Theoretical and empirical quantification of the accuracy of polygenic scores in ancestry divergent populations

Ying Wang, Jing Guo, Guiyan Ni, Jian Yang, Peter M. Visscher and Loic Yengo ()
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Ying Wang: The University of Queensland
Jing Guo: The University of Queensland
Guiyan Ni: The University of Queensland
Jian Yang: The University of Queensland
Peter M. Visscher: The University of Queensland
Loic Yengo: The University of Queensland

Nature Communications, 2020, vol. 11, issue 1, 1-9

Abstract: Abstract Polygenic scores (PGS) have been widely used to predict disease risk using variants identified from genome-wide association studies (GWAS). To date, most GWAS have been conducted in populations of European ancestry, which limits the use of GWAS-derived PGS in non-European ancestry populations. Here, we derive a theoretical model of the relative accuracy (RA) of PGS across ancestries. We show through extensive simulations that the RA of PGS based on genome-wide significant SNPs can be predicted accurately from modelling linkage disequilibrium (LD), minor allele frequencies (MAF), cross-population correlations of causal SNP effects and heritability. We find that LD and MAF differences between ancestries can explain between 70 and 80% of the loss of RA of European-based PGS in African ancestry for traits like body mass index and type 2 diabetes. Our results suggest that causal variants underlying common genetic variation identified in European ancestry GWAS are mostly shared across continents.

Date: 2020
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DOI: 10.1038/s41467-020-17719-y

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