Trait: self-reported trait

Experimental Factor Ontology (EFO) Information
Identifier EFO_0009799
Description Characteristics of an individual that are reported by the individual, usually to medical staff, including via questionnaires, rather than observed or measured directly by medical staff.
Trait category
Other trait
Child trait(s) 8 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 "self-reported trait" 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)
PGS000140
(GPpsy)
PGP000068 |
Cai N et al. Nat Genet (2020)
Broad Depression (seen a General Practitioner for nerves, anxiety, tension or depression) seeing a general practitioner for nerves, anxiety, tension or depression, self-reported,
depressive disorder
24,665
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000140/ScoringFiles/PGS000140.txt.gz
PGS000141
(Psypsy)
PGP000068 |
Cai N et al. Nat Genet (2020)
Seen a psychiatrist for nerves, anxiety, tension or depression seeing a psychiatrist for nerves, anxiety, tension or depression, self-reported,
depressive disorder
22,728
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000141/ScoringFiles/PGS000141.txt.gz
PGS000142
(DepAll)
PGP000068 |
Cai N et al. Nat Genet (2020)
Probable Depression (low mood or anhedonia, and seen a GP or psychiatrist for nerves, anxiety, tension or depression) seeing a general practitioner for nerves, anxiety, tension or depression, self-reported,
seeing a psychiatrist for nerves, anxiety, tension or depression, self-reported,
depressive disorder
21,908
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000142/ScoringFiles/PGS000142.txt.gz
PGS000143
(GPNoDep)
PGP000068 |
Cai N et al. Nat Genet (2020)
Seen a General Practitioner for nerves, anxiety, tension or depression (without report of low mood or anhedonia) seeing a general practitioner for nerves, anxiety, tension or depression, self-reported 21,042
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000143/ScoringFiles/PGS000143.txt.gz
PGS000144
(SelfRepDep)
PGP000068 |
Cai N et al. Nat Genet (2020)
Self-reported depression or depression symptoms depressive symptom measurement,
self-reported trait
21,828
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000144/ScoringFiles/PGS000144.txt.gz
PGS000716
(PGS295_elbs)
PGP000132 |
Richardson TG et al. BMJ (2020)
Early life body size body mass index,
comparative body size at age 10, self-reported
295
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000716/ScoringFiles/PGS000716.txt.gz
PGS000998
(GBE_QT_FC1001697)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Comparative body height at age 10 comparative body size at age 10, self-reported 24,144
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000998/ScoringFiles/PGS000998.txt.gz
PGS000999
(GBE_QT_FC1001687)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Comparative body size at age 10 comparative body size at age 10, self-reported 13,034
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000999/ScoringFiles/PGS000999.txt.gz
PGS001000
(GBE_QT_FC1001190)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Nap during day nap during day, self-reported 10,264
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001000/ScoringFiles/PGS001000.txt.gz
PGS001001
(GBE_QT_FC1001170)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Getting up in morning ease of getting up in the morning, self-reported 7,743
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001001/ScoringFiles/PGS001001.txt.gz
PGS001003
(GBE_INI137)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Number of medications taken number of treatments or medications taken, self-reported 8,085
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001003/ScoringFiles/PGS001003.txt.gz
PGS001004
(GBE_INI135)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Number of non-cancer illnesses number of non-cancer illnesses, self-reported 5,212
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001004/ScoringFiles/PGS001004.txt.gz
PGS001005
(GBE_INI134)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Number of self reported cancers number of cancers, self-reported 526
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001005/ScoringFiles/PGS001005.txt.gz
PGS001006
(GBE_BIN_FC1002306)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Weight change compared with 1 year ago body weight,
self-reported trait
2,638
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001006/ScoringFiles/PGS001006.txt.gz
PGS001114
(GBE_BIN_FC8006154)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Ibuprofen use self-reported NSAID use measurement,
self-reported trait
419
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001114/ScoringFiles/PGS001114.txt.gz
PGS001115
(GBE_BIN_FC9006154)
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Paracetamol use self-reported NSAID use measurement,
self-reported trait
4,673
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001115/ScoringFiles/PGS001115.txt.gz
PGS002254
(PRS_reported)
