Trait: metabolic disease

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
  • DIS METAB
  • Disease, Metabolic
  • Diseases, Metabolic
  • Disorder of metabolism NOS
  • Disorder of metabolism NOS (disorder)
  • Generalised metabolic disorder
  • Generalized metabolic disorder
  • Generalized metabolic disorder (disorder)
  • MD - Metabolic disorders
  • METAB DIS
  • METABOLISM DISORDER NOS
  • Metabolic Diseases
  • Metabolic Disorder
  • Metabolic disease (disorder)
  • Metabolic disease, NOS
  • Metabolic disorder, NOS
  • Metabolic disorders
  • Thesaurismoses
  • Thesaurismosis
  • Unspecified disorder of metabolism
  • disease of metabolism
  • disorder of metabolic process
  • metabolic disease
  • metabolic disorder
  • metabolic process disease
  • metabolism disorder
Mapped terms 13 mapped terms
  • DOID:0014667
  • ICD10:E70.E90
  • ICD10:E88.9
  • ICD9:277.8
  • ICD9:277.9
  • MESH:D008659
  • MONDO:0005066
  • MeSH:D008659
  • NCIT:C3235
  • NCIt:C3235
  • SCTID:75934005
  • SNOMEDCT:75934005
  • UMLS:C0025517
Child trait(s) 10 child traits

Associated Polygenic Score(s)

Filter PGS by Participant Ancestry
Individuals included in:
G - Source of Variant Associations (GWAS)
D - Score Development/Training
E - PGS Evaluation
List of ancestries includes:
Display options:
Ancestry legend
Multi-ancestry (including European)
Multi-ancestry (excluding European)
African
East Asian
South Asian
Additional Asian Ancestries
European
Greater Middle Eastern
Hispanic or Latin American
Additional Diverse Ancestries
Not Reported
Note: This table shows all PGS for "metabolic disease" and any child terms of this trait in the EFO hierarchy by default.
Polygenic Score ID & Name PGS Publication ID (PGP) Reported Trait Mapped Trait(s) (Ontology) Number of Variants Ancestry distribution Scoring File (FTP Link)
PGS000014
(GPS_T2D)
PGP000006 |
Khera AV et al. Nat Genet (2018)
Type 2 diabetes type II diabetes mellitus 6,917,436
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000014/ScoringFiles/PGS000014.txt.gz - Check Terms/Licenses
PGS000020
(dGRS1000)
PGP000010 |
Läll K et al. Genet Med (2016)
Type 2 diabetes type II 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 type I 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 type I 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 type I 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 type I 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 type II 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 II 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 II 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 type II 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 type II 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 type II 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 - Check Terms/Licenses
PGS000712
(T2D_HbA1c_39)
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
T2D (cases vs HbA1c filtered controls) type II diabetes mellitus 183,695
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000712/ScoringFiles/PGS000712.txt.gz - Check Terms/Licenses
PGS000713
(T2D)
PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
T2D type II diabetes mellitus 183,830
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000713/ScoringFiles/PGS000713.txt.gz - Check Terms/Licenses
PGS000729
(T2D_PGS)
PGP000137 |
Ritchie SC et al. Nat Metab (2021)
Type 2 diabetes type II 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 type II diabetes mellitus 582
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000804/ScoringFiles/PGS000804.txt.gz - Check Terms/Licenses
PGS000805
(GRS582_T2Deur)
PGP000193 |
Polfus LM et al. HGG Adv (2021)
Type 2 diabetes type II diabetes mellitus 582
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000805/ScoringFiles/PGS000805.txt.gz - Check Terms/Licenses
PGS000806
(GRS582_T2Dafr)
PGP000193 |
Polfus LM et al. HGG Adv (2021)
Type 2 diabetes type II diabetes mellitus 582
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000806/ScoringFiles/PGS000806.txt.gz - Check Terms/Licenses
PGS000807
(GRS582_T2Dasn)
PGP000193 |
Polfus LM et al. HGG Adv (2021)
Type 2 diabetes type II diabetes mellitus 582
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000807/ScoringFiles/PGS000807.txt.gz - Check Terms/Licenses
PGS000808
(GRS582_T2Dhis)
PGP000193 |
Polfus LM et al. HGG Adv (2021)
Type 2 diabetes type II diabetes mellitus 582
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000808/ScoringFiles/PGS000808.txt.gz - Check Terms/Licenses
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 type II 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 type I 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 II 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 II 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 II 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 II 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 II 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 II 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 II 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 II 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 II 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 II 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 II 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 type II 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 II diabetes type II 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 I diabetes type I 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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
