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Allele frequency differentiation at height-associated SNPs among continental human populations

European Journal of Human Genetics volume 29, pages 1542–1548 (2021)Cite this article

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Abstract

Methods to detect polygenic adaptation have recently been shown to be sensitive to uncorrected stratification in GWAS, thereby casting doubts on whether polygenic adaptation is prevalent among humans. Consistent with a signal of adaptation at human height loci, the mean FST among African, East Asian, and European populations was shown to be significantly higher at height-associated SNPs than that at non-associated SNPs. This conclusion was reached, however, using height-associated SNPs ascertained from a GWAS design impacted by residual confounding due to uncorrected stratification. Specifically, we show here that the estimated effect sizes are significantly correlated with population structure across continents, potentially explaining the elevated differentiation previously reported. We alleviated these concerns of confounding by ascertaining height-associated SNPs from two biobank GWAS (UK Biobank, UKB, and Biobank Japan, BBJ), where measures to control for confounding in GWAS are more effective. Consistent with a global signature of polygenic adaptation, we found that compared to non-associated SNPs, frequencies of height-associated SNPs are indeed significantly more differentiated among continental populations from both the 1000 Genomes Project (p = 0.0012 for UKB and p = 0.0265 for BBJ), and the Human Genome Diversity Project (p = 0.0225 for UKB and p = 0.0032 for BBJ). However, we found no significant difference among continental populations in polygenic height scores. Through simulations, we found that polygenic score-based statistics could lose power in detecting polygenic adaptation in presence of independent converging selections, thereby potentially explaining the inconsistent results based on FST and polygenic scores.

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Fig. 1: Evidence of stratification in GWAS summary statistics.
Fig. 2: Mean FST values of the height-associated SNPs across the three continental populations from 1000 Genomes.
Fig. 3: QX tests on PSs for the three continental populations from 1000 Genomes.
Fig. 4: Forward simulation of power of QX and FST under different scenarios.

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Acknowledgements

We gratefully thank Jing Guo and Jian Yang for providing the script for PS analysis. This work is supported by start-up funds provided by the Center for Genetic Epidemiology at the Keck School of Medicine of the University of Southern California (USC) (to CWKC). Computation for this work is supported by USC’s Center for Advanced Research Computing (https://carc.usc.edu).

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Authors and Affiliations

  1. Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

    Minhui Chen & Charleston W. K. Chiang

  2. Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA

    Charleston W. K. Chiang

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  1. Minhui Chen
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  2. Charleston W. K. Chiang
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Correspondence to Minhui Chen or Charleston W. K. Chiang.

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Chen, M., Chiang, C.W.K. Allele frequency differentiation at height-associated SNPs among continental human populations. Eur J Hum Genet 29, 1542–1548 (2021). https://doi.org/10.1038/s41431-021-00938-2

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