Distribution of hepatitis C virus genotypes in a diverse US integrated health care population

ArticleinJournal of Medical Virology 84(11):1744-50 · November 2012with51 Reads
DOI: 10.1002/jmv.23399 · Source: PubMed
Abstract
Hepatitis C virus (HCV) genotypes influence response to therapy, and recently approved direct-acting antivirals are genotype-specific. Genotype distribution information can help to guide antiviral development and elucidate infection patterns. HCV genotype distributions were studied in a diverse cross-section of patients in the Northern California Kaiser Permanente health plan. Associations between genotype and race/ethnicity, age, and sex were assessed with multivariate logistic regression models. The 10,256 patients studied were median age 56 years, 62% male, 55% White non-Hispanic. Overall, 70% were genotype 1, 16% genotype 2, 12% genotype 3, 1% genotype 4, <1% genotype 5, and 1% genotype 6. Blacks (OR 4.5 [3.8-5.5]) and Asians (OR 1.2 [1.0-1.4]) were more likely to have genotype 1 than 2/3 versus non-Hispanic Whites. Women less likely had genotype 1 versus 2/3 than did men (OR 0.86 [0.78-0.94]). Versus non-Hispanic Whites, Asians (OR 0.38 [0.31-0.46]) and Blacks (OR 0.73 [0.63-0.84]) were less likely genotype1a than 1b; Hispanics (OR 1.3 [1.1-1.5]) and Native Americans (OR 1.9 [1.2-2.8]) more likely had genotype 1a than 1b. Patients age ≥65 years less likely had genotype 1a than 1b versus those age 45-64 (OR 0.34 [0.29-0.41]). The predominance of genotype 1 among all groups studied reinforces the need for new therapies targeting this genotype. Racial/ethnic variations in HCV genotype and subtype distribution must be considered in formulating new agents and novel strategies to successfully treat the diversity of hepatitis C patients. J. Med. Virol. 84:1744-1750, 2012. © 2012 Wiley Periodicals, Inc.
    • "We have inferred the fitness landscape for the RNA-dependent RNA polymerase—nonstructural protein 5B (NS5B)—that is known to be an important target for natural and therapeutic control [7, 41, 42]. We consider HCV genotype 1a, the most prevalent infecting genotype in the United States, which is responsible for 35%–50% of infections domestically434445 and ∼60% worldwide [46]. As described below, we validate our fitness landscape in comparisons with experimental measurements and clinical data, and combine our models with population level immunological data to design cytotoxic T lymphocyte (CTL) immunogens predicted to have high efficacy and broad coverage in the United States population. "
    [Show abstract] [Hide abstract] ABSTRACT: Hepatitis C virus (HCV) afflicts 170 million people worldwide, 2%–3% of the global population, and kills 350 000 each year. Prophylactic vaccination offers the most realistic and cost effective hope of controlling this epidemic in the developing world where expensive drug therapies are not available. Despite 20 years of research, the high mutability of the virus and lack of knowledge of what constitutes effective immune responses have impeded development of an effective vaccine. Coupling data mining of sequence databases with spin glass models from statistical physics, we have developed a computational approach to translate clinical sequence databases into empirical fitness landscapes quantifying the replicative capacity of the virus as a function of its amino acid sequence. These landscapes explicitly connect viral genotype to phenotypic fitness, and reveal vulnerable immunological targets within the viral proteome that can be exploited to rationally design vaccine immunogens. We have recovered the empirical fitness landscape for the HCV RNA-dependent RNA polymerase (protein NS5B) responsible for viral genome replication, and validated the predictions of our model by demonstrating excellent accord with experimental measurements and clinical observations. We have used our landscapes to perform exhaustive in silico screening of 16.8 million T-cell immunogen candidates to identify 86 optimal formulations. By reducing the search space of immunogen candidates by over five orders of magnitude, our approach can offer valuable savings in time, expense, and labor for experimental vaccine development and accelerate the search for a HCV vaccine. Abbreviations: HCV—hepatitis C virus, HLA—human leukocyte antigen, CTL—cytotoxic T lymphocyte, NS5B—nonstructural protein 5B, MSA—multiple sequence alignment, PEG-IFN—pegylated interferon.
    Full-text · Article · Nov 2015
    • "Furthermore, there is variation in HCV genotypes: up to six types and more than 80 subtypes exist.[20] In the United States, 70% of cases have HCV genotype 1a/1b, 15-20% genotype 2, about 10% genotype 3, 1% genotype 4 and less than 1% genotypes 5 and 6.[21] In contrast, in Egypt, the prevalence of genotype 4a/4b is 91%; among those, 63% are genotype 4a.222324 "
    [Show abstract] [Hide abstract] ABSTRACT: The Child-Turcotte-Pugh score (CTP) is the standard tool for hepatic reserve assessment in hepatocellular carcinoma (HCC). Recently, we reported that integrating plasma insulin-like growth factor-1 (IGF-1) level into the CTP score was associated with better patient risk stratification in two U.S. independent cohorts. Our current study aimed to validate the IGF-CTP score in patients who have different demographics and risk factors. We prospectively recruited 100 Egyptian patients and calculated their IGF-CTP score compared to CTP score. C-index was used to compare the prognostic significance of the two scoring systems. Finally, we compared our results with our U.S. cohorts published data. IGF-CTP score showed significant better patient stratification compared to CTP score in the international validation cohort. Among CTP class A patients, who usually considered for active treatment and clinical trial enrollment, 32.5% were reclassified as IGF-CTP class B with significantly shorter OS than patients reclassified as class A with hazard ratio [HR] = 6.15, 95% confidence interval [CI] = 2.18 -17.37. IGF-CTP score showed significantly better patient stratification and survival prediction not only in the U.S. population but also in international validation population, who had different demographics and HCC risk factors.
    Full-text · Article · May 2015
    • "Within these, a variable number of sub-groupings are apparent. HCV genotype 1 is most prevalent genotype in the United States, Europe and Japan (Manos et al., 2012; Qattan and Emery, 2012; Wu et al., 2012). HCV genotype 2 is dominant in Korea and Taiwan. "
    [Show abstract] [Hide abstract] ABSTRACT: High degree of sequence variations are present throughout in the coding regions of Hepatitis C virus (HCV) genome. However, a high degree of sequence conservation within the 5'untranslated region (UTR) has made this region a target of choice for most of detection assays based on nucleic acid amplification. The current study was designed to determine the HCV genotypes in samples of HCV chronically infected patients in Pakistan. Specific primers targeting 5'UTR region were designed, which were then used for both amplification and sequencing of all isolates. All HCV isolates were sequenced and genotyped based upon phylogenetically informative regions within the 5'UTR of HCV genome. Out of 15 samples, 9 (60 %) samples 5'UTR of HCV genome was successfully sequenced. However, only 6 (66.7 %) samples were assigned genotypes based upon sequence comparison with reference sequences of database. Results of this study revealed that five isolates that were assigned genotype 3a, showed 97 to 99 % sequence conservation to isolates of genotype 3a previously reported from Pakistan as well as from rest of world, grouped together and coincided with their positions in the phylogenetic tree. Moreover, one isolate that was assigned genotype 4a, showed 97 % sequence conservation to isolates of genotype 4a previously reported from rest of world, coincided with its position in the phylogenetic tree. Our findings suggest that direct sequencing analysis of the 5'UTR of HCV genome is a sensitive and efficient approach of HCV genotyping; it may be adopted as a routine diagnostic procedure for HCV genotyping in clinical settings.
    Full-text · Article · Jan 2015 · Oncotarget
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