 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019259 | PGS004051 (megaprs.auto.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.90388 β: 0.64389 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019260 | PGS004051 (megaprs.auto.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.53763 β: 0.43024 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019261 | PGS004051 (megaprs.auto.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.63845 β: 0.49375 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019262 | PGS004051 (megaprs.auto.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.9624 β: 0.67417 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019263 | PGS004067 (megaprs.CV.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.38476 β: 0.32553 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019264 | PGS004067 (megaprs.CV.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 2.01137 β: 0.69881 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019265 | PGS004067 (megaprs.CV.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.90373 β: 0.64382 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019266 | PGS004067 (megaprs.CV.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.53272 β: 0.42704 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019267 | PGS004067 (megaprs.CV.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.64423 β: 0.49727 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019268 | PGS004067 (megaprs.CV.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.9918 β: 0.68904 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019269 | PGS004097 (prscs.CV.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.33762 β: 0.29089 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019270 | PGS004097 (prscs.CV.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.9368 β: 0.66104 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019271 | PGS004097 (prscs.CV.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.81277 β: 0.59485 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019272 | PGS004097 (prscs.CV.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.53892 β: 0.43108 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019273 | PGS004097 (prscs.CV.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.64559 β: 0.4981 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019274 | PGS004097 (prscs.CV.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.86814 β: 0.62494 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019275 | PGS004081 (prscs.auto.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.33947 β: 0.29227 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019276 | PGS004081 (prscs.auto.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.93798 β: 0.66165 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019277 | PGS004081 (prscs.auto.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.81701 β: 0.59719 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019278 | PGS004081 (prscs.auto.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.52897 β: 0.4246 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019279 | PGS004081 (prscs.auto.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.64491 β: 0.49768 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019281 | PGS004013 (lassosum.CV.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.37266 β: 0.31675 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019282 | PGS004013 (lassosum.CV.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.95504 β: 0.67041 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019283 | PGS004013 (lassosum.CV.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.88804 β: 0.63554 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019284 | PGS004013 (lassosum.CV.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.53614 β: 0.42927 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019285 | PGS004013 (lassosum.CV.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.72939 β: 0.54777 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019286 | PGS004013 (lassosum.CV.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.8643 β: 0.62289 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019287 | PGS003997 (lassosum.auto.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.35075 β: 0.30066 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019288 | PGS003997 (lassosum.auto.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.94603 β: 0.66579 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019289 | PGS003997 (lassosum.auto.GCST004131.IBD) |
PSS011244| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.83801 β: 0.60869 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019290 | PGS003997 (lassosum.auto.GCST004131.IBD) |
PSS011260| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.53922 β: 0.43128 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019291 | PGS003997 (lassosum.auto.GCST004131.IBD) |
PSS011288| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.73594 β: 0.55155 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019292 | PGS003997 (lassosum.auto.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.84612 β: 0.61309 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019293 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.51531 β: 0.41562 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019294 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.52599 β: 0.42265 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019295 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.29096 β: 0.25538 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019296 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.55991 β: 0.44463 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019297 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.41025 β: 0.34376 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019298 | PGS004039 (ldpred2.CV.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.6442 β: 0.49725 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019299 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.25413 β: 0.22644 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019300 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.2706 β: 0.23949 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019301 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.1856 β: 0.17025 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019302 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.30688 β: 0.26765 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019303 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.25033 β: 0.22341 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019304 | PGS004106 (pt_clump.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.32877 β: 0.28426 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019305 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.32208 β: 0.2792 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019306 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.34756 β: 0.29829 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019307 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.21072 β: 0.19122 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019308 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.36428 β: 0.31063 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019309 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.28905 β: 0.2539 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019310 | PGS004122 (pt_clump_nested.CV.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.41752 β: 0.34891 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019312 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.50796 β: 0.41076 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019313 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.26658 β: 0.23632 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019314 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.53274 β: 0.42705 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019315 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.40966 β: 0.34335 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019316 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.6067 β: 0.47419 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019317 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.48356 β: 0.39444 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019319 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.28557 β: 0.2512 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019320 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.54343 β: 0.43401 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019321 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.4041 β: 0.3394 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019322 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.60963 β: 0.476 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019323 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.53171 β: 0.42638 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019324 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.5534 β: 0.44045 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019325 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.29976 β: 0.26218 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019326 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.57552 β: 0.45459 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019327 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.44083 β: 0.36522 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019328 | PGS004152 (UKBB_EnsPGS.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.66922 β: 0.51236 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019329 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.48498 β: 0.3954 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019330 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.50219 β: 0.40693 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019331 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.2876 β: 0.25278 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019332 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.53513 β: 0.42861 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019333 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.39993 β: 0.33642 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019334 | PGS004024 (ldpred2.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.608 β: 0.47499 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019335 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.51227 β: 0.41361 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019337 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.2863 β: 0.25177 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019338 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.5456 β: 0.43541 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019339 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.4232 β: 0.35291 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019340 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.64766 β: 0.49936 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019341 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.51406 β: 0.41479 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019342 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.54026 β: 0.43195 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019343 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.28668 β: 0.25206 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019344 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.55065 β: 0.43868 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019345 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.42683 β: 0.35546 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019346 | PGS004068 (megaprs.CV.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.65089 β: 0.50131 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019347 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.49969 β: 0.40526 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019348 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.49743 β: 0.40375 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019349 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.26384 β: 0.23416 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019350 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.52107 β: 0.41942 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019351 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.37392 β: 0.31767 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019352 | PGS004082 (prscs.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.61184 β: 0.47737 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019353 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.42404 β: 0.3535 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019354 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.43926 β: 0.36413 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019355 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.2647 β: 0.23483 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019356 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.47667 β: 0.38979 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019357 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.36032 β: 0.30772 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019358 | PGS003998 (lassosum.auto.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.53698 β: 0.42982 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019359 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.48322 β: 0.39422 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019360 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.47356 β: 0.38768 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019361 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011249| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.25868 β: 0.23007 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019362 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011265| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.49153 β: 0.3998 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019364 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011278| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.57088 β: 0.45164 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019365 | PGS004040 (ldpred2.CV.GCST004988.Breast_cancer) |
PSS011215| European Ancestry| 130,758 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.66024 β: 0.50696 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019366 | PGS004040 (ldpred2.CV.GCST004988.Breast_cancer) |
PSS011227| European Ancestry| 217,530 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.77072 β: 0.57138 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019367 | PGS004040 (ldpred2.CV.GCST004988.Breast_cancer) |
PSS011238| South Asian Ancestry| 24,319 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.60503 β: 0.47314 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019368 | PGS004040 (ldpred2.CV.GCST004988.Breast_cancer) |
PSS011254| European Ancestry| 35,377 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.74575 β: 0.55719 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019369 | PGS004040 (ldpred2.CV.GCST004988.Breast_cancer) |
PSS011282| South Asian Ancestry| 4,350 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.46589 β: 0.38246 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019370 | PGS004040 (ldpred2.CV.GCST004988.Breast_cancer) |
PSS011268| European Ancestry| 48,968 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.80882 β: 0.59268 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019371 | PGS004107 (pt_clump.auto.GCST004988.Breast_cancer) |
PSS011215| European Ancestry| 130,758 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.50345 β: 0.40776 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019372 | PGS004107 (pt_clump.auto.GCST004988.Breast_cancer) |
PSS011227| European Ancestry| 217,530 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.5159 β: 0.41601 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019373 | PGS004107 (pt_clump.auto.GCST004988.Breast_cancer) |
PSS011238| South Asian Ancestry| 24,319 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.41368 β: 0.34619 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019374 | PGS004107 (pt_clump.auto.GCST004988.Breast_cancer) |
PSS011254| European Ancestry| 35,377 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.51726 β: 0.4169 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019375 | PGS004107 (pt_clump.auto.GCST004988.Breast_cancer) |
PSS011282| South Asian Ancestry| 4,350 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.36644 β: 0.31221 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019376 | PGS004107 (pt_clump.auto.GCST004988.Breast_cancer) |
PSS011268| European Ancestry| 48,968 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.52553 β: 0.42234 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019377 | PGS004123 (pt_clump_nested.CV.GCST004988.Breast_cancer) |
PSS011215| European Ancestry| 130,758 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.51371 β: 0.41457 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019378 | PGS004123 (pt_clump_nested.CV.GCST004988.Breast_cancer) |
PSS011227| European Ancestry| 217,530 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.57309 β: 0.45304 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019379 | PGS004123 (pt_clump_nested.CV.GCST004988.Breast_cancer) |
