Systems Biology to Identify Biomarkers of Neonatal Vaccine Immunogenicity
Systems Biology to Identify Biomarkers of Neonatal Vaccine Immunogenicity
批准号:
10265672
负责人:
OFER LEVY
金额:
$227.57万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-05-11 至 2023-11-30
关键词:
AdultAgeAntibodiesAntibody ResponseBCG LiveBiological AssayBiological MarkersBirthBloodBlood VolumeCause of DeathCell CompartmentationCellsCharacteristicsChildClinical ResearchComplementComplexDataDetectionDeveloping CountriesDevelopmentDoseEnrollmentGambiaGene ExpressionGene ProteinsGlobal ChangeHealth BenefitHepatitisHepatitis B Surface AntigensHepatitis B VaccinationHepatitis B VaccinesHumanImmuneImmune responseImmunizationImmunization ProgramsImmunizeIn VitroInfantInfectionKnowledgeLeukocytesLifeMeasuresMediatingModelingMolecularMorbidity - disease rateNeonatalNewborn InfantOutputPapua New GuineaPathway interactionsPatternPhenotypePlasmaProceduresProteinsProteomeProteomicsPublic HealthRNASamplingSignal TransductionSiteSurface AntigensSystemSystems BiologyTechnologyTestingTimeTrainingTranslatingVaccinationVaccinesValidationVariantWhole BloodWorkanti-hepatitis Bbioinformatics toolbiological systemscohortexperiencefunctional statusglobal healthimmunogenicityimmunological statusimprovedin silicoin vivoinsightmortalityneonatal hepatitisnovelnovel strategiesperipheral bloodpredictive markerprotective efficacyresponsesample collectiontooltranscriptomicsvaccine developmentvaccine responsevaccine-induced immunityvaccinology
中文摘要
项目总结
改善早期生命免疫需要更好地理解疫苗诱导的分子
作为保护相关性(COP)的保护性免疫原性基础的途径。系统疫苗学
使用测量分子变化的技术(“组学”)提供了对
成人对疫苗的免疫反应,但尚未应用于最年轻的人,尽管他们需要
加强免疫接种。我们将应用强大的基因组学工具来研究新生儿对乙肝的免疫反应
接种疫苗(乙肝病毒)。乙肝病毒是确定新生儿成功免疫机制的理想模型
因为:a)乙肝病毒是高效的(90%保护),并具有良好的抗乙型肝炎病毒特性
表面抗原抗体(抗-HBs);b)抗-HBs滴度与保护直接相关,即较高的抗-HBs
HBs具有更好和更持久的保护作用;c)第一次接种(新生儿)后的抗-HBs滴度与
最后一个之后的滴度;d)不同受试者的抗-HBs水平差异很大;这种受试者之间的变异性使
强大的系统疫苗学工具,以提取有意义的相关性;e)新生儿乙肝病毒反应是
对卡介苗(BCG)联合给药敏感,卡介苗通常与乙肝病毒一起服用
扩大免疫计划(EPI);这提供了在体内描述这一特征的独特机会
通过组学的微扰。我们在冈比亚和巴布亚新几内亚选择的临床研究地点包括
世界上在新生儿疫苗接种方面最有经验的人。在这里,新生儿将接种疫苗
免疫前后无(延迟)、乙肝、卡介苗或(乙肝+卡介苗)及外周血采集
转录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、跨平台的生物信息学工具,用于识别与COP相关的途径。项目2,将
将无偏免疫表型分析工具应用于相同的样本,并转化为宿主免疫
计算机衍生组学签名中的参数。在项目3中,关键的分子信号将在
在体外建立因果关系。我们已经优化了所有的分析,以适用于小血量和
在我们的试点中证明了快速招生、严格控制样本采集和
处理产生了令人信服的数据,这些数据已经暗示了不同的疫苗诱导反应。我们的跨平台
验证和与包含训练集和测试集的队列中的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记物I)接种前(总体目标1)
和二)疫苗接种后(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的产出。总体而言,我们的工作将确定疫苗诱导的分子通路的关键
对于成功的疫苗诱导的新生儿免疫反应,从而增强和加速疫苗
为那些最有需要的人提供发展。
英文摘要
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.
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