Non-insulin-dependent diabetes (time-to-event) type II 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. medRxiv (2021)
|Pre
Type 2 diabetes type II 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. medRxiv (2021)
|Pre
Insulin-dependent diabetes mellitus (time-to-event) type I 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. medRxiv (2021)
|Pre
Type 1 diabetes type I 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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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. medRxiv (2021)
|Pre
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 type II 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. medRxiv (2021)
|Pre
Age diabetes diagnosed diabetes mellitus,
age at diagnosis
26
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001371/ScoringFiles/PGS001371.txt.gz

Performance Metrics

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

PGS Performance
Metric ID (PPM)
Evaluated Score PGS Sample Set ID
(PSS)
Performance Source Trait PGS Effect Sizes
(per SD change)
Classification Metrics Other Metrics Covariates Included in the Model PGS Performance:
Other Relevant Information
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
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
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
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)
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
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
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
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)
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
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
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
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
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
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
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
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
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
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
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
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]
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]
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)
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)
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)
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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)
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.
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)
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
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
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
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
PPM007030 PGS001371
(GBE_INI2976)
PSS006886|
African Ancestry|
673 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: Age diabetes diagnosed : 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. medRxiv (2021)
|Pre
Reported Trait: Age diabetes diagnosed : 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. medRxiv (2021)
|Pre
Reported Trait: Age diabetes diagnosed : 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. medRxiv (2021)
|Pre
Reported Trait: Age diabetes diagnosed : 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. medRxiv (2021)
|Pre
Reported Trait: Age diabetes diagnosed : 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
PPM007448 PGS000924
(GBE_HC702)
PSS004600|
African Ancestry|
6,497 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism AUROC: 0.87825 [0.76546, 0.99105] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism AUROC: 0.89799 [0.85782, 0.93815] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism AUROC: 0.85394 [0.77864, 0.92924] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism AUROC: 0.90591 [0.88325, 0.92858] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of mineral metabolism AUROC: 0.70572 [0.64003, 0.77141] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of mineral metabolism AUROC: 0.72332 [0.56417, 0.88247] : 0.06686
Incremental AUROC (full-covars): 0.0
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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of mineral metabolism AUROC: 0.70459 [0.66766, 0.74152] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of mineral metabolism AUROC: 0.60481 [0.54255, 0.66706] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of mineral metabolism AUROC: 0.65351 [0.63175, 0.67527] : 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. medRxiv (2021)
|Pre
Reported Trait: Gout AUROC: 0.8285 [0.79138, 0.86562] : 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. medRxiv (2021)
|Pre
Reported Trait: Gout AUROC: 0.84973 [0.79458, 0.90489] : 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. medRxiv (2021)
|Pre
Reported Trait: Gout AUROC: 0.83619 [0.82126, 0.85113] : 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. medRxiv (2021)
|Pre
Reported Trait: Gout AUROC: 0.77913 [0.74649, 0.81177] : 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. medRxiv (2021)
|Pre
Reported Trait: Gout AUROC: 0.81572 [0.80628, 0.82516] Incremental AUROC (full-covars): 0.04061
