Mendelian Randomization: Concepts and Scope
Open accessAbstract
Mendelian randomization (MR) is a method of studying the causal effects of modifiable exposures (i.e., potential risk factors) on health, social, and economic outcomes using genetic variants associated with the specific exposures of interest. MR provides a more robust understanding of the influence of these exposures on outcomes because germline genetic variants are randomly inherited from parents to offspring and, as a result, should not be related to potential confounding factors that influence exposure-outcome associations. The genetic variant can therefore be used as a tool to link the proposed risk factor and outcome, and to estimate this effect with less confounding and bias than conventional epidemiological approaches. We describe the scope of MR, highlighting the range of applications being made possible as genetic data sets and resources become larger and more freely available. We outline the MR approach in detail, covering concepts, assumptions, and estimation methods. We cover some common misconceptions, provide strategies for overcoming violation of assumptions, and discuss future prospects for extending the clinical applicability, methodological innovations, robustness, and generalizability of MR findings.
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Causal effect estimates from MR can be evaluated within a triangulation of evidence framework, which involves interpreting findings alongside results from complementary approaches that rely on different assumptions.
“Causal effect estimates from MR can be evaluated within a triangulation of evidence framework, which involves interpreting findings alongside results from complementary approaches that rely on different assumptions.”
From Mendelian randomization (2022) · cites this paper as [8]
MR is especially appealing because it relies on different assumptions to conventional observational studies and therefore circumvents some of their common biases.
“MR is especially appealing because it relies on different assumptions to conventional observational studies and therefore circumvents some of their common biases.8”
From Mendelian randomization (2022) · cites this paper as [8]
Papers reporting two-sample MR have grown rapidly over recent years and now constitute a large majority of published studies.
“Papers reporting two-sample MR have grown rapidly over recent years and now constitute a large majority of published studies.8,81”
From Mendelian randomization (2022) · cites this paper as [8]
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References 199 · Cited by 841
Research works printed but not linked: 3
- Sanderson E, Spiller W, Bowden J. 2020. Testing and cor- recting for weak and pleiotropic instruments in two-sam- ple multivariable Mendelian randomisation. bioRxiv doi:10.1101/2020.04.02.021980 · DOI
- Tyrrell J, Richmond RC, Palmer TM, Feenstra B, Rangarajan J, Metrustry S, Cavadino A, Paternoster L, Armstrong LL, De Silva NMG, et al. 2016b. Genetic evidence for causal relationships between maternal obesity-related traits and birth weight. JAMA 315: 1129-1140. doi:10.1001/jama .2016.1975 · DOI · Paper page
- West-Eberhard MJ. 2003. Developmental plasticity and evo- lution. Oxford University Press, Oxford.
- Authors
- Richmond, R. C., & Davey Smith, G.
- Affiliations
- University of Bristol (GB)
- ORCID
- Richmond, Rebecca C.
- Venue
- Cold Spring Harbor Perspectives in Medicine
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2021-08-23
- Volume
- 12
- Issue
- 1
- Pages
- a040501
- ISSN
- 2157-1422 (ISSN-L)
- PMC
- PMC8725623
- OpenAlex
- W3195291379
- Cited by
- 841
- References
- 199
- Citations by year
- 2026: 151 · 2025: 283 · 2024: 250 · 2023: 113 · 2022: 34 · 2021: 8 · 2020: 2
- Type
- posted content
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cold Spring Harbor Perspectives in Medicine (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Explore Bristol Research (publishedVersion, cc-by)
- Bristol Research (University of Bristol) (publishedVersion, cc-by)
- Explore Bristol Research (submittedVersion, other-oa)
- Funders
- Medical Research Council (MC_UU_00011/5, MC_UU_00011/1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- Mendelian randomization, causal inference, genetic variants, confounding, risk factors, estimation methods, generalizability, clinical applicability
- MeSH terms
- Risk Factors, Causality, Mendelian Randomization Analysis
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