Evidence map›Paper›PMID 30895926›Full record

ArticleeLife2019

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

Mashaal Sohail, Robert M Maier, Andrea Ganna, Alex Bloemendal, Alicia R Martin, Michael C Turchin, Charleston Wk Chiang, Joel Hirschhorn, Mark J Daly, Nick Patterson and 4 more

Abstract read
In one paragraph

Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 259 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
259citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

259 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Ancient DNA and Human Physiology.Physiology (Bethesda, Md.) · 2026
    Review
  4. Review
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  16. Estimating uncertainty in family-based GWAS.bioRxiv : the preprint server for biology · 2026
    Article
  17. Observational epidemiological studies can mitigate genetic confounding with a genetic relatedness matrix.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  18. Quantifying direct genetic signal captured by principal component adjustment.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  19. Review
  20. Review

199 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Mashaal Sohail *Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, United States.ORCID 0000-0002-6586-4403
Robert M Maier *Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States.ORCID 0000-0002-3044-090X
Andrea GannaProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States.
Alex BloemendalProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States.
Alicia R MartinProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States.
Michael C TurchinCenter for Computational Molecular Biology, Brown University, Providence, United States.ORCID 0000-0003-3569-1529
Charleston Wk ChiangDepartment of Preventive Medicine, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, United States.ORCID 0000-0002-0668-7865
Joel HirschhornProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States.
Mark J DalyProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States.
Nick PattersonProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States.
Benjamin Neale *Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States.
Iain Mathieson *Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States.
David Reich *Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, United States.
Shamil R Sunyaev *Department of Biomedical Informatics, Harvard Medical School, Boston, United States.ORCID 0000-0001-5715-5677

Funding

Cell Interactions in the Inflamed Intestinal MucosaR01DK075787 · NIDDK · BOSTON CHILDREN'S HOSPITAL · PI JOEL N HIRSCHHORN · 2007 to 2026
$13.1M
Statistical methods for studies of rare variantsR01MH101244 · NIMH · HARVARD MEDICAL SCHOOL · PI Benjamin Michael Neale, ALKES L PRICE · 2013 to 2026
$9.4M
The origin, the function and the phenotypic impact of human allelesR35GM127131 · NIGMS · HARVARD MEDICAL SCHOOL · PI SHAMIL SUNYAEV · 2018 to 2026
$8.1M
Methods for Genome-wide Association Studies in Admixed PopulationsR01HG006399 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L · 2011 to 2024
$6.3M
Powering whole genome sequence-based genetic discovery for common human diseases- Extended 2021-2022.U01HG009088 · NHGRI · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIN, XIHONG, NEALE, BENJAMIN MICHAEL · 2016 to 2021
$5.1M
Population mixture in evolutionary and medical geneticsR01GM100233 · NIGMS · HARVARD MEDICAL SCHOOL · PI PATTERSON, NICK J, REICH, DAVID E · 2012 to 2019
$2.7M
Alfred P. Sloan Foundation Sloan Research FellowshipCharles E Kaufman Foundation New Investigator Research GrantHoward Hughes Medical Institute InvestigatorNHGRI NIH HHS R01 HG006399NHGRI NIH HHS U01 HG009088NIDDK NIH HHS R01 DK075787NIGMS NIH HHS R01 GM100233NIGMS NIH HHS R35 GM127131NIH HHS GM100233NIH HHS GM127131NIH HHS HG006399NIH HHS HG009088NIH HHS MH101244NIMH NIH HHS R01 MH101244Paul Allen Foundation Allen Discovery Center
6 · The paper itself

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 (see decision letter).

Indexed as

Body HeightMultifactorial InheritanceAdaptation, BiologicalBiostatisticsComputational BiologyDatabases, FactualGenome-Wide Association StudyHumansPhylogenyPolymorphism, Single NucleotideUnited Kingdomevolutionary biologygeneticsgenomicsGWAShumanpolygenic adaptationpopulation stratificationselection for human height

Identifiers

PMID30895926
PMCPMC6428571

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.