Blood metabolites, mitochondrial biofunction, and cervical cancer: a bidirectional Mendelian randomization study.
Blood metabolites and mitochondrial biological functions are associated with the occurrence and development of cancer, but the potential causal relationship between them and cervical cancer remains unknown. This bidirectional two-sample Mendelian randomization study aims to investigate the potential causal relationship between blood metabolites, mitochondrial biofunction and cervical cancer.
In this study, the blood metabolites and mitochondrial biofunction datasets were used as exposure factors, and the cervical cancer dataset from the Finnish dataset was used as the outcome. The study employed single nucleotide polymorphisms (SNPs) as instrumental variables and utilizes Inverse Variance Weighted (IVW), MR Egger, and Weighted Median methods for Mendelian randomization analysis. Sensitivity analysis was used to assess the reliability of the results. We also performed subgroup analysis based on the pathological types of cervical cancer. To further illuminate the possible metabolic mechanisms, MetaboAnalyst 6.0 tool was employed for metabolic pathway analysis.
The results indicated that 25 blood metabolites and 3 mitochondrial biofunctions have a potential causal relationship with cervical cancer. Among these blood metabolites, they can be categorized into fatty acid metabolites, bile acid metabolites, amino acid metabolites, hormone metabolites, caffeine metabolites, and others. Subgroup analysis reveals that different pathological types of cervical cancer have distinct potential risk and protective factors. Furthermore, metabolic pathway analysis suggests that linolenic acid metabolism exhibits strong anti-tumor potential. Specifically, Linolenate [alpha or gamma; (18:3n3 or 6)] showed an OR value of 0.81 (95% CI: 0.67-0.99), indicating a potential causal relationship between lipid metabolism and cervical cancer.
Blood metabolites and mitochondrial biofunction have potential causal relationships with cervical cancer, which provides new insights for further research on the etiology and treatment of cervical cancer.
In this study, the blood metabolites and mitochondrial biofunction datasets were used as exposure factors, and the cervical cancer dataset from the Finnish dataset was used as the outcome. The study employed single nucleotide polymorphisms (SNPs) as instrumental variables and utilizes Inverse Variance Weighted (IVW), MR Egger, and Weighted Median methods for Mendelian randomization analysis. Sensitivity analysis was used to assess the reliability of the results. We also performed subgroup analysis based on the pathological types of cervical cancer. To further illuminate the possible metabolic mechanisms, MetaboAnalyst 6.0 tool was employed for metabolic pathway analysis.
The results indicated that 25 blood metabolites and 3 mitochondrial biofunctions have a potential causal relationship with cervical cancer. Among these blood metabolites, they can be categorized into fatty acid metabolites, bile acid metabolites, amino acid metabolites, hormone metabolites, caffeine metabolites, and others. Subgroup analysis reveals that different pathological types of cervical cancer have distinct potential risk and protective factors. Furthermore, metabolic pathway analysis suggests that linolenic acid metabolism exhibits strong anti-tumor potential. Specifically, Linolenate [alpha or gamma; (18:3n3 or 6)] showed an OR value of 0.81 (95% CI: 0.67-0.99), indicating a potential causal relationship between lipid metabolism and cervical cancer.
Blood metabolites and mitochondrial biofunction have potential causal relationships with cervical cancer, which provides new insights for further research on the etiology and treatment of cervical cancer.