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Review article: genetic factors that modify the outcome of viral hepatitis.

ABSTRACT: BACKGROUND:Genetic factors can play an important role for treatment response and disease progression in chronic viral hepatitis. AIM:To review the influence of host genetic factors on the clinical course as well as on treatment response in patients with viral hepatitis. METHODS:Review of the literature. RESULTS:A landmark genome-wide association study (GWAS) identified polymorphisms in the IL28B gene on chromosome 19 (19q13.13) associated with response to therapy with pegylated interferon-? (PEG-IFN) and ribavirin (RBV) and spontaneous viral clearance in acute hepatitis C. Furthermore, IL28B genotype is associated with changes of lipid metabolism and insulin resistance. A further GWAS demonstrated that ITPA genetic variants protect HCV genotype 1 patients from RBV-induced anaemia. Another polymorphism in the patatin-like phospholipase domain containing 3 (PNPLA3) is associated with hepatic steatosis. Difficult-to-treat hepatitis C patients homozygous for GG had an up to five-fold lower chance of viral clearance on PEG/RBV than non-GG patients. In chronic hepatitis B patients treated with PEG-IFN several retrospective analyses of IL28B rs12980275 and rs12979860 genotypes yielded conflicting results which can be explained by the heterogeneity between the study populations. Some variants of the HLA-DP locus (HLA-DPA1 A allele and HLA-DPB1) protect against progression of chronic hepatitis B infection. CONCLUSIONS:The determination of IL28B polymorphisms may be useful to individualise treatment options when using PEG/RBV based therapies for chronic hepatitis C infection. In contrast, so far identified genetic factors play only a minor role in chronic hepatitis B infection.

SUBMITTER: Stattermayer AF

PROVIDER: S-EPMC7159786 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Review article: genetic factors that modify the outcome of viral hepatitis.

Stättermayer A F AF Scherzer T T Beinhardt S S Rutter K K Hofer H H Ferenci P P

Alimentary pharmacology & therapeutics 20140324 10

<h4>Background</h4>Genetic factors can play an important role for treatment response and disease progression in chronic viral hepatitis.<h4>Aim</h4>To review the influence of host genetic factors on the clinical course as well as on treatment response in patients with viral hepatitis.<h4>Methods</h4>Review of the literature.<h4>Results</h4>A landmark genome-wide association study (GWAS) identified polymorphisms in the IL28B gene on chromosome 19 (19q13.13) associated with response to therapy wit ...[more]

PMID: 24654629

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Project description:BackgroundOnly 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.MethodologySeventy-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 findingsA 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 significanceThe 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.

Project description: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.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.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.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.

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Review article: genetic factors that modify the outcome of viral hepatitis.

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Review article: genetic factors that modify the outcome of viral hepatitis.

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