Accurate Genetic Detection of Hepatitis C Virus Transmissions in Outbreak Settings

Abstract

Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections are associated with unsafe injection practices, drug diversion, and other exposures to blood, being difficult to detect and investigate. Here, we developed and validated a simple approach for molecular detection of HCV transmissions in outbreak settings. We obtained sequences from the HCV hypervariable region 1 (HVR1) using End-Point Limiting-Dilution (EPLD) from 127 cases involved in 32 epidemiologically defined HCV outbreaks and 193 individuals with unrelated HCV strains. We compared several types of genetic distances and calculated a threshold using minimal Hamming distances that identifies transmission clusters in all tested outbreaks with 100% accuracy. The approach was also validated on sequences from 239 individuals obtained using next-generation sequencing, showing the same accuracy as EPLD. In average, nucleotide diversity of the intra-host population was 6.2-times greater in the source than in any incident case, allowing the correct detection of transmission direction in 8 outbreaks for which source cases were known. A simple and accurate distance-based approach for detecting HCV transmissions developed here streamlines molecular investigation of outbreaks, thus improving the public health capacity for rapid and effective control of hepatitis C.

A latent class approach to identify multi‐risk profiles associated with phylogenetic clustering of recent hepatitis C virus infection in Australia and New Zealand from 2004 to 2015

“…Phylogenetic analysis of HCV NS5B sequences from HIV‐negative GBM receiving PrEP in Amsterdam demonstrated GBM‐specific HCV clusters containing both HIV‐positive and HIV‐negative individuals . Interventions implemented because of real time detection of phylogenetic signals in HCV are being developed and evaluated in the Netherlands and the United States , and may be useful in Australia to reduce transmission of HCV and investigate HCV outbreaks.…”

Intelligent Network DisRuption Analysis (INDRA): A targeted strategy for efficient interruption of hepatitis C transmissions

“…Availability of transmission networks enables the development of targeted strategies for elimination of HCV infections in high-risk communities. ITN used in this study (Ramachandran et al, 2016) was generated by GHOST, a new computational and molecular technology for automatic detection of HCV transmission networks from next-generation sequence data (Campo et al, 2015; Longmire et al, 2017). Here, we used this network for the development and evaluation of targeted approaches for preventing prevention of new HCV infections in two epidemiological settings: (1) long-established infection with many HCV strains as was observed in a PWID community during investigation in Indiana and (2) a hypothetical rapid spread of a single HCV strain as observed during an outbreak.…”

“…GHOST (Campo et al, 2015; Longmire et al, 2017; Rytsareva et al, 2017) was used to genetically characterize HCV strains and detect a transmission network. GHOST generates networks where 2 nodes representing infected individuals are linked by transmission if the minimal Hamming distance between any pair of HCV HVR1 sequences obtained from these individuals is below a relatedness threshold of 3.77% (Campo et al, 2015). We used this HCV transmission network (ITN) as a case study (Fig.…”

“…Here, we take advantage of a complex HCV transmission network, which was recently identified among PWID in Indiana (Conrad et al, 2015; Peters et al, 2016; Ramachandran et al, 2016) using the Global Hepatitis Outbreak and Surveillance Technology (GHOST) (Campo et al, 2015; Longmire et al, 2017; Rytsareva et al, 2017), to devise and evaluate a new targeted, network-based strategy for reducing circulation and dissemination of HCV infection in 2 epidemiological settings: (1) long-established HCV infection as was observed in a PWID community during investigation in Indiana (Peters et al, 2016) and (2) a hypothetical rapid spread of a single HCV strain as observed during an outbreak.…”

Fast estimation of genetic relatedness between members of heterogeneous populations of closely related genomic variants

“…Consider two sets T 1 and T 2 each containing N DNA or RNA sequences of length L. The similarity join problem consists in locating the set P of all pairs of sequences, with one sequence from T 1 and the other from T 2 , within an edit distance or Hamming distance defined by the specified threshold t. In molecular epidemiology, this computational problem needs to be solved for detection of viral transmissions from sequences of intra-host viral variants sampled from infected individuals [1,2]. Viral populations, for which the minimal inter-sample distance does not exceed the threshold, are considered to be potentially linked by transmission [1], while the number of pairs in P may suggest the time since a transmission event [3]. The related genetic network construction problem aims to build a graph with vertices corresponding to sequences from a given dataset T and edges corresponding to all pairs of sequences with an edit or Hamming distance less than the threshold t. This problem arises in studying and analysis of viral populations [4] or antibody repertoires [5].…”