Abstract
BACKGROUND: In recent years, the development of metabolomics has provided new opportunities to explore the associations between hundreds of metabolites and cancer risk, and it is increasingly being utilized in cancer research. After the occurrence of cancer, there are often abnormal changes in the body's metabolic processes, including alterations in glucose metabolism, lipid metabolism, amino acid metabolism, and nucleotide metabolism. These metabolomic changes provide new insights for the identification of effective tumor biomarkers and the development of targeted therapeutic approaches. However, whether blood metabolites have a causal impact on the development of gastrointestinal (GI) cancer remains to be elucidated. Therefore, the aim of this study is to investigate the potential causal effects of human blood metabolites on the risk of GI cancer through Mendelian randomization (MR) analysis. METHODS AND RESULTS: We employed a two-sample Mendelian randomization approach to assess the unconfounded causal relationships between 275 blood metabolites and the occurrence of GI cancer. We conducted screening of exposure and outcome factors through GWAS databases and SNP selection, and employed various MR statistical methods, including inverse variance weighted (IVW) method, on the eligible instrumental variables. Additionally, a series of sensitivity analyses were performed to assess the heterogeneity and pleiotropy of the instrumental variables, ensuring the robustness of the results. Univariable MR analysis revealed that genetically predicted elevated levels of various metabolites, including Octanoylcarnitine, were causally associated with an increased risk of GI cancer. Conversely, elevated levels of several metabolites, including Laurate (12:0), were associated with a decreased risk of GI cancer. Moreover, certain metabolites exhibited potential causal relationships with multiple types of GI cancer simultaneously. Through MVMR analysis, we observed significant associations of 1-Stearoylglycerophosphocholine (p: 0.019), 1-eicosatrienoylglycerophosphocholine (p: 0.028), X-11,793-oxidized bilirubin (p: 0.013), and 1-arachidonoylglycerophosphocholine (p: 0.023) with GI cancer. Furthermore, we integrated nine metabolic pathways associated with GI cancer-related metabolites, suggesting that certain types of GI cancer may share common metabolic pathways. CONCLUSIONS: We identified 36 human blood metabolites that are associated with GI cancer, thus confirming the significant role of blood metabolites in the pathogenesis of GI cancer. Furthermore, our findings provide novel potential biomarkers and targets for early screening and prevention of GI cancer.