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 丙型肝炎病毒（HCV）感染，这是一个重大的临床，社会和经济 这对受感染的个人和整个社会都是一种负担。的结果 病毒感染是由病毒和宿主之间的相互作用决定的 免疫反应宿主遗传因素也可能有助于观察到的 疾病患病率、进展和治疗反应的差异， 非裔美国人（AA）和非西班牙裔白色（白色）人群。因此我们 提出一项全面的药物遗传学研究，以检验宿主 遗传因素有助于HCV的治疗反应和疾病进展 通过检查大量的免疫学候选物， 基因. 具体来说，我们提出了一个两阶段的设计：初始测试与多态 标记间距为3- 5 kb的15个候选基因中的每一个，然后是精细标记。 基于统计学显著性水平选择的那些基因的作图， 显著标志物的数量和来自第二样品的结果。三套 样本将用于评价对治疗和/或疾病的反应 进展：入组Virahep C试验的患者（N=400），患者 从试验中排除，但有疾病进展信息（N=400），和 NIDDK肝病科研究的患者（N=400）。遗传 后一个样本的关联结果将有助于决策， 哪些基因需要进行精细定位我们还将利用多个 分析方法来评估候选基因之间的关联， 结果变量：评估基因-基因相互作用，以及 基因-病毒/环境因素相互作用。此外，我们还建立了 通过基因分型控制人群分层的策略 群体特异性标记和评价群体结构。 通过全面覆盖重要的候选基因，利用多个 样本，并明确测试可能的混杂因素，这一建议 最大限度地提高了识别基因及其变体的机会， 有助于HCV感染对治疗的反应和疾病进展。 由于确定了这些宿主因素的遗传和调查 它们与HCV的分子相互作用，我们可能会获得更多关于HCV的见解， 致病机理，并为疫苗开发发现新的潜在靶点， 疗法

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.