| Publication Information (EuropePMC) | |
| Title | Healthy lifestyle counteracts the risk effect of genetic factors on incident gout: a large population-based longitudinal study. |
| PubMed ID | 35484537(Europe PMC) |
| doi | 10.1186/s12916-022-02341-0 |
| Publication Date | April 29, 2022 |
| Journal | BMC Med |
| Author(s) | Zhang Y, Yang R, Dove A, Li X, Yang H, Li S, Wang J, Li WD, Zhao H, Xu W, Wang Y. |
| Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants |
Ancestry distribution GWAS Dev Eval |
Scoring File (FTP Link) |
|---|---|---|---|---|---|---|
| PGS002307 (PRS33_gout) |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Gout | gout | 33 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002307/ScoringFiles/PGS002307.txt.gz |
|
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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM013045 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, highest vs. lowest tertile): 1.77 [1.66, 1.89] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI) | — |
| PPM013046 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout without cardiometabolic diseases | — | — | Hazard Ratio (HR, highest vs. lowest tertile): 4.94 [3.91, 6.23] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), Unfavorable lifestyle | — |
| PPM013047 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout with cardiometabolic diseases | — | — | Hazard Ratio (HR, highest vs. lowest tertile): 3.0 [2.62, 3.43] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), Unfavorable lifestyle | — |
| PPM013048 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, middle vs. lowest tertile): 1.53 [1.35, 1.74] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), favorable lifestyle | — |
| PPM013049 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, middle vs. lowest tertile): 2.39 [2.12, 2.7] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), unfavorable lifestyle | — |
| PPM013050 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, highest vs. lowest tertile): 1.98 [1.75, 2.24] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), favorable lifestyle | — |
| PPM013044 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, middle vs. lowest tertile): 1.44 [1.35, 1.54] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI) | — |
| PPM013051 | PGS002307 (PRS33_gout) |
PSS009665| European Ancestry| 416,481 individuals |
PGP000329 | Zhang Y et al. BMC Med (2022) |
Reported Trait: Incident gout | — | — | Hazard Ratio (HR, highest vs. lowest tertile): 3.13 [2.79, 3.52] | Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), unfavorable lifestyle | — |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS009665 | Gout was ascertained based on information from self- report (Data-Field 20002, code: 1466), medical records (ICD-10 codes: M10.0, M10.2, M10.3, M10.4, M10.9), and death records (ICD-10 codes: M10.0, M10.2, M10.3, M10.4, M10.9) | Median = 12.1 years | [ ,
45.9 % Male samples |
Mean = 56.6 years Sd = 8.0 years |
European | — | UKB | — |