Trait: waist-hip ratio

Experimental Factor Ontology (EFO) Information
Identifier EFO_0004343
Description The waist circumference measurement divided by the hip circumference measurement. For both men and women, a waist-to-hip ratio (WHR) of 1.0 or higher is considered "at risk" for undesirable health consequences, such as heart disease and ailments associated with OVERWEIGHT. A healthy WHR is 0.90 or less for men, and 0.80 or less for women. (National Center for Chronic Disease Prevention and Health Promotion, 2004)
Trait category
Body measurement
Mapped terms 2 mapped terms
  • MeSH:D049629
  • NCIt:C17651
Child trait(s) BMI-adjusted waist-hip ratio

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 "waist-hip ratio" 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)
PGS000299
(GRS462_WHRadjBMI)
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Waist-to-hip ratio (body mass index adjusted) BMI-adjusted waist-hip ratio 462
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000299/ScoringFiles/PGS000299.txt.gz
PGS000842
(WHR)
PGP000211 |
Aly DM et al. Nat Genet (2021)
Waist-hip ratio waist-hip ratio 39
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000842/ScoringFiles/PGS000842.txt.gz
PGS000843
(WHRadjBMI)
PGP000211 |
Aly DM et al. Nat Genet (2021)
WHR adjusted for BMI BMI-adjusted waist-hip ratio 63
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000843/ScoringFiles/PGS000843.txt.gz
PGS002356
(body_WHRadjBMIz.BOLT-LMM)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Waist-hip ratio waist-hip ratio 1,109,311
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002356/ScoringFiles/PGS002356.txt.gz
PGS002428
(body_WHRadjBMIz.P+T.0.0001)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Waist-hip ratio waist-hip ratio 9,477
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002428/ScoringFiles/PGS002428.txt.gz
PGS002477
(body_WHRadjBMIz.P+T.0.001)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Waist-hip ratio waist-hip ratio 27,033
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002477/ScoringFiles/PGS002477.txt.gz
PGS002526
(body_WHRadjBMIz.P+T.0.01)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Waist-hip ratio waist-hip ratio 126,268
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002526/ScoringFiles/PGS002526.txt.gz
PGS002575
(body_WHRadjBMIz.P+T.1e-06)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Waist-hip ratio waist-hip ratio 2,912
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002575/ScoringFiles/PGS002575.txt.gz
PGS002624
(body_WHRadjBMIz.P+T.5e-08)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Waist-hip ratio waist-hip ratio 1,829
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002624/ScoringFiles/PGS002624.txt.gz
PGS002673
(body_WHRadjBMIz.PolyFun-pred)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Waist-hip ratio waist-hip ratio 325,206
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002673/ScoringFiles/PGS002673.txt.gz
PGS002722
(body_WHRadjBMIz.SBayesR)
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Waist-hip ratio waist-hip ratio 984,160
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002722/ScoringFiles/PGS002722.txt.gz
PGS003484
(LDPred2_WHR)
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Waist-hip ratio waist-hip ratio 855,882
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003484/ScoringFiles/PGS003484.txt.gz
PGS003485
(LDPred2_WHRadjBMI)
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
BMI-adjusted waist-hip ratio BMI-adjusted waist-hip ratio 785,126
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003485/ScoringFiles/PGS003485.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
PPM000766 PGS000299
(GRS462_WHRadjBMI)
PSS000376|
European Ancestry|
1,354 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Waist-to-hip ratio : 0.0138 Sex, age, age^2, BMI
PPM000767 PGS000299
(GRS462_WHRadjBMI)
PSS000377|
European Ancestry|
1,174 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Waist-to-hip ratio : 0.0141 Sex, age, age^2, BMI
PPM000768 PGS000299
(GRS462_WHRadjBMI)
PSS000378|
European Ancestry|
1,095 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Waist-to-hip ratio : 0.0195 Sex, age, age^2, BMI
PPM000796 PGS000299
(GRS462_WHRadjBMI)
PSS000371|
European Ancestry|
288 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Waist-to-hip ratio : 0.01 Sex, age, age^2, BMI
PPM000797 PGS000299
(GRS462_WHRadjBMI)
PSS000372|
European Ancestry|
265 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Waist-to-hip ratio : 0.017 Sex, age, age^2, BMI
