Summary
This narrative review synthesises established best practices for Mendelian randomization, a genomic method for inferring causality in observational epidemiology. The authors emphasise that whilst MR exploits the non-susceptibility of genotypes to reverse causation and confounding, the approach carries important assumptions and limitations that, if unaddressed, can yield erroneous conclusions. The paper provides practical guidance on study design, analysis and interpretation, with particular attention to emerging two-sample approaches and their application to large consortial datasets.
UK applicability
The methodological guidance is applicable to UK-based epidemiological research and evidence synthesis, particularly where UK Biobank and NHS health records are integrated with genome-wide association study data. The review supports strengthening the evidence base for public health policy and intervention targeting in the UK context.
Key measures
Design principles, analytical strategies, and interpretation frameworks for Mendelian randomization studies; assessment of assumptions and potential sources of bias
Outcomes reported
The paper reviews best practices for designing, analysing and interpreting Mendelian randomization (MR) studies, with emphasis on key assumptions and limitations. It examines how MR can be used as a cost-effective strategy for causal inference and prioritising intervention targets for disease prevention.
Topic tags
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