| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0000589 |
| Description | A congenital disorder (due to inherited enzyme abnormality) or acquired (due to failure of a metabolically important organ) disorder resulting from an abnormal metabolic process. [NCIT: C3235] | Trait category |
Metabolic disorder
|
| Synonyms |
26 synonyms
|
| Mapped terms |
13 mapped terms
|
| Child trait(s) |
16 child traits
|
| Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants |
Ancestry distribution GWAS Dev Eval |
Scoring File (FTP Link) |
|---|---|---|---|---|---|---|
| PGS000014 (GPS_T2D) |
PGP000006 | Khera AV et al. Nat Genet (2018) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,917,436 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000014/ScoringFiles/PGS000014.txt.gz | |
| PGS000020 (dGRS1000) |
PGP000010 | Läll K et al. Genet Med (2016) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 7,502 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000020/ScoringFiles/PGS000020.txt.gz |
| PGS000021 (GRS1) |
PGP000011 | Oram RA et al. Diabetes Care (2015) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 30 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000021/ScoringFiles/PGS000021.txt.gz | |
| PGS000022 (T1D_GRS) |
PGP000012 | Perry DJ et al. Sci Rep (2018) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 37 | - - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000022/ScoringFiles/PGS000022.txt.gz |
| PGS000023 (AA_GRS) |
PGP000013 | Onengut-Gumuscu S et al. Diabetes Care (2019) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 7 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000023/ScoringFiles/PGS000023.txt.gz |
| PGS000024 (GRS2) |
PGP000014 | Sharp SA et al. Diabetes Care (2019) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 67 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000024/ScoringFiles/PGS000024.txt.gz |
| PGS000031 (GRSt) |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 62 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000031/ScoringFiles/PGS000031.txt.gz |
| PGS000032 (GRSB) |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Type 2 diabetes (based on SNPs involved in β-cell function) | type 2 diabetes mellitus | 20 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000032/ScoringFiles/PGS000032.txt.gz |
| PGS000033 (GRSIR) |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Type 2 diabetes (based on SNPs involved in insulin resistance) | type 2 diabetes mellitus | 10 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000033/ScoringFiles/PGS000033.txt.gz |
| PGS000036 (gePS_T2D) |
PGP000023 | Mahajan A et al. Nat Genet (2018) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 171,249 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000036/ScoringFiles/PGS000036.txt.gz | |
| PGS000125 (Qi_T2D_2017) |
PGP000062 | Qi Q et al. Diabetes (2017) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 80 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000125/ScoringFiles/PGS000125.txt.gz |
| PGS000199 (G-PROB_Gout) |
PGP000081 | Knevel R et al. Sci Transl Med (2020) |
Gout | gout | 250 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000199/ScoringFiles/PGS000199.txt.gz |
| PGS000330 (PRS_T2D) |
PGP000100 | Mars N et al. Nat Med (2020) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,437,380 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000330/ScoringFiles/PGS000330.txt.gz | |
| PGS000711 (HC328) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Gout | gout | 183,332 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000711/ScoringFiles/PGS000711.txt.gz |
| PGS000712 (T2D_HbA1c_39) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
T2D (cases vs HbA1c filtered controls) | type 2 diabetes mellitus | 183,695 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000712/ScoringFiles/PGS000712.txt.gz |
| PGS000713 (T2D) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 183,830 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000713/ScoringFiles/PGS000713.txt.gz |
| PGS000729 (T2D_PGS) |
PGP000137 | Ritchie SC et al. Nat Metab (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 2,017,388 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000729/ScoringFiles/PGS000729.txt.gz |
| PGS000804 (GRS582_T2Dmulti) |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 582 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000804/ScoringFiles/PGS000804.txt.gz |
| PGS000805 (GRS582_T2Deur) |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 582 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000805/ScoringFiles/PGS000805.txt.gz |
| PGS000806 (GRS582_T2Dafr) |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 582 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000806/ScoringFiles/PGS000806.txt.gz |
| PGS000807 (GRS582_T2Dasn) |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 582 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000807/ScoringFiles/PGS000807.txt.gz |
| PGS000808 (GRS582_T2Dhis) |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 582 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000808/ScoringFiles/PGS000808.txt.gz |
| PGS000819 (PRS_DR) |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Diabetic retinopathy | diabetic retinopathy | 3,537,914 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000819/ScoringFiles/PGS000819.txt.gz |
| PGS000832 (T2D-GRS) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 384 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000832/ScoringFiles/PGS000832.txt.gz |
| PGS000833 (T1D) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 66 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000833/ScoringFiles/PGS000833.txt.gz |
| PGS000848 (T2D_Adiposity) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with adiposity) | type 2 diabetes mellitus | 6 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000848/ScoringFiles/PGS000848.txt.gz |
| PGS000849 (T2D_Impaired_Lipids) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with impaired lipids) | type 2 diabetes mellitus | 3 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000849/ScoringFiles/PGS000849.txt.gz |
| PGS000850 (T2D_Insulin_Action) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with insulin action) | type 2 diabetes mellitus | 16 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000850/ScoringFiles/PGS000850.txt.gz |
| PGS000851 (T2D_Insulin_Action_Secretion) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with insulin action/secretion) | type 2 diabetes mellitus | 37 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000851/ScoringFiles/PGS000851.txt.gz |
| PGS000852 (T2D_Insulin_Secretion_1) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with insulin secretion) | type 2 diabetes mellitus | 8 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000852/ScoringFiles/PGS000852.txt.gz |
| PGS000853 (T2D_Insulin_Secretion_2) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with insulin secretion) | type 2 diabetes mellitus | 21 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000853/ScoringFiles/PGS000853.txt.gz |
| PGS000854 (T2D_BetaCell) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with beta cell function) | type 2 diabetes mellitus | 27 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000854/ScoringFiles/PGS000854.txt.gz |
| PGS000855 (T2D_Lipodystrophy) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with lipodystrophy) | type 2 diabetes mellitus | 18 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000855/ScoringFiles/PGS000855.txt.gz |
| PGS000856 (T2D_LiverLipids) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with liver lipids) | type 2 diabetes mellitus | 3 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000856/ScoringFiles/PGS000856.txt.gz |
| PGS000857 (T2D_Obesity) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with obesity) | type 2 diabetes mellitus | 4 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000857/ScoringFiles/PGS000857.txt.gz |
| PGS000858 (T2D_Proinsulin) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (based on SNPs associated with proinsulin levels) | type 2 diabetes mellitus | 6 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000858/ScoringFiles/PGS000858.txt.gz |
| PGS000862 (DR) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Diabetic Retinopathy | diabetic retinopathy | 30 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000862/ScoringFiles/PGS000862.txt.gz |
| PGS000864 (T2D-gPRS) |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 389,243 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000864/ScoringFiles/PGS000864.txt.gz |
| PGS000868 (T2D_221) |
PGP000214 | Aksit MA et al. J Clin Endocrinol Metab (2020) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 221 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000868/ScoringFiles/PGS000868.txt.gz |
| PGS000869 (T1D_48) |
PGP000214 | Aksit MA et al. J Clin Endocrinol Metab (2020) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 48 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000869/ScoringFiles/PGS000869.txt.gz |
| PGS000924 (GBE_HC702) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Disorders of porphyrin and bilirubin metabolism (time-to-event) | bilirubin metabolism disease, porphyrin metabolism disease |
5 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000924/ScoringFiles/PGS000924.txt.gz |
| PGS001023 (GBE_HC703) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Disorders of mineral metabolism (time-to-event) | mineral metabolism disease | 2 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001023/ScoringFiles/PGS001023.txt.gz |
| PGS001248 (GBE_HC328) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Gout | gout | 880 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001248/ScoringFiles/PGS001248.txt.gz |
| PGS001249 (GBE_HC1215) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Gout (time-to-event) | gout | 1,796 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001249/ScoringFiles/PGS001249.txt.gz |
| PGS001294 (GBE_HC649) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Non-insulin-dependent diabetes (time-to-event) | type 2 diabetes mellitus | 3,496 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001294/ScoringFiles/PGS001294.txt.gz |
| PGS001295 (GBE_HC165) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 385 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001295/ScoringFiles/PGS001295.txt.gz |
| PGS001296 (GBE_HC648) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Insulin-dependent diabetes mellitus (time-to-event) | type 1 diabetes mellitus | 356 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001296/ScoringFiles/PGS001296.txt.gz |
| PGS001297 (GBE_HC337) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 69 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001297/ScoringFiles/PGS001297.txt.gz |
| PGS001298 (GBE_HC689) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Obesity (time-to-event) | obesity | 9,227 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001298/ScoringFiles/PGS001298.txt.gz |
| PGS001305 (GBE_HC608) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Vitamin B12 deficiency induced anemia (time-to-event) | vitamin B12 deficiency, anemia |
121 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001305/ScoringFiles/PGS001305.txt.gz |
| PGS001318 (GBE_HC700) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Disorders of lipoprotein metabolism and other lipidaemias (time-to-event) | metabolic disease | 7,845 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001318/ScoringFiles/PGS001318.txt.gz |
| PGS001319 (GBE_HC708) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Other metabolic disorders (time-to-event) | metabolic disease | 2 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001319/ScoringFiles/PGS001319.txt.gz |
| PGS001327 (GBE_HC221) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Diabetes | diabetes mellitus | 4,053 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001327/ScoringFiles/PGS001327.txt.gz |
| PGS001329 (GBE_HC652) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Unspecified diabetes mellitus (time-to-event) | diabetes mellitus | 2,270 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001329/ScoringFiles/PGS001329.txt.gz |
| PGS001357 (T2D_AnnoPred_PRS) |
PGP000252 | Ye Y et al. Circ Genom Precis Med (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 2,996,761 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001357/ScoringFiles/PGS001357.txt.gz | |
| PGS001371 (GBE_INI2976) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Age diabetes diagnosed | diabetes mellitus, age at diagnosis |
26 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001371/ScoringFiles/PGS001371.txt.gz |
| PGS001781 (T2D_PRSCS) |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,091,673 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001781/ScoringFiles/PGS001781.txt.gz |
| PGS001789 (1kgeur_gbmi_leaveUKBBout_Gout_pst_eff_a1_b0.5_phiauto) |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Gout | gout | 910,151 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001789/ScoringFiles/PGS001789.txt.gz |
| PGS001817 (portability-PLR_250.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 825 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001817/ScoringFiles/PGS001817.txt.gz |
| PGS001818 (portability-PLR_250.2) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 30,745 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001818/ScoringFiles/PGS001818.txt.gz |
| PGS001819 (portability-PLR_250.7) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Diabetic retinopathy | diabetic retinopathy | 249 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001819/ScoringFiles/PGS001819.txt.gz |
| PGS001822 (portability-PLR_274.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Gout | gout | 216 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001822/ScoringFiles/PGS001822.txt.gz |
| PGS001823 (portability-PLR_275.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Disorders of iron metabolism | iron metabolism disease | 654 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001823/ScoringFiles/PGS001823.txt.gz |
| PGS001824 (portability-PLR_277.4) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Disorders of bilirubin excretion | Disorder of bilirubin metabolism and excretion | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001824/ScoringFiles/PGS001824.txt.gz |
| PGS001825 (portability-PLR_278) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Overweight, obesity and other hyperalimentation | obesity, overweight body mass index status, overnutrition |
13,009 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001825/ScoringFiles/PGS001825.txt.gz |
| PGS002025 (portability-ldpred2_250.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 106,800 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002025/ScoringFiles/PGS002025.txt.gz |
| PGS002026 (portability-ldpred2_250.2) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 830,783 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002026/ScoringFiles/PGS002026.txt.gz |
| PGS002027 (portability-ldpred2_250.7) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Diabetic retinopathy | diabetic retinopathy | 389,029 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002027/ScoringFiles/PGS002027.txt.gz |
| PGS002030 (portability-ldpred2_274.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Gout | gout | 163,210 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002030/ScoringFiles/PGS002030.txt.gz |
| PGS002031 (portability-ldpred2_275.1) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Disorders of iron metabolism | iron metabolism disease | 6,713 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002031/ScoringFiles/PGS002031.txt.gz |
| PGS002032 (portability-ldpred2_277.4) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Disorders of bilirubin excretion | Disorder of bilirubin metabolism and excretion | 19,768 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002032/ScoringFiles/PGS002032.txt.gz |
| PGS002033 (portability-ldpred2_278) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Overweight, obesity and other hyperalimentation | obesity, overweight body mass index status, overnutrition |
846,292 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002033/ScoringFiles/PGS002033.txt.gz |
| PGS002098 (portability-ldpred2_abnormal_appetite) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Recent poor appetite or overeating | eating disorder | 764,146 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002098/ScoringFiles/PGS002098.txt.gz |
| PGS002243 (ldpred_t2d) |
PGP000271 | Mars N et al. Cell Genom (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,431,973 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002243/ScoringFiles/PGS002243.txt.gz | |
| PGS002256 (GRS4_GDM) |
PGP000282 | Wu Q et al. Diabetol Metab Syndr (2022) |
Gestational diabetes mellitus in early pregnancy | gestational diabetes | 4 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002256/ScoringFiles/PGS002256.txt.gz | |
| PGS002277 (pPS_Insulin_secretion_1) |
PGP000305 | Siddiqui MK et al. Diabetologia (2022) |
Type 2 diabetes (based on SNPs associated with insulin secretion) | type 2 diabetes mellitus | 8 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002277/ScoringFiles/PGS002277.txt.gz |
| PGS002307 (PRS33_gout) |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Gout | gout | 33 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002307/ScoringFiles/PGS002307.txt.gz |
| PGS002308 (PRScsx_T2D) |
PGP000331 | Ge T et al. Genome Med (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,259,754 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002308/ScoringFiles/PGS002308.txt.gz |
| PGS002321 (disease_DIABETES_ANY_DIAGNOSED.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002321/ScoringFiles/PGS002321.txt.gz |
| PGS002324 (disease_ENDOCRINE_DIABETES.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002324/ScoringFiles/PGS002324.txt.gz |
| PGS002354 (disease_T2D.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002354/ScoringFiles/PGS002354.txt.gz |
| PGS002379 (disease_T2D.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 920,930 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002379/ScoringFiles/PGS002379.txt.gz |
| PGS002393 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 3,813 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002393/ScoringFiles/PGS002393.txt.gz |
| PGS002396 (disease_ENDOCRINE_DIABETES.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
3,681 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002396/ScoringFiles/PGS002396.txt.gz |
| PGS002426 (disease_T2D.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 3,947 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002426/ScoringFiles/PGS002426.txt.gz |
| PGS002442 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 15,915 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002442/ScoringFiles/PGS002442.txt.gz |
| PGS002445 (disease_ENDOCRINE_DIABETES.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
15,629 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002445/ScoringFiles/PGS002445.txt.gz |
| PGS002475 (disease_T2D.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 16,275 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002475/ScoringFiles/PGS002475.txt.gz |
| PGS002491 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 95,066 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002491/ScoringFiles/PGS002491.txt.gz |
| PGS002494 (disease_ENDOCRINE_DIABETES.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
93,293 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002494/ScoringFiles/PGS002494.txt.gz |
| PGS002524 (disease_T2D.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 95,287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002524/ScoringFiles/PGS002524.txt.gz |
| PGS002540 (disease_DIABETES_ANY_DIAGNOSED.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 598 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002540/ScoringFiles/PGS002540.txt.gz |
| PGS002543 (disease_ENDOCRINE_DIABETES.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
528 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002543/ScoringFiles/PGS002543.txt.gz |
| PGS002573 (disease_T2D.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 673 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002573/ScoringFiles/PGS002573.txt.gz |
| PGS002589 (disease_DIABETES_ANY_DIAGNOSED.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 267 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002589/ScoringFiles/PGS002589.txt.gz |
| PGS002592 (disease_ENDOCRINE_DIABETES.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
187 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002592/ScoringFiles/PGS002592.txt.gz |
| PGS002622 (disease_T2D.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 293 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002622/ScoringFiles/PGS002622.txt.gz |
| PGS002638 (disease_DIABETES_ANY_DIAGNOSED.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 247,386 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002638/ScoringFiles/PGS002638.txt.gz |
| PGS002641 (disease_ENDOCRINE_DIABETES.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
256,678 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002641/ScoringFiles/PGS002641.txt.gz |
| PGS002671 (disease_T2D.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 258,382 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002671/ScoringFiles/PGS002671.txt.gz |
| PGS002687 (disease_DIABETES_ANY_DIAGNOSED.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Diabetes (any type) | diabetes mellitus | 923,080 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002687/ScoringFiles/PGS002687.txt.gz |
| PGS002690 (disease_ENDOCRINE_DIABETES.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Endocrine and diabetes diseases | diabetes mellitus, endocrine system disease |
905,637 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002690/ScoringFiles/PGS002690.txt.gz |
| PGS002720 (disease_T2D.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 911,809 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002720/ScoringFiles/PGS002720.txt.gz |
| PGS002733 (GRS17_T2D) |
PGP000342 | Pezzilli S et al. Diabetes Metab (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 17 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002733/ScoringFiles/PGS002733.txt.gz |
| PGS002762 (Urate_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Gout | gout | 1,092,214 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002762/ScoringFiles/PGS002762.txt.gz |
| PGS002771 (Type_2_diabetes_prscs) |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,091,608 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002771/ScoringFiles/PGS002771.txt.gz |
| PGS002779 (GTG_T2D_maxCT) |
PGP000365 | Wong CK et al. PLoS One (2022) |
Incident type 2 diabetes | type 2 diabetes mellitus | 46,353 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002779/ScoringFiles/PGS002779.txt.gz | |
| PGS002780 (GTG_T2D_SCT) |
PGP000365 | Wong CK et al. PLoS One (2022) |
Incident type 2 diabetes | type 2 diabetes mellitus | 419,209 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002780/ScoringFiles/PGS002780.txt.gz | |
| PGS003089 (ExPRSweb_T2D_2443_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 488,969 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003089/ScoringFiles/PGS003089.txt.gz | |
| PGS003090 (ExPRSweb_T2D_2443_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,888 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003090/ScoringFiles/PGS003090.txt.gz | |
| PGS003091 (ExPRSweb_T2D_2443_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 2,707 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003091/ScoringFiles/PGS003091.txt.gz | |
| PGS003092 (ExPRSweb_T2D_2443_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 10,304,000 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003092/ScoringFiles/PGS003092.txt.gz | |
| PGS003093 (ExPRSweb_T2D_2443_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,113,832 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003093/ScoringFiles/PGS003093.txt.gz | |
| PGS003094 (ExPRSweb_T2D_29358691-GCST005413_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 266,890 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003094/ScoringFiles/PGS003094.txt.gz | |
| PGS003095 (ExPRSweb_T2D_29358691-GCST005413_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 45 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003095/ScoringFiles/PGS003095.txt.gz | |
| PGS003096 (ExPRSweb_T2D_29358691-GCST005413_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 46 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003096/ScoringFiles/PGS003096.txt.gz | |
| PGS003097 (ExPRSweb_T2D_29358691-GCST005413_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 229 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003097/ScoringFiles/PGS003097.txt.gz | |
| PGS003098 (ExPRSweb_T2D_29358691-GCST005413_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,116,101 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003098/ScoringFiles/PGS003098.txt.gz | |
| PGS003099 (ExPRSweb_T2D_30054458-GCST006867_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 555,512 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003099/ScoringFiles/PGS003099.txt.gz | |
| PGS003100 (ExPRSweb_T2D_30054458-GCST006867_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 5,693 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003100/ScoringFiles/PGS003100.txt.gz | |
| PGS003101 (ExPRSweb_T2D_30054458-GCST006867_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 5,693 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003101/ScoringFiles/PGS003101.txt.gz | |
| PGS003102 (ExPRSweb_T2D_30054458-GCST006867_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 5,052,574 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003102/ScoringFiles/PGS003102.txt.gz | |
| PGS003103 (ExPRSweb_T2D_30054458-GCST006867_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 945,820 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003103/ScoringFiles/PGS003103.txt.gz | |
| PGS003104 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_LASSOSUM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 374,510 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003104/ScoringFiles/PGS003104.txt.gz | |
| PGS003105 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PT_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 187 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003105/ScoringFiles/PGS003105.txt.gz | |
| PGS003106 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PLINK_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 187 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003106/ScoringFiles/PGS003106.txt.gz | |
| PGS003107 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_DBSLMM_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 995 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003107/ScoringFiles/PGS003107.txt.gz | |
| PGS003108 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PRSCS_MGI_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,118,480 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003108/ScoringFiles/PGS003108.txt.gz | |
| PGS003109 (ExPRSweb_T2D_29358691-GCST005413_LASSOSUM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 311,565 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003109/ScoringFiles/PGS003109.txt.gz | |
| PGS003110 (ExPRSweb_T2D_29358691-GCST005413_PT_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 118 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003110/ScoringFiles/PGS003110.txt.gz | |
| PGS003111 (ExPRSweb_T2D_29358691-GCST005413_PLINK_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 143 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003111/ScoringFiles/PGS003111.txt.gz | |
| PGS003112 (ExPRSweb_T2D_29358691-GCST005413_DBSLMM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 222 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003112/ScoringFiles/PGS003112.txt.gz | |
| PGS003113 (ExPRSweb_T2D_29358691-GCST005413_PRSCS_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,117,087 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003113/ScoringFiles/PGS003113.txt.gz | |
| PGS003114 (ExPRSweb_T2D_30054458-GCST006867_LASSOSUM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 555,528 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003114/ScoringFiles/PGS003114.txt.gz | |
| PGS003115 (ExPRSweb_T2D_30054458-GCST006867_PT_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 31,462 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003115/ScoringFiles/PGS003115.txt.gz | |
| PGS003116 (ExPRSweb_T2D_30054458-GCST006867_PLINK_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 31,462 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003116/ScoringFiles/PGS003116.txt.gz | |
| PGS003117 (ExPRSweb_T2D_30054458-GCST006867_DBSLMM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 5,052,993 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003117/ScoringFiles/PGS003117.txt.gz | |
| PGS003118 (ExPRSweb_T2D_30054458-GCST006867_PRSCS_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 945,921 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003118/ScoringFiles/PGS003118.txt.gz | |
| PGS003119 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_LASSOSUM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 407,553 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003119/ScoringFiles/PGS003119.txt.gz | |
| PGS003120 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PT_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 193 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003120/ScoringFiles/PGS003120.txt.gz | |
| PGS003121 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PLINK_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 193 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003121/ScoringFiles/PGS003121.txt.gz | |
| PGS003122 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_DBSLMM_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 264 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003122/ScoringFiles/PGS003122.txt.gz | |
| PGS003123 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PRSCS_UKB_20211120) |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,119,522 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003123/ScoringFiles/PGS003123.txt.gz | |
| PGS003329 (PRS19_gout) |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Gout | gout | 19 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003329/ScoringFiles/PGS003329.txt.gz |
| PGS003353 (GRS_T2D) |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003353/ScoringFiles/PGS003353.txt.gz |
| PGS003400 (PRS97_obesity) |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Obesity | obesity | 97 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003400/ScoringFiles/PGS003400.txt.gz |
| PGS003402 (PRS_T2D) |
PGP000419 | Lamri A et al. Elife (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,838 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003402/ScoringFiles/PGS003402.txt.gz | |
| PGS003443 (PRScsx_T2D_LAT_EURweights) |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,092,496 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003443/ScoringFiles/PGS003443.txt.gz | |
| PGS003444 (PRScsx_T2D_LAT_EASweights) |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,001,579 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003444/ScoringFiles/PGS003444.txt.gz | |
| PGS003445 (PRScsx_T2D_LAT_LATweights) |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,149,210 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003445/ScoringFiles/PGS003445.txt.gz | |
| PGS003452 (PRS2_WM) |
PGP000448 | Berndt SI et al. Leukemia (2022) |
Waldenström macroglobulinemia | Waldenstrom macroglobulinemia | 2 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003452/ScoringFiles/PGS003452.txt.gz |
| PGS003728 (PS_T2D_183-AGEN) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 183 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003728/ScoringFiles/PGS003728.txt.gz |
| PGS003729 (PS_T2D_293-DIAGRAM) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 293 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003729/ScoringFiles/PGS003729.txt.gz |
| PGS003730 (PS_T2D_287-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003730/ScoringFiles/PGS003730.txt.gz |
| PGS003731 (PS_T2D_282-SAS-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 282 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003731/ScoringFiles/PGS003731.txt.gz |
| PGS003732 (PS_T2D_287-HIS-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003732/ScoringFiles/PGS003732.txt.gz |
| PGS003733 (PS_T2D_287-EUR-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 287 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003733/ScoringFiles/PGS003733.txt.gz |
| PGS003734 (PS_T2D_280-EAS-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 280 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003734/ScoringFiles/PGS003734.txt.gz |
| PGS003735 (PS_T2D_276-AFR-DIAMANTE) |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 276 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003735/ScoringFiles/PGS003735.txt.gz |
| PGS003749 (ModelT1D_under25) |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 6,612 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003749/ScoringFiles/PGS003749.txt.gz | |
| PGS003750 (ModelT1D) |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Type 1 diabetes (T1D) | type 1 diabetes mellitus | 7,835 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003750/ScoringFiles/PGS003750.txt.gz | |
| PGS003751 (ModelT2D_over45) |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 354 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003751/ScoringFiles/PGS003751.txt.gz | |
| PGS003752 (ModelT2D) |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 333 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003752/ScoringFiles/PGS003752.txt.gz | |
| PGS003867 (T2D_PRScs_ARB) |
PGP000501 | Shim I et al. Nature Communications (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,068,166 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003867/ScoringFiles/PGS003867.txt.gz |
| PGS003959 (GRS940_obesity) |
PGP000507 | Liu X et al. Clin Nutr (2023) |
Obesity | obesity | 940 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003959/ScoringFiles/PGS003959.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 | |
| 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 |
| 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 | |
| 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 | |
| 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 |
| 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 | |
| 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 | |
| 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 |
| 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 | |
| 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 | |
| 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 |
| 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 | |
| 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 | |
| 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 |
| 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 | |
| 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 |
| 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 | |
| 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 | |
| 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 | |
| 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 | |
| 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 |
