Genetically predicted 486 blood metabolites in relation to risk of colorectal cancer: A Mendelian randomization study

Metabolic disorders are a hallmark feature of cancer. However, the evidence for the causality of circulating metabolites to promote or prevent colorectal cancer (CRC) is still lacking. We performed a two-sample Mendelian randomization (MR) analysis to assess the causality from genetically proxied 486 blood metabolites to CRC.Genome-wide association study (GWAS) data for exposures were extracted from 7824 Europeans GWAS on metabolite levels. GWAS data for CRC from the GWAS catalog database GCST012879 were used for the preliminary analysis. The random inverse variance weighted (IVW) is the primary analysis for causality analysis while MR-Egger and weighted median as complementary analyses. Cochran Q test, MR-Egger intercept test, MR-PRESSO, Radial MR, and leave-one-out analysis were used for sensitivity analyses. For significant associations, additional independent CRC GWAS data GCST012880 were used for replication analysis and meta-analysis. For the final identification of metabolites, Steiger test, linkage disequilibrium score regression, and colocalization analysis were performed for further evaluation. Multivariable MR was performed to assess the direct effect of metabolites on CRC.The results of this study indicated significant associations between six metabolites pyruvate (odds ratio [OR]: 0.49, 95% confidence interval [CI]: 0.32-0.77, p = 0.002), 1,6-anhydroglucose (OR: 1.33, 95% CI: 1.11-1.59, p = 0.002), nonadecanoate (19:0) (OR: 0.40, 95% C I:0.4-0.68, p = 0.0008), 1-linoleoylglycerophosphoethanolamine (OR: 0.47, 95% CI: 0.30-0.75, p = 0.001), 2-hydroxystearate (OR: 0.39, 95% CI: 0.23-0.67, p = 0.0007), gamma-glutamylthreonine (OR: 2.14, 95% CI: 1.02-4.50, p = 0.040) and CRC. MVMR analysis revealed that genetically predicted pyruvate, 1-linoleoylglycerophosphoethanolamine and gamma-glutamylthreonine can directly influence CRC independently of other metabolites.The current work provides evidence to support the causality of the six circulating metabolites on CRC and a new perspective on the exploration of the biological mechanisms of CRC by combining genomics and metabolomics. These findings contribute to the screening, prevention and treatment of CRC.