Immune development in early life (IDEAL) shapes vaccine response, respiratory infectious diseaseand asthma

生命早期的免疫发育 (IDEAL) 影响疫苗反应、呼吸道传染病和哮喘

• 批准号: 10435035
• 负责人: OFER LEVY
• 金额: $ 166.59万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-10 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10435035
• 关键词: Adjuvant; Adult; Africa; Age; Asthma; Australasia; Bacteria; Bioinformatics; Biological Assay; Biological Markers; Biological Models; Birth; Blood Donations; Blood Volume; Cells; Childhood; Clinical; Communicable Diseases; Coupled; Data; Development; Disease; Enrollment; Epigenetic Process; Goals; Greek; Growth; Health; Human; Human body; Immune; Immune system; Immunity; Immunologics; Immunomodulators; In Vitro; Individual; Infant; Infection; Intervention; Knowledge; Life; Liquid substance; Measures; Mediating; Medical; Memory; Modeling; Molecular; Molecular Profiling; Mucous Membrane; Newborn Infant; North America; Nose; PRTN3 gene; Pathway interactions; Pattern; Pediatric cohort; Phenotype; Physiological; Plasma Cells; Positioning Attribute; Predisposition; Prognostic Marker; Protective Agents; Proteins; Proteomics; Publishing; Resistance; Respiratory Disease; Respiratory Tract Infections; Risk; Sampling; Shapes; System; Systems Biology; Testing; Training; Translating; Vaccines; Validation; adaptive immune response; age related; biobank; bioinformatics tool; body system; clinical phenotype; cohort; experience; gut microbiome; high risk; in silico; in utero; in vitro Model; infancy; infection risk; insight; inter-individual variation; metabolomics; microbiome; multiple omics; novel strategies; predictive marker; prevent; programs; prospective; protein metabolite; respiratory; response; specific biomarkers; tool; vaccine response

PROJECT SUMMARY To date, efforts to define and apply precision endotyping has been limited to studies of adults. However, immune development in early life (IDEAL) is dynamic and varies between individuals suggesting that endotypes corresponding to distinct pathophysiological mechanisms will be age-dependent. We propose therefore a novel approach in which we will study well-defined longitudinal childhood cohorts and use in silico integrative analyses of existing and prospectively collected data coupled with age-specific human in vitro model systems to identify agents that redirect IDEAL away from disease endotypes towards those associated with health. We have selected three clinical endpoints to correlate with systems biology data to identify IDEAL endotypes: a) vaccine responsiveness, as vaccines are the most important biomedical intervention to reduce childhood disease; b) respiratory infection which represents the greatest burden of childhood infectious disease; and c) asthma, an immune-mediated respiratory disease which manifests in childhood and results in substantial health burden. Each of these endpoints demonstrates substantial inter-individual variability enabling powerful systems biology tools to extract meaningful correlations. We will harmonize and study an IDEAL Meta-Cohort (IMC) comprised of longitudinal childhood cohorts enrolled in North America, Africa and Australasia. Our Clinical Core in Rochester, NY, is nationally prominent in the study of childhood immune ontogeny. Project (PR) 1 will employ cutting edge, cross- platform integrative bioinformatics tools to identify endotypes associated with clinical endpoints. PR2, will apply epigenetic analysis tools to the same samples and translate to host immune parameters the in silico-derived signatures. In PR3, key endotype-associated biomarkers and pathways will be dissected in vitro to establish cause and effect and identify agents (e.g., proteins, metabolites, adjuvants, vaccines) that may redirect IDEAL away from unfavorable endotypes and towards favorable ones. We have optimized sample-sparing assays to enable systems biology in infants and our published preliminary data demonstrate feasibility, robust IDEAL, and suggest distinct signatures by clinical status. Our cross- platform validation and correlation with endotypes correlating with clinical phenotypes will identify predictive/actionable biomarkers by i) characterizing IDEAL and microbiome in systemic/mucosal compartments (Overall Aim 1), ii) identifying endotype-specific biomarkers (Overall Aim 2), identifying in vitro interventions that re-direct IDEAL endotypes towards health (Overall Aim 3). Overall, we will enhance and accelerate discovery of new approaches to predict and prevent childhood disease.

项目概要 迄今为止，定义和应用精确内分型的努力仅限于成人研究。然而， 生命早期的免疫发育（IDEAL）是动态的，并且因个体而异，这表明 与不同病理生理机制相对应的内型具有年龄依赖性。我们建议 因此，我们将采用一种新颖的方法来研究明确定义的纵向童年队列并在计算机中使用 对现有和前瞻性收集的数据以及特定年龄的人体体外模型进行综合分析 系统来识别将 IDEAL 从疾病内型转向与疾病相关的内型的药物 健康。我们选择了三个临床终点来与系统生物学数据相关联，以确定 IDEAL 内型：a）疫苗反应性，因为疫苗是最重要的生物医学干预措施 减少儿童疾病； b) 呼吸道感染是儿童时期最大的负担 传染病; c) 哮喘，一种免疫介导的呼吸道疾病，表现为 童年并导致沉重的健康负担。这些终点中的每一个都表明了实质性 个体间的变异性使强大的系统生物学工具能够提取有意义的相关性。我们 将协调和研究由纵向童年队列组成的理想元队列 (IMC) 在北美、非洲和澳大利亚注册。我们位于纽约州罗彻斯特的临床核心是全国性的 在儿童免疫个体发育研究中很突出。项目 (PR) 1 将采用尖端、跨领域技术 平台综合生物信息学工具，用于识别与临床终点相关的内型。 PR2，将 将表观遗传分析工具应用于相同的样本，并将其转化为宿主免疫参数 硅派生签名。在 PR3 中，将剖析关键的内型相关生物标志物和通路 体外确定因果关系并识别能够 可能会将 IDEAL 从不利的内型转向有利的内型。我们已经优化了 使婴儿系统生物学成为可能的样本保留测定以及我们发布的初步数据 证明可行性、稳健的 IDEAL，并根据临床状态提出不同的特征。我们的跨 平台验证以及与临床表型相关的内型的相关性将确定 预测/可操作的生物标志物，通过 i) 表征系统/粘膜中的 IDEAL 和微生物组 区室（总体目标 1），ii) 识别内型特异性生物标志物（总体目标 2），识别 将 IDEAL 内型重新引导至健康的体外干预措施（总体目标 3）。总体而言，我们将加强 并加速发现预测和预防儿童疾病的新方法。