Genetic variability in hepatitis C virus and its role in antiviral treatment response

Factors Correlating to the Development of Hepatitis C Virus Infection among Drug Users-Findings from a Systematic Review and Meta-Analysis

Hepatitis C remains a significant public health threat. However, the main routes of transmission have changed since the early 1990s. Currently, drug use is the main source of hepatitis C virus (HCV) infection, and some measures have been successively implemented and additional studies have been published. However, the factors correlating with HCV infection failed to clearly define. Our study pooled the odds ratios (ORs) with 95% confidence intervals (CIs) and analyzed sensitivity by searching data in the PubMed, Elsevier, Springer, Wiley, and EBSCO databases. Publication bias was determined by Egger's test. In our meta-analysis, HCV-infected and non-HCV-infected patients from 49 studies were analyzed. The pooled ORs with 95% CIs for study factors were as follows: Injecting drug use 10.11 (8.54, 11.97); sharing needles and syringes 2.24 (1.78, 2.83); duration of drug use >5 years 2.39 (1.54, 3.71); unemployment 1.50 (1.22, 1.85); commercial sexual behavior 1.00 (0.73, 1.38); married or cohabiting with a regular partner 0.88 (0.79, 0.98), and sexual behavior without a condom 1.72 (1.07, 2.78). This study found that drug users with histories of injecting drug use, sharing needles and syringes, drug use duration of >5 years, and unemployment, were at increased risk of HCV infection. Our findings indicate that sterile needles and syringes should be made available to ensure safe injection. In view of that, methadone maintenance treatment can reduce or put an end to risky drug-use behaviors, and should be scaled up further, thereby reducing HCV infection.

Discovery of velpatasvir (GS-5816): A potent pan-genotypic HCV NS5A inhibitor in the single-tablet regimens Vosevi® and Epclusa®

Direct-acting antiviral inhibitors have revolutionized the treatment of hepatitis C virus (HCV) infected patients. Herein is described the discovery of velpatasvir (VEL, GS-5816), a potent pan-genotypic HCV NS5A inhibitor that is a component of the only approved pan-genotypic single-tablet regimens (STRs) for the cure of HCV infection. VEL combined with sofosbuvir (SOF) is Epclusa^®, an STR with 98% cure-rates for genotype 1-6 HCV infected patients. Addition of the pan-genotypic HCV NS3/4A protease inhibitor voxilaprevir to SOF/VEL is the STR Vosevi^®, which affords 97% cure-rates for genotype 1-6 HCV patients who have previously failed another treatment regimen.

Analysis of mutations in the core and NS5A genes of hepatitis C virus in non-responder and relapser patients after treatment with Peg-IFN-α and ribavirin

Mutations in several regions of HCV genome are shown to correlate with response to interferon (IFN) treatment. Persistence of HCV infection and poor susceptibility to treatment might be contributed by mutations arising within HCV genome which enable the virus to escape from host immune response/IFN treatment. This study investigated mutations in core and NS5A genes of HCV from non-responder and relapser patients after treatment with Peg-IFN-α and ribavirin. Viral RNA was extracted from patient sera and core and NS5A genes were amplified by RT-PCR. Nucleotide sequences of the core and NS5A genes were determined by direct sequencing, and converted to amino acid sequences. Nucleotide and amino acid sequences in the core region, ISDR, PKRBD, and V3 regions within NS5A after treatment were highly conserved when comparing to their corresponding sequences obtained before treatment. Interestingly, when comparing the virus from relapsers to those from non-responders, the number of mutations after treatment in N-terminal region of NS5A of virus from relapsers was significantly higher than those from non-responders (P < 0.05). Amino acid mutations at the N-terminus of NS5A of the virus in relapsers might help the virus to survive and somehow relapse after the cessation of the treatment.

