Hepatitis C virus molecular evolution: Transmission, disease progression and antiviral therapy

Hepatitis C virus (HCV) infection represents an important public health problem worldwide. Reduction of HCV morbidity and mortality is a current challenge owned to several viral and host factors. Virus molecular evolution plays an important role in HCV transmission, disease progression and therapy outcome. The high degree of genetic heterogeneity characteristic of HCV is a key element for the rapid adaptation of the intrahost viral population to different selection pressures (e.g., host immune responses and antiviral therapy). HCV molecular evolution is shaped by different mechanisms including a high mutation rate, genetic bottlenecks, genetic drift, recombination, temporal variations and compartmentalization. These evolutionary processes constantly rearrange the composition of the HCV intrahost population in a staging manner. Remarkable advances in the understanding of the molecular mechanism controlling HCV replication have facilitated the development of a plethora of direct-acting antiviral agents against HCV. As a result, superior sustained viral responses have been attained. The rapidly evolving field of anti-HCV therapy is expected to broad its landscape even further with newer, more potent antivirals, bringing us one step closer to the interferon-free era.Fil: Preciado, María Victoria. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños ; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Valva, Pamela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños ; ArgentinaFil: Escobar Gutierrez, Alejandro. Instituto de Diagnóstico y Referencia Epidemiológicos; MéxicoFil: Rahal, Paula. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Ruiz Tovar, Karina. Instituto de Diagnóstico y Referencia Epidemiológicos; MéxicoFil: Yamasaki, Lilian. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Vazquez Chacon, Carlos. Instituto de Diagnóstico y Referencia Epidemiológicos; MéxicoFil: Martinez Guarneros, Armando. Instituto de Diagnóstico y Referencia Epidemiológicos; MéxicoFil: Carpio Pedroza, Juan Carlos. Instituto de Diagnóstico y Referencia Epidemiológicos; MéxicoFil: Fonseca Coronado, Salvador. Universidad Nacional Autónoma de México; MéxicoFil: Cruz Rivera, Mayra. Universidad Nacional Autónoma de México; Méxic

Hepatitis C virus resistance to the new direct-acting antivirals

Introduction: The treatment of hepatitis C virus (HCV) infection has dramatically improved in recent years with the widespread use of interferon-free combination regimens. Despite the high sustained virological response (SVR) rates (over 90%) obtained with direct-acting antivirals (DAAs), drug resistance has emerged as a potential challenge. The high replication rate of HCV and the low fidelity of its RNA polymerase result in a high degree of genetic variability in the HCV population, which ultimately explains the rapid selection of drug resistance associated variants (RAVs). Areas covered: Results from clinical trials and real-world experience have both provided important information on the rate and clinical significance of RAVs. They can be present in treatment-naive patients as natural polymorphisms although more frequently they are selected upon treatment failure. In patients engaged in high-risk behaviors, RAVs can be transmitted. Expert opinion: Although DAA failures generally occur in less than 10% of treated chronic hepatitis C patients, selection of drug resistance is the rule in most cases. HCV re-treatment options are available, but first-line therapeutic strategies should be optimized to efficiently prevent DAA failure due to baseline HCV resistance. Considerable progress is being made and next-generation DAAs are coming with pangenotypic activity and higher resistance barrier.Fil: Esposito, Isabella. Hospital Universitario La Paz; EspañaFil: Trinks, Julieta. Hospital Italiano. Instituto de Ciencias Básicas y Medicina Experimental; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Soriano, Vicente. Hospital Universitario La Paz; Españ

Selective Hyper-responsiveness of the Interferon System in Major Depressive Disorders and Depression Induced by Interferon Therapy

Though an important percentage of patients with chronic hepatitis C virus (HCV) undergoing interferon (IFN) therapy develop depressive symptoms, the role of the IFN system in the pathogenesis of depressive disorders is not well understood.50 patients with HCV infection were treated with standard combination therapy (pegylated IFN-α2a/ribavirin). IFN-induced gene expression was analyzed to identify genes which are differentially regulated in patients with or without IFN-induced depression. For validation, PBMC from 22 psychiatric patients with a severe depressive episode (SDE) and 11 controls were cultivated in vitro with pegylated IFN-α2a and gene expression was analyzed.IFN-induced depression in HCV patients was associated with selective upregulation of 15 genes, including 6 genes that were previously described to be relevant for major depressive disorders or neuronal development. In addition, increased endogenous IFN-production and selective hyper-responsiveness of these genes to IFN stimulation were observed in SDE patients.Our data suggest that selective hyper-responsiveness to exogenous (IFN therapy) or endogenous (depressive disorders) type I IFNs may lead to the development of depressive symptoms. These data could lead to the discovery of novel therapeutic approaches to treat IFN-induced and major depressive disorders

