Genome Study of the Hepatitis C Virus (HCV)

Published Date: 12 Mar 2018

Hepatitis C virus (HCV) is the causative agent of hepatitis C, which is an infectious liver disease of humans. Estimates indicate that 170 million people are chronically infected globally and are at risk of developing liver disease including cirrhosis (scarring of tissue) and liver cancer. Furthermore, 350,000 deaths occur each year due to all HCV-related causes [1]. Although 20%–30% of the 170 million people infected with HCV recover spontaneously, the remainder develop chronic infection [2]. In Pakistan, liver cancer is becoming a leading cause of death and accounts for 60%-90% of all primary liver malignancies [3] and 80% of these patients are found to be infected with HCV [4]. According to a study, approximately 6-8% of total individuals in Pakistan are infected with HCV whose number is increasing with an alarming rate [5]. Studies show that current therapy with pegylated interferon-alpha and ribavirin (PegIFN/RBV) achieves a sustained virological response (SVR) (cases in which HCV RNA became undetectable 6 month post cessation of therapy) in 84% non-cirrhotic and in 34% of cirrhotic patients infected with HCV genotype 3a [6]. Hepatitis C treatment is very expensive and is associated with numerous side effects such as fatigue, nausea, anorexia, marked anemia, neutropenia, thrombocytopenia, depression, dementia, irritability, skin rashes [7-9]. Suicide rate is also very high among HCV patients undergoing interferon and ribavirin treatment [10]. These side effects sometimes require dose reduction and premature treatment cessation, thus increasing the risk of treatment failure. Thus, genotyping tests for host factors (e.g. IL28b polymorphism) should be commercially available which can help physicians in predicting treatment response. As a result patient will not suffer adverse side effects of the treatment unnecessarily. Unfortunately, no such population based study has been done in Pakistan to evaluate the usefulness of such host gene variants in predicting HCV treatment response. In the current study we will try to correlate different immunological host factor variants, HCV genotype and treatment response in HCV patients of Pakistani origin. We will also try to relate these host factors and their effects on immunological response of the body against HCV infection.

There has been little success, so far, in developing an effective prophylactic vaccine against HCV because of the very high mutation rate and the presence of quasiespecies [11]. The current therapies, peg-IFN/RBV provide limited efficacy and are poorly tolerated, a consequence of combining two nonspecific antiviral agents with pleiotropic effects that were not originally designed to treat chronic HCV infection. The undefined nature of the current treatment makes it very difficult to pharmacologically refine combination strategies, especially in the treatment of a significant proportion of patients that have experienced drug resistance and therapeutic failure. As sustained virological response (SVR) is not achieved in every patient thus this therapy leads to numerous profound side effects worsening the condition of patient. This situation highlights the need for well-defined antiviral and immunomodulatory therapeutics to rationalize mechanism-based combination strategies in treatments achieving a high genetic barrier to resistance and restoring HCV-specific immunity (Laurent et al, 2010). But there is still a long way to go in order to achieve this goal. No one knows for sure how long until the controversial interferon treatment can be sent packing and new direct antivirals can be used commercially. Until then, we are left with no choice but to make intelligent decisions regarding interferon/ribavirin treatment. The decision as to who should receive this treatment or not is based on many factors. One of the most important factors is the genotype variants of host factors which play a significant role in predicting the treatment response to considerable extent.

In this regard, genome wide analysis studies (GWAS) have identified important single nucleotide polymorphisms (SNPs) which are associated with prediction of treatment success or failure. No such study has been done on Pakistani population, infected with HCV genotype 3a. In the current study, variants of different important host immunological factors will be analyzed in >1000 Pakistani HCV patients from different geographical locations. Also, associated immune signaling pathways will be modeled using petrinets model. Petrinet model is a type of mathematical modeling approach which can be used very easily to model and visualize biological signaling pathways and networks. Previous approaches of differential equation required a considerable effort to reconstruct a network of differential equation based on biological map. Petri nets do not require such redundant effort because of its intuitive graphical representation and their capabilities for mathematical analyses and simulation. In our study we will try to correlate different immunological pathways, which are altered due to presence of HCV infection, and specific genotype of host factors which we are studying in our project. To the best of our knowledge, no such study exists which correlates all the signaling pathways involved in HCV qualitatively or quantitatively. Based on our HCV petrinet model, we will design expression studies in order to validate our findings. Once established, our model will be able to predict the outcomes of expression variations significantly. It will help researchers to save time and money on actual cell culture based experiments. Furthermore, careful analysis of HCV infection pathways and our predicted petrinet model will be used to predict new putative targets for therapeutic intervention. These targets will be validated further by using real-time PCR (qPCR) analysis.