PPM000798 PGS000299
(GRS462_WHRadjBMI)
PSS000373|
European Ancestry|
245 individuals
PGP000092 |
Xie T et al. Circ Genom Precis Med (2020)
Reported Trait: Waist-to-hip ratio : 0.0156 Sex, age, age^2, BMI
PPM002293 PGS000842
(WHR)
PSS001086|
European Ancestry|
3,194 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Severe Autoimmune Diabetes OR: 1.13 [1.02, 1.25] PC1-10
PPM002295 PGS000842
(WHR)
PSS001088|
European Ancestry|
3,869 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Severe Insulin-Resistant Diabetes OR: 1.14 [1.06, 1.22] PC1-10
PPM002296 PGS000842
(WHR)
PSS001085|
European Ancestry|
4,116 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Moderate Obesity-related Diabetes OR: 1.1 [1.03, 1.18] PC1-10
PPM002297 PGS000842
(WHR)
PSS001084|
European Ancestry|
5,597 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Moderate Age-Related Diabetes OR: 1.03 [0.98, 1.08] PC1-10
PPM002294 PGS000842
(WHR)
PSS001087|
European Ancestry|
3,930 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Severe Insulin-Deficient Diabetes OR: 1.04 [0.97, 1.11] PC1-10
PPM020166 PGS000842
(WHR)
PSS011301|
South Asian Ancestry|
1,282 individuals
PGP000525 |
Yajnik CS et al. Lancet Reg Health Southeast Asia (2023)
|Ext.
Reported Trait: Type 2 diabetes OR: 1.17 [1.04, 1.32] sex
PPM020181 PGS000842
(WHR)
PSS011301|
South Asian Ancestry|
1,282 individuals
PGP000525 |
Yajnik CS et al. Lancet Reg Health Southeast Asia (2023)
|Ext.
Reported Trait: BMI β: 0.05687 (0.027539)
PPM020186 PGS000842
(WHR)
PSS011302|
South Asian Ancestry|
830 individuals
PGP000525 |
Yajnik CS et al. Lancet Reg Health Southeast Asia (2023)
|Ext.
Reported Trait: Severe insulin deficiency diabetes OR: 1.22 [1.06, 1.41] sex
PPM002298 PGS000843
(WHRadjBMI)
PSS001086|
European Ancestry|
3,194 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Severe Autoimmune Diabetes OR: 1.19 [1.08, 1.31] PC1-10
PPM002299 PGS000843
(WHRadjBMI)
PSS001087|
European Ancestry|
3,930 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Severe Insulin-Deficient Diabetes OR: 1.09 [1.02, 1.17] PC1-10
PPM002300 PGS000843
(WHRadjBMI)
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
PPM002301 PGS000843
(WHRadjBMI)
PSS001085|
European Ancestry|
4,116 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Moderate Obesity-related Diabetes OR: 1.03 [0.96, 1.1] PC1-10
PPM002302 PGS000843
(WHRadjBMI)
PSS001084|
European Ancestry|
5,597 individuals
PGP000211 |
Aly DM et al. Nat Genet (2021)
Reported Trait: Moderate Age-Related Diabetes OR: 1.05 [0.99, 1.1] PC1-10
PPM013121 PGS002356
(body_WHRadjBMIz.BOLT-LMM)
PSS009867|
African Ancestry|
6,423 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0167 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013170 PGS002356
(body_WHRadjBMIz.BOLT-LMM)
PSS009868|
East Asian Ancestry|
917 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0412 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013219 PGS002356
(body_WHRadjBMIz.BOLT-LMM)
PSS009869|
European Ancestry|
43,384 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0764 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013268 PGS002356
(body_WHRadjBMIz.BOLT-LMM)
PSS009870|
South Asian Ancestry|
8,026 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0414 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013409 PGS002428
(body_WHRadjBMIz.P+T.0.0001)
PSS009867|
African Ancestry|
6,423 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0036 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013458 PGS002428
(body_WHRadjBMIz.P+T.0.0001)
PSS009868|
East Asian Ancestry|
917 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.008 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013507 PGS002428
(body_WHRadjBMIz.P+T.0.0001)
PSS009869|
European Ancestry|
43,384 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0406 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013556 PGS002428
(body_WHRadjBMIz.P+T.0.0001)
PSS009870|
South Asian Ancestry|
8,026 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0201 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013605 PGS002477
(body_WHRadjBMIz.P+T.0.001)
PSS009867|
African Ancestry|
6,423 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0008 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013654 PGS002477
(body_WHRadjBMIz.P+T.0.001)
PSS009868|
East Asian Ancestry|
917 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0067 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013703 PGS002477
(body_WHRadjBMIz.P+T.0.001)
