Advanced molecular surveillance of hepatitis C virus

Evaluation and Comparison of Serum Vitamin D Levels between Injection Drug Users with and without Chronic Hepatitis C Infection in Hamadan-Iran

Background and objective: Hepatitis C virus (HCV) infection causes disruption in the metabolism of biochemicals, such as vitamin D, and subsequently alters their serum level via the involvement of the liver. The current study aimed at determining the serum level of vitamin D in injection drug users with chronic HCV infection. Methods:The current case-control study was conducted on 46 injection drug users referred to Imam Khomeini Specialty Clinic in Hamadan City, Iran, between 2017 and 2019, when their HCV infection was diagnosed with HCV PCR test, and 46 healthy injection drug users as the control group in order to compare serum vitamin D levels and liver enzymes. Both the case and control groups were matched for age and gender. ELISA technique was used to measure serum vitamin D level. The collected data were analyzed with STATA software based on 95% significance level. Results:In the present study, 43 (93.5%) of all subjects were male and three (6.6%) females. The mean age of subjects in the case and control groups was 41.87 ± 11.97 and 40.66 ± 11.89 years, respectively. The mean serum vitamin D levels in the case and control groups were 21.20 ± 19.84 and 42.42 ± 29.08 ng/L, respectively (P = 0.001). The mean serum vitamin D levels in the injection drug users with mild, moderate, and severe HCV infection was 32.90, 30.34 and 29.74 ng/L, respectively (P = 0.454). The correlation between vitamin D level and AST and ALT enzymes was -0.053 and -0.103, respectively (P >0.05). Conclusion:Serum vitamin D level decreases in addicts with chronic HCV infection. With increasing the severity of HCV infection, the serum level of vitamin D decreases.

An Insight into Hepatitis C Virus: In Search of Promising Drug Targets

Hepatitis C Virus (HCV) is a global health concern, chronically infecting over 70 million people worldwide. HCV is a bloodborne pathogen that primarily affects the liver, and chronic HCV infection can lead to cirrhosis, liver cancer, and liver failure over time. There is an urgent need for more effective approaches to prevent and treat HCV. This review summarizes current knowledge on the virology, transmission, diagnosis, and management of HCV infection. It also provides an in-depth analysis of HCV proteins as promising targets for antiviral drug and vaccine development. Specific HCV proteins discussed as potential drug targets include the NS5B polymerase, NS3/4A protease, entry receptors like CD81, and core proteins. The implications of HCV proteins as diagnostic and prognostic biomarkers are also explored. Current direct-acting antiviral therapies are effective but have cost, genotype specificity, and resistance limitations. This review aims to synthesize essential information on HCV biology and pathogenesis to inform future research on improved preventive, diagnostic, and therapeutic strategies against this global infectious disease threat.

Sensitive detection of hepatitis C virus using a catalytic hairpin assembly coupled with a lateral flow immunoassay test strip

Currently, PCR is the gold standard for the detection of hepatitis C virus (HCV). However, the PCR technique is complicated and time-consuming, which prevents its application and, clinical point-of-care testing (POCT). Herein, we report a POCT method with simplicity, high sensitivity and specificity, which consists of a catalytic hairpin assembly (CHA) signal amplification system coupled with a lateral flow immunochromatographic (LFIA) test strip for the detection of HCV. Two ingeniously designed hairpin probes were hybridized to form the H1-H2 duplex in the presence of the target DNA. The catalytic hairpin assembly which was characterized of isothermal and enzyme-free, was accomplished within 40 min and the reaction was then applied to a LFIA test strip. Only the H1-H2 duplex labeled with both digoxin and biotin could be captured by the test strip, and the fluorescence value was determined. In addition, we evaluated the application potential for the detection of clinical samples. The reported method demonstrated high sensitivity with a detectable minimum concentration at 1 fM and showed a good linear range from 10 nM to 10pM, and high specificity for various mismatched sequences. The results demonstrated that clinically positive samples could be successfully detected. In conclusion, the reported method is simple, rapid, and free of large-scale equipment. POCT is expected to be useful for HCV detection in clinic.

