Causal association between metabolites and cardiovascular MACE events: a two-sample Mendelian randomization study

Abstract

Objective: Adverse cardiovascular events are key clinical endpoints in cardiovascular diseases. Recent metabolomics studies have highlighted the significant role of metabolites and their ratios in the occurrence and progression of these events. This study aims to explore the causal relationship between circulating metabolites and seven types of cardiovascular adverse events using Mendelian randomization analysis. Methods: A two-sample Mendelian randomization analysis was employed in this study. We selected 1,400 circulating metabolites as exposure factors and examined their association with seven cardiovascular adverse events (including Acute Myocardial Infarction, Unstable Angina, sudden Cardiac Death, Cardiac Arrest, Ventricular Tachycardia, Heart Failure, and Cerebral Infarction). The inverse-variance weighted method was primarily used for the analysis, and the results were subjected to FDR multiple testing correction to identify metabolites of significant and potential relevance. Additionally, multiple sensitivity analyses, including MR Egger intercept, MR-PRESSO, and Cochran Q, were conducted to enhance the reliability and accuracy of the findings. Finally, metabolic pathway analysis was performed for all metabolites with established causal relationships. Results: Our study identified 254 metabolites and metabolite ratios associated with cardiovascular adverse events. We confirmed potential causal relationships of 339 metabolites with these diseases (53 with Cerebral Infarction, 29 with Unstable Angina, 22 with Acute Myocardial Infarction, 53 with Malignant Arrhythmias, 57 with Cardiac Arrest, 62 with Cardiogenic Death, and 63 with Heart Failure), and eventually pinpointed 7 significant metabolites and 12 metabolic pathways closely related to cardiovascular adverse events.Meanwhile, the results of the sensitivity analysis showed the stability of our findings. Conclusion: Through Mendelian randomization analysis, we identified multiple metabolites associated with cardiovascular adverse events, providing vital evidence and support for the metabolomic study of these events.