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

Author:

Sohail Mashaal123ORCID,Maier Robert M345ORCID,Ganna Andrea34567,Bloemendal Alex345,Martin Alicia R345,Turchin Michael C89ORCID,Chiang Charleston WK10ORCID,Hirschhorn Joel31112,Daly Mark J3457,Patterson Nick313,Neale Benjamin345,Mathieson Iain14,Reich David31315,Sunyaev Shamil R231ORCID

Affiliation:

1. Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, United States

2. Department of Biomedical Informatics, Harvard Medical School, Boston, United States

3. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States

4. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States

5. Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, United States

6. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

7. Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland

8. Center for Computational Molecular Biology, Brown University, Providence, United States

9. Department of Ecology and Evolutionary Biology, Brown University, Providence, United States

10. Department of Preventive Medicine, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, United States

11. Departments of Pediatrics and Genetics, Harvard Medical School, Boston, United States

12. Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Boston, United States

13. Department of Genetics, Harvard Medical School, Boston, United States

14. Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States

15. Howard Hughes Medical Institute, Harvard Medical School, Boston, United States

Abstract

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.Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (<xref ref-type="decision-letter" rid="SA1">see decision letter</xref>).

Funder

National Institutes of Health

Alfred P. Sloan Foundation

Charles E Kaufman Foundation

Paul Allen Foundation

Howard Hughes Medical Institute

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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