PGS R2 (no covariates): 0.04014
: 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. medRxiv (2021)
|Pre
Reported Trait: TTE gout AUROC: 0.77537 [0.73576, 0.81498] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE gout AUROC: 0.8503 [0.79897, 0.90164] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE gout AUROC: 0.81772 [0.80388, 0.83156] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE gout AUROC: 0.76492 [0.73884, 0.79099] : 0.11928
Incremental AUROC (full-covars): 0.02377
PGS R2 (no covariates): 0.02209
PGS AUROC (no covariates): 0.61344 [0.57941, 0.64746]
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. medRxiv (2021)
|Pre
Reported Trait: TTE gout AUROC: 0.79258 [0.7842, 0.80095] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE non-insulin-dependent diabetes mellitus AUROC: 0.70052 [0.68094, 0.7201] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE non-insulin-dependent diabetes mellitus AUROC: 0.75536 [0.71488, 0.79584] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE non-insulin-dependent diabetes mellitus AUROC: 0.72888 [0.71557, 0.7422] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE non-insulin-dependent diabetes mellitus AUROC: 0.68707 [0.67293, 0.70121] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE non-insulin-dependent diabetes mellitus AUROC: 0.71038 [0.70256, 0.71821] : 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. medRxiv (2021)
|Pre
Reported Trait: Type 2 diabetes AUROC: 0.68145 [0.62426, 0.73864] : 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. medRxiv (2021)
|Pre
Reported Trait: Type 2 diabetes AUROC: 0.83509 [0.71831, 0.95186] : 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. medRxiv (2021)
|Pre
Reported Trait: Type 2 diabetes AUROC: 0.69318 [0.65625, 0.73011] : 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. medRxiv (2021)
|Pre
Reported Trait: Type 2 diabetes AUROC: 0.65806 [0.61856, 0.69756] : 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. medRxiv (2021)
|Pre
Reported Trait: Type 2 diabetes AUROC: 0.68247 [0.66155, 0.70338] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE insulin-dependent diabetes mellitus AUROC: 0.66885 [0.62172, 0.71599] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE insulin-dependent diabetes mellitus AUROC: 0.89264 [0.80447, 0.98081] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE insulin-dependent diabetes mellitus AUROC: 0.70536 [0.66494, 0.74577] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE insulin-dependent diabetes mellitus AUROC: 0.67679 [0.6379, 0.71568] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE insulin-dependent diabetes mellitus AUROC: 0.65986 [0.63673, 0.68299] : 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. medRxiv (2021)
|Pre
Reported Trait: Type 1 diabetes AUROC: 0.78146 [0.64554, 0.91738] : 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. medRxiv (2021)
|Pre
Reported Trait: Type 1 diabetes AUROC: 0.79737 [0.708, 0.88674] : 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. medRxiv (2021)
|Pre
Reported Trait: Type 1 diabetes AUROC: 0.81031 [0.66359, 0.95703] : 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. medRxiv (2021)
|Pre
Reported Trait: Type 1 diabetes AUROC: 0.7643 [0.7041, 0.8245] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE obesity AUROC: 0.631 [0.60757, 0.65443] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE obesity AUROC: 0.65328 [0.53612, 0.77044] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE obesity AUROC: 0.59854 [0.58297, 0.61411] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE obesity AUROC: 0.61415 [0.59079, 0.6375] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE obesity AUROC: 0.59555 [0.58697, 0.60413] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE vitamin b12 deficiency anaemia AUROC: 0.66063 [0.54547, 0.77579] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE vitamin b12 deficiency anaemia AUROC: 0.65118 [0.60827, 0.69409] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE vitamin b12 deficiency anaemia AUROC: 0.72387 [0.6834, 0.76434] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE vitamin b12 deficiency anaemia AUROC: 0.64482 [0.61972, 0.66993] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias AUROC: 0.72671 [0.71075, 0.74267] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias AUROC: 0.72108 [0.68694, 0.75523] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias AUROC: 0.74382 [0.73637, 0.75127] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias AUROC: 0.7175 [0.70581, 0.7292] : 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
PPM009132 PGS001329
(GBE_HC652)
PSS004580|
African Ancestry|
6,497 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: TTE unspecified diabetes mellitus AUROC: 0.69503 [0.67407, 0.716] : 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
PPM009087 PGS001318
(GBE_HC700)
PSS004599|
European Ancestry|
67,425 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias AUROC: 0.73453 [0.73009, 0.73896] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE other metabolic disorders AUROC: 0.77406 [0.68678, 0.86135] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE other metabolic disorders AUROC: 0.70958 [0.62744, 0.79171] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE other metabolic disorders AUROC: 0.64684 [0.54842, 0.74526] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE other metabolic disorders AUROC: 0.60186 [0.54294, 0.66079] : 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. medRxiv (2021)
