Search

Background: Observational studies have highlighted the pivotal role of inflammatory cytokines in cirrhosis progression. However, the existence of a causal link between inflammatory cytokines and cirrhosis remains uncertain. In this study, we conducted a bidirectional Mendelian randomization (MR) analysis at a summarized level to illuminate the potential causal relationship between the two variables. Methods: This study utilized genetic variance in cirrhosis and inflammatory cytokines from a genome-wide association study (GWAS) of European descent. The MR-PRESSO outlier test, Cochran’s Q test, and MR-Egger regression were applied to assess outliers, heterogeneity, and pleiotropy. The inverse variance weighted method and multiple sensitivity analyses were used to evaluate causalities. Furthermore, the validation set was used for simultaneous data validation. Results: The inflammatory cytokine monocyte chemoattractant protein 3 (MCP-3) was supposedly associated with a greater risk of cirrhosis. And cirrhosis was significantly correlated with increased levels of hepatocyte growth factor (HGF). Conclusions: This study suggests that MCP-3 might be associated with the etiology of cirrhosis, while several inflammatory cytokines could potentially play a role in its downstream development. Additionally, the progression of cirrhosis was associated with elevated levels of HGF, suggesting a possible role for liver repair functions.

Chronic hepatitis B (CHB) virus infection is a major risk factor for cirrhosis and hepatocellular carcinoma (HCC). Hepatitis B virus (HBV) immune escape is regulated by the exhaustion of virus-specific CD8+ T cells, which is associated with abnormal expression of negative regulatory molecule CD244. However, the underlying mechanisms are unclear. To investigate the important roles of non-coding RNAs play in CD244 regulating HBV immune escape, we performed microarray analysis to determine the differential expression profiles of long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in patients with CHB and patients with spontaneous clearance of HBV. Competing endogenous RNA (ceRNA) was analyzed by bioinformatics methods and confirmed by the dual-luciferase reporter assay. Furthermore, gene silencing and overexpression experiments were used to further identify the roles of lncRNA and miRNA in HBV immune escape through CD244 regulation. The results showed that the expression of CD244 on the surface of CD8+ T cells was significantly increased in CHB patients and in the co-culture system of T cells and HBV-infected HepAD38 cells, which was accompanied by the reduction of miR-330-3p and the elevation of lnc-AIFM2-1. The down-regulated miR-330-3p induced the apoptosis of T cells by lifting the inhibition of CD244, which was reversed by miR-330-3p mimic or CD244-siRNA. Lnc-AIFM2-1 promotes the accumulation of CD244, which is mediated by decreased miR-330-3p, and then reduced the clearance ability of CD8+ T cells to HBV through regulated CD244 expression. And the injury in the ability of CD8+ T cells to clear HBV can be reversed by lnc-AIFM2-1-siRNA, miR-330-3p mimic, or CD244-siRNA. Collectively, our findings indicate that lnc-AIFM2-1 on CD244 by acting as a ceRNA of miR-330-3p contributes to HBV immune escape, which may provide novel insights into the roles of interaction networks among lncRNA, miRNA, and mRNA in HBV immune escape, highlighting potential applications of lnc-AIFM2-1 and CD244 for diagnosis and treatment in CHB.

Non-alcoholic fatty liver disease (NAFLD) encompasses a broad spectrum of conditions from simple steatosis (non-alcoholic fatty liver (NAFL)) to non-alcoholic steatohepatitis (NASH), and its global prevalence continues to rise. NASH, the progressive form of NAFLD, has higher risks of liver and non-liver related adverse outcomes compared with those patients with NAFL alone. Therefore, the present study aimed to explore the mechanisms in the progression of NAFLD and to develop a model to diagnose NASH based on the transcriptome and epigenome. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) among the three groups (normal, NAFL, and NASH) were identified, and the functional analysis revealed that the development of NAFLD was primarily related to the oxidoreductase-related activity, PPAR signaling pathway, tight junction, and pathogenic Escherichia coli infection. The logistic regression (LR) model, consisting of ApoF, THOP1, and BICC1, outperformed the other five models. With the highest AUC (0.8819, 95%CI: 0.8128–0.9511) and a sensitivity of 97.87%, as well as a specificity of 64.71%, the LR model was determined as the diagnostic model, which can differentiate NASH from NAFL. In conclusion, several potential mechanisms were screened out based on the transcriptome and epigenome, and a diagnostic model was built to help patient stratification for NAFLD populations.