Vaccination and infection: indicators of immunological health and responsiveness

描述（由申请人提供）：在本提案中，我们的目标是使用系统生物学方法来调查一系列不同疫苗的免疫反应性，包括季节性流感和新的大流行性H1N1 v、带状疱疹、麻疹和脑膜炎奈瑟菌。在流感和带状疱疹的情况下，我们也将能够直接比较对疫苗的免疫反应与对病原体本身的自然反应。这些研究将比较不同的年龄组-儿童，年轻人和老年人-寻找特定的标记物和免疫能力的测定，特别是那些可能在不同的病原体和年龄组中常见的。我们还将调查免疫系统受损或失调的个体对流感疫苗的反应，以了解这些个体如何偏离健康个体。我们将采用一个简化的模型，其中暴露于不同疫苗或传染病的个体的临床标本将在我们的人类免疫监测中心进行一系列基本免疫功能的测定，并进行几种“最先进”的测定，例如我们最近开发的高通量HLA测序技术，该技术能够同时从数百人中生成完整的HLA单倍型。我们还将进行选定的免疫球蛋白和T细胞受体库分析和组合肽-MHC四聚体分析，以有效地搜索信息性T细胞表位。我们将采用先进的生物信息学分析，例如我们的新细胞类型特异性SAM算法（csSAM），该算法使用细胞亚群信息从全血基因表达数据中获得更高的灵敏度，并开发新的生物信息学工具来询问我们在所有项目，试点和核心中丰富而复杂的数据库。

DESCRIPTION (provided by applicant): In this proposal, we aim to use a systems biology approach to survey immune responsiveness across a range of different vaccines including influenza, both seasonal and the new pandemic H1N1v, Herpes zoster, Measles, and the bacterium Neisseria meningitidis. In the case of influenza and Herpes zoster, we will also be able to directly compare the immune response to vaccines with those natural responses to the pathogen itself. These investigations will compare different age groups-children, young adults, and the elderly-to look for specific markers and assays of immune competence and especially those that might be common across different pathogens and age groups. We will also survey the influenza vaccine responses of individuals with impaired or dysregulated immune systems in order to see how these might deviate from healthy individuals. We will employ a streamlined model in which clinical specimens from individuals exposed to different vaccines or infectious diseases will all be assayed for an array of basic immune functions in our Human Immune Monitoring Center and also for several "state of the art" assays such as our recently developed high throughput HLA sequencing technique, which is able to generate complete HLA haplotypes from hundreds of people simultaneously. We will also perform selected Immunoglobulin and T Cell Receptor repertoire analysis and combinatorial peptide-MHC tetramer analysis to efficiently search for informative T cell epitopes. We will employ advanced bioinformatics analysis such as our new cell type specific SAM algorithms (csSAM), which use cell subset information to achieve much higher sensitivity from whole blood gene expression data as well as developing new bioinformatics tools to interrogate our rich and complex data base across all projects, pilots and cores.