Predicted Trait | |
Reported Trait | Gout |
Mapped Trait(s) | gout (EFO_0004274) |
Score Construction | |
PGS Name | GRS13_gout |
Development Method | |
Name | Genome-wide significant SNPs |
Parameters | NR |
Variants | |
Original Genome Build | NR |
Number of Variants | 13 |
Effect Weight Type | beta |
PGS Source | |
PGS Catalog Publication (PGP) ID | PGP000522 |
Citation (link to publication) | Wu Q et al. J Psychosom Res (2023) |
Ancestry Distribution | |
Source of Variant Associations (GWAS) | European: 100% 71,473 individuals (100%) |
PGS Evaluation |
Study Identifiers | Sample Numbers | Sample Ancestry | Cohort(s) |
---|---|---|---|
GWAS Catalog: GCST012338 Europe PMC: 33832965 |
71,473 individuals | European | NR |
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 |
---|---|---|---|---|---|---|---|---|
PPM020157 | PSS011298| Multi-ancestry (including European)| 403,630 individuals |
PGP000522 | Wu Q et al. J Psychosom Res (2023) |
Reported Trait: Incident gout | — | — | p (interaction between PRS and sleep pattern): 0.043 | Age, sex, race, Townsend deprivation index (TDI), body mass index (BMI), smoking and drinking status, history of hypertension and diabetes, uric acid, total cholesterol, estimated glomerular filtration rate (eGFR) levels, the use of diuretics medications | — |
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 |
---|---|---|---|---|---|---|---|---|
PSS011298 | — | — | 382,477 individuals | — | European | — | UKB | — |
PSS011298 | — | — | 21,153 individuals | — | Not reported | — | UKB | — |