PSS009869|
European Ancestry|
43,384 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0413 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013752 PGS002477
(body_WHRadjBMIz.P+T.0.001)
PSS009870|
South Asian Ancestry|
8,026 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0164 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013801 PGS002526
(body_WHRadjBMIz.P+T.0.01)
PSS009867|
African Ancestry|
6,423 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0003 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013850 PGS002526
(body_WHRadjBMIz.P+T.0.01)
PSS009868|
East Asian Ancestry|
917 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0077 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013899 PGS002526
(body_WHRadjBMIz.P+T.0.01)
PSS009869|
European Ancestry|
43,384 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0224 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013948 PGS002526
(body_WHRadjBMIz.P+T.0.01)
PSS009870|
South Asian Ancestry|
8,026 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0048 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM013997 PGS002575
(body_WHRadjBMIz.P+T.1e-06)
PSS009867|
African Ancestry|
6,423 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0117 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014046 PGS002575
(body_WHRadjBMIz.P+T.1e-06)
PSS009868|
East Asian Ancestry|
917 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0221 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014095 PGS002575
(body_WHRadjBMIz.P+T.1e-06)
PSS009869|
European Ancestry|
43,384 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0313 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014144 PGS002575
(body_WHRadjBMIz.P+T.1e-06)
PSS009870|
South Asian Ancestry|
8,026 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0178 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014193 PGS002624
(body_WHRadjBMIz.P+T.5e-08)
PSS009867|
African Ancestry|
6,423 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0117 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014242 PGS002624
(body_WHRadjBMIz.P+T.5e-08)
PSS009868|
East Asian Ancestry|
917 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.016 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014291 PGS002624
(body_WHRadjBMIz.P+T.5e-08)
PSS009869|
European Ancestry|
43,384 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0273 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014340 PGS002624
(body_WHRadjBMIz.P+T.5e-08)
PSS009870|
South Asian Ancestry|
8,026 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.016 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014389 PGS002673
(body_WHRadjBMIz.PolyFun-pred)
PSS009867|
African Ancestry|
6,423 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0289 age, sex, age*sex, assessment center, genotyping array, 10 PCs See body_WHRadjBMIz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014438 PGS002673
(body_WHRadjBMIz.PolyFun-pred)
PSS009868|
East Asian Ancestry|
917 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0456 age, sex, age*sex, assessment center, genotyping array, 10 PCs See body_WHRadjBMIz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014487 PGS002673
(body_WHRadjBMIz.PolyFun-pred)
PSS009869|
European Ancestry|
43,384 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0799 age, sex, age*sex, assessment center, genotyping array, 10 PCs See body_WHRadjBMIz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014536 PGS002673
(body_WHRadjBMIz.PolyFun-pred)
PSS009870|
South Asian Ancestry|
8,026 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0442 age, sex, age*sex, assessment center, genotyping array, 10 PCs See body_WHRadjBMIz.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights
PPM014585 PGS002722
(body_WHRadjBMIz.SBayesR)
PSS009867|
African Ancestry|
6,423 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0214 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014634 PGS002722
(body_WHRadjBMIz.SBayesR)
PSS009868|
East Asian Ancestry|
917 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0413 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014683 PGS002722
(body_WHRadjBMIz.SBayesR)
PSS009869|
European Ancestry|
43,384 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0746 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM014732 PGS002722
(body_WHRadjBMIz.SBayesR)
PSS009870|
South Asian Ancestry|
8,026 individuals
PGP000332 |
Weissbrod O et al. Nat Genet (2022)