PSS011238| South Asian Ancestry| 24,319 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.48885 β: 0.39801 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019380 | PGS004123 (pt_clump_nested.CV.GCST004988.Breast_cancer) |
PSS011254| European Ancestry| 35,377 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.54351 β: 0.43406 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019381 | PGS004123 (pt_clump_nested.CV.GCST004988.Breast_cancer) |
PSS011282| South Asian Ancestry| 4,350 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.35605 β: 0.30458 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019382 | PGS004123 (pt_clump_nested.CV.GCST004988.Breast_cancer) |
PSS011268| European Ancestry| 48,968 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.58738 β: 0.46208 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019383 | PGS004153 (UKBB_EnsPGS.GCST004988.Breast_cancer) |
PSS011215| European Ancestry| 130,758 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.68728 β: 0.52312 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019384 | PGS004153 (UKBB_EnsPGS.GCST004988.Breast_cancer) |
PSS011227| European Ancestry| 217,530 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.79574 β: 0.58542 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019385 | PGS004153 (UKBB_EnsPGS.GCST004988.Breast_cancer) |
PSS011238| South Asian Ancestry| 24,319 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.65971 β: 0.50664 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019386 | PGS004153 (UKBB_EnsPGS.GCST004988.Breast_cancer) |
PSS011254| European Ancestry| 35,377 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.77954 β: 0.57636 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019387 | PGS004153 (UKBB_EnsPGS.GCST004988.Breast_cancer) |
PSS011282| South Asian Ancestry| 4,350 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.54652 β: 0.43601 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019388 | PGS004153 (UKBB_EnsPGS.GCST004988.Breast_cancer) |
PSS011268| European Ancestry| 48,968 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.82572 β: 0.60197 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019389 | PGS003983 (dbslmm.auto.GCST004988.Breast_cancer) |
PSS011215| European Ancestry| 130,758 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.60508 β: 0.47317 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019390 | PGS003983 (dbslmm.auto.GCST004988.Breast_cancer) |
PSS011227| European Ancestry| 217,530 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.71525 β: 0.53956 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019391 | PGS003983 (dbslmm.auto.GCST004988.Breast_cancer) |
PSS011238| South Asian Ancestry| 24,319 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.53934 β: 0.43136 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019392 | PGS003983 (dbslmm.auto.GCST004988.Breast_cancer) |
PSS011254| European Ancestry| 35,377 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.70143 β: 0.53147 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019394 | PGS003983 (dbslmm.auto.GCST004988.Breast_cancer) |
PSS011268| European Ancestry| 48,968 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.75801 β: 0.56418 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019395 | PGS004137 (sbayesr.auto.GCST004988.Breast_cancer) |
PSS011215| European Ancestry| 130,758 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.59437 β: 0.46648 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019396 | PGS004137 (sbayesr.auto.GCST004988.Breast_cancer) |
PSS011227| European Ancestry| 217,530 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.66993 β: 0.51278 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019397 | PGS004137 (sbayesr.auto.GCST004988.Breast_cancer) |
PSS011238| South Asian Ancestry| 24,319 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.51618 β: 0.41619 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019398 | PGS004137 (sbayesr.auto.GCST004988.Breast_cancer) |
PSS011254| European Ancestry| 35,377 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.73541 β: 0.55124 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019399 | PGS004137 (sbayesr.auto.GCST004988.Breast_cancer) |
PSS011282| South Asian Ancestry| 4,350 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.41849 β: 0.34959 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019400 | PGS004137 (sbayesr.auto.GCST004988.Breast_cancer) |
PSS011268| European Ancestry| 48,968 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.75895 β: 0.56472 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019401 | PGS004025 (ldpred2.auto.GCST004988.Breast_cancer) |
PSS011215| European Ancestry| 130,758 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.66191 β: 0.50797 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019402 | PGS004025 (ldpred2.auto.GCST004988.Breast_cancer) |
PSS011227| European Ancestry| 217,530 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.77035 β: 0.57118 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019403 | PGS004025 (ldpred2.auto.GCST004988.Breast_cancer) |
PSS011238| South Asian Ancestry| 24,319 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.61352 β: 0.47842 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019404 | PGS004025 (ldpred2.auto.GCST004988.Breast_cancer) |
PSS011254| European Ancestry| 35,377 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.74007 β: 0.55393 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019405 | PGS004025 (ldpred2.auto.GCST004988.Breast_cancer) |
PSS011282| South Asian Ancestry| 4,350 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.44836 β: 0.37043 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019406 | PGS004025 (ldpred2.auto.GCST004988.Breast_cancer) |
PSS011268| European Ancestry| 48,968 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.80647 β: 0.59138 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019407 | PGS004069 (megaprs.CV.GCST004988.Breast_cancer) |
PSS011215| European Ancestry| 130,758 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.64103 β: 0.49532 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019408 | PGS004069 (megaprs.CV.GCST004988.Breast_cancer) |
PSS011227| European Ancestry| 217,530 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.7432 β: 0.55573 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019409 | PGS004069 (megaprs.CV.GCST004988.Breast_cancer) |
PSS011238| South Asian Ancestry| 24,319 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.56536 β: 0.44811 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019410 | PGS004069 (megaprs.CV.GCST004988.Breast_cancer) |
PSS011254| European Ancestry| 35,377 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.72445 β: 0.54491 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019411 | PGS004069 (megaprs.CV.GCST004988.Breast_cancer) |
PSS011282| South Asian Ancestry| 4,350 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.51041 β: 0.41238 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019412 | PGS004069 (megaprs.CV.GCST004988.Breast_cancer) |
PSS011268| European Ancestry| 48,968 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.78417 β: 0.57895 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019413 | PGS004053 (megaprs.auto.GCST004988.Breast_cancer) |
PSS011215| European Ancestry| 130,758 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.61464 β: 0.47911 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019414 | PGS004053 (megaprs.auto.GCST004988.Breast_cancer) |
PSS011227| European Ancestry| 217,530 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.72899 β: 0.54754 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019415 | PGS004053 (megaprs.auto.GCST004988.Breast_cancer) |
PSS011238| South Asian Ancestry| 24,319 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.58283 β: 0.45922 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019416 | PGS004053 (megaprs.auto.GCST004988.Breast_cancer) |
PSS011254| European Ancestry| 35,377 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.7155 β: 0.5397 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019417 | PGS004053 (megaprs.auto.GCST004988.Breast_cancer) |
PSS011282| South Asian Ancestry| 4,350 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.42423 β: 0.35363 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019418 | PGS004053 (megaprs.auto.GCST004988.Breast_cancer) |
PSS011268| European Ancestry| 48,968 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.75979 β: 0.5652 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019419 | PGS004083 (prscs.auto.GCST004988.Breast_cancer) |
PSS011215| European Ancestry| 130,758 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.62802 β: 0.48736 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019420 | PGS004083 (prscs.auto.GCST004988.Breast_cancer) |
PSS011227| European Ancestry| 217,530 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.73797 β: 0.55272 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019421 | PGS004083 (prscs.auto.GCST004988.Breast_cancer) |
PSS011238| South Asian Ancestry| 24,319 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.57454 β: 0.45396 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019422 | PGS004083 (prscs.auto.GCST004988.Breast_cancer) |
PSS011254| European Ancestry| 35,377 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.72094 β: 0.54287 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019423 | PGS004083 (prscs.auto.GCST004988.Breast_cancer) |
PSS011282| South Asian Ancestry| 4,350 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.51133 β: 0.41299 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019424 | PGS004083 (prscs.auto.GCST004988.Breast_cancer) |
PSS011268| European Ancestry| 48,968 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.77492 β: 0.57375 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019427 | PGS003999 (lassosum.auto.GCST004988.Breast_cancer) |
PSS011238| South Asian Ancestry| 24,319 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.60371 β: 0.47232 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019428 | PGS003999 (lassosum.auto.GCST004988.Breast_cancer) |
PSS011254| European Ancestry| 35,377 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.71179 β: 0.53754 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019429 | PGS003999 (lassosum.auto.GCST004988.Breast_cancer) |
PSS011282| South Asian Ancestry| 4,350 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.48538 β: 0.39567 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019430 | PGS003999 (lassosum.auto.GCST004988.Breast_cancer) |
PSS011268| European Ancestry| 48,968 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.75341 β: 0.56157 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019431 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.11588 β: 0.10965 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019432 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16332 β: 0.15128 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019433 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1116 β: 0.1058 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019434 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13921 β: 0.13033 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019435 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21092 β: 0.19138 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019436 | PGS004041 (ldpred2.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20936 β: 0.19009 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019437 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08291 β: 0.07965 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019438 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06579 β: 0.06372 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019439 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 0.97393 β: -0.02642 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019440 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06709 β: 0.06493 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019441 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 0.99729 β: -0.00271 |
AUROC: 0.5 | — | 0 | beta = log(or)/sd_pgs |
| PPM019442 | PGS004108 (pt_clump.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08405 β: 0.0807 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019443 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.06894 β: 0.06667 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019444 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10078 β: 0.09602 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019445 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12773 β: 0.12021 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019446 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10772 β: 0.1023 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019447 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14403 β: 0.13455 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019448 | PGS004124 (pt_clump_nested.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13266 β: 0.12457 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019449 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12083 β: 0.11407 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019450 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15341 β: 0.14273 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019451 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09189 β: 0.08791 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019452 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12141 β: 0.11459 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019453 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18126 β: 0.16658 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019454 | PGS003984 (dbslmm.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20912 β: 0.1899 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019455 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08855 β: 0.08485 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019456 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14381 β: 0.13436 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019457 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09703 β: 0.09261 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019458 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09561 β: 0.09131 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019459 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15035 β: 0.14007 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019460 | PGS004138 (sbayesr.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20185 β: 0.18386 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019927 | PGS004146 (sbayesr.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.79245 β: 0.58358 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019462 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17327 β: 0.15979 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019463 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.08287 β: 0.07961 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019464 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14197 β: 0.13276 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019466 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23115 β: 0.20795 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019467 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10756 β: 0.10216 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019468 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16199 β: 0.15013 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019469 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.13492 β: 0.12656 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019470 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1247 β: 0.11752 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019471 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23606 β: 0.21193 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019472 | PGS004026 (ldpred2.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21946 β: 0.19841 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019473 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12005 β: 0.11337 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019474 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.16971 β: 0.15675 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019475 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09218 β: 0.08817 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019476 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1469 β: 0.13706 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019477 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23492 β: 0.211 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019478 | PGS004054 (megaprs.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.21483 β: 0.1946 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019479 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12262 β: 0.11566 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019480 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17236 β: 0.15902 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019481 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09524 β: 0.09097 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019482 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14508 β: 0.13548 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019483 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.24252 β: 0.21714 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019484 | PGS004070 (megaprs.