Cited by 1,496Genetic Associations and EpidemiologyAdvanced Causal Inference TechniquesGenetics and Physical Performance

Evaluating the potential role of pleiotropy in Mendelian randomization studies

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Hemani, Gibran, Bowden, Jack, Davey Smith, George·2018·Human Molecular Genetics

Abstract

Pleiotropy, the phenomenon of a single genetic variant influencing multiple traits, is likely widespread in the human genome. If pleiotropy arises because the single nucleotide polymorphism (SNP) influences one trait, which in turn influences another ('vertical pleiotropy'), then Mendelian randomization (MR) can be used to estimate the causal influence between the traits. Of prime focus among the many limitations to MR is the unprovable assumption that apparent pleiotropic associations are mediated by the exposure (i.e. reflect vertical pleiotropy), and do not arise due to SNPs influencing the two traits through independent pathways ('horizontal pleiotropy'). The burgeoning treasure trove of genetic associations yielded through genome wide association studies makes for a tantalizing prospect of phenome-wide causal inference. Recent years have seen substantial attention devoted to the problem of horizontal pleiotropy, and in this review we outline how newly developed methods can be used together to improve the reliability of MR.

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  • Confounding of the genetic variants with the outcome in a sample can be induced by population stratification, dynastic effects and assortative mating, violating the second IV condition.

    “However, confounding of the genetic variants with the outcome in a sample can be induced by population stratification, dynastic effects and assortative mating,60 violating the second IV condition.”

    From Mendelian randomization (2022) · cites this paper as [60]

  • If there are many correlated candidate variants in a gene region, then including all variants in a single analysis will typically result in numerical instability, as the analysis can be highly sensitive to small changes in the variant correlation matrix.

    “If there are many correlated candidate variants in a gene region, then including all variants in a single analysis will typically result in numerical instability, as the analysis can be highly sensitive to small changes in the variant correlation matrix 62 .”

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Research works printed but not linked: 2

  1. [72]Hemani G., Bowden J., Haycock P.C., Zheng J., Davis O., Flach P., Gaunt T.R., Davey Smith G. (2017) Automating Mendelian randomization through machine learning to construct a putative causal map of the human phenome. bioRxiv.
  2. [100]Spiller W., Davies N.M., Palmer T.M. (2017) Software application profile: mrrobust – a tool for performing two-sample summary Mendelian randomization analyses. bioRxiv 142125. doi:10.1101/142125 · DOI

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Authors
Hemani, G., Bowden, J., & Davey Smith, G.
Affiliations
  • University of Bristol (GB)
  • MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol
Corresponding author
Hemani, Gibran
Venue
Human Molecular Genetics
Published
2018-05-16
Volume
27
Issue
R2
Pages
R195-R208
ISSN
  • 0964-6906 (ISSN-L)
  • 1460-2083
OpenAlex
W2810852503
Cited by
1,496
References
113
Citations by year
2026: 129 · 2025: 266 · 2024: 422 · 2023: 209 · 2022: 169 · 2021: 131 · 2020: 101 · 2019: 62 · 2018: 7
FWCI
10.71
Type
journal article
Language
en
Open access
Locations
  • Human Molecular Genetics (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Bristol Research (University of Bristol) (submittedVersion, cc-by)
Funders
  • Wellcome Trust (208806/Z/17/Z)
  • Medical Research Council (MC_UU_12013/1)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
Keywords
pleiotropy, Mendelian randomization, horizontal pleiotropy, single nucleotide polymorphisms, causal inference, phenome-wide association study, genetic variants
MeSH terms
Animals, Humans, Phenotype, Genetic Variation, Reproducibility of Results, Genome, Human, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Mendelian Randomization Analysis, Genetic Pleiotropy

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