|Pre
Reported Trait: Diabetes AUROC: 0.68586 [0.66802, 0.7037] : 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. medRxiv (2021)
|Pre
Reported Trait: Diabetes AUROC: 0.69569 [0.64958, 0.7418] : 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. medRxiv (2021)
|Pre
Reported Trait: Diabetes AUROC: 0.70541 [0.69227, 0.71854] : 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. medRxiv (2021)
|Pre
Reported Trait: Diabetes AUROC: 0.68746 [0.67395, 0.70097] : 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. medRxiv (2021)
|Pre
Reported Trait: Diabetes AUROC: 0.69818 [0.69047, 0.70589] : 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
PPM009133 PGS001329
(GBE_HC652)
PSS004581|
East Asian Ancestry|
1,704 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: TTE unspecified diabetes mellitus AUROC: 0.70891 [0.65305, 0.76477] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE unspecified diabetes mellitus AUROC: 0.72437 [0.70887, 0.73987] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE unspecified diabetes mellitus AUROC: 0.70359 [0.68854, 0.71865] : 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. medRxiv (2021)
|Pre
Reported Trait: TTE unspecified diabetes mellitus AUROC: 0.7046 [0.69521, 0.71399] : 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

Evaluated Samples

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
PSS004203
[
  • 145 cases
  • , 6,352 controls
]
African unspecified UKB
PSS004204
[
  • 46 cases
  • , 1,658 controls
]
East Asian UKB
PSS004205
[
  • 749 cases
  • , 24,156 controls
]
European non-white British ancestry UKB
PSS004206
[
  • 286 cases
  • , 7,545 controls
]
South Asian UKB
PSS004207
[
  • 2,391 cases
  • , 65,034 controls
]
European white British ancestry UKB Testing cohort (heldout set)
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.
[
  • 5,853 cases
  • , 283,125 controls
]
European UKB UKB Phase 2
PSS000754 87,413 individuals European UKB
PSS000755 87,413 individuals European UKB
PSS000756 ICD-10 E11.0 - E11.9
[
  • 17,519 cases
  • , 117,781 controls
]
European
(Finnish)
FinnGen
PSS000025 Incident cases of Type 2 Diabetes in 5.63 years follow-up
[
  • 302 cases
  • , 5,978 controls
]
,
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 cases
  • , 177 controls
]
,
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.
[
  • 84 cases
  • , 63 controls
]
,
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.
[
  • 65 cases
  • , 43 controls
]
,
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.
[
  • 478 cases
  • , 290 controls
]
,
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
[
  • 1,021 cases
  • , 2,928 controls
]
African unspecified 7 cohorts
  • BDC
  • ,CLEAR
  • ,GoKinD
  • ,NYCP
  • ,SEARCH
  • ,T1DGC
  • ,UAB
PSS000031 Cases are diagnosed with type 1 diabetes.
[
  • 61 cases
  • , 54 controls
]
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)
[
  • 387 cases
  • , 373,613 controls
]
European UKB
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.
[
  • 1,346 cases
  • , 19,684 controls
]
,
47.3 % Male samples
Mean (Age At Baseline) = 48.0 years European
(Finnish)
FINRISK FINRISK surveys from 1992, 1997, 2002 and 2007
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.
[
  • 17,519 cases
  • , 117,781 controls
]
,
43.7 % Male samples
Mean (Age At Baseline) = 59.2 years
Sd = 16.6 years
European
(Finnish)
FinnGen
PSS000815 87,413 individuals European UKB
PSS000816 ICD-10 M10
[
  • 1,936 cases
  • , 133,364 controls
]
European
(Finnish)
FinnGen
PSS000042 T2D was defined by a fasting plasma glucose ≥7.0 mmol/L (≥126 mg/dL) or report of taking diabetes medications
[
  • 118 cases
  • , 702 controls
]
,
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
[
  • 97 cases
  • , 1,553 controls
]
,
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
[
  • 446 cases
  • , 3,025 controls
]
,
46.6 % Male samples
European FOS
PSS004312
[
  • 89 cases
  • , 6,408 controls
]
African unspecified UKB
PSS004313
[
  • 16 cases
  • , 1,688 controls
]
East Asian UKB
PSS004314
[
  • 180 cases
  • , 24,725 controls
]
European non-white British ancestry UKB
PSS004315
[
  • 171 cases
  • , 7,660 controls
]
South Asian UKB
PSS004316
[
  • 581 cases
  • , 66,844 controls
]
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 cases
  • , 213 controls
]
,
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
[
  • 22 cases
  • , 221 controls
]
,
32.0 % Male samples
European PHB
PSS006886 673 individuals African unspecified UKB
PSS006887 86 individuals East Asian UKB
PSS000054 Prevalent T2D status was defined using self-reported medical history and medication
[
  • 13,480 cases
  • , 311,390 controls
]
European 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)
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
[
  • 387 cases
  • , 824 controls
]
,
43.0 % Male samples
European, African unspecified, Asian unspecified, NR Primarily European, African and Asian ancestry eMERGE
PSS004359
[
  • 1,023 cases
  • , 5,474 controls
]
African unspecified UKB
PSS004360
[
  • 132 cases
  • , 1,572 controls
]
East Asian UKB
PSS004361
[
  • 1,571 cases
  • , 23,334 controls
]
European non-white British ancestry UKB
PSS004362
[
  • 1,878 cases
  • , 5,953 controls
]
South Asian 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.