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.22477 β: 0.20275 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019485 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10211 β: 0.09723 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019486 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15335 β: 0.14267 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019487 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14227 β: 0.13302 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019488 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.11617 β: 0.1099 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019489 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23173 β: 0.20842 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019490 | PGS004098 (prscs.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.19231 β: 0.17589 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019491 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10161 β: 0.09677 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019492 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.15354 β: 0.14283 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019493 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.1249 β: 0.1177 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019494 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10581 β: 0.10058 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019495 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.23758 β: 0.21316 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019496 | PGS004084 (prscs.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.20497 β: 0.18646 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019497 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.09992 β: 0.09524 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019499 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.03582 β: 0.0352 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019500 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12602 β: 0.11869 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019501 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.05895 β: 0.05728 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019502 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12993 β: 0.12215 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019503 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10789 β: 0.10246 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019504 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.14267 β: 0.13337 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019505 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011247| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.10577 β: 0.10054 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019506 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011263| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12027 β: 0.11357 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019507 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18187 β: 0.1671 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019508 | PGS004015 (lassosum.CV.GCST005838.Stroke) |
PSS011276| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.17792 β: 0.16375 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019509 | PGS004042 (ldpred2.CV.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.84253 β: 0.61114 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019510 | PGS004042 (ldpred2.CV.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.11238 β: 0.74782 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019511 | PGS004042 (ldpred2.CV.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.18207 β: 0.78027 |
AUROC: 0.72 | — | 0 | beta = log(or)/sd_pgs |
| PPM019512 | PGS004042 (ldpred2.CV.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.93239 β: 0.65876 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019513 | PGS004042 (ldpred2.CV.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.29829 β: 0.83216 |
AUROC: 0.73 | — | 0 | beta = log(or)/sd_pgs |
| PPM019514 | PGS004042 (ldpred2.CV.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.05028 β: 0.71798 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019515 | PGS004109 (pt_clump.auto.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.59583 β: 0.46739 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019516 | PGS004109 (pt_clump.auto.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.7257 β: 0.54563 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019517 | PGS004109 (pt_clump.auto.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.56915 β: 0.45054 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019518 | PGS004109 (pt_clump.auto.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.64521 β: 0.49787 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019519 | PGS004109 (pt_clump.auto.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.93373 β: 0.65945 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019520 | PGS004109 (pt_clump.auto.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.75123 β: 0.56032 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019521 | PGS004125 (pt_clump_nested.CV.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.65268 β: 0.5024 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019522 | PGS004125 (pt_clump_nested.CV.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.82864 β: 0.60357 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019523 | PGS004125 (pt_clump_nested.CV.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.6915 β: 0.52562 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019524 | PGS004125 (pt_clump_nested.CV.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.73299 β: 0.54985 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019928 | PGS004034 (ldpred2.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.45859 β: 0.37747 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019526 | PGS004125 (pt_clump_nested.CV.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.81235 β: 0.59462 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019527 | PGS003985 (dbslmm.auto.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.76053 β: 0.56562 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019528 | PGS003985 (dbslmm.auto.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.01802 β: 0.70212 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019529 | PGS003985 (dbslmm.auto.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.88516 β: 0.63401 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019530 | PGS003985 (dbslmm.auto.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.83859 β: 0.609 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019531 | PGS003985 (dbslmm.auto.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.1788 β: 0.77878 |
AUROC: 0.72 | — | 0 | beta = log(or)/sd_pgs |
| PPM019532 | PGS003985 (dbslmm.auto.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.93585 β: 0.66054 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019533 | PGS004155 (UKBB_EnsPGS.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.88737 β: 0.63519 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019534 | PGS004155 (UKBB_EnsPGS.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.16613 β: 0.77294 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019535 | PGS004155 (UKBB_EnsPGS.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.17738 β: 0.77812 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019536 | PGS004155 (UKBB_EnsPGS.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.96184 β: 0.67388 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019537 | PGS004155 (UKBB_EnsPGS.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.33409 β: 0.84762 |
AUROC: 0.73 | — | 0 | beta = log(or)/sd_pgs |
| PPM019539 | PGS004139 (sbayesr.auto.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.83755 β: 0.60843 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019540 | PGS004139 (sbayesr.auto.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.10912 β: 0.74627 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019541 | PGS004139 (sbayesr.auto.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.09532 β: 0.73971 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019542 | PGS004139 (sbayesr.auto.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.94637 β: 0.66597 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019543 | PGS004139 (sbayesr.auto.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.33868 β: 0.84959 |
AUROC: 0.73 | — | 0 | beta = log(or)/sd_pgs |
| PPM019544 | PGS004139 (sbayesr.auto.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.05644 β: 0.72098 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019545 | PGS004027 (ldpred2.auto.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.82561 β: 0.60191 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019546 | PGS004027 (ldpred2.auto.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.07696 β: 0.73091 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019547 | PGS004027 (ldpred2.auto.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.12005 β: 0.75144 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019548 | PGS004027 (ldpred2.auto.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.93632 β: 0.66079 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019549 | PGS004027 (ldpred2.auto.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.34953 β: 0.85421 |
AUROC: 0.72 | — | 0 | beta = log(or)/sd_pgs |
| PPM019550 | PGS004027 (ldpred2.auto.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.03998 β: 0.71294 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019551 | PGS004071 (megaprs.CV.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.85969 β: 0.62041 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019552 | PGS004071 (megaprs.CV.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.07288 β: 0.72894 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019553 | PGS004071 (megaprs.CV.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.03055 β: 0.70831 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019554 | PGS004071 (megaprs.CV.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.89962 β: 0.64165 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019555 | PGS004071 (megaprs.CV.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.24918 β: 0.81056 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019556 | PGS004071 (megaprs.CV.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.99361 β: 0.68995 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019557 | PGS004055 (megaprs.auto.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.85139 β: 0.61594 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019558 | PGS004055 (megaprs.auto.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.08323 β: 0.73392 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019559 | PGS004055 (megaprs.auto.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.14725 β: 0.76419 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019560 | PGS004055 (megaprs.auto.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.88479 β: 0.63382 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019561 | PGS004055 (megaprs.auto.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.22812 β: 0.80116 |
AUROC: 0.72 | — | 0 | beta = log(or)/sd_pgs |
| PPM019562 | PGS004055 (megaprs.auto.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.98362 β: 0.68492 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019563 | PGS004099 (prscs.CV.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.79229 β: 0.58349 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019564 | PGS004099 (prscs.CV.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.0553 β: 0.72042 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019566 | PGS004099 (prscs.CV.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.88631 β: 0.63462 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019567 | PGS004099 (prscs.CV.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.13119 β: 0.75668 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019568 | PGS004099 (prscs.CV.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.97586 β: 0.681 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019569 | PGS004085 (prscs.auto.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.80595 β: 0.59109 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019570 | PGS004085 (prscs.auto.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.05454 β: 0.72005 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019571 | PGS004085 (prscs.auto.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.12708 β: 0.75475 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019572 | PGS004085 (prscs.auto.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.87036 β: 0.62613 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019573 | PGS004085 (prscs.auto.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.10264 β: 0.74319 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019574 | PGS004085 (prscs.auto.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.9751 β: 0.68062 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019575 | PGS004001 (lassosum.auto.GCST006085.Prostate_cancer) |
PSS011221| European Ancestry| 68,516 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.81364 β: 0.59533 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019576 | PGS004001 (lassosum.auto.GCST006085.Prostate_cancer) |
PSS011232| European Ancestry| 171,474 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.03616 β: 0.71106 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019577 | PGS004001 (lassosum.auto.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.06139 β: 0.72338 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019578 | PGS004001 (lassosum.auto.GCST006085.Prostate_cancer) |
PSS011261| European Ancestry| 31,410 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.87698 β: 0.62967 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019579 | PGS004001 (lassosum.auto.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.36011 β: 0.85871 |
AUROC: 0.73 | — | 0 | beta = log(or)/sd_pgs |
| PPM019580 | PGS004001 (lassosum.auto.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 1.94974 β: 0.6677 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019581 | PGS004043 (ldpred2.CV.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.26872 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019583 | PGS004043 (ldpred2.CV.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.33678 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019584 | PGS004043 (ldpred2.CV.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.29518 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019585 | PGS004043 (ldpred2.CV.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.32507 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019586 | PGS004110 (pt_clump.auto.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.19456 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019587 | PGS004110 (pt_clump.auto.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.26354 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019588 | PGS004110 (pt_clump.auto.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.24443 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019589 | PGS004110 (pt_clump.auto.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.21783 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019590 | PGS004110 (pt_clump.auto.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.22784 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019591 | PGS004126 (pt_clump_nested.CV.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.20542 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019592 | PGS004126 (pt_clump_nested.CV.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.26646 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019593 | PGS004126 (pt_clump_nested.CV.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.25473 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019594 | PGS004126 (pt_clump_nested.CV.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.22475 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019596 | PGS003986 (dbslmm.auto.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.25416 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019597 | PGS003986 (dbslmm.auto.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.32356 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019598 | PGS003986 (dbslmm.auto.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.33276 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019599 | PGS003986 (dbslmm.auto.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.28776 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019600 | PGS003986 (dbslmm.auto.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.3104 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019601 | PGS004156 (UKBB_EnsPGS.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.28413 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019602 | PGS004156 (UKBB_EnsPGS.