Evaluation of Regulatory T Cells in Chronic Hepatitis C Patients

Background: Although there have been significant improvements in treatment strategies, hepatitis C infection is still among the most critical public health problems worldwide. Upon entry of hepatitis C virus (HCV) into host liver cells, many antagonist immune responses are induced, including the production of regulatory T cells (Tregs). The main function of Tregs is coordinating an appropriate immune response, including suppression of this response once it is no longer needed. Tregs protect cells from immunopathologic damage of HCV-specific T cells but, on the other hand, cause viral persistence, cirrhosis and hepatocellular carcinoma (HCC). In this study, we aimed to determine whether the evaluation of Tregs in hepatitis C patients was a useful method for indicating disease chronicity.Materials and Methods: The peripheral blood samples were taken from sixty volunteers, including 30 non-cirrhotic chronic hepatitis C patients and 30 healthy controls selected from infectious diseases outpatient/clinic service applicants. Their CD4+CD25high FoxP3+CD152+CD127(low) Treg distributions were measured by flow cytometry, using recently identified markers combined.Results: Treg percentages of the subjects with hepatitis C infection (7.97 +/- 1.25) were significantly higher than those of the healthy control group (4.29 +/- 1.37) (p<0.05). Additionally, the percentages of Tregs were strongly correlated with HCV RNA load (r=0.725, p<0.05) as well as serum AFP levels (r=0.711, p<0.05).Conclusion: Tregs are thought to play an important role in the immunology of HCV infection, thereby providing a promising method for the prediction of disease prognosis and for new the

Automated summary

This study indicates that the percentage of Tregs in patients with hepatitis C infection is significantly higher than in healthy controls, and is strongly correlated with HCV RNA load and serum AFP levels. Tregs are believed to play a crucial role in the immunology of HCV infection, providing a promising method for predicting disease prognosis and new treatments.