Polygenic Score (PGS) ID: PGS001004

Predicted Trait
Reported Trait Number of non-cancer illnesses
Mapped Trait(s) number of non-cancer illnesses, self-reported (EFO_0009801)
Additional Trait Information https://biobankengine.stanford.edu/RIVAS_HG19/snpnet/INI135
Released in PGS Catalog: Oct. 21, 2021
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Terms and Licenses
PGS obtained from the Catalog should be cited appropriately, and used in accordance with any licensing restrictions set by the authors. See EBI Terms of Use (https://www.ebi.ac.uk/about/terms-of-use/) for additional details.

Score Details

Score Construction
PGS Name GBE_INI135
Development Method
Name snpnet
Parameters NR
Variants
Original Genome Build GRCh37
Number of Variants 5,212
Effect Weight Type NR
PGS Source
PGS Catalog Publication (PGP) ID PGP000244
Citation (link to publication) Tanigawa Y et al. PLoS Genet (2022)
Ancestry Distribution
Score Development/Training
European: 100%
269,672 individuals (100%)
PGS Evaluation
European: 40%
African: 20%
East Asian: 20%
South Asian: 20%
5 Sample Sets

Development Samples

Score Development/Training
Study Identifiers Sample Numbers Sample Ancestry Cohort(s) Phenotype Definitions & Methods Age of Study Participants Participant Follow-up Time Additional Ancestry Description Additional Sample/Cohort Information
— 269,672 individuals European UKB — — — white British ancestry —

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) 		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
PPM007783 PSS004831|
African Ancestry|
6,483 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: # of self-reported non-cancer illnesses — — R²: 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 PSS004832|
East Asian Ancestry|
1,702 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: # of self-reported non-cancer illnesses — — R²: 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 PSS004833|
European Ancestry|
24,894 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: # of self-reported non-cancer illnesses — — R²: 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 PSS004834|
South Asian Ancestry|
7,812 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: # of self-reported non-cancer illnesses — — R²: 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 PSS004835|
European Ancestry|
67,419 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: # of self-reported non-cancer illnesses — — R²: 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 —

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
PSS004831 — — 6,483 individuals — African unspecified — UKB —
PSS004832 — — 1,702 individuals — East Asian — UKB —
PSS004833 — — 24,894 individuals — European non-white British ancestry UKB —
PSS004834 — — 7,812 individuals — South Asian — UKB —
PSS004835 — — 67,419 individuals — European white British ancestry UKB Testing cohort (heldout set)