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Variable prediction accuracy of polygenic scores within an ancestry group

View ORCID ProfileHakhamanesh Mostafavi, View ORCID ProfileArbel Harpak, View ORCID ProfileDalton Conley, View ORCID ProfileJonathan K Pritchard, View ORCID ProfileMolly Przeworski
doi: https://doi.org/10.1101/629949
Hakhamanesh Mostafavi
1Department of Biological Sciences, Columbia University
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  • For correspondence: hsm2137@columbia.edu ah3586@columbia.edu mp3284@columbia.edu
Arbel Harpak
1Department of Biological Sciences, Columbia University
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  • For correspondence: hsm2137@columbia.edu ah3586@columbia.edu mp3284@columbia.edu
Dalton Conley
2Department of Sociology, Princeton University
3Office of Population Research, Princeton University
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Jonathan K Pritchard
4Departments of Genetics and Biology
5Howard Hughes Medical Institute, Stanford University
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Molly Przeworski
1Department of Biological Sciences, Columbia University
6Department of Systems Biology, Columbia University
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  • For correspondence: hsm2137@columbia.edu ah3586@columbia.edu mp3284@columbia.edu
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Abstract

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, the prediction accuracy of polygenic scores depends on characteristics such as the age or sex composition of the individuals in which the GWAS and the prediction were conducted, and on the GWAS study design. Our findings highlight both the complexities of interpreting polygenic scores and underappreciated obstacles to their broad use.

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Posted May 07, 2019.
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Variable prediction accuracy of polygenic scores within an ancestry group
Hakhamanesh Mostafavi, Arbel Harpak, Dalton Conley, Jonathan K Pritchard, Molly Przeworski
bioRxiv 629949; doi: https://doi.org/10.1101/629949
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Variable prediction accuracy of polygenic scores within an ancestry group
Hakhamanesh Mostafavi, Arbel Harpak, Dalton Conley, Jonathan K Pritchard, Molly Przeworski
bioRxiv 629949; doi: https://doi.org/10.1101/629949

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