Elevated expression and polymorphisms of SOCS3 influence patient response to antiviral therapy in chronic hepatitis C
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Summary
This summary is machine-generated.Genetic factors, specifically suppressor of cytokine signalling 3 (SOCS3) gene polymorphisms, influence hepatitis C treatment response. Higher SOCS3 levels are linked to non-response, suggesting its potential as a predictive biomarker.
Area Of Science
- Hepatology and Viral Immunology
- Pharmacogenomics and Genetic Biomarkers
Background
- Chronic hepatitis C virus (HCV) infection treatment response is multifactorial, influenced by virological, environmental, and genetic elements.
- Identifying genetic factors can improve prediction of treatment outcomes for hepatitis C.
Purpose Of The Study
- To investigate if specific gene expression and haplotype frequencies differentiate between non-responders (NRs) and sustained virological responders (SVRs) to antiviral therapy.
- To determine the role of suppressor of cytokine signalling 3 (SOCS3) gene polymorphisms in predicting treatment success for hepatitis C.
Main Methods
- Molecular marker discovery and validation in lymphoblastoid cell lines from 74 genotype 1b HCV patients.
- Association study of three single nucleotide polymorphisms (SNPs) in the SOCS3 gene (rs12952093, rs4969170, rs4969168) in 162 NRs and 184 SVRs.
- Analysis of SOCS3 expression levels and correlation with genetic variations and treatment response.
Main Results
- Significantly increased basal SOCS3 expression levels were observed in non-responder groups.
- A strong association was found between non-response and specific SOCS3 haplotypes (positively and negatively associated).
- The SOCS3 -4874 AA genotype was significantly associated with antiviral therapy failure and higher SOCS3 mRNA and protein levels.
Conclusions
- Basal SOCS3 levels and its genetic polymorphisms are significant factors influencing the outcome of antiviral treatment for hepatitis C.
- SOCS3, an inhibitor of interferon signaling pathways, emerges as a novel blood biomarker for predicting treatment response in hepatitis C patients.