| 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 | |
| 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 | |
| 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 | |
| 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 |
| 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 | |
| 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 | |
| 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 |
| 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 | |
| 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 | |
| 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 |
| 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 | |
| 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 | |
| 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 | |
| PGS004171 (t1d_1) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 1 diabetes | type 1 diabetes mellitus | 520 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004171/ScoringFiles/PGS004171.txt.gz |
| PGS004172 (t1d_2) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 1 diabetes | type 1 diabetes mellitus | 70 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004172/ScoringFiles/PGS004172.txt.gz |
| PGS004173 (t1d_3) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 1 diabetes | type 1 diabetes mellitus | 295 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004173/ScoringFiles/PGS004173.txt.gz |
| PGS004174 (t1d_4) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 1 diabetes | type 1 diabetes mellitus | 49 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004174/ScoringFiles/PGS004174.txt.gz |
| PGS004175 (t1d_5) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 1 diabetes | type 1 diabetes mellitus | 315 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004175/ScoringFiles/PGS004175.txt.gz |
| PGS004181 (t2d_1) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 10,202 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004181/ScoringFiles/PGS004181.txt.gz |
| PGS004182 (t2d_2) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 10,778 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004182/ScoringFiles/PGS004182.txt.gz |
| PGS004183 (t2d_3) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 8,154 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004183/ScoringFiles/PGS004183.txt.gz |
| PGS004184 (t2d_4) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 9,645 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004184/ScoringFiles/PGS004184.txt.gz |
| PGS004185 (t2d_5) |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 3,277 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004185/ScoringFiles/PGS004185.txt.gz |
| PGS004222 (GRS13_gout) |
PGP000522 | Wu Q et al. J Psychosom Res (2023) |
Gout | gout | 13 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004222/ScoringFiles/PGS004222.txt.gz |
| PGS004223 (PRS139_T2D) |
PGP000523 | Lin J et al. Sci Total Environ (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 139 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004223/ScoringFiles/PGS004223.txt.gz |
| PGS004225 (PRS46_T2DEastAsia) |
PGP000526 | Liu J et al. Nutrients (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 46 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004225/ScoringFiles/PGS004225.txt.gz |
| PGS004226 (PRS50_T2DEur) |
PGP000526 | Liu J et al. Nutrients (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 50 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004226/ScoringFiles/PGS004226.txt.gz |
| PGS004323 (PRS91_T2D) |
PGP000557 | Tan Q et al. J Hazard Mater (2023) |
Type 2 diabetes | type 2 diabetes mellitus | 91 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004323/ScoringFiles/PGS004323.txt.gz |
| PGS004447 (disease.E66.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
E66 (Obesity) | obesity | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004447/ScoringFiles/PGS004447.txt.gz |
| PGS004448 (disease.E78.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
E78 (Disorders of lipoprotein metabolism and other lipidaemias) | metabolic disease | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004448/ScoringFiles/PGS004448.txt.gz |
| PGS004499 (disease.T2D.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004499/ScoringFiles/PGS004499.txt.gz |
| PGS004517 (meta.E66.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
E66 (Obesity) | obesity | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004517/ScoringFiles/PGS004517.txt.gz |
| PGS004518 (meta.E78.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
E78 (Disorders of lipoprotein metabolism and other lipidaemias) | metabolic disease | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004518/ScoringFiles/PGS004518.txt.gz |
| PGS004569 (meta.T2D.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004569/ScoringFiles/PGS004569.txt.gz |
| PGS004602 (PRS424_T2D) |
PGP000580 | Zhuang P et al. Diabetes Care (2021) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 424 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004602/ScoringFiles/PGS004602.txt.gz |
| PGS004767 (gout_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Gout | gout | 908,271 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004767/ScoringFiles/PGS004767.txt.gz |
| PGS004768 (gout_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Gout | gout | 1,580,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004768/ScoringFiles/PGS004768.txt.gz |
| PGS004837 (t2d_PRSmix_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 3,306,136 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004837/ScoringFiles/PGS004837.txt.gz |
| PGS004838 (t2d_PRSmix_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,586,458 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004838/ScoringFiles/PGS004838.txt.gz |
| PGS004839 (t2d_PRSmixPlus_eur) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 4,594,694 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004839/ScoringFiles/PGS004839.txt.gz |
| PGS004840 (t2d_PRSmixPlus_sas) |
PGP000604 | Truong B et al. Cell Genom (2024) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,586,458 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004840/ScoringFiles/PGS004840.txt.gz |
| PGS004859 (T2D_PRS_CS) |
PGP000605 | Deutsch AJ et al. Diabetes Care (2023) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 1,108,235 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004859/ScoringFiles/PGS004859.txt.gz |
| PGS004868 (T2DPGS) |
PGP000617 | Yun JS et al. Cardiovasc Diabetol (2022) |
Type 2 diabetes (T2D) | type 2 diabetes mellitus | 6,580,804 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004868/ScoringFiles/PGS004868.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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM000023 | PGS000014 (GPS_T2D) |
PSS000017| European Ancestry| 288,978 individuals |
PGP000006 | Khera AV et al. Nat Genet (2018) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.73 [0.72, 0.73] | Nagelkerke’s R2 (estimate of variance explained by the PGS after covariate adjustment): 0.029 | age; sex; Ancestry PC 1-4; genotyping chip | — |
| PPM002477 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes | — | C-index: 0.709 [0.696, 0.722] | Hazard ratio (HR, top 10% vs. remaining 90%): 2.0 [1.73, 2.31] | Sex, age, principal components, assessment center | — |
| PPM002478 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in males | — | C-index: 0.68 [0.663, 0.697] | — | Age, principal components and assessment center | — |
| PPM002479 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in females | — | C-index: 0.705 [0.682, 0.728] | — | Age, principal components and assessment center | — |
| PPM002480 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes | — | C-index: 0.776 [0.764, 0.788] | — | Sex, age, principal components, assessment center, polyexposure score | — |
| PPM002481 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes | — | C-index: 0.844 [0.834, 0.854] | — | Sex, age, principal components, assessment center, clinical risk score | — |
| PPM002482 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes | — | C-index: 0.855 [0.845, 0.865] | — | Sex, age, principal components, assessment center, polyexposure socre, clinical risk score | — |
| PPM002483 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in females | — | C-index: 0.786 [0.765, 0.807] | — | Age, principal components, assessment center, polyexposure score | — |
| PPM002485 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in females | — | C-index: 0.859 [0.842, 0.876] | — | Sex, age, principal components, assessment center, clinical risk score | — |
| PPM002486 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in males | — | C-index: 0.749 [0.734, 0.764] | — | Age, principal components, assessment center, polyexposure score | — |
| PPM002487 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in males | — | C-index: 0.821 [0.808, 0.834] | — | Age, principal components, assessment center, polyexposure socre, clinical risk score | — |
| PPM002488 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in males | — | C-index: 0.834 [0.821, 0.847] | — | Sex, age, principal components, assessment center, clinical risk score | — |
| PPM002484 | PGS000014 (GPS_T2D) |
PSS001117| European Ancestry| 68,229 individuals |
PGP000218 | He Y et al. Diabetes Care (2021) |Ext. |
Reported Trait: Incident type II diabetes in females | — | C-index: 0.869 [0.853, 0.885] | — | Age, principal components, assessment center, polyexposure socre, clinical risk score | — |
| PPM015522 | PGS000014 (GPS_T2D) |
PSS009971| Multi-ancestry (including European)| 36,422 individuals |
PGP000381 | Hao L et al. Nat Med (2022) |Ext. |
Reported Trait: Type 2 diabetes mellitus | OR: 1.75 [1.57, 1.95] | — | — | 4 genetic PCs | — |
| PPM019100 | PGS000014 (GPS_T2D) |
PSS011181| Ancestry Not Reported| 3,071 individuals |
PGP000504 | Duschek E et al. Sci Rep (2023) |Ext. |
Reported Trait: Incident type 2 diabetes | — | AUROC: 0.613 [0.565, 0.657] | — | — | — |
| PPM019098 | PGS000014 (GPS_T2D) |
PSS011181| Ancestry Not Reported| 3,071 individuals |
PGP000504 | Duschek E et al. Sci Rep (2023) |Ext. |
Reported Trait: Incident type 2 diabetes | OR: 1.67 [1.37, 2.03] | — | — | Age, Sex, BMI, Physical activity, FamRS | — |
| PPM019099 | PGS000014 (GPS_T2D) |
PSS011181| Ancestry Not Reported| 3,071 individuals |
PGP000504 | Duschek E et al. Sci Rep (2023) |Ext. |
Reported Trait: Prevelant type 2 diabetes | — | AUROC: 0.869 [0.842, 0.896] | — | — | — |
| PPM019097 | PGS000014 (GPS_T2D) |
PSS011181| Ancestry Not Reported| 3,071 individuals |
PGP000504 | Duschek E et al. Sci Rep (2023) |Ext. |
Reported Trait: Prevelant type 2 diabetes | OR: 6.21 [5.06, 7.74] | — | — | Age, Sex, BMI, Physical activity, FamRS | — |
| PPM000040 | PGS000020 (dGRS1000) |
PSS000025| European Ancestry| 6,280 individuals |
PGP000010 | Läll K et al. Genet Med (2016) |
Reported Trait: Incident type 2 diabetes | HR: 1.48 [1.32, 1.66] | C-index: 0.79 [0.771, 0.812] | — | BMI category, smoking level, waist-to-hip ratio, waist circumference, physical activity level, history of high blood glucose, fruit and vegetable consumption, and sex. | Cox age-as-time-scale |
| PPM000132 | PGS000021 (GRS1) |
PSS000083| European Ancestry| 2,768 individuals |
PGP000038 | Patel KA et al. Diabetes (2016) |Ext. |
Reported Trait: Type 1 diabetes aetiology (non-monogenic) | — | AUROC: 0.87 [0.86, 0.89] | — | — | Testing the ability of the GRS to discriminate between two sets of cases: - Positive: individuals with type 1 diabetes - Negative: individuals with diabetes and a maturity-onset diabetes of young (MODY) mutation |
| PPM000041 | PGS000021 (GRS1) |
PSS000026| European Ancestry| 223 individuals |
PGP000011 | Oram RA et al. Diabetes Care (2015) |
Reported Trait: Severe insulin deficiency | — | AUROC: 0.96 [0.94, 0.99] | AUROC (without covariates): 0.87 | islet auto-antibody status, body mass index (BMI), age at diagnosis | — |
| PPM000046 | PGS000021 (GRS1) |
PSS000030| African Ancestry| 3,949 individuals |
PGP000013 | Onengut-Gumuscu S et al. Diabetes Care (2019) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.798 | — | — | — |
| PPM000049 | PGS000021 (GRS1) |
PSS000032| European Ancestry| 374,000 individuals |
PGP000014 | Sharp SA et al. Diabetes Care (2019) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.893 | — | — | — |
| PPM000042 | PGS000022 (T1D_GRS) |
PSS000029| European Ancestry| 1,447 individuals |
PGP000012 | Perry DJ et al. Sci Rep (2018) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.8508 | — | — | AUROCs are reported with respect to unrelated-control samples |
| PPM000043 | PGS000022 (T1D_GRS) |
PSS000028| Hispanic or Latin American Ancestry| 252 individuals |
PGP000012 | Perry DJ et al. Sci Rep (2018) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.9003 | — | — | AUROCs are reported with respect to unrelated-control samples |
| PPM000044 | PGS000022 (T1D_GRS) |
PSS000027| African Ancestry| 299 individuals |
PGP000012 | Perry DJ et al. Sci Rep (2018) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.7522 | — | — | AUROCs are reported with respect to unrelated-control samples |
| PPM000045 | PGS000023 (AA_GRS) |
PSS000030| African Ancestry| 3,949 individuals |
PGP000013 | Onengut-Gumuscu S et al. Diabetes Care (2019) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.87 | — | — | NOTE: Evaluated using cross-validation on training samples (20% heldout, 1000 iterations) |
| PPM000047 | PGS000023 (AA_GRS) |
PSS000031| African Ancestry| 145 individuals |
PGP000013 | Onengut-Gumuscu S et al. Diabetes Care (2019) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.779 | — | — | — |
| PPM018536 | PGS000023 (AA_GRS) |
PSS011012| Multi-ancestry (including European)| 39,820 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.781 | — | — | — |
| PPM018537 | PGS000023 (AA_GRS) |
PSS011009| Multi-ancestry (including European)| 57,643 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.817 | — | — | — |
| PPM018539 | PGS000023 (AA_GRS) |
PSS011011| European Ancestry| 16,663 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 97.0 % PPV (reference): 86.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM018541 | PGS000023 (AA_GRS) |
PSS011010| Multi-ancestry (excluding European)| 40,980 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 86.0 % PPV (reference): 71.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM018543 | PGS000023 (AA_GRS) |
PSS011013| Multi-ancestry (excluding European)| 4,881 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 83.0 % PPV (reference): 53.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM000048 | PGS000024 (GRS2) |
PSS000032| European Ancestry| 374,000 individuals |
PGP000014 | Sharp SA et al. Diabetes Care (2019) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.921 | Youden index: 0.698 | — | — |
| PPM000753 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (5 years horizon time; landmark age 2 years) | — | AUROC: 0.93 | — | autoantibodies, family history | — |
| PPM000754 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (8 years horizon time; landmark age 2 years) | — | AUROC: 0.87 | — | autoantibodies, family history | — |
| PPM000755 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (5 years horizon time; landmark age 4 years) | — | AUROC: 0.96 | — | autoantibodies, family history | — |
| PPM000751 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (1 year horizon time; landmark age 2 years) | — | AUROC: 0.96 | — | autoantibodies, family history | — |
| PPM000752 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (3 years horizon time; landmark age 2 years) | — | AUROC: 0.94 | — | autoantibodies, family history | — |
| PPM000750 | PGS000024 (GRS2) |
PSS000368| Ancestry Not Reported| 7,798 individuals |
PGP000091 | Ferrat LA et al. Nat Med (2020) |Ext. |
Reported Trait: Type 1 diabetes (by age 8; landmark age 2 years) | — | AUROC: 0.73 [0.7, 0.77] | — | — | — |
| PPM002249 | PGS000024 (GRS2) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |Ext. |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.0 [0.93, 1.07] | — | — | PC1-10 | 8 proxy variants were used to evaluate this score |
| PPM002250 | PGS000024 (GRS2) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |Ext. |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.0 [0.93, 1.07] | — | — | PC1-10 | 8 proxy variants were used to evaluate this score |
| PPM002251 | PGS000024 (GRS2) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |Ext. |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.01 [0.95, 1.08] | — | — | PC1-10 | 8 proxy variants were used to evaluate this score |
| PPM002252 | PGS000024 (GRS2) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |Ext. |
Reported Trait: Moderate Age-Related Diabetes | OR: 0.99 [0.94, 1.04] | — | — | PC1-10 | 8 proxy variants were used to evaluate this score |
| PPM002248 | PGS000024 (GRS2) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |Ext. |
Reported Trait: Severe Autoimmune Diabetes | OR: 2.55 [2.28, 2.86] | — | — | PC1-10 | 8 proxy variants were used to evaluate this score |
| PPM014801 | PGS000024 (GRS2) |
PSS009895| European Ancestry| 1,168 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.864 [0.823, 0.905] | — | — | — |
| PPM014803 | PGS000024 (GRS2) |
PSS009893| African Ancestry| 366 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.851 [0.805, 0.897] | — | — | — |
| PPM014805 | PGS000024 (GRS2) |
PSS009894| Hispanic or Latin American Ancestry| 412 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.935 [0.906, 0.964] | — | — | — |
| PPM014807 | PGS000024 (GRS2) |
PSS009896| Ancestry Not Reported| 99 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.79 [0.679, 0.902] | — | — | — |
| PPM018532 | PGS000024 (GRS2) |
PSS011012| Multi-ancestry (including European)| 39,820 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.875 | — | — | — |
| PPM018533 | PGS000024 (GRS2) |
PSS011009| Multi-ancestry (including European)| 57,643 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.822 | — | — | — |
| PPM018534 | PGS000024 (GRS2) |
PSS011014| European Ancestry| 34,939 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.888 | — | — | — |
| PPM018535 | PGS000024 (GRS2) |
PSS011014| European Ancestry| 34,939 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | AUROC: 0.858 | — | — | — |
| PPM018538 | PGS000024 (GRS2) |
PSS011011| European Ancestry| 16,663 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 100.0 % PPV (reference): 86.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM018540 | PGS000024 (GRS2) |
PSS011010| Multi-ancestry (excluding European)| 40,980 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 93.0 % PPV (reference): 71.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM018542 | PGS000024 (GRS2) |
PSS011014| European Ancestry| 34,939 individuals |
PGP000477 | Deutsch AJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes | — | — | PPV (+PRS): 97.0 % PPV (reference): 71.0 % |
eMERGE type 1 diabetes algorithm | — |
| PPM020098 | PGS000024 (GRS2) |
PSS011295| Ancestry Not Reported| 1,798 individuals |
PGP000519 | Thomas NJ et al. Diabetes Care (2023) |Ext. |
Reported Trait: Type 1 diabetes vs autoantibody negative T2D | — | — | p-value (inferior to): 0.0001 | — | — |
| PPM021124 | PGS000024 (GRS2) |
PSS011531| European Ancestry| 9,465 individuals |
PGP000614 | Qu HQ et al. Diabetes Obes Metab (2021) |Ext. |
Reported Trait: Type 1 diabetes | β: -0.22 | AUROC: 0.87 | — | — | — |
| PPM021125 | PGS000024 (GRS2) |
PSS011532| European Ancestry| 9,450 individuals |
PGP000614 | Qu HQ et al. Diabetes Obes Metab (2021) |Ext. |
Reported Trait: Type 1 diabetes | β: -0.234 | AUROC: 0.862 | — | — | — |
| PPM000062 | PGS000031 (GRSt) |
PSS000044| European Ancestry| 3,471 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.06 [1.04, 1.08] | C-index: 0.906 [0.892, 0.92] | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000063 | PGS000031 (GRSt) |
PSS000043| European Ancestry| 1,650 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.06 [1.02, 1.1] | C-index: 0.853 [0.81, 0.896] | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000064 | PGS000031 (GRSt) |
PSS000042| African Ancestry| 820 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.05 [1.0, 1.09] | C-index: 0.771 [0.727, 0.814] | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model", SNPs were not weighted by their effect size as the betas were measure in Europeans |
| PPM000065 | PGS000032 (GRSB) |
PSS000044| European Ancestry| 3,471 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.1 [1.06, 1.14] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000066 | PGS000032 (GRSB) |
PSS000043| European Ancestry| 1,650 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.09 [1.02, 1.17] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000067 | PGS000032 (GRSB) |
PSS000042| African Ancestry| 820 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.06 [0.99, 1.15] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model", SNPs were not weighted by their effect size as the betas were measure in Europeans |
| PPM002415 | PGS000032 (GRSB) |
PSS001092| Ancestry Not Reported| 5,740 individuals |
PGP000214 | Aksit MA et al. J Clin Endocrinol Metab (2020) |Ext. |
Reported Trait: Cystic-fibrosis related diabetes onset | HR: 1.192 | — | — | PCs(1-4), site of recruitment | — |
| PPM000068 | PGS000033 (GRSIR) |
PSS000044| European Ancestry| 3,471 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 0.98 [0.93, 1.04] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000069 | PGS000033 (GRSIR) |
PSS000043| European Ancestry| 1,650 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.01 [0.91, 1.12] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model" |
| PPM000070 | PGS000033 (GRSIR) |
PSS000042| African Ancestry| 820 individuals |
PGP000020 | Vassy JL et al. Diabetes (2014) |
Reported Trait: Incident type 2 diabetes cases | HR: 1.06 [0.99, 1.15] | — | — | age, sex, family history (parents), body mass index, systolic blood pressure, fasting glucose, log-HDL cholesterol, log-triglyceride levels | Results from the "Clinical model", SNPs were not weighted by their effect size as the betas were measure in Europeans |
| PPM000080 | PGS000036 (gePS_T2D) |
PSS000054| European Ancestry| 324,870 individuals |
PGP000024 | Udler MS et al. Endocr Rev (2019) |Ext. |
Reported Trait: Type 2 diabetes | — | AUROC: 0.66 | — | genotyping array, first 6 PCs of ancestry | — |
| PPM000081 | PGS000036 (gePS_T2D) |
PSS000054| European Ancestry| 324,870 individuals |
PGP000024 | Udler MS et al. Endocr Rev (2019) |Ext. |
Reported Trait: Type 2 diabetes | — | AUROC: 0.73 | — | age, sex, genotyping array, first 6 PCs of ancestry | — |
| PPM014802 | PGS000036 (gePS_T2D) |
PSS009895| European Ancestry| 1,168 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.661 [0.606, 0.716] | — | — | — |
| PPM014804 | PGS000036 (gePS_T2D) |
PSS009893| African Ancestry| 366 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.574 [0.506, 0.643] | — | — | — |
| PPM014806 | PGS000036 (gePS_T2D) |
PSS009894| Hispanic or Latin American Ancestry| 412 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.722 [0.667, 0.778] | — | — | — |
| PPM014808 | PGS000036 (gePS_T2D) |
PSS009896| Ancestry Not Reported| 99 individuals |
PGP000338 | Oram RA et al. Diabetes Care (2022) |Ext. |
Reported Trait: Diabetes autoantibody positive insulin sensitive | — | AUROC: 0.677 [0.532, 0.822] | — | — | — |
| PPM000404 | PGS000125 (Qi_T2D_2017) |
PSS000232| Hispanic or Latin American Ancestry| 7,746 individuals |
PGP000062 | Qi Q et al. Diabetes (2017) |
Reported Trait: Type 2 Diabetes | — | — | OR (Odds Ratio, per risk allele): 1.07 [1.06, 1.08] | center, age, sex, 5 PCs of ancestry | Covariance matrices corresponding to genetic relatedness (kinship), household, and census block group were included as random effects in the mixed model analysis |
| PPM000582 | PGS000199 (G-PROB_Gout) |
PSS000311| European Ancestry| 243 individuals |
PGP000081 | Knevel R et al. Sci Transl Med (2020) |
Reported Trait: Gout diagnosis in patient with arthritis | — | AUROC: 0.85 [0.8, 0.91] | — | — | (Setting III: Selecting patients presenting with inflammatory arthritis at their first visit) |
| PPM000576 | PGS000199 (G-PROB_Gout) |
PSS000310| European Ancestry| 245 individuals |
PGP000081 | Knevel R et al. Sci Transl Med (2020) |
Reported Trait: Gout diagnosis in patient with arthritis | — | AUROC: 0.82 [0.73, 0.94] | — | — | (Setting II: Assigning patient diagnoses based on medical records) |
| PPM000570 | PGS000199 (G-PROB_Gout) |
PSS000320| Multi-ancestry (including European)| 1,211 individuals |
PGP000081 | Knevel R et al. Sci Transl Med (2020) |
Reported Trait: Gout diagnosis in patient with arthritis | — | AUROC: 0.78 [0.75, 0.8] | — | — | (Setting I: Assigning patient diagnoses based on billing codes) |
| PPM000897 | PGS000330 (PRS_T2D) |
PSS000441| European Ancestry| 21,030 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Incident type 2 diabetes | — | C-index: 0.845 | — | age, sex, BMI, history of stroke or CHD, parental history of diabetes, SBP, DBP, HDL, triglycerides, FINRISK cohort, genotyping array/batch, 10 ancestry PCs | 10-year risk |
| PPM000892 | PGS000330 (PRS_T2D) |
PSS000441| European Ancestry| 21,030 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Incident type 2 diabetes | HR: 1.7 [1.63, 1.78] | C-index: 0.763 | — | age, sex, FINRISK cohort, genotyping array/batch, 10 ancestry PCs | 10-year risk |
| PPM000887 | PGS000330 (PRS_T2D) |
PSS000448| European Ancestry| 135,300 individuals |
PGP000100 | Mars N et al. Nat Med (2020) |
Reported Trait: Type 2 diabetes (incident and prevalent cases) | HR: 1.74 [1.72, 1.77] | — | — | genotyping array/batch, 10 ancestry PCs, stratified by sex | — |
| PPM001603 | PGS000711 (HC328) |
PSS000815| European Ancestry| 87,413 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Gout | — | AUROC: 0.7107 | — | Age, sex, PCs(1-10) | — |
| PPM001616 | PGS000711 (HC328) |
PSS000816| European Ancestry| 135,300 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Gout | HR: 1.58 [1.51, 1.65] | C-index: 0.673 | — | Age as time scale, sex, batch, PCs(1-10) | — |
| PPM001604 | PGS000712 (T2D_HbA1c_39) |
PSS000755| European Ancestry| 87,413 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.68713 | — | Age, sex, PCs(1-10) | — |
| PPM001605 | PGS000713 (T2D) |
PSS000754| European Ancestry| 87,413 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.688 | — | Age, sex, PCs(1-10) | — |
| PPM001615 | PGS000713 (T2D) |
PSS000756| European Ancestry| 135,300 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Type 2 diabetes | HR: 1.49 [1.47, 1.51] | C-index: 0.669 | — | Age as time scale, sex, batch, PCs(1-10) | — |
| PPM001667 | PGS000729 (T2D_PGS) |
PSS000869| European Ancestry| 3,087 individuals |
PGP000137 | Ritchie SC et al. Nat Metab (2021) |
Reported Trait: Incident type 2 diabetes | HR: 2.0 [1.36, 2.94] | — | — | age, sex, 10 genetic PCs | — |
| PPM002117 | PGS000804 (GRS582_T2Dmulti) |
PSS001044| African Ancestry| 15,609 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.568 [0.5588, 0.5772] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002119 | PGS000804 (GRS582_T2Dmulti) |
PSS001046| European Ancestry| 423,729 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.825 [0.8222, 0.8279] | Odds Ratio (OR, top 10% vs middle 20%): 2.94 [2.8, 3.08] | Age, sex, body mass index, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002121 | PGS000804 (GRS582_T2Dmulti) |
PSS001046| European Ancestry| 423,729 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6586 [0.6547, 0.6624] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002123 | PGS000804 (GRS582_T2Dmulti) |
PSS001047| Hispanic or Latin American Ancestry| 20,486 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.7293 [0.721, 0.7376] | Odds Ratio (OR, top 10% vs middle 20%): 2.39 [2.1, 2.73] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002125 | PGS000804 (GRS582_T2Dmulti) |
PSS001047| Hispanic or Latin American Ancestry| 20,486 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6249 [0.6156, 0.6342] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002127 | PGS000804 (GRS582_T2Dmulti) |
PSS001045| Additional Asian Ancestries| 4,576 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.8411 [0.8298, 0.8523] | Odds Ratio (OR, top 10% vs middle 20%): 3.08 [2.4, 3.95] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002129 | PGS000804 (GRS582_T2Dmulti) |
PSS001045| Additional Asian Ancestries| 4,576 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6263 [0.6101, 0.6425] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002131 | PGS000804 (GRS582_T2Dmulti) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.7989 [0.7845, 0.8133] | Odds Ratio (OR, top 10% vs middle 20%): 2.02 [1.54, 2.65] | Age, sex, body mass index, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002133 | PGS000804 (GRS582_T2Dmulti) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6214 [0.603, 0.6399] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002115 | PGS000804 (GRS582_T2Dmulti) |
PSS001044| African Ancestry| 15,609 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6701 [0.6615, 0.6788] | Odds Ratio (OR, top 10% vs middle 20%): 1.57 [1.39, 1.77] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002120 | PGS000805 (GRS582_T2Deur) |
PSS001046| European Ancestry| 423,729 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.8253 [0.8224, 0.8281] | Odds Ratio (OR, top 10% vs middle 20%): 2.95 [2.81, 3.1] | Age, sex, body mass index, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002122 | PGS000805 (GRS582_T2Deur) |
PSS001046| European Ancestry| 423,729 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6593 [0.6555, 0.6632] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002134 | PGS000805 (GRS582_T2Deur) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6213 [0.6029, 0.6397] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. Population-specific weights were not available for indiviuals of an Oceanian ancestry (Native Hawaiian). Therefore, GRS582_T2Deur was utilised to predict type 2 diabetes in individuals of an Oceanian ancestry. |
| PPM002132 | PGS000805 (GRS582_T2Deur) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.7985 [0.7842, 0.8129] | Odds Ratio (OR, top 10% vs middle 20%): 2.13 [1.63, 2.79] | Age, sex, body mass index, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. Population-specific weights were not available for indiviuals of an Oceanian ancestry (Native Hawaiian). Therefore, GRS582_T2Deur was utilised to predict type 2 diabetes in individuals of an Oceanian ancestry. |
| PPM002116 | PGS000806 (GRS582_T2Dafr) |
PSS001044| African Ancestry| 15,609 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6656 [0.6569, 0.6743] | Odds Ratio (OR, top 10% vs middle 20%): 1.53 [1.36, 1.73] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002118 | PGS000806 (GRS582_T2Dafr) |
PSS001044| African Ancestry| 15,609 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.5592 [0.5499, 0.5684] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002128 | PGS000807 (GRS582_T2Dasn) |
PSS001045| Additional Asian Ancestries| 4,576 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.8388 [0.8274, 0.8502] | Odds Ratio (OR, top 10% vs middle 20%): 2.84 [2.21, 3.65] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002130 | PGS000807 (GRS582_T2Dasn) |
PSS001045| Additional Asian Ancestries| 4,576 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6161 [0.5998, 0.6324] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002135 | PGS000807 (GRS582_T2Dasn) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.7909 [0.7763, 0.8056] | Odds Ratio (OR, top 10% vs middle 20%): 1.62 [1.23, 2.14] | Age, sex, body mass index, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. Population-specific weights were not available for indiviuals of an Oceanian ancestry (Native Hawaiian). Therefore, GRS582_T2Dasn was utilised to predict type 2 diabetes in individuals of an Oceanian ancestry. |
| PPM002136 | PGS000807 (GRS582_T2Dasn) |
PSS001048| Additional Diverse Ancestries| 3,551 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.5768 [0.558, 0.5956] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. Population-specific weights were not available for indiviuals of an Oceanian ancestry (Native Hawaiian). Therefore, GRS582_T2Dasn was utilised to predict type 2 diabetes in individuals of an Oceanian ancestry. |
| PPM002124 | PGS000808 (GRS582_T2Dhis) |
PSS001047| Hispanic or Latin American Ancestry| 20,486 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.7202 [0.7118, 0.7286] | Odds Ratio (OR, top 10% vs middle 20%): 2.04 [1.79, 2.32] | Age, sex, body mass index, study, PCs(1-10) | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002126 | PGS000808 (GRS582_T2Dhis) |
PSS001047| Hispanic or Latin American Ancestry| 20,486 individuals |
PGP000193 | Polfus LM et al. HGG Adv (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6098 [0.6004, 0.6192] | — | — | Only 579 SNPs from the 582 SNP GRS, were utilised with imputation INFO scores > 0.45. 3 SNPs were not included as they were not present in the cohorts. |
| PPM002190 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Retinal hemorrhage in inidividuals with type 2 diabetes | OR: 1.44 [1.03, 2.02] | — | — | — | — |
| PPM002185 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.12 [1.04, 1.2] | — | — | — | — |
| PPM002186 | PGS000819 (PRS_DR) |
PSS001066| European Ancestry| 978 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.22 [1.02, 1.41] | — | — | — | — |
| PPM002187 | PGS000819 (PRS_DR) |
PSS001065| African Ancestry| 1,925 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.15 [1.03, 1.28] | — | — | — | — |
| PPM002188 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | — | — | Odds Ratio (OR, top 10% vs bottom 10%): 1.8 [1.28, 2.55] | Age, sex, body mass index, PCs(1-20), history of hypertension, glucose levels | — |
| PPM002189 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diabetic retinopathy in individuals with type 2 diabetes | OR: 1.14 [1.05, 1.23] | — | — | PCs(1-20), type 2 diabetes duration, type 2 diabetes medication, hyperglycemia, elevated HbA1c, hypertension, hypercholesterolemia, hyperlipidemia, insomina, sleep apnea, age, sex, body mass index | — |
| PPM002191 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Diplopia in individuals with type 2 diabetes | OR: 1.31 [1.02, 1.7] | — | — | — | — |
| PPM002192 | PGS000819 (PRS_DR) |
PSS001067| Multi-ancestry (including European)| 6,079 individuals |
PGP000203 | Forrest IS et al. Hum Mol Genet (2021) |
Reported Trait: Time to diabetic retinopathy diagnosis in individuals with type 2 diabetes | HR: 1.13 [1.05, 1.21] | — | — | Age, sex, body mass index, PCs(1-20), history of hypertension, glucose levels | — |
| PPM002240 | PGS000832 (T2D-GRS) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.24 [1.16, 1.34] | — | — | PC1-10 | — |
| PPM002242 | PGS000832 (T2D-GRS) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.77 [1.67, 1.88] | — | — | PC1-10 | — |
| PPM002239 | PGS000832 (T2D-GRS) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.96 [1.81, 2.12] | — | — | PC1-10 | — |
| PPM002238 | PGS000832 (T2D-GRS) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.28 [1.16, 1.42] | — | — | PC1-10 | — |
| PPM002241 | PGS000832 (T2D-GRS) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.73 [1.61, 1.86] | — | — | PC1-10 | — |
| PPM020163 | PGS000832 (T2D-GRS) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.78 [1.49, 2.13] | — | — | age, sex and BMI | Evaluated on 381 of 384 SNPs based on the availability of variants in the cohort |