Hepatitis C virus genetic variability and evolution

Hepatitis C virus (HCV) has infected over 170 million people worldwide and creates a huge disease burden due to chronic, progressive liver disease. HCV is a single-stranded, positive sense, RNA virus, member of the Flaviviridae family. The high error rate of RNA-dependent RNA polymerase and the pressure exerted by the host immune system, has driven the evolution of HCV into 7 different genotypes and more than 67 subtypes. HCV evolves by means of different mechanisms of genetic variation. On the one hand, its high mutation rates generate the production of a large number of different but closely related viral variants during infection, usually referred to as a quasispecies. The great quasispecies variability of HCV has also therapeutic implications since the continuous generation and selection of resistant or fitter variants within the quasispecies spectrum might allow viruses to escape control by antiviral drugs. On the other hand HCV exploits recombination to ensure its survival. This enormous viral diversity together with some host factors has made it difficult to control viral dispersal. Current treatment options involve pegylated interferon-α and ribavirin as dual therapy or in combination with a direct-acting antiviral drug, depending on the country. Despite all the efforts put into antiviral therapy studies, eradication of the virus or the development of a preventive vaccine has been unsuccessful so far. This review focuses on current available data reported to date on the genetic mechanisms driving the molecular evolution of HCV populations and its relation with the antiviral therapies designed to control HCV infection.

A comparison of 454 sequencing and clonal sequencing for the characterization of hepatitis C virus NS3 variants

We compared 454 amplicon sequencing with clonal sequencing for the characterization of intra-host hepatitis C virus (HCV) NS3 variants. Clonal and 454 sequences were obtained from 12 patients enrolled in a clinical phase I study for telaprevir, an NS3-4a protease inhibitor. Thirty-nine datasets were used to compare the consensus sequence, average pairwise distance, normalized Shannon entropy, phylogenetic tree topology and the number and frequency of variants derived from both sequencing techniques. In general, a good concordance was observed between both techniques for the majority of datasets. Discordant results were observed for 5 out of 39 clonal and 454 datasets, which could be attributed to primer-related selective amplification used for clonal sequencing. Both 454 and clonal datasets consisted of a few major variants and a large number of low-frequency variants. Telaprevir resistance-associated variants were observed in low frequencies and were detected more often by 454. We conclude that performance of 454 and clonal sequencing is comparable for the characterization of intra-host virus populations. Not surprisingly, 454 is superior for the detection of low frequency resistance-associated variants. However, despite the greater coverage, 454 failed to detect some low frequency variants detected by clonal sequencing.

A novel approach to identify candidate prognostic factors for hepatitis C treatment response integrating clinical and viral genetic data

The combined therapy of pegylated interferon (IFN) plus ribavirin (RBV) has been for a long time the standard treatment for patients infected with hepatitis C virus (HCV). In the case of genotype 1, only 38%–48% of patients have a positive response to the combined treatment. In previous studies, viral genetic information has been occasionally included as a predictor. Here, we consider viral genetic variation in addition to 11 clinical and 19 viral populations and evolutionary parameters to identify candidate baseline prognostic factors that could be involved in the treatment outcome. We obtained potential prognostic models for HCV subtypes la and lb in combination as well as separately. We also found that viral genetic information is relevant for the combined treatment assessment of patients, as the potential prognostic model of joint subtypes includes 9 viral-related variables out of 11. Our proposed methodology fully characterizes viral genetic information and finds a combination of positions that modulate inter-patient variability.

Deep sequencing of hepatitis C virus hypervariable region 1 reveals no correlation between genetic heterogeneity and antiviral treatment outcome

Background

Hypervariable region 1 (HVR1) contained within envelope protein 2 (E2) gene is the most variable part of HCV genome and its translation product is a major target for the host immune response. Variability within HVR1 may facilitate evasion of the immune response and could affect treatment outcome. The aim of the study was to analyze the impact of HVR1 heterogeneity employing sensitive ultra-deep sequencing, on the outcome of PEG-IFN-α (pegylated interferon α) and ribavirin treatment.

Methods

HVR1 sequences were amplified from pretreatment serum samples of 25 patients infected with genotype 1b HCV (12 responders and 13 non-responders) and were subjected to pyrosequencing (GS Junior, 454/Roche). Reads were corrected for sequencing error using ShoRAH software, while population reconstruction was done using three different minimal variant frequency cut-offs of 1%, 2% and 5%. Statistical analysis was done using Mann–Whitney and Fisher’s exact tests.