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.34723 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019603 | PGS004156 (UKBB_EnsPGS.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.35432 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019604 | PGS004156 (UKBB_EnsPGS.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.30961 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019605 | PGS004156 (UKBB_EnsPGS.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.34098 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019607 | PGS004140 (sbayesr.auto.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.30851 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019608 | PGS004140 (sbayesr.auto.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.33111 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019609 | PGS004140 (sbayesr.auto.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.27622 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019610 | PGS004140 (sbayesr.auto.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.31881 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019611 | PGS004028 (ldpred2.auto.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.22842 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019612 | PGS004028 (ldpred2.auto.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.2698 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019613 | PGS004028 (ldpred2.auto.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.30321 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019614 | PGS004028 (ldpred2.auto.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.24804 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019615 | PGS004028 (ldpred2.auto.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.29375 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019616 | PGS004056 (megaprs.auto.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.25856 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019617 | PGS004056 (megaprs.auto.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.29794 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019618 | PGS004056 (megaprs.auto.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.30975 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019619 | PGS004056 (megaprs.auto.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.27027 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019620 | PGS004056 (megaprs.auto.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.30312 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019621 | PGS004072 (megaprs.CV.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.26826 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019622 | PGS004072 (megaprs.CV.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.31437 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019623 | PGS004072 (megaprs.CV.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.32671 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019624 | PGS004072 (megaprs.CV.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.28601 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019625 | PGS004072 (megaprs.CV.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.31308 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019626 | PGS004100 (prscs.CV.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.2649 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019627 | PGS004100 (prscs.CV.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.32581 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019628 | PGS004100 (prscs.CV.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.33324 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019629 | PGS004100 (prscs.CV.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.28641 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019630 | PGS004100 (prscs.CV.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.31709 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019631 | PGS004086 (prscs.auto.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.26523 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019632 | PGS004086 (prscs.auto.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.32349 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019633 | PGS004086 (prscs.auto.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.33006 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019634 | PGS004086 (prscs.auto.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.28497 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019635 | PGS004086 (prscs.auto.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.3146 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019636 | PGS004002 (lassosum.auto.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.2609 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019637 | PGS004002 (lassosum.auto.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.31942 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019638 | PGS004002 (lassosum.auto.GCST007140.HDL) |
PSS011257| European Ancestry| 49,824 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.32133 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019639 | PGS004002 (lassosum.auto.GCST007140.HDL) |
PSS011285| South Asian Ancestry| 8,065 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.28641 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019640 | PGS004002 (lassosum.auto.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.30952 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019641 | PGS004044 (ldpred2.CV.GCST007954.HbA1c) |
PSS011242| South Asian Ancestry| 12,948 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.02666 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019642 | PGS004044 (ldpred2.CV.GCST007954.HbA1c) |
PSS011258| European Ancestry| 34,192 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.16248 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019643 | PGS004044 (ldpred2.CV.GCST007954.HbA1c) |
PSS011286| South Asian Ancestry| 8,748 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.15314 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019644 | PGS004044 (ldpred2.CV.GCST007954.HbA1c) |
PSS011272| European Ancestry| 86,050 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.19178 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019645 | PGS004111 (pt_clump.auto.GCST007954.HbA1c) |
PSS011242| South Asian Ancestry| 12,948 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.00455 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019646 | PGS004111 (pt_clump.auto.GCST007954.HbA1c) |
PSS011258| European Ancestry| 34,192 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.1122 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019647 | PGS004111 (pt_clump.auto.GCST007954.HbA1c) |
PSS011286| South Asian Ancestry| 8,748 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.07796 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019648 | PGS004111 (pt_clump.auto.GCST007954.HbA1c) |
PSS011272| European Ancestry| 86,050 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.13494 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019649 | PGS004127 (pt_clump_nested.CV.GCST007954.HbA1c) |
PSS011242| South Asian Ancestry| 12,948 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.02027 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019650 | PGS004127 (pt_clump_nested.CV.GCST007954.HbA1c) |
PSS011258| European Ancestry| 34,192 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.13414 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019652 | PGS004127 (pt_clump_nested.CV.GCST007954.HbA1c) |
PSS011272| European Ancestry| 86,050 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.14619 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019653 | PGS003987 (dbslmm.auto.GCST007954.HbA1c) |
PSS011242| South Asian Ancestry| 12,948 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.0202 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019654 | PGS003987 (dbslmm.auto.GCST007954.HbA1c) |
PSS011258| European Ancestry| 34,192 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.1522 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019655 | PGS003987 (dbslmm.auto.GCST007954.HbA1c) |
PSS011286| South Asian Ancestry| 8,748 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.14804 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019656 | PGS003987 (dbslmm.auto.GCST007954.HbA1c) |
PSS011272| European Ancestry| 86,050 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.18031 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019657 | PGS004157 (UKBB_EnsPGS.GCST007954.HbA1c) |
PSS011242| South Asian Ancestry| 12,948 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.035 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019658 | PGS004157 (UKBB_EnsPGS.GCST007954.HbA1c) |
PSS011258| European Ancestry| 34,192 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.17514 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019659 | PGS004157 (UKBB_EnsPGS.GCST007954.HbA1c) |
PSS011286| South Asian Ancestry| 8,748 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.16507 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019660 | PGS004157 (UKBB_EnsPGS.GCST007954.HbA1c) |
PSS011272| European Ancestry| 86,050 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.20758 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019661 | PGS004141 (sbayesr.auto.GCST007954.HbA1c) |
PSS011242| South Asian Ancestry| 12,948 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.02812 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019662 | PGS004141 (sbayesr.auto.GCST007954.HbA1c) |
PSS011258| European Ancestry| 34,192 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.15673 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019663 | PGS004141 (sbayesr.auto.GCST007954.HbA1c) |
PSS011286| South Asian Ancestry| 8,748 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.14236 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019664 | PGS004141 (sbayesr.auto.GCST007954.HbA1c) |
PSS011272| European Ancestry| 86,050 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.18408 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019665 | PGS004029 (ldpred2.auto.GCST007954.HbA1c) |
PSS011242| South Asian Ancestry| 12,948 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.03102 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019666 | PGS004029 (ldpred2.auto.GCST007954.HbA1c) |
PSS011258| European Ancestry| 34,192 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.11223 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019667 | PGS004029 (ldpred2.auto.GCST007954.HbA1c) |
PSS011286| South Asian Ancestry| 8,748 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.10588 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019668 | PGS004029 (ldpred2.auto.GCST007954.HbA1c) |
PSS011272| European Ancestry| 86,050 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.13529 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019669 | PGS004073 (megaprs.CV.GCST007954.HbA1c) |
PSS011242| South Asian Ancestry| 12,948 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.02487 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019670 | PGS004073 (megaprs.CV.GCST007954.HbA1c) |
PSS011258| European Ancestry| 34,192 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.16593 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019671 | PGS004073 (megaprs.CV.GCST007954.HbA1c) |
PSS011286| South Asian Ancestry| 8,748 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.16274 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019672 | PGS004073 (megaprs.CV.GCST007954.HbA1c) |
PSS011272| European Ancestry| 86,050 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.19138 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019673 | PGS004057 (megaprs.auto.GCST007954.HbA1c) |
PSS011242| South Asian Ancestry| 12,948 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.02167 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019674 | PGS004057 (megaprs.auto.GCST007954.HbA1c) |
PSS011258| European Ancestry| 34,192 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.16342 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019675 | PGS004057 (megaprs.auto.GCST007954.HbA1c) |
PSS011286| South Asian Ancestry| 8,748 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.16331 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019676 | PGS004057 (megaprs.auto.GCST007954.HbA1c) |
PSS011272| European Ancestry| 86,050 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.18961 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019677 | PGS004087 (prscs.auto.GCST007954.HbA1c) |
PSS011242| South Asian Ancestry| 12,948 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.02279 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019678 | PGS004087 (prscs.auto.GCST007954.HbA1c) |
PSS011258| European Ancestry| 34,192 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.1563 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019679 | PGS004087 (prscs.auto.GCST007954.HbA1c) |
PSS011286| South Asian Ancestry| 8,748 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.15808 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019680 | PGS004087 (prscs.auto.GCST007954.HbA1c) |
PSS011272| European Ancestry| 86,050 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.17698 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019681 | PGS004003 (lassosum.auto.GCST007954.HbA1c) |
PSS011242| South Asian Ancestry| 12,948 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.01939 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019682 | PGS004003 (lassosum.auto.GCST007954.HbA1c) |
PSS011258| European Ancestry| 34,192 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.15659 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019683 | PGS004003 (lassosum.auto.GCST007954.HbA1c) |
PSS011286| South Asian Ancestry| 8,748 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.1469 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019684 | PGS004003 (lassosum.auto.GCST007954.HbA1c) |
PSS011272| European Ancestry| 86,050 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.18516 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019685 | PGS004045 (ldpred2.CV.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.242 β: 0.21672 |
AUROC: 0.56 | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019686 | PGS004045 (ldpred2.CV.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.19906 β: 0.18153 |
AUROC: 0.55 | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019687 | PGS004046 (ldpred2.CV.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.22224 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019688 | PGS004045 (ldpred2.CV.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.1551 β: 0.14419 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019689 | PGS004046 (ldpred2.CV.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.22732 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019690 | PGS004045 (ldpred2.CV.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.18451 β: 0.16933 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019691 | PGS004046 (ldpred2.CV.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.28008 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019692 | PGS004045 (ldpred2.CV.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.27638 β: 0.24403 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019693 | PGS004046 (ldpred2.CV.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.32473 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019694 | PGS004045 (ldpred2.CV.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.37553 β: 0.31884 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019695 | PGS004112 (pt_clump.auto.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.11711 β: 0.11075 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019696 | PGS004112 (pt_clump.auto.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.08316 β: 0.07988 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019697 | PGS004113 (pt_clump.auto.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.13077 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019698 | PGS004112 (pt_clump.auto.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.09504 β: 0.09079 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019699 | PGS004113 (pt_clump.auto.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.14395 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019700 | PGS004112 (pt_clump.auto.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.10467 β: 0.09955 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019701 | PGS004113 (pt_clump.auto.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.19146 | — | — | 0 | — |
| PPM019702 | PGS004112 (pt_clump.auto.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.07811 β: 0.07521 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019703 | PGS004113 (pt_clump.auto.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.20975 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019704 | PGS004112 (pt_clump.auto.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.18494 β: 0.16969 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019705 | PGS004128 (pt_clump_nested.CV.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.2025 β: 0.1844 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019706 | PGS004128 (pt_clump_nested.CV.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.17535 β: 0.16157 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019707 | PGS004129 (pt_clump_nested.CV.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.15438 | — | — | 0 | — |
