| Title: | Adjusting for population stratification in polygenic risk score analyses: a guide for model specifications in the UK Biobank |
| Journal: | Journal of Human Genetics |
| Published: | 15 May 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37188914/ |
| DOI: | https://doi.org/10.1038/s10038-023-01161-1 |
| Citations: | 2 (2 in last 2 years) as of 8 Aug 2024 |
Publication 7831
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Abstract
The current study was conducted to provide a general guidance for model specifications in polygenic risk score (PRS) analyses of the UK Biobank, such as adjusting for covariates (i.e. age, sex, recruitment centers, and genetic batch) and the number of principal components (PCs) that need to be included. To cover behavioral, physical and mental health outcomes, we evaluated three continuous outcomes (BMI, smoking, drinking) and two binary outcomes (Major Depressive Disorder and educational attainment). We applied 3280 (656 per phenotype) different models including different sets of covariates. We evaluated these different model specifications by comparing regression parameters such as R2, coefficients, and P values, as well as ANOVA tests. Findings suggest that only up to three PCs appears to be sufficient for controlling population stratification for most outcomes, whereas including other covariates (particularly age and sex) appears to be more essential for model performance.6 Authors
- Bochao Danae Lin
- Lotta-Katrin Pries
- Jim van Os
- Jurjen J. Luykx
- Bart P. F. Rutten
- Sinan Guloksuz
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