Results

Complexity, Shannon entropy, nucleotide diversity per site, genetic distance and the number of genetic substitutions were not significantly different between responders and non-responders, when analyzing viral populations at any of the three frequencies (≥1%, ≥2% and ≥5%). When clonal sample was used to determine pyrosequencing error, 4% of reads were found to be incorrect and the most abundant variant was present at a frequency of 1.48%. Use of ShoRAH reduced the sequencing error to 1%, with the most abundant erroneous variant present at frequency of 0.5%.

Conclusions

While deep sequencing revealed complex genetic heterogeneity of HVR1 in chronic hepatitis C patients, there was no correlation between treatment outcome and any of the analyzed quasispecies parameters.

Variability of hepatitis C virus hypervariable region 1 (HVR-1) during the early phase of pegylated interferon and ribavirin therapy

PURPOSE

Genetic variability of hepatitis C virus (HCV) is considered to be an important factor defining viral pathogenesis, persistence and resistance to treatment. The aim of the present study was to characterize HCV genetic heterogeneity within a hypervariable region 1 (HVR-1) before and during the early period of pegylated interferon alfa (PEG-IFN-α) and ribavirin treatment in correlation with treatment outcome.

MATERIAL AND METHODS

The study involved 24 patients treated with PEG-IFN-α and ribavirin whose sera were collected before (baseline) and at 7, 14, 21 28 and 56 day of treatment. HCV HVR-1 region was amplified by nested RT- PCR and subjected to SSCP (single strand conformational polymorphism) analysis. SSCP changes of HCV HVR-1 over time in each patient were compared to treatment outcome results.

RESULTS

In 2/11 (18%) SVR+ and 8/13 (62%) SVR- treated patients, HVR-1 genetic changes manifested by new SSCP bands (new genetic variants) and were significantly more frequent in nonresponders (P <0.05).

CONCLUSIONS

Our results indicate that HCV HVR-1 variability during the early phase of PEG-IFN-α and ribavirin therapy may be predictive of treatment outcome.

Relevance of baseline viral genetic heterogeneity and host factors for treatment outcome prediction in hepatitis C virus 1b-infected patients

BACKGROUND

Only about 50% of patients chronically infected with HCV genotype 1 (HCV-1) respond to treatment with pegylated interferon-alfa and ribavirin (dual therapy), and protease inhibitors have to be administered together with these drugs increasing costs and side-effects. We aimed to develop a predictive model of treatment response based on a combination of baseline clinical and viral parameters.

METHODOLOGY

Seventy-four patients chronically infected with HCV-1b and treated with dual therapy were studied (53 retrospectively -training group-, and 21 prospectively -validation group-). Host and viral-related factors (viral load, and genetic variability in the E1-E2, core and Interferon Sensitivity Determining Region) were assessed. Multivariate discriminant analysis and decision tree analysis were used to develop predictive models on the training group, which were then validated in the validation group.

PRINCIPAL FINDINGS

A multivariate discriminant predictive model was generated including the following variables in decreasing order of significance: the number of viral variants in the E1-E2 region, an amino acid substitution pattern in the viral core region, the IL28B polymorphism, serum GGT and ALT levels, and viral load. Using this model treatment outcome was accurately predicted in the training group (AUROC = 0.9444; 96.3% specificity, 94.7% PPV, 75% sensitivity, 81% NPV), and the accuracy remained high in the validation group (AUROC = 0.8148, 88.9% specificity, 90.0% PPV, 75.0% sensitivity, 72.7% NPV). A second model was obtained by a decision tree analysis and showed a similarly high accuracy in the training group but a worse reproducibility in the validation group (AUROC = 0.9072 vs. 0.7361, respectively).

CONCLUSIONS AND SIGNIFICANCE

The baseline predictive models obtained including both host and viral variables had a high positive predictive value in our population of Spanish HCV-1b treatment naïve patients. Accurately identifying those patients that would respond to the dual therapy could help reducing implementation costs and additional side effects of new treatment regimens.