Reported Trait: Waist-Hip Ratio Incremental R2 (full model vs. covariates alone): 0.0416 age, sex, age*sex, assessment center, genotyping array, 10 PCs
PPM017316 PGS003484
(LDPred2_WHR)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea β: 0.009 (0.025) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017356 PGS003484
(LDPred2_WHR)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index in obsese β: 0.025 (0.017) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017357 PGS003484
(LDPred2_WHR)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index in non-obsese β: 0.015 (0.013) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017377 PGS003484
(LDPred2_WHR)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea in non-obsese β: -0.002 (0.036) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017293 PGS003484
(LDPred2_WHR)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index β: 0.019 (0.01) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017376 PGS003484
(LDPred2_WHR)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea in obsese β: 0.012 (0.035) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017400 PGS003484
(LDPred2_WHR)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index x obesity interaction β: -0.002 (0.998) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017410 PGS003484
(LDPred2_WHR)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea x obesity interaction β: 1.015 (0.05) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017294 PGS003485
(LDPred2_WHRadjBMI)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index β: 0.025 (0.01) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017358 PGS003485
(LDPred2_WHRadjBMI)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index in obsese β: 0.028 (0.017) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017359 PGS003485
(LDPred2_WHRadjBMI)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index in non-obsese β: 0.029 (0.013) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017378 PGS003485
(LDPred2_WHRadjBMI)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea in obsese β: 0.034 (0.035) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017379 PGS003485
(LDPred2_WHRadjBMI)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea in non-obsese β: 0.042 (0.035) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017317 PGS003485
(LDPred2_WHRadjBMI)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea β: 0.038 (0.025) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017401 PGS003485
(LDPred2_WHRadjBMI)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Respiratory event index x obesity interaction β: -0.016 (0.984) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI
PPM017411 PGS003485
(LDPred2_WHRadjBMI)
PSS010185|
Hispanic or Latin American Ancestry|
1,115 individuals
PGP000456 |
Zhang Y et al. EBioMedicine (2022)
Reported Trait: Obstructive sleep apnea x obesity interaction β: 0.993 (0.05) Age, sex, center, 5 genetic PCs, Hispanic/Latino background, BMI

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
PSS009868 917 individuals East Asian UKB
PSS009869 43,384 individuals European Non-British European UKB
PSS009870 8,026 individuals South Asian UKB
PSS000371 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 288 individuals,
69.2 % Male samples
Mean = 15.83 years
Sd = 0.6 years
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000372 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 265 individuals,
69.2 % Male samples
Mean = 19.2 years
Sd = 0.66 years
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000373 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 245 individuals,
69.2 % Male samples
Mean = 22.04 years
Sd = 0.69 years
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS011301
[
  • 821 cases
  • , 461 controls
]
South Asian
(Indian)
WellGen
PSS000376 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,354 individuals,
47.56 % Male samples
Mean = 16.22 years
Sd = 0.66 years
European TRAILS
PSS000377 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,174 individuals,
47.6 % Male samples
Mean = 19.2 years European TRAILS
PSS000378 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,095 individuals,
47.6 % Male samples
Mean = 22.4 years European TRAILS
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
PSS011302
[
  • 369 cases
  • , 461 controls
]
South Asian
(Indian)
WellGen
PSS010185 1,115 individuals,
41.1 % Male samples
Mean = 46.18 years Hispanic or Latin American HCHS, SOL
PSS009867 6,423 individuals African unspecified UKB