Impact of cohort size and host factors on combined analysis of interleukin 28B rs12979860 and rs8099917 in hepatitis C virus infection§


  • Supported by the German Competence Network for Viral Hepatitis (Hep-Net), funded by the German Ministry of Education and Research (BMBF, Grant No. 01 KI 0437, Project No. 10.1.3 and Core Project No. 10.1 Genetic host factors in viral hepatitis and Genetic Epidemiology Group in viral hepatitis), by the EU-Vigilance network of excellence combating viral resistance (VIRGIL, Project No. LSHM-CT-2004-503359), and by the BMBF Project: Host and viral determinants for susceptibility and resistance to hepatitis C virus infection (Grant No. 01KI0787). Parts of the work were supported by an Australian Research Council Linkage Project Grant (LPO0990067), a National Health and Medical Research Council Grant (1006759) and the Robert W. Storr Bequest to the Sydney Medical Foundation, University of Sydney.

  • Author contributions: All authors contributed to data and sample collection, in different study centers, and provided critical review of the article.

  • §

    Potential conflict of interest: Nothing to report.

    Additional Supporting Information may be found in the online version of the article.

To the Editor:

We studied with interest the correspondence letter by Galmozzi et al.1 externally validating the findings about the impact of the combined genotyping of interleukin-28B (IL28B) polymorphisms rs12979860 and rs8099917 on the treatment outcome after interferon-based dual combination therapy.2 The authors genotyped 187 hepatitis C virus (HCV)-1 infected patients from an Italian cohort who received pegylated interferon and ribavirin. The overall genotype distribution of rs12979860 and rs8099917 and of the most prevalent combined genotypes rs12979860CC/rs8099917TT, rs12979860CT/rs8099917TT, and rs12979860CT/rs8099917TG were comparable to our cohort, as were the sustained virologic response (SVR) rates for the individual single nucleotide polymorphisms (SNPs). In contrast to our results, the authors were not able to confirm that carriers of the heterozygous genotype rs12979860CT benefit from the additional determination of rs8099917 for SVR prediction (rs12979860CT/rs8099917TT versus rs12979860CT/rs8099917TG: 43% vs 39%).

As the authors suggest, these discrepancies may be caused by divergences in sample size and differences in patient cohorts. To show this, we randomized our HCV samples into nine groups with different sample sizes, starting with 10% of the initial cohort. Significant differences between SVR rates of patients carrying the genotypes rs12979860CT/rs8099917TT and rs12979860CT/rs8099917TG were primarily observed in cohorts with ∼400 patients (Table 1), pointing out the importance of sample sizes. We further analyzed the effects of baseline parameters such as age, HCV RNA level, HCV subtype, gender, and fibrosis stage on the SVR rates of genotype rs12979860CT/rs8099917TT and rs12979860CT/rs8099917TG (Supporting Table 1). Again, it becomes obvious that the impact of additional genotyping of rs8099917 on the prediction of SVR is improved in patients with heterozygous genotype of rs12979860 who have high baseline HCV RNA levels (P = 3.7 × 10−5), HCV subtype 1a (P = 3.3 × 10−5), or severe fibrosis stages (P = 0.001), being female (P = 0.023), or of younger age (P = 0.029). Thus, the different patient characteristics most likely explain the differences in the SVR rates.

Table 1. Characteristics of the Randomized Cohorts and SVR Rates of Heterozygous Genotype rs12979860CT With Additional Genotyping of rs8099917
Random Sample SizeSample NumberMean Age ±SDMaleHCV RNA ≥400.000 IU/mLSevere FibrosisSVRP-value
rs12979680CT/ rs8099917TTrs12979680CT/ rs8099917TG
  1. SD, standard deviation; IU, international units; SVR, sustained virological response; P < 0.05 considered to be statistically significant.


From that, one possibly may conclude that two SNPs are good in large cohorts but not relevant for clinical practice. However, the idea of large studies is to inform individual clinical practice. Our results derived from a large cohort suggest that algorithms and models that include both rs12979860 and rs809917 as well as baseline parameters and viral factors are informative to guide therapeutic decision making.3

Janett Fischer Ph.D.*, Stephan Böhm X.X.*, Jacob George X.X.†, Christoph Sarrazin X.X.‡, Thomas Berg X.X.*, * Department of Hepatology, Clinic of Gastroenterology and Rheumatology, Universitätsklinikum Leipzig, Leipzig, Germany, † Storr Liver Unit, Westmead Hospital and Westmead Millennium Institute, University of Sydney, Sydney, Australia, ‡ Department of Internal Medicine I, J. W. Goethe-University Hospital, Frankfurt, Germany.