Topological Mapping of Immune, Microbiota, Metabolomic and Clinical Phenotypes to Reveal ME/CFS Disease Mechanisms - Clinical Research Project

免疫、微生物群、代谢组学和临床表型的拓扑图绘制以揭示 ME/CFS 疾病机制 - 临床研究项目

• 批准号: 10248307
• 负责人: Peter Nicholas Robinson
• 金额: $ 65.88万
• 依托单位: JACKSON LABORATORY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-30 至 2024-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10248307
• 关键词: Address; Algorithms; Bacteria; Basic Science; Bioinformatics; Biological Markers; Biometry; Blood; CRISPR/Cas technology; Cells; Characteristics; Chronic; Chronic Fatigue Syndrome; Clinical; Clinical Research; Color; Communities; Complex; Computer Models; Custom; Data; Disease; Disease Progression; Disease stratification; Etiology; Fatigue; Flow Cytometry; Follow-Up Studies; Genomics; Goals; Immune; Immune System Diseases; Immune response; Immune system; Immunologics; Inflammation; Investigation; Link; Longitudinal prospective study; Machine Learning; Metabolic; Metabolism; Metadata; Microbe; Modality; Modeling; Molecular; Ontology; Pain; Pathway interactions; Patients; Predisposition; Prospective cohort; Research Design; Research Project Grants; Risk Factors; Role; Sample Size; Sampling; Services; Severities; Severity of illness; Shotguns; Stimulus; Subgroup; Surveys; Symptoms; Techniques; Testing; The Jackson Laboratory; Therapeutic; Time; Universities; Utah; Validation; Work; candidate marker; clinical phenotype; cohort; data repository; design; dysbiosis; gut microbiome; immune activation; inflammatory marker; large scale data; longitudinal analysis; metabolome; metabolomics; metagenomic sequencing; microbial; microbiome; microbiome research; microbiota; molecular diagnostics; molecular marker; multimodality; patient subsets; prospective; stool sample; success

PROJECT SUMMARY CLINICAL RESEARCH PROJECT The goal of the Clinical Project is to generate and integrate a complex network of clinical, immunologic, metabolic, and microbiome datatypes on the ME/CFS etiology to engender hypotheses on immune dysfunction in ME/CFS disease mechanisms. Given the lack of diagnostic molecular markers for ME/CFS and a very limited understanding of its etiology, there is critical need to define new risk factors and mechanisms of ME/CFS predisposition and severity. While early studies showed promise in identifying different metabolic, immunologic, or microbial biomarkers of ME/CFS, these studies were limited in scope, sample size, or, importantly, integration across datatypes, examining one or a small handful of correlates at a time. While this may be sufficient for diseases with a more straightforward mechanism, ME/CFS' compound symptoms and potential etiologies require integrated analysis that incorporates multiple datatypes. In addition, longitudinal and prospective studies are needed to identify mechanisms of disease progression and severity. We hypothesize that immune dysfunction is a central etiology of ME/CFS, both by virtue of its propensity to respond aberrantly to environmental stimuli and its vulnerability to aberrant stimulation by the ME/CFS microbiome and/or its metabolites. Our goal is to define likely clinical correlates of ME/CFS disease, centering on the microbiome and metabolome as immune triggers. We will address multiple central goals of the Center, most notably the application of computational modeling and machine learning approaches to integrate detailed clinical, immune, metabolomic and microbiome datatypes to characterize and predict the immune responses triggered and the associated clinical correlates. Moreover, this study will provide, in addition to valuable hypotheses to guide the mechanistic work proposed in the Basic Research Project, a battery of different immune, metabolomic, and microbial biomarkers associated with different ME/CFS subtypes and disease severity. This project benefits from the deep clinical research expertise at Bateman Horne Center and University of Utah CTSA, cutting-edge core services at The Jackson Laboratory, and the world-class computational and biostatistics team assembled here, with expertise in clinical study design and integrative modeling of large-scale complex genomics cohorts. Our Specific Aims are: 1) To assess immunological abnormalities and blood metabolomic changes prospectively in a large ME/CFS patient cohort; 2) To define correlations between microbiome ecological distribution and clinical state of ME/CFS; and 3) to establish ME/CFS clinical ontology with computational and biostatistical analysis of the immune, metabolic and microbiome interactome in ME/CFS patients. Impact: Success of our aims will yield a large-scale data repository and integrated analytic workflow that can accommodate samples from multiple centers. Identified correlates will be strong candidates for mechanistic biomarkers of disease and will provide hypotheses for mechanistic follow-up studies linking the microbiome to immune and metabolic dysbiosis in ME/CFS.

项目摘要临床研究项目 临床项目的目的是生成和整合一个复杂的临床，免疫学网络， 关于ME/CFS病因的代谢和微生物组数据类型，以引起免疫功能障碍的假设 在我/CFS疾病机制中。鉴于我/CF缺乏诊断分子标记，并且非常有限 了解其病因，至关重要的是定义ME/CFS的新风险因素和机制 倾向和严重性。虽然早期研究表明有望识别不同的代谢，免疫学，但 或ME/CFS的微生物生物标志物，这些研究的范围，样本量或重要的是集成限制 在数据型中，一次或一小段少量相关。虽然这可能足够 具有更直接机制的疾病，ME/CFS的复合症状和潜在的病因需要 综合多个数据类型的集成分析。此外，纵向和前瞻性研究是 需要确定疾病进展和严重程度的机制。我们假设这种免疫力 功能障碍是ME/CFS的中心病因，既依赖于对 环境刺激及其因ME/CFS微生物组和/或ITS刺激异常刺激的脆弱性 代谢物。我们的目标是定义ME/CFS疾病的可能临床相关性，以微生物组和 代谢组作为免疫触发器。我们将解决该中心的多个核心目标，最著名的是 计算建模和机器学习方法的应用以整合详细的临床，免疫， 代谢组和微生物组数据类型，以表征和预测触发的免疫反应，并 相关的临床相关。此外，这项研究还将提供，除了有价值的假设以指导 基础研究项目中提出的机械工作，由不同的免疫，代谢组和 与不同的ME/CFS亚型和疾病严重程度相关的微生物生物标志物。这个项目从中受益 贝特曼·霍恩中心（Bateman Horne Center）和犹他大学CTSA的深层临床研究专业知识，前沿核心 杰克逊实验室的服务，世界一流的计算和生物统计学团队在这里组装， 具有大规模复杂基因组学队列的临床研究设计和综合建模方面的专业知识。我们的 具体目的是：1）预期评估免疫学异常和血液代谢组学变化 大ME/CFS患者队列； 2）定义微生物组生态分布与临床之间的相关性 我/cfs的状态； 3）建立我/CFS临床本体论，并通过计算和生物统计分析 ME/CFS患者的免疫，代谢和微生物组相互作用。影响：我们目标的成功将产生 一个大规模的数据存储库和集成的分析工作流，可以容纳来自多个的样本 中心。确定的相关物将是疾病机械生物标志物的强大候选者，并将提供 用于机械随访研究的假设，将微生物组与免疫和代谢营养不良联系起来 我/CFS。