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A combination of genetic polymorphisms increases the risk of progressive disease in chronic hepatitis C

Abstract

Background: There is increasing interest in the influence of host genetic factors on hepatic fibrosis, and whether genetic markers can reliably identify subjects at risk of developing severe disease. We hypothesised that hepatitis C virus (HCV) infected subjects with progressive fibrosis, classified using strict criteria based on histology at biopsy in addition to disease duration would be more likely to inherit several genetic polymorphisms associated with disease progression compared with subjects with a low rate of disease progression.

Methods: We examined polymorphisms in eight genes that have been reported to have an association with hepatic fibrosis.

Results: Associations between polymorphisms in six genes and more rapidly progressing fibrosis were observed, with individual adjusted odds ratios ranging from 2.1 to 4.5. The relationship between rapidly progressing fibrosis and possession of ⩾3, ⩾4, or ⩾5 progression associated alleles was determined and the adjusted odds ratios increased with increasing number of progression associated alleles (9.1, 15.5, and 24.1, respectively). Using logistic regression analysis, a predictive equation was developed and tested using a second cohort of patients with rapidly progressing fibrosis. The predictive equation correctly classified 80% of patients in this second cohort.

Conclusions: This approach may allow determination of a genetic profile predictive of rapid disease progression in HCV and identify patients warranting more aggressive therapeutic management.

  • APOE, apolipoprotein E
  • BMI, body mass index
  • CCR5, CC chemokine receptor 5
  • CTLA4, cytotoxic T lymphocyte associated protein 4
  • HCV, hepatitis C virus
  • HFE, haemochromatosis gene
  • LDLR, low density lipoprotein receptor
  • MPO, myeloperoxidase
  • MTP, microsomal triglyceride transfer protein
  • PBMC, peripheral blood mononuclear cells
  • PCR, polymerase chain reaction
  • ROC, receiver operating characteristic curve
  • ROS, reactive oxygen species
  • SOD2, manganese superoxide dismutase 2
  • Th cells, T helper cells
  • genomic profiling
  • hepatic fibrosis
  • hepatitis C virus
  • liver

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