PGP000280 |
Kujala UM et al. Med Sci Sports Exerc (2020)
Physical activity (self-reported) physical activity measurement,
self-reported trait
1,142,416
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002254/ScoringFiles/PGS002254.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
PPM000432 PGS000140
(GPpsy)
PSS000250|
European Ancestry|
36,709 individuals
PGP000068 |
Cai N et al. Nat Genet (2020)
Reported Trait: Major Depressive Disorder status AUROC: 0.53193 : 0.00481 Cohort
PPM000433 PGS000141
(Psypsy)
PSS000250|
European Ancestry|
36,709 individuals
PGP000068 |
Cai N et al. Nat Genet (2020)
Reported Trait: Major Depressive Disorder status AUROC: 0.52988 : 0.00438 Cohort
PPM000434 PGS000142
(DepAll)
PSS000250|
European Ancestry|
36,709 individuals
PGP000068 |
Cai N et al. Nat Genet (2020)
Reported Trait: Major Depressive Disorder status AUROC: 0.5333 : 0.00492 Cohort
PPM000435 PGS000143
(GPNoDep)
PSS000250|
European Ancestry|
36,709 individuals
PGP000068 |
Cai N et al. Nat Genet (2020)
Reported Trait: Major Depressive Disorder status AUROC: 0.53441 : 0.00471 Cohort
PPM000436 PGS000144
(SelfRepDep)
PSS000250|
European Ancestry|
36,709 individuals
PGP000068 |
Cai N et al. Nat Genet (2020)
Reported Trait: Major Depressive Disorder status AUROC: 0.51641 : 0.00117 Cohort
PPM001708 PGS000716
(PGS295_elbs)
PSS000883|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 30-69.9 AUROC: 0.569 [0.564, 0.574] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001709 PGS000716
(PGS295_elbs)
PSS000876|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 12-15.9 AUROC: 0.656 [0.626, 0.686] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001710 PGS000716
(PGS295_elbs)
PSS000878|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 16-17.9 AUROC: 0.623 [0.589, 0.657] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001711 PGS000716
(PGS295_elbs)
PSS000880|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 18-23.9 AUROC: 0.601 [0.589, 0.612] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001712 PGS000716
(PGS295_elbs)
PSS000882|
European Ancestry|
17,139 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 14-29.9 AUROC: 0.591 [0.582, 0.6] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001713 PGS000716
(PGS295_elbs)
PSS000884|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 30-69.9 AUROC: 0.568 [0.563, 0.573] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001707 PGS000716
(PGS295_elbs)
PSS000879|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 18-23.9 AUROC: 0.618 [0.594, 0.641] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001687 PGS000716
(PGS295_elbs)
PSS000879|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 18-23.9 AUROC: 0.619 [0.596, 0.643] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001688 PGS000716
(PGS295_elbs)
PSS000881|
European Ancestry|
17,139 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 24-29.9 AUROC: 0.602 [0.585, 0.618] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001689 PGS000716
(PGS295_elbs)
PSS000883|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 30-69.9 AUROC: 0.569 [0.564, 0.574] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001690 PGS000716
(PGS295_elbs)
PSS000876|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 12-15.9 AUROC: 0.658 [0.628, 0.687] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001691 PGS000716
(PGS295_elbs)
PSS000878|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 16-17.9 AUROC: 0.624 [0.589, 0.658] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001692 PGS000716
(PGS295_elbs)
PSS000880|
European Ancestry|
12,179 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 18-23.9 AUROC: 0.602 [0.59, 0.613] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001693 PGS000716
(PGS295_elbs)
PSS000882|
European Ancestry|
17,139 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 14-29.9 AUROC: 0.591 [0.582, 0.6] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001633 PGS000716
(PGS295_elbs)
PSS000849|
European Ancestry|
5,898 individuals
PGP000132 |
Richardson TG et al. BMJ (2020)
Reported Trait: Childhood body mass index AUROC: 0.64
PPM001635 PGS000716
(PGS295_elbs)
PSS000847|
European Ancestry|
3,997 individuals
PGP000132 |
Richardson TG et al. BMJ (2020)
Reported Trait: Adolescent body mass index AUROC: 0.63
PPM001637 PGS000716
(PGS295_elbs)
PSS000848|
European Ancestry|
2,199 individuals
PGP000132 |
Richardson TG et al. BMJ (2020)
Reported Trait: Adult body mass index AUROC: 0.57
PPM001705 PGS000716
(PGS295_elbs)
PSS000875|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 12-15.9 AUROC: 0.739 [0.667, 0.811] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001706 PGS000716
(PGS295_elbs)
PSS000877|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 16-17.9 AUROC: 0.66 [0.566, 0.754] Due to a lack of information in the HUNT dataset, only 277 of the 295 common variants used to build the childhood score by Richardson et al were included.
