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Hepatitis C virus (HCV) infection is associated with alterations in host lipid and insulin signaling cascades, which are partially explained by a dependence of the HCV life cycle on key molecules in these metabolic pathways. Yet, little is known on the role in the HCV life cycle of glycogen synthase kinase 3 (GSK3), one of the most important kinases in cellular metabolism. Therefore, the impact of GSK3 on the HCV life cycle was assessed in human hepatoma cell lines harboring subgenomic genotype 1b and 2a replicons or producing cell culture-derived HCV genotype 2a by exposure to synthetic GSK3 inhibitors, GSK3 gene silencing, overexpression of GSK3 constructs and immunofluorescence analyses. In addition, the role of GSK3 in hepatitis E virus (HEV) replication was investigated to assess virus specificity of the observed findings. We found that both inhibition of GSK3 function by synthetic inhibitors as well as silencing of GSK3β gene expression resulted in a decrease of HCV replication and infectious particle production, whereas silencing of the GSK3α isoform had no relevant effect on the HCV life cycle. Conversely, overexpression of GSK3β resulted in enhanced HCV replication. In contrast, GSK3β had no effect on replication of subgenomic HEV replicon. The pro-viral effect of GSK3β on HCV replication was mediated by supporting expression of microRNA-122 (miR-122), a micro-RNA which is mandatory for wild-type HCV replication, as GSK3 inhibitors suppressed miR-122 levels and as inhibitors of GSK3 had no antiviral effect on a miR-122-independent HCV mutant. In conclusion, we have identified GSK3β is a novel host factor supporting HCV replication by maintaining high levels of hepatic miR-122 expression.
Background: IL28B gene polymorphism is the best baseline predictor of response to interferon alfa-based antiviral therapies in chronic hepatitis C. Recently, a new IFN-L4 polymorphism was identified as first potential functional variant for induction of IL28B expression. Individualization of interferon alfa-based therapies based on a combination of IL28B/IFN-L4 polymorphisms may help to optimize virologic outcome and economic resources.
Methods: Optimization of treatment outcome prediction was assessed by combination of different IL28B and IFN-L4 polymorphisms in patients with chronic HCV genotype 1 (n = 385), 2/3 (n = 267), and 4 (n = 220) infection treated with pegylated interferon alfa (PEG-IFN) and ribavirin with (n = 79) or without telaprevir. Healthy people from Germany (n = 283) and Egypt (n = 96) served as controls.
Results: Frequencies of beneficial IL28B rs12979860 C/C genotypes were lower in HCV genotype 1/4 infected patients in comparison to controls (20–35% vs. 46–47%) this was also true for ss469415590 TT/TT (20–35% vs. 45–47%). Single interferon-lambda SNPs (rs12979860, rs8099917, ss469415590) correlated with sustained virologic response (SVR) in genotype 1, 3, and 4 infected patients while no association was observed for genotype 2. Interestingly, in genotype 3 infected patients, best SVR prediction was based on IFN-L4 genotype. Prediction of SVR with high accuracy (71–96%) was possible in genotype 1, 2, 3 and 4 infected patients who received PEG-IFN/ribavirin combination therapy by selection of beneficial IL28B rs12979860 C/C and/or ss469415590 TT/TT genotypes (p<0.001). For triple therapy with first generation protease inhibitors (PIs) (boceprevir, telaprevir) prediction of high SVR (90%) rates was based on the presence of at least one beneficial genotype of the 3 IFN-lambda SNPs.
Conclusion: IFN-L4 seems to be the best single predictor of SVR in genotype 3 infected patients. For optimized prediction of SVR by treatment with dual combination or first generation PI triple therapies, grouping of interferon-lambda haplotypes may be helpful with positive predictive values of 71–96%.
Background: Different parameters have been determined for prediction of treatment outcome in hepatitis c virus genotype 1 infected patients undergoing pegylated interferon, ribavirin combination therapy. Results on the importance of vitamin D levels are conflicting. In the present study, a comprehensive analysis of vitamin D levels before and during therapy together with single nucleotide polymorphisms involved in vitamin D metabolism in the context of other known treatment predictors has been performed.
Methods: In a well characterized prospective cohort of 398 genotype 1 infected patients treated with pegylated interferon-α and ribavirin for 24–72 weeks (INDIV-2 study) 25-OH-vitamin D levels and different single nucleotide polymorphisms were analyzed together with known biochemical parameters for a correlation with virologic treatment outcome.
Results: Fluctuations of more than 5 (10) ng/ml in 25-OH-vitamin D-levels have been observed in 66 (39) % of patients during the course of antiviral therapy and neither pretreatment nor under treatment 25-OH-vitamin D-levels were associated with treatment outcome. The DHCR7-TT-polymorphism within the 7-dehydrocholesterol-reductase showed a significant association (P = 0.031) to sustained viral response in univariate analysis. Among numerous further parameters analyzed we found that age (OR = 1.028, CI = 1.002–1.056, P = 0.035), cholesterol (OR = 0.983, CI = 0.975–0.991, P<0.001), ferritin (OR = 1.002, CI = 1.000–1.004, P = 0.033), gGT (OR = 1.467, CI = 1.073–2.006, P = 0.016) and IL28B-genotype (OR = 2.442, CI = 1.271–4.695, P = 0.007) constituted the strongest predictors of treatment response.
Conclusions: While 25-OH-vitamin D-levels levels show considerable variations during the long-lasting course of antiviral therapy they do not show any significant association to treatment outcome in genotype 1 infected patients.
This paper reports on Monte Carlo simulation results for future measurements of the moduli of time-like proton electromagnetic form factors, |GE | and |GM|, using the ¯pp → μ+μ− reaction at PANDA (FAIR). The electromagnetic form factors are fundamental quantities parameterizing the electric and magnetic structure of hadrons. This work estimates the statistical and total accuracy with which the form factors can be measured at PANDA, using an analysis of simulated data within the PandaRoot software framework. The most crucial background channel is ¯pp → π+π−,due to the very similar behavior of muons and pions in the detector. The suppression factors are evaluated for this and all other relevant background channels at different values of antiproton beam momentum. The signal/background separation is based on a multivariate analysis, using the Boosted Decision Trees method. An expected background subtraction is included in this study, based on realistic angular distribuations of the background contribution. Systematic uncertainties are considered and the relative total uncertainties of the form factor measurements are presented.