Pooled Prevalence of NS5A Resistance-Associated Substitutions in Chronic HCV Genotype 3 Infection: A Study Based on Deposited Sequences in GenBank

Using direct-acting antiviral agents (DAAs) against hepatitis C virus (HCV) infection results in a high treatment response rate. However, several factors can significantly alter this outcome such as resistance-associated substitutions (RASs) in HCV NS5A gene. This study aimed to evaluate the prevalence of naturally occurring RASs of NS5A in HCV genotype 3 (HCV-3) sequences isolated from individuals with chronic HCV-3 infection. All the registered sequences in the GenBank under "NS5A" AND "Hepacivirus C" query were evaluated and screened, those which followed our inclusion criteria were enrolled in our pooled analysis. The retrieved sequences of included studies were evaluated for substitutions, RASs, and RASs conferring >100 resistance fold change (RASs >100 × ) in NS5A amino acid positions 24, 28, 30, 31, 62, 92, and 93. From 7 enrolled studies, a total of 370 HCV-3a isolates were retrieved and investigated. Forty-eight (13.0%, 95% CI = 9.9-16.8%) isolates harbored NS5A RASs. Moreover, Y93H was the only NS5A RAS >100 × observed in 13 (3.5%, 95% CI = 2.0-5.9%) retrieved sequences. The low frequency of naturally occurring NS5A RASs, especially those with clinical relevance (RASs >100 × ), among individuals with HCV-3 infection and the high rate of treatment response to DAAs suggest not to investigate every individual with HCV-3 infection for NS5A RASs before treatment.

Screening haemodialysis patients for hepatitis C in Vietnam: The inconsistency between common hepatitis C virus serological and virological tests

Selecting the appropriate screening method and interval for the early detection of hepatitis C virus (HCV) infection in low-resourced haemodialysis settings is a challenge. The challenge occurs when patients are classified as HCV-RNA positive but negative to HCV-core antigen (HCV-coreAg), anti-HCV and genotyping tests. We aim to clarify the inconsistency between HCV-RNA, HCV-coreAg, anti-HCV and HCV genotyping tests in haemodialysis patients and determine the reliability of HCV-coreAg as a routine two-monthly screening strategy. Haemodialysis patients were tested every 2 months between 2012 and 2014 at the largest district haemodialysis unit in Ho Chi Minh City, Vietnam, for aminotransferases, anti-HCV antibodies, HCV-coreAg, HCV-RNA and HCV genotype. HCV-coreAg and anti-HCV results were tested against HCV-RNA for sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV). All 201 patients participated in the study. The HCV-coreAg test performed better than the anti-HCV test for sensitivity (100% vs 31%), NPV (100% vs 90%) and accuracy (100% vs 90%). The HCV-coreAg and anti-HCV tests performed no differently for specificity (100% and 98%, respectively) or PPV (100% and 73%, respectively). Kappa values for HCV-coreAg and anti-HCV tests were 1 and 0.39, respectively. Early detection of HCV for the purpose of infection prevention requires a high level of sensitivity and HCV-coreAg performed better in our chronic haemodialysis population as a two-monthly screening method than routine anti-HCV testing. HCV-coreAg test is less labour-intensive with a higher level of accuracy in patients with low viral loads making it cost effective for low-resourced settings. Repeating genotyping may be required in HCV-coreAg positive patients with a low viral load.

HCV adaptation to HIV coinfection

Human immunodeficiency virus (HIV) infection is rising as a leading cause of morbidity and mortality among hepatitis C virus (HCV)-infected patients. Both viruses interact in co-infected hosts, which may affect their intra-host evolution, potentially leading to differing genetic composition of viral populations in co-infected (CIP) and mono-infected (MIP) patients. Here, we investigate genetic differences between intra-host variants of the HCV hypervariable region 1 (HVR1) sampled from CIP and MIP. Nucleotide (nt) sequences of intra-host HCV HVR1 variants (N = 28,622) obtained from CIP (N = 112) and MIP (n = 176) were represented using 148 physical-chemical (PhyChem) indexes of DNA nt dimers. Significant (p < .0001) differences in the means and frequency distributions of 7 PhyChem properties were found between HVR1 variants from both groups. Linear projection analysis of 29 PhyChem features extracted from such PhyChem properties showed that the CIP and MIP HVR1 variants have a distinct distribution in the modeled 2D-space, with only ~1.3% of PhyChem profiles (N = 6782), shared by all HVR1 variants, being found in both groups. Probabilistic neural network (PNN) and naïve Bayesian (NB) classifiers trained on the PhyChem features accurately classified HVR1 variants by the group in cross-validation experiments (AUROC ≥ 0.96). Similarly, both models showed a high accuracy (AUROC ≥ 0.95) when evaluated on a test dataset of HVR1 sequences obtained from 10 patients, data from whom were not used for model building. Both models performed at the expected lower accuracy on randomly labeled datasets in cross-validation experiments (AUROC = 0.50). The random-label trained PNN showed a similar drop in accuracy on the test dataset (AUROC = 0.48), indicating that the detected associations were unlikely due to random correlations. Marked differences in genetic composition of HCV HVR1 variants sampled from CIP and MIP suggest differing intra-host HCV evolution in the presence of HIV infection. PhyChem features identified here may be used for detection of HIV infection from intra-host HCV variants alone in co-infected patients, thus facilitating monitoring for HIV introduction to high-risk populations with high HCV prevalence.

