Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies.

Genetic predictions of height differ among human populations and these differences have been interpreted as evidence of polygenic adaptation. These differences were first detected using SNPs genome-wide significantly associated with height, and shown to grow stronger when large numbers of sub-significant SNPs were included, leading to excitement about the prospect of analyzing large fractions of the genome to detect polygenic adaptation for multiple traits. Previous studies of height have been based on SNP effect size measurements in the GIANT Consortium meta-analysis. Here we repeat the analyses in the UK Biobank, a much more homogeneously designed study. We show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population stratification. More generally, our results imply that typical constructions of polygenic scores are sensitive to population stratification and that population-level differences should be interpreted with caution.
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Competing Interests: MS, RM, AG, AB, AM, MT, CC, JH, MD, NP, IM, DR, SS No competing interests declared, BN Ben Neale is a member and on the scientific advisory board of Deep Genomics, a consultant for Camp4 Therapeutics Corporation, a consultant for Merck & Co., a consultant for Takeda Phamaceutical, and a consultant for Avanir Pharmaceuticals. None of these entities played a role in determining the content of this paper.
(© 2019, Sohail et al.)