PPM001685 PGS000716
(PGS295_elbs)
PSS000875|
European Ancestry|
3,124 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 12-15.9 AUROC: 0.735 [0.663, 0.806] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001686 PGS000716
(PGS295_elbs)
PSS000877|
European Ancestry|
2,896 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Obesity in individuals aged 16-17.9 AUROC: 0.672 [0.577, 0.766] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM001694 PGS000716
(PGS295_elbs)
PSS000884|
European Ancestry|
62,541 individuals
PGP000140 |
Brandkvist M et al. Hum Mol Genet (2020)
|Ext.
Reported Trait: Overweight in individuals aged 30-69.9 AUROC: 0.568 [0.563, 0.573] Due to a lack of information in the HUNT dataset, only 289 of the 295 common variants used to build the childhood score by Richardson et al were included. Additionally, 11 of the 289 common variants were proxies. Proxy SNPs were accepted if they had an R^2 ≥0.8 as well as a D’ ≥0.95 using publicly available reference haplotypes of a European British in England and Scotland population from Phase 3 (Version 5) of the 1000 Genomes Project.
PPM007753 PGS000998
(GBE_QT_FC1001697)
PSS007576|
African Ancestry|
6,049 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Comparative height size at age 10 : 0.02069 [0.01384, 0.02754]
Incremental R2 (full-covars): 0.01167
PGS R2 (no covariates): 0.0149 [0.00905, 0.02074]
age, sex, UKB array type, Genotype PCs
PPM007754 PGS000998
(GBE_QT_FC1001697)
PSS007577|
East Asian Ancestry|
1,574 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Comparative height size at age 10 : 0.05189 [0.03143, 0.07236]
Incremental R2 (full-covars): 0.02937
PGS R2 (no covariates): 0.03568 [0.01842, 0.05294]
age, sex, UKB array type, Genotype PCs
PPM007755 PGS000998
(GBE_QT_FC1001697)
PSS007578|
European Ancestry|
24,391 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Comparative height size at age 10 : 0.1366 [0.12868, 0.14453]
Incremental R2 (full-covars): 0.12631
PGS R2 (no covariates): 0.13848 [0.13052, 0.14644]
age, sex, UKB array type, Genotype PCs
PPM007756 PGS000998
(GBE_QT_FC1001697)
PSS007579|
South Asian Ancestry|
7,225 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Comparative height size at age 10 : 0.05926 [0.04912, 0.0694]
Incremental R2 (full-covars): 0.05228
PGS R2 (no covariates): 0.05606 [0.04617, 0.06596]
age, sex, UKB array type, Genotype PCs
PPM007757 PGS000998
(GBE_QT_FC1001697)
PSS007580|
European Ancestry|
66,430 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Comparative height size at age 10 : 0.1468 [0.14186, 0.15173]
Incremental R2 (full-covars): 0.14445
PGS R2 (no covariates): 0.14612 [0.1412, 0.15105]
age, sex, UKB array type, Genotype PCs
PPM007758 PGS000999
(GBE_QT_FC1001687)
PSS007571|
African Ancestry|
5,987 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Comparative body size at age 10 : 0.00794 [0.00364, 0.01223]
Incremental R2 (full-covars): 5e-05
PGS R2 (no covariates): 0.00274 [0.0002, 0.00527]
age, sex, UKB array type, Genotype PCs
PPM007759 PGS000999
(GBE_QT_FC1001687)
PSS007572|
East Asian Ancestry|
1,568 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Comparative body size at age 10 : 0.02263 [0.0087, 0.03657]
Incremental R2 (full-covars): 0.01234
PGS R2 (no covariates): 0.01384 [0.00284, 0.02483]
age, sex, UKB array type, Genotype PCs
PPM007760 PGS000999
(GBE_QT_FC1001687)
PSS007573|
European Ancestry|
24,369 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Comparative body size at age 10 : 0.05659 [0.05101, 0.06216]
Incremental R2 (full-covars): 0.05131
PGS R2 (no covariates): 0.0515 [0.04615, 0.05684]
age, sex, UKB array type, Genotype PCs
PPM007761 PGS000999
(GBE_QT_FC1001687)
PSS007574|
South Asian Ancestry|
7,142 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Comparative body size at age 10 Incremental R2 (full-covars): 0.01063
: 0.01573 [0.01026, 0.02119]
PGS R2 (no covariates): 0.01201 [0.00722, 0.0168]
age, sex, UKB array type, Genotype PCs
PPM007762 PGS000999
(GBE_QT_FC1001687)
PSS007575|
European Ancestry|
66,372 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Comparative body size at age 10 : 0.06039 [0.05691, 0.06388]
