Back

Clinical mechanism of ribavirin action in Hepatitis C treatment: insights from the STOPHCV-1 randomised trial

Moradi Marjaneh, M.; Badhan, A.; Chai, H.; Hadfield, O.; Chen, Y.; Wang, Z.; Thomson, E. C.; Taylor, G. P.; Walker, A. S.; Ansari, M. A.; Barnes, E.; Cooke, G. S.

2026-04-15 infectious diseases
10.64898/2026.04.14.26350846 medRxiv
Show abstract

BackgroundRibavirin is a guanosine analogue with clinical antiviral activity against a range of RNA viruses including hepatitis C virus (HCV), respiratory syncytial virus and Lassa virus. Several potential mechanisms of action have been proposed, but there is limited data supporting them clinically. MethodsWe studied 196 HCV-infected participants from a trial of short-course directly antiviral therapy (STOPHCV-1) which included a factorial randomisation to ribavirin versus no ribavirin. Deep sequencing of the HCV genome was performed on samples with detectable viremia from three time-points: baseline (n = 191), day 3 of treatment (n = 25) and post-treatment failure (n = 47). ResultsRibavirin exposure significantly increased total mutational load at treatment failure (P = 0.0065) and enriched classical ribavirin-associated transitions, including G[->]A (P = 0.026) and C[->]U (P = 0.004), along with other key changes including A[->]G (P = 0.005), U[->]C (P = 0.023), C[->]G (P = 0.010), and U[->]A (P = 0.026). Ribavirins mutational signature was broad, not dominated by G-related changes. Region-specific analyses demonstrated this increase was broadly distributed across the viral genome, without strong evidence for protection of specific regions. Non-synonymous to synonymous mutation ratios (dN/dS) rose at day 3 (P = 5.5e-5) before declining at failure (P = 8.5e-7), with trends toward higher dN/dS in the ribavirin group at day 3 (P = 0.06). ConclusionsRibavirin acts as a potent in vivo mutagen, driving viral populations toward genome-wide diversity rather than selecting a few highly fit drug-resistant clones. These findings support an error-catastrophe model.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.