Multiple approaches to genetic sequencing to identify hepatitis C virus reinfection among people who inject drugs

The burden of hepatitis C virus (HCV) among persons who inject drugs is determined by dynamics of infection, spontaneous clearance, treatment clearance, treatment failure, and reinfection. Although analysis of HCV sequences is often used to infer the net contribution of these factors, those inferences are complicated by the quasispecies distribution and continued evolution of infection within each host. We used deep sequencing by Nanopore to study sequences of persons with and without self-reported HCV treatment. Even after years of evolution, sequences from the same person were always more similar than sequences from different persons and a Hamming distance threshold of 0.064 reliably differentiated (AUC 0.999) the groups. By comparison to sequences before treatment, identification of unique sequences (distance > 0.064) after treatment reliably identified 8 of 28 instances of post-treatment reinfection. There were multiple causes for finding the same (distance < 0.064) sequence after intended treatment including not commencing or abbreviating treatment, pharmacological treatment failure, or possibly reinfection from same source. These data underscore the value of HCV sequence analysis in understanding viral dynamics among PWID.