Risk factors for infection with different hepatitis C virus genotypes in southern Brazil

Objectives. To investigate the proportion of different genotypes in countryside microregions in southern Brazil, and their association with risk factors. Methods. Cross-sectional study including a convenience sample of patients who tested positive for HCV-RNA and were referred to a regional health center for genotyping, from December 2003 to January 2008. Data were obtained through the National Disease Surveillance Data System, from laboratory registers and from patient charts. Identification of genotypes was carried out using the Restriction Fragment Length Polymorphism “in house” technique. Independent associations with genotypes were evaluated in multinomial logistic regression and prevalence rates of genotypes were estimated with modified Poisson regression. Results. The sample consisted of 441 individuals, 41.1 ± 12.0 years old, 56.5% men. Genotype 1 was observed in 41.5% (95% CI 37.9–48.1) of patients, genotype 2 in 19.3% (95% CI 15.0–23.6), and genotype 3 in 39.2% (95% CI 35.6–43.0). HCV genotype was significantly associated with gender and age. Dental procedures were associated with higher proportion of genotype 2 independently of age, education, and patient treatment center. Conclusions. The hepatitis C virus genotype 1 was the most frequent. Genotype 2 was associated with female gender, age, and dental procedure exposition.

[Current options for predicting therapeutic response in chronically infected patients with hepatitis C virus genotype 1]

Only about 50% of patients chronically infected with hepatitis C virus genotype 1 achieve a successful response to standard treatment with pegylated interferon-alfa and ribavirin. Moreover, the recently approved protease inhibitors will have to be administered together with these drugs. Consequently, predicting response to standard treatment, ideally before starting it, remains an important challenge. Although several baseline predictors of treatment failure have been described, including clinical and virological factors, none of them is able to provide reliable predictions at the individual level. In addition, the development of multivariate models combining several predictive factors has not yet yielded predictions with the requisite reliability for use in clinical practice. Therefore, further research is needed to improve predictive models and to describe new factors that would enable us to predict treatment outcome with greater reliability and reproducibility. The development of candidate selection algorithms that help clinicians to identify which patients could benefit from the new therapies on the basis of their chances of responding to standard therapy is of major interest for both patient well-being and healthcare expense. This review attempts to provide a view of the current options for predicting the response to pegylated interferon-alfa plus ribavirin therapy in patients chronically infected with hepatitis C virus genotype 1.

Evidence for separation of HCV subtype 1a into two distinct clades

The nucleotide sequence diversity present among hepatitis C virus (HCV) isolates allows rapid adjustment to exterior forces including host immunity and drug therapy. This viral response reflects a combination of a high rate of replication together with an error-prone RNA-dependent RNA polymerase, providing for the selection and proliferation of the viruses with the highest fitness. We examined HCV subtype 1a whole-genome sequences to identify positions contributing to genotypic and phenotypic diversity. Phylogenetic tree reconstructions showed two distinct clades existing within the 1a subtype with each clade having a star-like tree topology and lacking definite correlation between time or place of isolation and phylogeny. Identification of significant phylogenetically informative sites at the nucleotide level revealed positions not only contributing to clade differentiation, but which are located at or proximal to codons associated with resistance to protease inhibitors (NS3 Q41) or polymerase inhibitors (NS5B S368). Synonymous/nonsynonymous substitution mutation analyses revealed that the majority of nucleotide mutations yielded synonymous amino acids, indicating the presence of purifying selection pressure across the polyprotein with pockets of positive selection also being detected. Despite evidence for divergence at several loci, certain 1a characteristics were preserved including the length of the alternative reading frame/F protein (ARF/F) gene, and a subtype 1a-specific phosphorylation site in NS5A (S349). Our analysis suggests that there may be strain-specific differences in the development of antiviral resistance to viruses infecting patients who are dependent on the genetic variation separating these two clades.