Incremental R2 (full-covars): 0.05578
PGS R2 (no covariates): 0.05527 [0.05191, 0.05862]
age, sex, UKB array type, Genotype PCs
PPM007763 PGS001000
(GBE_QT_FC1001190)
PSS007531|
African Ancestry|
6,354 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Nap during day : 0.02805 [0.02013, 0.03596]
Incremental R2 (full-covars): -0.0026
PGS R2 (no covariates): 0.0015 [-0.00038, 0.00338]
age, sex, UKB array type, Genotype PCs
PPM007764 PGS001000
(GBE_QT_FC1001190)
PSS007532|
East Asian Ancestry|
1,639 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Nap during day : 0.04314 [0.02431, 0.06197]
Incremental R2 (full-covars): 0.00779
PGS R2 (no covariates): 0.00945 [0.00032, 0.01858]
age, sex, UKB array type, Genotype PCs
PPM007765 PGS001000
(GBE_QT_FC1001190)
PSS007533|
European Ancestry|
24,845 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Nap during day : 0.05039 [0.0451, 0.05569]
Incremental R2 (full-covars): 0.01434
PGS R2 (no covariates): 0.01525 [0.01223, 0.01827]
age, sex, UKB array type, Genotype PCs
PPM007766 PGS001000
(GBE_QT_FC1001190)
PSS007534|
South Asian Ancestry|
7,429 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Nap during day : 0.03321 [0.02541, 0.04101]
Incremental R2 (full-covars): 0.0042
PGS R2 (no covariates): 0.00671 [0.0031, 0.01031]
age, sex, UKB array type, Genotype PCs
PPM007767 PGS001000
(GBE_QT_FC1001190)
PSS007535|
European Ancestry|
67,398 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Nap during day : 0.06089 [0.05739, 0.06439]
Incremental R2 (full-covars): 0.01718
PGS R2 (no covariates): 0.01737 [0.01541, 0.01932]
age, sex, UKB array type, Genotype PCs
PPM007768 PGS001001
(GBE_QT_FC1001170)
PSS007521|
African Ancestry|
6,380 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Getting up in morning : 0.02759 [0.01974, 0.03544]
Incremental R2 (full-covars): -0.00068
PGS R2 (no covariates): 0.0016 [-0.00034, 0.00354]
age, sex, UKB array type, Genotype PCs
PPM007769 PGS001001
(GBE_QT_FC1001170)
PSS007522|
East Asian Ancestry|
1,654 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Getting up in morning : 0.05654 [0.03528, 0.0778]
Incremental R2 (full-covars): 0.01249
PGS R2 (no covariates): 0.00998 [0.00061, 0.01936]
age, sex, UKB array type, Genotype PCs
PPM007770 PGS001001
(GBE_QT_FC1001170)
PSS007523|
European Ancestry|
24,834 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Getting up in morning : 0.06844 [0.06239, 0.0745]
Incremental R2 (full-covars): 0.01035
PGS R2 (no covariates): 0.01095 [0.00838, 0.01352]
age, sex, UKB array type, Genotype PCs
PPM007771 PGS001001
(GBE_QT_FC1001170)
PSS007524|
South Asian Ancestry|
7,605 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Getting up in morning : 0.02641 [0.0194, 0.03341]
Incremental R2 (full-covars): -0.00065
PGS R2 (no covariates): 0.00176 [-0.0001, 0.00361]
age, sex, UKB array type, Genotype PCs
PPM007772 PGS001001
(GBE_QT_FC1001170)
PSS007525|
European Ancestry|
67,358 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Getting up in morning : 0.06645 [0.06282, 0.07008]
Incremental R2 (full-covars): 0.01088
PGS R2 (no covariates): 0.0111 [0.00953, 0.01267]
age, sex, UKB array type, Genotype PCs
PPM007778 PGS001003
(GBE_INI137)
PSS004836|
African Ancestry|
6,483 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of medications taken : 0.10873 [0.09444, 0.12301]
Incremental R2 (full-covars): -0.00564
PGS R2 (no covariates): 0.00035 [-0.00056, 0.00126]
age, sex, UKB array type, Genotype PCs
PPM007779 PGS001003
(GBE_INI137)
PSS004837|
East Asian Ancestry|
1,702 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of medications taken : 0.10438 [0.07695, 0.1318]
Incremental R2 (full-covars): -0.01455
PGS R2 (no covariates): 3e-05 [-0.00047, 0.00053]
age, sex, UKB array type, Genotype PCs
PPM007780 PGS001003
(GBE_INI137)
PSS004838|
European Ancestry|
24,894 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of medications taken : 0.09752 [0.09052, 0.10452]
Incremental R2 (full-covars): 0.01417
PGS R2 (no covariates): 0.01416 [0.01125, 0.01708]
age, sex, UKB array type, Genotype PCs
PPM007781 PGS001003
