Hepatitis C virus genetic association to rate of liver fibrosis progression

Hepatitis C virus (HCV) is a major cause of liver disease world-wide and the leading cause of liver transplantation in developed countries. There are 7 major genotypes divided into >100 subtypes, with genotype 1 being responsible for the majority of infections in the US. Several risk factors predisposing patients to rapid progression of liver fibrosis have been identified. However, to date, there are no conclusive studies supporting the role of HCV genetic heterogeneity in progression of liver disease. Here, consensus sequences of the HCV 1b Core, NS3 and NS5b genomic regions obtained from patients with known rate of fibrosis progression (RFP), who have been identified through a study of cohorts of hepatitis C patients with (n=22) and without (n=20) liver transplantation, were analyzed. All HCV sequences were linked to RFP and transplantation status. Based on RFP all patients were classified into 2 classes with rapid (RP) and slow (SP) progression to fibrosis. A set of Bayesian networks (BN) and linear projection (LP) models was generated using nucleotide (nt) sequences and nt physicochemical properties, such as hydrophobicity, polarity, dipole moment, surface area and stacking area, to examine HCV genetic association to RFP. Both types of models consider inter-relationships among polymorphic nt sites and associate them to RFP. Clustering of HCV variants based on physicochemical properties in LP graphs as well as BN analysis of nt sequences revealed similarity among HCV variants sampled from patients of same RFP class. Especially tight clustering was observed for HCV variants from SP class in LP model. Both models allow for the identification of the most RFP-relevant genetic features of HCV. Models constructed using these features classified HCV strains into 2 RFP classes with the 85%-93% accuracy in validation assays regardless of the transplantation status, thus indicating a significant robustness of the models and suggesting a potential application of the identified genetic features as markers for detection of RFP. This is the first report of HCV genetic markers strongly associated with RFP. The apparent HCV genetic association to yearly RFP in all patients studied here has significant implications for understanding the contribution of HCV genetic diversity to RFP and offers a new framework for molecular surveillance of the HCV-related disease and viral diseases in general.