Uncovering the dynamics of human pathogens using high throughput multiplexed serological tools

使用高通量多重血清学工具揭示人类病原体的动态

• 批准号: 10028788
• 负责人: Isabel Rodríguez-Barraquer
• 金额: $ 40.21万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10028788
• 关键词: Antibody Repertoire; Antibody Response; Antigens; Biological Assay; Birth; Cohort Studies; Collaborations; Communicable Diseases; Country; Cross-Sectional Studies; Data; Data Analyses; Disease; Epidemiology; Evolution; Goals; Immune; Immunologics; Individual; Infection; Intervention; Methodology; Methods; Modeling; Performance; Population; Population Study; Predisposition; Recording of previous events; Research; Research Personnel; Resources; Risk; Sampling; Serologic tests; Serological; Serum; Software Tools; Technology; Time; Translating; Validation; Work; analytical method; disorder control; human pathogen; insight; multiple data sources; new technology; open source; pathogen; programs; response; simulation; tool; transmission process

PROJECT SUMMARY Understanding the distribution and dynamics of human pathogens is fundamental to control infectious diseases by guiding where and when to target resources. Until now, however, efforts to understand the dynamics of most pathogens have been conducted in isolation, focusing on one specific disease at a time. Over the past years, high throughput multiplexed serological assays have become available, allowing to simultaneously quantify antibody responses against 100s and even 1000s of antigens, from a single sample. These novel technologies offer unprecedented opportunities to (1) study the dynamics of multiple pathogens simultaneously, (2) characterize immune profiles of populations, and (3) evaluate hypotheses around immunological interactions within and between pathogen groups. Numerous methodological and computational challenges remain in terms of how to make meaningful epidemiological inferences from these new tools. We have been developing methods to analyze and estimate key transmission parameters from multiple sources of data, with a focus on serological assays. This proposal will expand these lines of work, developing tools and analytic methods necessary to translate the promise of high throughput serology into mechanistic insights about pathogen dynamics. We will leverage existing collaborations with researchers at the forefront of these technologies, as well as detailed population studies (including longitudinal birth cohorts and cross-sectional studies) that have collected and characterized serum samples to apply and evaluate these platforms in over 10 countries. We aim to develop and validate a suite of robust computational and analytical pipelines with the goal of (1) reconstructing the longitudinal evolution of antibody repertoires in individuals within and across pathogen groups as a function of infection history, and (2) characterizing transmission histories and immune profiles of populations. In developing our analytical pipelines, we will perform extensive simulation studies to evaluate the performance of different models under multiple assumptions of how the data is generated. We will then perform data analysis and inference to reconstruct transmission histories, susceptibility profiles of populations to multiple pathogens, estimate attack rates, and characterize longitudinal evolution of antibody responses. This will be the most comprehensive assessment, and validation, of population and individual serological responses across pathogen groups, performed to date. Through these projects, we will also develop a suite of open-source software/tools to disseminate our methods and allow other researchers to analyze their data and gain insight into immune landscapes population risk profiles. This project will create tools that use high-throughput multiplexed serological data to answer fundamental questions on the dynamics and interactions of different pathogen groups and provide insights that can be used by policymakers to guide infectious disease control efforts.

项目摘要 了解人类病原体的分布和动态是控制传染性疾病的基础。 通过指导在何处和何时使用资源来预防疾病。然而，直到现在， 大多数病原体的动态是孤立进行的，集中在一种特定的疾病上 一次。 在过去的几年中，高通量多重血清学测定已经变得可用，使得能够进行高通量多重血清学测定。 为了同时定量针对100甚至1000种抗原的抗体应答， 单样本。这些新技术提供了前所未有的机会，（1）研究动态 （2）描述人群的免疫特征，以及（3） 评估病原体组内和组间免疫相互作用的假设。 在如何使有意义的 从这些新工具中得出流行病学推论。 我们一直在开发分析和估计关键传输参数的方法， 多个数据来源，重点是血清学检测。该提案将扩大这些产品线， 工作，开发必要的工具和分析方法，以实现高通量的承诺 将血清学转化为病原体动力学的机制见解。我们将利用现有的合作 研究人员站在这些技术的最前沿， （包括纵向出生队列和横断面研究）， 在10多个国家应用和评估这些平台。我们致力于发展和 验证一套强大的计算和分析管道，目标是（1）重建 病原体组内和病原体组间个体中抗体库的纵向进化， 感染史的功能，以及（2）表征感染者的传播史和免疫状况 人口。在开发分析管道时，我们将进行广泛的模拟研究， 评估不同模型在多个假设下的性能， 生成的.然后，我们将进行数据分析和推理，以重建传输历史， 人群对多种病原体的易感性概况，估计发病率，并表征 抗体反应的纵向进化。这将是最全面的评估， 验证不同病原体群体和个体的血清学应答， 约会通过这些项目，我们还将开发一套开源软件/工具， 传播我们的方法，并允许其他研究人员分析他们的数据， 免疫景观人口风险概况。 该项目将创建使用高通量多重血清学数据来回答 关于不同病原体群体的动力学和相互作用的基本问题，并提供 决策者可以利用这些见解来指导传染病控制工作。