Last modified: 2014-03-31
Abstract
Background
The Hepatitis C virus (HCV) epidemic is fuelled by transmission in high-risk communities, notably people who inject drugs (PWID). In New South Wales (NSW), approximately 10,000 prisoners are incarcerated due to illegal drug use in which 30% have been infected with HCV. Despite the HCV incidence in NSW prisons, transmission dynamics remain unclear. In this study, we characterise HCV transmission in NSW prisons by integrating information from viral populations, spatiotemporal records and self-reported drug-injecting behaviour.
Methods
Blood samples and drug-injecting behaviour were collected from 79 subjects enrolled in the Hepatitis C Incidence and Transmission Study cohort. Phylogenetic analysis was performed on 35 gt1 and 49 gt3 E1-HVR1 viral sequence (657 nt). HCV viral evolution was explored by computing the pairwise genetic distance of sequences within-host and between-hosts in relation to the interval between sampling timepoints. Within-host genetic evolution was further analysed using next-generation sequencing. Transmission clusters were identified using PhyloPart, which implements a clustering detection algorithm based on the median patristic distance of any sub-tree. A detection threshold was fixed at 0.02 substitutions per site. Potential transmission events were identified from the clusters detected and validated using spatiotemporal records.
Results
Four clusters (2 in Gt1 and 2 in Gt3 subsets) were identified, along with five likely transmission events. From these, four events were supported by co-location and three events were concordant with self-reported drug-injecting behaviour. Analysing within-host E1HVR1 deep-sequencing data from two subjects shows that within-host evolution does not exceed 0.02 substitutions per site.
Conclusion
Quantitative analysis of early primary HCV infection suggests that strong selective pressures limit viral evolution during transmission. Despite the small data set, we have detected HCV transmission clusters in NSW prisons. This study demonstrates the role of within-host evolution in detecting HCV transmission events and the use of population genetics in HCV transmission analysis