Abstract
OBJECTIVE: To explore the causal relationship between blood metabolites and the risk of coronary artery disease (CAD) using a two-sample Mendelian randomization (MR) approach. OBJECTIVE: Based on the data from a large-scale metabolome-based genome-wide association study (mGWAS) and the GWAS of CAD, we investigated the causality between blood metabolites and CAD using an inverse variance weighted (IVW) method and another 4 two-sample MR models. Heterogeneity, horizontal pleiotropy, and sensitivity tests were performed to evaluate the stability and reliability of the results. OBJECTIVE: Among the 486 blood metabolites, 32 metabolites showed nominally causative association with CAD with the IVW method (P < 0.05), including 11 known metabolites and 21 unknown metabolites. Three known metabolites [N-acetylornithine, bradykinin-des-arg(9), and succinylcarnitine] were statistically significant in at least 3 MR models, but their causal effects on CAD were no longer significant after sensitivity analysis using leave-one-out method and elimination of the confounding instrumental variables. OBJECTIVE: There is no strong evidence to support a robust causal relationship between the 486 blood metabolites and the risk of CAD.