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Understanding the assumptions underlying Mendelian randomization

European Journal of Human Genetics volume 30, pages 653–660 (2022)Cite this article

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Abstract

With the rapidly increasing availability of large genetic data sets in recent years, Mendelian Randomization (MR) has quickly gained popularity as a novel secondary analysis method. Leveraging genetic variants as instrumental variables, MR can be used to estimate the causal effects of one phenotype on another even when experimental research is not feasible, and therefore has the potential to be highly informative. It is dependent on strong assumptions however, often producing biased results if these are not met. It is therefore imperative that these assumptions are well-understood by researchers aiming to use MR, in order to evaluate their validity in the context of their analyses and data. The aim of this perspective is therefore to further elucidate these assumptions and the role they play in MR, as well as how different kinds of data can be used to further support them.

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Fig. 1: Graphical representation of valid instrument causal scenarios, for a variant j.
Fig. 2: Graphical representation of several violations of instrumental variable assumptions, for a variant j.
Fig. 3: Graphical representation of scenarios involving longitudinal data and imperfect measurement of variables, for a variant j.

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Acknowledgements

This work was funded by The Netherlands Organization for Scientific Research (NWO VICI 453-14-005 (DP), 645-000-003 (DP), CHiLL 617-001-451 (IGB)) and by F. Hoffman-La Roche AG (CdL).

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Authors and Affiliations

  1. Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, The Netherlands

    Christiaan de Leeuw, Jeanne Savage & Danielle Posthuma

  2. Department of Data Science, Institute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands

    Ioan Gabriel Bucur & Tom Heskes

  3. Department of Clinical Genetics, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands

    Danielle Posthuma

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  1. Christiaan de Leeuw
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  2. Jeanne Savage
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  3. Ioan Gabriel Bucur
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  5. Danielle Posthuma
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CdL wrote and revised the paper. The other authors contributed to revision and editing.

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Correspondence to Christiaan de Leeuw.

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de Leeuw, C., Savage, J., Bucur, I.G. et al. Understanding the assumptions underlying Mendelian randomization. Eur J Hum Genet 30, 653–660 (2022). https://doi.org/10.1038/s41431-022-01038-5

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