Dose-response : a publication of International Hormesis Society · 2026
Causal Association Between Gut Microbiota, Plasma Metabolites, and Prostate Cancer: Two-Step Mendelian Randomization Study.
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Li Junxiong, Hou Jian, Liu Haolin, Fan Shicheng, Wang Yumin, Liang Pinyao, Qin Jingbo, Gu Peng, Liu Xiaodong, Wen Xiangyang
Аннотация
OBJECTIVES: The specific role of metabolites in mediating the relationship between gut microbiota (GM) and prostate cancer (PCa) remains unclear. In this study, we utilized Mendelian randomization (MR) analyses to investigate the causal relationship between 430 GM traits, 1,400 plasma metabolites, and PCa.
METHODS: Inverse variance weighted (IVW) method is the primary analytical approach, with supplementary validation using MR-Egger, weighted median, and weighted mode methods. Mediation analysis was performed to assess the contribution of metabolites to the GM-PCa association.
RESULTS: IVW analysis identified 18 GM traits and 66 plasma metabolites showing a causal association with PCa. For instance, P_Firmicutes exhibited a causally protective effect against PCa (IVW: OR=0.937, P=0.008), while Parasutterella showed a causally risk-increasing effect (IVW: OR=1.029, P=0.039). Notably, four metabolites mediated the causal effects of GM on PCa: Subdoligranulum via unidentified metabolite X-25422 (20.785% mediation proportion, P=0.022), Bacteroides via N-acetylarginine (6.706%, P=0.020), and Parasutterella and G_Roseburia via N-acetyl-L-glutamine (-9.382%, P=0.031 and -9.094%, P=0.036, respectively). No significant heterogeneity or horizontal pleiotropy was detected.
CONCLUSION: These findings offer new insights into the metabolite-mediated pathways linking GM to PCa, which may serve as novel potential biomarkers and therapeutic targets for precision therapies.
METHODS: Inverse variance weighted (IVW) method is the primary analytical approach, with supplementary validation using MR-Egger, weighted median, and weighted mode methods. Mediation analysis was performed to assess the contribution of metabolites to the GM-PCa association.
RESULTS: IVW analysis identified 18 GM traits and 66 plasma metabolites showing a causal association with PCa. For instance, P_Firmicutes exhibited a causally protective effect against PCa (IVW: OR=0.937, P=0.008), while Parasutterella showed a causally risk-increasing effect (IVW: OR=1.029, P=0.039). Notably, four metabolites mediated the causal effects of GM on PCa: Subdoligranulum via unidentified metabolite X-25422 (20.785% mediation proportion, P=0.022), Bacteroides via N-acetylarginine (6.706%, P=0.020), and Parasutterella and G_Roseburia via N-acetyl-L-glutamine (-9.382%, P=0.031 and -9.094%, P=0.036, respectively). No significant heterogeneity or horizontal pleiotropy was detected.
CONCLUSION: These findings offer new insights into the metabolite-mediated pathways linking GM to PCa, which may serve as novel potential biomarkers and therapeutic targets for precision therapies.