Fields as diverse as human genetics and sociology are increasingly using polygenic scores based on genome-wide association studies (GWAS) for phenotypic prediction. However, recent work has shown that polygenic scores have limited portability across groups of different genetic ancestries, restricting the contexts in which they can be used reliably and potentially creating serious inequities in future clinical applications. Using the UK Biobank data, we demonstrate that even within a single ancestry group (i.e., when there are negligible differences in linkage disequilibrium or in causal alleles frequencies), the prediction accuracy of polygenic scores can depend on characteristics such as the socio-economic status, age or sex of the individuals in which the GWAS and the prediction were conducted, as well as on the GWAS design. Our findings highlight both the complexities of interpreting polygenic scores and underappreciated obstacles to their broad use.
- Molly Przeworski
- Jonathan K Pritchard
- Dalton Conley
- Arbel Harpak
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: This study has been conducted using the UK Biobank resource under application Number 11138, as approved by Columbia University Institutional Review Board, protocol AAAS2914.
- Ruth Loos, The Icahn School of Medicine at Mount Sinai, United States
- Received: May 10, 2019
- Accepted: January 28, 2020
- Accepted Manuscript published: January 30, 2020 (version 1)
© 2020, Mostafavi et al.
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