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，但尚不清楚个人和人口为什么不同 保护它们免受流感感染。保护基础的因素可以在多个尺度上起作用，并且 因此，建立对保护的更完整的理解需要一种将数据集成到 人口，个体和分子水平。哪些因素会影响人群和个人流感风险 感染？个体对流感的抗体反应有何不同，哪些因素驱动了这些因素 差异？在这里，我建议确定过去感染，疫苗接种和抗原的相对影响 通过定量建模高分辨率来确定个体和人口易感性的演变 流行病学和免疫学数据。特别是，我旨在确定过去的流感感染在 塑造不同年龄组的敏感性，确定人类抗体反应的特定靶标 反对流感，并推断感染病史，疫苗接种和表位免疫原性的相对重要性 关于抗体特异性。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 并允许我们将干预措施针对最高风险的人群。该项目的成功需要培训 成员的先进计算和统计方法以及最先进的免疫学技术 芝加哥大学生态与进化与医学系的工作。这个跨学科和 协作培训环境将为获得更全面了解的坚实基础 流感与人类免疫系统之间的相互作用。