Coevolution of the hepatitis C virus polyprotein sites in patients on combined pegylated interferon and ribavirin therapy

Genotype-specific sensitivity of the hepatitis C virus (HCV) to interferon-ribavirin (IFN-RBV) combination therapy and reduced HCV response to IFN-RBV as infection progresses from acute to chronic infection suggest that HCV genetic factors and intrahost HCV evolution play important roles in therapy outcomes. HCV polyprotein sequences (n = 40) from 10 patients with unsustainable response (UR) (breakthrough and relapse) and 10 patients with no response (NR) following therapy were identified through the Virahep-C study. Bayesian networks (BNs) were constructed to relate interrelationships among HCV polymorphic sites to UR/NR outcomes. All models showed an extensive interdependence of HCV sites and strong connections (P ≤ 0.003) to therapy response. Although all HCV proteins contributed to the networks, the topological properties of sites differed among proteins. E2 and NS5A together contributed ∼40% of all sites and ∼62% of all links to the polyprotein BN. The NS5A BN and E2 BN predicted UR/NR outcomes with 85% and 97.5% accuracy, respectively, in 10-fold cross-validation experiments. The NS5A model constructed using physicochemical properties of only five sites was shown to predict the UR/NR outcomes with 83.3% accuracy for 6 UR and 12 NR cases of the HALT-C study. Thus, HCV adaptation to IFN-RBV is a complex trait encoded in the interrelationships among many sites along the entire HCV polyprotein. E2 and NS5A generate broad epistatic connectivity across the HCV polyprotein and essentially shape intrahost HCV evolution toward the IFN-RBV resistance. Both proteins can be used to accurately predict the outcomes of IFN-RBV therapy.

Reappraisal of the importance of mutations in the NS5A-PKR-binding domain of hepatitis C-1b virus in the era of optimally individualized therapy

Past studies have reported that mutations in the protein kinase R-binding domain (PKRBD) sequences of hepatitis C virus (HCV) NS5A proteins are correlated with response to fixed-duration interferon (IFN)-based therapy in patients infected with HCV-1b. In this study, we investigated whether the substitutions in PKRBD, including the IFN sensitivity-determining region (ISDR) and 26 additional downstream amino acids from ISDR, will have effects upon patients infected with chronic HCV-1b in the era of individualized therapy with peginterferon and ribavirin. Thirty-seven patients were treated with optimally tailored therapy guided by baseline viral load combined with rapid and early virological responses while 23 patients were treated without guidance and/or assigned suboptimal treatment duration. The amino acid sequences of the PKRBD were determined by PCR and sequencing. The overall sustained virological response (SVR) rate of patients who received optimally individualized therapy was 78.4%, which was better than the SVR rate of patients who received suboptimal therapy (47.8%, P = 0.015). Multivariate analysis showed that optimally individualized therapy (P = 0.019) and 80/80/80 adherence (P = 0.006) were independent favourable predictors of SVR in the entire cohort. Further sub-analysis of the predictive factors of SVR in patients treated with optimally individualized therapy showed that mutations in the 26-amino acid downstream from the ISDR (P = 0.024) were the only independent predictor of SVR. We concluded that mutations in 26-amino acid downstream portion from the ISDR remained a prognosticator of SVR in the era of optimally tailored therapy.

Baseline prediction of combination therapy outcome in hepatitis C virus 1b infected patients by discriminant analysis using viral and host factors

Background

Current treatment of chronic hepatitis C virus (HCV) infection has limited efficacy −especially among genotype 1 infected patients−, is costly, and involves severe side effects. Thus, predicting non-response is of major interest for both patient wellbeing and health care expense. At present, treatment cannot be individualized on the basis of any baseline predictor of response. We aimed to identify pre-treatment clinical and virological parameters associated with treatment failure, as well as to assess whether therapy outcome could be predicted at baseline.

Methodology

Forty-three HCV subtype 1b (HCV-1b) chronically infected patients treated with pegylated-interferon alpha plus ribavirin were retrospectively studied (21 responders and 22 non-responders). Host (gender, age, weight, transaminase levels, fibrosis stage, and source of infection) and viral-related factors (viral load, and genetic variability in the E1–E2 and Core regions) were assessed. Logistic regression and discriminant analyses were used to develop predictive models. A “leave-one-out” cross-validation method was used to assess the reliability of the discriminant models.

Principal Findings

Lower alanine transaminase levels (ALT, p = 0.009), a higher number of quasispecies variants in the E1–E2 region (number of haplotypes, nHap_E1–E2) (p = 0.003), and the absence of both amino acid arginine at position 70 and leucine at position 91 in the Core region (p = 0.039) were significantly associated with treatment failure. Therapy outcome was most accurately predicted by discriminant analysis (90.5% sensitivity and 95.5% specificity, 85.7% sensitivity and 81.8% specificity after cross-validation); the most significant variables included in the predictive model were the Core amino acid pattern, the nHap_E1–E2, and gamma-glutamyl transferase and ALT levels.