Identification of T-cell epitopes in the Hepatitis C virus genotype 4 proteome: a step towards epitope-driven vaccine development

Hepatitis C is an inflammatory infectious disease of the liver caused by the Hepatitis C Virus (HCV). It is a global pandemic, chronically inflicting 150 million people worldwide, with millions of new infections arising annually. The standard therapy of HCV is expensive, associated with severe side effects, and has variable success rates. Thus far, no HCV vaccine has been developed, owing to the challenges that faced and still face its development. Despite these challenges, several attempts have been taken to develop a vaccine, some of which have progressed to phase II clinical trials. Most of these attempts, however, have focused on HCV genotypes 1 and 2 as vaccine targets, and almost no attention has been given to HCV genotype 4 (HCV-4), the viral genotype most prevalent in the Middle East and Central Africa. In an attempt to fill this gap in HCV-4 vaccine research, this project describes the in silico identification of a group of highly conserved and immunogenic T-cell epitopes from the HCV-4 proteome, using the iVAX immunoinformatics toolkit (EpiVax Inc., RI, USA), as a first step towards the development of an epitope-driven vaccine against the viral genotype. Furthermore, it puts forth a fast and inexpensive method for the validation of the results retrospectively using the repository of empirical HCV immune epitope data on the Immune Epitope Database (IEDB). 90 HLA class I and 14 HLA class II epitopes were identified. From those, 20 HLA class I epitopes were found to be previously uncharacterized, while the in silico HLA binding predictions for 27 others (class I and class II) have been retrospectively validated. The retrospective validation results for 4 of the identified HLA class II epitopes were confirmed by a pilot HLA class II binding assay. Furthermore, an investigation of the conservancy of a selected set of the identified epitopes in newly re-sequenced HCV strains from the Egyptian population was performed. The identified and retrospectively validated set of epitopes constitutes a good target for further immunogenicity testing and epitope-driven vaccine development against HCV-4

Prospects for personalizing antiviral therapy for hepatitis C virus with pharmacogenetics

Chronic hepatitis C virus (HCV) infection is a major cause of liver disease worldwide. HCV infection is currently treated with IFNα plus ribavirin for 24 to 48 weeks. This demanding therapy fails in up to 50% of patients, so the use of pharmacogenetic biomarkers to predict the outcome of treatment would reduce futile treatment of non-responders and help identify patients in whom therapy would be justified. Both IFNα and ribavirin primarily act by modulating the immune system of the patient, and HCV uses multiple mechanisms to counteract the antiviral effects stimulated by therapy. Therefore, response to therapy is influenced by variations in human genes governing the immune system and by differences in HCV genes that blunt antiviral immune responses. This article summarizes recent advances in understanding how host and viral genetic variation affect outcome of therapy. The most notable human associations are polymorphisms within the IL28B gene, but variations in human leukocyte antigen and cytokine genes have also been associated with treatment outcome. The most prominent viral genetic association with outcome of therapy is that HCV genotype 1 is much less sensitive to treatment than genotypes 2 and 3, but genetic differences below the genotype level also influence outcome of therapy, presumably by modulating the ability of viral genes to blunt antiviral immune responses. Pharmacogenetic prediction of the outcome of IFN-based therapy for HCV will require integrating the efficacies of the immunosuppressive mechanisms of a viral isolate, and then interpreting the viral resistance potential in context of the genetic profile of the patient at loci associated with outcome of therapy. Direct-acting inhibitors of HCV that will be used in combination with IFNα are nearing approval, so genetic prediction for anti-HCV therapy will soon need to incorporate viral genetic markers of viral resistance to the new drugs