(GBE_INI137)
PSS004839|
South Asian Ancestry|
7,812 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of medications taken : 0.13684 [0.1227, 0.15098]
Incremental R2 (full-covars): 0.00757
PGS R2 (no covariates): 0.00724 [0.0035, 0.01098]
age, sex, UKB array type, Genotype PCs
PPM007782 PGS001003
(GBE_INI137)
PSS004840|
European Ancestry|
67,419 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of medications taken : 0.08553 [0.0815, 0.08957]
Incremental R2 (full-covars): 0.01548
PGS R2 (no covariates): 0.01558 [0.01372, 0.01743]
age, sex, UKB array type, Genotype PCs
PPM007783 PGS001004
(GBE_INI135)
PSS004831|
African Ancestry|
6,483 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of self-reported non-cancer illnesses : 0.09535 [0.08177, 0.10893]
Incremental R2 (full-covars): -0.00187
PGS R2 (no covariates): 0.00097 [-0.00054, 0.00248]
age, sex, UKB array type, Genotype PCs
PPM007784 PGS001004
(GBE_INI135)
PSS004832|
East Asian Ancestry|
1,702 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of self-reported non-cancer illnesses : 0.07817 [0.05374, 0.10259]
Incremental R2 (full-covars): -0.00278
PGS R2 (no covariates): 0.0019 [-0.00222, 0.00603]
age, sex, UKB array type, Genotype PCs
PPM007785 PGS001004
(GBE_INI135)
PSS004833|
European Ancestry|
24,894 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of self-reported non-cancer illnesses : 0.06738 [0.06137, 0.0734]
Incremental R2 (full-covars): 0.0094
PGS R2 (no covariates): 0.00928 [0.00691, 0.01165]
age, sex, UKB array type, Genotype PCs
PPM007786 PGS001004
(GBE_INI135)
PSS004834|
South Asian Ancestry|
7,812 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of self-reported non-cancer illnesses : 0.10855 [0.09555, 0.12155]
Incremental R2 (full-covars): 0.00434
PGS R2 (no covariates): 0.00427 [0.00139, 0.00715]
age, sex, UKB array type, Genotype PCs
PPM007787 PGS001004
(GBE_INI135)
PSS004835|
European Ancestry|
67,419 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of self-reported non-cancer illnesses : 0.06288 [0.05934, 0.06643]
Incremental R2 (full-covars): 0.01064
PGS R2 (no covariates): 0.01063 [0.00909, 0.01217]
age, sex, UKB array type, Genotype PCs
PPM007788 PGS001005
(GBE_INI134)
PSS004826|
African Ancestry|
6,483 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of self-reported cancers : 0.01182 [0.00659, 0.01704]
Incremental R2 (full-covars): -0.00015
PGS R2 (no covariates): 0.00029 [-0.00054, 0.00112]
age, sex, UKB array type, Genotype PCs
PPM007789 PGS001005
(GBE_INI134)
PSS004827|
East Asian Ancestry|
1,702 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of self-reported cancers : 0.02753 [0.01224, 0.04282]
Incremental R2 (full-covars): -0.00083
PGS R2 (no covariates): 0.00016 [-0.00104, 0.00136]
age, sex, UKB array type, Genotype PCs
PPM007790 PGS001005
(GBE_INI134)
PSS004828|
European Ancestry|
24,894 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of self-reported cancers : 0.02065 [0.01715, 0.02414]
Incremental R2 (full-covars): 0.00068
PGS R2 (no covariates): 0.00081 [0.00011, 0.00152]
age, sex, UKB array type, Genotype PCs
PPM007791 PGS001005
(GBE_INI134)
PSS004829|
South Asian Ancestry|
7,812 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of self-reported cancers : 0.00918 [0.00497, 0.01338]
Incremental R2 (full-covars): -0.00087
PGS R2 (no covariates): 0.00012 [-0.00037, 0.00062]
age, sex, UKB array type, Genotype PCs
PPM007792 PGS001005
(GBE_INI134)
PSS004830|
European Ancestry|
67,419 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: # of self-reported cancers : 0.01676 [0.01484, 0.01868]
Incremental R2 (full-covars): 0.00083
PGS R2 (no covariates): 0.00079 [0.00036, 0.00121]
age, sex, UKB array type, Genotype PCs
PPM007793 PGS001006
(GBE_BIN_FC1002306)
PSS003760|
African Ancestry|
6,079 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Weight change compared with 1 year ago AUROC: 0.62073 [0.60627, 0.63518] : 0.05769
Incremental AUROC (full-covars): -1e-05
PGS R2 (no covariates): 0.00038
PGS AUROC (no covariates): 0.50745 [0.49252, 0.52238]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007794 PGS001006
(GBE_BIN_FC1002306)
