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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-signif...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428571/ https://www.ncbi.nlm.nih.gov/pubmed/30895926 http://dx.doi.org/10.7554/eLife.39702 |
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author | Sohail, Mashaal Maier, Robert M Ganna, Andrea Bloemendal, Alex Martin, Alicia R Turchin, Michael C Chiang, Charleston WK Hirschhorn, Joel Daly, Mark J Patterson, Nick Neale, Benjamin Mathieson, Iain Reich, David Sunyaev, Shamil R |
author_facet | Sohail, Mashaal Maier, Robert M Ganna, Andrea Bloemendal, Alex Martin, Alicia R Turchin, Michael C Chiang, Charleston WK Hirschhorn, Joel Daly, Mark J Patterson, Nick Neale, Benjamin Mathieson, Iain Reich, David Sunyaev, Shamil R |
author_sort | Sohail, Mashaal |
collection | PubMed |
description | 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 (see decision letter). |
format | Online Article Text |
id | pubmed-6428571 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-64285712019-03-25 Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies Sohail, Mashaal Maier, Robert M Ganna, Andrea Bloemendal, Alex Martin, Alicia R Turchin, Michael C Chiang, Charleston WK Hirschhorn, Joel Daly, Mark J Patterson, Nick Neale, Benjamin Mathieson, Iain Reich, David Sunyaev, Shamil R eLife Evolutionary Biology 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 (see decision letter). eLife Sciences Publications, Ltd 2019-03-21 /pmc/articles/PMC6428571/ /pubmed/30895926 http://dx.doi.org/10.7554/eLife.39702 Text en © 2019, Sohail et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Evolutionary Biology Sohail, Mashaal Maier, Robert M Ganna, Andrea Bloemendal, Alex Martin, Alicia R Turchin, Michael C Chiang, Charleston WK Hirschhorn, Joel Daly, Mark J Patterson, Nick Neale, Benjamin Mathieson, Iain Reich, David Sunyaev, Shamil R Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies |
title | Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies |
title_full | Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies |
title_fullStr | Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies |
title_full_unstemmed | Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies |
title_short | Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies |
title_sort | polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies |
topic | Evolutionary Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428571/ https://www.ncbi.nlm.nih.gov/pubmed/30895926 http://dx.doi.org/10.7554/eLife.39702 |
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