| PPM019708 | PGS004128 (pt_clump_nested.CV.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.12482 β: 0.11762 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019709 | PGS004129 (pt_clump_nested.CV.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.18248 | — | — | 0 | — |
| PPM019710 | PGS004128 (pt_clump_nested.CV.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.14728 β: 0.1374 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019711 | PGS004129 (pt_clump_nested.CV.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.20014 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019712 | PGS004128 (pt_clump_nested.CV.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.1553 β: 0.14436 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019714 | PGS004128 (pt_clump_nested.CV.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.28244 β: 0.24876 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019715 | PGS004158 (UKBB_EnsPGS.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.24774 β: 0.22134 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019716 | PGS004158 (UKBB_EnsPGS.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.20836 β: 0.18926 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019717 | PGS004158 (UKBB_EnsPGS.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.15782 β: 0.14654 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019718 | PGS004158 (UKBB_EnsPGS.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.19045 β: 0.17433 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019719 | PGS004158 (UKBB_EnsPGS.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.28519 β: 0.25091 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019720 | PGS004158 (UKBB_EnsPGS.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.38925 β: 0.32876 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019722 | PGS004159 (UKBB_EnsPGS.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.23365 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019723 | PGS004159 (UKBB_EnsPGS.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.28908 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019724 | PGS004159 (UKBB_EnsPGS.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.3364 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019725 | PGS003988 (dbslmm.auto.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.23024 β: 0.20721 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019726 | PGS003988 (dbslmm.auto.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.19381 β: 0.17715 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019727 | PGS003989 (dbslmm.auto.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.20785 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019728 | PGS003988 (dbslmm.auto.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.13529 β: 0.12688 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019729 | PGS003989 (dbslmm.auto.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.21486 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019730 | PGS003988 (dbslmm.auto.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.17463 β: 0.16095 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019731 | PGS003989 (dbslmm.auto.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.26244 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019732 | PGS003988 (dbslmm.auto.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.21118 β: 0.19159 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019733 | PGS003989 (dbslmm.auto.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.2994 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019734 | PGS003988 (dbslmm.auto.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.32812 β: 0.28376 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019735 | PGS004142 (sbayesr.auto.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.23421 β: 0.21043 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019736 | PGS004142 (sbayesr.auto.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.18832 β: 0.17254 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019737 | PGS004143 (sbayesr.auto.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.2195 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019738 | PGS004142 (sbayesr.auto.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.14325 β: 0.13388 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019739 | PGS004143 (sbayesr.auto.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.22058 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019740 | PGS004142 (sbayesr.auto.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.17317 β: 0.15971 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019741 | PGS004143 (sbayesr.auto.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.27556 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019742 | PGS004142 (sbayesr.auto.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.23784 β: 0.21337 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019743 | PGS004143 (sbayesr.auto.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.31768 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019744 | PGS004142 (sbayesr.auto.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.36398 β: 0.3104 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019745 | PGS004030 (ldpred2.auto.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.23112 β: 0.20793 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019746 | PGS004030 (ldpred2.auto.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.19337 β: 0.17678 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019747 | PGS004031 (ldpred2.auto.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.21464 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019748 | PGS004030 (ldpred2.auto.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.1534 β: 0.14271 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019749 | PGS004031 (ldpred2.auto.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.22342 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019750 | PGS004030 (ldpred2.auto.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.17966 β: 0.16522 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019751 | PGS004031 (ldpred2.auto.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.27229 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019752 | PGS004030 (ldpred2.auto.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.26323 β: 0.23368 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019754 | PGS004030 (ldpred2.auto.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.37576 β: 0.31901 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019755 | PGS004058 (megaprs.auto.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.23792 β: 0.21343 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019756 | PGS004058 (megaprs.auto.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.20337 β: 0.18513 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019757 | PGS004059 (megaprs.auto.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.22316 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019758 | PGS004058 (megaprs.auto.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.15047 β: 0.14017 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019759 | PGS004059 (megaprs.auto.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.22692 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019760 | PGS004058 (megaprs.auto.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.18412 β: 0.169 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019761 | PGS004059 (megaprs.auto.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.28361 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019762 | PGS004058 (megaprs.auto.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.28993 β: 0.25459 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019763 | PGS004059 (megaprs.auto.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.32293 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019764 | PGS004058 (megaprs.auto.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.36871 β: 0.31387 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019765 | PGS004074 (megaprs.CV.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.23578 β: 0.2117 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019766 | PGS004074 (megaprs.CV.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.20198 β: 0.18397 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019767 | PGS004075 (megaprs.CV.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.22663 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019768 | PGS004074 (megaprs.CV.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.14888 β: 0.13879 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019769 | PGS004075 (megaprs.CV.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.22823 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019770 | PGS004074 (megaprs.CV.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.18135 β: 0.16666 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019771 | PGS004075 (megaprs.CV.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.28276 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019772 | PGS004074 (megaprs.CV.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.27181 β: 0.24044 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019773 | PGS004075 (megaprs.CV.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.32666 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019775 | PGS004101 (prscs.CV.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.22532 β: 0.2032 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019776 | PGS004101 (prscs.CV.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.18489 β: 0.16965 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019777 | PGS004101 (prscs.CV.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.14104 β: 0.13194 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019778 | PGS004101 (prscs.CV.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.17256 β: 0.15919 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019780 | PGS004101 (prscs.CV.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.33357 β: 0.28786 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019781 | PGS004088 (prscs.auto.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.22843 β: 0.20574 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019782 | PGS004088 (prscs.auto.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.1913 β: 0.17504 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019783 | PGS004089 (prscs.auto.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.21078 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019784 | PGS004088 (prscs.auto.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.13127 β: 0.12334 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019785 | PGS004089 (prscs.auto.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.21808 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019786 | PGS004088 (prscs.auto.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.18048 β: 0.16592 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019787 | PGS004089 (prscs.auto.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.27584 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019788 | PGS004088 (prscs.auto.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.24645 β: 0.2203 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019789 | PGS004089 (prscs.auto.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.30818 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019790 | PGS004088 (prscs.auto.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.34394 β: 0.2956 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019791 | PGS004004 (lassosum.auto.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.21322 β: 0.19327 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019792 | PGS004004 (lassosum.auto.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.1667 β: 0.15418 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019793 | PGS004005 (lassosum.auto.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.1977 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019794 | PGS004004 (lassosum.auto.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.14563 β: 0.13596 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019795 | PGS004005 (lassosum.auto.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.20614 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019796 | PGS004004 (lassosum.auto.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.17435 β: 0.16072 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019797 | PGS004005 (lassosum.auto.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.25654 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019798 | PGS004004 (lassosum.auto.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.17987 β: 0.1654 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019799 | PGS004005 (lassosum.auto.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.29184 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019800 | PGS004004 (lassosum.auto.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.32743 β: 0.28325 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019801 | PGS004016 (lassosum.CV.GCST008059.CKD) |
PSS011216| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.23332 β: 0.20971 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019802 | PGS004016 (lassosum.CV.GCST008059.CKD) |
PSS011228| European Ancestry| 383,843 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.19566 β: 0.1787 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019803 | PGS004017 (lassosum.CV.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.20463 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019804 | PGS004016 (lassosum.CV.GCST008059.CKD) |
PSS011239| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.14431 β: 0.1348 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019806 | PGS004016 (lassosum.CV.GCST008059.CKD) |
PSS011255| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.18937 β: 0.17342 |
AUROC: 0.55 | — | 0 | beta = log(or)/sd_pgs |
| PPM019807 | PGS004017 (lassosum.CV.GCST008059.eGFR) |
PSS011293| South Asian Ancestry| 8,855 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.26617 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019808 | PGS004016 (lassosum.CV.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.23734 β: 0.21296 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019809 | PGS004017 (lassosum.CV.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.30382 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019810 | PGS004016 (lassosum.CV.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.3499 β: 0.30003 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019811 | PGS004047 (ldpred2.CV.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.57029 β: 0.45126 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019812 | PGS004047 (ldpred2.CV.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.65592 β: 0.50435 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019813 | PGS004048 (ldpred2.CV.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.25902 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019814 | PGS004047 (ldpred2.CV.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.81978 β: 0.59872 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019815 | PGS004047 (ldpred2.CV.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.73092 β: 0.54865 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019816 | PGS004048 (ldpred2.CV.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.25163 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019817 | PGS004047 (ldpred2.CV.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.57863 β: 0.45655 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019818 | PGS004048 (ldpred2.CV.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.28769 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019819 | PGS004047 (ldpred2.CV.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.99932 β: 0.69281 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019820 | PGS004114 (pt_clump.auto.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.35293 β: 0.30227 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019821 | PGS004114 (pt_clump.auto.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.4164 β: 0.34812 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019822 | PGS004115 (pt_clump.auto.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.20755 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019823 | PGS004114 (pt_clump.auto.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.6966 β: 0.52862 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019824 | PGS004114 (pt_clump.auto.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.52441 β: 0.42161 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019825 | PGS004115 (pt_clump.auto.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.19593 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019826 | PGS004114 (pt_clump.auto.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.39654 β: 0.334 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019827 | PGS004115 (pt_clump.auto.