Conclusions and Significance

Discriminant analysis has been shown as a useful tool to predict treatment outcome using baseline HCV genetic variability and host characteristics. The discriminant models obtained in this study led to accurate predictions in our population of Spanish HCV-1b treatment naïve patients.

Potential treatment options and future research to increase hepatitis C virus treatment response rate

Hepatitis C virus (HCV) is a liver-tropic blood-borne pathogen that affects more than 170 million people worldwide. Although acute infections are usually asymptomatic, up to 90% of HCV infections persist with the possibility of long-term consequences such as liver fibrosis, cirrhosis, steatosis, insulin resistance, or hepatocellular carcinoma. As such, HCV-associated liver disease is a major public health concern. Although the currently available standard of care therapy of pegylated interferon α plus ribavirin successfully treats infection in a subset of patients, the development of more effective, less toxic HCV antivirals is a health care imperative. This review not only discusses the limitations of the current HCV standard of care but also evaluates upcoming HCV treatment options and how current research elucidating the viral life cycle is facilitating the development of HCV-specific therapeutics that promise to greatly improve treatment response rates both before and after liver transplantation.

Clinical relevance of genetic heterogeneity in HCV

Infection by HCV affects an estimated 170 million people worldwide and it represents one of the major causes of liver transplantation and a heavy burden to healthcare systems. As with many other RNA viruses, HCV is characterized by very high levels of genetic variation, which have been associated to differences in disease progression and efficiency of antiviral treatment. Studies show many contradictory results and little consensus on such associations. Nevertheless, some general guidelines translating research results to clinical practice have been postulated. Here, we review the main research results obtained on HCV variation so far and explore the reasons for their lack of congruence under a population genetics framework. Understanding the factors responsible for the variable dynamics of HCV diversity in human populations and variation within infected individuals is even more necessary in face of the soon-to-arrive new HCV therapies.

High diversity of hepatitis C viral quasispecies is associated with early virological response in patients undergoing antiviral therapy

Differential response patterns to optimal antiviral therapy, peginterferon alpha plus ribavirin, are well documented in patients with chronic hepatitis C virus (HCV) infection. Among many factors that may affect therapeutic efficiency, HCV quasispecies (QS) characteristics have been a major focus of previous studies, yielding conflicting results. To obtain a comprehensive understanding of the role of HCV QS in antiviral therapy, we performed the largest-ever HCV QS analysis in 153 patients infected with HCV genotype 1 strains. A total of 4,314 viral clones spanning hypervarible region 1 were produced from these patients during the first 12 weeks of therapy, followed by detailed genetic analyses. Our data show an exponential distribution pattern of intrapatient QS diversity in this study population in which most patients (63%) had small QS diversity with genetic distance (d) less than 0.2. The group of patients with genetic distance located in the decay region (d>0.53) had a significantly higher early virologic response (EVR) rate (89.5%), which contributed substantially to the overall association between EVR and increased baseline QS diversity. In addition, EVR was linked to a clustered evolutionary pattern in terms of QS dynamic changes.

CONCLUSION

EVR is associated with elevated HCV QS diversity and complexity, especially in patients with significantly higher HCV genetic heterogeneity.

Pegylated interferon and ribavirin promote early evolution of nonstructural 5A protein in individuals with hepatitis C who demonstrate a response to treatment

BACKGROUND

Hepatitis C virus (HCV) quasispecies diversity is more likely to affect early viral decline during treatment of hepatitis C than is having human immunodeficiency virus (HIV) infection. We evaluated the influence of HCV therapy on changes in the nonstructural 5A (NS5A) protein.

METHODS

Fifteen patients with HCV genotype 1 infection with or without HIV infection were recruited for the present study, and the decrease in the HCV RNA level was measured at early time points. The evolution of HCV NS5A quasispecies within the first week was analyzed by comparing the clones observed at later times in the study with the baseline consensus sequence of individual patients. The response to therapy was defined as an early response (ER; ie, an HCV RNA level <615 IU/mL at week 4) or a slow response (SR; ie, a detectable HCV RNA level at week 4).

