Gut 58:846-858 doi:10.1136/gut.2008.166348
  • Recent advances in basic science

Gene expression and hepatitis C virus infection

Open Access
  1. T Asselah1,2,3,
  2. I Bièche4,5,
  3. A Sabbagh4,5,
  4. P Bedossa6,
  5. R Moreau1,2,3,
  6. D Valla1,2,3,
  7. M Vidaud4,5,
  8. P Marcellin1,2,3
  1. 1
    INSERM, U773, Centre de Recherche Bichat-Beaujon CRB3, Paris, France
  2. 2
    Université Denis Diderot-Paris 7, Site Bichat, France
  3. 3
    Service d’hépatologie, Hôpital Beaujon, Clichy, France
  4. 4
    INSERM, U745, Université René Descartes, Paris, France
  5. 5
    Service de Génétique Moléculaire, Hôpital Beaujon, Clichy, France
  6. 6
    Service d’Anatomie-Pathologie, Hôpital Beaujon, Clichy, France
  1. Dr T Asselah, Service d’Hépatologie, Hôpital Beaujon, 100 Bd du Gl Leclerc, 92118 Clichy, France; tarik.asselah{at}
  • Revised 27 October 2008
  • Accepted 18 November 2008
  • Published Online First 11 December 2008


Hepatitis C virus (HCV) is a major cause of chronic liver disease, with about 170 million people infected worldwide. Up to 70% of patients will have persistent infection after inoculation, making this disease a significant cause of morbidity and mortality.

The severity of disease varies widely, from asymptomatic chronic infection to cirrhosis and hepatocellular carcinoma. Since the discovery of HCV, the treatment of hepatitis C has considerably improved. Recently, combination of pegylated interferons with ribavirin gives a response rate of about 55%. Treatment is indicated in patients with moderate or severe fibrosis. The tolerability of combination treatment is relatively poor, with a frequent flu-like syndrome and an impaired quality of life.

In addition to viral and environmental behavioural factors, host genetic diversity is believed to contribute to the spectrum of clinical outcomes in HCV infection. The sequencing of the human genome, together with the development of high-throughput technologies that measure the function of the genome, have afforded unique opportunities to develop profiles that can distinguish, identify and classify discrete subsets of disease, predict the disease outcome or predict the response to treatment. This paper reviews the published literature on gene expression associated with HCV infection (HCV infection, fibrosis progression), and also according to response to treatment.


  • Competing interests: None.