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Published on: December 15, 2017
Novel causal associations between plasma metabolites and prostate cancer risk revealed by mendelian randomization
Hanghang Chen1, Huiduo Zhao1, Bingxin Meng1
1Breast Surgery, The First Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou, 450000, China.
Background:
Prostate cancer (PCa) is a major global health concern for men, yet its underlying metabolic mechanisms are not fully understood. Identifying causal metabolites could reveal novel pathways for risk assessment and prevention.
Methods:
We conducted a comprehensive two-sample Mendelian randomization (TSMR) study following STROBE-MR guidelines. Genetic instruments for plasma metabolites were derived from two independent sources, including the METSIM study, a cohort exclusively comprising Finnish men, and the Canadian Longitudinal Study on Aging (CLSA). Summary-level data for PCa were obtained from the PRACTICAL consortium and FinnGen. Inverse variance weighted (IVW) was the primary analysis method, supplemented by sensitivity analyses and Bayesian colocalization (coloc) to assess shared causal genetic variants, a key methodological strength enhancing causal inference.
Results:
Our analysis identified four plasma metabolites with a significant causal relationship with PCa risk. Ribitol was associated with a reduced risk, while N2,N5-diacetylornithine, N-acetylarginine, and N-acetylcitrulline were associated with an elevated risk. These findings were consistent across datasets and robust in sensitivity analyses. Colocalization analysis provided strong evidence (PP.H4 > 0.8) for a shared causal variant at the rs10201159 locus between N2,N5-diacetylornithine and PCa.
Conclusion:
This study provides robust genetic evidence supporting a causal role of specific plasma metabolites in prostate cancer development. The incorporation of a male-exclusive metabolomic dataset (METSIM) strengthens the validity of our findings for this male-specific cancer. These metabolites represent promising candidates for further mechanistic investigation into prostate cancer etiology and potential translation into clinical biomarkers.
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