Hepatitis C, a huge blood borne menace and a serious encumbrance, is the most prevailing type among 8 known types of Hepatitis affecting the health of 3.3% population worldwide (Di Lorenzo et al., 2011). Hepatocellular carcinoma and liver cirrhosis are the major HCV intricacies causing morbidity, mortality, economic burden and social disgrace. HCV has multiple interconnected pathogenic mechanisms with liver being the major site for HCV replication. The clinical significance of SNPs in relationship to Interferon-Ribavirin treatment response is highly established fact, still to be explored in Pakistani population. Three genome wide analysis studies have identified variants of certain host factors which strongly indicate treatment response based on individual’s genotype. In developed countries specific genotyping tests (e.g. IL28b polymorphism) are available which can help physicians in predicting treatment response so that the patient does not suffer adverse side effects of the treatment. Unfortunately, no such population based study has been done to evaluate the usefulness of such variants based on Pakistani origin.

Previous studies have shown that SNP variants are significant predictors of the treatment response. The favourable genotypes of the following are significant predictors of higher SVR rates; rs12979860, rs12980275, and rs8099917 of IFN-λ3 and IFN-λ4. Along with IFN-λ3 and IFN-λ4, other immunological gene variants are also being evaluated to determine treatment response. Among these KIR and HLA variants are known to be highly significant in determining HCV treatment response. Genotyping of these genes in Pakistani cohort along with the specific genotype of HCV is very important so that prognosis can be determined with respect to HCV treatment.

In the current study, we will try to correlate different immunological host factor variants, HCV genotype and treatment response in HCV patients of Pakistani origin. These will include the variant analysis of IFN-λ3, IFN-λ4, KIR, and HLA-C. Furthermore, as there is no vaccine available for HCV because of high mutation rate, thus different signaling pathways will be subjected to computational analysis for predicting new therapeutic targets. These targets will be based on extensive study and modeling of all related pathways involved in HCV pathogenesis. Petrinets modeling and biological regulatory network approach will be used to formulate an extensive model correlating the different host signaling pathways which are hijacked by HCV during chronic infection of liver. This study will help physicians and clinicians to introduce such tests and better plan HCV treatment in Pakistan. Our model once validated, will help researchers to better plan their experiments and save a lot of time and expenses.

Hepatitis C virus (HCV) is the causative agent of Hepatitis C disease in Human, conclusively proved in 1989, when its genome was cloned for the first time [12]. HCV is a member of Flaviviridae family [13] . It is a small (55-65nmin size) enveloped virus, containing positive single stranded RNA of 9.6 kilo bases [14]. HCV has 6 genotypes and multiple sub genotypes with ~30% difference among the genotypes [15, 16]. The prevalent genotype in Pakistan is 3a followed by 3b and 1a [17]. 20%–30% of the 170 million people infected with the hepatitis C virus (HCV) recover spontaneously; the remainder develop chronic infection with a risk for developing cirrhosis, liver failure, and hepatocellular carcinoma (HCC) [2] The risk of developing HCC for a patient with HCV-related cirrhosis is approximately 2-6% per year across the globe [18].

Current therapy of peg IFN/RBV is associated with numerous side effects, complications as well as drug resistance. With the advent of new technologies and resources, several new avenues have been explored to predict better response to treatment with regard to human genetics. Host genotyping studies have the potential to identify genes and therefore pathogenic processes important in viral clearance, enabling a rational approach to design new drugs, and to identify patients who will most likely respond to current and new treatments [19]

Several Genome wide association studies (GWAS) have been conducted in this regard. On the basis of these studies few factors have been identified which are highly significant in determining the treatment response or failure in case of HCV infection, such as variants of IL28B gene. These studies have led to changes in treatment profiles for patients in USA and other technologically advanced countries. There is a strong need to study these genetic associations with regard to Pakistani population and prevalent HCV genotype. Differences in ethnicity and genetics due to geographical location have a vital role in determining gene association and linkages.

The IFN-λ family consists of IFN-λ 1, 2, 3, 4 (equivalent to IL-29, 28A, 28B). The primary sources of IFN-λ are dendritic cells (DCs). These cytokines are mainly produced in response to viral infection or by activation of Toll-like receptors (TLRs). IFN-λ showed antiviral activity against many viruses such as HCV, HIV etc. these cytokines have an important role in regulation and development of the adaptive immune response against viruses. SNPs within chromosome 19, in the vicinity of the IL29, IL28A, and IL28B genes, are importantly associated with the treatment response of HCV infection. Three SNPs related to these genes, rs8099917, rs12980275, and rs12979860, are very important. Interleukin 28 B (IL28B), which encodes Interferon-Lambda 3 (IFN-λ3), genotype predicts treatment-induced and spontaneous clearance of HCV. In 2009, 3 genome-wide association studies (GWASs) demonstrated an impact of single-nucleotide polymorphisms (SNPs) in the spanning region between IL28A and IL28B on interferon-based hepatitis C clearance implicating rs12979860 and rs8099917 as the strongest genetic determinants of Sustained Virologic Response (SVR). According to these studies, the rs12979860 C and rs8099917 T alleles are associated with a higher rate of SVR, whereas the rs12979860 T and rs8099917 G alleles are linked to a lower rate of SVR and a higher rate of treatment failure. Also, it has been shown that the rs12979860 CC and rs8099917 TT genotypes are strongly associated with spontaneous resolution of HCV infection [20-23]. These SNPs rs8099917 and rs12979860 are in strong linkage disequilibrium with each other. Also another set of SNPs rs11881222 rs12980275 are strongly related to the lower rate of SVR implicated in Chinese studies [24]. Thus, rs1188222 (AG), rs12979860 (CT), rs12980275 (AG) and rs8099917 (GT) play a pivotal role in determining response to HCV infection treatment.

