Elucidating the causal relationship between 486 genetically predicted blood metabolites and the risk of gastric cancer: a comprehensive Mendelian randomization analysis - Qian, Lei; Song, Jiawei; Zhang, Xiaoqun; Qiao, Yihuan; Tan, Zhaobang; Li, Shisen; Zhu, Jun; Li, Jipeng (Frontiers in Oncology, 2024)
BackgroundPrevious epidemiological studies have yielded inconclusive results regarding the causality between blood metabolites and the risk of gastric cancer (GC). To address this shortcoming, we conducted a two-sample Mendelian randomization (MR) study, combined with metabolomics techniques, to elucidate the causality between 486 genetically predicted blood metabolites and GC.MethodsMR analysis and metabolomics techniques such as ultra-high performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) and gas chromatography/tandem mass spectrometry (GC-MS/MS) technologies were employed to assess the causality of 486 genetically predicted blood metabolites on the risk of GC. The genome-wide association study (GWAS) summary data for 486 blood metabolites from 7,824 individuals. The GWAS summary data for GC (ebi-a-GCST90018849) were obtained from the IEU Open GWAS project, including 1,029 GC cases and 474,841 controls. Primary causality estimates were obtained using inverse variance weighting (IVW), supplemented with the weighted median, MR-Egger, weighted mode, and simple mode. In addition, we conducted sensitivity analyses (including Cochran’s Q, MR-Egger intercept, MR-PRESSO, and leave-one-out tests),Steiger’s test, linked disequilibrium score regression, and multivariate MR (MVMR) to improve the assessment of causality between GC and blood metabolite. Finally, we recruited a total of 11 patients diagnosed with gastric cancer from the First Affiliated Hospital of Air Force Military Medical University between September and October 2024. The control group comprised 11 healthy individuals. Serum samples were collected from both groups for the evaluation of blood-related metabolite expression levels using advanced techniques such as ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and gas chromatography-mass spectrometry (GC-MS/MS).ResultsThe MVMR analysis revealed a significant association between genetically predicted elevated levels of tryptophan (odds ratio [OR] = 0.523, 95% confidence interval [CI] = 0.313–0.872, p = 0.013), nonadecanoate (19:0) (odds ratio [OR] = 0.460, 95% confidence interval [CI] = 0.225–0.943, p = 0.034), and erythritol (odds ratio [OR] = 0.672, 95% confidence interval [CI] = 0.468–0.930, p = 0.016) with a decreased risk of gastric cancer. Based on metabolomic techniques such as UPLC-MS/MS and GC-MS/MS analyses, it has been demonstrated that the expression levels of tryptophan, nonadecanoate (19:0), and erythritol are reduced in patients with gastric cancer. This finding aligns with the results obtained from our MR analysis and provides further confirmation regarding the protective role of tryptophan, nonadecanoate (19:0), and erythritol against gastric cancer.ConclusionsThese findings indicate that three blood metabolites are causally related to GC and provide new perspectives for combining genomics and metabolomics to study the mechanisms of metabolite-mediated GC development.