| PPM020196 | PGS000832 (T2D-GRS) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.5 [1.27, 1.76] | — | — | sex | Evaluated on 381 of 384 SNPs based on the availability of variants in the cohort |
| PPM020207 | PGS000832 (T2D-GRS) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.54 [1.27, 1.87] | — | — | sex | Evaluated on 381 of 384 SNPs based on the availability of variants in the cohort |
| PPM020184 | PGS000832 (T2D-GRS) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.66 [1.42, 1.93] | — | — | sex | Evaluated on 381 of 384 SNPs based on the availability of variants in the cohort |
| PPM002243 | PGS000833 (T1D) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.39 [1.25, 1.54] | — | — | PC1-10 | — |
| PPM002246 | PGS000833 (T1D) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.04 [0.97, 1.11] | — | — | PC1-10 | — |
| PPM002247 | PGS000833 (T1D) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.02 [0.97, 1.07] | — | — | PC1-10 | — |
| PPM002244 | PGS000833 (T1D) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.01 [0.94, 1.08] | — | — | PC1-10 | — |
| PPM002245 | PGS000833 (T1D) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.03 [0.96, 1.11] | — | — | PC1-10 | — |
| PPM002323 | PGS000848 (T2D_Adiposity) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.11 [1.0, 1.23] | — | — | PC1-10 | — |
| PPM002324 | PGS000848 (T2D_Adiposity) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.1 [1.02, 1.18] | — | — | PC1-10 | — |
| PPM002325 | PGS000848 (T2D_Adiposity) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.11 [1.03, 1.19] | — | — | PC1-10 | — |
| PPM002326 | PGS000848 (T2D_Adiposity) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.2 [1.12, 1.28] | — | — | PC1-10 | — |
| PPM002327 | PGS000848 (T2D_Adiposity) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.06 [1.0, 1.12] | — | — | PC1-10 | — |
| PPM020167 | PGS000848 (T2D_Adiposity) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.14 [1.01, 1.28] | — | — | sex | — |
| PPM020183 | PGS000848 (T2D_Adiposity) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: BMI | β: 0.06772 (0.027943) | — | — | — | — |
| PPM020187 | PGS000848 (T2D_Adiposity) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.23 [1.07, 1.43] | — | — | sex | — |
| PPM002329 | PGS000849 (T2D_Impaired_Lipids) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.07 [1.0, 1.15] | — | — | PC1-10 | — |
| PPM002330 | PGS000849 (T2D_Impaired_Lipids) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.09 [1.01, 1.17] | — | — | PC1-10 | — |
| PPM002331 | PGS000849 (T2D_Impaired_Lipids) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.0 [0.93, 1.07] | — | — | PC1-10 | — |
| PPM002332 | PGS000849 (T2D_Impaired_Lipids) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.06 [1.0, 1.12] | — | — | PC1-10 | — |
| PPM002328 | PGS000849 (T2D_Impaired_Lipids) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.08 [0.97, 1.2] | — | — | PC1-10 | — |
| PPM020176 | PGS000849 (T2D_Impaired_Lipids) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.2 [1.0, 1.44] | — | — | age, sex and BMI | — |
| PPM020194 | PGS000849 (T2D_Impaired_Lipids) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.2 [1.03, 1.4] | — | — | sex | — |
| PPM020204 | PGS000849 (T2D_Impaired_Lipids) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.26 [1.07, 1.49] | — | — | sex | — |
| PPM002333 | PGS000850 (T2D_Insulin_Action) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.08 [0.98, 1.2] | — | — | PC1-10 | — |
| PPM002334 | PGS000850 (T2D_Insulin_Action) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.17 [1.09, 1.25] | — | — | PC1-10 | — |
| PPM002335 | PGS000850 (T2D_Insulin_Action) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.17 [1.09, 1.26] | — | — | PC1-10 | — |
| PPM002337 | PGS000850 (T2D_Insulin_Action) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.16 [1.1, 1.23] | — | — | PC1-10 | — |
| PPM002336 | PGS000850 (T2D_Insulin_Action) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.14 [1.07, 1.22] | — | — | PC1-10 | — |
| PPM020173 | PGS000850 (T2D_Insulin_Action) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.16 [1.03, 1.3] | — | — | sex | — |
| PPM020201 | PGS000850 (T2D_Insulin_Action) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.17 [1.0, 1.36] | — | — | sex | — |
| PPM020213 | PGS000850 (T2D_Insulin_Action) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.26 [1.04, 1.53] | — | — | sex | — |
| PPM002338 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.24 [1.12, 1.37] | — | — | PC1-10 | — |
| PPM002339 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.23 [1.15, 1.32] | — | — | PC1-10 | — |
| PPM002340 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.04 [0.97, 1.11] | — | — | PC1-10 | — |
| PPM002341 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.19 [1.12, 1.28] | — | — | PC1-10 | — |
| PPM002342 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.19 [1.13, 1.26] | — | — | PC1-10 | — |
| PPM020172 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.07 [0.9, 1.28] | — | — | age, sex and BMI | — |
| PPM020192 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.17 [1.01, 1.34] | — | — | sex | — |
| PPM020212 | PGS000851 (T2D_Insulin_Action_Secretion) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.45 [1.19, 1.78] | — | — | sex | — |
| PPM002343 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.01 [0.91, 1.12] | — | — | PC1-10 | — |
| PPM002344 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.31 [1.22, 1.41] | — | — | PC1-10 | — |
| PPM002345 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.04 [0.97, 1.12] | — | — | PC1-10 | — |
| PPM002347 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.29 [1.22, 1.37] | — | — | PC1-10 | — |
| PPM002346 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.26 [1.18, 1.35] | — | — | PC1-10 | — |
| PPM020170 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.33 [1.12, 1.58] | — | — | age, sex and BMI | — |
| PPM020190 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.38 [1.19, 1.59] | — | — | sex | — |
| PPM020199 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.25 [1.08, 1.46] | — | — | sex | — |
| PPM020210 | PGS000852 (T2D_Insulin_Secretion_1) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.33 [1.1, 1.61] | — | — | sex | — |
| PPM002348 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 0.99 [0.9, 1.1] | — | — | PC1-10 | — |
| PPM002349 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.26 [1.18, 1.36] | — | — | PC1-10 | — |
| PPM002350 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.02 [0.95, 1.09] | — | — | PC1-10 | — |
| PPM002351 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.18 [1.11, 1.27] | — | — | PC1-10 | — |
| PPM002352 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.23 [1.17, 1.3] | — | — | PC1-10 | — |
| PPM020171 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.32 [1.11, 1.57] | — | — | age, sex and BMI | — |
| PPM020200 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.24 [1.07, 1.45] | — | — | sex | — |
| PPM020211 | PGS000853 (T2D_Insulin_Secretion_2) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.32 [1.1, 1.59] | — | — | sex | — |
| PPM002353 | PGS000854 (T2D_BetaCell) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.0 [0.91, 1.11] | — | — | PC1-10 | — |
| PPM002354 | PGS000854 (T2D_BetaCell) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.32 [1.23, 1.42] | — | — | PC1-10 | — |
| PPM002355 | PGS000854 (T2D_BetaCell) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.01 [0.94, 1.08] | — | — | PC1-10 | — |
| PPM002357 | PGS000854 (T2D_BetaCell) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.27 [1.2, 1.34] | — | — | PC1-10 | — |
| PPM002356 | PGS000854 (T2D_BetaCell) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.21 [1.13, 1.3] | — | — | PC1-10 | — |
| PPM020168 | PGS000854 (T2D_BetaCell) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 0.89 [0.79, 1.0] | — | — | sex | — |
| PPM020188 | PGS000854 (T2D_BetaCell) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 0.87 [0.75, 1.0] | — | — | sex | — |
| PPM020209 | PGS000854 (T2D_BetaCell) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 0.81 [0.67, 0.97] | — | — | sex | — |
| PPM002358 | PGS000855 (T2D_Lipodystrophy) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.12 [1.01, 1.25] | — | — | PC1-10 | — |
| PPM002359 | PGS000855 (T2D_Lipodystrophy) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.23 [1.15, 1.33] | — | — | PC1-10 | — |
| PPM002360 | PGS000855 (T2D_Lipodystrophy) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.15 [1.07, 1.24] | — | — | PC1-10 | — |
| PPM002361 | PGS000855 (T2D_Lipodystrophy) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.14 [1.06, 1.22] | — | — | PC1-10 | — |
| PPM002362 | PGS000855 (T2D_Lipodystrophy) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.18 [1.11, 1.24] | — | — | PC1-10 | — |
| PPM020175 | PGS000855 (T2D_Lipodystrophy) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.17 [1.04, 1.31] | — | — | sex | — |
| PPM020193 | PGS000855 (T2D_Lipodystrophy) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.16 [1.0, 1.34] | — | — | sex | — |
| PPM020203 | PGS000855 (T2D_Lipodystrophy) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.18 [1.01, 1.37] | — | — | sex | — |
| PPM002363 | PGS000856 (T2D_LiverLipids) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.35 [1.22, 1.51] | — | — | PC1-10 | — |
| PPM002364 | PGS000856 (T2D_LiverLipids) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.01 [0.94, 1.08] | — | — | PC1-10 | — |
| PPM002366 | PGS000856 (T2D_LiverLipids) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.02 [0.95, 1.09] | — | — | PC1-10 | — |
| PPM002367 | PGS000856 (T2D_LiverLipids) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 0.95 [0.9, 1.01] | — | — | PC1-10 | — |
| PPM002365 | PGS000856 (T2D_LiverLipids) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 0.97 [0.91, 1.05] | — | — | PC1-10 | — |
| PPM020177 | PGS000856 (T2D_LiverLipids) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.29 [1.09, 1.54] | — | — | age, sex and BMI | — |
| PPM020195 | PGS000856 (T2D_LiverLipids) |
PSS011302| South Asian Ancestry| 830 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin deficiency diabetes | OR: 1.24 [1.07, 1.43] | — | — | sex | — |
| PPM020205 | PGS000856 (T2D_LiverLipids) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.31 [1.12, 1.53] | — | — | sex | — |
| PPM020206 | PGS000856 (T2D_LiverLipids) |
PSS011304| South Asian Ancestry| 482 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Severe insulin-resistant diabetes | OR: 2.04 [1.26, 3.3] | — | — | sex | — |
| PPM002368 | PGS000857 (T2D_Obesity) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.07 [0.97, 1.19] | — | — | PC1-10 | — |
| PPM002369 | PGS000857 (T2D_Obesity) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.08 [1.01, 1.16] | — | — | PC1-10 | — |
| PPM002370 | PGS000857 (T2D_Obesity) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.13 [1.05, 1.22] | — | — | PC1-10 | — |
| PPM002371 | PGS000857 (T2D_Obesity) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.19 [1.11, 1.27] | — | — | PC1-10 | — |
| PPM002372 | PGS000857 (T2D_Obesity) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.04 [0.99, 1.1] | — | — | PC1-10 | — |
| PPM020164 | PGS000857 (T2D_Obesity) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 0.87 [0.77, 0.99] | — | — | sex | — |
| PPM002373 | PGS000858 (T2D_Proinsulin) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 0.94 [0.85, 1.04] | — | — | PC1-10 | — |
| PPM002374 | PGS000858 (T2D_Proinsulin) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.14 [1.06, 1.22] | — | — | PC1-10 | — |
| PPM002376 | PGS000858 (T2D_Proinsulin) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.06 [0.99, 1.13] | — | — | PC1-10 | — |
| PPM002377 | PGS000858 (T2D_Proinsulin) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.1 [1.04, 1.16] | — | — | PC1-10 | — |
| PPM002375 | PGS000858 (T2D_Proinsulin) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 0.93 [0.87, 1.0] | — | — | PC1-10 | — |
| PPM020174 | PGS000858 (T2D_Proinsulin) |
PSS011301| South Asian Ancestry| 1,282 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Type 2 diabetes | OR: 1.22 [1.03, 1.44] | — | — | age, sex and BMI | — |
| PPM020202 | PGS000858 (T2D_Proinsulin) |
PSS011303| South Asian Ancestry| 729 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild obesity-related diabetes | OR: 1.2 [1.03, 1.4] | — | — | sex | — |
| PPM020214 | PGS000858 (T2D_Proinsulin) |
PSS011305| South Asian Ancestry| 624 individuals |
PGP000525 | Yajnik CS et al. Lancet Reg Health Southeast Asia (2023) |Ext. |
Reported Trait: Mild age-related diabetes | OR: 1.23 [1.01, 1.48] | — | — | sex | — |
| PPM002393 | PGS000862 (DR) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 0.98 [0.89, 1.08] | — | — | PC1-10 | — |
| PPM002395 | PGS000862 (DR) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.09 [1.02, 1.17] | — | — | PC1-10 | — |
| PPM002397 | PGS000862 (DR) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.01 [0.96, 1.07] | — | — | PC1-10 | — |
| PPM002394 | PGS000862 (DR) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.03 [0.96, 1.1] | — | — | PC1-10 | — |
| PPM002396 | PGS000862 (DR) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 1.09 [1.02, 1.17] | — | — | PC1-10 | — |
| PPM002403 | PGS000864 (T2D-gPRS) |
PSS001086| European Ancestry| 3,194 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Autoimmune Diabetes | OR: 1.42 [1.28, 1.58] | — | — | PC1-10 | — |
| PPM002404 | PGS000864 (T2D-gPRS) |
PSS001087| European Ancestry| 3,930 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Deficient Diabetes | OR: 1.93 [1.79, 2.09] | — | — | PC1-10 | — |
| PPM002406 | PGS000864 (T2D-gPRS) |
PSS001085| European Ancestry| 4,116 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Obesity-related Diabetes | OR: 2.12 [1.96, 2.29] | — | — | PC1-10 | — |
| PPM002407 | PGS000864 (T2D-gPRS) |
PSS001084| European Ancestry| 5,597 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Moderate Age-Related Diabetes | OR: 1.59 [1.5, 1.69] | — | — | PC1-10 | — |
| PPM002405 | PGS000864 (T2D-gPRS) |
PSS001088| European Ancestry| 3,869 individuals |
PGP000211 | Aly DM et al. Nat Genet (2021) |
Reported Trait: Severe Insulin-Resistant Diabetes | OR: 1.56 [1.45, 1.69] | — | — | PC1-10 | — |
| PPM002413 | PGS000868 (T2D_221) |
PSS001092| Ancestry Not Reported| 5,740 individuals |
PGP000214 | Aksit MA et al. J Clin Endocrinol Metab (2020) |
Reported Trait: Cystic-fibrosis related diabetes | HR: 1.285 | — | — | PCs(1-4), site of recruitment | — |
| PPM002414 | PGS000869 (T1D_48) |
PSS001092| Ancestry Not Reported| 5,740 individuals |
PGP000214 | Aksit MA et al. J Clin Endocrinol Metab (2020) |
Reported Trait: Cystic-fibrosis related diabetes | HR: 1.077 | — | — | PCs(1-4), site of recruitment | — |
| PPM007448 | PGS000924 (GBE_HC702) |
PSS004600| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism | — | AUROC: 0.87825 [0.76546, 0.99105] | R²: 0.13644 Incremental AUROC (full-covars): -0.00608 PGS R2 (no covariates): 0.01768 PGS AUROC (no covariates): 0.66722 [0.47474, 0.85969] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007449 | PGS000924 (GBE_HC702) |
PSS004602| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism | — | AUROC: 0.89799 [0.85782, 0.93815] | R²: 0.23107 Incremental AUROC (full-covars): 0.18304 PGS R2 (no covariates): 0.18886 PGS AUROC (no covariates): 0.85948 [0.81228, 0.90668] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007450 | PGS000924 (GBE_HC702) |
PSS004603| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism | — | AUROC: 0.85394 [0.77864, 0.92924] | R²: 0.15917 Incremental AUROC (full-covars): 0.14922 PGS R2 (no covariates): 0.11194 PGS AUROC (no covariates): 0.81401 [0.72659, 0.90144] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007451 | PGS000924 (GBE_HC702) |
PSS004604| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism | — | AUROC: 0.90591 [0.88325, 0.92858] | R²: 0.23709 Incremental AUROC (full-covars): 0.28213 PGS R2 (no covariates): 0.21843 PGS AUROC (no covariates): 0.88697 [0.86397, 0.90997] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007878 | PGS001023 (GBE_HC703) |
PSS004605| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of mineral metabolism | — | AUROC: 0.70572 [0.64003, 0.77141] | R²: 0.04772 Incremental AUROC (full-covars): -0.00243 PGS R2 (no covariates): 0.00257 PGS AUROC (no covariates): 0.49279 [0.49133, 0.49424] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007879 | PGS001023 (GBE_HC703) |
PSS004606| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of mineral metabolism | — | AUROC: 0.72332 [0.56417, 0.88247] | Incremental AUROC (full-covars): 0.0 R²: 0.06686 PGS R2 (no covariates): 0.00038 PGS AUROC (no covariates): 0.49882 [0.49767, 0.49998] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007880 | PGS001023 (GBE_HC703) |
PSS004607| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of mineral metabolism | — | AUROC: 0.70459 [0.66766, 0.74152] | R²: 0.07164 Incremental AUROC (full-covars): 0.05404 PGS R2 (no covariates): 0.07064 PGS AUROC (no covariates): 0.63902 [0.6046, 0.67344] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007881 | PGS001023 (GBE_HC703) |
PSS004608| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of mineral metabolism | — | AUROC: 0.60481 [0.54255, 0.66706] | R²: 0.01967 Incremental AUROC (full-covars): -0.00045 PGS R2 (no covariates): 0.00194 PGS AUROC (no covariates): 0.50905 [0.4878, 0.5303] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007882 | PGS001023 (GBE_HC703) |
PSS004609| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of mineral metabolism | — | AUROC: 0.65351 [0.63175, 0.67527] | R²: 0.03407 Incremental AUROC (full-covars): 0.05096 PGS R2 (no covariates): 0.02793 PGS AUROC (no covariates): 0.57843 [0.55918, 0.59767] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008749 | PGS001248 (GBE_HC328) |
PSS004452| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Gout | — | AUROC: 0.8285 [0.79138, 0.86562] | R²: 0.15624 Incremental AUROC (full-covars): 0.01741 PGS R2 (no covariates): 0.02051 PGS AUROC (no covariates): 0.62118 [0.56505, 0.67731] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008750 | PGS001248 (GBE_HC328) |
PSS004453| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Gout | — | AUROC: 0.84973 [0.79458, 0.90489] | R²: 0.22864 Incremental AUROC (full-covars): 0.02603 PGS R2 (no covariates): 0.04315 PGS AUROC (no covariates): 0.65938 [0.56975, 0.74901] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008751 | PGS001248 (GBE_HC328) |
PSS004454| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Gout | — | AUROC: 0.83619 [0.82126, 0.85113] | R²: 0.17414 Incremental AUROC (full-covars): 0.02904 PGS R2 (no covariates): 0.03561 PGS AUROC (no covariates): 0.66092 [0.63744, 0.6844] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008752 | PGS001248 (GBE_HC328) |
PSS004455| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Gout | — | AUROC: 0.77913 [0.74649, 0.81177] | R²: 0.11671 Incremental AUROC (full-covars): 0.03258 PGS R2 (no covariates): 0.0283 PGS AUROC (no covariates): 0.63533 [0.59256, 0.6781] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008753 | PGS001248 (GBE_HC328) |
PSS004456| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Gout | — | AUROC: 0.81572 [0.80628, 0.82516] | Incremental AUROC (full-covars): 0.04061 PGS R2 (no covariates): 0.04014 R²: 0.15436 PGS AUROC (no covariates): 0.66908 [0.65556, 0.6826] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008754 | PGS001249 (GBE_HC1215) |
PSS004203| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE gout | — | AUROC: 0.77537 [0.73576, 0.81498] | R²: 0.12063 Incremental AUROC (full-covars): 0.01433 PGS R2 (no covariates): 0.01201 PGS AUROC (no covariates): 0.58952 [0.54447, 0.63458] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008755 | PGS001249 (GBE_HC1215) |
PSS004204| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE gout | — | AUROC: 0.8503 [0.79897, 0.90164] | R²: 0.23863 Incremental AUROC (full-covars): 0.01971 PGS R2 (no covariates): 0.02733 PGS AUROC (no covariates): 0.62617 [0.54055, 0.7118] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008756 | PGS001249 (GBE_HC1215) |
PSS004205| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE gout | — | AUROC: 0.81772 [0.80388, 0.83156] | R²: 0.17135 Incremental AUROC (full-covars): 0.02929 PGS R2 (no covariates): 0.03724 PGS AUROC (no covariates): 0.65807 [0.63913, 0.67702] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008757 | PGS001249 (GBE_HC1215) |
PSS004206| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE gout | — | AUROC: 0.76492 [0.73884, 0.79099] | PGS AUROC (no covariates): 0.61344 [0.57941, 0.64746] R²: 0.11928 Incremental AUROC (full-covars): 0.02377 PGS R2 (no covariates): 0.02209 |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008758 | PGS001249 (GBE_HC1215) |
PSS004207| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE gout | — | AUROC: 0.79258 [0.7842, 0.80095] | R²: 0.14867 Incremental AUROC (full-covars): 0.03784 PGS R2 (no covariates): 0.03919 PGS AUROC (no covariates): 0.65389 [0.64293, 0.66484] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008968 | PGS001294 (GBE_HC649) |
PSS004575| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE non-insulin-dependent diabetes mellitus | — | AUROC: 0.70052 [0.68094, 0.7201] | R²: 0.10493 Incremental AUROC (full-covars): 0.00213 PGS R2 (no covariates): 0.00615 PGS AUROC (no covariates): 0.54526 [0.52378, 0.56673] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008969 | PGS001294 (GBE_HC649) |
PSS004576| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE non-insulin-dependent diabetes mellitus | — | AUROC: 0.75536 [0.71488, 0.79584] | R²: 0.1242 Incremental AUROC (full-covars): 0.01544 PGS R2 (no covariates): 0.01604 PGS AUROC (no covariates): 0.5808 [0.52621, 0.63538] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008970 | PGS001294 (GBE_HC649) |
PSS004577| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE non-insulin-dependent diabetes mellitus | — | AUROC: 0.72888 [0.71557, 0.7422] | R²: 0.10344 Incremental AUROC (full-covars): 0.03534 PGS R2 (no covariates): 0.03413 PGS AUROC (no covariates): 0.63582 [0.62119, 0.65045] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008971 | PGS001294 (GBE_HC649) |
PSS004578| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE non-insulin-dependent diabetes mellitus | — | AUROC: 0.68707 [0.67293, 0.70121] | R²: 0.11343 Incremental AUROC (full-covars): 0.01724 PGS R2 (no covariates): 0.02384 PGS AUROC (no covariates): 0.58532 [0.56986, 0.60078] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008972 | PGS001294 (GBE_HC649) |
PSS004579| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE non-insulin-dependent diabetes mellitus | — | AUROC: 0.71038 [0.70256, 0.71821] | R²: 0.08854 Incremental AUROC (full-covars): 0.04133 PGS R2 (no covariates): 0.03493 PGS AUROC (no covariates): 0.63323 [0.62453, 0.64194] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008973 | PGS001295 (GBE_HC165) |
PSS004312| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.68145 [0.62426, 0.73864] | R²: 0.04466 Incremental AUROC (full-covars): 0.00427 PGS R2 (no covariates): 0.00162 PGS AUROC (no covariates): 0.5359 [0.47698, 0.59482] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008974 | PGS001295 (GBE_HC165) |
PSS004313| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.83509 [0.71831, 0.95186] | R²: 0.20575 Incremental AUROC (full-covars): -0.00085 PGS R2 (no covariates): 0.00265 PGS AUROC (no covariates): 0.56328 [0.47919, 0.64736] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008975 | PGS001295 (GBE_HC165) |
PSS004314| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69318 [0.65625, 0.73011] | R²: 0.04603 Incremental AUROC (full-covars): 0.0115 PGS R2 (no covariates): 0.00675 PGS AUROC (no covariates): 0.58258 [0.54116, 0.62401] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008976 | PGS001295 (GBE_HC165) |
PSS004315| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.65806 [0.61856, 0.69756] | R²: 0.0392 Incremental AUROC (full-covars): 0.01243 PGS R2 (no covariates): 0.00618 PGS AUROC (no covariates): 0.5613 [0.5184, 0.60421] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008977 | PGS001295 (GBE_HC165) |
PSS004316| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.68247 [0.66155, 0.70338] | R²: 0.03772 Incremental AUROC (full-covars): 0.01405 PGS R2 (no covariates): 0.00633 PGS AUROC (no covariates): 0.57592 [0.55208, 0.59975] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008978 | PGS001296 (GBE_HC648) |
PSS004570| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE insulin-dependent diabetes mellitus | — | AUROC: 0.66885 [0.62172, 0.71599] | R²: 0.04054 Incremental AUROC (full-covars): -0.01128 PGS R2 (no covariates): 0.00021 PGS AUROC (no covariates): 0.51906 [0.4689, 0.56923] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008979 | PGS001296 (GBE_HC648) |
PSS004571| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE insulin-dependent diabetes mellitus | — | AUROC: 0.89264 [0.80447, 0.98081] | R²: 0.19006 Incremental AUROC (full-covars): -0.01413 PGS R2 (no covariates): 0.00422 PGS AUROC (no covariates): 0.43531 [0.15162, 0.71901] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008980 | PGS001296 (GBE_HC648) |
PSS004572| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE insulin-dependent diabetes mellitus | — | AUROC: 0.70536 [0.66494, 0.74577] | R²: 0.0607 Incremental AUROC (full-covars): 0.12077 PGS R2 (no covariates): 0.05496 PGS AUROC (no covariates): 0.68941 [0.64672, 0.73209] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008981 | PGS001296 (GBE_HC648) |
PSS004573| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE insulin-dependent diabetes mellitus | — | AUROC: 0.67679 [0.6379, 0.71568] | R²: 0.04266 Incremental AUROC (full-covars): -0.01593 PGS R2 (no covariates): 0.0016 PGS AUROC (no covariates): 0.54249 [0.49552, 0.58946] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008982 | PGS001296 (GBE_HC648) |
PSS004574| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE insulin-dependent diabetes mellitus | — | AUROC: 0.65986 [0.63673, 0.68299] | R²: 0.03385 Incremental AUROC (full-covars): 0.06785 PGS R2 (no covariates): 0.02496 PGS AUROC (no covariates): 0.62694 [0.60131, 0.65256] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008983 | PGS001297 (GBE_HC337) |
PSS004457| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.78146 [0.64554, 0.91738] | R²: 0.08635 Incremental AUROC (full-covars): -0.05504 PGS R2 (no covariates): 0.00185 PGS AUROC (no covariates): 0.41884 [0.19064, 0.64704] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008984 | PGS001297 (GBE_HC337) |
PSS004458| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.79737 [0.708, 0.88674] | R²: 0.11683 Incremental AUROC (full-covars): 0.09636 PGS R2 (no covariates): 0.0912 PGS AUROC (no covariates): 0.77118 [0.67108, 0.87128] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008985 | PGS001297 (GBE_HC337) |
PSS004459| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.81031 [0.66359, 0.95703] | R²: 0.06825 Incremental AUROC (full-covars): -0.01908 PGS R2 (no covariates): 6e-05 PGS AUROC (no covariates): 0.53853 [0.37761, 0.69945] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008986 | PGS001297 (GBE_HC337) |
PSS004460| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.7643 [0.7041, 0.8245] | R²: 0.06625 Incremental AUROC (full-covars): 0.19149 PGS R2 (no covariates): 0.06103 PGS AUROC (no covariates): 0.76543 [0.70744, 0.82342] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008987 | PGS001298 (GBE_HC689) |
PSS004590| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE obesity | — | AUROC: 0.631 [0.60757, 0.65443] | R²: 0.03591 Incremental AUROC (full-covars): -0.00374 PGS R2 (no covariates): 0.00346 PGS AUROC (no covariates): 0.54117 [0.51549, 0.56685] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008988 | PGS001298 (GBE_HC689) |
PSS004591| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE obesity | — | AUROC: 0.65328 [0.53612, 0.77044] | R²: 0.04232 Incremental AUROC (full-covars): -0.00574 PGS R2 (no covariates): 0.00287 PGS AUROC (no covariates): 0.54699 [0.43971, 0.65426] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008989 | PGS001298 (GBE_HC689) |
PSS004592| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE obesity | — | AUROC: 0.59854 [0.58297, 0.61411] | R²: 0.01902 Incremental AUROC (full-covars): 0.02082 PGS R2 (no covariates): 0.00911 PGS AUROC (no covariates): 0.56858 [0.5529, 0.58426] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008990 | PGS001298 (GBE_HC689) |
PSS004593| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE obesity | — | AUROC: 0.61415 [0.59079, 0.6375] | R²: 0.02737 Incremental AUROC (full-covars): 0.00377 PGS R2 (no covariates): 0.00603 PGS AUROC (no covariates): 0.55658 [0.53218, 0.58097] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM008991 | PGS001298 (GBE_HC689) |
PSS004594| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE obesity | — | AUROC: 0.59555 [0.58697, 0.60413] | R²: 0.01814 Incremental AUROC (full-covars): 0.03355 PGS R2 (no covariates): 0.01146 PGS AUROC (no covariates): 0.57573 [0.56713, 0.58434] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009020 | PGS001305 (GBE_HC608) |
PSS004536| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vitamin b12 deficiency anaemia | — | AUROC: 0.66063 [0.54547, 0.77579] | R²: 0.02699 Incremental AUROC (full-covars): 0.01762 PGS R2 (no covariates): 0.00536 PGS AUROC (no covariates): 0.5839 [0.43974, 0.72805] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009021 | PGS001305 (GBE_HC608) |
PSS004538| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vitamin b12 deficiency anaemia | — | AUROC: 0.65118 [0.60827, 0.69409] | R²: 0.02729 Incremental AUROC (full-covars): 0.02555 PGS R2 (no covariates): 0.00865 PGS AUROC (no covariates): 0.59612 [0.5552, 0.63704] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009022 | PGS001305 (GBE_HC608) |
PSS004539| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vitamin b12 deficiency anaemia | — | AUROC: 0.72387 [0.6834, 0.76434] | R²: 0.06747 Incremental AUROC (full-covars): 0.01252 PGS R2 (no covariates): 0.00966 PGS AUROC (no covariates): 0.57469 [0.52685, 0.62252] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009023 | PGS001305 (GBE_HC608) |
PSS004540| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE vitamin b12 deficiency anaemia | — | AUROC: 0.64482 [0.61972, 0.66993] | R²: 0.02374 Incremental AUROC (full-covars): 0.02212 PGS R2 (no covariates): 0.0068 PGS AUROC (no covariates): 0.57972 [0.55331, 0.60612] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009083 | PGS001318 (GBE_HC700) |
PSS004595| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias | — | AUROC: 0.72671 [0.71075, 0.74267] | R²: 0.1504 Incremental AUROC (full-covars): 0.008 PGS R2 (no covariates): 0.01331 PGS AUROC (no covariates): 0.5658 [0.54786, 0.58375] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009084 | PGS001318 (GBE_HC700) |
PSS004596| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias | — | AUROC: 0.72108 [0.68694, 0.75523] | R²: 0.12667 Incremental AUROC (full-covars): 0.00638 PGS R2 (no covariates): 0.01352 PGS AUROC (no covariates): 0.56443 [0.52596, 0.6029] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009085 | PGS001318 (GBE_HC700) |
PSS004597| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias | — | AUROC: 0.74382 [0.73637, 0.75127] | R²: 0.17729 Incremental AUROC (full-covars): 0.02969 PGS R2 (no covariates): 0.04099 PGS AUROC (no covariates): 0.61613 [0.60728, 0.62497] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009086 | PGS001318 (GBE_HC700) |
PSS004598| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias | — | AUROC: 0.7175 [0.70581, 0.7292] | R²: 0.17483 Incremental AUROC (full-covars): 0.01739 PGS R2 (no covariates): 0.02931 PGS AUROC (no covariates): 0.5892 [0.57589, 0.60251] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009087 | PGS001318 (GBE_HC700) |
PSS004599| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias | — | AUROC: 0.73453 [0.73009, 0.73896] | R²: 0.17195 Incremental AUROC (full-covars): 0.03242 PGS R2 (no covariates): 0.04352 PGS AUROC (no covariates): 0.61734 [0.61215, 0.62253] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009088 | PGS001319 (GBE_HC708) |
PSS004610| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other metabolic disorders | — | AUROC: 0.77406 [0.68678, 0.86135] | R²: 0.06649 Incremental AUROC (full-covars): -0.00199 PGS R2 (no covariates): 0.00603 PGS AUROC (no covariates): 0.44259 [0.3516, 0.53358] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009089 | PGS001319 (GBE_HC708) |
PSS004611| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other metabolic disorders | — | AUROC: 0.70958 [0.62744, 0.79171] | R²: 0.04504 Incremental AUROC (full-covars): 0.02495 PGS R2 (no covariates): 0.01479 PGS AUROC (no covariates): 0.54987 [0.46099, 0.63876] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009090 | PGS001319 (GBE_HC708) |
PSS004612| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other metabolic disorders | — | AUROC: 0.64684 [0.54842, 0.74526] | R²: 0.02913 Incremental AUROC (full-covars): -0.00029 PGS R2 (no covariates): 0.00067 PGS AUROC (no covariates): 0.52382 [0.42834, 0.61931] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009091 | PGS001319 (GBE_HC708) |
PSS004613| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE other metabolic disorders | — | AUROC: 0.60186 [0.54294, 0.66079] | R²: 0.02952 Incremental AUROC (full-covars): 0.09428 PGS R2 (no covariates): 0.05151 PGS AUROC (no covariates): 0.62356 [0.56795, 0.67918] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009122 | PGS001327 (GBE_HC221) |
PSS004359| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diabetes | — | AUROC: 0.68586 [0.66802, 0.7037] | R²: 0.09776 Incremental AUROC (full-covars): 0.00638 PGS R2 (no covariates): 0.00926 PGS AUROC (no covariates): 0.55541 [0.53643, 0.5744] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009123 | PGS001327 (GBE_HC221) |
PSS004360| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diabetes | — | AUROC: 0.69569 [0.64958, 0.7418] | R²: 0.08294 Incremental AUROC (full-covars): 0.01187 PGS R2 (no covariates): 0.01141 PGS AUROC (no covariates): 0.56178 [0.51127, 0.61228] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009124 | PGS001327 (GBE_HC221) |
PSS004361| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diabetes | — | AUROC: 0.70541 [0.69227, 0.71854] | R²: 0.08595 Incremental AUROC (full-covars): 0.04263 PGS R2 (no covariates): 0.03446 PGS AUROC (no covariates): 0.63125 [0.61738, 0.64511] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009125 | PGS001327 (GBE_HC221) |
PSS004362| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diabetes | — | AUROC: 0.68746 [0.67395, 0.70097] | R²: 0.11895 Incremental AUROC (full-covars): 0.02618 PGS R2 (no covariates): 0.03527 PGS AUROC (no covariates): 0.60108 [0.5865, 0.61565] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009126 | PGS001327 (GBE_HC221) |
PSS004363| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Diabetes | — | AUROC: 0.69818 [0.69047, 0.70589] | R²: 0.08111 Incremental AUROC (full-covars): 0.04455 PGS R2 (no covariates): 0.03558 PGS AUROC (no covariates): 0.63112 [0.6228, 0.63945] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009132 | PGS001329 (GBE_HC652) |
PSS004580| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified diabetes mellitus | — | AUROC: 0.69503 [0.67407, 0.716] | R²: 0.08972 Incremental AUROC (full-covars): 0.00332 PGS R2 (no covariates): 0.00713 PGS AUROC (no covariates): 0.55713 [0.53377, 0.58048] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009133 | PGS001329 (GBE_HC652) |
