HCV genotype-specific correlation with serum markers: higher predictability for genotype 4a

Hepatitis C virus in Iran; transmission routes, growth in 3a genotype distribution, and lack of liver marker relation with genotypes

BACKGROUND

The hepatitis C virus (HCV) outbreak in Iran is increasing. This study investigated the dissemination and transmission routes of HCV genotypes in different regions of Iran. The relationship between serum biochemical markers and viral genotypes was also assessed to find whether liver enzymes level can be considered as the markers for HCV genotypes.

MATERIALS AND METHODS

HCV-infected patients from different provinces of Iran (from August 2017 to March 2019) were enrolled. Nested reverse transcriptase polymerase chain reaction (PCR)-restriction fragment length polymorphism and real-time PCR were used to discover the genotypes. The infection transmission routes in the study population were investigated and recorded. Serum samples with equal viral loud from the patients without other liver disorders were recruited to explore the association between the genotypes and the liver biochemical markers.

RESULTS

One thousand serum samples positive for the HCV genome were recruited. Genotype 3a was the most prevalent in the north, while genotype 1a was dominant at the center. In total, genotype 3a was the dominant genotype closely followed by 1a. Needle sharing by addicts was the most common transmission way of infection in Iran. This way was also the most for genotype 3a dissemination, and genotype 1a was transmitted mostly between family members. No significant association (P > 0.05) was observed between biochemical marker titers and HCV genotypes.

CONCLUSION

A shift in the distribution profile of HCV genotypes, related to the transmission routes, has happened over time. Public awareness of the main routes of HCV transmission can break the cycle of transmission. Liver enzyme values in HCV-infected patients showed no relation with genotypes and only represented hepatocellular dysfunction.

Prediction of HCV load using genotype, liver biomarkers, and clinical symptoms by a mathematical model in patients with HCV infection

Hepatitis C virus (HCV) infection is a major public health problem with about 1.75 million new HCV cases and 71 million chronic HCV infections worldwide. The study aimed to evaluate clinical, serological, molecular, and liver markers to develop a mathematical predictive model for the quantification of the HCV viral load in chronic HCV infected patients. In this cross-sectional study, blood samples were taken from 249 recently diagnosed HCV-infected subjects and were tested for liver condition, viral genotype, and HCV RNA load. Receiver operating characteristics (ROC) curves and multiple linear regression analysis were used to predict the HCV-RNA load. Genotype 3 followed by genotype 1 were the most prevalent genotypes in Mashhad, Northeastern Iran. The maximum levels of viral load were detected in the mixed genotype group, and the lowest levels in the undetectable genotype group. The log of the HCV viral load was significantly associated with thrombocytopenia and higher serum levels of alanine transaminase (ALT). In addition, the log HCV RNA was significantly higher in patients with arthralgia, fatigue, fever, vomiting, or dizziness. Moreover, genotype 3 was significantly associated with icterus. A ROC curve analysis revealed that the best cut-off points for serum levels of aspartate aminotransferase (AST), ALT, and alkaline phosphatase (ALP) were >31, >34, and ≤246 IU/L, respectively. Sensitivity, specificity, and positive predictive values for AST were 87.7%, 84.36%, and 44.6%, for ALT they were 83.51%, 81.11%, and 36%, and for ALP were 72.06%, 42.81%, and 8.3%, respectively. A mathematical regression model was developed that could estimate the HCV-RNA load. Regression model: log viral load = 7.69 - 1.01 × G3 - 0.7 × G1 + 0.002 × ALT - 0.86 × fatigue.

HCV infection causes cirrhosis in human by step-wise regulation of host genes involved in cellular functioning and defense during fibrosis: Identification of bio-markers

