Differentiation of acute from chronic hepatitis C virus infection by nonstructural 5B deep sequencing: A population‐level tool for incidence estimation. Issue 6 (18th March 2015) - Montoya, Vincent; Olmstead, Andrea D.; Janjua, Naveed Z.; Tang, Patrick; Grebely, Jason; Cook, Darrel; Richard Harrigan, P.; Krajden, Mel
<x xml:space="preserve">Abstract</x> The ability to classify acute versus chronic hepatitis C virus (HCV) infections at the time of diagnosis is desirable to improve the quality of surveillance information. The aim of this study was to differentiate acute from chronic HCV infections utilizing deep sequencing. HCV nonstructural 5B (NS5B) amplicons (n = 94) were generated from 77 individuals (13 acute and 64 chronic HCV infections) in British Columbia, Canada, with documented seroconversion time frames. Amplicons were deep sequenced and HCV genomic diversity was measured by Shannon entropy (SE) and a single nucleotide variant (SNV) analysis. The relationship between each diversity measure and the estimated days since infection was assessed using linear mixed models, and the ability of each diversity measure to differentiate acute from chronic infections was assessed using generalized estimating equations. Both SE and the SNV diversity measures were significantly different for acute versus chronic infections (P < 0.009). NS5B nucleotide diversity continued to increase for at least 3 years postinfection. Among individuals with the least uncertainty with regard to duration of infection (n = 39), the area under the receiver operating characteristic curve (AUROC) was high (0.96 for SE; 0.98 for SNV). Although the AUROCs were lower (0.86 for SE; 0.80 for SNV) when data for all individuals were included, they remain sufficiently high for epidemiological purposes. Synonymous mutations were the primary discriminatory variable accounting for over 78% of the measured genetic diversity. Conclusions: NS5B sequence diversity assessed by deep sequencing can differentiate acute from chronic HCV infections and, with further validation, could become a powerful population‐level surveillance tool for incidence estimation. (Hepatology 2015;61:1842–1850)