PSS004581| East Asian Ancestry| 1,704 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified diabetes mellitus | — | AUROC: 0.70891 [0.65305, 0.76477] | R²: 0.09058 Incremental AUROC (full-covars): 0.02211 PGS R2 (no covariates): 0.02321 PGS AUROC (no covariates): 0.60847 [0.55016, 0.66678] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009134 | PGS001329 (GBE_HC652) |
PSS004582| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified diabetes mellitus | — | AUROC: 0.72437 [0.70887, 0.73987] | R²: 0.08424 Incremental AUROC (full-covars): 0.03715 PGS R2 (no covariates): 0.02619 PGS AUROC (no covariates): 0.62743 [0.60999, 0.64487] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009135 | PGS001329 (GBE_HC652) |
PSS004583| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified diabetes mellitus | — | AUROC: 0.70359 [0.68854, 0.71865] | R²: 0.11885 Incremental AUROC (full-covars): 0.02262 PGS R2 (no covariates): 0.02671 PGS AUROC (no covariates): 0.59807 [0.58121, 0.61493] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM009136 | PGS001329 (GBE_HC652) |
PSS004584| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE unspecified diabetes mellitus | — | AUROC: 0.7046 [0.69521, 0.71399] | R²: 0.0749 Incremental AUROC (full-covars): 0.04078 PGS R2 (no covariates): 0.03024 PGS AUROC (no covariates): 0.63102 [0.62084, 0.64119] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM005189 | PGS001357 (T2D_AnnoPred_PRS) |
PSS003606| European Ancestry| 178,138 individuals |
PGP000252 | Ye Y et al. Circ Genom Precis Med (2021) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.6446 | — | Age, sex, PCs(1-10) | — |
| PPM007030 | PGS001371 (GBE_INI2976) |
PSS006886| African Ancestry| 673 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Age diabetes diagnosed | — | — | R²: 0.28398 [0.26544, 0.30253] Incremental R2 (full-covars): -0.00362 PGS R2 (no covariates): 0.00112 [-0.0005, 0.00275] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007031 | PGS001371 (GBE_INI2976) |
PSS006887| East Asian Ancestry| 86 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Age diabetes diagnosed | — | — | R²: 0.31131 [0.27489, 0.34772] Incremental R2 (full-covars): 0.00576 PGS R2 (no covariates): 0.00203 [-0.00223, 0.00629] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007032 | PGS001371 (GBE_INI2976) |
PSS006888| European Ancestry| 1,059 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Age diabetes diagnosed | — | — | R²: 0.37828 [0.36879, 0.38778] Incremental R2 (full-covars): 0.02371 PGS R2 (no covariates): 0.04728 [0.04214, 0.05243] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007033 | PGS001371 (GBE_INI2976) |
PSS006889| South Asian Ancestry| 1,335 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Age diabetes diagnosed | — | — | R²: 0.20384 [0.18792, 0.21975] Incremental R2 (full-covars): -0.00895 PGS R2 (no covariates): 0.00042 [-0.00049, 0.00133] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007034 | PGS001371 (GBE_INI2976) |
PSS006890| European Ancestry| 3,195 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Age diabetes diagnosed | — | — | R²: 0.28031 [0.27455, 0.28606] Incremental R2 (full-covars): 0.02294 PGS R2 (no covariates): 0.03923 [0.03636, 0.0421] |
age, sex, UKB array type, Genotype PCs | — |
| PPM009277 | PGS001781 (T2D_PRSCS) |
PSS007684| European Ancestry| 309,154 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Type 2 diabetes (incident and prevalent) | OR: 1.59 [1.57, 1.61] | AUROC: 0.758 [0.756, 0.761] | — | year of birth, sex, ten first principal components of Finnish ancestry, batch, genotyping array | — |
| PPM009281 | PGS001781 (T2D_PRSCS) |
PSS007685| European Ancestry| 279,879 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Incident type 2 diabetes | OR: 1.52 [1.49, 1.55] | AUROC: 0.852 [0.849, 0.855] | — | year of birth, sex, ten first principal components of Finnish ancestry, batch, genotyping array | — |
| PPM009287 | PGS001781 (T2D_PRSCS) |
PSS007692| European Ancestry| 343,672 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Prevalent type 2 diabetes | OR: 1.75 [1.72, 1.78] | AUROC: 0.725 [0.721, 0.729] | — | year of birth, sex | — |
| PPM009283 | PGS001781 (T2D_PRSCS) |
PSS007691| European Ancestry| 328,115 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Incident type 2 diabetes | OR: 1.51 [1.48, 1.54] | AUROC: 0.669 [0.664, 0.675] | — | year of birth, sex | — |
| PPM009285 | PGS001781 (T2D_PRSCS) |
PSS007686| European Ancestry| 309,154 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Prevalent type 2 diabetes | OR: 1.59 [1.57, 1.61] | AUROC: 0.81 [0.808, 0.813] | — | year of birth, sex, ten first principal components of Finnish ancestry, batch, genotyping array | — |
| PPM009279 | PGS001781 (T2D_PRSCS) |
PSS007690| European Ancestry| 343,672 individuals |
PGP000261 | Tamlander M et al. Commun Biol (2022) |
Reported Trait: Type 2 diabetes (incident and prevalent) | OR: 1.68 [1.65, 1.7] | AUROC: 0.708 [0.705, 0.711] | — | year of birth, sex | — |
| PPM009309 | PGS001789 (1kgeur_gbmi_leaveUKBBout_Gout_pst_eff_a1_b0.5_phiauto) |
PSS007699| African Ancestry| 6,206 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Gout | — | AUROC: 0.805 | Nagelkerke's R2 (covariates regressed out): 0.01073 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM009293 | PGS001789 (1kgeur_gbmi_leaveUKBBout_Gout_pst_eff_a1_b0.5_phiauto) |
PSS007712| European Ancestry| 359,345 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Gout | — | AUROC: 0.807 | Nagelkerke's R2 (covariates regressed out): 0.03121 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM009304 | PGS001789 (1kgeur_gbmi_leaveUKBBout_Gout_pst_eff_a1_b0.5_phiauto) |
PSS007703| Additional Asian Ancestries| 8,184 individuals |
PGP000262 | Wang Y et al. Cell Genom (2023) |
Reported Trait: Gout | — | AUROC: 0.78 | Nagelkerke's R2 (covariates regressed out): 0.00748 | sex,age,age2,age*sex,age^2*sex, 20PCs | — |
| PPM009436 | PGS001817 (portability-PLR_250.1) |
PSS009287| European Ancestry| 18,975 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0752 [0.061, 0.0893] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009437 | PGS001817 (portability-PLR_250.1) |
PSS009061| European Ancestry| 3,954 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0684 [0.0372, 0.0994] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009438 | PGS001817 (portability-PLR_250.1) |
PSS008615| European Ancestry| 6,300 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0739 [0.0493, 0.0985] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009439 | PGS001817 (portability-PLR_250.1) |
PSS008391| Greater Middle Eastern Ancestry| 1,107 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0349 [-0.0246, 0.0941] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009440 | PGS001817 (portability-PLR_250.1) |
PSS008169| South Asian Ancestry| 5,228 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0224 [-0.0047, 0.0496] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009441 | PGS001817 (portability-PLR_250.1) |
PSS007956| East Asian Ancestry| 1,729 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): -0.0001 [-0.0475, 0.0474] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009442 | PGS001817 (portability-PLR_250.1) |
PSS007737| African Ancestry| 2,200 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): -0.0006 [-0.0426, 0.0414] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009443 | PGS001817 (portability-PLR_250.1) |
PSS008840| African Ancestry| 3,490 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): -0.0187 [-0.052, 0.0146] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009444 | PGS001818 (portability-PLR_250.2) |
PSS009288| European Ancestry| 19,931 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1246 [0.1109, 0.1382] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009445 | PGS001818 (portability-PLR_250.2) |
PSS009062| European Ancestry| 4,121 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0862 [0.0557, 0.1165] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009447 | PGS001818 (portability-PLR_250.2) |
PSS008392| Greater Middle Eastern Ancestry| 1,197 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1735 [0.1176, 0.2284] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009448 | PGS001818 (portability-PLR_250.2) |
PSS008170| South Asian Ancestry| 6,312 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1556 [0.1314, 0.1796] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009449 | PGS001818 (portability-PLR_250.2) |
PSS007957| East Asian Ancestry| 1,808 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0665 [0.0202, 0.1125] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009450 | PGS001818 (portability-PLR_250.2) |
PSS007738| African Ancestry| 2,476 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0956 [0.0562, 0.1346] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009451 | PGS001818 (portability-PLR_250.2) |
PSS008841| African Ancestry| 3,896 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0522 [0.0208, 0.0836] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009446 | PGS001818 (portability-PLR_250.2) |
PSS008616| European Ancestry| 6,646 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.108 [0.0842, 0.1317] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009452 | PGS001819 (portability-PLR_250.7) |
PSS009289| European Ancestry| 19,330 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0366 [0.0226, 0.0507] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009453 | PGS001819 (portability-PLR_250.7) |
PSS009063| European Ancestry| 4,032 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0638 [0.033, 0.0946] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009454 | PGS001819 (portability-PLR_250.7) |
PSS008617| European Ancestry| 6,465 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0315 [0.0071, 0.0559] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009455 | PGS001819 (portability-PLR_250.7) |
PSS008393| Greater Middle Eastern Ancestry| 1,162 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0471 [-0.1048, 0.011] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009456 | PGS001819 (portability-PLR_250.7) |
PSS008171| South Asian Ancestry| 6,081 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0325 [0.0074, 0.0577] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009457 | PGS001819 (portability-PLR_250.7) |
PSS007958| East Asian Ancestry| 1,764 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0249 [-0.0718, 0.022] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009459 | PGS001819 (portability-PLR_250.7) |
PSS008842| African Ancestry| 3,732 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0089 [-0.0233, 0.041] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009458 | PGS001819 (portability-PLR_250.7) |
PSS007739| African Ancestry| 2,385 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0193 [-0.0596, 0.021] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009476 | PGS001822 (portability-PLR_274.1) |
PSS009292| European Ancestry| 19,983 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0364 [0.0226, 0.0503] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009477 | PGS001822 (portability-PLR_274.1) |
PSS009066| European Ancestry| 4,135 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.043 [0.0125, 0.0735] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009478 | PGS001822 (portability-PLR_274.1) |
PSS008620| European Ancestry| 6,655 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0538 [0.0297, 0.0777] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009479 | PGS001822 (portability-PLR_274.1) |
PSS008396| Greater Middle Eastern Ancestry| 1,200 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0122 [-0.0449, 0.0692] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009480 | PGS001822 (portability-PLR_274.1) |
PSS008174| South Asian Ancestry| 6,325 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0166 [-0.008, 0.0413] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009481 | PGS001822 (portability-PLR_274.1) |
PSS007961| East Asian Ancestry| 1,810 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0287 [-0.0176, 0.075] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009482 | PGS001822 (portability-PLR_274.1) |
PSS007742| African Ancestry| 2,480 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0314 [-0.0082, 0.0708] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009483 | PGS001822 (portability-PLR_274.1) |
PSS008845| African Ancestry| 3,918 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0294 [-0.002, 0.0607] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009484 | PGS001823 (portability-PLR_275.1) |
PSS009293| European Ancestry| 19,883 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): 0.1307 [0.117, 0.1444] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009485 | PGS001823 (portability-PLR_275.1) |
PSS009067| European Ancestry| 4,105 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): 0.109 [0.0786, 0.1392] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009486 | PGS001823 (portability-PLR_275.1) |
PSS008621| European Ancestry| 6,637 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): 0.0178 [-0.0063, 0.0419] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009487 | PGS001823 (portability-PLR_275.1) |
PSS008175| South Asian Ancestry| 6,298 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): 0.0003 [-0.0244, 0.025] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009489 | PGS001823 (portability-PLR_275.1) |
PSS008846| African Ancestry| 3,903 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): 0.0193 [-0.0121, 0.0507] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009488 | PGS001823 (portability-PLR_275.1) |
PSS007962| East Asian Ancestry| 1,809 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): 0.0117 [-0.0346, 0.058] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009490 | PGS001824 (portability-PLR_277.4) |
PSS009294| European Ancestry| 19,924 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): 0.0716 [0.0577, 0.0854] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009491 | PGS001824 (portability-PLR_277.4) |
PSS009068| European Ancestry| 4,126 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): 0.0565 [0.026, 0.087] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009492 | PGS001824 (portability-PLR_277.4) |
PSS008622| European Ancestry| 6,636 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): 0.0696 [0.0455, 0.0935] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009493 | PGS001824 (portability-PLR_277.4) |
PSS008397| Greater Middle Eastern Ancestry| 1,196 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): -0.0314 [-0.0885, 0.0258] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009494 | PGS001824 (portability-PLR_277.4) |
PSS008176| South Asian Ancestry| 6,292 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): 0.0243 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009495 | PGS001824 (portability-PLR_277.4) |
PSS007743| African Ancestry| 2,472 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): 0.002 [-0.0376, 0.0416] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009496 | PGS001824 (portability-PLR_277.4) |
PSS008847| African Ancestry| 3,901 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): 0.0014 [-0.0301, 0.0328] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009497 | PGS001825 (portability-PLR_278) |
PSS009295| European Ancestry| 20,000 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0547 [0.0409, 0.0686] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009499 | PGS001825 (portability-PLR_278) |
PSS008623| European Ancestry| 6,660 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0516 [0.0276, 0.0756] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009500 | PGS001825 (portability-PLR_278) |
PSS008398| Greater Middle Eastern Ancestry| 1,200 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0493 [-0.0078, 0.106] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009501 | PGS001825 (portability-PLR_278) |
PSS008177| South Asian Ancestry| 6,331 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0334 [0.0087, 0.058] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009502 | PGS001825 (portability-PLR_278) |
PSS007963| East Asian Ancestry| 1,810 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): -0.0049 [-0.0513, 0.0414] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009503 | PGS001825 (portability-PLR_278) |
PSS007744| African Ancestry| 2,484 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0323 [-0.0072, 0.0717] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009504 | PGS001825 (portability-PLR_278) |
PSS008848| African Ancestry| 3,924 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0208 [-0.0105, 0.0522] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM009498 | PGS001825 (portability-PLR_278) |
PSS009069| European Ancestry| 4,136 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0453 [0.0148, 0.0758] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011074 | PGS002025 (portability-ldpred2_250.1) |
PSS009287| European Ancestry| 18,975 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0824 [0.0682, 0.0965] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011075 | PGS002025 (portability-ldpred2_250.1) |
PSS009061| European Ancestry| 3,954 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0666 [0.0354, 0.0976] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011076 | PGS002025 (portability-ldpred2_250.1) |
PSS008615| European Ancestry| 6,300 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0719 [0.0472, 0.0964] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011077 | PGS002025 (portability-ldpred2_250.1) |
PSS008391| Greater Middle Eastern Ancestry| 1,107 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0529 [-0.0066, 0.112] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011078 | PGS002025 (portability-ldpred2_250.1) |
PSS008169| South Asian Ancestry| 5,228 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0228 [-0.0044, 0.0499] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011079 | PGS002025 (portability-ldpred2_250.1) |
PSS007956| East Asian Ancestry| 1,729 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): -0.0048 [-0.0522, 0.0427] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011080 | PGS002025 (portability-ldpred2_250.1) |
PSS007737| African Ancestry| 2,200 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): 0.0089 [-0.0331, 0.0509] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011081 | PGS002025 (portability-ldpred2_250.1) |
PSS008840| African Ancestry| 3,490 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 1 diabetes | — | — | Partial Correlation (partial-r): -0.013 [-0.0463, 0.0203] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011082 | PGS002026 (portability-ldpred2_250.2) |
PSS009288| European Ancestry| 19,931 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1304 [0.1168, 0.1441] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011083 | PGS002026 (portability-ldpred2_250.2) |
PSS009062| European Ancestry| 4,121 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0862 [0.0558, 0.1165] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011084 | PGS002026 (portability-ldpred2_250.2) |
PSS008616| European Ancestry| 6,646 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1134 [0.0896, 0.1371] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011085 | PGS002026 (portability-ldpred2_250.2) |
PSS008392| Greater Middle Eastern Ancestry| 1,197 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1764 [0.1205, 0.2312] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011087 | PGS002026 (portability-ldpred2_250.2) |
PSS007957| East Asian Ancestry| 1,808 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0786 [0.0324, 0.1246] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011088 | PGS002026 (portability-ldpred2_250.2) |
PSS007738| African Ancestry| 2,476 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.1001 [0.0607, 0.1391] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011089 | PGS002026 (portability-ldpred2_250.2) |
PSS008841| African Ancestry| 3,896 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.0806 [0.0493, 0.1118] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011086 | PGS002026 (portability-ldpred2_250.2) |
PSS008170| South Asian Ancestry| 6,312 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Partial Correlation (partial-r): 0.158 [0.1338, 0.182] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM020894 | PGS002026 (portability-ldpred2_250.2) |
PSS011441| African Ancestry| 504 individuals |
PGP000599 | Guarischi-Sousa R et al. Circ Genom Precis Med (2023) |Ext. |
Reported Trait: Raised coronary lesion | OR: 1.1 [0.9, 1.35] | — | — | — | — |
| PPM020889 | PGS002026 (portability-ldpred2_250.2) |
PSS011442| European Ancestry| 564 individuals |
PGP000599 | Guarischi-Sousa R et al. Circ Genom Precis Med (2023) |Ext. |
Reported Trait: Raised coronary lesion | OR: 0.96 [0.8, 1.16] | — | — | — | — |
| PPM011090 | PGS002027 (portability-ldpred2_250.7) |
PSS009289| European Ancestry| 19,330 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0451 [0.031, 0.0592] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011091 | PGS002027 (portability-ldpred2_250.7) |
PSS009063| European Ancestry| 4,032 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0607 [0.0298, 0.0915] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011092 | PGS002027 (portability-ldpred2_250.7) |
PSS008617| European Ancestry| 6,465 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0241 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011093 | PGS002027 (portability-ldpred2_250.7) |
PSS008393| Greater Middle Eastern Ancestry| 1,162 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0311 [-0.0889, 0.027] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011094 | PGS002027 (portability-ldpred2_250.7) |
PSS008171| South Asian Ancestry| 6,081 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0351 [0.01, 0.0603] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011095 | PGS002027 (portability-ldpred2_250.7) |
PSS007958| East Asian Ancestry| 1,764 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0302 [-0.077, 0.0168] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011096 | PGS002027 (portability-ldpred2_250.7) |
PSS007739| African Ancestry| 2,385 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): -0.0204 [-0.0606, 0.0199] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011097 | PGS002027 (portability-ldpred2_250.7) |
PSS008842| African Ancestry| 3,732 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Diabetic retinopathy | — | — | Partial Correlation (partial-r): 0.0062 [-0.0259, 0.0384] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011116 | PGS002030 (portability-ldpred2_274.1) |
PSS008620| European Ancestry| 6,655 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0476 [0.0236, 0.0716] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011114 | PGS002030 (portability-ldpred2_274.1) |
PSS009292| European Ancestry| 19,983 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0415 [0.0277, 0.0554] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011115 | PGS002030 (portability-ldpred2_274.1) |
PSS009066| European Ancestry| 4,135 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.047 [0.0165, 0.0775] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011117 | PGS002030 (portability-ldpred2_274.1) |
PSS008396| Greater Middle Eastern Ancestry| 1,200 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): -0.0053 [-0.0623, 0.0518] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011118 | PGS002030 (portability-ldpred2_274.1) |
PSS008174| South Asian Ancestry| 6,325 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0231 [-0.0015, 0.0478] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011119 | PGS002030 (portability-ldpred2_274.1) |
PSS007961| East Asian Ancestry| 1,810 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0262 [-0.0201, 0.0725] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011120 | PGS002030 (portability-ldpred2_274.1) |
PSS007742| African Ancestry| 2,480 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0336 [-0.006, 0.073] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011121 | PGS002030 (portability-ldpred2_274.1) |
PSS008845| African Ancestry| 3,918 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Gout | — | — | Partial Correlation (partial-r): 0.0254 [-0.006, 0.0568] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011122 | PGS002031 (portability-ldpred2_275.1) |
PSS009293| European Ancestry| 19,883 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): 0.1355 [0.1219, 0.1492] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011123 | PGS002031 (portability-ldpred2_275.1) |
PSS009067| European Ancestry| 4,105 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): 0.1073 [0.0769, 0.1375] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011124 | PGS002031 (portability-ldpred2_275.1) |
PSS008621| European Ancestry| 6,637 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): 0.0173 [-0.0068, 0.0414] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011125 | PGS002031 (portability-ldpred2_275.1) |
PSS008175| South Asian Ancestry| 6,298 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): -0.0027 [-0.0274, 0.0221] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011127 | PGS002031 (portability-ldpred2_275.1) |
PSS008846| African Ancestry| 3,903 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): -0.0075 [-0.039, 0.0239] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011126 | PGS002031 (portability-ldpred2_275.1) |
PSS007962| East Asian Ancestry| 1,809 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of iron metabolism | — | — | Partial Correlation (partial-r): -0.008 [-0.0543, 0.0384] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011128 | PGS002032 (portability-ldpred2_277.4) |
PSS009294| European Ancestry| 19,924 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): 0.0716 [0.0578, 0.0854] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011129 | PGS002032 (portability-ldpred2_277.4) |
PSS009068| European Ancestry| 4,126 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): 0.0534 [0.0228, 0.0838] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011130 | PGS002032 (portability-ldpred2_277.4) |
PSS008622| European Ancestry| 6,636 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): 0.0714 [0.0474, 0.0953] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011131 | PGS002032 (portability-ldpred2_277.4) |
PSS008397| Greater Middle Eastern Ancestry| 1,196 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): -0.0333 [-0.0903, 0.0239] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011132 | PGS002032 (portability-ldpred2_277.4) |
PSS008176| South Asian Ancestry| 6,292 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): 0.0252 | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011133 | PGS002032 (portability-ldpred2_277.4) |
PSS007743| African Ancestry| 2,472 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): 0.0011 [-0.0385, 0.0406] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011134 | PGS002032 (portability-ldpred2_277.4) |
PSS008847| African Ancestry| 3,901 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Disorders of bilirubin excretion | — | — | Partial Correlation (partial-r): -0.0017 [-0.0332, 0.0297] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011135 | PGS002033 (portability-ldpred2_278) |
PSS009295| European Ancestry| 20,000 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0789 [0.0651, 0.0927] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011137 | PGS002033 (portability-ldpred2_278) |
PSS008623| European Ancestry| 6,660 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0824 [0.0585, 0.1062] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011138 | PGS002033 (portability-ldpred2_278) |
PSS008398| Greater Middle Eastern Ancestry| 1,200 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0801 [0.0232, 0.1366] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011139 | PGS002033 (portability-ldpred2_278) |
PSS008177| South Asian Ancestry| 6,331 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0502 [0.0255, 0.0747] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011140 | PGS002033 (portability-ldpred2_278) |
PSS007963| East Asian Ancestry| 1,810 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0109 [-0.0354, 0.0572] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011141 | PGS002033 (portability-ldpred2_278) |
PSS007744| African Ancestry| 2,484 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0265 [-0.013, 0.0659] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011142 | PGS002033 (portability-ldpred2_278) |
PSS008848| African Ancestry| 3,924 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0516 [0.0203, 0.0829] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011136 | PGS002033 (portability-ldpred2_278) |
PSS009069| European Ancestry| 4,136 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | — | — | Partial Correlation (partial-r): 0.0523 [0.0218, 0.0827] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011640 | PGS002098 (portability-ldpred2_abnormal_appetite) |
PSS009381| European Ancestry| 6,451 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Recent poor appetite or overeating | — | — | Partial Correlation (partial-r): 0.0629 [0.0385, 0.0872] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011641 | PGS002098 (portability-ldpred2_abnormal_appetite) |
PSS009155| European Ancestry| 1,243 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Recent poor appetite or overeating | — | — | Partial Correlation (partial-r): 0.1194 [0.0638, 0.1743] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011642 | PGS002098 (portability-ldpred2_abnormal_appetite) |
PSS008709| European Ancestry| 2,260 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Recent poor appetite or overeating | — | — | Partial Correlation (partial-r): 0.0823 [0.0411, 0.1233] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011644 | PGS002098 (portability-ldpred2_abnormal_appetite) |
PSS008261| South Asian Ancestry| 814 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Recent poor appetite or overeating | — | — | Partial Correlation (partial-r): 0.0558 [-0.0138, 0.1249] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011645 | PGS002098 (portability-ldpred2_abnormal_appetite) |
PSS008039| East Asian Ancestry| 427 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Recent poor appetite or overeating | — | — | Partial Correlation (partial-r): 0.0486 [-0.0488, 0.1451] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011646 | PGS002098 (portability-ldpred2_abnormal_appetite) |
PSS007825| African Ancestry| 372 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Recent poor appetite or overeating | — | — | Partial Correlation (partial-r): -0.0014 [-0.1059, 0.1032] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011647 | PGS002098 (portability-ldpred2_abnormal_appetite) |
PSS008929| African Ancestry| 511 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Recent poor appetite or overeating | — | — | Partial Correlation (partial-r): -0.014 [-0.1023, 0.0746] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM011643 | PGS002098 (portability-ldpred2_abnormal_appetite) |
PSS008483| Greater Middle Eastern Ancestry| 201 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Recent poor appetite or overeating | — | — | Partial Correlation (partial-r): 0.1181 [-0.0282, 0.2595] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012733 | PGS002243 (ldpred_t2d) |
PSS009522| European Ancestry| 258,402 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.58 [1.56, 1.6] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012737 | PGS002243 (ldpred_t2d) |
PSS009518| European Ancestry| 110,597 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.55 [1.51, 1.59] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012741 | PGS002243 (ldpred_t2d) |
PSS009514| East Asian Ancestry| 178,726 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.37 [1.36, 1.39] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012745 | PGS002243 (ldpred_t2d) |
PSS009526| European Ancestry| 69,422 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.64 [1.6, 1.69] | — | — | birth year, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012749 | PGS002243 (ldpred_t2d) |
PSS009534| European Ancestry| 25,696 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.46 [1.41, 1.51] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012753 | PGS002243 (ldpred_t2d) |
PSS009530| African Ancestry| 1,535 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.24 [1.09, 1.42] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012757 | PGS002243 (ldpred_t2d) |
PSS009542| European Ancestry| 343,676 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.78 [1.75, 1.81] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012762 | PGS002243 (ldpred_t2d) |
PSS009538| African Ancestry| 7,618 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.46 [1.32, 1.62] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012767 | PGS002243 (ldpred_t2d) |
PSS009546| South Asian Ancestry| 7,628 individuals |
PGP000271 | Mars N et al. Cell Genom (2022) |
Reported Trait: Type 2 diabetes | OR: 1.66 [1.55, 1.79] | — | — | age, sex, 10 PCs (+/- dataset-specific technical covariates) | — |
| PPM012834 | PGS002256 (GRS4_GDM) |
PSS009573| East Asian Ancestry| 985 individuals |
PGP000282 | Wu Q et al. Diabetol Metab Syndr (2022) |
Reported Trait: Gestational diabetes mellitus in early pregnancy | — | AUROC: 0.62 [0.573, 0.667] | — | — | — |
| PPM012948 | PGS002277 (pPS_Insulin_secretion_1) |
PSS009629| South Asian Ancestry| 5,806 individuals |
PGP000305 | Siddiqui MK et al. Diabetologia (2022) |
Reported Trait: Age at diagnosis (normal BMI) | β: 37.31 (16.7) | — | R²: 0.012 | — | — |
| PPM012947 | PGS002277 (pPS_Insulin_secretion_1) |
PSS009629| South Asian Ancestry| 5,806 individuals |
PGP000305 | Siddiqui MK et al. Diabetologia (2022) |
Reported Trait: Age at diagnosis | — | — | Z: 5.2 | — | Z-score p-value < 0.0001 |
| PPM012949 | PGS002277 (pPS_Insulin_secretion_1) |
PSS009629| South Asian Ancestry| 5,806 individuals |
PGP000305 | Siddiqui MK et al. Diabetologia (2022) |
Reported Trait: Age at diagnosis (overweight BMI) | β: 32.68 (20.7) | — | R²: 0.0097 | — | — |
| PPM012950 | PGS002277 (pPS_Insulin_secretion_1) |
PSS009629| South Asian Ancestry| 5,806 individuals |
PGP000305 | Siddiqui MK et al. Diabetologia (2022) |
Reported Trait: Age at diagnosis (obese BMI) | β: 18.9 (10.76) | — | R²: 0.0036 | — | — |
| PPM013045 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, highest vs. lowest tertile): 1.77 [1.66, 1.89] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI) | — |
| PPM013046 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout without cardiometabolic diseases | — | — | Hazard Ratio (HR, highest vs. lowest tertile): 4.94 [3.91, 6.23] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), Unfavorable lifestyle | — |
| PPM013047 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout with cardiometabolic diseases | — | — | Hazard Ratio (HR, highest vs. lowest tertile): 3.0 [2.62, 3.43] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), Unfavorable lifestyle | — |
| PPM013048 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, middle vs. lowest tertile): 1.53 [1.35, 1.74] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), favorable lifestyle | — |
