Serum miR-192-5p levels predict the efficacy of pegylated interferon therapy for chronic hepatitis B

An In-Depth Approach to the Associations between MicroRNAs and Viral Load in Patients with Chronic Hepatitis B-A Systematic Review and Meta-Analysis

Scientists study the molecular activities of the hepatitis B virus (HBV). However, in vivo experiments are scarce. Some microRNAs are HBV-related, but their exact mechanisms are unknown. Our study provides an up-to-date view of the associations between microRNAs and HBV-DNA levels in chronically infected individuals. We conducted this large-scale research on five databases according to PRISMA guidance. Joanna Briggs Institute tools and Newcastle Ottawa Quality Assessment scores helped with quality evaluations. R 4.2.2 performed statistical computations for the meta-analysis. DIANA-microT 2023 and g:Profiler enriched the predictions of liver genes associated with miR-122 and miR-192-5p. From the 1313 records, we eliminated those irrelevant to our theme, non-article methodologies, non-English entries, and duplicates. We assessed associations between microRNAs and HBV-DNA levels. Overall, the pooled correlations favoured the general idea of the connection between non-coding molecules and viremia levels. MiR-122 and miR-192-5p were the most researched microRNAs, significantly associated with HBV-DNA levels. The connections between miR-122, miR-192-5p, let-7, miR-215, miR-320, and viral loads need further in vivo assessment. To conclude, this study evaluates systematically, for the first time, the correlations between non-coding molecules and viremia levels in patients. Our meta-analysis emphasizes potentially important pathways toward new inhibitors of the viral replication cycle.

Hepatitis B Virus and microRNAs: A Bioinformatics Approach

In recent decades, microRNAs (miRNAs) have emerged as key regulators of gene expression, and the identification of viral miRNAs (v-miRNAs) within some viruses, including hepatitis B virus (HBV), has attracted significant attention. HBV infections often progress to chronic states (CHB) and may induce fibrosis/cirrhosis and hepatocellular carcinoma (HCC). The presence of HBV can dysregulate host miRNA expression, influencing several biological pathways, such as apoptosis, innate and immune response, viral replication, and pathogenesis. Consequently, miRNAs are considered a promising biomarker for diagnostic, prognostic, and treatment response. The dynamics of miRNAs during HBV infection are multifaceted, influenced by host variability and miRNA interactions. Given the ability of miRNAs to target multiple messenger RNA (mRNA), understanding the viral-host (human) interplay is complex but essential to develop novel clinical applications. Therefore, bioinformatics can help to analyze, identify, and interpret a vast amount of miRNA data. This review explores the bioinformatics tools available for viral and host miRNA research. Moreover, we introduce a brief overview focusing on the role of miRNAs during HBV infection. In this way, this review aims to help the selection of the most appropriate bioinformatics tools based on requirements and research goals.

The Connection between MiR-122 and Lymphocytes in Patients Receiving Treatment for Chronic Hepatitis B Virus Infection

New molecular predictors for the response to treatment in HBV (hepatitis B virus) infection are assessed. Among them is miR-122. Our article searches the connection between miR-122 and the counts of lymphocytes in chronic HBV patients receiving treatment. We included the sera of 38 Romanian subjects with chronic HBV infection (20 receiving treatment and 18 not receiving treatment) and 5 healthy controls. The expression of miR-122 was determined using RT-PCR (real-time PCR) and a 2-ΔΔCT method. Two systematic analyses were also performed on databases (PUBMED, Web of Science, and Science Direct), eliminating systematic reviews, editorials, letters to editors, meta-analyses, reviews, conference proceedings, or pre-print manuscripts. We included human-based articles following the PRISMA criteria and the Newcastle Ottawa Assessment Scale for Case-Control and Cohort studies. R 4.2.2 was used for statistics, and MIENTURNET and STRING were used for the bioinformatic analysis. Our results showed a link between the variations in the expression of miR-122 and the counts of lymphocytes in HBV Romanian patients receiving therapy. Treatment influenced miR-122 and the lymphocyte numbers. This is the first study with these results, and it may lead to a new perspective on the inter-relationships between microRNAs and therapy in HBV patients.

CXCL13 variant predicts pegylated-interferon α treatment response in HBeAg-positive chronic hepatitis B patients

As a key immune cytokine, C-X-C motif chemokine ligand 13 (CXCL13) has been reported to play critical roles in immune control of hepatitis B virus (HBV) infection. We aimed to screen single-nucleotide polymorphisms (SNPs) of CXCL13 for predicting response to pegylated interferon-alpha (PegIFNα) therapy of chronic hepatitis B (CHB) patients. Two independent cohorts with a total of 945 (Cohort 1, n = 238; Cohort 2, n = 707) hepatitis B e antigen (HBeAg)-positive CHB patients treated with PegIFNα were enrolled in this retrospective cohort study. Eight candidate SNPs were selected through gene-wide SNP mining within or flanking CXCL13. A polygenic score (PGS) was utilized to assess the cumulative effects of multiple SNPs. The associations of candidate SNPs and PGS with combined response (CR, defined as the combination of HBeAg seroconversion and HBV DNA level <3.3log₁₀ IU/mL) and hepatitis B surface antigen (HBsAg) level were evaluated. Among the eight candidate SNPs, rs76084459 which is located at upstream of CXCL13 was significantly associated with both CR (p = 0.002) and HBsAg level (p = 0.015). A PGS integrating CXCL13_rs76084459 and five other SNPs, which were previously identified as predictors of PegIFNα treatment response, was further strongly correlated with CR (p = 1.759 × 10^-10 ) and HBsAg level (p = 0.004). This study demonstrated that CXCL13_rs76084459 can predict response to PegIFNα treatment of HBeAg-positive CHB patients. A PGS composed of six SNPs including CXCL13_rs76084459 predicts PegIFNα treatment response better.

Improving the Diagnostic Potential of Extracellular miRNAs Coupled to Multiomics Data by Exploiting the Power of Artificial Intelligence

In recent years, the clinical use of extracellular miRNAs as potential biomarkers of disease has increasingly emerged as a new and powerful tool. Serum, urine, saliva and stool contain miRNAs that can exert regulatory effects not only in surrounding epithelial cells but can also modulate bacterial gene expression, thus acting as a “master regulator” of many biological processes. We think that in order to have a holistic picture of the health status of an individual, we have to consider comprehensively many “omics” data, such as miRNAs profiling form different parts of the body and their interactions with cells and bacteria. Moreover, Artificial Intelligence (AI) and Machine Learning (ML) algorithms coupled to other multiomics data (i.e., big data) could help researchers to classify better the patient’s molecular characteristics and drive clinicians to identify personalized therapeutic strategies. Here, we highlight how the integration of “multiomic” data (i.e., miRNAs profiling and microbiota signature) with other omics (i.e., metabolomics, exposomics) analyzed by AI algorithms could improve the diagnostic and prognostic potential of specific biomarkers of disease.

Management and Treatment of Patients with Chronic Hepatitis B: Towards Personalized Medicine

The currently available antiviral treatments (Peg-Interferon-α and Nucleos(t)ide Analogues, NA) for chronic hepatitis B (CHB) achieve a functional cure (serum HBsAg and HDV-DNA clearance) of HBV infection in a limited number of patients. Nevertheless, the continuous pharmacological suppression of viral replication by NA halts liver disease progression lowering the risk of HCC development and improving the survival. In the near future, to fully exploit the potential of old and new drugs for HBV treatment a personalized approach to the patients will be required according to an accurate definition of their virologic, immunologic and clinical profile.