RESULTS

HIV infection did not affect early viral kinetics. At baseline, lower diversity was seen in NS5A and in the amino and carboxyl termini of patients with an ER, compared with those with an SR. Rapid evolution of the NS5A genetic region occurred in patients with an ER (P = .01) but not in those with an SR (P = .73). The evolution was the result of an increase in the number of amino acid substitutions in the carboxyl region (P = .02) in patients with an ER.

CONCLUSIONS

Selective pressure appears to result in more-marked changes in individuals with an ER than in those with an SR. The carboxyl terminus was subject to the most change and may be an important determinant of phenotypic resistance to interferon-based therapy.

Effect of ribavirin on the mutation rate and spectrum of hepatitis C virus in vivo

Their extremely error-prone replication makes RNA viruses targets for lethal mutagenesis. In the case of hepatitis C virus (HCV), the standard treatment includes ribavirin, a base analog with an in vitro mutagenic effect, but the in vivo mode of action of ribavirin remains poorly understood. Here, we test the mutagenic effects of ribavirin plus interferon treatment in vivo using a new method to estimate mutation rates based on the analysis of nonsense mutations. We apply this methodology to a large HCV sequence database containing over 15,000 reverse transcription-PCR molecular clone sequences from 74 patients infected with HCV. We obtained an estimate of the spontaneous mutation rate of ca. 10(-4) substitutions per site or lower, a value within the typically accepted range for RNA viruses. A roughly threefold increase in mutation rate and a significant shift in mutation spectrum were observed in samples from patients undergoing 6 months of interferon plus ribavirin treatment. This result is consistent with the known in vitro mutagenic effect of ribavirin and suggests that the antiviral effect of ribavirin plus interferon treatment is at least partly exerted through lethal mutagenesis.

Combined therapy of interferon plus ribavirin promotes multiple adaptive solutions in hepatitis C virus

Hepatitis C virus (HCV) presents several regions involved potentially in evading antiviral treatment and host immune system. Two regions, known as PKR-BD and V3 domains, have been proposed to be involved in resistance to interferon. Additionally, hypervariable regions in the envelope E2 glycoprotein are also good candidates to participate in evasion from the immune system. In this study, we have used a cohort of 22 non-responder patients to combined therapy (interferon alpha-2a plus ribavirin) for which samples obtained just before initiation of therapy and after 6 or/and 12 months of treatment were available. A range of 25-100 clones per patient, genome region and time sample were obtained. The predominant amino acid sequences for each time sample and patient were determined. Next, the sequences of the PKR-BD and V3 domains and the hypervariable regions from different time samples were compared for each patient. The highest levels of variability were detected at the three hypervariable regions of the E2 protein and, to a lower extent, at the V3 domain of the NS5A protein. However, no clear patterns of adaptation to the host immune system or to antiviral treatment were detected. In summary, although high levels of variability are correlated to viral adaptive response, antiviral treatment does not seem to promote convergent adaptive changes. Consequently, other regions must be involved in evasion strategies likely based on a combination of multiple mechanisms, in which pools of changes along the HCV genome could confer viruses the ability to overcome strong selective pressures.

Predicting response to hepatitis C therapy

Current treatment for chronic hepatitis C is expensive, is often accompanied by burdensome side effects, and, sadly, fails in almost half of cases. The ability to predict such failures prior to treatment could save a great deal of pain and expense for the patient with HCV. In this issue of the JCI, Aurora and colleagues describe the development of genetic markers predictive of treatment response based on a study of viral sequence variation (see the related article beginning on page 225). Genome-wide covariation analyses of pretreatment virus sequences from 94 patients showed distinct patterns of mutations strongly associated with the ultimate success or failure of treatment. Such analyses suggest markers predictive of response to therapy and may lead to new insights into the underlying biology of hepatitis C.

