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Deconvolution and reconstruction of immune histories to enhance infectious disease prevention and vaccination strategies and optimize surveillance efforts

Deconvolution and reconstruction of immune histories to enhance infectious disease prevention and vaccination strategies and optimize surveillance efforts
免疫历史的反卷积和重建,以加强传染病预防和疫苗接种策略并优化监测工作
批准号:
9794872
负责人:
Michael J. Mina
金额:
$39.88万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-16 至 2024-08-31
关键词:
AgeAntibodiesAntibody RepertoireAppointmentBacteriaBiologyBirthBloodBlood donorClinicalClinical PathologyCollaborationsCommunicable DiseasesComputing MethodologiesCoupledCulicidaeDataData AnalysesDengueDetectionDevelopmentDisciplineDisease SurveillanceDoctor of PhilosophyEarly DiagnosisEducational process of instructingElderlyEpidemicEpidemiologyEpitopesExposure toFacultyFrequenciesFundingFutureGenderGeographyGoalsGrowthHealthHospitalsHumanImmuneImmunologicsImmunologyImprove AccessIndividualInfectionInterdisciplinary StudyInvestigationJournalsLaboratoriesLaboratory TechniciansLeadershipLinkLongevityLongitudinal cohortMaternal antibodyMathematicsMeaslesMeasurementMeasuresMedicalMentorsMethodsMolecular BiologyMolecular ComputationsNicaraguaOutputParasitesPathologyPhage DisplayPhysician ExecutivesPopulationPopulation SurveillancePositioning AttributePostdoctoral FellowPrevention MeasuresPrevention strategyPropertyPublic HealthPublic Health SchoolsPublicationsRecording of previous eventsReportingResearchResearch PersonnelResourcesRunningSalivaSamplingSeriesSerologicalSpecimenSpottingsStatistical ModelsStructureStudentsSystemTechnologyTimeTrainingTravelVaccinationVaccinesVascular blood supplyWagesWaterWomanWorkZika Virusbaseclinically relevantco-infectioncomputerized toolscostenvironmental changeepidemiological modelexperiencegraduate studenthuman pathogenimprovedinfluenza virus vaccineinterdisciplinary approachlife historymathematical modelmedical schoolsmembermortalitymultidisciplinarynovelpathogenpathogen exposureprofessorprogramsreconstructionrecruitskillssuccesstenure tracktoolvaccination strategyvector mosquitovirtual

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中文摘要
翻译
项目总结 传染病仍然是对人类健康的最大威胁之一。新的流行病随着越来越多的人出现 由于旅行的便利,频率促进了传播,环境变化改变了 无法预测的方式。与此同时,疫苗正在越来越多地控制许多主要的人类病原体。然而, 这些进步的潜力只有通过准确地衡量和量化 传染病横跨许多病原体和规模,从个人到全球人口, 并涵盖相关或不相关病原体的相互作用和潜在的意外后果。 总体目标是将分子生物学和计算工具的新发展联系起来,以 从根本上提高传染病监测和研究水平。AIM 1将建立在之前报道的 噬菌体展示系统,并对其进行优化,用于传染病监测。抗体噬菌体展示 通过病原体表位识别检测和分析传染病和公共卫生谱系 监测)将:实现对接触所有人类病原体的血清学监测,包括细菌, 寄生虫和蚊子媒介,同时来自可获得的样本,即唾液和干血点; 将区分与密切相关的病原体(即寨卡病毒和登革热)的暴露,并估计自 感染或接种疫苗。重要的是,它将进行优化,以便在低资源环境下使用,并且只需使用 现有技术的成本。目标2将通过EPI示踪剂(表位)的开发来改进疫情检测 基于通过全面表位识别跟踪匿名样本)。EPI-Tracer将使用 摘自(1)的PADERNS曲目提取和构建了流行病学上强大的“虚拟纵向队列” 来自包含“隐藏的”系列样本的横截面样本集(即80%的美国血液供应来自 来自重复捐赠者)。由于Epi-Tracer在PADERNS数据上运行,因此它将同时启用重建 对过去和当前流行病的早期发现。目标3将阐明病原体暴露的生活史。 跨越年龄(从出生前到老年人)、时间、性别和地理位置:以前所未有的详细程度量化病原体 攻击率,疫苗对非目标病原体的异源影响,并衡量疫苗的寿命和衰弱 抗体,包括母源抗体,以改进疫苗接种和控制战略。 这些目标将通过多学科方法实现,包括分子生物学和 噬菌体展示系统,通过合作进行健壮的纵向样本筛选,最重要的是,仔细 发展数学和统计模型,将生物学与个体和种群水平联系起来 推论。一旦完成,这些工具、方法和数据将可用于公共卫生机构和传染病 疾病研究人员,为检测或控制现有和新的病原体开辟了道路。
英文摘要
PROJECT SUMMARY Infectious diseases remain among the greatest threats to human health. Novel epidemics occur with increasing frequency as ease of travel facilitates spread, and environmental changes alter underlying dynamics in unpredictable ways. At the same time, vaccines are increasingly controlling many major human pathogens. Yet, the potential of these advances can only be fully realized with a means to accurately measure and quantify the landscape of infectious diseases across many pathogens and scales, from the individual to the global population, and encompassing interactions and potential unintended consequences across related or unrelated pathogens. The overall objectives are to bridge novel developments in molecular biology and computational tools to fundamentally improve infectious disease surveillance and research. Aim 1 will build on a previously reported phage display system, and optimize it for infectious disease surveillance. PADERNS (Phage display for Antibody repertoire Detection and profiling via pathogen Epitope RecognitioN for infectious disease and public health Surveillance) will: enable serological surveillance for exposures to all human pathogens, including bacteria, parasites and mosquitos vectors, simultaneously, from accessible samples, i.e. saliva and dried blood spots; will discriminate exposures from closely related pathogens (i.e. Zika and Dengue) and estimate time since infection or vaccination. Importantly, it will be optimized for use in low resource settings and at a fraction of the cost of current technologies. Aim 2 will improve epidemic detection with development of Epi-TRACER (Epitope based TRacking of Anonymous samples via Comprehensive Epitope Recogntion). Epi-TRACER will use PADERNS repertoires from (1) to extract and construct epidemiologically powerful ‘virtual longitudinal cohorts’ from cross-sectional sample sets that contain ‘hidden’ serial samples (i.e. 80% of the US blood supply comes from repeat donors). Because Epi-TRACER runs on PADERNS data, it will simultaneously enable reconstruction of past, and early detection of current epidemics. Aim 3 will elucidate the life-histories of pathogen exposures across ages (pre-birth to elderly), time, genders and geographies to: quantify in unprecedented detail pathogen attack rates, heterologous effects of vaccines on off-target pathogens, and measure the longevity and waning of antibodies, including maternally derived antibodies, to improving vaccination and control strategies. These aims will be accomplished through a multi-disciplinary approach involving molecular biology and phage-display systems, robust longitudinal sample curation through collaborations, and, crucially, careful development of mathematical and statistical models to link the biology to individual and population level inference. Once complete, the tools, methods and data will be available to public health agencies and infectious disease researchers, opening the way to a step change in detection or control of existing and novel pathogens.
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Deconvolution and reconstruction of immune histories to enhance infectious disease prevention and vaccination strategies and optimize surveillance efforts
  • 批准号:
    10018944
  • 项目类别:
  • 资助金额:
    $39.88万
  • 财政年份:
    2019
  • 负责人:
    Michael J. Mina
  • 依托单位:
海外基金