Separation and assembly of deep sequencing data into discrete sub-population genomes

Sequence heterogeneity is a common characteristic of RNA viruses that is often referred to as sub-populations or quasispecies. Traditional techniques used for assembly of short sequence reads produced by deep sequencing, such as de-novo assemblers, ignore the underlying diversity. Here, we introduce a novel algorithm that simultaneously assembles discrete sequences of multiple genomes present in populations. Using in silico data we were able to detect populations at as low as 0.1% frequency with complete global genome reconstruction and in a single sample detected 16 resolved sequences with no mismatches. We also applied the algorithm to high throughput sequencing data obtained for viruses present in sewage samples and successfully detected multiple sub-populations and recombination events in these diverse mixtures. High sensitivity of the algorithm also enables genomic analysis of heterogeneous pathogen genomes from patient samples and accurate detection of intra-host diversity, enabling not just basic research in personalized medicine but also accurate diagnostics and monitoring drug therapies, which are critical in clinical and regulatory decision-making process.

Clinical evaluation of a newly developed automated massively parallel sequencing assay for hepatitis C virus genotyping and detection of resistance-association variants. Comparison with a line probe assay

Hepatitis C virus (HCV) infection is a leading cause of chronic liver disease, cirrhosis and hepatocellular carcinoma. Recently, HCV was classified into 6 major genotypes (GTs) and 67 subtypes (STs). Efficient genotyping has become an essential tool for prognosis and indicating suitable treatment, prior to starting therapy in all HCV-infected individuals. The widely used genotyping assays have limitation with regard to genotype accuracy. This study was a comparative evaluation of exact HCV genotyping in a newly developed automated-massively parallel sequencing (MPS) system, versus the established Line probe assay 2.0 (LiPA), substantiated by Sanger sequencing, using 120 previously identified-HCV RNA positive specimens. LiPA gave identical genotypes in the majority of samples tested with MPS. However, as much as 25% of LiPA did not identify subtypes, whereas MPS did, and 0.83% of results were incompatible. Interestingly, only MPS could identify mixed infections in the remaining cases (1.67%). In addition, MPS could detect Resistance-Associated Variants (RAVs) simultaneously in GT1 in 56.82% of the specimens, which were known to affect drug resistance in the HCV NS3/NS4A and NS5A genomic regions. MPS can thus be deemed beneficial for guiding decisions on HCV therapy and saving costs in the long term when compared to traditional methods.

Multiregion deep sequencing of hepatitis C virus: An improved approach for genetic relatedness studies

Hepatitis C virus (HCV) is a major public health problem that affects more than 180 million people worldwide. Identification of HCV transmission networks is of critical importance for disease control. HCV related cases are often difficult to identify due to the characteristic long incubation period and lack of symptoms during the acute phase of the disease, making it challenging to link related cases to a common source of infection. Additionally, HCV transmission chains are difficult to trace back since viral variants from epidemiologically linked cases are genetically related but rarely identical. Genetic relatedness studies primarily rely on information obtained from the rapidly evolving HCV hypervariable region 1 (HVR1). However, in some instances, the rapid divergence of this region can lead to loss of genetic links between related isolates, which represents an important challenge for outbreak investigations and genetic relatedness studies. Sequencing of multiple and longer sub-genomic regions has been proposed as an alternative to overcome the limitations imposed by the rapid molecular evolution of the HCV HVR1. Additionally, conventional molecular approaches required to characterize the HCV intra-host genetic variation are laborious, time-consuming, and expensive while providing limited information about the composition of the viral population. Next generation sequencing (NGS) approaches enormously facilitate the characterization of the HCV intra-host population by detecting rare variants at much lower frequencies. Thus, NGS approaches using multiple sub-genomic regions should improve the characterization of the HCV intra-host population. Here, we explore the usefulness of multiregion sequencing using a NGS platform for genetic relatedness studies among HCV cases.