Next-generation sequencing for the clinical management of hepatitis C virus infections: does one test fits all purposes?

Abstract

While the prospect of viral cure is higher than ever for individuals infected with the hepatitis C virus (HCV) due to ground-breaking progress in antiviral treatment, success rates are still negatively influenced by HCV’s high genetic variability. This genetic diversity is represented in the circulation of various genotypes and subtypes, mixed infections, recombinant forms and the presence of numerous drug resistant variants among infected individuals. Common misclassifications by commercial genotyping assays in combination with the limitations of currently used targeted population sequencing approaches have encouraged researchers to exploit alternative methods for the clinical management of HCV infections. Next-generation sequencing (NGS), a revolutionary and powerful tool with a variety of applications in clinical virology, can characterize viral diversity and depict viral dynamics in an ultra-wide and ultra-deep manner. The level of detail it provides makes it the method of choice for the diagnosis and clinical assessment of HCV infections. The sequence library provided by NGS is of a higher magnitude and sensitivity than data generated by conventional methods. Therefore, these technologies are helpful to guide clinical practice and at the same time highly valuable for epidemiological studies. The decreasing costs of NGS to determine genotypes, mixed infections, recombinant strains and drug resistant variants will soon make it feasible to employ NGS in clinical laboratories, to assist in the daily care of patients with HCV.

Keywords:

• NGS
• HCV
• full-genome
• genotyping
• drug resistance

Acknowledgments

The authors gratefully thank Dr Bram Vrancken for his assistance in preparing Figure 2, and Lore Vinken for valuable discussions with respect to Figure 3.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Part of this research was funded by a project of the FWO [Fonds Wetenschappelijk Onderzoek Vlaanderen – G0B2317N]. Marijn Thijssen is a SB PhD fellow at FWO Vlaanderen and Mahmoud Reza Pourkarim is supported by a postdoctoral grant from the FWO Vlaanderen.