Signals of polygenic adaptation on height have been overestimated due to uncorrected population structure in genome-wide association studies

Abstract

Genetic predictions of height differ significantly among human populations and these differences are too large to be explained by random genetic drift. This observation has been interpreted as evidence of polygenic adaptation, natural selection acting on many positions in the genome simultaneously. Selected differences across populations were detected using single nucleotide polymorphisms (SNPs) that were genome-wide significantly associated with height, and many studies also found that the signals grew stronger when large numbers of sub-significant SNPs were analyzed. This has led to excitement about the prospect of analyzing large fractions of the genome to detect subtle signals of selection for diverse traits, the introduction of methods to do this, and claims of polygenic adaptation for multiple traits. All of the claims of polygenic adaptation for height to date have been based on SNP ascertainment or effect size measurement in the GIANT Consortium meta-analysis of studies in people of European ancestry. Here we repeat the height analyses in the UK Biobank, a much more homogeneously designed study. While we replicate most previous findings when restricting to genome-wide significant SNPs, when we extend the analyses to large fractions of SNPs in the genome, the differences across groups attenuate and some change ordering. Our results show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population structure, a more severe problem in GIANT and possibly other meta-analyses than in the more homogeneous UK Biobank. Therefore, claims of polygenic adaptation for height and other traits, particularly those that rely on SNPs below genome-wide significance, should be viewed with caution.