| PPM013049 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, middle vs. lowest tertile): 2.39 [2.12, 2.7] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), unfavorable lifestyle | — |
| PPM013050 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, highest vs. lowest tertile): 1.98 [1.75, 2.24] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), favorable lifestyle | — |
| PPM013044 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, middle vs. lowest tertile): 1.44 [1.35, 1.54] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI) | — |
| PPM013051 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, highest vs. lowest tertile): 3.13 [2.79, 3.52] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), unfavorable lifestyle | — |
| PPM020291 | PGS002307 (PRS33_gout) |
PSS011325| European Ancestry| 181,559 individuals |
PGP000540 | Zhang T et al. Rheumatology (Oxford) (2023) |Ext. |
Reported Trait: Incident gout with ultraprocessed food consumption | — | — | Hazard ratio (HR, high UPF consumption and highest PRS quartile vs. low UPF consumption and lowest PRS quartile): 1.9 [1.39, 2.6] | age, sex, BMI, education levels, Townsend deprivation index, physical activity, smoking status, drinking status, family history of diseases (hypertension, cardiovascular disease, and diabetes), healthy diet score, ultra-processed food consumption, medical history of hypertension, diabetes, kidney disease, cancer, and cardiovascular disease, first ten genetic principal components and genotype measurement batch | — |
| PPM013067 | PGS002308 (PRScsx_T2D) |
PSS009671| African Ancestry| 6,745 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.7 [1.58, 1.84] | AUROC: 0.631 | R²: 0.046 | age, sex, top 10 PCs | — |
| PPM013064 | PGS002308 (PRScsx_T2D) |
PSS009677| European Ancestry| 54,793 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.96 [1.91, 2.02] | AUROC: 0.793 | R²: 0.092 | age, sex, top 10 PCs, study site | — |
| PPM013065 | PGS002308 (PRScsx_T2D) |
PSS009676| African Ancestry| 12,472 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.54 [1.46, 1.64] | AUROC: 0.848 | R²: 0.028 | age, sex, top 10 PCs, study site | — |
| PPM013066 | PGS002308 (PRScsx_T2D) |
PSS009678| Hispanic or Latin American Ancestry| 2,374 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 2.08 [1.84, 2.35] | AUROC: 0.851 | R²: 0.08 | age, sex, top 10 PCs, study site | — |
| PPM013068 | PGS002308 (PRScsx_T2D) |
PSS009669| African Ancestry| 5,498 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.85 [1.7, 2.01] | AUROC: 0.633 | R²: 0.036 | age, sex, top 10 PCs | — |
| PPM013069 | PGS002308 (PRScsx_T2D) |
PSS009670| African Ancestry| 1,896 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.75 [1.52, 2.02] | AUROC: 0.757 | R²: 0.062 | age, sex, top 10 PCs | — |
| PPM013070 | PGS002308 (PRScsx_T2D) |
PSS009675| African Ancestry| 655 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 1.37 [1.13, 1.65] | AUROC: 0.631 | R²: 0.015 | age, sex, top 10 PCs | — |
| PPM013071 | PGS002308 (PRScsx_T2D) |
PSS009672| East Asian Ancestry| 25,110 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 2.19 [2.05, 2.33] | AUROC: 0.81 | R²: 0.151 | age, sex, top 10 PCs | — |
| PPM013072 | PGS002308 (PRScsx_T2D) |
PSS009673| East Asian Ancestry| 54,078 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 2.01 [1.93, 2.1] | AUROC: 0.781 | R²: 0.129 | age, sex, top 10 PCs | — |
| PPM013073 | PGS002308 (PRScsx_T2D) |
PSS009674| East Asian Ancestry| 10,378 individuals |
PGP000331 | Ge T et al. Genome Med (2022) |
Reported Trait: Type 2 diabetes | OR: 2.16 [1.96, 2.38] | AUROC: 0.802 | R²: 0.153 | age, sex, top 10 PCs | — |
| PPM013086 | PGS002321 (disease_DIABETES_ANY_DIAGNOSED.BOLT-LMM) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.005 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013135 | PGS002321 (disease_DIABETES_ANY_DIAGNOSED.BOLT-LMM) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.006 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013184 | PGS002321 (disease_DIABETES_ANY_DIAGNOSED.BOLT-LMM) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0159 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013233 | PGS002321 (disease_DIABETES_ANY_DIAGNOSED.BOLT-LMM) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.028 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013089 | PGS002324 (disease_ENDOCRINE_DIABETES.BOLT-LMM) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0025 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013138 | PGS002324 (disease_ENDOCRINE_DIABETES.BOLT-LMM) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0029 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013187 | PGS002324 (disease_ENDOCRINE_DIABETES.BOLT-LMM) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0101 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013236 | PGS002324 (disease_ENDOCRINE_DIABETES.BOLT-LMM) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0219 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013119 | PGS002354 (disease_T2D.BOLT-LMM) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0047 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013168 | PGS002354 (disease_T2D.BOLT-LMM) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0025 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013217 | PGS002354 (disease_T2D.BOLT-LMM) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0135 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013266 | PGS002354 (disease_T2D.BOLT-LMM) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0218 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013291 | PGS002379 (disease_T2D.BOLT-LMM-BBJ) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013314 | PGS002379 (disease_T2D.BOLT-LMM-BBJ) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0148 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013360 | PGS002379 (disease_T2D.BOLT-LMM-BBJ) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0091 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013337 | PGS002379 (disease_T2D.BOLT-LMM-BBJ) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0026 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013374 | PGS002393 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.0001) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013423 | PGS002393 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.0001) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0017 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013472 | PGS002393 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.0001) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013521 | PGS002393 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.0001) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013377 | PGS002396 (disease_ENDOCRINE_DIABETES.P+T.0.0001) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013426 | PGS002396 (disease_ENDOCRINE_DIABETES.P+T.0.0001) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013475 | PGS002396 (disease_ENDOCRINE_DIABETES.P+T.0.0001) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013524 | PGS002396 (disease_ENDOCRINE_DIABETES.P+T.0.0001) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013407 | PGS002426 (disease_T2D.P+T.0.0001) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013505 | PGS002426 (disease_T2D.P+T.0.0001) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013554 | PGS002426 (disease_T2D.P+T.0.0001) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013456 | PGS002426 (disease_T2D.P+T.0.0001) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0032 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013570 | PGS002442 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.001) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013619 | PGS002442 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.001) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0056 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013717 | PGS002442 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.001) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013668 | PGS002442 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.001) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013622 | PGS002445 (disease_ENDOCRINE_DIABETES.P+T.0.001) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0026 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013671 | PGS002445 (disease_ENDOCRINE_DIABETES.P+T.0.001) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013720 | PGS002445 (disease_ENDOCRINE_DIABETES.P+T.0.001) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013573 | PGS002445 (disease_ENDOCRINE_DIABETES.P+T.0.001) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013603 | PGS002475 (disease_T2D.P+T.0.001) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013652 | PGS002475 (disease_T2D.P+T.0.001) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0041 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013701 | PGS002475 (disease_T2D.P+T.0.001) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013750 | PGS002475 (disease_T2D.P+T.0.001) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013766 | PGS002491 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.01) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013815 | PGS002491 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.01) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0047 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013864 | PGS002491 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.01) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013913 | PGS002491 (disease_DIABETES_ANY_DIAGNOSED.P+T.0.01) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013769 | PGS002494 (disease_ENDOCRINE_DIABETES.P+T.0.01) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013867 | PGS002494 (disease_ENDOCRINE_DIABETES.P+T.0.01) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013916 | PGS002494 (disease_ENDOCRINE_DIABETES.P+T.0.01) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013818 | PGS002494 (disease_ENDOCRINE_DIABETES.P+T.0.01) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0026 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013799 | PGS002524 (disease_T2D.P+T.0.01) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013848 | PGS002524 (disease_T2D.P+T.0.01) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0033 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013897 | PGS002524 (disease_T2D.P+T.0.01) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013946 | PGS002524 (disease_T2D.P+T.0.01) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013962 | PGS002540 (disease_DIABETES_ANY_DIAGNOSED.P+T.1e-06) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014011 | PGS002540 (disease_DIABETES_ANY_DIAGNOSED.P+T.1e-06) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014060 | PGS002540 (disease_DIABETES_ANY_DIAGNOSED.P+T.1e-06) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014109 | PGS002540 (disease_DIABETES_ANY_DIAGNOSED.P+T.1e-06) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0008 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013965 | PGS002543 (disease_ENDOCRINE_DIABETES.P+T.1e-06) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014014 | PGS002543 (disease_ENDOCRINE_DIABETES.P+T.1e-06) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014063 | PGS002543 (disease_ENDOCRINE_DIABETES.P+T.1e-06) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014112 | PGS002543 (disease_ENDOCRINE_DIABETES.P+T.1e-06) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0003 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014093 | PGS002573 (disease_T2D.P+T.1e-06) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013995 | PGS002573 (disease_T2D.P+T.1e-06) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014044 | PGS002573 (disease_T2D.P+T.1e-06) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014142 | PGS002573 (disease_T2D.P+T.1e-06) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014305 | PGS002589 (disease_DIABETES_ANY_DIAGNOSED.P+T.5e-08) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0009 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014158 | PGS002589 (disease_DIABETES_ANY_DIAGNOSED.P+T.5e-08) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014207 | PGS002589 (disease_DIABETES_ANY_DIAGNOSED.P+T.5e-08) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0009 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014256 | PGS002589 (disease_DIABETES_ANY_DIAGNOSED.P+T.5e-08) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014161 | PGS002592 (disease_ENDOCRINE_DIABETES.P+T.5e-08) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014210 | PGS002592 (disease_ENDOCRINE_DIABETES.P+T.5e-08) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014308 | PGS002592 (disease_ENDOCRINE_DIABETES.P+T.5e-08) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0005 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014259 | PGS002592 (disease_ENDOCRINE_DIABETES.P+T.5e-08) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014191 | PGS002622 (disease_T2D.P+T.5e-08) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014240 | PGS002622 (disease_T2D.P+T.5e-08) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0002 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014289 | PGS002622 (disease_T2D.P+T.5e-08) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014338 | PGS002622 (disease_T2D.P+T.5e-08) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014354 | PGS002638 (disease_DIABETES_ANY_DIAGNOSED.PolyFun-pred) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.005 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_DIABETES_ANY_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014403 | PGS002638 (disease_DIABETES_ANY_DIAGNOSED.PolyFun-pred) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0097 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_DIABETES_ANY_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014452 | PGS002638 (disease_DIABETES_ANY_DIAGNOSED.PolyFun-pred) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0136 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_DIABETES_ANY_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014501 | PGS002638 (disease_DIABETES_ANY_DIAGNOSED.PolyFun-pred) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0339 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_DIABETES_ANY_DIAGNOSED.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014357 | PGS002641 (disease_ENDOCRINE_DIABETES.PolyFun-pred) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0025 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_ENDOCRINE_DIABETES.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014455 | PGS002641 (disease_ENDOCRINE_DIABETES.PolyFun-pred) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0105 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_ENDOCRINE_DIABETES.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014504 | PGS002641 (disease_ENDOCRINE_DIABETES.PolyFun-pred) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0244 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_ENDOCRINE_DIABETES.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014406 | PGS002641 (disease_ENDOCRINE_DIABETES.PolyFun-pred) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0029 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_ENDOCRINE_DIABETES.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014387 | PGS002671 (disease_T2D.PolyFun-pred) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0047 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_T2D.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014436 | PGS002671 (disease_T2D.PolyFun-pred) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0072 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_T2D.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014485 | PGS002671 (disease_T2D.PolyFun-pred) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0128 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_T2D.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014534 | PGS002671 (disease_T2D.PolyFun-pred) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0251 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See disease_T2D.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014599 | PGS002687 (disease_DIABETES_ANY_DIAGNOSED.SBayesR) |
PSS009728| East Asian Ancestry| 898 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.005 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014648 | PGS002687 (disease_DIABETES_ANY_DIAGNOSED.SBayesR) |
PSS009729| European Ancestry| 43,355 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0145 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014697 | PGS002687 (disease_DIABETES_ANY_DIAGNOSED.SBayesR) |
PSS009730| South Asian Ancestry| 7,926 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0281 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014550 | PGS002687 (disease_DIABETES_ANY_DIAGNOSED.SBayesR) |
PSS009727| African Ancestry| 6,430 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Diabetes (any type) | — | — | Incremental R2 (full model vs. covariates alone): 0.0057 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014602 | PGS002690 (disease_ENDOCRINE_DIABETES.SBayesR) |
PSS009740| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0034 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014553 | PGS002690 (disease_ENDOCRINE_DIABETES.SBayesR) |
PSS009739| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0046 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014651 | PGS002690 (disease_ENDOCRINE_DIABETES.SBayesR) |
PSS009741| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0094 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014700 | PGS002690 (disease_ENDOCRINE_DIABETES.SBayesR) |
PSS009742| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Endocrine and diabetes diseases | — | — | Incremental R2 (full model vs. covariates alone): 0.0221 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014583 | PGS002720 (disease_T2D.SBayesR) |
PSS009859| African Ancestry| 6,503 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.006 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014632 | PGS002720 (disease_T2D.SBayesR) |
PSS009860| East Asian Ancestry| 922 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0021 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014681 | PGS002720 (disease_T2D.SBayesR) |
PSS009861| European Ancestry| 43,505 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0129 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014730 | PGS002720 (disease_T2D.SBayesR) |
PSS009862| South Asian Ancestry| 8,098 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (full model vs. covariates alone): 0.0207 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014821 | PGS002733 (GRS17_T2D) |
PSS009902| European Ancestry| 600 individuals |
PGP000342 | Pezzilli S et al. Diabetes Metab (2022) |
Reported Trait: Early-onset type 2 diabetes | OR: 1.09 [1.01, 1.18] | — | — | — | — |
| PPM014822 | PGS002733 (GRS17_T2D) |
PSS009902| European Ancestry| 600 individuals |
PGP000342 | Pezzilli S et al. Diabetes Metab (2022) |
Reported Trait: Early-onset type 2 diabetes in rare variant carriers | OR: 1.45 [1.15, 1.57] | — | — | — | — |
| PPM014823 | PGS002733 (GRS17_T2D) |
PSS009902| European Ancestry| 600 individuals |
PGP000342 | Pezzilli S et al. Diabetes Metab (2022) |
Reported Trait: Early-onset type 2 diabetes in rare variant non-carriers | OR: 1.06 [1.01, 1.13] | — | — | — | — |
| PPM014962 | PGS002762 (Urate_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Gout | OR: 1.69 [1.6, 1.78] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM014971 | PGS002771 (Type_2_diabetes_prscs) |
PSS009939| European Ancestry| 39,444 individuals |
PGP000364 | Mars N et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 diabetes | OR: 1.88 [1.82, 1.95] | — | — | age, sex, 10 PCs, technical covariates | — |
| PPM014979 | PGS002779 (GTG_T2D_maxCT) |
PSS009943| European Ancestry| 5,472 individuals |
PGP000365 | Wong CK et al. PLoS One (2022) |
Reported Trait: Incident type 2 diabetes | OR: 1.35 [1.25, 1.45] | AUROC: 0.585 [0.564, 0.605] | — | — | — |
| PPM014980 | PGS002780 (GTG_T2D_SCT) |
PSS009943| European Ancestry| 5,472 individuals |
PGP000365 | Wong CK et al. PLoS One (2022) |
Reported Trait: Incident type 2 diabetes | OR: 1.41 [1.31, 1.51] | AUROC: 0.595 [0.575, 0.615] | — | — | — |
| PPM015993 | PGS003089 (ExPRSweb_T2D_2443_LASSOSUM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.524 [1.468, 1.583] β: 0.422 (0.0191) |
AUROC: 0.616 [0.6, 0.63] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015996 | PGS003090 (ExPRSweb_T2D_2443_PT_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.425 [1.373, 1.479] β: 0.354 (0.0191) |
AUROC: 0.599 [0.582, 0.615] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015994 | PGS003091 (ExPRSweb_T2D_2443_PLINK_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.379 [1.329, 1.431] β: 0.321 (0.0189) |
AUROC: 0.591 [0.574, 0.606] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015992 | PGS003092 (ExPRSweb_T2D_2443_DBSLMM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.275 [1.23, 1.321] β: 0.243 (0.0184) |
AUROC: 0.563 [0.546, 0.58] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015995 | PGS003093 (ExPRSweb_T2D_2443_PRSCS_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.6 [1.539, 1.664] β: 0.47 (0.0199) |
AUROC: 0.625 [0.608, 0.639] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015999 | PGS003094 (ExPRSweb_T2D_29358691-GCST005413_LASSOSUM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.333 [1.286, 1.382] β: 0.287 (0.0184) |
AUROC: 0.589 [0.572, 0.604] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016005 | PGS003095 (ExPRSweb_T2D_29358691-GCST005413_PT_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.239 [1.196, 1.284] β: 0.214 (0.0181) |
AUROC: 0.562 [0.546, 0.578] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016001 | PGS003096 (ExPRSweb_T2D_29358691-GCST005413_PLINK_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.232 [1.189, 1.277] β: 0.209 (0.0181) |
AUROC: 0.56 [0.545, 0.576] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM015997 | PGS003097 (ExPRSweb_T2D_29358691-GCST005413_DBSLMM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.011 [0.976, 1.047] β: 0.011 (0.0181) |
AUROC: 0.5 [0.484, 0.517] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016003 | PGS003098 (ExPRSweb_T2D_29358691-GCST005413_PRSCS_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.358 [1.31, 1.408] β: 0.306 (0.0183) |
AUROC: 0.593 [0.577, 0.608] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016009 | PGS003099 (ExPRSweb_T2D_30054458-GCST006867_LASSOSUM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.657 [1.595, 1.722] β: 0.505 (0.0196) |
AUROC: 0.626 [0.609, 0.641] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016015 | PGS003100 (ExPRSweb_T2D_30054458-GCST006867_PT_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.531 [1.474, 1.591] β: 0.426 (0.0193) |
AUROC: 0.6 [0.585, 0.616] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016011 | PGS003101 (ExPRSweb_T2D_30054458-GCST006867_PLINK_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.531 [1.474, 1.591] β: 0.426 (0.0193) |
AUROC: 0.6 [0.585, 0.616] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016007 | PGS003102 (ExPRSweb_T2D_30054458-GCST006867_DBSLMM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.639 [1.577, 1.703] β: 0.494 (0.0196) |
AUROC: 0.628 [0.611, 0.643] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016013 | PGS003103 (ExPRSweb_T2D_30054458-GCST006867_PRSCS_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.704 [1.639, 1.772] β: 0.533 (0.0198) |
AUROC: 0.637 [0.621, 0.653] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016019 | PGS003104 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_LASSOSUM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.536 [1.479, 1.596] β: 0.429 (0.0195) |
AUROC: 0.611 [0.595, 0.626] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016025 | PGS003105 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PT_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.33 [1.283, 1.379] β: 0.285 (0.0184) |
AUROC: 0.572 [0.555, 0.588] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016021 | PGS003106 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PLINK_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.33 [1.283, 1.379] β: 0.285 (0.0184) |
AUROC: 0.572 [0.555, 0.588] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016017 | PGS003107 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_DBSLMM_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.028 [0.992, 1.065] β: 0.0276 (0.0182) |
AUROC: 0.541 [0.523, 0.557] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016023 | PGS003108 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PRSCS_MGI_20211120) |
PSS010014| European Ancestry| 21,356 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.563 [1.504, 1.624] β: 0.446 (0.0195) |
AUROC: 0.61 [0.594, 0.625] | — | SEX,AGE,Batch,PC1,PC2,PC3,PC4 | — |
| PPM016000 | PGS003109 (ExPRSweb_T2D_29358691-GCST005413_LASSOSUM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.522 [1.491, 1.554] β: 0.42 (0.0106) |
AUROC: 0.616 [0.61, 0.622] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016006 | PGS003110 (ExPRSweb_T2D_29358691-GCST005413_PT_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.406 [1.378, 1.435] β: 0.341 (0.0103) |
AUROC: 0.594 [0.588, 0.6] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016002 | PGS003111 (ExPRSweb_T2D_29358691-GCST005413_PLINK_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.392 [1.364, 1.42] β: 0.331 (0.0103) |
AUROC: 0.59 [0.584, 0.596] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM015998 | PGS003112 (ExPRSweb_T2D_29358691-GCST005413_DBSLMM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.01 [0.989, 1.031] β: 0.00976 (0.0104) |
AUROC: 0.501 [0.495, 0.507] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016004 | PGS003113 (ExPRSweb_T2D_29358691-GCST005413_PRSCS_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.522 [1.491, 1.554] β: 0.42 (0.0106) |
AUROC: 0.616 [0.611, 0.622] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016010 | PGS003114 (ExPRSweb_T2D_30054458-GCST006867_LASSOSUM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 3.959 [3.866, 4.055] β: 1.38 (0.0121) |
AUROC: 0.825 [0.82, 0.829] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016016 | PGS003115 (ExPRSweb_T2D_30054458-GCST006867_PT_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 3.755 [3.669, 3.844] β: 1.32 (0.0119) |
AUROC: 0.816 [0.811, 0.82] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016012 | PGS003116 (ExPRSweb_T2D_30054458-GCST006867_PLINK_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 3.755 [3.669, 3.844] β: 1.32 (0.0119) |
AUROC: 0.816 [0.811, 0.82] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016008 | PGS003117 (ExPRSweb_T2D_30054458-GCST006867_DBSLMM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 3.061 [2.992, 3.132] β: 1.12 (0.0116) |
AUROC: 0.778 [0.774, 0.783] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016014 | PGS003118 (ExPRSweb_T2D_30054458-GCST006867_PRSCS_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 3.193 [3.12, 3.268] β: 1.16 (0.0118) |
AUROC: 0.786 [0.782, 0.791] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016020 | PGS003119 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_LASSOSUM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.662 [1.628, 1.698] β: 0.508 (0.0107) |
AUROC: 0.639 [0.634, 0.645] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016026 | PGS003120 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PT_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.451 [1.421, 1.48] β: 0.372 (0.0104) |
AUROC: 0.603 [0.597, 0.609] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016022 | PGS003121 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PLINK_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.451 [1.421, 1.48] β: 0.372 (0.0104) |
AUROC: 0.603 [0.597, 0.609] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016018 | PGS003122 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_DBSLMM_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.009 [0.988, 1.03] β: 0.00858 (0.0105) |
AUROC: 0.547 [0.541, 0.552] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016024 | PGS003123 (ExPRSweb_T2D_METAANALYSIS-DIAGRAM_PRSCS_UKB_20211120) |
PSS010036| European Ancestry| 203,197 individuals |
PGP000393 | Ma Y et al. Am J Hum Genet (2022) |
Reported Trait: Type 2 Diabetes | OR: 1.715 [1.679, 1.752] β: 0.539 (0.0107) |
AUROC: 0.648 [0.642, 0.654] | — | Sex,birthYear,genotyping.array,PC1,PC2,PC3,PC4 | — |
| PPM016117 | PGS003329 (PRS19_gout) |
PSS010039| European Ancestry| 5,522 individuals |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Reported Trait: Age at onset of gout (in men) | β: -3.61 [-4.32, -2.9] | — | — | 10 Global PCs | — |
| PPM016120 | PGS003329 (PRS19_gout) |
PSS010039| European Ancestry| 5,522 individuals |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Reported Trait: Tophaceous Disease (in men) | β: 1.15 [1.0, 1.31] | — | — | 10 Global PCs | — |
| PPM016123 | PGS003329 (PRS19_gout) |
PSS010039| European Ancestry| 5,522 individuals |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Reported Trait: Age at onset of gout (in women) | β: 0.07 [-2.32, 2.45] | — | — | 10 Global PCs | — |
| PPM016126 | PGS003329 (PRS19_gout) |
PSS010039| European Ancestry| 5,522 individuals |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Reported Trait: Tophaceous Disease (in women) | β: 0.68 [0.42, 1.1] | — | — | 10 Global PCs | — |
| PPM016119 | PGS003329 (PRS19_gout) |
PSS010040| Additional Diverse Ancestries| 869 individuals |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Reported Trait: Age at onset of gout (in men) | β: -3.51 [-5.46, -1.57] | — | — | 10 Global PCs + 10 Oceanian PCs | — |
| PPM016121 | PGS003329 (PRS19_gout) |
PSS010038| Additional Diverse Ancestries| 1,386 individuals |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Reported Trait: Tophaceous Disease (in men) | β: 2.6 [1.66, 4.06] | — | — | 10 Global PCs + 10 Oceanian PCs | — |
| PPM016122 | PGS003329 (PRS19_gout) |
PSS010040| Additional Diverse Ancestries| 869 individuals |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Reported Trait: Tophaceous Disease (in men) | β: 1.53 [1.07, 2.19] | — | — | 10 Global PCs + 10 Oceanian PCs | — |
| PPM016124 | PGS003329 (PRS19_gout) |
PSS010038| Additional Diverse Ancestries| 1,386 individuals |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Reported Trait: Age at onset of gout (in women) | β: 0.2 [-7.21, 7.62] | — | — | 10 Global PCs + 10 Oceanian PCs | — |
| PPM016125 | PGS003329 (PRS19_gout) |
PSS010040| Additional Diverse Ancestries| 869 individuals |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Reported Trait: Age at onset of gout (in women) | β: -3.33 [-9.28, 2.62] | — | — | 10 Global PCs + 10 Oceanian PCs | — |
| PPM016127 | PGS003329 (PRS19_gout) |
PSS010038| Additional Diverse Ancestries| 1,386 individuals |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Reported Trait: Tophaceous Disease (in women) | β: 1.45 [0.39, 5.36] | — | — | 10 Global PCs + 10 Oceanian PCs | — |
| PPM016118 | PGS003329 (PRS19_gout) |
PSS010038| Additional Diverse Ancestries| 1,386 individuals |
PGP000394 | Sumpter NA et al. Arthritis Rheumatol (2022) |
Reported Trait: Age at onset of gout (in men) | β: -6.35 [-8.91, -3.8] | — | — | 10 Global PCs + 10 Oceanian PCs | — |
| PPM016201 | PGS003353 (GRS_T2D) |
PSS010055| East Asian Ancestry| 22,608 individuals |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Reported Trait: Fasting plasma glucose | OR: 1.83 [1.59, 2.11] | — | — | — | — |
| PPM016202 | PGS003353 (GRS_T2D) |
PSS010055| East Asian Ancestry| 22,608 individuals |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Reported Trait: Hemoglobin A1c level | OR: 1.68 [1.46, 1.93] | — | — | — | — |
| PPM016203 | PGS003353 (GRS_T2D) |
PSS010055| East Asian Ancestry| 22,608 individuals |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Reported Trait: Type 2 diabetes | OR: 2.99 [2.61, 3.44] | — | — | — | — |
| PPM016204 | PGS003353 (GRS_T2D) |
PSS010055| East Asian Ancestry| 22,608 individuals |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Reported Trait: Fasting plasma glucose and Type 2 diabetes | OR: 3.52 [2.69, 4.61] | — | — | — | — |
| PPM016326 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Atrial fibrillation | OR: 1.45 β: 0.37 (0.07) |
— | — | — | — |
| PPM016327 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Ischemic Heart Disease | OR: 1.35 β: 0.3 (0.06) |
— | — | — | — |
| PPM016328 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Gastrojejunal ulcer | OR: 6.42 β: 1.86 (0.38) |
— | — | — | — |
| PPM016482 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cholelithiasis | OR: 1.5 β: 0.4 (0.1) |
— | — | — | — |
| PPM016499 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Barrett's esophagus | OR: 2.2 β: 0.8 (0.2) |
— | — | — | — |
| PPM016480 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic pulmonary heart disease | OR: 1.6 β: 0.4 (0.1) |
— | — | — | — |
| PPM016485 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other chronic ischemic heart disease, unspecified | OR: 1.4 β: 0.4 (0.1) |
— | — | — | — |
| PPM016486 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Osteoarthritis; localized | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016487 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic ulcer of leg or foot | OR: 1.6 β: 0.5 (0.1) |
— | — | — | — |
| PPM016481 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Postoperative infection | OR: 1.6 β: 0.5 (0.1) |
— | — | — | — |
| PPM016496 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Myocardial infarction | OR: 1.4 β: 0.3 (0.1) |
— | — | — | — |
| PPM016497 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hyperlipidemia | OR: 1.2 β: 0.2 (0.1) |
— | — | — | — |
| PPM016423 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Shock | OR: 1.58 β: 0.46 (0.15) |
— | — | — | — |
| PPM016424 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Candidiasis of skin and nails | OR: 1.7 β: 0.53 (0.17) |
— | — | — | — |
| PPM016425 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Depression | OR: 1.2 β: 0.18 (0.06) |
— | — | — | — |
| PPM016426 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Nonspecific chest pain | OR: 1.17 β: 0.16 (0.05) |
— | — | — | — |
| PPM016427 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Nonrheumatic aortic valve disorders | OR: 1.31 β: 0.27 (0.09) |
— | — | — | — |
| PPM016428 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Ingrowing nail | OR: 1.46 β: 0.38 (0.12) |
— | — | — | — |
| PPM016429 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Sleep disorders | OR: 1.21 β: 0.19 (0.06) |
— | — | — | — |
| PPM016430 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic kidney disease, Stage I or II | OR: 1.49 β: 0.4 (0.13) |
— | — | — | — |
| PPM016431 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypoventilation | OR: 1.64 β: 0.49 (0.17) |
— | — | — | — |
| PPM016432 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Gouty arthropathy | OR: 1.52 β: 0.42 (0.14) |
— | — | — | — |
| PPM016433 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Heart failure NOS | OR: 1.35 β: 0.3 (0.1) |
— | — | — | — |
| PPM016435 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Arthropathy associated with neurological disorders | OR: 2.76 β: 1.01 (0.35) |
— | — | — | — |
| PPM016436 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Coagulation defects | OR: 1.27 β: 0.24 (0.08) |
— | — | — | — |
| PPM016437 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Osteoarthrosis involving more than one site, but not specified as generalized | OR: 1.5 β: 0.4 (0.14) |