[
  • 2,499 cases
  • , 5,247 controls
]
,
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
PSS004363
[
  • 4,540 cases
  • , 62,885 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS000869 CALIBER rule-based phenotyping algorithms (https://github.com/spiros/chronological-map-phenotypes#diabetes) Median = 6.9 years
[
  • 27 cases
  • , 3,060 controls
]
,
51.0 % Male samples
Median = 44.0 years
IQR = [30.5, 54.7] years
European INTERVAL
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.
[
  • 1,963 cases
  • , 0 controls
]
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.
[
  • 805 cases
  • , 0 controls
]
,
33.91 % Male samples
European NR Maturity-onset diabetes of young (MODY) cases ascertained from the Genetic Βeta Cell Research Bank, Exeter, U.K.
PSS004452
[
  • 93 cases
  • , 6,404 controls
]
African unspecified UKB
PSS004453
[
  • 38 cases
  • , 1,666 controls
]
East Asian UKB
PSS004454
[
  • 486 cases
  • , 24,419 controls
]
European non-white British ancestry UKB
PSS004455
[
  • 175 cases
  • , 7,656 controls
]
South Asian UKB
PSS004456
[
  • 1,484 cases
  • , 65,941 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS004457
[
  • 9 cases
  • , 6,488 controls
]
African unspecified UKB
PSS004458
[
  • 33 cases
  • , 24,872 controls
]
European non-white British ancestry UKB
PSS004459
[
  • 7 cases
  • , 7,824 controls
]
South Asian UKB
PSS004460
[
  • 58 cases
  • , 67,367 controls
]
European white British ancestry UKB Testing cohort (heldout set)
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.
[
  • 5,972 cases
  • , 9,637 controls
]
African American or Afro-Caribbean ARIC, BMBB, 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.”.
[
  • 2,004 cases
  • , 2,572 controls
]
Asian unspecified BMBB, 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.
[
  • 19,786 cases
  • , 403,943 controls
]
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.
[
  • 4,137 cases
  • , 16,349 controls
]
Hispanic or Latin American BMBB, 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.
[
  • 1,534 cases
  • , 2,017 controls
]
Oceanian
(Native Hawaiian)
MEC
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.
[
  • 317 cases
  • , 1,608 controls
]
African American or Afro-Caribbean Mount Sinai
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.
[
  • 90 cases
  • , 888 controls
]
European Mount Sinai
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.
[
  • 90 cases
  • , 888 controls
]
European Mount Sinai
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.
[
  • 317 cases
  • , 1,608 controls
]
African American or Afro-Caribbean Mount Sinai
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.
[
  • 507 cases
  • , 2,182 controls
]
Hispanic or Latin American Mount Sinai
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.
[
  • 49 cases
  • , 438 controls
]
Asian unspecified, Native American, NR Mount Sinai
PSS004536
[
  • 19 cases
  • , 6,478 controls
]
African unspecified UKB
PSS004538
[
  • 160 cases
  • , 24,745 controls
]
European non-white British ancestry UKB
PSS004539
[
  • 138 cases
  • , 7,693 controls
]
South Asian UKB
PSS004540
[
  • 447 cases
  • , 66,978 controls
]
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
[
  • 305 cases
  • , 7,493 controls
]
,
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.