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.19725 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019828 | PGS004114 (pt_clump.auto.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.60047 β: 0.4703 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019829 | PGS004130 (pt_clump_nested.CV.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.41975 β: 0.35048 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019830 | PGS004130 (pt_clump_nested.CV.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.49959 β: 0.40519 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019831 | PGS004131 (pt_clump_nested.CV.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.21235 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019832 | PGS004130 (pt_clump_nested.CV.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.59226 β: 0.46516 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019833 | PGS004130 (pt_clump_nested.CV.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.54512 β: 0.4351 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019834 | PGS004131 (pt_clump_nested.CV.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.20496 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019835 | PGS004130 (pt_clump_nested.CV.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.47895 β: 0.39133 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019836 | PGS004131 (pt_clump_nested.CV.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.22201 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019837 | PGS004130 (pt_clump_nested.CV.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.69355 β: 0.52682 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019838 | PGS003990 (dbslmm.auto.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.50745 β: 0.41042 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019839 | PGS003990 (dbslmm.auto.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.59028 β: 0.46391 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019840 | PGS003991 (dbslmm.auto.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.20962 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019841 | PGS003990 (dbslmm.auto.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.63718 β: 0.49298 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019842 | PGS003990 (dbslmm.auto.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.67929 β: 0.51837 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019929 | PGS004034 (ldpred2.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.5321 β: 0.42664 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019844 | PGS003990 (dbslmm.auto.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.46542 β: 0.38214 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019846 | PGS003990 (dbslmm.auto.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.88159 β: 0.63211 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019847 | PGS004144 (sbayesr.auto.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.37049 β: 0.31517 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019848 | PGS004144 (sbayesr.auto.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.39569 β: 0.33339 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019849 | PGS004145 (sbayesr.auto.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.12294 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019850 | PGS004144 (sbayesr.auto.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.35132 β: 0.30108 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019851 | PGS004144 (sbayesr.auto.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.4915 β: 0.39978 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019852 | PGS004145 (sbayesr.auto.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.13599 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019853 | PGS004144 (sbayesr.auto.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.23735 β: 0.21298 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019854 | PGS004145 (sbayesr.auto.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.2343 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019855 | PGS004144 (sbayesr.auto.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.71118 β: 0.53718 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019856 | PGS004161 (UKBB_EnsPGS.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.2779 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019857 | PGS004161 (UKBB_EnsPGS.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.26797 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019858 | PGS004161 (UKBB_EnsPGS.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.30227 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019859 | PGS004160 (UKBB_EnsPGS.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.58633 β: 0.46142 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019860 | PGS004160 (UKBB_EnsPGS.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.67706 β: 0.51704 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019861 | PGS004160 (UKBB_EnsPGS.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.88658 β: 0.63476 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019862 | PGS004160 (UKBB_EnsPGS.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.73594 β: 0.55155 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019863 | PGS004160 (UKBB_EnsPGS.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.63885 β: 0.49399 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019864 | PGS004160 (UKBB_EnsPGS.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 2.04859 β: 0.71715 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019865 | PGS004032 (ldpred2.auto.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.47805 β: 0.39072 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019866 | PGS004032 (ldpred2.auto.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.53483 β: 0.42842 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019867 | PGS004033 (ldpred2.auto.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.18346 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019868 | PGS004032 (ldpred2.auto.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.58389 β: 0.45989 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019869 | PGS004032 (ldpred2.auto.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.63475 β: 0.49149 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019870 | PGS004033 (ldpred2.auto.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.19643 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019871 | PGS004032 (ldpred2.auto.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.38725 β: 0.32733 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019872 | PGS004033 (ldpred2.auto.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.27115 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019873 | PGS004032 (ldpred2.auto.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.91462 β: 0.64952 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019874 | PGS004076 (megaprs.CV.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.55746 β: 0.44305 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019875 | PGS004076 (megaprs.CV.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.63709 β: 0.49292 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019876 | PGS004076 (megaprs.CV.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.76885 β: 0.57033 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019877 | PGS004076 (megaprs.CV.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.67754 β: 0.51733 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019878 | PGS004076 (megaprs.CV.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.63078 β: 0.48906 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019880 | PGS004060 (megaprs.auto.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.53017 β: 0.42538 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019881 | PGS004060 (megaprs.auto.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.6092 β: 0.47574 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019882 | PGS004061 (megaprs.auto.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.24798 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019883 | PGS004060 (megaprs.auto.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.8073 β: 0.59183 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019884 | PGS004060 (megaprs.auto.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.64854 β: 0.49989 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019885 | PGS004061 (megaprs.auto.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.24495 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019886 | PGS004060 (megaprs.auto.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.59359 β: 0.46599 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019887 | PGS004061 (megaprs.auto.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.26687 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019888 | PGS004060 (megaprs.auto.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.94028 β: 0.66283 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019889 | PGS004077 (megaprs.CV.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.24953 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019890 | PGS004077 (megaprs.CV.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.25448 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019891 | PGS004077 (megaprs.CV.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.27905 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019892 | PGS004090 (prscs.auto.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.50656 β: 0.40983 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019893 | PGS004090 (prscs.auto.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.57446 β: 0.45391 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019894 | PGS004091 (prscs.auto.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.21095 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019895 | PGS004090 (prscs.auto.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.6051 β: 0.47319 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM019896 | PGS004090 (prscs.auto.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.68882 β: 0.52403 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019898 | PGS004090 (prscs.auto.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.42666 β: 0.35534 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019899 | PGS004091 (prscs.auto.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.27156 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019900 | PGS004090 (prscs.auto.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.93464 β: 0.65992 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019901 | PGS004006 (lassosum.auto.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.49846 β: 0.40444 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019902 | PGS004006 (lassosum.auto.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.5767 β: 0.45534 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019903 | PGS004007 (lassosum.auto.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.23632 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019904 | PGS004006 (lassosum.auto.GCST008972.Gout) |
PSS011240| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.75393 β: 0.56186 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019905 | PGS004006 (lassosum.auto.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.67964 β: 0.51858 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019906 | PGS004007 (lassosum.auto.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.22465 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019907 | PGS004006 (lassosum.auto.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.48465 β: 0.39518 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019908 | PGS004007 (lassosum.auto.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.26029 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019909 | PGS004006 (lassosum.auto.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.89517 β: 0.63931 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019910 | PGS004018 (lassosum.CV.GCST008972.Gout) |
PSS011217| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.53836 β: 0.43072 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019911 | PGS004018 (lassosum.CV.GCST008972.Gout) |
PSS011229| European Ancestry| 257,781 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.63119 β: 0.48931 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019913 | PGS004018 (lassosum.CV.GCST008972.Gout) |
PSS011256| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.68276 β: 0.52044 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM019914 | PGS004018 (lassosum.CV.GCST008972.Gout) |
PSS011284| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.54257 β: 0.43345 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019915 | PGS004018 (lassosum.CV.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.92725 β: 0.6561 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019916 | PGS004019 (lassosum.CV.GCST008972.Urate) |
PSS011250| European Ancestry| 4,730 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.26269 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019917 | PGS004019 (lassosum.CV.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.24751 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019918 | PGS004019 (lassosum.CV.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.27253 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019919 | PGS004116 (pt_clump.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.27295 β: 0.24134 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM019920 | PGS004116 (pt_clump.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.2393 β: 0.21454 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019921 | PGS004116 (pt_clump.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.44592 β: 0.36875 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019922 | PGS003992 (dbslmm.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.36764 β: 0.31309 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019923 | PGS003992 (dbslmm.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.33446 β: 0.28853 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019924 | PGS003992 (dbslmm.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.59974 β: 0.46984 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019931 | PGS004062 (megaprs.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.46172 β: 0.37961 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019933 | PGS004062 (megaprs.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.73895 β: 0.55328 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019934 | PGS004092 (prscs.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.50751 β: 0.41046 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019935 | PGS004092 (prscs.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.48977 β: 0.39862 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019936 | PGS004092 (prscs.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.77852 β: 0.57578 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019937 | PGS004008 (lassosum.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.42671 β: 0.35537 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019938 | PGS004008 (lassosum.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.48397 β: 0.39472 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019939 | PGS004008 (lassosum.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.73288 β: 0.54979 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019940 | PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.50723 β: 0.41027 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019941 | PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.76472 β: 0.56799 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019942 | PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.06976 β: 0.06744 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019943 | PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.21972 β: 0.19862 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019944 | PGS004117 (pt_clump.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.8907 β: 0.63695 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019945 | PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.53997 β: 0.43176 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019946 | PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.83108 β: 0.6049 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019947 | PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.10378 β: 0.09874 |
AUROC: 0.52 | — | 0 | beta = log(or)/sd_pgs |
| PPM019948 | PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.23285 β: 0.20933 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019949 | PGS004132 (pt_clump_nested.CV.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.87052 β: 0.62622 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019950 | PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.95715 β: 0.67149 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019951 | PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.37817 β: 0.86633 |
AUROC: 0.73 | — | 0 | beta = log(or)/sd_pgs |
| PPM019952 | PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.02806 β: 0.02768 |
AUROC: 0.49 | — | 0 | beta = log(or)/sd_pgs |
