PLoS ONE (Jan 2013)

Influence of vitamin D-related gene polymorphisms (CYP27B and VDR) on the response to interferon/ribavirin therapy in chronic hepatitis C.

  • Elena García-Martín,
  • José A G Agúndez,
  • María L Maestro,
  • Avelina Suárez,
  • Marta Vidaurreta,
  • Carmen Martínez,
  • Cristina Fernández-Pérez,
  • Luis Ortega,
  • José M Ladero

DOI
https://doi.org/10.1371/journal.pone.0074764
Journal volume & issue
Vol. 8, no. 9
p. e74764

Abstract

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Vitamin D exerts immunomodulatory effects on the host response against infection with hepatitis C virus (HCV). This study was performed to assess the putative influence of polymorphisms in vitamin D-related genes on the response to antiviral therapy in patients with chronic hepatitis C (CHC).Single nucleotide polymorphisms (SNPs) in CYP27B-1260 gene promoter (rs10877012AC) and in vitamin D receptor (VDR) gene rs2228570TC, rs1544410CT, rs7975232AC and rs731236AT were analyzed in a cohort of 238 Caucasian CHC patients treated with pegylated interferon (Peg-IFN) plus ribavirin (RBV). Multivariate analyses were performed to exclude confounding effects of well-known baseline predictors of response to therapy (HCV genotype and load, IL28B genotype, age, and GGT and serum cholesterol).Three SNPs at the VDR gene (rs1544410, rs7975232 and rs731236) were in strong linkage disequilibrium, with the CCA haplotype predicting therapeutic failure [Odds ratio 2.743; (95% C.I. 1.313-5.731), p = 0.007]. The carrier state of the VDR rs2228570 T allele was inversely related to the probability of therapeutic failure [Odds ratio 0.438; 95 C.I. (0.204-0.882), p = 0.021]. No relation existed between CYP27B-1260 rs10877012 polymorphism and response to therapy. The area under the operating curve (AUROC) based on the model including all variables significantly related to the response to therapy was 0.846 (95% confidence interval = 0.793-0.899).VDR gene polymorphisms are independently related to the response to Peg-IFN+RBV therapy in chronic hepatitis C and could be used as complementary biomarkers of response when included in a prediction algorithm in association with demographic, virologic, biochemical and genetic traits.