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find Author "HUAN Yunfeng" 1 results
  • Assessing the causal association of 1 400 blood metabolites with the risk of pancreatic cancer: a comprehensive Mendelian randomized study

    ObjectiveTo systematically evaluate the causal relationship between blood metabolites and pancreatic cancer (PC) risk using Mendelian randomization (MR). MethodsWe conducted a two-sample MR analysis using genetic instruments for 8 299 blood metabolites derived from a European genome-wide association study (GWAS) and PC outcome data from the GWAS Catalog. The primary analysis employed inverse-variance weighted (IVW) regression, with sensitivity analyses including MR-Egger, weighted median, weighted mode, and simple mode methods. Heterogeneity was assessed using Cochran’s Q test, pleiotropy was evaluated via MR-Egger intercept tests, and outliers were identified using MR-PRESSO. Robustness was confirmed through leave-one-out analyses. For metabolites showing significant associations (P<0.05), we performed independent replication using the same European PC GWAS cohort, followed by meta-analysis of all results. Reverse causation was excluded using Steiger directionality tests and bidirectional MR, while genetic confounding was assessed via linkage disequilibrium score regression (LDSC). ResultsAfter multi-stage screening, 26 blood metabolites demonstrated statistically significant associations with PC risk (P<0.05), comprising 18 annotated metabolites (12 lipids, 3 amino acids, 2 coenzymes/vitamins, 1 nucleotide, and 1 peptide), 3 metabolite ratios, and 5 unannotated metabolites. Replication analysis confirmed 6 of these 26 metabolites in the independent European PC GWAS cohort. Crucially, meta-analysis of all 26 metabolites yielded consistent significant associations (P<0.05 for all), with 1-palmitoleoylglycerol (16:1) exhibiting the strongest protective effect [OR=0.76, 95%CI (0.68, 0.85), P<1.0×10-5]. LDSC analysis revealed no significant genetic confounding for 25/26 metabolites (P>0.05), except for myristate (14:0), Rg=1.534, Se=0.571, P=0.007), where genetic correlation potentially influenced MR estimates. Pathway analysis further implicated dysregulation of lipid metabolism as a key mechanism, with 1-palmitoleoylglycerol emerging as a high-priority biomarker candidate for PC risk stratification. ConclusionsThis study provides causal evidence within the European population that some blood metabolites are associated with PC risk, identifying 1-palmitoleoylglycerol as a novel protective biomarker and highlighting targeting lipid metabolic pathways as a promising therapeutic strategy for pancreatic cancer.

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