Identifying determinants of human immunity against influenza: a multiscale approach

确定人类流感免疫力的决定因素：多尺度方法

• 批准号: 9760507
• 负责人: Philip Arevalo
• 金额: $ 6.53万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9760507
• 关键词: Affect; Affinity; Amino Acid Substitution; Antibodies; Antibody Avidity; Antibody Response; Antibody Specificity; Binding; Birth; Cells; Cessation of life; Chicago; Computing Methodologies; Data; Data Set; Ecology; Effectiveness; Environment; Epidemiology; Epitopes; Evolution; Exposure to; Foundations; Future; Glycoproteins; Hemagglutinin; Hospitalization; Human; Immune; Immune response; Immune system; Immunity; Immunologic Techniques; Immunologics; Individual; Infection; Influenza; Intervention; Link; Machine Learning; Medicine; Modeling; Molecular; Neuraminidase; Pattern; Policies; Population; Populations at Risk; Predisposition; Prevention; Preventive measure; Property; Proteins; Public Health; Recording of previous events; Resolution; Risk; Role; Seasons; Shapes; Site; Specificity; Statistical Methods; Surface Antigens; Testing; Training; United States; Universities; Vaccination; Variant; Virus; Work; adaptive immune response; age group; base; cohort; combat; design; immunogenicity; imprint; improved; individual response; infection risk; influenzavirus; insight; learning strategy; member; novel; predictive modeling; seasonal influenza; success; universal influenza vaccine

Project Summary Seasonal influenza is a significant public health concern, yet it is not clear why individuals and populations differ in their protection against influenza infection. The factors underlying protection can act at multiple scales, and thus building a more complete understanding of protection requires an approach that integrates data at the population, individual, and molecular levels. What factors influence population and individual risk of influenza infection? How different are the antibody responses of individuals against influenza and what factors drive those differences? Here, I propose to identify the relative influence of past infection, vaccination, and antigenic evolution on determining both individual and population susceptibility by quantitatively modeling high-resolution epidemiological and immunological data. In particular, I aim to determine the role of past influenza infection in shaping the susceptibility of different age groups, identify the specific targets of the human antibody response against influenza, and infer the relative importance of infection history, vaccination, and epitope immunogenicity on antibody specificity. This work will have a significant impact on our ability to predict future influenza infection and allow us to target interventions toward the most at-risk populations. Success of this project requires training in advanced computational and statistical methods and state-of-the-art immunological techniques by members of the Departments of Ecology & Evolution and Medicine at the University of Chicago. This interdisciplinary and collaborative training environment will provide a strong foundation for gaining more complete understanding of the interactions between influenza and the human immune system.

项目摘要 季节性流感是一个重大的公共卫生问题，但目前尚不清楚为什么个人和人群的差异 对流感感染的保护作用。保护背后的因素可以在多个层面上发挥作用， 因此，要更全面地了解保护工作，就需要采取一种方法， 群体、个体和分子水平。哪些因素影响人群和个人患流感的风险 感染？个体对流感的抗体反应有多大差异，是什么因素驱动这些差异？ 差异？在这里，我建议确定过去的感染，疫苗接种和抗原的相对影响， 通过高分辨率定量建模确定个体和群体易感性的进展 流行病学和免疫学数据。特别是，我的目标是确定过去的流感感染在其中的作用 塑造不同年龄段的易感人群，确定人体抗体反应的特异性靶点 并推断感染史、疫苗接种和表位免疫原性的相对重要性 抗体的特异性。这项工作将对我们预测未来流感感染的能力产生重大影响 并使我们能够针对风险最高的人群进行干预。这个项目的成功需要培训 先进的计算和统计方法以及最先进的免疫学技术 他是芝加哥大学生态与进化系和医学系的教授。这一跨学科和 协作培训环境将为更全面地了解 流感和人体免疫系统之间的相互作用。