However, the functional link between polymorphisms at IL28B and HCV clearance still remains unsettled. It seems that these genetic traits are related with levels of intra-hepatic IL28B gene expression, [25] and the baseline expression of interferon stimulated genes (ISGs) is significantly higher in patients carrying the minor rs8099917 G allele.[26] Since HCV itself is not cytopathic, liver damage in CHC is commonly attributed to immune-mediated mechanisms.

Role of variants of HLA-C and KIR in predicting HCV treatment failure:

Natural killer (NK) cells eliminate infected and transformed cells while still are self-tolerant. Interactions of the independently segregating Killer Cell Immunoglobulin-like receptors (KIR) and Human Leucocyte Antigens (HLA) loci play a critical role in NK cell regulation. Different compound KIR-HLA genotypes can impart different thresholds of activation to the NK-cell repertoire and such genotypic variation has been found to confer altered risk in a number of human diseases including viral infections, autoimmune disorders, reproduction abnormalities and cancers. Thus , to improve the predictive value of the IFNL3/IL28B genotype, several studies have reported the combined effect of variants of IL28B with human leukocyte antigen C (HLA-C), and its ligands the killer immunoglobulin-like receptors (KIR), which have previously been implicated in HCV viral control [19].

HLA-C group 1 (HLAC1) alleles are ligands for the inhibitory receptors KIR2DL2 and KIR2DL3, and the activating receptor KIR2DS2. HLA-C group 2 (HLA-C2) alleles, on the other hand, are recognized by inhibitory KIR2DL1 and activating KIR2DS1 receptors. The HLA-C2C2 genotype predicted failure to clear HCV on treatment, but no association with failure to clear HCV without treatment was detected. The prediction of treatment-induced clearance was additive and interactive between IL28B and HLA-C; and there was evidence of additive and interactive effects between KIR2DL2 and KIR2DL3, KIR2DS1 and KIR2DS2 and HLAC2C2. Previous reports point to HLA-C as being the second gene predicting PegIFN/R treatment response in HCV. This genetic evidence supports an underlying physiological mechanism for HCV viral control involving an interaction between IL28B, HLA-C, and KIRs [19].

Role of IFN-λ4 in failure to clear HCV:

3kb upstream of IFNL3 (IL28B) on chromosome 19q13.13, a new transiently induced region has been discovered that harbors a dinucleotide variant ss469415590 (TT or DG), which is in high linkage disequilibrium with rs12979860, a genetic marker strongly associated with HCV clearance. ss469415590 [DG] is a frame shift variant that creates a novel gene, designated IFNL4, encoding 179 amino acid interferon-L4 protein (IFNL4), which is moderately similar to IFNL3 [27]. Compared to rs12979860, ss469415590 is more strongly associated with HCV clearance in individuals of African ancestry, although it provides comparable information in Europeans and Asians. Transient overexpression of IFNL4 in a hepatoma cell line induced STAT1 and STAT2 phosphorylation and the expression of interferon-stimulated genes (ISGs) [28, 29].

In one study, treatment failure occurred in 77% of minor ΔG-allele carriers versus 48% of noncarriers, indicating that the ΔG allele was strongly associated with treatment failure [30] . Importantly, multivariate analysis revealed that ss469415590 genotype was a better predictor of treatment failure than IFNL3 rs12979860. The GWAS markers rs12979860 and rs8099917 are located 367bp downstream (intron 1) and 4 kb upstream of ss469415590, respectively. IFNL4-creating ss469415590 [ΔG] allele is perfectly correlated with the unfavorable rs12979860 [T] allele in Asians, China and Japan and well correlated in Europeans. In Africans, however, this correlation is only moderate even though rs12979860 is the best surrogate for ss469415590 of all markers within the 100-kb region. Correlation between ss469415590 and rs8099917 was high in Asians and moderate in Europeans but very low in Africans [28]. There is need to study the combined effect of this variant of IFNL4 with variants of IFNL3 and other immunological proteins involved in treatment response to HCV.

Following diagram shows the differential expression of many host factors which are involved in HCV infection progression. Each of these host dependencies is not only a potential therapeutic target but also determinant of treatment response.