Why the study?
Do NS5B protein polymorphisms (E124K and I85V) predict early viral clearance in patients with genotype 1b chronic hepatitis C and high viremia treated with interferon and ribavirin?
Do NS5B protein polymorphisms (E124K and I85V) predict early viral clearance in patients with genotype 1b chronic hepatitis C and high viremia treated with interferon and ribavirin?
Polymorphisms E124K and I85V in the NS5B protein may predict early viral clearance in patients with genotype 1b chronic hepatitis C treated with interferon and ribavirin.
NS5B E124K/I85V may predict early clearance on interferon-ribavirin; hypothesis-generating and requires prospective validation before any clinical use.
Although randomized trials have shown enhancement of efficacy for combination therapy with interferon (IFN) alpha-2b and ribavirin compared with IFN monotherapy as first-line treatment for chronic hepatitis C, infection with genotype 1b and high viremia are still associated with significantly low response rates compared with non-1 genotypes and low viremia. We analysed amino acid sequences of the viral RNA-dependent RNA polymerase (RdRP) or nonstructural protein 5B (NS5B), responsible for ribavirin misincorporation into RNA products in patients with genotype 1b-related chronic hepatitis C and high viremia, and examined the relationship between such RdRp polymorphisms, and the initial decline in viral load induced by combination therapy with IFN-alpha and ribavirin. Substitution of glutamic acid to lysine at the 124th position (E124K) and of isoleucine to valine at the 85th position (I85V) were found to be closely associated with a potent decline of viral load and viral clearance at 8 weeks of treatment (five of five patients, coincidence rate 100%). In conclusion, our results suggest that the polymorphisms of E124K and I85V identified in NS5B protein are crucial for early viral clearance in patients with genotype 1b and high viremia by combination therapy with IFN and ribavirin, and that detection of amino acid sequence motifs might enable prediction of clinical efficacy.
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Kumagai et al. (2004) studied this question.
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