— | — | — | — |
| PPM016438 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Liver abscess and sequelae of chronic liver disease | OR: 1.65 β: 0.5 (0.17) |
— | — | — | — |
| PPM016439 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypothyroidism | OR: 1.21 β: 0.19 (0.07) |
— | — | — | — |
| PPM016440 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Bursitis | OR: 1.37 β: 0.31 (0.11) |
— | — | — | — |
| PPM016441 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Umbilical hernia | OR: 1.54 β: 0.43 (0.15) |
— | — | — | — |
| PPM016442 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cardiomyopathy | OR: 1.29 β: 0.26 (0.09) |
— | — | — | — |
| PPM016443 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Calcaneal spur; Exostosis NOS | OR: 1.39 β: 0.33 (0.12) |
— | — | — | — |
| PPM016444 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Pulmonary embolism and infarction, acute | OR: 1.43 β: 0.35 (0.13) |
— | — | — | — |
| PPM016445 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic pain | OR: 1.31 β: 0.27 (0.1) |
— | — | — | — |
| PPM016446 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Spondylosis without myelopathy | OR: 1.2 β: 0.19 (0.07) |
— | — | — | — |
| PPM016447 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Obesity | OR: 3.5 β: 1.2 (0.1) |
— | — | — | — |
| PPM016449 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 2 diabetes | OR: 2.0 β: 0.7 (0.1) |
— | — | — | — |
| PPM016450 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Sleep apnea | OR: 2.2 β: 0.8 (0.1) |
— | — | — | — |
| PPM016451 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Diabetes mellitus | OR: 1.9 β: 0.7 (0.1) |
— | — | — | — |
| PPM016452 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypertension | OR: 1.8 β: 0.6 (0.1) |
— | — | — | — |
| PPM016453 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Essential hypertension | OR: 1.8 β: 0.6 (0.1) |
— | — | — | — |
| PPM016454 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | OR: 2.2 β: 0.8 (0.1) |
— | — | — | — |
| PPM016455 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic liver disease and cirrhosis | OR: 2.1 β: 0.7 (0.1) |
— | — | — | — |
| PPM016456 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Edema | OR: 1.6 β: 0.4 (0.1) |
— | — | — | — |
| PPM016457 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 1 diabetes | OR: 1.9 β: 0.6 (0.1) |
— | — | — | — |
| PPM016459 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other disorders of intestine | OR: 1.7 β: 0.5 (0.1) |
— | — | — | — |
| PPM016460 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Acute renal failure | OR: 1.6 β: 0.5 (0.1) |
— | — | — | — |
| PPM016461 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Osteoarthrosis | OR: 1.4 β: 0.4 (0.1) |
— | — | — | — |
| PPM016462 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Osteoarthrosis NOS | OR: 1.4 β: 0.4 (0.1) |
— | — | — | — |
| PPM016463 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Respiratory failure, insufficiency, arrest | OR: 1.6 β: 0.5 (0.1) |
— | — | — | — |
| PPM016464 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Osteoarthrosis, localized, primary | OR: 1.7 β: 0.5 (0.1) |
— | — | — | — |
| PPM016465 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Renal failure | OR: 1.4 β: 0.4 (0.1) |
— | — | — | — |
| PPM016466 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Shortness of breath | OR: 1.4 β: 0.3 (0.1) |
— | — | — | — |
| PPM016467 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Coronary atherosclerosis | OR: 1.4 β: 0.3 (0.1) |
— | — | — | — |
| PPM016468 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cardiomegaly | OR: 1.5 β: 0.4 (0.1) |
— | — | — | — |
| PPM016469 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Congestive heart failure | OR: 1.5 β: 0.4 (0.1) |
— | — | — | — |
| PPM016471 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Respiratory failure | OR: 1.7 β: 0.5 (0.1) |
— | — | — | — |
| PPM016472 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic venous insufficiency | OR: 1.8 β: 0.6 (0.1) |
— | — | — | — |
| PPM016473 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Pulmonary heart disease | OR: 1.5 β: 0.4 (0.1) |
— | — | — | — |
| PPM016474 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Atrial fibrillation and flutter | OR: 1.4 β: 0.4 (0.1) |
— | — | — | — |
| PPM016475 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 2 diabetes with renal manifestations | OR: 1.8 β: 0.6 (0.1) |
— | — | — | — |
| PPM016476 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Ischemic Heart Disease | OR: 1.4 β: 0.3 (0.1) |
— | — | — | — |
| PPM016477 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic ulcer of skin | OR: 1.6 β: 0.4 (0.1) |
— | — | — | — |
| PPM016478 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Superficial cellulitis and abscess | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016479 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 2 diabetes with ophthalmic manifestations | OR: 1.9 β: 0.6 (0.1) |
— | — | — | — |
| PPM016484 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Pulmonary collapse; interstitial and compensatory emphysema | OR: 1.4 β: 0.3 (0.1) |
— | — | — | — |
| PPM016488 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Spinal stenosis of lumbar region | OR: 1.5 β: 0.4 (0.1) |
— | — | — | — |
| PPM016489 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic renal failure | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016490 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Diabetic retinopathy | OR: 1.7 β: 0.6 (0.1) |
— | — | — | — |
| PPM016491 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cardiac dysrhythmias | OR: 1.3 β: 0.2 (0.1) |
— | — | — | — |
| PPM016492 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Ventral hernia | OR: 1.8 β: 0.6 (0.1) |
— | — | — | — |
| PPM016494 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Spinal stenosis | OR: 1.4 β: 0.3 (0.1) |
— | — | — | — |
| PPM016495 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Iron deficiency anemias | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016498 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypertensive heart and/or renal disease | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016502 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Gout | OR: 1.4 β: 0.4 (0.1) |
— | — | — | — |
| PPM016503 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Polycystic ovaries | OR: 2.7 β: 1.0 (0.3) |
— | — | — | — |
| PPM016504 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Bacterial infection NOS | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016505 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Disorders of adrenal glands | OR: 1.6 β: 0.5 (0.1) |
— | — | — | — |
| PPM016506 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Disorders of lipoid metabolism | OR: 1.2 β: 0.2 (0.1) |
— | — | — | — |
| PPM016507 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Diabetes type 2 with peripheral circulatory disorders | OR: 1.8 β: 0.6 (0.2) |
— | — | — | — |
| PPM016508 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 1 diabetes with neurological manifestations | OR: 2.0 β: 0.7 (0.2) |
— | — | — | — |
| PPM016509 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other forms of chronic heart disease | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016510 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic Kidney Disease, Stage IV | OR: 1.5 β: 0.4 (0.1) |
— | — | — | — |
| PPM016511 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Ovarian dysfunction | OR: 2.2 β: 0.8 (0.2) |
— | — | — | — |
| PPM016513 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Iron deficiency anemias, unspecified or not due to blood loss | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016514 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Gout and other crystal arthropathies | OR: 1.4 β: 0.3 (0.1) |
— | — | — | — |
| PPM016515 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Intervertebral disc disorders | OR: 1.2 β: 0.2 (0.1) |
— | — | — | — |
| PPM016516 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Mood disorders | OR: 1.2 β: 0.2 (0.1) |
— | — | — | — |
| PPM016517 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypothyroidism | OR: 1.3 β: 0.2 (0.1) |
— | — | — | — |
| PPM016518 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Unstable angina (intermediate coronary syndrome) | OR: 1.4 β: 0.3 (0.1) |
— | — | — | — |
| PPM016519 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cholelithiasis with other cholecystitis | OR: 1.6 β: 0.5 (0.1) |
— | — | — | — |
| PPM016520 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypertensive chronic kidney disease | OR: 1.3 β: 0.2 (0.1) |
— | — | — | — |
| PPM016521 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Acute pulmonary heart disease | OR: 1.5 β: 0.4 (0.1) |
— | — | — | — |
| PPM016522 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Depression | OR: 1.2 β: 0.2 (0.1) |
— | — | — | — |
| PPM016523 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Nonspecific chest pain | OR: 1.2 β: 0.2 (0.1) |
— | — | — | — |
| PPM016525 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Sleep disorders | OR: 1.2 β: 0.2 (0.1) |
— | — | — | — |
| PPM016526 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypoventilation | OR: 1.6 β: 0.5 (0.2) |
— | — | — | — |
| PPM016527 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Heart failure NOS | OR: 1.4 β: 0.3 (0.1) |
— | — | — | — |
| PPM016528 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypothyroidism | OR: 1.2 β: 0.2 (0.1) |
— | — | — | — |
| PPM016529 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Umbilical hernia | OR: 1.5 β: 0.4 (0.2) |
— | — | — | — |
| PPM016530 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cardiomyopathy | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016531 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Calcaneal spur; Exostosis | OR: 1.4 β: 0.3 (0.1) |
— | — | — | — |
| PPM016532 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Pulmonary embolism and infarction, acute | OR: 1.4 β: 0.4 (0.1) |
— | — | — | — |
| PPM016533 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Spondylosis without myelopathy | OR: 1.2 β: 0.2 (0.1) |
— | — | — | — |
| PPM016399 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic Kidney Disease, Stage IV | OR: 1.54 β: 0.43 (0.13) |
— | — | — | — |
| PPM016329 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cardiac pacemaker/device in situ | OR: 1.68 β: 0.52 (0.1) |
— | — | — | — |
| PPM016284 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: BMI | — | — | R²: 0.0192 | — | — |
| PPM016286 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Morbid obesity | OR: 6.08 β: 1.8 (0.08) |
— | — | — | — |
| PPM016287 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Obesity | OR: 3.48 β: 1.25 (0.06) |
— | — | — | — |
| PPM016289 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Bariatric surgery | OR: 7.85 β: 2.06 (0.15) |
— | — | — | — |
| PPM016290 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 2 diabetes | OR: 1.99 β: 0.69 (0.06) |
— | — | — | — |
| PPM016291 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Sleep apnea | OR: 2.24 β: 0.81 (0.07) |
— | — | — | — |
| PPM016292 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Diabetes mellitus | OR: 1.95 β: 0.67 (0.06) |
— | — | — | — |
| PPM016293 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Eating disorder | OR: 6.44 β: 1.86 (0.17) |
— | — | — | — |
| PPM016294 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypertension | OR: 1.82 β: 0.6 (0.06) |
— | — | — | — |
| PPM016295 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Obstructive sleep apnea | OR: 2.13 β: 0.76 (0.08) |
— | — | — | — |
| PPM016296 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Essential hypertension | OR: 1.79 β: 0.58 (0.06) |
— | — | — | — |
| PPM016297 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Gastrointestinal complications | OR: 2.72 β: 1.0 (0.12) |
— | — | — | — |
| PPM016298 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other chronic nonalcoholic liver disease | OR: 2.17 β: 0.77 (0.09) |
— | — | — | — |
| PPM016300 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Insulin pump user | OR: 2.15 β: 0.77 (0.1) |
— | — | — | — |
| PPM016301 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Edema | OR: 1.56 β: 0.44 (0.06) |
— | — | — | — |
| PPM016302 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 1 diabetes | OR: 1.9 β: 0.64 (0.09) |
— | — | — | — |
| PPM016303 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 2 diabetes with neurological manifestations | OR: 1.96 β: 0.67 (0.1) |
— | — | — | — |
| PPM016304 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Localized adiposity | OR: 5.12 β: 1.63 (0.25) |
— | — | — | — |
| PPM016305 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other disorders of intestine | OR: 1.67 β: 0.51 (0.08) |
— | — | — | — |
| PPM016306 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Acute renal failure | OR: 1.61 β: 0.47 (0.07) |
— | — | — | — |
| PPM016307 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Osteoarthrosis | OR: 1.45 β: 0.37 (0.06) |
— | — | — | — |
| PPM016308 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Osteoarthrosis NOS | OR: 1.45 β: 0.37 (0.06) |
— | — | — | — |
| PPM016310 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Osteoarthrosis, localized, primary | OR: 1.66 β: 0.51 (0.09) |
— | — | — | — |
| PPM016311 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Renal failure | OR: 1.43 β: 0.36 (0.06) |
— | — | — | — |
| PPM016312 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Shortness of breath | OR: 1.38 β: 0.32 (0.06) |
— | — | — | — |
| PPM016313 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Polyneuropathy in diabetes | OR: 1.87 β: 0.63 (0.11) |
— | — | — | — |
| PPM016314 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Encounter for long-term (current) use of anticoagulants | OR: 1.48 β: 0.4 (0.07) |
— | — | — | — |
| PPM016315 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Coronary atherosclerosis | OR: 1.42 β: 0.35 (0.06) |
— | — | — | — |
| PPM016316 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cardiomegaly | OR: 1.51 β: 0.41 (0.07) |
— | — | — | — |
| PPM016317 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Congestive heart failure (CHF) NOS | OR: 1.49 β: 0.4 (0.07) |
— | — | — | — |
| PPM016318 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | OR: 1.45 β: 0.37 (0.07) |
— | — | — | — |
| PPM016319 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Respiratory failure | OR: 1.68 β: 0.52 (0.1) |
— | — | — | — |
| PPM016321 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Pulmonary heart disease | OR: 1.52 β: 0.42 (0.08) |
— | — | — | — |
| PPM016322 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Heart failure with reduced EF [Systolic or combined heart failure] | OR: 1.72 β: 0.54 (0.1) |
— | — | — | — |
| PPM016323 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Atrial fibrillation and flutter | OR: 1.45 β: 0.37 (0.07) |
— | — | — | — |
| PPM016324 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 2 diabetes with renal manifestations | OR: 1.76 β: 0.57 (0.11) |
— | — | — | — |
| PPM016325 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Panniculitis | OR: 4.3 β: 1.46 (0.29) |
— | — | — | — |
| PPM016336 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Incisional hernia | OR: 2.14 β: 0.76 (0.16) |
— | — | — | — |
| PPM016337 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Septicemia | OR: 1.53 β: 0.43 (0.09) |
— | — | — | — |
| PPM016338 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic pulmonary heart disease | OR: 1.56 β: 0.44 (0.1) |
— | — | — | — |
| PPM016339 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Postoperative infection | OR: 1.64 β: 0.49 (0.11) |
— | — | — | — |
| PPM016340 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other arthropathies | OR: 1.39 β: 0.33 (0.07) |
— | — | — | — |
| PPM016341 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cholelithiasis | OR: 1.53 β: 0.43 (0.09) |
— | — | — | — |
| PPM016343 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Dysmetabolic syndrome X | OR: 2.4 β: 0.88 (0.19) |
— | — | — | — |
| PPM016344 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cholelithiasis and cholecystitis | OR: 1.49 β: 0.4 (0.09) |
— | — | — | — |
| PPM016345 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Pulmonary collapse; interstitial and compensatory emphysema | OR: 1.38 β: 0.32 (0.07) |
— | — | — | — |
| PPM016346 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other chronic ischemic heart disease, unspecified | OR: 1.43 β: 0.35 (0.08) |
— | — | — | — |
| PPM016347 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Osteoarthritis; localized | OR: 1.35 β: 0.3 (0.07) |
— | — | — | — |
| PPM016348 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic ulcer of leg or foot | OR: 1.64 β: 0.49 (0.11) |
— | — | — | — |
| PPM016349 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cellulitis and abscess of leg, except foot | OR: 1.57 β: 0.45 (0.1) |
— | — | — | — |
| PPM016350 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Spinal stenosis of lumbar region | OR: 1.52 β: 0.42 (0.1) |
— | — | — | — |
| PPM016351 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cardiac pacemaker in situ | OR: 1.66 β: 0.51 (0.12) |
— | — | — | — |
| PPM016352 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic renal failure [CKD] | OR: 1.34 β: 0.3 (0.07) |
— | — | — | — |
| PPM016354 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Dependence on respirator [Ventilator] or supplemental oxygen | OR: 2.04 β: 0.71 (0.17) |
— | — | — | — |
| PPM016355 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cardiac defibrillator in situ | OR: 1.87 β: 0.63 (0.15) |
— | — | — | — |
| PPM016356 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cardiac dysrhythmias | OR: 1.25 β: 0.22 (0.05) |
— | — | — | — |
| PPM016357 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Osteomyelitis | OR: 1.91 β: 0.65 (0.15) |
— | — | — | — |
| PPM016358 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Swelling of limb | OR: 1.34 β: 0.29 (0.07) |
— | — | — | — |
| PPM016359 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Asthma | OR: 1.32 β: 0.28 (0.07) |
— | — | — | — |
| PPM016361 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Ventral hernia | OR: 1.84 β: 0.61 (0.15) |
— | — | — | — |
| PPM016362 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Decubitus ulcer | OR: 1.75 β: 0.56 (0.14) |
— | — | — | — |
| PPM016363 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Pulmonary congestion and hypostasis | OR: 1.56 β: 0.44 (0.11) |
— | — | — | — |
| PPM016364 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Spinal stenosis | OR: 1.41 β: 0.35 (0.09) |
— | — | — | — |
| PPM016365 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Iron deficiency anemias | OR: 1.34 β: 0.29 (0.07) |
— | — | — | — |
| PPM016366 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Wheezing | OR: 1.52 β: 0.42 (0.1) |
— | — | — | — |
| PPM016367 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Intestinal malabsorption (non-celiac) | OR: 2.08 β: 0.73 (0.18) |
— | — | — | — |
| PPM016368 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Portal hypertension | OR: 2.55 β: 0.94 (0.24) |
— | — | — | — |
| PPM016369 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Myocardial infarction | OR: 1.35 β: 0.3 (0.08) |
— | — | — | — |
| PPM016370 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Fluid overload | OR: 1.52 β: 0.42 (0.11) |
— | — | — | — |
| PPM016371 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hyperlipidemia | OR: 1.25 β: 0.22 (0.06) |
— | — | — | — |
| PPM016372 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypertensive heart and/or renal disease | OR: 1.3 β: 0.26 (0.07) |
— | — | — | — |
| PPM016373 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic tonsillitis and adenoiditis | OR: 2.02 β: 0.7 (0.18) |
— | — | — | — |
| PPM016374 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Abnormal weight gain | OR: 1.51 β: 0.41 (0.11) |
— | — | — | — |
| PPM016375 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Dermatophytosis of nail | OR: 1.38 β: 0.32 (0.09) |
— | — | — | — |
| PPM016376 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Barrett's esophagus | OR: 2.19 β: 0.78 (0.21) |
— | — | — | — |
| PPM016377 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Degeneration of intervertebral disc | OR: 1.3 β: 0.27 (0.07) |
— | — | — | — |
| PPM016379 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Heart failure with preserved EF [Diastolic heart failure] | OR: 1.49 β: 0.4 (0.11) |
— | — | — | — |
| PPM016380 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Deep vein thrombosis | OR: 1.52 β: 0.42 (0.11) |
— | — | — | — |
| PPM016381 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other symptoms of respiratory system | OR: 1.21 β: 0.19 (0.05) |
— | — | — | — |
| PPM016382 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Gout | OR: 1.42 β: 0.35 (0.1) |
— | — | — | — |
| PPM016383 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Polycystic ovaries | OR: 2.7 β: 0.99 (0.27) |
— | — | — | — |
| PPM016384 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Sinoatrial node dysfunction (Bradycardia) | OR: 1.62 β: 0.48 (0.13) |
— | — | — | — |
| PPM016385 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Bacterial infection NOS | OR: 1.31 β: 0.27 (0.07) |
— | — | — | — |
| PPM016386 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Disorders of adrenal glands | OR: 1.63 β: 0.49 (0.13) |
— | — | — | — |
| PPM016387 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Disorders of lipoid metabolism | OR: 1.23 β: 0.21 (0.06) |
— | — | — | — |
| PPM016388 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Mixed hyperlipidemia | OR: 1.31 β: 0.27 (0.08) |
— | — | — | — |
| PPM016389 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Corns and callosities | OR: 1.49 β: 0.4 (0.11) |
— | — | — | — |
| PPM016390 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Acquired acanthosis nigricans | OR: 3.19 β: 1.16 (0.32) |
— | — | — | — |
| PPM016391 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Paroxysmal ventricular tachycardia | OR: 1.51 β: 0.41 (0.12) |
— | — | — | — |
| PPM016392 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Atrial flutter | OR: 1.51 β: 0.41 (0.12) |
— | — | — | — |
| PPM016393 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Vitamin deficiency | OR: 1.28 β: 0.24 (0.07) |
— | — | — | — |
| PPM016395 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Osteomyelitis, periostitis, and other infections involving bone | OR: 1.62 β: 0.48 (0.14) |
— | — | — | — |
| PPM016396 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Dermatophytosis | OR: 1.29 β: 0.25 (0.07) |
— | — | — | — |
| PPM016397 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 1 diabetes with neurological manifestations | OR: 1.99 β: 0.69 (0.2) |
— | — | — | — |
| PPM016398 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other forms of chronic heart disease | OR: 1.34 β: 0.29 (0.08) |
— | — | — | — |
| PPM016400 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Encounter for long-term (current) use of aspirin | OR: 1.34 β: 0.29 (0.09) |
— | — | — | — |
| PPM016401 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Ovarian dysfunction | OR: 2.18 β: 0.78 (0.23) |
— | — | — | — |
| PPM016402 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Acquired foot deformities | OR: 1.32 β: 0.28 (0.08) |
— | — | — | — |
| PPM016404 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Gout and other crystal arthropathies | OR: 1.35 β: 0.3 (0.09) |
— | — | — | — |
| PPM016405 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Intervertebral disc disorders | OR: 1.24 β: 0.22 (0.06) |
— | — | — | — |
| PPM016406 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Mood disorders | OR: 1.21 β: 0.19 (0.06) |
— | — | — | — |
| PPM016407 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypothyroidism NOS | OR: 1.25 β: 0.23 (0.07) |
— | — | — | — |
| PPM016408 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Arrhythmia (cardiac) NOS | OR: 1.26 β: 0.23 (0.07) |
— | — | — | — |
| PPM016409 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Dermatophytosis / Dermatomycosis | OR: 1.26 β: 0.23 (0.07) |
— | — | — | — |
| PPM016410 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Unstable angina (intermediate coronary syndrome) | OR: 1.35 β: 0.3 (0.09) |
— | — | — | — |
| PPM016411 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Thoracic or lumbosacral neuritis or radiculitis, unspecified | OR: 1.33 β: 0.28 (0.09) |
— | — | — | — |
| PPM016412 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other dyspnea | OR: 1.2 β: 0.18 (0.06) |
— | — | — | — |
| PPM016413 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Abnormal coagulation profile | OR: 1.52 β: 0.42 (0.13) |
— | — | — | — |
| PPM016414 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cholelithiasis with other cholecystitis | OR: 1.61 β: 0.47 (0.15) |
— | — | — | — |
| PPM016415 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Dislocation | OR: 1.37 β: 0.31 (0.1) |
— | — | — | — |
| PPM016416 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Vitamin D deficiency | OR: 1.26 β: 0.23 (0.07) |
— | — | — | — |
| PPM016417 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypertensive chronic kidney disease | OR: 1.28 β: 0.24 (0.08) |
— | — | — | — |
| PPM016418 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Flat foot | OR: 1.61 β: 0.48 (0.15) |
— | — | — | — |
| PPM016330 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other venous embolism and thrombosis | OR: 1.47 β: 0.39 (0.08) |
— | — | — | — |
| PPM016331 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic ulcer of skin | OR: 1.55 β: 0.44 (0.09) |
— | — | — | — |
| PPM016332 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Non-healing surgical wound | OR: 3.16 β: 1.15 (0.23) |
— | — | — | — |
| PPM016333 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Arthropathy NOS | OR: 1.43 β: 0.36 (0.07) |
— | — | — | — |
| PPM016334 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Superficial cellulitis and abscess | OR: 1.35 β: 0.3 (0.06) |
— | — | — | — |
| PPM016419 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hypertensive heart disease | OR: 1.35 β: 0.3 (0.1) |
— | — | — | — |
| PPM016420 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic obstructive asthma | OR: 1.56 β: 0.45 (0.14) |
— | — | — | — |
| PPM016421 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Respiratory abnormalities | OR: 1.37 β: 0.32 (0.1) |
— | — | — | — |
| PPM016422 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Acute pulmonary heart disease | OR: 1.46 β: 0.38 (0.12) |
— | — | — | — |
| PPM016434 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Hereditary and idiopathic peripheral neuropathy | OR: 1.3 β: 0.26 (0.09) |
— | — | — | — |
| PPM016448 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | OR: 3.0 β: 1.1 (0.1) |
— | — | — | — |
| PPM016458 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 2 diabetes with neurological manifestations | OR: 2.0 β: 0.7 (0.1) |
— | — | — | — |
| PPM016470 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Congestive heart failure; nonhypertensive | OR: 1.5 β: 0.4 (0.1) |
— | — | — | — |
| PPM016483 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Cholelithiasis and cholecystitis | OR: 1.5 β: 0.4 (0.1) |
— | — | — | — |
| PPM016493 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Pulmonary congestion and hypostasis | OR: 1.6 β: 0.4 (0.1) |
— | — | — | — |
| PPM016500 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Degeneration of intervertebral disc | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016501 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other symptoms of respiratory system | OR: 1.2 β: 0.2 (0.1) |
— | — | — | — |
| PPM016512 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Acquired foot deformities | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016524 | PGS003400 (PRS97_obesity) |
PSS010096| Multi-ancestry (including European)| 65,174 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Nonrheumatic aortic valve disorders | OR: 1.3 β: 0.3 (0.1) |
— | — | — | — |
| PPM016288 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Overweight, obesity and other hyperalimentation | OR: 3.02 β: 1.1 (0.05) |
— | — | — | — |
| PPM016299 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic liver disease and cirrhosis | OR: 2.1 β: 0.74 (0.09) |
— | — | — | — |
| PPM016309 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Respiratory failure, insufficiency, arrest | OR: 1.63 β: 0.49 (0.08) |
— | — | — | — |
| PPM016320 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Chronic venous insufficiency [CVI] | OR: 1.76 β: 0.57 (0.11) |
— | — | — | — |
| PPM016335 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Type 2 diabetes with ophthalmic manifestations | OR: 1.91 β: 0.65 (0.13) |
— | — | — | — |
| PPM016342 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Other disorders of the kidney and ureters | OR: 1.37 β: 0.31 (0.07) |
— | — | — | — |
| PPM016353 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Diabetic retinopathy | OR: 1.74 β: 0.55 (0.13) |
— | — | — | — |
| PPM016360 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Encounter for long-term (current) use of anticoagulants, antithrombotics, aspirin | OR: 1.41 β: 0.34 (0.08) |
— | — | — | — |
| PPM016378 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Infection/inflammation of internal prosthetic device; implant; and graft | OR: 1.57 β: 0.45 (0.12) |
— | — | — | — |
| PPM016394 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Diabetes type 2 with peripheral circulatory disorders | OR: 1.84 β: 0.61 (0.17) |
— | — | — | — |
| PPM016403 | PGS003400 (PRS97_obesity) |
PSS010097| Multi-ancestry (including European)| 405,432 individuals |
PGP000416 | Robinson JR et al. Obesity (Silver Spring) (2022) |
Reported Trait: Iron deficiency anemias, unspecified or not due to blood loss | OR: 1.3 β: 0.27 (0.08) |
— | — | — | — |
| PPM017036 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: Fasting glucose x BMI interaction | β: 89.0 | — | — | age, BMI, education level, birth region (South Asia vs. other), parity, parental history of diabetes, and genetic PC axes 1-5 | — |
| PPM017037 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: Fasting glucose x Born in South Asia interaction | β: 84.0 | — | — | age, BMI, education level, birth region (South Asia vs. other), parity, parental history of diabetes, and genetic PC axes 1-5 | — |
| PPM017038 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: Fasting glucose x Low diet quality interaction (only in START cohort) | β: 0.141 [0.053, 0.228] | — | — | age, BMI, education level, birth region (South Asia vs. other), parity, parental history of diabetes, and genetic PC axes 1-5 | — |
| PPM017039 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: AUC glucose x BMI interaction | β: 77.0 | — | — | age, BMI, education level, birth region (South Asia vs. other), parity, parental history of diabetes, and genetic PC axes 1-5 | — |
| PPM017040 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: GDM (IADPSG criteria) x BMI interaction | OR: 0.0 | — | — | age, BMI, education level, birth region (South Asia vs. other), parity, parental history of diabetes, and genetic PC axes 1-5 | — |
| PPM017032 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: Fasting glucose | β: 0.085 [0.067, 0.103] | — | — | first five principal components (PCs) | — |
| PPM017033 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: 2h postload glucose | β: 0.207 [0.157, 0.257] | — | — | first five principal components (PCs) | — |
| PPM017034 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: AUC glucose | β: 0.155 [0.125, 0.184] | — | — | first five principal components (PCs) | — |
| PPM017035 | PGS003402 (PRS_T2D) |
PSS010101| South Asian Ancestry| 3,712 individuals |
PGP000419 | Lamri A et al. Elife (2022) |
Reported Trait: GDM (IADPSG criteria) | OR: 1.45 [1.32, 1.6] | — | — | first five principal components (PCs) | — |
| PPM017182 | PGS003443 (PRScsx_T2D_LAT_EURweights) |
PSS010157| Hispanic or Latin American Ancestry| 1,484 individuals |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Reported Trait: type 2 diabetes | OR: 1.9 [1.65, 2.19] | AUROC: 0.7475 | R²: 0.207 | sex, age, PCs(1-10), PRScsx_T2D_LAT_EASweights, PRScsx_T2D_LAT_LATweights | NOTE: Performance is based on a linear combination of this PGS with PRScsx_T2D_LAT_EASweights and PRScsx_T2D_LAT_LATweights (metascore=(zscoreEUR* 0.531117)+(zscoreEAS*0.5690198)+(zscoreLAT*0.1465538)). See score development details for how to apply |
| PPM017183 | PGS003444 (PRScsx_T2D_LAT_EASweights) |
PSS010157| Hispanic or Latin American Ancestry| 1,484 individuals |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Reported Trait: type 2 diabetes | OR: 1.9 [1.65, 2.19] | AUROC: 0.7475 | R²: 0.207 | sex, age, PCs(1-10), PRScsx_T2D_LAT_EURweights, PRScsx_T2D_LAT_LATweights | NOTE: Performance is based on a linear combination of this PGS with PRScsx_T2D_LAT_EASweights and PRScsx_T2D_LAT_LATweights (metascore=(zscoreEUR* 0.531117)+(zscoreEAS*0.5690198)+(zscoreLAT*0.1465538)). See score development details for how to apply |
| PPM017184 | PGS003445 (PRScsx_T2D_LAT_LATweights) |
PSS010157| Hispanic or Latin American Ancestry| 1,484 individuals |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Reported Trait: type 2 diabetes | OR: 1.9 [1.65, 2.19] | AUROC: 0.7475 | R²: 0.207 | sex, age, PCs(1-10), PRScsx_T2D_LAT_EURweights, PRScsx_T2D_LAT_EASweights | NOTE: Performance is based on a linear combination of this PGS with PRScsx_T2D_LAT_EASweights and PRScsx_T2D_LAT_LATweights (metascore=(zscoreEUR* 0.531117)+(zscoreEAS*0.5690198)+(zscoreLAT*0.1465538)). See score development details for how to apply |
| PPM017228 | PGS003452 (PRS2_WM) |
PSS010176| European Ancestry| 20,134 individuals |
PGP000448 | Berndt SI et al. Leukemia (2022) |
Reported Trait: Chronic lymphocytic leukemia | OR: 1.07 [1.01, 1.14] | — | — | — | — |
| PPM017236 | PGS003452 (PRS2_WM) |
PSS010176| European Ancestry| 20,134 individuals |
PGP000448 | Berndt SI et al. Leukemia (2022) |
Reported Trait: Diffuse large B-cell lymphoma | OR: 1.24 [1.18, 1.31] | — | — | — | — |
| PPM017244 | PGS003452 (PRS2_WM) |
PSS010176| European Ancestry| 20,134 individuals |
PGP000448 | Berndt SI et al. Leukemia (2022) |
Reported Trait: Follicular lymphoma | OR: 1.12 [1.05, 1.19] | — | — | — | — |
| PPM017252 | PGS003452 (PRS2_WM) |
PSS010176| European Ancestry| 20,134 individuals |
PGP000448 | Berndt SI et al. Leukemia (2022) |
Reported Trait: Marginal zone lymphoma | OR: 1.18 [1.07, 1.3] | — | — | — | — |
| PPM018476 | PGS003728 (PS_T2D_183-AGEN) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.28 [1.12, 1.46] | — | Net reclassification improvement: 0.331 [0.141, 0.521] ∆AUC: 0.005 [-0.003, 0.012] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018484 | PGS003728 (PS_T2D_183-AGEN) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.27 [1.15, 1.39] | — | Net reclassification improvement: 0.164 [0.025, 0.303] ∆AUC: 0.037 [0.013, 0.06] |
sex, parental diabetes, and birth weight | — |