PSS003761|
East Asian Ancestry|
1,602 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Weight change compared with 1 year ago AUROC: 0.59942 [0.57137, 0.62747] : 0.04761
Incremental AUROC (full-covars): 0.00968
PGS R2 (no covariates): 0.00719
PGS AUROC (no covariates): 0.53616 [0.5075, 0.56482]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007795 PGS001006
(GBE_BIN_FC1002306)
PSS003762|
European Ancestry|
24,477 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Weight change compared with 1 year ago AUROC: 0.57635 [0.56917, 0.58352] : 0.02324
Incremental AUROC (full-covars): 0.00533
PGS R2 (no covariates): 0.00365
PGS AUROC (no covariates): 0.5289 [0.52165, 0.53616]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007796 PGS001006
(GBE_BIN_FC1002306)
PSS003763|
South Asian Ancestry|
7,281 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Weight change compared with 1 year ago AUROC: 0.60517 [0.59225, 0.61809] : 0.04456
Incremental AUROC (full-covars): -0.00065
PGS R2 (no covariates): 0.00024
PGS AUROC (no covariates): 0.50809 [0.49482, 0.52135]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007797 PGS001006
(GBE_BIN_FC1002306)
PSS003764|
European Ancestry|
66,390 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Weight change compared with 1 year ago AUROC: 0.58453 [0.5802, 0.58886] : 0.02896
Incremental AUROC (full-covars): 0.00463
PGS R2 (no covariates): 0.00376
PGS AUROC (no covariates): 0.5295 [0.5251, 0.5339]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008308 PGS001114
(GBE_BIN_FC8006154)
PSS004019|
African Ancestry|
4,198 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Ibuprofen use self-reported AUROC: 0.58623 [0.56747, 0.60499] : 0.02659
Incremental AUROC (full-covars): 0.00105
PGS R2 (no covariates): 0.00105
PGS AUROC (no covariates): 0.51676 [0.49751, 0.53601]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008309 PGS001114
(GBE_BIN_FC8006154)
PSS004020|
East Asian Ancestry|
1,283 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Ibuprofen use self-reported AUROC: 0.63391 [0.58944, 0.67838] : 0.07333
Incremental AUROC (full-covars): 0.00219
PGS R2 (no covariates): 0.00605
PGS AUROC (no covariates): 0.55222 [0.50424, 0.60019]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008310 PGS001114
(GBE_BIN_FC8006154)
PSS004021|
European Ancestry|
18,055 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Ibuprofen use self-reported AUROC: 0.59904 [0.58905, 0.60903] : 0.03286
Incremental AUROC (full-covars): 0.00267
PGS R2 (no covariates): 0.00221
PGS AUROC (no covariates): 0.52523 [0.51521, 0.53524]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008311 PGS001114
(GBE_BIN_FC8006154)
PSS004022|
South Asian Ancestry|
4,705 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Ibuprofen use self-reported AUROC: 0.61281 [0.59188, 0.63374] : 0.036
Incremental AUROC (full-covars): -0.00199
PGS R2 (no covariates): 3e-05
PGS AUROC (no covariates): 0.49833 [0.47621, 0.52045]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008312 PGS001114
(GBE_BIN_FC8006154)
PSS004023|
European Ancestry|
47,828 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Ibuprofen use self-reported AUROC: 0.59831 [0.59215, 0.60447] : 0.03148
Incremental AUROC (full-covars): 0.00304
PGS R2 (no covariates): 0.00188
PGS AUROC (no covariates): 0.52406 [0.51781, 0.5303]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008313 PGS001115
(GBE_BIN_FC9006154)
PSS004024|
African Ancestry|
5,085 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Paracetamol use self-reported AUROC: 0.61918 [0.60368, 0.63468] : 0.05618
Incremental AUROC (full-covars): -0.00248
PGS R2 (no covariates): 0.00088
PGS AUROC (no covariates): 0.514 [0.49793, 0.53008]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008314 PGS001115
(GBE_BIN_FC9006154)
PSS004025|
East Asian Ancestry|
1,387 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Paracetamol use self-reported AUROC: 0.66023 [0.62475, 0.6957] : 0.10401
Incremental AUROC (full-covars): 0.00543
PGS R2 (no covariates): 0.00338
PGS AUROC (no covariates): 0.53113 [0.49267, 0.56958]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008315 PGS001115
