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: 10589800
• 负责人: OFER LEVY
• 金额: $ 154.65万
• 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/10589800
• 关键词: Acceleration; 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; Innate Immune Response; Intervention; Knowledge; Life; Liquid substance; Measures; Mediating; Medical; Memory; Modeling; Molecular; Molecular Profiling; Mucous Membrane; Newborn Infant; North America; Nose; Organ; PRTN3 gene; Pathway interactions; Pattern; Pediatric cohort; Phenotype; Physiological; Plasma; 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; 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; respiratory; response; risk prediction; 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.

项目摘要 迄今为止，定义和应用精度内型的努力仅限于对成年人的研究。然而， 早期生命中的免疫发育（理想）是动态的，并且个人之间有所不同，表明个人 与不同病理生理机制相对应的内型将依赖于年龄。我们建议 因此，一种新的方法，我们将研究定义明确的纵向童年队列并用于计算机 对现有和前瞻性收集的数据以及特定年龄特定的人体体外模型的综合分析 确定将理想从疾病内型转移到与之相关的疾病的系统的系统 健康。我们选择了三个临床终点来与系统生物学数据相关以确定理想 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）呼吸道感染代表了童年的最大负担 传染病; c）哮喘，一种免疫介导的呼吸道疾病，表现在 童年和造成重大健康负担。这些端点中的每一个都证明了实质性 个体间的可变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 将统一和研究由纵向儿童队列组成的理想元元素（IMC） 在北美，非洲和大洋洲招收。我们在纽约州罗切斯特的临床核心在全国 在儿童免疫本体发育研究中突出。项目（PR）1将采用尖端，交叉 - 平台集成生物信息学工具，以识别与临床终点相关的内型。 Pr2，威尔 将表观遗传分析工具应用于同一样品，并转化为托管免疫参数 有机硅的签名。在PR3中，将在PR3中剖析与内种型相关的生物标志物和途径 体外以建立因果关系，并鉴定剂（例如蛋白质，代谢物，辅助物，疫苗） 可能会将理想从不利的内型和有利的理想转移到良好的内部。我们已经优化了 样本比较测定，以使婴儿和我们已发表的初步数据启用系统生物学 表现出可行性，理想的稳健性，并通过临床状况提出不同的签名。我们的交叉 平台验证和与与临床表型相关的内型相关的相关性将确定 通过i）表征全身/粘膜中的理想和微生物组的预测性/可作用的生物标志物 车间（总体目标1），ii）识别内型特异性生物标志物（总目标2），确定 体外干预措施将理想的内型转向健康（总体目标3）。总体而言，我们将增强 并加速发现新方法来预测和预防儿童疾病。