Clinical and Data Coordinating Center (CDCC)]

临床和数据协调中心（CDCC）]

• 批准号: 10323176
• 负责人: OFER LEVY
• 金额: $ 210.3万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-07 至 2022-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10323176
• 关键词: Adult; Age; Antibodies; Antibody Response; BCG Live; Biological Assay; Biological Markers; Birth; Blood; Blood Volume; Cause of Death; Cell Compartmentation; Cells; Characteristics; Child; Clinical Data; Clinical Research; Complement; Complex; Data; Data Coordinating Center; Detection; Developing Countries; Development; Dose; Enrollment; Gambia; Gene Expression; Gene Proteins; Global Change; Health Benefit; Hepatitis; Hepatitis B Surface Antigens; Hepatitis B Vaccination; Hepatitis B Vaccines; Human; Immune; Immune response; Immunization; Immunization Programs; Immunize; In Vitro; Infant; Infection; Knowledge; Leukocytes; Life; Measures; Mediating; Modeling; Molecular; Morbidity - disease rate; Neonatal; Newborn Infant; Output; Papua New Guinea; Pathway interactions; Pattern; Phenotype; Plasma; Procedures; Proteins; Proteome; Proteomics; Public Health; RNA; Sampling; Signal Transduction; Site; Surface Antigens; System; Systems Biology; Technology; Testing; Time; Training; Translating; Vaccination; Vaccines; Validation; Variant; Whole Blood; Work; anti-hepatitis B; bioinformatics tool; biological systems; cohort; experience; functional status; global health; immunogenicity; immunological status; improved; in silico; in vivo; insight; mortality; neonatal hepatitis; novel; novel strategies; peripheral blood; predictive marker; protective efficacy; response; sample collection; tool; transcriptomics; vaccine development; vaccine response; vaccine-induced immunity; vaccinology

PROJECT SUMMARY Improvement of early life immunization requires a better understanding of vaccine-induced molecular pathways that underlie protective immunogenicity as Correlates of Protection (CoP). Systems vaccinology employing technologies that measure molecular changes (“OMICs”) has provided critical insights into the adult immune response to vaccination, but has yet to be applied to the youngest, despite their need for improved immunization. We will apply powerful OMIC tools to the neonatal immune response to Hepatitis B vaccination (HBV). HBV is an ideal model to define mechanisms of successful neonatal immunization because: a) HBV is highly effective (>90% protection) and has a well-characterized CoP (anti-hepatitis B surface antigen antibody (anti-HBs)); b) anti-HBs titres directly correlate with protection, i.e. the higher anti- HBs the better and more durable protection; c) anti-HBs titers after the fist (neonatal) dose correlate with titers after the last; d) anti-HBs levels vary widely between subjects; such inter-subject variability enables powerful systems vaccinology tools to extract meaningful correlations; e) the neonatal HBV response is sensitive to co-administration of Bacille Calmette-Guérin (BCG), which is routinely given together with HBV in the Expanded Program of Immunization (EPI); this offers the unique opportunity to characterize this in vivo perturbation via OMICs. Our chosen clinical study sites in the Gambia and Papua New Guinea are amongst the world's most experienced with respect to neonatal vaccinology. Here, newborns will be immunized with nothing (delayed), HBV, BCG or (HBV + BCG) and peripheral blood pre-/post-immunization collected for transcriptomic and proteomic analysis as well as immune phenotyping. Project 1 will develop and employ cutting edge, cross-platform bioinformatics tools to identify pathways associated with CoP. Project 2, will apply unbiased immune phenotyping analysis tools to the same samples and translate to host immune parameters the in silico derived OMICs signatures. In Project 3 key molecular signals will be dissected in vitro to establish cause and effect. We have optimized all assays to work with small blood volumes and demonstrated feasibility in our pilot of rapid enrollment, stringently controlled sample collection and processing yielding cogent data that already hint at distinct vaccine-induced responses. Our cross-platform validation and correlation with CoP in a cohort containing training- and test-sets as well as a validation cohort, will identify biomarkers predicting neonatal vaccine immunogenicity i) pre-vaccination (Overall Aim 1) and ii) post-vaccination (Overall Aim 2). Delineation of the relevant mechanisms in vitro (Overall Aim 3) complements the output of this HIPC. Overall, our work will identify vaccine-induced molecular pathways key for successful vaccine-induced neonatal immune responses, thereby enhancing and accelerating vaccine development for those in greatest need.

项目摘要 提高生命早期免疫需要更好地理解疫苗诱导的分子生物学效应。 作为保护性免疫原性的基础的途径作为保护相关物（CoP）。系统疫苗学 采用测量分子变化（“OMIC”）的技术已经提供了对 成年人对疫苗接种有免疫反应，但尚未应用于最年轻的人，尽管他们需要 改善免疫。我们将把强大的OMIC工具应用于新生儿对B型肝炎的免疫应答 疫苗接种（HBV）。HBV是确定新生儿免疫成功机制的理想模型 因为：a）HBV是高度有效的（>90%的保护），并具有良好的特征性CoP（抗B型肝炎 表面抗原抗体（抗-HBs））; B）抗-HBs滴度与保护直接相关，即抗-HBs滴度越高， 抗-HBs保护作用更好、更持久; c）首次（新生儿）给药后抗-HBs滴度与 最后一次之后的滴度; d）抗-HBs水平在受试者之间变化很大;这种受试者间的变化使得 强大的系统疫苗学工具，以提取有意义的相关性; e）新生儿HBV应答， 对卡介苗（BCG）联合给药敏感，BCG通常与HBV一起给药， 扩大免疫计划（EPI）;这提供了独特的机会，在体内表征这一点 通过OMIC进行扰动。我们在冈比亚和巴布亚新几内亚选择的临床研究中心是 世界上最有经验的新生儿疫苗学。在这里，新生儿将接种 无（延迟）、HBV、BCG或（HBV + BCG）和免疫前/免疫后采集的外周血 转录组学和蛋白质组学分析以及免疫表型分析。项目1将开发和使用 尖端的、跨平台的生物信息学工具，以识别与CoP相关的途径。项目2，将 将无偏的免疫表型分析工具应用于相同的样本，并将其转化为宿主免疫表型分析工具。 参数计算机推导的OMIC特征。在项目3中，关键的分子信号将在 建立因果关系我们已经优化了所有检测方法，以适用于小血容量， 在我们的快速入组、严格控制的样本采集和 处理产生令人信服的数据，已经暗示了不同的疫苗诱导的反应。我们的跨平台 在包含训练集和测试集的队列中验证和与CoP的相关性，以及验证 队列，将确定预测新生儿疫苗免疫原性的生物标志物i）接种前（总体目标1） 和ii）接种后（总体目标2）。体外相关机制的描述（总体目标3） 补充了这一重债穷国倡议的产出。总的来说，我们的工作将确定疫苗诱导的关键分子途径 用于成功的疫苗诱导的新生儿免疫应答，从而增强和加速疫苗 为最需要的人发展。