4.5 Article

High sensitivity assay using serum sample for IL28B genotyping to predict treatment response in chronic hepatitis C patients

Journal

HEPATOLOGY RESEARCH
Volume 40, Issue 10, Pages 956-962

Publisher

WILEY-BLACKWELL
DOI: 10.1111/j.1872-034X.2010.00702.x

Keywords

hepatitis C virus; IL28B; pegylated interferon-alpha plus ribavirin; single nucleotide polymorphism typing

Funding

  1. Ministry of Health, Labor and Welfare of Japan

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Aim: Recent human genome-wide association studies (GWAS) revealed a strong association between IL28B gene variation and the pegylated interferon-alpha with ribavirin (PEG-IFN-alpha/RBV) treatment response in chronic hepatitis C patients. Two single nucleotide polymorphisms (SNP), rs8103142 and rs11881222 located in the IL28B gene, were found in significant association with the viral clearance. The present study employed these SNPs to develop a new accessible screening method allowing identification of potential non-responders before starting the therapy. Methods: Primer sets were designed to amplify rs8103142 and rs11881222 fragments from genomic DNA extracted from serum samples. This method was validated using microarray typing (GWAS) and applied for genotyping of 68 hepatitis C virus-infected patients with PEG-IFN-alpha/RBV treatment at baseline. Results: In comparison with GWAS, the screening method showed 100% and 95.6% accuracy in typing of rs8103142 and rs11881222, respectively, indicating incomplete specificity but 100% of sensitivity in both. Genotyping by both SNP showed that 53 (77.9%), 14 (20.6%) and one (1.5%) of the patients were of major homozygous, heterozygous and minor homozygous type, respectively. The majority (85%) of homozygous patients exhibited response to therapy in contrast to heterozygous patients (29%). Among all genotyped only one case was found with the minor homozygous genotype which had late virological response to therapy before relapsing. Conclusion: This study described a highly sensitive assay that can be useful in determining SNP genotypes as well as in predicting the response to IFN-based treatment.

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