ExPRSweb: An online repository with polygenic risk scores for common health-related exposures

Ying Ma; Snehal Patil; Xiang Zhou; Bhramar Mukherjee; Lars G Fritsche

doi:10.1016/j.ajhg.2022.09.001

ExPRSweb: An online repository with polygenic risk scores for common health-related exposures

Am J Hum Genet. 2022 Oct 6;109(10):1742-1760. doi: 10.1016/j.ajhg.2022.09.001. Epub 2022 Sep 23.

Authors

Ying Ma¹, Snehal Patil¹, Xiang Zhou², Bhramar Mukherjee³, Lars G Fritsche⁴

Affiliations

¹ Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
² Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
³ Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; University of Michigan Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Institute for Data Science, University of Michigan, Ann Arbor, MI 48109, USA.
⁴ Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; University of Michigan Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: larsf@umich.edu.

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.

Keywords: EHR; GWAS; PGS; PRS; complex diseases; complex traits; electronic health records; exposures; polygenic risk scores; polygenic scores.

Publication types

Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Genetic Predisposition to Disease*
Genome-Wide Association Study*
Humans
Lipids
Multifactorial Inheritance / genetics
Risk Factors

Substances

Lipids

Abstract

Publication types

MeSH terms

Substances

Grants and funding