scholarly journals Expression of Interferon Effector Gene SART1 Correlates with Interferon Treatment Response against Hepatitis B Infection

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Yong Li ◽  
Chuanlong Zhu ◽  
Faxi Wang ◽  
Tiantian Zhu ◽  
Jun Li ◽  
...  

Interferon-α (IFN-α) has limited response rate in the treatment of chronic hepatitis B (CHB). The underlying mechanism of differential responsiveness to IFN remains elusive. It has been recently reported that SART1 mediates antiviral effects of IFN-α in the hepatitis C virus (HCV) cell culture model. In this study, we investigated the role of SART1 in antiviral activity of IFN-α against hepatitis B virus (HBV) using blood and liver biopsy samples from chronic hepatitis B patients treated with pegylated IFN-α and HepG2 cells transfected with cloned HBV DNA. We observed that the basal SART1 expression in liver and PBMCs before IFN treatment was significantly higher in responders than in nonresponders. Furthermore, baseline SART1 expression level positively correlated with the degree of HBV DNA and HBeAg decline after IFN treatment. Mechanistically, silencing SART1 abrogated the antiviral activity of IFN-α, reduced the expression of IFN-stimulated genes (ISGs) Mx, OAS, and PKR, and attenuated JAK-STAT signaling in HepG2 cells, suggesting that SART1 regulates IFN-mediated antiviral activity through JAK-STAT signaling and ISG expression. Our study elucidates the important role of SART1 in IFN-mediated anti-HBV response and provides new insights into understanding variation of IFN treatment response in CHB patients.

Author(s):  
Mina S Farag ◽  
Margo J H van Campenhout ◽  
Maria Pfefferkorn ◽  
Janett Fischer ◽  
Danilo Deichsel ◽  
...  

Abstract Background Hepatitis B virus RNA (HBV-RNA) is a novel serum biomarker that correlates with transcription of intrahepatic covalently closed circular (cccDNA), which is an important target for pegylated interferon (PEG-IFN) and novel therapies for functional cure. We studied HBV-RNA kinetics following PEG-IFN treatment and its potential role as a predictor to response in HBeAg-negative chronic hepatitis B (CHB) patients. Methods HBV-RNA levels were measured in 133 HBeAg-negative CHB patients treated in an international randomized controlled trial (PARC study). Patients received PEG-IFN α-2a for 48 weeks. HBV-RNA was measured from baseline through week 144. Response was defined as HBV-DNA <2000 IU/mL and ALT normalization at week 72. Kinetics of HBV-RNA were compared with HBV-DNA, HBsAg, and HBcrAg. Results Mean HBV-RNA at baseline was 4.4 (standard deviation [SD] 1.2) log10 c/mL. At week 12, HBV-RNA declined by −1.6 (1.1) log10 c/mL. HBV-RNA showed a greater decline in responders compared to nonresponders early at week 12 (−2.0 [1.2] vs −1.5 [1.1] log10 c/mL, P = .04). HBV-RNA level above 1700 c/mL (3.2 log10 c/mL) had a negative predictive value of 91% at week 12 and 93% at week 24 (P = .01) for response. Overall, HBV-RNA showed a stronger correlation with HBV-DNA and HBcrAg (.82 and .80, P < .001) and a weak correlation with HBsAg (.25). At week 12, HBV-RNA was significantly lower among patients with lower HBsAg (<100 IU/mL) or HBsAg loss at week 144. Conclusions During PEG-IFN treatment for HBeAg-negative CHB, HBV-RNA showed a fast and significant decline that correlates with treatment response and HBsAg loss at long-term follow-up. Clinical Trials Registration NCT00114361


2011 ◽  
pp. 25-29
Author(s):  

Aims: To measure the prevalence of HBV genotypes in chronic hepatitis B patients and their relation to HBeAg and HBV DNA level. Methods: 81 patients were enrolled in this study from January 2009 to December 2010. Clinical, laboratory data were collected during the patient’s hospitalization. Sera were quantitatively tested for HBeAg and HBV DNA. HBV genotyping was made by real-time PCR. Results: Among the 81 patients, 60.5% had genotype B, 26.7% had genotype C and 8.6% had mixed genotype B-C. Prevalence of symptoms (fatigue, anorexia, insomnia...) was higher in genotype C than in genotype B. Genotype C patients had positivity higher HBeAg than genotype B patients (56% vs. 38,8%, p <0.05). The rate of HBV DNA > 107 copies/mL was higher in genotype C group than in genotype B group (36% vs. 28,6%, p > 0.05). Conclusions: Most of the patients had genotypes B or C. Patients with genotype C had positive HBeAg and may be related to higher serological HBV DNA level than in genotype B.


Antioxidants ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 77
Author(s):  
Jing-Hua Wang ◽  
Sung-Bae Lee ◽  
Dong-Soo Lee ◽  
Chang-Gue Son

Oxidative stress plays a pivotal role in the progression of chronic hepatitis B; however, it is unclear whether the status of blood oxidative stress and antioxidant components differs depending on the degree of hepatic fibrosis. To explore the relationship between oxidative stress/antioxidant capacity and the extent of hepatic fibrosis, fifty-four subjects with liver fibrosis (5.5 ≤ liver stiffness measurement (LSM) score ≤ 16.0 kPa) by chronic hepatitis B virus (HBV) were analyzed. From the analysis of eight kinds of serum oxidative stress/antioxidant profiles and liver fibrosis degrees, the level of total antioxidant capacity (TAC) reflected a negative correlation with the severity of hepatic fibrosis (Pearson correlation, r = −0.35, p = 0.01). Moreover, TAC showed higher sensitivity (73.91%) than the aspartate transaminase (AST) to platelet ratio index (APRI, 56.52%) in the receiver operating characteristic (ROC) curves. Interestingly, the TAC level finely reflected the fibrosis degree in inactive carriers (HBV DNA < 2000 IU/mL), while the APRI did in active carriers (HBV DNA > 2000 IU/mL). In conclusion, TAC is a promising biomarker for evaluating the progression of liver fibrosis in patients with HBV, and this finding may indicate the involvement of TAC-composing factors in the pathogenesis of hepatic fibrosis in chronic HBV carriers.


Cytokine ◽  
2021 ◽  
pp. 155525
Author(s):  
Walid Ben Selma ◽  
Ahmed Baligh Laribi ◽  
Sana Alibi ◽  
Jalel Boukadida

Vaccine ◽  
2010 ◽  
Vol 28 (51) ◽  
pp. 8169-8174 ◽  
Author(s):  
Xuan-Yi Wang ◽  
Xin-Xin Zhang ◽  
Xin Yao ◽  
Jie-Hong Jiang ◽  
You-Hua Xie ◽  
...  

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