| Title: | ExPRSweb: An online repository with polygenic risk scores for common health-related exposures |
| Journal: | American Journal of Human Genetics |
| Published: | 23 Sep 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36152628/ |
| DOI: | https://doi.org/10.1016/j.ajhg.2022.09.001 |
Publication 7053
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Abstract
Complex traits are influenced by genetic risk factors, lifestyle, and environmental variables, so-called exposures. Some exposures, e.g., smoking or lipid levels, have common genetic modifiers identified in genome-wide association studies. Because measurements are often unfeasible, exposure polygenic risk scores (ExPRSs) offer an alternative to study the influence of exposures on various phenotypes. Here, we collected publicly available summary statistics for 28 exposures and applied four common PRS methods to generate ExPRSs in two large biobanks: the Michigan Genomics Initiative and the UK Biobank. We established ExPRSs for 27 exposures and demonstrated their applicability in phenome-wide association studies and as predictors for common chronic conditions. Especially the addition of multiple ExPRSs showed, for several chronic conditions, an improvement compared to prediction models that only included traditional, disease-focused PRSs. To facilitate follow-up studies, we share all ExPRS constructs and generated results via an online repository called ExPRSweb.5 Authors
- Ying Ma
- Snehal Patil
- Xiang Zhou
- Bhramar Mukherjee
- Lars G Fritsche
Enabling scientific discoveries that improve human health