Abstract
BACKGROUND: There is a growing body of evidence indicating that metabolites are associated with an increased risk of cardiovascular diseases (CVDs), the underlying causality of these associations remains largely unchallenged. Given the inherent difficulty in establishing causality using epidemiological data, we employed the technique of Mendelian randomization to investigate the potential role of plasma metabolite factors in influencing the risk of CVDs. METHODS: The exposure was based on 1,400 plasma metabolites, and outcomes involved four CVD datasets from public databases. Initial causality was assessed by inverse variance weighting (IVW), followed by sensitivity analyses using MR-Egger regression, weighted median, and Multiple Effectiveness Residual Sums and Outliers (MR-PRESSO) method. Potential heterogeneity and multivalence were assessed using the MR-Egger intercept and Cochran's Q statistic. After Bonferroni correction, causal associations were found to be significant with p-values less than 0.05. All statistical analyses were rigorously executed in R software. RESULTS: Our findings identified causal relationships between 15 metabolites and cardiovascular disease. Of these, 4 were associated with AA (aortic aneurysm), 7 with atrial fibrillation and flutter, 2 with HF (heart failure), and 3 with stroke. CONCLUSION: This is the first systematic mendelian randomization analysis using genome-wide data to assess the causal relationship between serum metabolites and different cardiovascular diseases, providing preliminary evidence for the impact of lipid metabolism disorders on cardiovascular disease risk.