Mendelian randomisation for mediation analysis: current methods and challenges for implementation
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Abstract
Mediation analysis seeks to explain the pathway(s) through which an exposure affects an outcome. Traditional, non-instrumental variable methods for mediation analysis experience a number of methodological difficulties, including bias due to confounding between an exposure, mediator and outcome and measurement error. Mendelian randomisation (MR) can be used to improve causal inference for mediation analysis. We describe two approaches that can be used for estimating mediation analysis with MR: multivariable MR (MVMR) and two-step MR. We outline the approaches and provide code to demonstrate how they can be used in mediation analysis. We review issues that can affect analyses, including confounding, measurement error, weak instrument bias, interactions between exposures and mediators and analysis of multiple mediators. Description of the methods is supplemented by simulated and real data examples. Although MR relies on large sample sizes and strong assumptions, such as having strong instruments and no horizontally pleiotropic pathways, our simulations demonstrate that these methods are unaffected by confounders of the exposure or mediator and the outcome and non-differential measurement error of the exposure or mediator. Both MVMR and two-step MR can be implemented in both individual-level MR and summary data MR. MR mediation methods require different assumptions to be made, compared with non-instrumental variable mediation methods. Where these assumptions are more plausible, MR can be used to improve causal inference in mediation analysis.
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If all instrumental variable conditions are satisfied, the multivariable Mendelian randomization estimate will differ from a univariable Mendelian randomization estimate where all or part of the effect of the exposure on the outcome acts through a mediating phenotype included in the multivariable Mendelian randomization estimation.
“If all of the IV conditions are satisfied, this estimate will differ from a univariable MR estimate where all or part of the effect of the exposure on the outcome acts through a mediating phenotype included in the multivariable MR estimation.104”
From Mendelian randomization (2022) · cites this paper as [104]
Mendelian randomization can be used to estimate the proportion of the effect of an exposure on an outcome that is mediated by an intermediate phenotype.
“MR can be used to estimate the proportion of the effect of an exposure on an outcome that is mediated by an intermediate phenotype.104,105”
From Mendelian randomization (2022) · cites this paper as [104]
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- Authors
- Carter, A. R., Sanderson, E., Hammerton, G., Richmond, R. C., Davey Smith, G., Heron, J., Taylor, A. E., Davies, N. M., & Howe, L. D.
- Affiliations
- University of Bristol (GB)
- University Hospitals Bristol NHS Foundation Trust (GB)
- Norwegian University of Science and Technology (NO)
- Corresponding author
- Carter, Alice R.
- ORCID
- Venue
- European Journal of Epidemiology
- Published
- 2021-05
- Volume
- 36
- Issue
- 5
- Pages
- 465-478
- ISSN
- 0393-2990 (ISSN-L)
- 1573-7284
- PMC
- PMC8159796
- OpenAlex
- W3159102563
- Cited by
- 1,215
- References
- 67
- Citations by year
- 2026: 196 · 2025: 407 · 2024: 386 · 2023: 143 · 2022: 54 · 2021: 18 · 2020: 7 · 2019: 1 · 2018: 1 · 2014: 1
- FWCI
- 117.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- European Journal of Epidemiology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Bristol Research (University of Bristol) (submittedVersion, cc-by)
- Funders
- UK Medical Research Council (MC_UU_00011/1, MR/M020894)
- UK Economic and Social Research Council (ES/N000757/1)
- Wellcome Trust (209138/Z/17/Z)
- Norwegian Research Council (295989)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- Mendelian randomization, mediation analysis, causal inference, confounding, measurement error, weak instrument bias, pleiotropy, multiple mediators
- MeSH terms
- Mediation Analysis, Humans, Genetic Variation, Bias, Causality, Genome-Wide Association Study, Mendelian Randomization Analysis, Genetic Pleiotropy
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