Genetics and hepatitis C treatment: towards a personalized treatment?

Chronic HCV (hepatitis C virus) infection is an important cause of liver cirrhosis and hepatocellular carcinoma worldwide. HCV-related cirrhosis is the main indication for liver transplantation in our geographical area. Thus, treatment of this disease represents an important economical burden for the Health Care System. Current treatment of hepatitis C consists of pegylated interferon and ribavirin: only half of the patients achieve a sustained virological response after treatment. Factors related to the virus and the host influence response to treatment. Polymorphisms near the gene IL28B (encoding interferon-λ-3) have been recently identified as strong predictors of spontaneous HCV clearance in acute infection and of response to antiviral treatment in chronic hepatitis C. The aim of this article is to review the genetic studies that have emerged during the last months and its clinical implications, as well as to emphasize how Genetics is gaining importance in the management of liver diseases.     

Non-invasive candidate protein signature predicts hepatic venous pressure gradient reduction in cirrhotic patients after sustained virologic response

Background and Aims

A reduction in hepatic venous pressure gradient (HVPG) is the most accurate marker for assessing the severity of portal hypertension and the effectiveness of intervention treatments. This study aimed to evaluate the prognostic potential of blood-based proteomic biomarkers in predicting HVPG response amongst cirrhotic patients with portal hypertension due to Hepatitis C virus (HCV) and had achieved sustained virologic response (SVR).

Methods

The study comprised 59 patients from two cohorts. Patients underwent paired HVPG (pretreatment and after SVR), liver stiffness (LSM), and enhanced liver fibrosis scores (ELF) measurements, as well as proteomics-based profiling on serum samples using SomaScan® at baseline (BL) and after SVR (EOS). Machine learning with feature selection (Caret, Random Forest and RPART) methods were performed to determine the proteins capable of classifying HVPG responders. Model performance was evaluated using AUROC (pROC R package).

Results

Patients were stratified by a change in HVPG (EOS vs. BL) into responders (greater than 20% decline in HVPG from BL, or <10 mmHg at EOS with >10 mmHg at BL) and non-responders. LSM and ELF decreased markedly after SVR but did not correlate with HVPG response. SomaScan (SomaLogic, Inc., Boulder, CO) analysis revealed a substantial shift in the peripheral proteome composition, reflected by 82 significantly differentially abundant proteins. Twelve proteins accurately distinguished responders from non-responders, with an AUROC of .86, sensitivity of 83%, specificity of 83%, accuracy of 83%, PPV of 83%, and NPV of 83%.

Conclusions

A combined non-invasive soluble protein signature was identified, capable of accurately predicting HVPG response in HCV liver cirrhosis patients after achieving SVR.