Evidence of recombination in intrapatient populations of hepatitis C virus

Hepatitis C virus (HCV) is a major cause of liver disease worldwide and a potential cause of substantial morbidity and mortality in the future. HCV is characterized by a high level of genetic heterogeneity. Although homologous recombination has been demonstrated in many members of the family Flaviviridae, to which HCV belongs, there are only a few studies reporting recombination on natural populations of HCV, suggesting that these events are rare in vivo. Furthermore, these few studies have focused on recombination between different HCV genotypes/subtypes but there are no reports on the extent of intra-genotype or intra-subtype recombination between viral strains infecting the same patient. Given the important implications of recombination for RNA virus evolution, our aim in this study has been to assess the existence and eventually the frequency of intragenic recombination on HCV. For this, we retrospectively have analyzed two regions of the HCV genome (NS5A and E1-E2) in samples from two different groups: (i) patients infected only with HCV (either treated with interferon plus ribavirin or treatment naïve), and (ii) HCV-HIV co-infected patients (with and without treatment against HIV). The complete data set comprised 17712 sequences from 136 serum samples derived from 111 patients. Recombination analyses were performed using 6 different methods implemented in the program RDP3. Recombination events were considered when detected by at least 3 of the 6 methods used and were identified in 10.7% of the amplified samples, distributed throughout all the groups described and the two genomic regions studied. The resulting recombination events were further verified by detailed phylogenetic analyses. The complete experimental procedure was applied to an artificial mixture of relatively closely viral populations and the ensuing analyses failed to reveal artifactual recombination. From these results we conclude that recombination should be considered as a potentially relevant mechanism generating genetic variation in HCV and with important implications for the treatment of this infection.

Genetic variability of hepatitis C virus before and after combined therapy of interferon plus ribavirin

We present an analysis of the selective forces acting on two hepatitis C virus genome regions previously postulated to be involved in the viral response to combined antiviral therapy. One includes the three hypervariable regions in the envelope E2 glycoprotein, and the other encompasses the PKR binding domain and the V3 domain in the NS5A region. We used a cohort of 22 non-responder patients to combined therapy (interferon alpha-2a plus ribavirin) for which samples were obtained before initiation of therapy and after 6 or/and 12 months of treatment. A range of 25-100 clones per patient, genome region and time sample were sequenced. These were used to detect general patterns of adaptation, to identify particular adaptation mechanisms and to analyze the patterns of evolutionary change in both genome regions. These analyses failed to detect a common adaptive mechanism for the lack of response to antiviral treatment in these patients. On the contrary, a wide range of situations were observed, from patients showing no positively selected sites to others with many, and with completely different topologies in the reconstructed phylogenetic trees. Altogether, these results suggest that viral strategies to evade selection pressure from the immune system and antiviral therapies do not result from a single mechanism and they are likely based on a range of different alternatives, in which several different changes, or their combination, along the HCV genome confer viruses the ability to overcome strong selective pressures.

Refined analysis of genetic variability parameters in hepatitis C virus and the ability to predict antiviral treatment response

Hepatitis C virus (HCV) infects approximately 3% of the world population. The chronicity of hepatitis C seems to depend on the level of genetic variability. We have recently (Torres-Puente et al., J Viral Hepat, 2008; 15: 188) reported genetic variability estimates from a large-scale sequence analysis of 67 patients infected with HCV subtypes 1a (23 patients) and 1b (44 patients) and related them to response, or lack of, to alpha-interferon plus ribavirin treatment.. Two HCV genome regions were analysed in samples prior to antiviral therapy, one compressing the three hypervariable regions of the E2 glycoprotein and another one including the interferon sensitive determining region and the V3 domain of the NS5A protein. Haplotype and nucleotide diversity measures showed a clear tendency to higher genetic variability levels in nonresponder than in responder patients. Here, we have refined the analysis of genetic variability (haplotype and nucleotide diversity, number of haplotypes and mutations) by considering their distribution in each of the biologically meaningful subregions mentioned above, as well as in their surrounding and intervening regions. Variability levels are very heterogeneous among the different subregions, being higher for nonresponder patients. Interestingly, significant differences were detected in the biologically relevant regions, but also in the surrounding regions, suggesting that the level of variability of the whole HCV genome, rather than exclusively that from the hypervariable regions, is the main indicator of the treatment response. Finally, the number of haplotypes and mutations seem to be better discriminators than haplotype and nucleotide diversity, especially in the NS5A region.