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Cited by 122Genetic Associations and EpidemiologyForensic and Genetic ResearchGenetic diversity and population structure

Demographic history mediates the effect of stratification on polygenic scores

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Zaidi, Arslan A, Mathieson, Iain·2020·eLife
DOI 10.7554/elife.61548PMC PMC7758063

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Abstract

Population stratification continues to bias the results of genome-wide association studies (GWAS). When these results are used to construct polygenic scores, even subtle biases can cumulatively lead to large errors. To study the effect of residual stratification, we simulated GWAS under realistic models of demographic history. We show that when population structure is recent, it cannot be corrected using principal components of common variants because they are uninformative about recent history. Consequently, polygenic scores are biased in that they recapitulate environmental structure. Principal components calculated from rare variants or identity-by-descent segments can correct this stratification for some types of environmental effects. While family-based studies are immune to stratification, the hybrid approach of ascertaining variants in GWAS but reestimating effect sizes in siblings reduces but does not eliminate stratification. We show that the effect of population stratification depends not only on allele frequencies and environmental structure but also on demographic history.

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  • Analytical techniques including PCA and linear mixed models reduce population stratification confounding but often leave residual confounding in GWAS results.

    “Analytical techniques including principal component analysis (PCA) and linear mixed models have been developed to reduce population stratification confounding12, but these techniques often leave residual confounding in GWAS results5,8,10.”

    From Family-GWAS reveals effects of environment and mating on genetic associations (2024) · cites this paper as [10]

  • Genetic associations (including those from GWAS) can be affected by gene-environment correlations and non-random mating, such as indirect genetic effects, assortative mating, and population stratification, leading to biased inferences.

    “However, genetic associations can be affected by gene-environment correlations and non-random mating, which can lead to biased inferences in downstream analyses.”

    From Family-GWAS reveals effects of environment and mating on genetic associations (2024) · cites this paper as [10]

  • The residual confounding may be because principal components derived from common variants do not effectively capture recent structure in the population.

    “This may be because the principal components derived from common variants do not effectively capture recent structure in the population10.”

    From Family-GWAS reveals effects of environment and mating on genetic associations (2024) · cites this paper as [10]

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Cited by

Sorted by citations

Authors
Zaidi, A. A., & Mathieson, I.
Affiliations
University of Pennsylvania (US)
Corresponding author
  • Zaidi, Arslan A
  • Mathieson, Iain
ORCID
Venue
eLife
Publisher
eLife Sciences Publications, Ltd
Published
2020-11-17
Volume
9
ISSN
2050-084X (ISSN-L)
DOI
10.7554/elife.61548
PMC
PMC7758063
OpenAlex
W3098933058
Cited by
122
References
10
Citations by year
2026: 16 · 2025: 23 · 2024: 24 · 2023: 14 · 2022: 26 · 2021: 13 · 2020: 6
FWCI
8.78
Type
journal article
Language
en
Open access
Licence
Locations
  • eLife (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Institute of General Medical Sciences (R35GM133708)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
Keywords
population stratification, polygenic risk score, demographic history, genome-wide association study, rare variants, identity by descent, family-based association, environmental structure, allele frequency
MeSH terms
Demography, Humans, Bias, Multifactorial Inheritance, Genome-Wide Association Study

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