PSS003606
[
  • 4,659 cases
  • , 173,479 controls
]
Mean = 56.81 years European UKB
PSS004570
[
  • 119 cases
  • , 6,378 controls
]
African unspecified UKB
PSS004571
[
  • 5 cases
  • , 1,699 controls
]
East Asian UKB
PSS004572
[
  • 186 cases
  • , 24,719 controls
]
European non-white British ancestry UKB
PSS004573
[
  • 153 cases
  • , 7,678 controls
]
South Asian UKB
PSS004574
[
  • 568 cases
  • , 66,857 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS004575
[
  • 806 cases
  • , 5,691 controls
]
African unspecified UKB
PSS004576
[
  • 106 cases
  • , 1,598 controls
]
East Asian UKB
PSS004577
[
  • 1,354 cases
  • , 23,551 controls
]
European non-white British ancestry UKB
PSS004578
[
  • 1,637 cases
  • , 6,194 controls
]
South Asian UKB
PSS004579
[
  • 4,071 cases
  • , 63,354 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS004580
[
  • 676 cases
  • , 5,821 controls
]
African unspecified UKB
PSS004581
[
  • 85 cases
  • , 1,619 controls
]
East Asian UKB
PSS004582
[
  • 964 cases
  • , 23,941 controls
]
European non-white British ancestry UKB
PSS004583
[
  • 1,284 cases
  • , 6,547 controls
]
South Asian UKB
PSS004584
[
  • 2,899 cases
  • , 64,526 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS004590
[
  • 536 cases
  • , 5,961 controls
]
African unspecified UKB
PSS004591
[
  • 27 cases
  • , 1,677 controls
]
East Asian UKB
PSS004592
[
  • 1,355 cases
  • , 23,550 controls
]
European non-white British ancestry UKB
PSS004593
[
  • 564 cases
  • , 7,267 controls
]
South Asian UKB
PSS004594
[
  • 4,477 cases
  • , 62,948 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS001084 Moderate Age-Related Diabetes (MARD) vs. controls
[
  • 2,853 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001085 Moderate Obesity-related Diabetes (MOD) vs. controls
[
  • 1,372 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001086 Severe Autoimmune Diabetes (SAID) vs. controls
[
  • 450 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001087 Severe Insulin-Deficient Diabetes (SIDD) vs. controls
[
  • 1,186 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS001088 Severe Insulin-Resistant Diabetes (SIRD) vs. controls
[
  • 1,125 cases
  • , 2,744 controls
]
European Swedish ANDIS
PSS004600
[
  • 4 cases
  • , 6,493 controls
]
African unspecified UKB
PSS004595
[
  • 1,165 cases
  • , 5,332 controls
]
African unspecified UKB
PSS004602
[
  • 79 cases
  • , 24,826 controls
]
European non-white British ancestry UKB
PSS004603
[
  • 23 cases
  • , 7,808 controls
]
South Asian UKB
PSS004604
[
  • 215 cases
  • , 67,210 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS004605
[
  • 49 cases
  • , 6,448 controls
]
African unspecified UKB
PSS004606
[
  • 8 cases
  • , 1,696 controls
]
East Asian UKB
PSS004607
[
  • 225 cases
  • , 24,680 controls
]
European non-white British ancestry UKB
PSS004608
[
  • 65 cases
  • , 7,766 controls
]
South Asian UKB
PSS004609
[
  • 613 cases
  • , 66,812 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS004596
[
  • 243 cases
  • , 1,461 controls
]
East Asian UKB
PSS004610
[
  • 17 cases
  • , 6,480 controls
]
African unspecified UKB
PSS004611
[
  • 41 cases
  • , 24,864 controls
]
European non-white British ancestry UKB
PSS004612
[
  • 26 cases
  • , 7,805 controls
]
South Asian UKB
PSS004613
[
  • 112 cases
  • , 67,313 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS004597
[
  • 4,635 cases
  • , 20,270 controls
]
European non-white British ancestry UKB
PSS004598
[
  • 2,630 cases
  • , 5,201 controls
]
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.
[
  • 1,341 cases
  • , 4,399 controls
]
,
47.04 % Male samples
Mean = 20.0 years Not reported CGS, CWRU, FrGMC, JHU, UNC
PSS004599
[
  • 13,783 cases
  • , 53,642 controls
]
European white British ancestry UKB Testing cohort (heldout set)
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
[
  • 1,281 cases
  • , 66,948 controls
]
,
47.81 % Male samples
European UKB