| PPM018468 | PGS003728 (PS_T2D_183-AGEN) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.14 [1.06, 1.24] | — | Net reclassification improvement: 0.115 [-0.014, 0.244] ∆AUC: 0.001 [-0.003, 0.005] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018469 | PGS003729 (PS_T2D_293-DIAGRAM) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.27 [1.17, 1.38] | AUROC: 0.735 | Net reclassification improvement: 0.27 [0.149, 0.392] ∆AUC: 0.007 [0.001, 0.014] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018477 | PGS003729 (PS_T2D_293-DIAGRAM) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.49 [1.29, 1.72] | AUROC: 0.812 | Net reclassification improvement: 0.268 [0.072, 0.464] ∆AUC: 0.007 [-0.003, 0.017] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018485 | PGS003729 (PS_T2D_293-DIAGRAM) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.48 [1.35, 1.63] | AUROC: 0.685 | Net reclassification improvement: 0.362 [0.222, 0.502] ∆AUC: 0.072 [0.045, 0.099] |
sex, parental diabetes, and birth weight | — |
| PPM018471 | PGS003730 (PS_T2D_287-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.2 [1.1, 1.3] | — | Net reclassification improvement: 0.216 [0.094, 0.338] ∆AUC: 0.004 [-0.001, 0.009] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018479 | PGS003730 (PS_T2D_287-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.34 [1.17, 1.54] | — | Net reclassification improvement: 0.314 [0.116, 0.512] ∆AUC: 0.004 [-0.001, 0.009] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018487 | PGS003730 (PS_T2D_287-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.45 [1.32, 1.6] | — | Net reclassification improvement: 0.259 [0.115, 0.403] ∆AUC: 0.073 |
sex, parental diabetes, and birth weight | — |
| PPM018475 | PGS003731 (PS_T2D_282-SAS-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.19 [1.09, 1.29] | — | Net reclassification improvement: 0.181 [0.054, 0.308] ∆AUC: 0.004 [-0.001, 0.009] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018483 | PGS003731 (PS_T2D_282-SAS-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.35 [1.18, 1.56] | — | Net reclassification improvement: 0.302 [0.089, 0.515] ∆AUC: 0.002 [-0.007, 0.012] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018491 | PGS003731 (PS_T2D_282-SAS-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.32 [1.2, 1.45] | — | Net reclassification improvement: 0.201 [0.057, 0.306] ∆AUC: 0.054 [0.031, 0.077] |
sex, parental diabetes, and birth weight | — |
| PPM018474 | PGS003732 (PS_T2D_287-HIS-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.18 [1.09, 1.29] | — | Net reclassification improvement: 0.219 [0.097, 0.34] ∆AUC: 0.004 [-0.001, 0.008] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018482 | PGS003732 (PS_T2D_287-HIS-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.32 [1.15, 1.51] | — | Net reclassification improvement: 0.15 [-0.054, 0.354] ∆AUC: 0.006 [-0.001, 0.014] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018490 | PGS003732 (PS_T2D_287-HIS-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.4 [1.28, 1.55] | — | Net reclassification improvement: 0.277 [0.125, 0.428] ∆AUC: 0.072 [0.046, 0.099] |
sex, parental diabetes, and birth weight | — |
| PPM018473 | PGS003733 (PS_T2D_287-EUR-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.21 [1.12, 1.32] | — | Net reclassification improvement: 0.277 [0.156, 0.397] ∆AUC: 0.005 [0.0, 0.011] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018481 | PGS003733 (PS_T2D_287-EUR-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.37 [1.19, 1.58] | — | Net reclassification improvement: 0.296 [0.09, 0.502] ∆AUC: 0.008 [-0.001, 0.017] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018489 | PGS003733 (PS_T2D_287-EUR-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.47 [1.33, 1.62] | — | Net reclassification improvement: 0.328 [0.183, 0.474] ∆AUC: 0.075 [0.048, 0.102] |
sex, parental diabetes, and birth weight | — |
| PPM018472 | PGS003734 (PS_T2D_280-EAS-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.13 [1.04, 1.23] | — | Net reclassification improvement: 0.115 [-0.014, 0.244] ∆AUC: 0.001 [-0.002, 0.005] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018480 | PGS003734 (PS_T2D_280-EAS-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.19 [1.04, 1.36] | — | Net reclassification improvement: 0.182 [-0.019, 0.383] ∆AUC: 0.001 [-0.004, 0.007] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018488 | PGS003734 (PS_T2D_280-EAS-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.33 [1.22, 1.46] | — | Net reclassification improvement: 0.176 [0.029, 0.323] ∆AUC: 0.052 [0.026, 0.077] |
sex, parental diabetes, and birth weight | — |
| PPM018470 | PGS003735 (PS_T2D_276-AFR-DIAMANTE) |
PSS010982| Additional Diverse Ancestries| 2,333 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (adult cohort at 10 year follow-up) | HR: 1.13 [1.04, 1.22] | — | ∆AUC: 0.003 [0.0, 0.007] Net reclassification improvement: 0.181 [0.047, 0.316] |
age, sex, parental diabetes, BMI, fasting plasma glucose and HbA1c. | — |
| PPM018478 | PGS003735 (PS_T2D_276-AFR-DIAMANTE) |
PSS010984| Additional Diverse Ancestries| 2,229 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (youth cohort at 10 year follow-up) | HR: 1.21 [1.06, 1.38] | — | Net reclassification improvement: 0.185 [-0.017, 0.388] ∆AUC: 0.005 [-0.001, 0.01] |
age, sex, parental diabetes, modified BMI z score, fasting plasma glucose | — |
| PPM018486 | PGS003735 (PS_T2D_276-AFR-DIAMANTE) |
PSS010983| Additional Diverse Ancestries| 2,894 individuals |
PGP000469 | Wedekind LE et al. Diabetologia (2023) |
Reported Trait: Incident type 2 diabetes (birth cohort at 30 year follow-up) | HR: 1.28 [1.16, 1.41] | — | Net reclassification improvement: 0.231 [0.091, 0.376] ∆AUC: 0.042 [0.019, 0.065] |
sex, parental diabetes, and birth weight | — |
| PPM018508 | PGS003749 (ModelT1D_under25) |
PSS011001| European Ancestry| 119,273 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Type 1 diabetes with age of diagnosis under 25 | — | AUROC: 0.797 | Nagelkerke R2: 0.099 | — | — |
| PPM018512 | PGS003749 (ModelT1D_under25) |
PSS011000| European Ancestry| 7,067 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Discrimination of Type 1 diabetes from Type 2 diabetes | — | AUROC: 0.792 | — | — | — |
| PPM018514 | PGS003749 (ModelT1D_under25) |
PSS010998| European Ancestry| 2,494 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Discrimination of Type 1 diabetes from Type 2 diabetes | — | AUROC: 0.686 | — | — | — |
| PPM018509 | PGS003750 (ModelT1D) |
PSS010999| European Ancestry| 120,028 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.64 | Nagelkerke R2: 0.014 | — | — |
| PPM018510 | PGS003751 (ModelT2D_over45) |
PSS011003| European Ancestry| 122,144 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Type 2 diabetes with age of diagnosis over 45 | — | AUROC: 0.596 | Nagelkerke R2: 0.016 | — | — |
| PPM018513 | PGS003751 (ModelT2D_over45) |
PSS011000| European Ancestry| 7,067 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Discrimination of Type 1 diabetes from Type 2 diabetes | — | AUROC: 0.527 | — | — | — |
| PPM018511 | PGS003752 (ModelT2D) |
PSS011002| European Ancestry| 125,189 individuals |
PGP000472 | Shoaib M et al. Genet Epidemiol (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.578 | Nagelkerke R2: 0.014 | — | — |
| PPM018759 | PGS003867 (T2D_PRScs_ARB) |
PSS011097| Greater Middle Eastern Ancestry| 2,669 individuals |
PGP000501 | Shim I et al. Nature Communications (2023) |
Reported Trait: Type 2 diabetes | OR: 1.83 [1.74, 1.92] | AUROC: 0.7384 [0.7194, 0.7574] | — | age, sex, array version, and the first 10 principal components of ancestry | — |
| PPM019108 | PGS003959 (GRS940_obesity) |
PSS011184| Multi-ancestry (including European)| 27,429 individuals |
PGP000507 | Liu X et al. Clin Nutr (2023) |
Reported Trait: Abdominal obesity | β: 0.078 (0.019) | — | — | Age, sex, race, centres, education, Townsend deprivation index, household income, smoking, alcohol consumption, physical activity, sleep pattern, energy intake, and BMI, WC or BF% at baseline | — |
| PPM019109 | PGS003959 (GRS940_obesity) |
PSS011184| Multi-ancestry (including European)| 27,429 individuals |
PGP000507 | Liu X et al. Clin Nutr (2023) |
Reported Trait: Body mass index increase | β: 0.157 (0.013) | — | — | Age, sex, race, centres, education, Townsend deprivation index, household income, smoking, alcohol consumption, physical activity, sleep pattern, energy intake, and BMI, WC or BF% at baseline | — |
| PPM019110 | PGS003959 (GRS940_obesity) |
PSS011184| Multi-ancestry (including European)| 27,429 individuals |
PGP000507 | Liu X et al. Clin Nutr (2023) |
Reported Trait: Wasit circumference increase | β: 0.213 (0.039) | — | — | Age, sex, race, centres, education, Townsend deprivation index, household income, smoking, alcohol consumption, physical activity, sleep pattern, energy intake, and BMI, WC or BF% at baseline | — |
| PPM019111 | PGS003959 (GRS940_obesity) |
PSS011184| Multi-ancestry (including European)| 27,429 individuals |
PGP000507 | Liu X et al. Clin Nutr (2023) |
Reported Trait: Body fat percentage increase | β: 0.042 (0.021) | — | — | Age, sex, race, centres, education, Townsend deprivation index, household income, smoking, alcohol consumption, physical activity, sleep pattern, energy intake, and BMI, WC or BF% at baseline | — |
| PPM019112 | PGS003959 (GRS940_obesity) |
PSS011184| Multi-ancestry (including European)| 27,429 individuals |
PGP000507 | Liu X et al. Clin Nutr (2023) |
Reported Trait: Obesity with sulfur microbial diet score | — | — | Hazard ratio (HR, Q4 sulphur microbial diet score and high PRS vs. Q1 sulphur microbial diet score and low PRS): 1.74 [1.33, 2.29] | age, sex, race, centers, household income, Townsend deprivation index, smoking, alcohol consumption, physical activity, sleep pattern, energy intake and body mass index or waist circumstance | — |
| PPM019113 | PGS003959 (GRS940_obesity) |
PSS011184| Multi-ancestry (including European)| 27,429 individuals |
PGP000507 | Liu X et al. Clin Nutr (2023) |
Reported Trait: Abdominal obesity with sulfur microbial diet score | — | — | Hazard ratio (HR, Q4 sulphur microbial diet score and high PRS vs. Q1 sulphur microbial diet score and low PRS): 1.41 [1.17, 1.71] | age, sex, race, centers, household income, Townsend deprivation index, smoking, alcohol consumption, physical activity, sleep pattern, energy intake and body mass index or waist circumstance | — |
| PPM019107 | PGS003959 (GRS940_obesity) |
PSS011184| Multi-ancestry (including European)| 27,429 individuals |
PGP000507 | Liu X et al. Clin Nutr (2023) |
Reported Trait: Obesity | β: 0.149 (0.028) | — | — | Age, sex, race, centres, education, Townsend deprivation index, household income, smoking, alcohol consumption, physical activity, sleep pattern, energy intake, and BMI, WC or BF% at baseline | — |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| PPM020104 | PGS004171 (t1d_1) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.7 | — | year of birth, sex | — |
| PPM020105 | PGS004172 (t1d_2) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.71 | — | year of birth, sex | — |
| PPM020106 | PGS004173 (t1d_3) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.71 | — | year of birth, sex | — |
| PPM020107 | PGS004174 (t1d_4) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.71 | — | year of birth, sex | — |
| PPM020108 | PGS004175 (t1d_5) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 1 diabetes | — | AUROC: 0.7 | — | year of birth, sex | — |
| PPM020114 | PGS004181 (t2d_1) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69418 | — | year of birth, sex | — |
| PPM020115 | PGS004182 (t2d_2) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69491 | — | year of birth, sex | — |
| PPM020116 | PGS004183 (t2d_3) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69959 | — | year of birth, sex | — |
| PPM020117 | PGS004184 (t2d_4) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69539 | — | year of birth, sex | — |
| PPM020118 | PGS004185 (t2d_5) |
PSS011296| European Ancestry| 45,334 individuals |
PGP000520 | Raben TG et al. Sci Rep (2023) |
Reported Trait: Type 2 diabetes | — | AUROC: 0.69924 | — | year of birth, sex | — |
| PPM020157 | PGS004222 (GRS13_gout) |
PSS011298| Multi-ancestry (including European)| 403,630 individuals |
PGP000522 | Wu Q et al. J Psychosom Res (2023) |
Reported Trait: Incident gout | — | — | p (interaction between PRS and sleep pattern): 0.043 | Age, sex, race, Townsend deprivation index (TDI), body mass index (BMI), smoking and drinking status, history of hypertension and diabetes, uric acid, total cholesterol, estimated glomerular filtration rate (eGFR) levels, the use of diuretics medications | — |
| PPM020158 | PGS004223 (PRS139_T2D) |
PSS011299| European Ancestry| 395,809 individuals |
PGP000523 | Lin J et al. Sci Total Environ (2023) |
Reported Trait: Incident type 2 diabetes | HR: 1.5 [1.48, 1.52] | — | — | age, gender, education, Townsend deprivation index, smoking status, alcohol consumption, body mass index, total physical activity, dietary pattern, vitamin D supplement, use of sun/UV protection, PM2.5, hypertension, cardiovascular disease, antihypertensive medications use, cholesterol-lowering medications use, and average outdoor light time | — |
| PPM020159 | PGS004223 (PRS139_T2D) |
PSS011299| European Ancestry| 395,809 individuals |
PGP000523 | Lin J et al. Sci Total Environ (2023) |
Reported Trait: Incident type 2 diabetes with outdoor light time in summer | — | — | Hazard ratio (HR, outdoor light time in summer >3h/day and PRS in top tertile vs. outdoor light time in summer <2-3 h/day and PRS in bottom tertile): 2.53 [2.39, 2.69] | Hb1Ac concentrations at baseline | — |
| PPM020160 | PGS004223 (PRS139_T2D) |
PSS011299| European Ancestry| 395,809 individuals |
PGP000523 | Lin J et al. Sci Total Environ (2023) |
Reported Trait: Incident type 2 diabetes with outdoor light time in winter | — | — | Hazard ratio (HR, outdoor light time in winter >2 h/day and PRS in top tertile vs. outdoor light time in winter <1-2 h/day and PRS in bottom tertile): 2.56 [2.42, 2.71] | Hb1Ac concentrations at baseline | — |
| PPM020161 | PGS004223 (PRS139_T2D) |
PSS011299| European Ancestry| 395,809 individuals |
PGP000523 | Lin J et al. Sci Total Environ (2023) |
Reported Trait: Incident type 2 diabetes with outdoor light time on average | — | — | Hazard ratio (HR, outdoor light time on average >2.5 h/day and PRS in top tertile vs. outdoor light time on average 1.5-2.5 h/day and PRS in bottom tertile): 2.52 [2.37, 2.67] | Hb1Ac concentrations at baseline | — |
| PPM020217 | PGS004225 (PRS46_T2DEastAsia) |
PSS011306| East Asian Ancestry| 5,024 individuals |
PGP000526 | Liu J et al. Nutrients (2023) |
Reported Trait: Type 2 diabetes with lifestyle group | — | — | Hazard ratio (HR, poor lifestyle and high PRS vs. ideal lifestyle and low PRS): 3.93 [2.07, 7.44] | — | — |
| PPM020215 | PGS004225 (PRS46_T2DEastAsia) |
PSS011306| East Asian Ancestry| 5,024 individuals |
PGP000526 | Liu J et al. Nutrients (2023) |
Reported Trait: Type 2 diabetes | — | — | Hazard ratio (HR, high vs low quintile): 2.06 [1.42, 2.97] | age, gender, SBP, DBP, FBG, TC, TG, HDLC, and diabetes family history | — |
| PPM020216 | PGS004226 (PRS50_T2DEur) |
PSS011306| East Asian Ancestry| 5,024 individuals |
PGP000526 | Liu J et al. Nutrients (2023) |
Reported Trait: Type 2 diabetes | — | — | Hazard ratio (HR, high vs low quintile): 1.69 [1.17, 2.44] | age, gender, SBP, DBP, FBG, TC, TG, HDLC, and diabetes family history | — |
| PPM020433 | PGS004323 (PRS91_T2D) |
PSS011360| East Asian Ancestry| 2,676 individuals |
PGP000557 | Tan Q et al. J Hazard Mater (2023) |
Reported Trait: Fasting plasma glucose | β: 0.292 [0.181, 0.404] | — | — | Age, gender, BMI, community, and the first 10 principal components of ancestry | — |
| PPM020434 | PGS004323 (PRS91_T2D) |
PSS011360| East Asian Ancestry| 2,676 individuals |
PGP000557 | Tan Q et al. J Hazard Mater (2023) |
Reported Trait: HOMA-beta | β: -0.143 [-0.212, -0.073] | — | — | Age, gender, BMI, community, and the first 10 principal components of ancestry | — |
| PPM020435 | PGS004323 (PRS91_T2D) |
PSS011360| East Asian Ancestry| 2,676 individuals |
PGP000557 | Tan Q et al. J Hazard Mater (2023) |
Reported Trait: Impaired fasting glucose | β: 1.809 [1.362, 2.402] | — | — | Age, gender, BMI, community, and the first 10 principal components of ancestry | — |
| PPM020436 | PGS004323 (PRS91_T2D) |
PSS011360| East Asian Ancestry| 2,676 individuals |
PGP000557 | Tan Q et al. J Hazard Mater (2023) |
Reported Trait: Type 2 diabetes | β: 2.263 [1.72, 2.977] | — | — | Age, gender, BMI, community, and the first 10 principal components of ancestry | — |
| PPM020562 | PGS004447 (disease.E66.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: E66 (Obesity) | OR: 1.3597 | — | — | — | — |
| PPM020563 | PGS004448 (disease.E78.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: E78 (Disorders of lipoprotein metabolism and other lipidaemias) | OR: 1.27887 | — | — | — | — |
| PPM020614 | PGS004499 (disease.T2D.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Type 2 diabetes (T2D) | OR: 1.51252 | — | — | — | — |
| PPM020632 | PGS004517 (meta.E66.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: E66 (Obesity) | OR: 1.22554 | — | — | — | — |
| PPM020633 | PGS004518 (meta.E78.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: E78 (Disorders of lipoprotein metabolism and other lipidaemias) | OR: 1.36819 | — | — | — | — |
| PPM020684 | PGS004569 (meta.T2D.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Type 2 diabetes (T2D) | OR: 1.63182 | — | — | — | — |
| PPM020759 | PGS004602 (PRS424_T2D) |
PSS011395| European Ancestry| 357,419 individuals |
PGP000580 | Zhuang P et al. Diabetes Care (2021) |
Reported Trait: Type 2 diabetes | HR: 1.54 [1.5, 1.58] β: 0.431 (0.014) |
— | — | Age, sex, center, BMI, education, Townsend deprivation index, household income, smoking, alcohol consumption, physical activity, history of hypertension, history of high cholesterol, vitamin supplement use, mineral supplement use, aspirin use, and lipid-lowering medication | — |
| PPM020760 | PGS004602 (PRS424_T2D) |
PSS011395| European Ancestry| 357,419 individuals |
PGP000580 | Zhuang P et al. Diabetes Care (2021) |
Reported Trait: HbA1c | β: 0.544 (0.007) | — | — | Age, sex, center, BMI, education, Townsend deprivation index, household income, smoking, alcohol consumption, physical activity, history of hypertension, history of high cholesterol, vitamin supplement use, mineral supplement use, aspirin use, and lipid-lowering medication | — |
| PPM020779 | PGS004602 (PRS424_T2D) |
PSS011407| Multi-ancestry (including European)| 59,325 individuals |
PGP000587 | Luo M et al. Br J Sports Med (2023) |Ext. |
Reported Trait: Incident type 2 diabetes | — | — | Hazard ratio (HR, high vs low PRS tertile): 2.43 [2.04, 2.9] | Age as the underlying timescale, gender, genotyping array, the first 10 principal components of ancestry, ethnicity, educational attainment, household income, Townsend deprivation index, employment status, assessment center, moking status, alcohol consumption, healthy diet score, hypertension, dyslipidemia, depression, total wear time, seasonality, and total volume of physical activity | — |
| PPM020992 | PGS004767 (gout_PRSmix_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Gout | — | — | Incremental R2 (Full model versus model with only covariates): 0.061 [0.052, 0.071] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM020993 | PGS004768 (gout_PRSmixPlus_eur) |
PSS011465| European Ancestry| 9,462 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Gout | — | — | Incremental R2 (Full model versus model with only covariates): 0.081 [0.071, 0.092] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021062 | PGS004837 (t2d_PRSmix_eur) |
PSS011507| European Ancestry| 7,879 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (Full model versus model with only covariates): 0.099 [0.087, 0.112] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021063 | PGS004838 (t2d_PRSmix_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (Full model versus model with only covariates): 0.061 [0.051, 0.07] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021064 | PGS004839 (t2d_PRSmixPlus_eur) |
PSS011507| European Ancestry| 7,879 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (Full model versus model with only covariates): 0.129 [0.115, 0.143] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021065 | PGS004840 (t2d_PRSmixPlus_sas) |
PSS011474| South Asian Ancestry| 8,837 individuals |
PGP000604 | Truong B et al. Cell Genom (2024) |
Reported Trait: Type 2 diabetes | — | — | Incremental R2 (Full model versus model with only covariates): 0.065 [0.055, 0.075] | age, sex, PC1, PC2, PC3, PC4, PC5, PC6, PC7, PC8, PC9, PC10 | Incremental R2 (Full model versus model with only covariates) |
| PPM021085 | PGS004859 (T2D_PRS_CS) |
PSS011514| African Ancestry| 7,010 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 1.43 [1.35, 1.52] | AUROC: 0.76 [0.74, 0.77] | — | age, sex, 10 principal components | — |
| PPM021086 | PGS004859 (T2D_PRS_CS) |
PSS011516| Hispanic or Latin American Ancestry| 5,382 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 2.09 [1.92, 2.27] | AUROC: 0.84 [0.82, 0.86] | — | age, sex, 10 principal components | — |
| PPM021087 | PGS004859 (T2D_PRS_CS) |
PSS011517| East Asian Ancestry| 663 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 1.8 [1.4, 2.32] | AUROC: 0.84 [0.79, 0.9] | — | age, sex, 10 principal components | — |
| PPM021088 | PGS004859 (T2D_PRS_CS) |
PSS011518| European Ancestry| 22,306 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 2.33 [2.23, 2.43] | AUROC: 0.77 [0.76, 0.78] | — | age, sex, 10 principal components | — |
| PPM021089 | PGS004859 (T2D_PRS_CS) |
PSS011519| South Asian Ancestry| 323 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 2.28 [1.64, 3.16] | AUROC: 0.88 [0.81, 0.95] | — | age, sex, 10 principal components | — |
| PPM021090 | PGS004859 (T2D_PRS_CS) |
PSS011515| Multi-ancestry (including European)| 35,684 individuals |
PGP000606 | Szczerbinski L et al. medRxiv (2023) |Ext.|Pre |
Reported Trait: Type 2 diabetes | OR: 1.93 [1.87, 1.99] | AUROC: 0.75 [0.74, 0.75] | — | age, sex, 10 principal components | — |
| PPM021084 | PGS004859 (T2D_PRS_CS) |
PSS011513| Multi-ancestry (including European)| 546 individuals |
PGP000605 | Deutsch AJ et al. Diabetes Care (2023) |
Reported Trait: Glucocorticoid-induced hyperglycemia | OR: 1.44 [1.02, 2.04] | AUROC: 0.68 | — | eGFR, glucocorticoid dose | — |
| PPM021133 | PGS004868 (T2DPGS) |
PSS011537| European Ancestry| 345,217 individuals |
PGP000617 | Yun JS et al. Cardiovasc Diabetol (2022) |
Reported Trait: Incident cardiovascular disease | HR: 1.06 [1.04, 1.07] | — | Hazard ratio (HR, top PRS percentile vs bottom quintile): 1.35 [1.19, 1.53] | Age, sex, genotyping array, 10 PCs | — |
|
PGS Sample Set ID (PSS) |
Phenotype Definitions and Methods | Participant Follow-up Time | Sample Numbers | Age of Study Participants | Sample Ancestry | Additional Ancestry Description | Cohort(s) | Additional Sample/Cohort Information |
|---|---|---|---|---|---|---|---|---|
| PSS011441 | — | — | [ ,
82.0 % Male samples |
Mean = 27.5 years | African unspecified | — | PDAY | — |
| PSS011442 | — | — | [ ,
77.0 % Male samples |
Mean = 26.7 years | European | — | PDAY | — |
| PSS000017 | Type 2 diabetes ascertainment was based on self-report in an interview with a trained nurse or an ICD-10 code of E11.X in hospitalization records. | — | [
|
— | European | — | UKB | UKB Phase 2 |
| PSS000025 | Incident cases of Type 2 Diabetes in 5.63 years follow-up | — | [ ,
55.0 % Male samples |
— | European (Estonian) |
— | EB | — |
| PSS000026 | Cases were defined on the presence or absence of severe insulin deficiency (requiring insulin treatment at 3 years after diagnosis). We cate- gorized people as severely insulin defi- cient if they received continuous insulin treatment at ,3 years from the time of diagnosis and had a low measured C-peptide level (nonfasting measured ,0.6 nmol/L or equivalent fasting blood glucose level or posthome meal urine C-peptide–to–creatinine ratio) | — | [ ,
46.3 % Male samples |
— | European | — | P2ID | A cross-sectional cohort of people in whom diabetes was diagnosed between the ages of 20 and 40 years (n = 223), who had had diabetes for .3 years, and who had self-reported as white European from Devon and Cornwall in South West England. Known monogenic diabetes and secondary diabetes pa- tients were excluded. |
| PSS000027 | Type 1 diabetes status was assigned according to clinician diagnosis. | — | [ ,
33.78 % Male samples |
— | African American or Afro-Caribbean | — | UFDI | Total sample number contains the number of controls, cases, and includes the number of first/second-degree relatives and samples identified as "at risk" (autoantibody positive) used in other analyses. |
| PSS000028 | Type 1 diabetes status was assigned according to clinician diagnosis. | — | [ ,
44.84 % Male samples |
— | Hispanic or Latin American | Samples labeled Caucasian (Hispanic ethnicity) in the original publication. | UFDI | Total sample number contains the number of controls, cases, and includes the number of first/second-degree relatives and samples identified as "at risk" (autoantibody positive) used in other analyses. |
| PSS000029 | Type 1 diabetes status was assigned according to clinician diagnosis. | — | [ ,
47.34 % Male samples |
— | European | Samples labeled Caucasian (non-Hispanic) in the original publication. | UFDI | Total sample number contains the number of controls, cases, and includes the number of first/second-degree relatives and samples identified as "at risk" (autoantibody positive) used in other analyses. |
| PSS000030 | — | — | [
|
— | African unspecified | — | 7 cohorts
|
— |
| PSS000031 | Cases are diagnosed with type 1 diabetes. | — | [
|
— | African unspecified | — | UOF | — |
| PSS000032 | Type 1 Diabetes Case Definition = Clinical diagnosis of diabetes at less than or equal to 20 years of age; On insulin within 1 year from the time of diagnosis; Still on insulin at the time of recruit- ment; Not using oral antihyperglycemic agents; Did not ever self-report as having type 2 diabetes (T2D) | — | [
|
— | European | — | UKB | — |
| PSS009287 | — | — | 18,975 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009288 | — | — | 19,931 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009289 | — | — | 19,330 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009292 | — | — | 19,983 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009293 | — | — | 19,883 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009294 | — | — | 19,924 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS009295 | — | — | 20,000 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS000042 | T2D was defined by a fasting plasma glucose ≥7.0 mmol/L (≥126 mg/dL) or report of taking diabetes medications | — | [ ,
38.8 % Male samples |
— | African American or Afro-Caribbean | — | CARDIA | — |
| PSS000043 | T2D was defined by a fasting plasma glucose ≥7.0 mmol/L (≥126 mg/dL) or report of taking diabetes medications | — | [ ,
46.5 % Male samples |
— | European | — | CARDIA | — |
| PSS000044 | T2D was defined by a fasting plasma glucose ≥7.0 mmol/L (≥126 mg/dL) or report of taking diabetes medications | — | [ ,
46.6 % Male samples |
— | European | — | FOS | — |
| PSS011465 | — | — | 9,462 individuals | — | European | — | AllofUs | — |
| PSS011474 | — | — | 8,837 individuals | — | South Asian | — | G&H | — |
| PSS000054 | Prevalent T2D status was defined using self-reported medical history and medication | — | [
|
— | European | — | UKB | — |
| PSS011507 | — | — | 7,879 individuals | — | European | — | AllofUs | — |
| PSS011513 | Manual curation of electronic medical records. Cases had no ICD code for diabetes, received a glucocorticoid dose equivalent to >= 10 mg of prednisone, and had random blood glucose >= 200 mg/dL or fasting blood glucose >= 126 mg/dL (drawn between 4:00 AM and 6:59 AM) | — | [
|
— | Asian unspecified | — | MGBB | — |
| PSS011513 | Manual curation of electronic medical records. Cases had no ICD code for diabetes, received a glucocorticoid dose equivalent to >= 10 mg of prednisone, and had random blood glucose >= 200 mg/dL or fasting blood glucose >= 126 mg/dL (drawn between 4:00 AM and 6:59 AM) | — | [
|
— | African American or Afro-Caribbean | — | MGBB | — |
| PSS011513 | Manual curation of electronic medical records. Cases had no ICD code for diabetes, received a glucocorticoid dose equivalent to >= 10 mg of prednisone, and had random blood glucose >= 200 mg/dL or fasting blood glucose >= 126 mg/dL (drawn between 4:00 AM and 6:59 AM) | — | [
|
— | European | — | MGBB | — |
| PSS011513 | Manual curation of electronic medical records. Cases had no ICD code for diabetes, received a glucocorticoid dose equivalent to >= 10 mg of prednisone, and had random blood glucose >= 200 mg/dL or fasting blood glucose >= 126 mg/dL (drawn between 4:00 AM and 6:59 AM) | — | [
|
— | Not reported | — | MGBB | — |
| PSS011514 | — | — | [
|
— | African American or Afro-Caribbean | — | AllofUs | — |
| PSS011515 | — | — | [
|
— | African American or Afro-Caribbean | — | AllofUs | — |
| PSS011515 | — | — | [
|
— | Hispanic or Latin American | — | AllofUs | — |
| PSS011515 | — | — | [
|
— | East Asian | — | AllofUs | — |
| PSS011515 | — | — | [
|
— | European | — | AllofUs | — |
| PSS011515 | — | — | [
|
— | South Asian | — | AllofUs | — |
| PSS011516 | — | — | [
|
— | Hispanic or Latin American | — | AllofUs | — |
| PSS011517 | — | — | [
|
— | East Asian | — | AllofUs | — |
| PSS011518 | — | — | [
|
— | European | — | AllofUs | — |
| PSS011519 | — | — | [
|
— | South Asian | — | AllofUs | — |
| PSS009381 | — | — | 6,451 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS000083 | Cases were clinically diagnosed with T1D before 17 years of age and treated with insulin from diagnosis. Patients with known MODY or NDM were excluded. | — | [
|
— | European | — | WTCCC | Cases with Type 1 Diabetes |
| PSS000083 | MODY patients with a confirmed monogenic etiology on genetic testing (415 patients with HNF1A MODY, 346 with GCK MODY, 42 with HNF4A MODY, and 2 with HNF1B MODY). The median age of diagnosis was 20 years (interquartile range 15, 30), and 532 patients were female. | — | [ ,
33.91 % Male samples |
— | European | — | NR | Maturity-onset diabetes of young (MODY) cases ascertained from the Genetic Βeta Cell Research Bank, Exeter, U.K. |
| PSS011531 | Cases were individuals with T1D | — | [ ,
53.51 % Male samples |
— | European | — | NR | — |
| PSS011532 | Cases were individuals with T1D | — | [ ,
53.79 % Male samples |
— | European | — | NR | — |
| PSS011537 | — | Median = 8.9 years IQR = [8.3, 9.5] years |
[ ,
44.6 % Male samples |
Mean = 56.1 years Sd = 8.0 years |
European (White British) |
— | UKB | — |
| PSS009514 | — | — | [
|
— | East Asian (Japanese) |
— | BBJ | — |
| PSS009518 | — | — | [
|
— | European (Estonian) |
— | EB | — |
| PSS003606 | — | — | [
|
Mean = 56.81 years | European | — | UKB | — |
| PSS009522 | — | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS009526 | — | — | [
|
— | European | Norwegian | HUNT | — |
| PSS009530 | — | — | [
|
— | African American or Afro-Caribbean | — | MGBB | — |
| PSS009534 | — | — | [
|
— | European | — | MGBB | — |
| PSS009538 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS009542 | — | — | [
|
— | European | British | UKB | — |
| PSS009546 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS007684 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 8/9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2019, whichever came first. | Median = 13.0 years IQR = [7.5, 19.7] years |
[ ,
43.8 % Male samples |
Mean (Age At Baseline) = 53.2 years Sd = 17.4 years |
European (Finnish) |
— | FinnGen | — |
| PSS007685 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 8/9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2019, whichever came first. | — | [ ,
42.9 % Male samples |
Mean (Age At Baseline) = 51.8 years Sd = 17.4 years |
European (Finnish) |
— | FinnGen | — |
| PSS007686 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 8/9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2019, whichever came first. | — | [ ,
43.8 % Male samples |
Mean (Age At Baseline) = 53.2 years Sd = 17.4 years |
European (Finnish) |
— | FinnGen | — |
| PSS009573 | — | — | [ ,
0.0 % Male samples |
— | East Asian (Chinese) |
— | NR | — |
| PSS007690 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the censoring date of hospital inpatient data (UK Biobank; English hospital inpatient records up to May 2020, Scottish up to November 2016, Welsh up to March 2016), whichever came first. | Median = 10.4 years IQR = [8.3, 11.3] years |
[ ,
46.3 % Male samples |
Mean (Age At Baseline) = 57.4 years Sd = 8.0 years |
European (British) |
UK Biobank participants with non-British ancestry were excluded based on genetically inferred ancestry. | UKB | — |
| PSS007691 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the censoring date of hospital inpatient data (UK Biobank; English hospital inpatient records up to May 2020, Scottish up to November 2016, Welsh up to March 2016), whichever came first. | — | [ ,
45.5 % Male samples |
Mean (Age At Baseline) = 57.2 years Sd = 8.0 years |
European (British) |
UK Biobank participants with non-British ancestry were excluded based on genetically inferred ancestry. | UKB | — |
| PSS007692 | Type 2 diabetes was defined by a strict type 2 diabetes definition, that excluded type 1 diabetes, ICD 9/10 codes are listed in Supplementary Data 1. National registeries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the censoring date of hospital inpatient data (UK Biobank; English hospital inpatient records up to May 2020, Scottish up to November 2016, Welsh up to March 2016), whichever came first. | — | [ ,
46.3 % Male samples |
Mean (Age At Baseline) = 57.4 years Sd = 8.0 years |
European (British) |
UK Biobank participants with non-British ancestry were excluded based on genetically inferred ancestry. | UKB | — |
| PSS007699 | — | — | [
|
— | African unspecified | Africa or admixed-ancestry diaspora | UKB | — |
| PSS007703 | — | — | [
|
— | Asian unspecified | Central and South Asian | UKB | — |
| PSS007712 | — | — | [
|
— | European | — | UKB | — |
| PSS000754 | — | — | 87,413 individuals | — | European | — | UKB | — |
| PSS000755 | — | — | 87,413 individuals | — | European | — | UKB | — |
| PSS000756 | ICD-10 E11.0 - E11.9 | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS007737 | — | — | 2,200 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007738 | — | — | 2,476 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007739 | — | — | 2,385 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007742 | — | — | 2,480 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007743 | — | — | 2,472 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS007744 | — | — | 2,484 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS000815 | — | — | 87,413 individuals | — | European | — | UKB | — |
| PSS000816 | ICD-10 M10 | — | [
|
— | European (Finnish) |
— | FinnGen | — |
| PSS009629 | — | — | 5,806 individuals | — | South Asian (Indian) |
— | INSPIRED | Dr. Mohan’s Diabetes Specialities Centre (INSPIRED - DMDSC) |
| PSS007825 | — | — | 372 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS000232 | Individuals with T2D were defined as those with fasting time >8 h and fasting glucose levels ≥126 mg/dL, fasting ≤8 h and fasting glucose ≥200 mg/dL, post–oral glucose tolerance test glucose ≥200 mg/dL, HbA1c ≥6.5% (48 mmol/mol), or on current treatment with antihyperglycemia medications. | — | [ ,
39.65 % Male samples |
— | Hispanic or Latin American (Central American, Cuban, Dominican, Mexican, Puerto Rican, South American) |
Ancestry groups were defined based on a combination of self-identified Hispanic/Latino background and genetic similarity | HCHS, SOL | — |
| PSS000869 | CALIBER rule-based phenotyping algorithms (https://github.com/spiros/chronological-map-phenotypes#diabetes) | Median = 6.9 years | [ ,
51.0 % Male samples |