| PPM019953 | PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.35954 β: 0.30715 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019954 | PGS003993 (dbslmm.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.40714 β: 0.87844 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019956 | PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.08691 β: 0.73568 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019957 | PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 0.97765 β: -0.0226 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019958 | PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.32037 β: 0.27791 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019959 | PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.73561 β: 0.55136 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM019960 | PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.35332 β: 0.85583 |
AUROC: 0.72 | — | 0 | beta = log(or)/sd_pgs |
| PPM019961 | PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.27887 β: 0.82368 |
AUROC: 0.72 | — | 0 | beta = log(or)/sd_pgs |
| PPM019962 | PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.0051 β: 0.00509 |
AUROC: 0.5 | — | 0 | beta = log(or)/sd_pgs |
| PPM019963 | PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.43168 β: 0.35885 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019964 | PGS004162 (UKBB_EnsPGS.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.88687 β: 1.06017 |
AUROC: 0.77 | — | 0 | beta = log(or)/sd_pgs |
| PPM019965 | PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.32281 β: 0.84278 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019966 | PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.04799 β: 0.71686 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019967 | PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.00124 β: 0.00124 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019968 | PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.41811 β: 0.34932 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019969 | PGS004035 (ldpred2.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.67223 β: 0.98291 |
AUROC: 0.75 | — | 0 | beta = log(or)/sd_pgs |
| PPM019970 | PGS004063 (megaprs.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.96796 β: 0.677 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019971 | PGS004063 (megaprs.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.98877 β: 0.68752 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019972 | PGS004063 (megaprs.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 0.99583 β: -0.00418 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019973 | PGS004063 (megaprs.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.34209 β: 0.29422 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019974 | PGS004063 (megaprs.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.32027 β: 0.84168 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019975 | PGS004078 (megaprs.CV.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.10311 β: 0.74342 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019976 | PGS004078 (megaprs.CV.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.14067 β: 0.76112 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM019977 | PGS004078 (megaprs.CV.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.00042 β: 0.00042 |
AUROC: 0.5 | — | 0 | beta = log(or)/sd_pgs |
| PPM019979 | PGS004078 (megaprs.CV.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.67623 β: 0.98441 |
AUROC: 0.76 | — | 0 | beta = log(or)/sd_pgs |
| PPM019980 | PGS004102 (prscs.CV.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.98839 β: 0.68733 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019981 | PGS004102 (prscs.CV.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.45742 β: 0.89911 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019982 | PGS004102 (prscs.CV.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 0.99231 β: -0.00772 |
AUROC: 0.5 | — | 0 | beta = log(or)/sd_pgs |
| PPM019983 | PGS004102 (prscs.CV.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.42533 β: 0.3544 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019984 | PGS004102 (prscs.CV.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.43145 β: 0.88849 |
AUROC: 0.75 | — | 0 | beta = log(or)/sd_pgs |
| PPM019985 | PGS004093 (prscs.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.96153 β: 0.67372 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019986 | PGS004093 (prscs.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.44508 β: 0.89408 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019987 | PGS004093 (prscs.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.0158 β: 0.01568 |
AUROC: 0.5 | — | 0 | beta = log(or)/sd_pgs |
| PPM019988 | PGS004093 (prscs.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.42395 β: 0.35343 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019989 | PGS004093 (prscs.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.39116 β: 0.87178 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019990 | PGS004020 (lassosum.CV.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.96291 β: 0.67443 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019991 | PGS004020 (lassosum.CV.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.44728 β: 0.89498 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019992 | PGS004020 (lassosum.CV.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.02458 β: 0.02428 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019993 | PGS004020 (lassosum.CV.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.42499 β: 0.35417 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019994 | PGS004020 (lassosum.CV.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.34601 β: 0.85271 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM019995 | PGS004009 (lassosum.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.95016 β: 0.66791 |
AUROC: 0.7 | — | 0 | beta = log(or)/sd_pgs |
| PPM019996 | PGS004009 (lassosum.auto.GCST90013445.T1D) |
PSS011235| European Ancestry| 322,349 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.41964 β: 0.88362 |
AUROC: 0.73 | — | 0 | beta = log(or)/sd_pgs |
| PPM019997 | PGS004009 (lassosum.auto.GCST90013445.T1D) |
PSS011248| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.02716 β: 0.0268 |
AUROC: 0.51 | — | 0 | beta = log(or)/sd_pgs |
| PPM019998 | PGS004009 (lassosum.auto.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.41112 β: 0.34438 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019999 | PGS004009 (lassosum.auto.GCST90013445.T1D) |
PSS011277| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 2.32891 β: 0.8454 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM020001 | PGS004049 (ldpred2.CV.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.63972 β: 0.49453 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM020002 | PGS004049 (ldpred2.CV.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.9896 β: 0.68793 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM020003 | PGS004049 (ldpred2.CV.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.54092 β: 0.43238 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM020004 | PGS004049 (ldpred2.CV.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 2.36914 β: 0.86253 |
AUROC: 0.73 | — | 0 | beta = log(or)/sd_pgs |
| PPM020005 | PGS004118 (pt_clump.auto.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.33056 β: 0.2856 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM020006 | PGS004118 (pt_clump.auto.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.40296 β: 0.33858 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM020007 | PGS004118 (pt_clump.auto.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.70576 β: 0.53401 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM020008 | PGS004118 (pt_clump.auto.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.30274 β: 0.26447 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM020009 | PGS004118 (pt_clump.auto.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.56663 β: 0.44893 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM020010 | PGS004133 (pt_clump_nested.CV.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.34749 β: 0.29824 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM020011 | PGS004133 (pt_clump_nested.CV.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.43562 β: 0.3616 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM020012 | PGS004133 (pt_clump_nested.CV.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.54617 β: 0.43578 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM020013 | PGS004133 (pt_clump_nested.CV.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.33067 β: 0.28568 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM020014 | PGS004133 (pt_clump_nested.CV.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.49068 β: 0.39923 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM020015 | PGS003994 (dbslmm.auto.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.33393 β: 0.28813 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM020017 | PGS003994 (dbslmm.auto.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.37351 β: 0.31737 |
AUROC: 0.57 | — | 0 | beta = log(or)/sd_pgs |
| PPM020018 | PGS003994 (dbslmm.auto.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.1176 β: 0.11118 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM020019 | PGS003994 (dbslmm.auto.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.82399 β: 0.60103 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM020020 | PGS004148 (sbayesr.auto.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.39911 β: 0.33583 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM020021 | PGS004148 (sbayesr.auto.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.62873 β: 0.4878 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM020022 | PGS004148 (sbayesr.auto.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.86907 β: 0.62544 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM020023 | PGS004148 (sbayesr.auto.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.46527 β: 0.38204 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM020024 | PGS004148 (sbayesr.auto.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.74045 β: 0.55414 |
AUROC: 0.66 | — | 0 | beta = log(or)/sd_pgs |
| PPM020025 | PGS004163 (UKBB_EnsPGS.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.64114 β: 0.49539 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM020026 | PGS004163 (UKBB_EnsPGS.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.75402 β: 0.56191 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM020027 | PGS004163 (UKBB_EnsPGS.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 2.39078 β: 0.87162 |
AUROC: 0.74 | — | 0 | beta = log(or)/sd_pgs |
| PPM020028 | PGS004163 (UKBB_EnsPGS.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.6676 β: 0.51138 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM020029 | PGS004163 (UKBB_EnsPGS.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 2.46183 β: 0.90091 |
AUROC: 0.75 | — | 0 | beta = log(or)/sd_pgs |
| PPM020030 | PGS004079 (megaprs.CV.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.50199 β: 0.40679 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM020031 | PGS004079 (megaprs.CV.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.61696 β: 0.48055 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM020032 | PGS004079 (megaprs.CV.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 2.0218 β: 0.70399 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM020033 | PGS004079 (megaprs.CV.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.60515 β: 0.47322 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM020035 | PGS004064 (megaprs.auto.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.52285 β: 0.42059 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM020036 | PGS004064 (megaprs.auto.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.6765 β: 0.51671 |
AUROC: 0.64 | — | 0 | beta = log(or)/sd_pgs |
| PPM020037 | PGS004064 (megaprs.auto.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 2.16519 β: 0.77251 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM020038 | PGS004064 (megaprs.auto.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.52777 β: 0.42381 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM020039 | PGS004064 (megaprs.auto.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 2.12896 β: 0.75563 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM020040 | PGS004103 (prscs.CV.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.39977 β: 0.33631 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM020041 | PGS004103 (prscs.CV.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.43354 β: 0.36015 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM020042 | PGS004103 (prscs.CV.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.62378 β: 0.48476 |
AUROC: 0.65 | — | 0 | beta = log(or)/sd_pgs |
| PPM020043 | PGS004103 (prscs.CV.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.24983 β: 0.22301 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM020044 | PGS004103 (prscs.CV.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.9189 β: 0.65175 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM020045 | PGS004094 (prscs.auto.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.43309 β: 0.35983 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM020046 | PGS004094 (prscs.auto.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.64768 β: 0.49937 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM020047 | PGS004094 (prscs.auto.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.45841 β: 0.37734 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM020048 | PGS004094 (prscs.auto.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.30074 β: 0.26293 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM020049 | PGS004094 (prscs.auto.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.88898 β: 0.63604 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM020050 | PGS004010 (lassosum.auto.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.32987 β: 0.28508 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM020051 | PGS004010 (lassosum.auto.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.49732 β: 0.40368 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM020052 | PGS004010 (lassosum.auto.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.28607 β: 0.25159 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM020053 | PGS004010 (lassosum.auto.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.18691 β: 0.17135 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM020054 | PGS004010 (lassosum.auto.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.59047 β: 0.46403 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM020055 | PGS004021 (lassosum.CV.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.46364 β: 0.38093 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM020056 | PGS004021 (lassosum.CV.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.61006 β: 0.47627 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM020057 | PGS004021 (lassosum.CV.GCST90013534.RA) |
PSS011246| South Asian Ancestry| 44,057 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.91213 β: 0.64822 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM020058 | PGS004021 (lassosum.CV.GCST90013534.RA) |
PSS011262| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.4387 β: 0.36374 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM020059 | PGS004021 (lassosum.CV.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 2.11267 β: 0.74795 |
AUROC: 0.71 | — | 0 | beta = log(or)/sd_pgs |