(GBE_BIN_FC9006154)
PSS004026|
European Ancestry|
19,451 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Paracetamol use self-reported AUROC: 0.58754 [0.57874, 0.59635] : 0.02785
Incremental AUROC (full-covars): 0.01048
PGS R2 (no covariates): 0.0066
PGS AUROC (no covariates): 0.54192 [0.53304, 0.5508]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008316 PGS001115
(GBE_BIN_FC9006154)
PSS004027|
South Asian Ancestry|
5,818 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Paracetamol use self-reported AUROC: 0.62877 [0.61375, 0.6438] : 0.06084
Incremental AUROC (full-covars): 0.00451
PGS R2 (no covariates): 0.0045
PGS AUROC (no covariates): 0.53799 [0.52235, 0.55363]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008317 PGS001115
(GBE_BIN_FC9006154)
PSS004028|
European Ancestry|
52,582 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Paracetamol use self-reported AUROC: 0.60087 [0.59559, 0.60615] : 0.03601
Incremental AUROC (full-covars): 0.01595
PGS R2 (no covariates): 0.01072
PGS AUROC (no covariates): 0.55514 [0.54977, 0.56051]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM012823 PGS002254
(PRS_reported)
PSS009569|
European Ancestry|
11,528 individuals
PGP000280 |
Kujala UM et al. Med Sci Sports Exerc (2020)
Reported Trait: Daily leisure-time physical activity (MET score) β: 0.1717 (0.0323) ΔR2 (%): 0.25 age, sex, and four genetic principal components
PPM012824 PGS002254
(PRS_reported)
PSS009571|
European Ancestry|
4,061 individuals
PGP000280 |
Kujala UM et al. Med Sci Sports Exerc (2020)
Reported Trait: Daily leisure-time physical activity (MET score) β: 0.0355 (0.0113) ΔR2 (%): 0.24 age, sex, and four genetic principal components

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
PSS004028
[
  • 15,397 cases
  • , 37,185 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS004023
[
  • 10,489 cases
  • , 37,339 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS004024
[
  • 2,117 cases
  • , 2,968 controls
]
African unspecified UKB
PSS004839 7,812 individuals South Asian UKB
PSS004025
[
  • 278 cases
  • , 1,109 controls
]
East Asian UKB
PSS004026
[
  • 5,524 cases
  • , 13,927 controls
]
European non-white British ancestry UKB
PSS004826 6,483 individuals African unspecified UKB
PSS004827 1,702 individuals East Asian UKB
PSS004828 24,894 individuals European non-white British ancestry UKB
PSS004829 7,812 individuals South Asian UKB
PSS004830 67,419 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS004831 6,483 individuals African unspecified UKB
PSS004832 1,702 individuals East Asian UKB
PSS007521 6,380 individuals African unspecified UKB
PSS007522 1,654 individuals East Asian UKB
PSS007523 24,834 individuals European non-white British ancestry UKB
PSS007524 7,605 individuals South Asian UKB
PSS007525 67,358 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS004836 6,483 individuals African unspecified UKB
PSS004837 1,702 individuals East Asian UKB
PSS004838 24,894 individuals European non-white British ancestry UKB
PSS000847 Measurs of BMI were dichotomised to classify individuals higher than th 85th centiles as overweight. 3,997 individuals Mean = 17.8 years European ALSPAC ALSPAC offspring
PSS000848 Measurs of BMI were dichotomised to classify individuals higher than th 85th centiles as overweight. 2,199 individuals,
0.0 % Male samples
Mean = 50.8 years European ALSPAC ALSPAC mothers
PSS000849 Measurs of BMI were dichotomised to classify individuals higher than th 85th centiles as overweight. 5,898 individuals Mean = 9.9 years European ALSPAC ALSPAC offspring
PSS007531 6,354 individuals African unspecified UKB
PSS007532 1,639 individuals East Asian UKB
PSS007533 24,845 individuals European non-white British ancestry UKB
PSS007534 7,429 individuals South Asian UKB
PSS007535 67,398 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS004840 67,419 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS004833 24,894 individuals European non-white British ancestry UKB
PSS004019
[
  • 1,214 cases
  • , 2,984 controls
]
African unspecified UKB
PSS004020