Chronic Hepatitis C Viral (HCV) infection is a leading health problem worldwide and resulted in fibrotic scar formation, and finally liver-cirrhosis. Although contemporary therapies can partially reverse this destructive process, the rehabilitation is too slow and unsuitable for all chronic infections. The current study elucidates the mechanism of disease progression from early (F1) to moderate (F2, F3), and to severe fibrosis (F4)/cirrhosis in HCV genotype 3a infected patients to find out new candidates as potential disease progression markers and antiviral therapeutic agents. A total of 550 genes were found differentially regulated in the four fibrosis stages and grouped in 22 classes according to their biological functions. Gene set enrichment (GSEA) and Ingenuity pathway analysis (IPA) were used to identify the regulation of crucial biological functions and pathways involved in HCV progression. HCV differentially regulated the expression of genes involved in apoptosis, cell structure, signal transduction, proliferation, metabolism, cytokine signaling, immune response, cell adhesion and maintenance, and post translational modifications by pathway analysis. There was an increasing trend of proliferative and cell growth related genes and shutting down of immune response as the disease progress mild to moderate to advanced stage cirrhosis. The myriad of changes in gene expression showed more chances of developing liver cancer in patients infected with HCV genotype 3a in a systematic manner. The identified gene set can act as disease markers for prediction, whether the fibrosis lead to cirrhosis and its association with end stage liver disease development.

Correlation Study Between HCV Genotypes Distribution Pattern and Viral Load in a Tertiary Care Hospital in Kolkata, India

BACKGROUND

Hepatitis C virus infection is a leading cause for chronic liver disease. It has wide population specific genotype variability. Genotype knowledge and viral load assessment are equally important for designing therapeutic strategies and as predictors of treatment outcome among hepatitis C (HCV) infected patients.

MATERIALS AND METHODS

Between June 2012 and 2013 an observational study was conducted among 350 chronic hepatitis patients visiting Calcutta National Medical College, Kolkata, India. Among them, 110 anti-HCV antibody positive cases were diagnosed and subjected to viral RNA extraction, viral genotyping and viral load quantification using polymerase chain reaction (PCR) based techniques.

STATISTICAL ANALYSIS

Statistical analysis was done with IBM SPSS Statistics software, version 20. p-value <0.05 was regarded as statically significant.

RESULTS

Among 66 HCV RNA positive cases, genotypes 1a, 3a and 3b were observed among 18 (27%), 44(67%) and 4(6%) cases respectively. Genotype 3a had higher viral load than patients infected with genotypes 1and 3b. However, no statistical significance was observed for viral load among the various HCV RNA genotypes.

CONCLUSION

Genotype 3a accounted for the highest number of cases with positive HCV RNA. However, no statistically significant difference existed for viral load among the various HCV RNA genotypes in this study.

The genetic diversity and evolutionary history of hepatitis C virus in Vietnam

Vietnam has a unique history in association with foreign countries, which may have resulted in multiple introductions of the alien HCV strains to mix with those indigenous ones. In this study, we characterized the HCV sequences in Core-E1 and NS5B regions from 236 Vietnamese individuals. We identified multiple HCV lineages; 6a, 6 e, 6h, 6k, 6l, 6 o, 6p, and two novel variants may represent the indigenous strains; 1a was probably introduced from the US; 1b and 2a possibly originated in East Asia; while 2i, 2j, and 2m were likely brought by French explorers. We inferred the evolutionary history for four major subtypes: 1a, 1b, 6a, and 6 e. The obtained Bayesian Skyline Plots (BSPs) consistently showed the rapid HCV population growth from 1955 to 1963 until 1984 or after, corresponding to the era of the Vietnam War. We also estimated HCV growth rates and reconstructed phylogeographic trees for comparing subtypes 1a, 1b, and HCV-2.

Correlation of viral loads with HCV genotypes: higher levels of virus were revealed among blood donors infected with 6a strains

Background

Both HCV genotypes and viral loads are predictors of therapeutic outcomes among patients treated with α-interferon plus ribavirin; however, such correlation has only been studied for genotypes 1, 2, and 3 but not for genotype 6.

Methodology/Findings

299 voluntary blood donors were recruited who were HCV viremic. Their mean age was 31.8; the male/female ratio was 3.82 (225/59). The viral loads of HCV were measured using the COBAS AmpliPrep/COBAS TaqMan test (CAP/CTM) while HCV genotypes were determined by direct sequencing the partial NS5B region. HCV genotypes 1, 2, 3, and 6 were determined in 48.9%, 8.7%, 12.3%, and 30.1% of the donors, respectively, and the levels of mean viral loads in genotype 1 and 6 significantly higher than that of 2 and 3 (P<0.001). As a whole, the viral loads in male donors were higher than in female (P = 0.006). Moreover, the donors' gender and HCV genotypes are independently correlated with the measured viral loads.

Conclusion

HCV genotype 1 and 6 had significantly higher viral loads than genotype 2 and 3.