Evaluating Causal Relationship Between Metabolites and Six Cardiovascular Diseases Based on GWAS Summary Statistics

Abstract

Cardiovascular diseases (CVDs) remain the main cause of morbidity and mortality worldwide. The pathological mechanism and underlying biological processes of these diseases with metabolites remain unclear. In this study, we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the causal effect of metabolites on these diseases by making full use of the latest GWAS summary statistics for 486 metabolites and six major CVDs. Extensive sensitivity analyses were implemented to validate our MR results. We also conducted linkage disequilibrium score regression (LDSC) and colocalization analysis to investigate whether MR findings were driven by genetic similarity or hybridization between LD and disease-associated gene loci. We identified a total of 310 suggestive associations across all metabolites and CVDs, and finally obtained four significant associations, including bradykinin, des-arg(9) (odds ratio [OR] = 1.160, 95% confidence intervals [CIs]: 1.080–1.246, false discovery rate [FDR] = 0.022) on ischemic stroke, N-acetylglycine (OR = 0.946, 95%CIs: 0.920–0.973, FDR = 0.023), X-09026 (OR = 0.845, 95%CIs: 0.779–0.916, FDR = 0.021) and X-14473 (OR = 0.938, 95%CIs = 0.907–0.971, FDR = 0.040) on hypertension. Sensitivity analyses showed that these causal associations were robust, the LDSC and colocalization analyses demonstrated that the identified associations were unlikely confused by LD. Moreover, we identified 15 important metabolic pathways might be involved in the pathogenesis of CVDs. Overall, our work identifies several metabolites that have a causal relationship with CVDs, and improves our understanding of the pathogenesis and treatment strategies for these diseases.