Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies
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- Mashaal Sohail
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, United States
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- Robert M Maier
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States
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- Andrea Ganna
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States
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- Alex Bloemendal
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States
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- Alicia R Martin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States
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- Michael C Turchin
- Center for Computational Molecular Biology, Brown University, Providence, United States
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- Charleston WK Chiang
- Department of Preventive Medicine, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, United States
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- Joel Hirschhorn
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States
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- Mark J Daly
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States
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- Nick Patterson
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States
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- Benjamin Neale
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States
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- Iain Mathieson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States
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- David Reich
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States
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- Shamil R Sunyaev
- Department of Biomedical Informatics, Harvard Medical School, Boston, United States
抄録
<jats:p>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.</jats:p><jats:p>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>).</jats:p>
収録刊行物
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- eLife
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eLife 8 e39702-, 2019-03-21
eLife Sciences Publications, Ltd