| PPM020061 | PGS004119 (pt_clump.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.26981 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020062 | PGS004119 (pt_clump.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.25362 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020063 | PGS004119 (pt_clump.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.27669 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020064 | PGS004119 (pt_clump.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.24036 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020065 | PGS003995 (dbslmm.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.35385 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020066 | PGS003995 (dbslmm.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.32614 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020067 | PGS003995 (dbslmm.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.26677 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020068 | PGS003995 (dbslmm.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.33511 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020069 | PGS003995 (dbslmm.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.27048 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020070 | PGS004149 (sbayesr.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.35918 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020071 | PGS004149 (sbayesr.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.32289 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020072 | PGS004149 (sbayesr.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.28496 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020073 | PGS004149 (sbayesr.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.33073 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020074 | PGS004149 (sbayesr.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.28263 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020075 | PGS004036 (ldpred2.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.36472 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020076 | PGS004036 (ldpred2.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.33197 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020077 | PGS004036 (ldpred2.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.28234 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020078 | PGS004036 (ldpred2.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.34509 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020079 | PGS004036 (ldpred2.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.28559 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020080 | PGS004065 (megaprs.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.33881 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020081 | PGS004065 (megaprs.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.30485 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020082 | PGS004065 (megaprs.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.26196 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020083 | PGS004065 (megaprs.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.31748 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020084 | PGS004065 (megaprs.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.26382 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020085 | PGS004095 (prscs.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.35864 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020086 | PGS004095 (prscs.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.33536 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020087 | PGS004095 (prscs.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.26465 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020088 | PGS004095 (prscs.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.34613 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020089 | PGS004095 (prscs.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.26176 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020090 | PGS004011 (lassosum.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.31544 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020091 | PGS004011 (lassosum.auto.GCST90018959.Height) |
PSS011230| European Ancestry| 267,343 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.29137 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020092 | PGS004011 (lassosum.auto.GCST90018959.Height) |
PSS011243| South Asian Ancestry| 34,089 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.25831 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020093 | PGS004011 (lassosum.auto.GCST90018959.Height) |
PSS011259| European Ancestry| 66,700 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.31267 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM020094 | PGS004011 (lassosum.auto.GCST90018959.Height) |
PSS011287| South Asian Ancestry| 9,108 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.24786 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019179 | PGS004134 (sbayesr.auto.GCST002783.BMI) |
PSS011267| European Ancestry| 89,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.24019 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019930 | PGS004034 (ldpred2.auto.GCST90012877.AD) |
PSS011252| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.78882 β: 0.58156 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019180 | PGS004022 (ldpred2.auto.GCST002783.BMI) |
PSS011214| European Ancestry| 189,651 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.22444 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019925 | PGS004146 (sbayesr.auto.GCST90012877.AD) |
PSS011213| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.48544 β: 0.39571 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019926 | PGS004146 (sbayesr.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.52213 β: 0.42011 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019181 | PGS004022 (ldpred2.auto.GCST002783.BMI) |
PSS011237| South Asian Ancestry| 33,146 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Body Mass Index | β: 0.18252 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019246 | PGS004135 (sbayesr.auto.GCST004131.IBD) |
PSS011231| European Ancestry| 396,819 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.982 β: 0.68411 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019251 | PGS004023 (ldpred2.auto.GCST004131.IBD) |
PSS011220| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.37223 β: 0.31644 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019280 | PGS004081 (prscs.auto.GCST004131.IBD) |
PSS011273| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Inflammatory bowel disease | OR: 1.87137 β: 0.62667 |
AUROC: 0.67 | — | 0 | beta = log(or)/sd_pgs |
| PPM019311 | PGS003982 (dbslmm.auto.GCST004773.T2D) |
PSS011225| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.48531 β: 0.39562 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019318 | PGS004136 (sbayesr.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.50666 β: 0.40989 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019336 | PGS004052 (megaprs.auto.GCST004773.T2D) |
PSS011236| European Ancestry| 377,408 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.53613 β: 0.42927 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM019363 | PGS004014 (lassosum.CV.GCST004773.T2D) |
PSS011291| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Type 2 Diabetes | OR: 1.34108 β: 0.29348 |
AUROC: 0.58 | — | 0 | beta = log(or)/sd_pgs |
| PPM019393 | PGS003983 (dbslmm.auto.GCST004988.Breast_cancer) |
PSS011282| South Asian Ancestry| 4,350 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Breast cancer | OR: 1.467 β: 0.38322 |
AUROC: 0.6 | — | 0 | beta = log(or)/sd_pgs |
| PPM019461 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011223| European Ancestry| 48,148 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12873 β: 0.1211 |
AUROC: 0.54 | — | 0 | beta = log(or)/sd_pgs |
| PPM019465 | PGS004154 (UKBB_EnsPGS.GCST005838.Stroke) |
PSS011290| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.18096 β: 0.16632 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019498 | PGS004000 (lassosum.auto.GCST005838.Stroke) |
PSS011234| European Ancestry| 376,733 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Stroke excluding subarachnoid hemorrhage | OR: 1.12015 β: 0.11346 |
AUROC: 0.53 | — | 0 | beta = log(or)/sd_pgs |
| PPM019525 | PGS004125 (pt_clump_nested.CV.GCST006085.Prostate_cancer) |
PSS011289| South Asian Ancestry| 4,976 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.09235 β: 0.73829 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019538 | PGS004155 (UKBB_EnsPGS.GCST006085.Prostate_cancer) |
PSS011274| European Ancestry| 41,305 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.07191 β: 0.72847 |
AUROC: 0.69 | — | 0 | beta = log(or)/sd_pgs |
| PPM019565 | PGS004099 (prscs.CV.GCST006085.Prostate_cancer) |
PSS011245| South Asian Ancestry| 19,738 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Prostate cancer | OR: 2.15033 β: 0.76562 |
AUROC: 0.72 | — | 0 | beta = log(or)/sd_pgs |
| PPM019582 | PGS004043 (ldpred2.CV.GCST007140.HDL) |
PSS011241| South Asian Ancestry| 29,628 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.33264 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019595 | PGS004126 (pt_clump_nested.CV.GCST007140.HDL) |
PSS011271| European Ancestry| 78,782 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.2406 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019606 | PGS004140 (sbayesr.auto.GCST007140.HDL) |
PSS011218| European Ancestry| 10,642 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: high-density lipoprotein cholesterol | β: 0.25977 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019651 | PGS004127 (pt_clump_nested.CV.GCST007954.HbA1c) |
PSS011286| South Asian Ancestry| 8,748 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Haemoglobin A1C | β: 0.12036 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019713 | PGS004129 (pt_clump_nested.CV.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.259 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019721 | PGS004159 (UKBB_EnsPGS.GCST008059.eGFR) |
PSS011251| South Asian Ancestry| 3,061 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.23205 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019753 | PGS004031 (ldpred2.auto.GCST008059.eGFR) |
PSS011280| European Ancestry| 86,034 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.3212 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019774 | PGS004074 (megaprs.CV.GCST008059.CKD) |
PSS011269| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.37315 β: 0.31711 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM019779 | PGS004101 (prscs.CV.GCST008059.CKD) |
PSS011283| South Asian Ancestry| 9,326 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Chronic kidney disease or dialysis | OR: 1.26007 β: 0.23117 |
AUROC: 0.56 | — | 0 | beta = log(or)/sd_pgs |
| PPM019805 | PGS004017 (lassosum.CV.GCST008059.eGFR) |
PSS011266| European Ancestry| 66,759 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: estimated glomerular filtration rate | β: 0.21678 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019843 | PGS003991 (dbslmm.auto.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.21712 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019845 | PGS003991 (dbslmm.auto.GCST008972.Urate) |
PSS011279| European Ancestry| 85,973 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.25263 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019879 | PGS004076 (megaprs.CV.GCST008972.Gout) |
PSS011270| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Gout | OR: 1.97547 β: 0.68081 |
AUROC: 0.68 | — | 0 | beta = log(or)/sd_pgs |
| PPM019897 | PGS004091 (prscs.auto.GCST008972.Urate) |
PSS011292| South Asian Ancestry| 8,842 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Urate | β: 0.20722 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
| PPM019932 | PGS004062 (megaprs.auto.GCST90012877.AD) |
PSS011226| European Ancestry| 389,004 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: AD | OR: 1.48022 β: 0.39219 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM019955 | PGS004147 (sbayesr.auto.GCST90013445.T1D) |
PSS011224| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.62883 β: 0.48786 |
AUROC: 0.63 | — | 0 | beta = log(or)/sd_pgs |
| PPM019978 | PGS004078 (megaprs.CV.GCST90013445.T1D) |
PSS011264| European Ancestry| 66,865 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: T1D | OR: 1.39887 β: 0.33567 |
AUROC: 0.59 | — | 0 | beta = log(or)/sd_pgs |
| PPM020000 | PGS004049 (ldpred2.CV.GCST90013534.RA) |
PSS011222| European Ancestry| 199,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.55377 β: 0.44069 |
AUROC: 0.62 | — | 0 | beta = log(or)/sd_pgs |
| PPM020016 | PGS003994 (dbslmm.auto.GCST90013534.RA) |
PSS011233| European Ancestry| 388,890 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 1.50841 β: 0.41106 |
AUROC: 0.61 | — | 0 | beta = log(or)/sd_pgs |
| PPM020034 | PGS004079 (megaprs.CV.GCST90013534.RA) |
PSS011275| European Ancestry| 90,274 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Seropositive RA | OR: 2.22137 β: 0.79813 |
AUROC: 0.72 | — | 0 | beta = log(or)/sd_pgs |
| PPM020060 | PGS004119 (pt_clump.auto.GCST90018959.Height) |
PSS011219| European Ancestry| 190,013 individuals |
PGP000517 | Monti M R et al. medRxiv (2023) |Pre |
Reported Trait: Height | β: 0.29998 | — | — | 0 | beta = sd_trait/sd_pgs = pearson correlation |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS011213 | — | — | [
|
— | European | — | EB | — |
| PSS011214 | — | — | 189,651 individuals | — | European | — | EB | — |
| PSS011215 | — | — | [ ,
0.0 % Male samples |
— | European | — | EB | — |
| PSS011216 | — | — | [
|
— | European | — | EB | — |
| PSS011217 | — | — | [
|
— | European | — | EB | — |
| PSS011218 | — | — | 10,642 individuals | — | European | — | EB | — |
| PSS011219 | — | — | 190,013 individuals | — | European | — | EB | — |
| PSS011220 | — | — | [
|
— | European | — | EB | — |
| PSS011221 | — | — | [ ,
100.0 % Male samples |
— | European | — | EB | — |
| PSS011222 | — | — | [
|
— | European | — | EB | — |
| PSS011223 | — | — | [
|
— | European | — | EB | — |
| PSS011224 | — | — | [
|
— | European | — | EB | — |
| PSS011225 | — | — | [
|
— | European | — | EB | — |
| PSS011226 | G6_AD_WIDE, ICD10: G30|F00, ICD9: 3310 | — | [
|
— | European | — | FinnGen | — |
| PSS011227 | C3_BREAST, ICD10: C0, ICD9: 174 | — | [ ,
0.0 % Male samples |
— | European | — | FinnGen | — |
| PSS011228 | N14_CHRONKIDNEYDIS, ICD10: N18, ICD9: 585, include dialysis (ICD10 Z992|Y841) | — | [
|
— | European | — | FinnGen | — |
| PSS011229 | M13_GOUT, ICD10: M10, ICD9: 2740 | — | [
|
— | European | — | FinnGen | — |
| PSS011230 | — | — | 267,343 individuals | — | European | — | FinnGen | — |
| PSS011231 | K11_IBD_STRICT, ICD10: K50|K51, ICD9: 555|556 | — | [
|
— | European | — | FinnGen | — |
| PSS011232 | C3_PROSTATE, ICD10: C61, ICD9: 185 | — | [ ,
100.0 % Male samples |
— | European | — | FinnGen | — |
| PSS011233 | RHEUMA_SEROPOS_OTH, ICD10: M05[8-9], ICD9: 7140A | — | [
|
— | European | — | FinnGen | — |
| PSS011234 | I9_STR, ICD10: I61 | I63 | I64 (exclude I636), ICD9:431|4330A|4331A|4339A|4340A|4341A|4349A|436 | — | [
|
— | European | — | FinnGen | — |
| PSS011235 | T1D, ICD10: E10, ICD9: 250[0|1]1 (exclude E11) | — | [
|
— | European | — | FinnGen | — |
| PSS011236 | T2D, ICD10: E11, ICD9: 250[0|1]0 (exclude E10) | — | [
|
— | European | — | FinnGen | — |
| PSS011237 | — | — | 33,146 individuals | — | South Asian | — | G&H | — |
| PSS011238 | — | — | [ ,
0.0 % Male samples |
— | South Asian | — | G&H | — |
| PSS011239 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS011240 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS011241 | — | — | 29,628 individuals | — | South Asian | — | G&H | — |
| PSS011242 | — | — | 12,948 individuals | — | South Asian | — | G&H | — |
| PSS011243 | — | — | 34,089 individuals | — | South Asian | — | G&H | — |
| PSS011244 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS011245 | — | — | [ ,
100.0 % Male samples |
— | South Asian | — | G&H | — |
| PSS011246 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS011247 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS011248 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS011249 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS011250 | — | — | 4,730 individuals | — | European | — | G&H | — |
| PSS011251 | — | — | 3,061 individuals | — | South Asian | — | G&H | — |
| PSS011252 | — | — | [
|
— | European | — | HUNT | — |
| PSS011253 | — | — | 66,663 individuals | — | European | — | HUNT | — |
| PSS011254 | — | — | [ ,
0.0 % Male samples |
— | European | — | HUNT | — |
| PSS011255 | — | — | [
|
— | European | — | HUNT | — |
| PSS011256 | — | — | [
|
— | European | — | HUNT | — |
| PSS011257 | — | — | 49,824 individuals | — | European | — | HUNT | — |
| PSS011258 | — | — | 34,192 individuals | — | European | — | HUNT | — |
| PSS011259 | — | — | 66,700 individuals | — | European | — | HUNT | — |
| PSS011260 | — | — | [
|
— | European | — | HUNT | — |
| PSS011261 | — | — | [ ,
100.0 % Male samples |
— | European | — | HUNT | — |
| PSS011262 | — | — | [
|
— | European | — | HUNT | — |
| PSS011263 | — | — | [
|
— | European | — | HUNT | — |
| PSS011264 | — | — | [
|
— | European | — | HUNT | — |
| PSS011265 | — | — | [
|
— | European | — | HUNT | — |
| PSS011266 | — | — | 66,759 individuals | — | European | — | HUNT | — |
| PSS011267 | — | — | 89,976 individuals | — | European | — | UKB | — |
| PSS011268 | — | — | [ ,
0.0 % Male samples |
— | European | — | UKB | — |
| PSS011269 | — | — | [
|
— | European | — | UKB | — |
| PSS011270 | — | — | [
|
— | European | — | UKB | — |
| PSS011271 | — | — | 78,782 individuals | — | European | — | UKB | — |
| PSS011272 | — | — | 86,050 individuals | — | European | — | UKB | — |
| PSS011273 | — | — | [
|
— | European | — | UKB | — |
| PSS011274 | — | — | [ ,
100.0 % Male samples |
— | European | — | UKB | — |
| PSS011275 | — | — | [
|
— | European | — | UKB | — |
| PSS011276 | — | — | [
|
— | European | — | UKB | — |
| PSS011277 | — | — | [
|
— | European | — | UKB | — |
| PSS011278 | — | — | [
|
— | European | — | UKB | — |
| PSS011279 | — | — | 85,973 individuals | — | European | — | UKB | — |
| PSS011280 | — | — | 86,034 individuals | — | European | — | UKB | — |
| PSS011281 | — | — | 9,097 individuals | — | South Asian | — | UKB | — |
| PSS011282 | — | — | [ ,
0.0 % Male samples |
— | South Asian | — | UKB | — |
| PSS011283 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS011284 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS011285 | — | — | 8,065 individuals | — | South Asian | — | UKB | — |
| PSS011286 | — | — | 8,748 individuals | — | South Asian | — | UKB | — |
| PSS011287 | — | — | 9,108 individuals | — | South Asian | — | UKB | — |
| PSS011288 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS011289 | — | — | [ ,
100.0 % Male samples |
— | South Asian | — | UKB | — |
| PSS011290 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS011291 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS011292 | — | — | 8,842 individuals | — | South Asian | — | UKB | — |
| PSS011293 | — | — | 8,855 individuals | — | South Asian | — | UKB | — |