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Reduced signal for polygenic adaptation of height in UK Biobank

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Berg, Jeremy J, Harpak, Arbel, Sinnott-Armstrong, Nasa, Joergensen, Anja Moltke, Mostafavi, Hakhamanesh, Field, Yair, Boyle, Evan August, Zhang, Xinjun +3 more·2019·eLife
DOI 10.7554/elife.39725PMC PMC6428572

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Abstract

Several recent papers have reported strong signals of selection on European polygenic height scores. These analyses used height effect estimates from the GIANT consortium and replication studies. Here, we describe a new analysis based on the the UK Biobank (UKB), a large, independent dataset. We find that the signals of selection using UKB effect estimates are strongly attenuated or absent. We also provide evidence that previous analyses were confounded by population stratification. Therefore, the conclusion of strong polygenic adaptation now lacks support. Moreover, these discrepancies highlight (1) that methods for correcting for population stratification in GWAS may not always be sufficient for polygenic trait analyses, and (2) that claims of differences in polygenic scores between populations should be treated with caution until these issues are better understood. 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).

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  • Previous evidence for adaptation on height using siblings in UK Biobank was suggestive of some adaptation, but statistically inconclusive.

    “Previous evidence for adaptation on height using siblings in UK Biobank was suggestive of some adaptation, but statistically inconclusive26.”

    From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [26]

    The Results (GWAS datasets; no page supplied) identify a UK Biobank sibling-pair analysis, and the Discussion says UK Biobank selection signals were absent or greatly attenuated, with weak significance in some analyses. Those passages support a cautious reading of the evidence, but they do not specifically say that the sibling-based result was suggestive yet statistically inconclusive. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

  • Within-sibship GWAS data are robust against population stratification.

    “Within-sibship GWAS data are particularly useful in this context as they are robust against population stratification26,27,29.”

    From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [26]

  • Given previous concerns, we performed several sensitivity analyses for the height analysis.

    “Given previous concerns26,27, we performed several sensitivity analyses for the height analysis detailed in the Supplementary Methods.”

    From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [26]

  • A previous study reporting polygenic adaptation on height in the UK population was found to be biased by population stratification in the GIANT consortium.

    “A previous study reporting polygenic adaptation on height in the UK population was found to be biased by population stratification in the Genetic Investigation of ANthropometric Traits (GIANT) consortium26–28.”

    From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [26]

  • Population stratification in GWAS data likely confounded previous estimates of polygenic adaptation on height.

    “However, this approach is sensitive to population stratification as illustrated by recent work using UK Biobank data which showed that population stratification in GWAS data likely confounded previous estimates of polygenic adaptation on height26,27.”

    From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [26]

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Authors
Berg, J. J., Harpak, A., Sinnott-Armstrong, N., Joergensen, A. M., Mostafavi, H., Field, Y., Boyle, E. A., Zhang, X., Racimo, F., Pritchard, J. K., & Coop, G.
Affiliations
  • Columbia University (US)
  • Stanford University (US)
  • Lundbeck GeoGenetics Centre, Department of Biology, University of Copenhagen, Copenhagen, Denmark
  • University of California, Davis (US)
  • University of Copenhagen (DK)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Berg, Jeremy J
  • Pritchard, Jonathan K
  • Coop, Graham
ORCID
Venue
eLife
Publisher
eLife Sciences Publications, Ltd
Published
2019-03-21
Volume
8
ISSN
2050-084X (ISSN-L)
DOI
10.7554/elife.39725
PMC
PMC6428572
OpenAlex
W2952596949
Cited by
339
References
8
Citations by year
2026: 25 · 2025: 26 · 2024: 32 · 2023: 26 · 2022: 51 · 2021: 60 · 2020: 59 · 2019: 51 · 2018: 7 · 2017: 2
FWCI
33.15
Type
journal article
Language
en
Open access
Licence
Locations
  • eLife (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Institutes of Health (R01 GM115889, F32 GM126787, R01 GM121372, R01 HG008140, R01 GM108779)
  • Stanford Center for Computational, Evolutionary and Human Genomics (Fellowship)
  • U.S. Department of Defense (National Defense Science and Engineering Gran, National Defense Science and Engineering Grant)
  • Stanford University (Graduate Fellowship)
  • Villum Fonden (Young Investigator award)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
Keywords
polygenic adaptation, height, polygenic risk score, selection signals, population stratification, UK Biobank, effect estimates
MeSH terms
Adaptation, Biological, Body Height, Europe, Humans, Selection, Genetic, Databases, Factual, Multifactorial Inheritance, Biostatistics

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