Key result
Mendelian randomization requires robust methods to address pleiotropy when estimating causal effects from genetic variants.
Why the study?
It is crucial to acknowledge instrumental variable assumptions in Mendelian randomization analysis when estimating causal effects of exposures on outcomes.
This methodological review provides a comprehensive overview of Mendelian randomization techniques, emphasizing the importance of verifying instrumental variable assumptions and utilizing robust methods when assumptions are violated.
Mendelian randomization (MR) is a statistical method that uses genetic variants as instrumental variables to estimate the causal effect of exposure on an outcome in the presence of unmeasured confounding. In this review, we argue that it is crucial to acknowledge the instrumental variable assumptions in MR analysis. We describe widely used MR methods, using an example from obesity-related metabolic disorders. We describe situations in which instrumental variable assumptions are violated and explain how to evaluate these violations and employ robust methods for accommodating such violations.
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Lee et al. (2025) conducted a review in Obesity-Related Diseases. Mendelian Randomization was evaluated. Mendelian randomization uses genetic variants as instrumental variables to estimate causal effects, requiring careful evaluation of assumptions and robust methods to address violations like pleiotropy.
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