MATHEMATICAL MODELING OF HOST CELL DETERMINANTS AND PHARMACOLOGICAL INTERVENTION IN HEPATITIS C VIRUS REPLICATION

Hepatitis C virus (HCV) is a blood-borne, enveloped, single-stranded, (+)-oriented RNA virus that mainly infects hepatocytes. Most infections progress into chronicity and eventually lead to severe liver disease. Although effective treatments have been developed, access to diagnosis and treatment is low, particularly in non-developed countries. Thus, eradication of the disease is unlikely without a prophylactic vaccine. Research, therefore, has to continue despite the high cure rates of today’s HCV regimens. We use mathematical modeling to study HCV replication and its intricate connection with the infected host cell. A model that is able to simulate intracellular HCV RNA replication suggested a host factor species (HF), representing a protein (complex) or a host process, to be critically involved in HCV replication. Gene expression profiling revealed several candidates potentially representing this HF. We validated those candidates in two variants of the human hepatoma cell line Huh7 and could confirm that five of them indeed played a role for HCV replication, namely CRAMP1, LBHD1, CRYM, THAP7, and NR0B2. The latter three are nuclear receptors or transcriptional (co )repressors, suggesting they could influence HCV replication indirectly, e.g. through glucose, lipid, or cholesterol metabolism. Follow-up studies will help to understand the implication of those factors in HCV replication and reveal important insights into the metabolic pathways regulating HCV replication. Model analyses also revealed the most sensitive steps in HCV RNA replication that could potentially be targeted by specific intervention. The standard of care for chronic HCV infection has been interferon alpha (IFN α) therapy that elicited a very broad but rather unspecific antiviral response of the host cell and came along with severe side effects. IFN-α activates signaling cascades that lead to the expression of hundreds of interferon stimulated genes that exert antiviral action. Despite its decades-long use, the exact mechanism of the suppression of HCV replication by IFN α treatment remains elusive. We thus combined experimental data with an intracellular model for HCV replication and revealed the steps in the viral replication cycle that are most probably affected by IFN α treatment. The obtained findings were well in line with in vitro data and confirmed the validity of our intracellular model to make such analyses. Recently, direct-acting antivirals (DAAs) have replaced IFN-α-containing regimens as the standard of care for chronic HCV infection. Those DAAs possess much less side effects, can be taken orally, and give extraordinarily high cure rates. Mainly three classes exist: inhibitors of the viral protease, the viral polymerase, and a viral multifunctional phosphoprotein. The latter class constitutes highly potent inhibitors of the HCV NS5A protein, exerting effects in the low picomolar range. However, due to the many roles of NS5A in the HCV life cycle, the exact mechanism of action of those DAAs remains unclear. For the other two classes, the mode of action is distinct and well defined. We, thus, used one representative member of each of these classes to validate the capacity of our model to implement drug effects and predict HCV replication correctly. Model predictions upon a priori fixing of the affected parameters in the model qualitatively resembled HCV replication dynamics under the respective drug treatment. This allowed us to apply our model to HCV replication data under treatment with an NS5A inhibitor in order to gain insights into its mode of action. The model revealed that the translation rate of HCV RNA as well as RNA synthesis steps in the HCV replication compartment are most probably affected by the drug. These findings were reasonable and supported by known roles of NS5A in the HCV life cycle. However, our model was limited to intracellular HCV replication and did not account for steps like particle assembly or infection of target cells. Therefore, we extended our intracellular model to cover the full viral life cycle. Our new full life cycle model could simulate viral (+)- and (-)-strand RNA, viral titers as well as spread of the infection, and was able to correctly predict HCV replication under drug treatment. Our new model will be helpful in further elucidating the mode of action of NS5A inhibitors and IFN α and in deciphering the role of host factors that determine permissiveness for HCV. Hence, this study provides a novel, extended mathematical model of the full HCV life cycle with the proven capacity of simulating and analyzing HCV replication even under pharmacological intervention. It can serve as an invaluable tool to study further molecular details of HCV replication and to devise and test novel therapeutic approaches

Interferon-lambda 3 and 4 polymorphisms increase sustained virological responses and regulate innate immunity in antiviral therapy with pegylated interferon-alpha

