Abstract
Objective: To analyze the causal relationship between circulating inflammatory proteins and the risk of liver cirrhosis by the two-sample Mendelian randomization (MR) method. Methods: Single nucleotide polymorphisms (SNP) strongly associated with 91 plasma inflammatory proteins in genome-wide association studies (GWAS) were used as instrumental variables, and liver cirrhosis was used as the outcome variable. Random-effects inverse variance-weighted (IVW), MR Egger regression, odds ratio (OR) and its 95% confidence interval were used to evaluate the causal relationship. Simultaneously, sensitivity analysis was performed using MR pleiotropy residuals and outliers (MR-PRESSO) and the Q-test. Results: The causal relationship between the expression of seven specific circulating inflammatory proteins and liver cirrhosis was confirmed by the inverse variance-weighted (IVW) method. The results showed that five plasma inflammatory proteins, including leukemia inhibitory factor [OR(CI)=0.66,P=9.73×10(-5)], interleukin-18 [OR(CI)=0.76,P=0.013], tumor necrosis factor ligand superfamily member 12[OR(CI)=0.75,P=0.024], monocyte chemoattractant protein 2 [OR(CI)=0.89,P=0.036], and C-C motif chemokine 25 [OR(CI)=0.84,P=0.039], were negatively correlated with cirrhosis and were protective factors for cirrhosis. T cell surface glycoprotein CD5 [OR (CI)=1.29,P=0.035] and C-X-C motif chemokine 10 [OR(CI)=1.32,P=0.043] were positively correlated with cirrhosis and were risk factors for cirrhosis. The results of the MR-PRESSO, Q-test, MR-Egger intercept test, and leave-one-out method all showed the stability. Conclusion: The research results indicated that the increased levels of leukemia inhibitory factor, interleukin-18, tumor necrosis factor ligand superfamily member 12, monocyte chemoattractant protein-2, and C-C motif chemokine 25 were protective factors in the development of cirrhosis, while the increased levels of T cell surface glycoprotein CD5 and C-X-C motif chemokine 10 were risk factors for the development of cirrhosis based on genetic data.