Hepatitis C: host determinants of progression and respo*

描述(由申请人提供)： 在美国，大约有270万人患有慢性丙型肝炎 病毒(丙型肝炎病毒)感染，这是一个重要的临床、社会和经济问题 感染者和整个社会的负担。一场比赛的结果 病毒感染由病毒与宿主之间的相互作用决定。 免疫反应。宿主遗传因素也可能对观察到的 在疾病患病率、进展和治疗反应方面的差异 非裔美国人(AA)和非西班牙裔白人(白人)人口。因此，我们 提出一项全面的药物遗传学研究，以检验宿主 遗传因素对丙型肝炎病毒治疗反应和疾病进展的影响 通过检测大量免疫学候选感染个体 基因。 具体地说，我们提出了一个两阶段设计：使用多态进行初始测试 15个候选基因中每一个的标记间距为3-5kb，然后是精细 基于统计显著性水平选择的那些基因的图谱， 显著标记的数量，以及第二个样本的结果。三套 样本将用于评估对治疗和/或疾病的反应。 进展：参加Virahep C试验的患者(N=400)，患者 被排除在试验之外，但有疾病进展信息(N=400)，以及 在NIDDK肝病科研究的患者(N=400)。基因 后一样本的关联结果将有助于决策 哪些基因需要通过精细定位进行后续研究。我们还将利用多个 评估候选基因和基因之间关联性的分析方法 结果变量：评估基因-基因相互作用，以及 基因-病毒/环境因素的相互作用。此外，我们还内置了 通过基因分型控制人口分层的策略 种群特异性标记和评价种群结构。 通过全面覆盖重要候选基因，利用几个 样本，并明确测试可能的混杂因素，这项建议 使识别基因及其变种的机会最大化 有助于丙型肝炎病毒感染的治疗反应和疾病进展。 由于从基因上识别了这些宿主因素并研究了 他们与丙型肝炎病毒的分子相互作用，我们可能会对丙型肝炎病毒有更多的了解 致病机制和发现疫苗开发和新的潜在靶点 心理治疗。

DESCRIPTION (provided by applicant): In the United States, approximately 2.7 million people have chronic hepatitis C virus (HCV) infection, which is a significant clinical, social, and economic burden for the infected individual and for society as a whole. The outcome of a viral infection is determined by the interaction between the virus and the host immune response. Host genetic factors may also contribute to observed differences in disease prevalence, progression, and treatment response between the African American (AA) and non-Hispanic white (white) populations. Thus, we propose a comprehensive pharmacogenetic study to test the hypothesis that host genetic factors contribute to treatment response and disease progression of HCV infected individuals by examining a large number of immunological candidate genes. Specifically, we propose a two-stage design: initial testing with polymorphic markers spacing at 3-5kb for each of 15 candidate genes, followed by fine mapping of those genes selected based on statistical significance levels, number of significant markers, and results from a second sample. Three sets of samples will be used to evaluate response to therapy and/or disease progression: patients enrolled in the Virahep C trial (N=400), patients excluded from the trial but with disease progression information (N=400), and patients studied at NIDDK Liver Disease Section (N=400). The genetic association results from the latter sample will aid in decision making as to which genes to follow-up with fine mapping. We will also utilize multiple analytic approaches to evaluate associations between candidate genes and outcome variables: evaluating gene-gene interaction, and gene-viral/environmental factor interaction. In addition, we have built in strategies for controlling population stratification by genotyping additional population specific markers and evaluating population structure. By covering important candidate genes comprehensively, utilizing several samples, and explicitly testing possible confounding factors, this proposal maximizes the opportunity to identify the genes and their variants that contribute to the response to therapy and disease progression in HCV infection. As a result of identifying these host factors genetically and investigating their molecular interactions with HCV, we may gain additional insights into HCV pathogenesis and uncover new potential targets for vaccine development and therapy.