Sensitivity Analyses for Robust Causal Inference from Mendelian Randomization Analyses with Multiple Genetic Variants.

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Bowden, J 
Fall, T 
Ingelsson, E 
Thompson, SG 

Mendelian randomization investigations are becoming more powerful and simpler to perform, due to the increasing size and coverage of genome-wide association studies and the increasing availability of summarized data on genetic associations with risk factors and disease outcomes. However, when using multiple genetic variants from different gene regions in a Mendelian randomization analysis, it is highly implausible that all the genetic variants satisfy the instrumental variable assumptions. This means that a simple instrumental variable analysis alone should not be relied on to give a causal conclusion. In this article, we discuss a range of sensitivity analyses that will either support or question the validity of causal inference from a Mendelian randomization analysis with multiple genetic variants. We focus on sensitivity analyses of greatest practical relevance for ensuring robust causal inferences, and those that can be undertaken using summarized data. Aside from cases in which the justification of the instrumental variable assumptions is supported by strong biological understanding, a Mendelian randomization analysis in which no assessment of the robustness of the findings to violations of the instrumental variable assumptions has been made should be viewed as speculative and incomplete. In particular, Mendelian randomization investigations with large numbers of genetic variants without such sensitivity analyses should be treated with skepticism.

C-Reactive Protein, Causality, Coronary Artery Disease, Genetic Variation, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Odds Ratio, Reproducibility of Results
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Wolters Kluwer
Medical Research Council (MR/L003120/1)
Medical Research Council (G0800270)
British Heart Foundation (CH/12/2/29428)
Wellcome Trust (100114/Z/12/Z)
British Heart Foundation (None)
British Heart Foundation (None)
Medical Research Council (MC_UU_00002/7)
Stephen Burgess is funded by a fellowship from the Wellcome Trust (100114). Jack Bowden is supported by a Methodology Research Fellowship from the UK Medical Research Council (grant number MR/N501906/1). Simon G. Thompson is supported by the British Heart Foundation (grant number CH/12/2/29428).