Abstract:Background and Aims: Inflammation may contribute to the development and progression of pancreatic cancer; however, conventional observational studies have difficulty distinguishing the potential causal relationships between circulating inflammation-related proteins and pancreatic cancer risk from disease-related secondary changes. This study aimed to systematically investigate the potential causal associations between circulating inflammation-related proteins and pancreatic cancer risk using genetic epidemiological approaches and to prioritize candidate proteins with relatively consistent genetic evidence. Methods: Publicly available genome-wide association study (GWAS) summary statistics were used to perform a two-sample Mendelian randomization (MR) analysis of 91 circulating inflammation-related proteins and pancreatic cancer risk. The inverse-variance weighted (IVW) method was used as the primary analytical approach, complemented by weighted median, MR-Egger regression, and weighted mode analyses for robustness assessment. Candidate proteins meeting the prespecified screening criteria were further evaluated using multivariable Mendelian randomization (MVMR) and Mendelian randomization Bayesian model averaging (MR-BMA) to assess their conditional effects and relative model support. Heterogeneity, horizontal pleiotropy, instrument strength, and statistical power were also evaluated. Results: Univariable MR analysis identified five candidate proteins showing nominal associations with pancreatic cancer risk and consistent effect directions across MR methods. Genetically predicted higher levels of cystatin D, CXCL6, and LIFR were associated with increased pancreatic cancer risk, whereas higher levels of IL-2 and IL-24 were associated with lower risk. In subsequent MVMR analyses, CXCL6 was the only protein that consistently retained a positive association across MVMR-IVW, MVMR-Egger, and MVMR-LASSO models. MR-BMA further showed that CXCL6 had the highest marginal inclusion probability (MIP=0.569), with the empirical P value remaining significant after Benjamini-Hochberg correction (P=0.005). Sensitivity analyses revealed no substantial evidence of heterogeneity or directional horizontal pleiotropy. The minimum single-SNP F statistic and conditional F statistic for CXCL6 were 22.67 and 17.49, respectively, with an estimated statistical power of 70.7%, indicating adequate but limited power to detect modest effects. Conclusion: This study identified five circulating inflammation-related proteins potentially associated with pancreatic cancer risk among 91 candidates. CXCL6 showed relatively consistent genetic evidence across MVMR and MR-BMA analyses and may represent a priority candidate for further investigation of inflammation-related pathways in pancreatic cancer susceptibility. However, the current evidence is insufficient to establish a definitive causal relationship between CXCL6 and pancreatic cancer, and further validation in independent populations and tissue-based and functional studies is warranted.