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Simultaneous estimation of bi-directional causal effects and heritable confounding from GWAS summary statistics

Author

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  • Liza Darrous

    (University Center for Primary Care and Public Health, University of Lausanne
    Swiss Institute of Bioinformatics)

  • Ninon Mounier

    (University Center for Primary Care and Public Health, University of Lausanne
    Swiss Institute of Bioinformatics)

  • Zoltán Kutalik

    (University Center for Primary Care and Public Health, University of Lausanne
    Swiss Institute of Bioinformatics
    University of Lausanne)

Abstract

Mendelian Randomisation (MR) is an increasingly popular approach that estimates the causal effect of risk factors on complex human traits. While it has seen several extensions that relax its basic assumptions, most suffer from two major limitations; their under-exploitation of genome-wide markers, and sensitivity to the presence of a heritable confounder of the exposure-outcome relationship. To overcome these limitations, we propose a Latent Heritable Confounder MR (LHC-MR) method applicable to association summary statistics, which estimates bi-directional causal effects, direct heritabilities, and confounder effects while accounting for sample overlap. We demonstrate that LHC-MR outperforms several existing MR methods in a wide range of simulation settings and apply it to summary statistics of 13 complex traits. Besides several concordant results with other MR methods, LHC-MR unravels new mechanisms (how disease diagnosis might lead to improved lifestyle) and reveals new causal effects (e.g. HDL cholesterol being protective against high systolic blood pressure), hidden from standard MR methods due to a heritable confounder of opposite effect direction.

Suggested Citation

  • Liza Darrous & Ninon Mounier & Zoltán Kutalik, 2021. "Simultaneous estimation of bi-directional causal effects and heritable confounding from GWAS summary statistics," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26970-w
    DOI: 10.1038/s41467-021-26970-w
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    References listed on IDEAS

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    Cited by:

    1. Liza Darrous & Gibran Hemani & George Davey Smith & Zoltán Kutalik, 2024. "PheWAS-based clustering of Mendelian Randomisation instruments reveals distinct mechanism-specific causal effects between obesity and educational attainment," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Jennifer Sjaarda & Zoltán Kutalik, 2023. "Partner choice, confounding and trait convergence all contribute to phenotypic partner similarity," Nature Human Behaviour, Nature, vol. 7(5), pages 776-789, May.

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