[
  • 166 cases
  • , 1,117 controls
]
East Asian UKB
PSS007571 5,987 individuals African unspecified UKB
PSS007572 1,568 individuals East Asian UKB
PSS007573 24,369 individuals European non-white British ancestry UKB
PSS007574 7,142 individuals South Asian UKB
PSS007575 66,372 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS007576 6,049 individuals African unspecified UKB
PSS007577 1,574 individuals East Asian UKB
PSS007578 24,391 individuals European non-white British ancestry UKB
PSS007579 7,225 individuals South Asian UKB
PSS007580 66,430 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS009569 11,528 individuals,
46.0 % Male samples
Mean = 44.0 years European
(Finnish)
FTC
PSS004021
[
  • 4,084 cases
  • , 13,971 controls
]
European non-white British ancestry UKB
PSS004835 67,419 individuals European white British ancestry UKB Testing cohort (heldout set)
PSS003763
[
  • 3,505 cases
  • , 3,776 controls
]
South Asian UKB
PSS009571 4,061 individuals,
48.0 % Male samples
Mean = 46.0 years European
(Finnish)
NFBC
PSS003764
[
  • 30,581 cases
  • , 35,809 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS000875 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth. To defiine corresponding cut-offs for obesity and overweight for participants younger than 18 years, BMI z score was calulated using age and sex specific reference from the International Obesity Task Force.
[
  • 37 cases
  • , 3,087 controls
]
European HUNT
PSS000876 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth. To defiine corresponding cut-offs for obesity and overweight for participants younger than 18 years, BMI z score was calulated using age and sex specific reference from the International Obesity Task Force.
[
  • 344 cases
  • , 2,780 controls
]
European HUNT
PSS000877 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth. To defiine corresponding cut-offs for obesity and overweight for participants younger than 18 years, BMI z score was calulated using age and sex specific reference from the International Obesity Task Force.
[
  • 30 cases
  • , 2,866 controls
]
European HUNT
PSS000878 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth. To defiine corresponding cut-offs for obesity and overweight for participants younger than 18 years, BMI z score was calulated using age and sex specific reference from the International Obesity Task Force.
[
  • 274 cases
  • , 2,622 controls
]
European HUNT
PSS000879 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 542 cases
  • , 11,637 controls
]
European HUNT
PSS000880 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 2,898 cases
  • , 9,281 controls
]
European HUNT
PSS000881 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 1,240 cases
  • , 15,899 controls
]
European HUNT
PSS000882 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 5,775 cases
  • , 11,364 controls
]
European HUNT
PSS000883 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 15,112 cases
  • , 47,429 controls
]
European HUNT
PSS000884 BMI was calculated as weight in kilograms per height in metres squared. Weight was measured to the nearest half kilogram wih participants wearing light cloes and no shoes and height was measured to the nearest centimeter. WHO defines overweight as BMI greater than or equal to 25 and obesity as BMI greater than or equal to 30. BMI strongly related to longitudinal growth.
[
  • 43,408 cases
  • , 19,133 controls
]
European HUNT
PSS004834 7,812 individuals South Asian UKB
PSS003760
[
  • 3,717 cases
  • , 2,362 controls
]
African unspecified UKB
PSS000250
[
  • 14,696 cases
  • , 22,013 controls
]
European 15 cohorts
  • BOMA
  • ,CoLaus
  • ,Edinburgh
  • ,GenPOD
  • ,GenRED
  • ,MARS
  • ,MPIP
  • ,NESDA
  • ,QIMR
  • ,RADIANT
  • ,RS
  • ,SHIP
  • ,STAR*D
  • ,TwinGene
  • ,i2b2
Part of PGC29 (PMID: 29700475)
PSS003761
[
  • 664 cases
  • , 938 controls
]
East Asian UKB
PSS003762
[
  • 10,994 cases
  • , 13,483 controls
]
European non-white British ancestry UKB
PSS004022
[
  • 811 cases
  • , 3,894 controls
]
South Asian UKB
PSS004027
[
  • 1,958 cases
  • , 3,860 controls
]
South Asian UKB