PgRNA kinetics predict HBsAg reduction in pregnant chronic hepatitis B carriers after treatment cessation.

Background: Pregenomic RNA (pgRNA) and hepatitis B core-related antigen (HBcrAg) play significant roles in predicting discontinuing treatment outcomes. However, their role in pregnancy has rarely been reported. We aimed to evaluate the performance of pgRNA and HBcrAg kinetics in predicting HBeAg seroconversion and HBsAg reduction postpartum in HBeAg-positive pregnant women. Methods: Pregnant HBeAg-positive patients receiving antiviral prophylaxis and ceasing treatment postpartum were included. PgRNA and HBcrAg levels were measured before treatment, at 32 weeks of gestation, and at treatment withdrawal postpartum. Other virological and biochemical parameters were regularly examined until 96 weeks postpartum. Results: Of 76 pregnant chronic hepatitis B (CHB) carriers with a median treatment duration of 18.1 weeks, HBeAg seroconversion and HBsAg reduction >0.3 log10 IU/mL at 96 weeks postpartum occurred in 8 (10.5%) and 13 (17.1%) patients, respectively. HBsAg correlated most strongly with pgRNA, while HBeAg correlated most strongly with HBcrAg. Multivariable regression analysis revealed that postpartum pgRNA decline and peak ALT levels were independent predictors of HBsAg reduction. The area under the curve of the regression model was 0.79 and reached as high as 0.76 through bootstrapping validation. The calibration plot showed that the nomogram had a performance similar to that of the ideal model. A decision tree was established to facilitate application of the nomogram. In addition, HBcrAg kinetics, as an independent predictor, performed poorly in predicting HBeAg seroconversion. Conclusions: Postpartum pgRNA decline together with peak ALT levels may identify patients with a higher probability of HBsAg reduction after treatment cessation postpartum among pregnant CHB carriers receiving antiviral prophylaxis.

Potential Molecular Targets of Tenofovir Disoproxil Fumarate for Alleviating Chronic Liver Diseases via a Non-Antiviral Effect in a Normal Mouse Model.

Accumulating evidence suggests that tenofovir disoproxil fumarate (TDF) can attenuate liver fibrosis directly, the mechanism of which, however, has not been fully elucidated, and there is a paucity of data concerning whether TDF can also mitigate other chronic liver diseases (CLDs). We aimed to identify the molecular targets and potential mechanism of TDF itself in ameliorating CLDs. RNA-sequencing was performed on mouse liver tissues treated with TDF or normal saline. Then the differentially expressed genes (DEGs) were screened, and enrichment analyses of the function and signaling pathways of DEGs were performed with Database for Annotation, Visualization, and Integrated Discovery (DAVID) and Metascape. Next, protein-protein interaction (PPI) networks were constructed and module analyses were utilized to identify significant genes. Subsequently, the DisGeNET platform was used to identify the potential target genes of TDF in mitigating these diseases. Finally, prediction of the transcription factors (TFs) and microRNAs (miRNAs) of the target genes was done to conjecture the underlying mechanism by which TDF relieved CLDs. As a result, a total of 854 DEGs were identified, and the DEGs were involved mainly in "immunity," "inflammation," and "metabolism" processes. In addition, 50 significant genes were obtained via PPI construction and module analyses. Furthermore, by means of DisGeNET, 19 genes (Adra2a, Cxcl1, Itgam, Cxcl2, Ccr1, Ccl5, Cxcl5, Fabp5, Sell, Lilr4b, Ccr2, Tlr2, Lilrb4a, Tnf, Itgb2, Lgals3, Cxcr4, Sucnr1, and Mme) were identified to be associated with nine CLDs. Finally, 34 miRNAs (especially mmu-miR-155-5p) and 12 TFs (especially Nfkb1) were predicted to be upstream of the nine target genes (Cxcl1, Cxcl2, Ccl5, Ccr2, Sell, Tlr2, Tnf, Cxcr4, and Mme) of TDF in ameliorating CLDs. In conclusion, our study suggests that TDF have the potential to ameliorate CLDs independently of its antiviral activity by affecting the expression of genes involved in hepatic immune, inflammatory, and metabolic processes via mmu-miR-155-5p-NF-κB signaling. These findings provided prima facie evidence for using TDF in CHB patients with concurrent CLDs.

Identification of key genes, pathways and potential therapeutic agents for liver fibrosis using an integrated bioinformatics analysis.

BACKGROUND: Liver fibrosis is often a consequence of chronic liver injury, and has the potential to progress to cirrhosis and liver cancer. Despite being an important human disease, there are currently no approved anti-fibrotic drugs. In this study, we aim to identify the key genes and pathways governing the pathophysiological processes of liver fibrosis, and to screen therapeutic anti-fibrotic agents. METHODS: Expression profiles were downloaded from the Gene Expression Omnibus (GEO), and differentially expressed genes (DEGs) were identified by R packages (Affy and limma). Gene functional enrichments of each dataset were performed on the DAVID database. Protein-protein interaction (PPI) network was constructed by STRING database and visualized in Cytoscape software. The hub genes were explored by the CytoHubba plugin app and validated in another GEO dataset and in a liver fibrosis cell model by quantitative real-time PCR assay. The Connectivity Map L1000 platform was used to identify potential anti-fibrotic agents. RESULTS: We integrated three fibrosis datasets of different disease etiologies, incorporating a total of 70 severe (F3-F4) and 116 mild (F0-F1) fibrotic tissue samples. Gene functional enrichment analyses revealed that cell cycle was a pathway uniquely enriched in a dataset from those patients infected by hepatitis B virus (HBV), while the immune-inflammatory response was enriched in both the HBV and hepatitis C virus (HCV) datasets, but not in the nonalcoholic fatty liver disease (NAFLD) dataset. There was overlap between these three datasets; 185 total shared DEGs that were enriched for pathways associated with extracellular matrix constitution, platelet-derived growth-factor binding, protein digestion and absorption, focal adhesion, and PI3K-Akt signaling. In the PPI network, 25 hub genes were extracted and deemed to be essential genes for fibrogenesis, and the expression trends were consistent with GSE14323 (an additional dataset) and liver fibrosis cell model, confirming the relevance of our findings. Among the 10 best matching anti-fibrotic agents, Zosuquidar and its corresponding gene target ABCB1 might be a novel anti-fibrotic agent or therapeutic target, but further work will be needed to verify its utility. CONCLUSIONS: Through this bioinformatics analysis, we identified that cell cycle is a pathway uniquely enriched in HBV related dataset and immune-inflammatory response is clearly enriched in the virus-related datasets. Zosuquidar and ABCB1 might be a novel anti-fibrotic agent or target.