Sustained virologic response (SVR) in chronic hepatitis C (CHC) treatment denotes that the host genetics controls the immune response and unequivocally contribute to viral clearance or disease severity. In this context, single nucleotide polymorphisms (SNPs) in the locus of interferon lambda 3 and 4 genes (IFNL3/4) have been important genetic markers of responsiveness to CHC as prognostic markers for the pegylated-Interferonalpha/ ribavirin (Peg-IFN-a/RBV). Here, we analyzed 12 SNPs at the IFNL3/4 region in 740 treatment-naïve patients with CHC infected with hepatitis C virus (HCV) genotypes 1, 2, or 3 treated with Peg-IFN-a/RBV. Individually, rs12979860-CC, rs8109886-CC, or rs8099917-TT were predictive markers of SVR, while rs12979860-CC demonstrated the stronger effect. Besides, the genotypic combination of these three predictors’ genotypes, CC/CC/TT, increased the rate of SVR. Serum levels of cytokines and gene expression analysis on the genes IFNL3, IFNL4, IFNA1, and some of the IFN-stimulated genes (ISGs) were measured in a subgroup of 24 treated patients and 24 healthy volunteers. An antagonist effect was highlighted between the expression of IFNL3/4 and IFNA1 mRNA among patients. Besides, a prominent production of the proinflammatory chemokines CCL4 and CXCL10 was observed at a 12-week treatment follow-up. Lower serum levels of these chemokines were detected in patients with an rs12979860-CC genotype associated with the better treatment outcome. Also, lower expression levels of the IFI6, IFI16, IRF9 genes were observed among rs12979860-CC individuals. In conclusion, a combination of the genotypes at the IFNL3/4 locus can act as a better marker for the prognosis for virological responses in an admixed Brazilian population presenting the modulating effect over innate immunity and inflammation that are controlling the outcome of the viral infection, but also other infectious diseases

Computational approaches for improving treatment and prevention of viral infections

The treatment of infections with HIV or HCV is challenging. Thus, novel drugs and new computational approaches that support the selection of therapies are required. This work presents methods that support therapy selection as well as methods that advance novel antiviral treatments. geno2pheno[ngs-freq] identifies drug resistance from HIV-1 or HCV samples that were subjected to next-generation sequencing by interpreting their sequences either via support vector machines or a rules-based approach. geno2pheno[coreceptor-hiv2] determines the coreceptor that is used for viral cell entry by analyzing a segment of the HIV-2 surface protein with a support vector machine. openPrimeR is capable of finding optimal combinations of primers for multiplex polymerase chain reaction by solving a set cover problem and accessing a new logistic regression model for determining amplification events arising from polymerase chain reaction. geno2pheno[ngs-freq] and geno2pheno[coreceptor-hiv2] enable the personalization of antiviral treatments and support clinical decision making. The application of openPrimeR on human immunoglobulin sequences has resulted in novel primer sets that improve the isolation of broadly neutralizing antibodies against HIV-1. The methods that were developed in this work thus constitute important contributions towards improving the prevention and treatment of viral infectious diseases.Die Behandlung von HIV- oder HCV-Infektionen ist herausfordernd. Daher werden neue Wirkstoffe, sowie neue computerbasierte Verfahren benötigt, welche die Therapie verbessern. In dieser Arbeit wurden Methoden zur Unterstützung der Therapieauswahl entwickelt, aber auch solche, welche neuartige Therapien vorantreiben. geno2pheno[ngs-freq] bestimmt, ob Resistenzen gegen Medikamente vorliegen, indem es Hochdurchsatzsequenzierungsdaten von HIV-1 oder HCV Proben mittels Support Vector Machines oder einem regelbasierten Ansatz interpretiert. geno2pheno[coreceptor-hiv2] bestimmt den HIV-2 Korezeptorgebrauch dadurch, dass es einen Abschnitt des viralen Oberflächenproteins mit einer Support Vector Machine analysiert. openPrimeR kann optimale Kombinationen von Primern für die Multiplex-Polymerasekettenreaktion finden, indem es ein Mengenüberdeckungsproblem löst und auf ein neues logistisches Regressionsmodell für die Vorhersage von Amplifizierungsereignissen zurückgreift. geno2pheno[ngs-freq] und geno2pheno[coreceptor-hiv2] ermöglichen die Personalisierung antiviraler Therapien und unterstützen die klinische Entscheidungsfindung. Durch den Einsatz von openPrimeR auf humanen Immunoglobulinsequenzen konnten Primersätze generiert werden, welche die Isolierung von breit neutralisierenden Antikörpern gegen HIV-1 verbessern. Die in dieser Arbeit entwickelten Methoden leisten somit einen wichtigen Beitrag zur Verbesserung der Prävention und Therapie viraler Infektionskrankheiten