Appraising the causal role of risk factors in coronary artery disease and stroke: A systematic review of Mendelian Randomization studies

BACKGROUND: Mendelian randomization (MR) offers a powerful approach to study potential causal associations between exposures and health outcomes, by using genetic variants associated with an exposure as instrumental variables. In this systematic review, we aimed to summarize previous MR studies and to evaluate the evidence for causality for a broad range of exposures in relation to coronary artery disease (CAD) and stroke. METHODS: MR studies investigating the association of any genetically predicted exposure with CAD or stroke were identified in Pubmed. Studies were classified into four categories, namely robust, probable, suggestive and insufficient, built on the significance of the main MR analysis results and its concordance with sensitivity analyses (MR-Egger, weighed median and MR-PRESSO). Associations that did not perform any sensitivity analysis were classified as non-evaluable. FINDINGS: We identified 2,718 associations eligible for evaluation, examining 535 distinct exposures. Of them, 138 were classified as robust, 347 as probable, 109 as suggestive and 886 had insufficient evidence. The most prominent robust associations were observed for anthropometric traits (i.e., body mass index, height, waist to hip ratio and birth weight) and lipids and lipoproteins (i.e., low- and high-density lipoproteins, triglycerides) and type 2 diabetes with CAD, clinical measurements (i.e., systolic and diastolic blood pressure) with CAD and stroke, and thrombotic factors (i.e., factors XI and VII, iron and vitamin K) with stroke. CONCLUSION: Despite the large number of studies that have been conducted, only a limited number of associations were supported by robust evidence. About half of the associations presented a MR sensitivity analysis along with the main analysis which further supported the causality of associations. Future research should focus on more thorough assessment of sensitivity MR analyses and assessment of mediation effects and nonlinearity in associations.