Median = 44.0 years IQR = [30.5, 54.7] years |
European | — | INTERVAL | — |
| PSS009665 | Gout was ascertained based on information from self- report (Data-Field 20002, code: 1466), medical records (ICD-10 codes: M10.0, M10.2, M10.3, M10.4, M10.9), and death records (ICD-10 codes: M10.0, M10.2, M10.3, M10.4, M10.9) | Median = 12.1 years | [ ,
45.9 % Male samples |
Mean = 56.6 years Sd = 8.0 years |
European | — | UKB | — |
| PSS009669 | T2D cases were defined with T2D ICD codes, a single measurement of glucose (fasting glucose ≥126 mg/dL [7 mmol/L] or random glucose ≥ 200 mg/dL [11.1 mmol/L]) or use of any glucose-lowering medications. | — | [
|
— | African American or Afro-Caribbean (African) |
— | GenHAT | — |
| PSS009670 | T2D cases were defined with T2D ICD codes, a single measurement of glucose (fasting glucose ≥126 mg/dL [7 mmol/L] or random glucose ≥ 200 mg/dL [11.1 mmol/L]) or use of any glucose-lowering medications. | — | [
|
— | African American or Afro-Caribbean (African) |
— | HYPERGEN | — |
| PSS009671 | T2D cases were defined with T2D ICD codes, a single measurement of glucose (fasting glucose ≥126 mg/dL [7 mmol/L] or random glucose ≥ 200 mg/dL [11.1 mmol/L]) or use of any glucose-lowering medications. | — | [
|
— | African American or Afro-Caribbean (African) |
— | REGARDS | — |
| PSS009672 | Self-reported T2D | — | [
|
— | East Asian (Taiwanese) |
— | TWB | — |
| PSS009673 | Self-reported T2D | — | [
|
— | East Asian (Taiwanese) |
— | TWB | — |
| PSS009674 | Self-reported T2D | — | [
|
— | East Asian (Taiwanese) |
— | TWB | — |
| PSS009675 | T2D cases were defined with T2D ICD codes, a single measurement of glucose (fasting glucose ≥126 mg/dL [7 mmol/L] or random glucose ≥ 200 mg/dL [11.1 mmol/L]) or use of any glucose-lowering medications. | — | [
|
— | African American or Afro-Caribbean (African) |
— | WPC | — |
| PSS009676 | An EHR-based phenotyping algorithm of T2D implemented across eMERGE sites | — | [
|
— | African American or Afro-Caribbean (African) |
— | eMERGE | — |
| PSS009677 | An EHR-based phenotyping algorithm of T2D implemented across eMERGE sites | — | [
|
— | European (European) |
— | eMERGE | — |
| PSS009678 | An EHR-based phenotyping algorithm of T2D implemented across eMERGE sites | — | [
|
— | Hispanic or Latin American (Hispanic/Latino) |
— | eMERGE | — |
| PSS007956 | — | — | 1,729 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007957 | — | — | 1,808 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007958 | — | — | 1,764 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007961 | — | — | 1,810 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007962 | — | — | 1,809 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS007963 | — | — | 1,810 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS009727 | — | — | 6,430 individuals | — | African unspecified | — | UKB | — |
| PSS009728 | — | — | 898 individuals | — | East Asian | — | UKB | — |
| PSS009729 | — | — | 43,355 individuals | — | European | Non-British European | UKB | — |
| PSS009730 | — | — | 7,926 individuals | — | South Asian | — | UKB | — |
| PSS010982 | — | Mean = 7.15 years | [
|
Mean = 31.04 years Sd = 10.43 years |
Native American | — | NR | — |
| PSS010983 | — | Mean = 21.28 years | [
|
— | Native American | — | NR | — |
| PSS010984 | — | Mean = 7.99 years | [
|
Mean = 12.05 years Sd = 3.73 years |
Native American | — | NR | — |
| PSS009739 | — | — | 6,503 individuals | — | African unspecified | — | UKB | — |
| PSS009740 | — | — | 922 individuals | — | East Asian | — | UKB | — |
| PSS009741 | — | — | 43,505 individuals | — | European | Non-British European | UKB | — |
| PSS009742 | — | — | 8,098 individuals | — | South Asian | — | UKB | — |
| PSS010998 | — | — | [
|
— | European | — | MGI | — |
| PSS010999 | — | — | [
|
— | European | — | UKB | — |
| PSS011000 | — | — | [
|
— | European | — | UKB | — |
| PSS011001 | — | — | [
|
— | European | — | UKB | — |
| PSS011002 | — | — | [
|
— | European | — | UKB | — |
| PSS011003 | — | — | [
|
— | European | — | UKB | — |
| PSS008039 | — | — | 427 individuals | — | East Asian | China (East Asia) | UKB | — |
| PSS011009 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 16,663 individuals, 48.0 % Male samples |
Mean = 51.9 years Sd = 14.8 years |
European | Self-identified race = White | BioMe | — |
| PSS011009 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 11,443 individuals, 39.0 % Male samples |
Mean = 48.4 years Sd = 14.1 years |
African American or Afro-Caribbean | Self-identified race = Black | BioMe | — |
| PSS011009 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 19,524 individuals, 37.0 % Male samples |
Mean = 50.3 years Sd = 15.3 years |
Hispanic or Latin American | Self-identified race = Hispanic | BioMe | — |
| PSS011009 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 10,013 individuals, 46.0 % Male samples |
Mean = 55.9 years Sd = 13.9 years |
East Asian, South East Asian, Native American, South Asian, Other | Self-identified race = Other | BioMe | — |
| PSS011010 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 11,443 individuals, 39.0 % Male samples |
Mean = 48.4 years Sd = 14.1 years |
African American or Afro-Caribbean | Self-identified race = Black | BioMe | — |
| PSS011010 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 19,524 individuals, 37.0 % Male samples |
Mean = 50.3 years Sd = 15.3 years |
Hispanic or Latin American | Self-identified race = Hispanic | BioMe | — |
| PSS011010 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 10,013 individuals, 46.0 % Male samples |
Mean = 55.9 years Sd = 13.9 years |
East Asian, South East Asian, Native American, South Asian, Other | Self-identified race = Other | BioMe | — |
| PSS011011 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 16,663 individuals, 48.0 % Male samples |
Mean = 51.9 years Sd = 14.8 years |
European | Self-identified race = White | BioMe | — |
| PSS011012 | — | — | 34,939 individuals, 47.0 % Male samples |
Mean = 59.1 years Sd = 16.9 years |
European | Self-identified race = white | MGBB | — |
| PSS011012 | — | — | 2,101 individuals, 37.0 % Male samples |
Mean = 52.1 years Sd = 16.3 years |
African American or Afro-Caribbean (Black) |
— | MGBB | — |
| PSS011012 | — | — | 1,269 individuals, 34.0 % Male samples |
Mean = 46.4 years Sd = 16.1 years |
Hispanic or Latin American (Hispanic) |
— | MGBB | — |
| PSS011012 | — | — | 1,511 individuals, 36.0 % Male samples |
Mean = 46.9 years Sd = 16.3 years |
Native American, Asian unspecified, Oceanian, Other | — | MGBB | — |
| PSS011013 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 2,101 individuals, 37.0 % Male samples |
Mean = 52.1 years Sd = 16.3 years |
African American or Afro-Caribbean | Self-identified race = Black | MGBB | — |
| PSS011013 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 1,269 individuals, 34.0 % Male samples |
Mean = 46.4 years Sd = 16.1 years |
Hispanic or Latin American | Self-identified race = Hispanic | MGBB | — |
| PSS011013 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 1,511 individuals, 36.0 % Male samples |
Mean = 46.9 years Sd = 16.3 years |
Native American, Asian unspecified, Oceanian, Other | Self-identified race = Other | MGBB | — |
| PSS011014 | At each site, a trained medical reviewer performed manual record review for all individuals identified as having type 1 diabetes by the eMERGE algorithm. To confirm a diagnosis of type 1 diabetes, participants had to meet all of the following criteria, modified from (13): Diagnosis confirmed by an endocrinologist or primary care physician Current use of basal-bolus insulin or pump No secondary cause of diabetes listed in the medical record: gestational diabetes, checkpoint inhibitor use, glucocorticoid-induced diabetes, cystic fibrosis diagnosis, hemochromatosis, pancreatogenic diabetes, posttransplantation diabetes, maturity-onset diabetes of the young, or diagnosis of type 1.5 diabetes | — | 34,939 individuals, 47.0 % Male samples |
Mean = 59.1 years Sd = 16.9 years |
European | Self-identified race = White | MGBB | — |
| PSS009859 | — | — | 6,503 individuals | — | African unspecified | — | UKB | — |
| PSS009860 | — | — | 922 individuals | — | East Asian | — | UKB | — |
| PSS009861 | — | — | 43,505 individuals | — | European | Non-British European | UKB | — |
| PSS009862 | — | — | 8,098 individuals | — | South Asian | — | UKB | — |
| PSS008169 | — | — | 5,228 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008170 | — | — | 6,312 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008171 | — | — | 6,081 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008174 | — | — | 6,325 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008175 | — | — | 6,298 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008176 | — | — | 6,292 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS008177 | — | — | 6,331 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS004203 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004204 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004205 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004206 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004207 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS009893 | — | — | 366 individuals | — | African American or Afro-Caribbean | — | SEARCH | — |
| PSS009894 | — | — | 412 individuals | — | Hispanic or Latin American | — | SEARCH | — |
| PSS009895 | — | — | 1,168 individuals | — | European | — | SEARCH | — |
| PSS009896 | — | — | 99 individuals | — | Not reported | — | SEARCH | — |
| PSS009902 | — | — | [
|
— | European (Italian) |
— | NR | — |
| PSS008261 | — | — | 814 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS004312 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004313 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004314 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004315 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004316 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS000310 | Setting II: Based on ICD codes and review of medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases | Median = 8.0 years | [ ,
32.0 % Male samples |
— | European | — | PHB | — |
| PSS000311 | Setting III: Based on ICD codes and final diagnosis in medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases | Median = 7.0 years | [ ,
32.0 % Male samples |
— | European | — | PHB | — |
| PSS011097 | — | — | 2,669 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Arab) |
— | NR | N total after excluding missing values = 2,553 |
| PSS000320 | Setting I: Based on ICD codes and expert opinion (ACR2010 criteria), in eMERGE network EMR database from Stanaway 2018; controls = other non-matching arthritis diseases | Median = 16.0 years | [ ,
43.0 % Male samples |
— | European, African unspecified, Asian unspecified, NR | Primarily European, African and Asian ancestry | eMERGE | — |
| PSS004359 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004360 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004361 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004362 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004363 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS009939 | — | — | 39,444 individuals | — | European (Finnish) |
— | FinnGen | — |
| PSS009943 | We used the disease definitions described in the supplement of Eastwood et al (2016). PMID: 27631769 | — | [ ,
45.0 % Male samples |
European | — | UKB | — | |
| PSS008391 | — | — | 1,107 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008392 | — | — | 1,197 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008393 | — | — | 1,162 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008396 | — | — | 1,200 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008397 | — | — | 1,196 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS008398 | — | — | 1,200 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS004452 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004453 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004454 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004455 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004456 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004457 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004458 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004459 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004460 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS009971 | — | — | 30,716 individuals | — | European | — | MGBB | — |
| PSS011181 | — | — | 3,071 individuals, 48.8 % Male samples |
Mean = 57.4 years Sd = 12.88 years |
Not reported | — | KORA | — |
| PSS009971 | — | — | 1,807 individuals | — | African unspecified (Black) |
— | MGBB | — |
| PSS009971 | — | — | 786 individuals | — | Asian unspecified | — | MGBB | — |
| PSS009971 | — | — | 3,113 individuals | — | Other | — | MGBB | — |
| PSS011184 | — | — | 27,429 individuals, 47.0 % Male samples |
Mean = 55.3 years Sd = 7.6 years |
European, Not reported | — | UKB | — |
| PSS001044 | Cases are individuals with type 2 diabetes (T2D). T2D cases were defined as individuals with (1) a T2D diagnosis by a physician/medical professional and use of medication for treatment of diabetes, and/or (2)a fasting(R8h)blood glucose measurement R126 mg/dL indicated in examination records. For the BMBB cohort T2D diabetes status was defined from algorithms extracted from electronic medical record (EMR) and includes family history of T2D as an exclusion criteria. For T2D cases, BMBB defined medications using unique RxNorm codes at an ingredient level and defined laboratory tests using the logical observations identifiers names and codes (LOINC) standard (https://www.phekb.org/phenotype/type-2-diabetes-mellitus). BioMe included all patients with ICD-9-CM codes of 250.x0 or 250.x2, except for codes 250.10 and 250.12 (indicative of T2D with ketoacidosis, a condition also closely associated with T1D), patients on T2D medications and/or insulin at any time, and all patients with abnormal glucose (>200 mg/dl) or hemoglobin A1c (HbA1c; ≥6.5%) laboratory test results. For the MEC cohort, T2D cases were defined using the following criteria: (a) a self-report of diabetes on the baseline questionnaire, 2nd questionnaire or 3rd questionnaire; and (b) self-report of taking medication for T2D at the time of blood draw; and (c) no diagnosis of T1D in the absence of a T2D diagnosis from the California Office of Statewide Health Planning and Development (OSHPD) for California Residents. In addition, cases included individuals who were linked to the diabetes registries of Hawaii Medical Service Association (HMSA) or Kaiser Permanente Hawaii (KPH) health plans, or who were designated as diabetic in the Chronic Conditions Data Warehouse (CCW) of Medicare. For the WHI cohort, T2D was documented at baseline by self-report in which each woman was asked whether she had ever been told that she had “sugar diabetes” by her physician. Incident diabetes during follow-up was documented by self-report at each semi-annual contact, when participants were asked, “Since the date given on the front of this form, has a doctor prescribed any of the following pills or treatments?” Choices included “pills for diabetes” and “insulin shots for diabetes.”. For the ARIC cohort prevalent type 2 diabetes was defined at the baseline examination as fasting (≥8 h) blood glucose ≥126 mg/dL, or nonfasting glucose ≥200 mg/dL, self-report physician diagnosis of diabetes or “sugar in the blood,” or current medication use for diabetes within the last two weeks. For the CARDIA cohort, T2D was determined at last visit based on a combination of measured fasting glucose levels (≥7.0 mmol/L and ≥126 mg/dL) at examination years 0, 7, 10, 15, 20, or 25; self-report of oral hypoglycemic medications or insulin at years 0, 7, 10, 15, 20, or 25; a 2-h postload glucose ≥11.1 mmol/L (≥200 mg/dL) during a 75-g oral glucose tolerance test at years 10, 20, and 25; or an HbA1c ≥6.5% at years 20 and 25. | — | [
|
— | African American or Afro-Caribbean | — | ARIC, BioMe, CARDIA, MEC, WHI | Possible sample overlap with this dataset and the datasets used to source/develop GRS582_T2Dmulti and GRS582_T2Dafr. |
| PSS001045 | Cases are individuals with type 2 diabetes (T2D). T2D cases were defined as individuals with (1) a T2D diagnosis by a physician/medical professional and use of medication for treatment of diabetes,and/or (2)a fasting(R8h)blood glucose measurement R126 mg/dL indicated in examination records. For the BMBB cohort T2D diabetes status was defined from algorithms extracted from electronic medical record (EMR) and includes family history of T2D as an exclusion criteria. For T2D cases, BMBB defined medications using unique RxNorm codes at an ingredient level and defined laboratory tests using the logical observations identifiers names and codes (LOINC) standard (https://www.phekb.org/phenotype/type-2-diabetes-mellitus). BioMe included all patients with ICD-9-CM codes of 250.x0 or 250.x2, except for codes 250.10 and 250.12 (indicative of T2D with ketoacidosis, a condition also closely associated with T1D), patients on T2D medications and/or insulin at any time, and all patients with abnormal glucose (>200 mg/dl) or hemoglobin A1c (HbA1c; ≥6.5%) laboratory test results. For the MEC cohort, T2D cases were defined using the following criteria: (a) a self-report of diabetes on the baseline questionnaire, 2nd questionnaire or 3rd questionnaire; and (b) self-report of taking medication for T2D at the time of blood draw; and (c) no diagnosis of T1D in the absence of a T2D diagnosis from the California Office of Statewide Health Planning and Development (OSHPD) for California Residents. In addition, cases included individuals who were linked to the diabetes registries of Hawaii Medical Service Association (HMSA) or Kaiser Permanente Hawaii (KPH) health plans, or who were designated as diabetic in the Chronic Conditions Data Warehouse (CCW) of Medicare. For the WHI cohort, T2D was documented at baseline by self-report in which each woman was asked whether she had ever been told that she had “sugar diabetes” by her physician. Incident diabetes during follow-up was documented by self-report at each semi-annual contact, when participants were asked, “Since the date given on the front of this form, has a doctor prescribed any of the following pills or treatments?” Choices included “pills for diabetes” and “insulin shots for diabetes.”. | — | [
|
— | Asian unspecified | — | BioMe, MEC, WHI | Possible sample overlap with this dataset and the datasets used to source/develop GRS582_T2Dmulti and GRS582_T2Dasn. |
| PSS001046 | Cases are individuals with type 2 diabetes (T2D). T2D cases were defined as individuals with (1) a T2D diagnosis by a physician/medical professional and use of medication for treatment of diabetes,and/or (2)a fasting(R8h)blood glucose measurement R126 mg/dL indicated in examination records. For the UKB cohort, T2D cases were defined by an ICD-10 code of E11.X or a self-reported diagnosis in an interview with a trained nurse. | — | [
|
— | European | — | UKB | Possible significant sample overlap with this dataset and the datasets used to source/develop GRS582_T2Dmulti and GRS582_T2Deur |
| PSS001047 | Cases are individuals with type 2 diabetes (T2D). T2D cases were defined as individuals with (1) a T2D diagnosis by a physician/medical professional and use of medication for treatment of diabetes,and/or (2)a fasting(R8h)blood glucose measurement R126 mg/dL indicated in examination records. For the BMBB cohort T2D diabetes status was defined from algorithms extracted from electronic medical record (EMR) and includes family history of T2D as an exclusion criteria. For T2D cases, BMBB defined medications using unique RxNorm codes at an ingredient level and defined laboratory tests using the logical observations identifiers names and codes (LOINC) standard (https://www.phekb.org/phenotype/type-2-diabetes-mellitus). BioMe included all patients with ICD-9-CM codes of 250.x0 or 250.x2, except for codes 250.10 and 250.12 (indicative of T2D with ketoacidosis, a condition also closely associated with T1D), patients on T2D medications and/or insulin at any time, and all patients with abnormal glucose (>200 mg/dl) or hemoglobin A1c (HbA1c; ≥6.5%) laboratory test results. For the MEC cohort, T2D cases were defined using the following criteria: (a) a self-report of diabetes on the baseline questionnaire, 2nd questionnaire or 3rd questionnaire; and (b) self-report of taking medication for T2D at the time of blood draw; and (c) no diagnosis of T1D in the absence of a T2D diagnosis from the California Office of Statewide Health Planning and Development (OSHPD) for California Residents. In addition, cases included individuals who were linked to the diabetes registries of Hawaii Medical Service Association (HMSA) or Kaiser Permanente Hawaii (KPH) health plans, or who were designated as diabetic in the Chronic Conditions Data Warehouse (CCW) of Medicare. For the WHI cohort, T2D was documented at baseline by self-report in which each woman was asked whether she had ever been told that she had “sugar diabetes” by her physician. Incident diabetes during follow-up was documented by self-report at each semi-annual contact, when participants were asked, “Since the date given on the front of this form, has a doctor prescribed any of the following pills or treatments?” Choices included “pills for diabetes” and “insulin shots for diabetes.”. For the SOL cohort, T2D cases were defined as those with fasting time >8 h and fasting glucose levels ≥126 mg/dL, fasting ≤8 h and fasting glucose ≥200 mg/dL, post–oral glucose tolerance test glucose ≥200 mg/dL, HbA1c ≥6.5% (48 mmol/mol), or on current treatment with antihyperglycemia medications. | — | [
|
— | Hispanic or Latin American | — | BioMe, MEC, SOL, WHI | Possible sample overlap with this dataset and the datasets used to source/develop GRS582_T2Dmulti and GRS582_T2Dhis. |
| PSS001048 | Cases are individuals with type 2 diabetes (T2D). T2D cases were defined as individualswith (1) a T2D diagnosis by a physician/medical professional and use of medication for treat-mentofdiabetes,and/or (2)a fasting(R8h)blood glucose measurement R126 mg/dL indicated in examination records. For the MEC cohort, T2D cases were defined using the following criteria: (a) a self-report of diabetes on the baseline questionnaire, 2nd questionnaire or 3rd questionnaire; and (b) self-report of taking medication for T2D at the time of blood draw; and (c) no diagnosis of T1D in the absence of a T2D diagnosis from the California Office of Statewide Health Planning and Development (OSHPD) for California Residents. In addition, cases included individuals who were linked to the diabetes registries of Hawaii Medical Service Association (HMSA) or Kaiser Permanente Hawaii (KPH) health plans, or who were designated as diabetic in the Chronic Conditions Data Warehouse (CCW) of Medicare. | — | [
|
— | Oceanian (Native Hawaiian) |
— | MEC | — |
| PSS008483 | — | — | 201 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS001065 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | African American or Afro-Caribbean | — | BioMe | — |
| PSS001066 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | European | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | European | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | African American or Afro-Caribbean | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | Hispanic or Latin American | — | BioMe | — |
| PSS001067 | All individuals had type 2 diabetes (T2D). Cases were individuals with diabetic retinopathy (DR). T2D was ascertained with ICD-10 from E11.0-E11.9. DR was ascertained with an ICD-10 of E11.3. | — | [
|
— | Asian unspecified, Native American, NR | — | BioMe | — |
| PSS004536 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004538 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004539 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004540 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS000368 | TEDDY children were followed prospectively from 3–4 months of age, with visits every 3 months until 4 years of age. Each evaluation tested the three islet antibodies (GADA, IA2A and IAA), changes in family history, as well as other measurements specified by the TEDDY protocol. After 4 years of age, children with any islet autoantibodies remained on quarterly visits, while antibody-negative children were evaluated every 6 months. Children were followed prospectively until 15 years of age or until T1D onset, as defined using the American Diabetes Association’s criteria for diagnosis (doi: 10.1196/annals.1447.062) | Median = 9.3 years Range = [0.0833, 14.0] years |
[ ,
50.86 % Male samples |
Range = [3.0, 4.0] years | NR | — | TEDDY | From 2004–2010, 424,788 newborns were screened at six US and European centers for high-risk HLA genotypes. TEDDY then enrolled 8,676 eligible infants with the intent to follow them until 15 years of age. The three major eligible HLA DR–DQ haplotypes are DR3–DQA1*0501–DQB1*0201, DR4–DQA1*0301–DQB1*0302 and DR8–DQA1*0401–DQB1*0402. |
| PSS004570 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004571 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004572 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004573 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004574 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004575 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004576 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004577 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004578 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004579 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004580 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004581 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004582 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004583 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004584 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004590 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004591 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004592 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004593 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004594 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004595 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS001084 | Moderate Age-Related Diabetes (MARD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001085 | Moderate Obesity-related Diabetes (MOD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001086 | Severe Autoimmune Diabetes (SAID) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001087 | Severe Insulin-Deficient Diabetes (SIDD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS001088 | Severe Insulin-Resistant Diabetes (SIRD) vs. controls | — | [
|
— | European | Swedish | ANDIS | — |
| PSS004600 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004602 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004603 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004604 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004605 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004606 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004607 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004608 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004609 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004610 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004611 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004612 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS004596 | — | — | [
|
— | East Asian | — | UKB | — |
| PSS004613 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004597 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004598 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS001092 | All individuals had cystic fibrosis with either 2 severe CFTR mutations and/or clinically diagnosed exocrine pancreatic insufficiency. Cases are individuals with cystic fibrosis related diabetes (CFRD).Phenotypes were obtained from extracted medical charts and CF Foundation Patient Registry through 2011. CFRD was defined by clinician diagnosis of diabetes plus insulin treatment for at least 1 year. The onset of CFRD was defined as the date at which insulin was started, if it was subsequently continued for at least 1 year. In approximately 50% of the participants, independent laboratory data (such as oral glucose tolerance test or hemoglobin A1c) were able to independently confirm the diagnosis of CFRD. Diabetes data were censored at the last clinic visit or date of solid organ transplant. | — | [ ,
47.04 % Male samples |
Mean = 20.0 years | Not reported | — | CGS, CWRU, FrGMC, JHU, UNC | — |
| PSS004599 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS008615 | — | — | 6,300 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008616 | — | — | 6,646 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008617 | — | — | 6,465 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008620 | — | — | 6,655 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008621 | — | — | 6,637 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008622 | — | — | 6,636 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS008623 | — | — | 6,660 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS001117 | T2D cases were defined as having an ICD-10 code of E11.X or having self-reported T2D in the in- terview. Only cases in which the individuals did not have T2D during the first assessment visit period (2006–2010) but were subsequently fol- lowed up for incident T2D events were considered. | Median = 3.58 years | [ ,
47.81 % Male samples |
— | European | — | UKB | — |
| PSS010014 | PheCode 250.2 (http://phewascatalog.org/); Binary | — | [
|
— | European | — | MGI | — |
| PSS008709 | — | — | 2,260 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS011217 | — | — | [
|
— | European | — | EB | — |
| PSS011224 | — | — | [
|
— | European | — | EB | — |
| PSS011225 | — | — | [
|
— | European | — | EB | — |
| PSS010036 | Field ID: 2443; Binary | — | [
|
— | European | — | UKB | — |
| PSS011229 | M13_GOUT, ICD10: M10, ICD9: 2740 | — | [
|
— | European | — | FinnGen | — |
| PSS010038 | — | — | [
|
— | Oceanian | Aotearoa NZ Maori and Cook Island Maori ancestry | NR | East Polynesian |
| PSS010039 | — | — | [
|
— | European | — | CLEAR | Australia and Aotearoa New Zealand cohort, GlobalGout, LASSO, CRYSTAL, LIGHT |
| PSS010040 | — | — | [
|
— | Oceanian | Samoan, Tongan, Niuean, Tokelauan and Pukapukan | NR | West Polynesian |
| 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 | — |
| PSS011240 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS011248 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS011249 | — | — | [
|
— | South Asian | — | G&H | — |
| PSS011256 | — | — | [
|
— | European | — | HUNT | — |
| PSS000441 | National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9. | — | [ ,
47.3 % Male samples |
Mean (Age At Baseline) = 48.0 years | European (Finnish) |
— | FINRISK | FINRISK surveys from 1992, 1997, 2002 and 2007 |
| PSS011264 | — | — | [
|
— | European | — | HUNT | — |
| PSS000448 | National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9. | — | [ ,
43.7 % Male samples |
Mean (Age At Baseline) = 59.2 years Sd = 16.6 years |
European (Finnish) |
— | FinnGen | — |
| PSS011265 | — | — | [
|
— | European | — | HUNT | — |
| PSS011270 | — | — | [
|
— | European | — | UKB | — |
| PSS011277 | — | — | [
|
— | European | — | UKB | — |
| PSS011278 | — | — | [
|
— | European | — | UKB | — |
| PSS011284 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS010055 | — | — | 22,608 individuals | — | East Asian | — | KBA, KoGES | — |
| PSS011291 | — | — | [
|
— | South Asian | — | UKB | — |
| PSS011295 | — | — | 1,798 individuals | — | Not reported | — | NR | StartRight |
| PSS011296 | 22,667 sibling pairs | — | 45,334 individuals | — | European | — | UKB | — |
| PSS006886 | — | — | 673 individuals | — | African unspecified | — | UKB | — |
| PSS006887 | — | — | 86 individuals | — | East Asian | — | UKB | — |
| PSS006888 | — | — | 1,059 individuals | — | European | non-white British ancestry | UKB | — |
| PSS006889 | — | — | 1,335 individuals | — | South Asian | — | UKB | — |
| PSS006890 | — | — | 3,195 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS011298 | — | — | 382,477 individuals | — | European | — | UKB | — |
| PSS011298 | — | — | 21,153 individuals | — | Not reported | — | UKB | — |
| PSS011299 | T2D ICD-10 code E11 | Median = 12.55 years IQR = [11.72, 13.27] years |
395,809 individuals, 45.8 % Male samples |
Mean = 56.7 years Sd = 8.0 years |
European | — | UKB | — |
| PSS011301 | — | — | [
|
— | South Asian (Indian) |
— | WellGen | — |
| PSS011302 | — | — | [
|
— | South Asian (Indian) |
— | WellGen | — |
| PSS011303 | — | — | [
|
— | South Asian (Indian) |
— | WellGen | — |
| PSS011304 | — | — | [
|
— | South Asian (Indian) |
— | WellGen | — |
| PSS011305 | — | — | [
|
— | South Asian (Indian) |
— | WellGen | — |
| PSS008840 | — | — | 3,490 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008841 | — | — | 3,896 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008842 | — | — | 3,732 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008845 | — | — | 3,918 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008846 | — | — | 3,903 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008847 | — | — | 3,901 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008848 | — | — | 3,924 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS011306 | — | — | 5,024 individuals, 40.0 % Male samples |
— | East Asian (Chinese) |
— | Wuxi NCDs | — |
| PSS010096 | — | — | 52,760 individuals | — | European | — | UKB | — |
| PSS010096 | — | — | 11,323 individuals | — | African unspecified (Black) |
— | UKB | — |
| PSS010096 | — | — | 1,091 individuals | — | Asian unspecified | — | UKB | — |
| PSS010097 | — | — | 390,459 individuals | — | European | — | eMERGE | — |
| PSS010097 | — | — | 3,018 individuals | — | African unspecified (Black) |
— | eMERGE | — |
| PSS010097 | — | — | 8,169 individuals | — | Asian unspecified | — | eMERGE | — |
| PSS010097 | — | — | 3,786 individuals | — | Other | — | eMERGE | — |
| PSS011325 | — | — | 181,559 individuals | — | European | — | UKB | — |
| PSS010101 | — | — | [ ,
0.0 % Male samples |
— | South Asian | — | BiB, START | 70% validation set from each cohort |
| PSS008929 | — | — | 511 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS011360 | — | — | 2,676 individuals, 32.47 % Male samples |
Mean = 54.0 years Sd = 11.8 years |
East Asian (Chinese) |
— | WHZH | — |
| PSS011364 | — | — | 56,192 individuals | — | European | — | UKB | — |
| PSS010157 | — | — | [
|
Mean = 42.3 years | Hispanic or Latin American (Mexican) |
— | METSB | — |
| PSS010176 | — | — | [
|
— | European | — | NR | Inter- Lymph Consortium |
| PSS009061 | — | — | 3,954 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009062 | — | — | 4,121 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009063 | — | — | 4,032 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009066 | — | — | 4,135 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009067 | — | — | 4,105 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009068 | — | — | 4,126 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009069 | — | — | 4,136 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS011395 | — | Mean = 8.1 years | 357,419 individuals | — | European (White British) |
— | UKB | — |
| PSS011407 | — | Mean = 6.8 years IQR = [6.3, 7.3] years |
[ ,
44.0 % Male samples |
Mean = 61.1 years Sd = 7.8 years |
European, Not reported | White European (97.1%) | UKB | — |
| PSS009155 | — | — | 1,243 individuals | — | European | Poland (NE Europe) | UKB | — |