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PreprintCited by 79Genetic Associations and EpidemiologyGenetic and phenotypic traits in livestockGenetic Mapping and Diversity in Plants and Animals

Interpreting population and family-based genome-wide association studies in the presence of confounding

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Veller, Carl, Coop, Graham·2023·PLoS Biology
DOI 10.1101/2023.02.26.530052PMC PMC10002712

Preprint — published as 10.1371/journal.pbio.3002511

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Abstract

A central aim of genome-wide association studies (GWASs) is to estimate direct genetic effects: the causal effects on an individual’s phenotype of the alleles that they carry. However, estimates of direct effects can be subject to genetic and environmental confounding, and can also absorb the ‘indirect’ genetic effects of relatives’ genotypes. Recently, an important development in controlling for these confounds has been the use of within-family GWASs, which, because of the randomness of Mendelian segregation within pedigrees, are often interpreted as producing unbiased estimates of direct effects. Here, we present a general theoretical analysis of the influence of confounding in standard population-based and within-family GWASs. We show that, contrary to common interpretation, family-based estimates of direct effects can be biased by genetic confounding. In humans, such biases will often be small per-locus, but can be compounded when effect size estimates are used in polygenic scores. We illustrate the influence of genetic confounding on population- and family-based estimates of direct effects using models of assortative mating, population stratification, and stabilizing selection on GWAS traits. We further show how family-based estimates of indirect genetic effects, based on comparisons of parentally transmitted and untransmitted alleles, can suffer substantial genetic confounding. In addition to known biases that can arise in family-based GWASs when interactions between family members are ignored, we show that biases can also arise from gene-by-environment (G×E) interactions when parental genotypes are not distributed identically across interacting environmental and genetic backgrounds. We conclude that, while family-based studies have placed GWAS estimation on a more rigorous footing, they carry subtle issues of interpretation that arise from confounding and interactions.

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  • FGWAS has been proposed as a solution to confounding in GWAS that also enables deeper investigation of gene-environment correlation and non-random mating.

    “Family-based GWAS (FGWAS) has been proposed as a solution to the problem of confounding in GWAS3,9,14–16 that also enables deeper investigation of the impact of gene-environment correlation — including from IGEs — and non-random mating, including population structure and assortative mating.”

    From Family-GWAS reveals effects of environment and mating on genetic associations (2024) · cites this paper as [16]

    The Introduction and Discussion say family-based GWASs were adopted to reduce confounding and examine how population structure, assortative mating, and indirect genetic effects affect estimates. But the Discussion cautions that family-based estimates retain some confounding and that estimates of indirect genetic effects can absorb confounds, so the paper does not support presenting FGWAS as an unqualified solution that can disentangle those effects. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • Because segregation of chromosomes during meiosis is independent of environment, estimates of DGEs are free from confounding due to gene-environment correlation, including from IGEs and population-stratification.

    “Because the segregation of chromosomes during meiosis is independent of environment, estimates of DGEs are free from confounding due to gene-environment correlation, including from IGEs and population-stratification3,9,15,16.”

    From Family-GWAS reveals effects of environment and mating on genetic associations (2024) · cites this paper as [16]

    The Discussion says within-family estimates avoid environmental confounding across families in the absence of G×E interactions because transmission is effectively randomized with respect to family environment. But it says these estimates can retain residual genetic confounding and sibling indirect effects; the “Sibling indirect effects” section explicitly shows that such effects can bias estimates of direct genetic effects. The unqualified claim that the estimates are free from confounding, including indirect genetic effects, overstates the source. (LLM, conf=0.90)

    Experimental — accuracy not yet measured

  • In FPGI analysis, adding parental PGIs as covariates enables estimation of the direct effect of the PGI, which reflects only direct genetic effects.

    “In the FPGI analysis, we add parental PGIs as covariates, enabling estimation of the ‘direct effect’ of the PGI, which reflects only DGEs15,16.”

    From Family-GWAS reveals effects of environment and mating on genetic associations (2024) · cites this paper as [16]

    The “Polygenic scores and their phenotypic associations” section (page unavailable) describes parent-offspring PGS regressions and says within-family PGS slopes are often interpreted as capturing direct genetic effects. But the Discussion’s “Direct genetic effects” section warns that population-GWAS-derived PGS weights can absorb confounding. The paper does not establish that adding parental PGIs as covariates yields an estimate reflecting only direct genetic effects. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • Cross-trait assortative mating is expected to have a negligible influence on genetic correlations estimated using direct genetic effects because the vast majority of correlations between causal alleles induced by cross-trait assortative mating are cross-chromosome and therefore do not contribute to direct genetic effect estimates.

    “xAM is expected to have a negligible influence on genetic correlations estimated using DGEs because the vast majority of correlations between causal alleles induced by xAM are cross-chromosome and therefore do not contribute to DGE estimates14–16.”

    From Family-GWAS reveals effects of environment and mating on genetic associations (2024) · cites this paper as [16]

    Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • FGWAS uses the natural experiment of random assignment of genotype within families to separate out the contribution of direct genetic effects (DGEs) from other factors contributing to genetic associations.

    “Family-based GWAS (FGWAS) uses the natural experiment of random assignment of genotype within families to separate out the contribution of direct genetic effects (DGEs) — causal effects of alleles in an individual on an individual — from other factors contributing to genetic associations.”

    From Family-GWAS reveals effects of environment and mating on genetic associations (2024) · cites this paper as [16]

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Authors
Veller, C., & Coop, G.
Affiliations
  • University of Chicago (US)
  • University of California, Davis (US)
Corresponding author
Veller, Carl
ORCID
Venue
PLoS Biology
Publisher
openRxiv
Published
2023-02-27
Volume
22
Issue
4
Pages
e3002511-e3002511
ISSN
1544-9173 (ISSN-L)
DOI
10.1101/2023.02.26.530052
PMC
PMC10002712
OpenAlex
W4394713667
Cited by
79
References
108
Citations by year
2026: 25 · 2025: 31 · 2024: 17 · 2023: 5 · 2022: 1
FWCI
19.31
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • PLoS Biology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
  • PubMed Central (submittedVersion, cc-by)
  • Knowledge@UChicago (University of Chicago) (submittedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • University of Chicago (cc-by)
Funders
  • Branco Weiss Fellowship – Society in Science
  • National Institutes of Health
  • National Institute of General Medical Sciences (R35GM136290)
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 › Genetic Mapping and Diversity in Plants and Animals
Keywords
genetic confounding, direct genetic effects, indirect genetic effects, family-based association study, polygenic risk score, assortative mating, population stratification, stabilizing selection, Mendelian segregation, effect size bias

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