Plasma Fibronectin Levels Identified via Quantitative Proteomics Profiling Predicts Hepatitis B Surface Antigen Seroclearance in Chronic Hepatitis B

Predictive Factors for HBsAg Loss in Chronic HBeAg-Negative Hepatitis B Virus Infection: Insights From a 5-Year French Cohort

Prognostic factors for the long-term evolution of chronic hepatitis B e antigen (HBeAg)-negative hepatitis B virus (HBV) infection may vary depending on local epidemiology. We aimed to identify these factors in France, where the epidemiology is influenced by diverse immigration. Hepatitis B surface antigen (HBsAg)-positive, HBeAg-negative adults with normal transaminase levels and viral loads < 20,000 IU/mL for 1 year, without viral co-infection or advanced liver disease, were enrolled for a 5-year follow-up. A total of 564 patients were recruited from 23 centres (54.4% women, mean age 42.3 ± 12 years, 47.7% from sub-Saharan Africa). HBV DNA was detectable but < 2000 IU/mL for most (71.3%). Genotypes E (27.8%) and A (20.0%) were predominant. The mean HBsAg titre was 3.8 ± 3.4 log IU/mL, > 1000 IU/mL in 60% of cases, and higher in genotype E (p < 0.0001). During follow-up, 18 patients received antiviral treatment, 9 for viral reactivation (0.3% per year) and 9 preemptively. HBsAg loss occurred in 39 patients (1.4% per year). These patients were older (p < 0.0001), more frequently treated for dyslipidemia, hypertension or diabetes (p < 0.05), and had lower baseline HBV DNA (p = 0.0112) and HBsAg (p < 0.0001), but similar levels of HBcrAg compared to those who did not clear HBsAg. Baseline HBsAg was the only independent predictor of HBsAg loss (p = 0.009). In this cohort, HBsAg < 153 IU/mL predicted clearance with 87% sensitivity and specificity. In conclusion, baseline HBsAg accurately predicted seroclearance at 5 years in patients with chronic HBeAg-negative infection, regardless of genotype, sex, or geographical origin, indicating that this marker is widely applicable for reducing the frequency of patient monitoring.

Advances in multi-omics research on viral hepatitis

Viral hepatitis is a major global public health problem that affects hundreds of millions of people and is associated with significant morbidity and mortality. Five biologically unrelated hepatotropic viruses account for the majority of the global burden of viral hepatitis, including hepatitis A virus (HAV), hepatitis B virus (HBV), hepatitis C virus (HCV), hepatitis D virus (HDV), and hepatitis E virus (HEV). Omics is defined as the comprehensive study of the functions, relationships and roles of various types of molecules in biological cells. The multi-omics analysis has been proposed and considered key to advancing clinical precision medicine, mainly including genomics, transcriptomics and proteomics, metabolomics. Overall, the applications of multi-omics can show the origin of hepatitis viruses, explore the diagnostic and prognostics biomarkers and screen out the therapeutic targets for viral hepatitis and related diseases. To better understand the pathogenesis of viral hepatitis and related diseases, comprehensive multi-omics analysis has been widely carried out. This review mainly summarizes the applications of multi-omics in different types of viral hepatitis and related diseases, aiming to provide new insight into these diseases.

Phenotypic Changes of PD-1 and GITR in T Cells Are Associated With Hepatitis B Surface Antigen Seroclearance

BACKGROUND

Regulatory T cells (Tregs) possess hepatitis B virus (HBV)-specific immunoregulatory effects in chronic HBV infection. The role of Tregs in spontaneous seroclearance of hepatitis B surface antigen (HBsAg) remains to be determined.

METHODS

We recruited treatment-naive chronic HBV patients achieving spontaneous HBsAg seroclearance (experimental group) and matched HBsAg-positive controls. Peripheral blood mononuclear cells were isolated using the Ficoll-Paque density gradient centrifugation method. The frequency of Tregs and inhibitory phenotypes and immunoregulatory cytokines of Tregs were detected by flow cytometry.

RESULTS

Twenty-seven patients with HBsAg seroclearance (mean age: 52.40±6.00 y, 55.6% male) and 27 matched controls were recruited. Median HBsAg and HBV DNA levels in the control group were 2.80 (1.24 to 3.43) and 3.16 (1.68 to 3.85) log IU/mL, respectively. Mean frequencies of Tregs and expressions of FoxP3+ Tregs were comparable in both groups (both P>0.05). The mean expression of programmed death 1 (PD-1) and glucocorticoid-induced TNFR family-related gene (GITR) in total CD4+ T cells were significantly downregulated in the experimental group when compared with the control group (10.62% vs. 13.85%, P=0.003; 16.20% vs. 27.02%, P=0.002, respectively). When compared with the control group, PD-1+CD4+ Tregs expression in the experimental group was significantly downregulated (13.85% vs. 10.62%, P=0.003). A similar phenomenon was noted for GITR+CD8+ Tregs (20.16% vs. 14.08%, P=0.049). Intracellular cytokine productions showed no significant differences (all P>0.05).

CONCLUSIONS

The reduced expression of PD-1 and GITR might attenuate the immunosuppressive capability of Tregs. Decreased expression on CD4+ T cells might represent an enhanced antiviral function, playing a role in initiating the "functional cure" of chronic HBV infection.

Advances in Multi-Omics Applications in HBV-Associated Hepatocellular Carcinoma

Hepatitis B virus (HBV) specifically infects liver cells, leading to progressive liver cirrhosis and significantly increasing the risk of hepatocellular carcinoma (HCC). The maturity of sequencing technology, improvement in bioinformatics data analysis and progress of omics technologies had improved research efficiency. The occurrence and progression of HCC are affected by multisystem and multilevel pathological changes. With the application of single-omics technologies, including genomics, transcriptomics, metabolomics and proteomics in tissue and body fluid samples, and even the novel development of multi-omics analysis on a single-cell platform, HBV-associated HCC changes can be better analyzed. The review summarizes the application of single omics and combined analysis of multi-omics data in HBV-associated HCC and proposes the importance of multi-omics analysis in the type of HCC, which provide the possibility for the precise diagnosis and therapy of HBV-associated HCC.