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.

项目总结临床研究项目 临床项目的目标是生成和整合一个复杂的临床，免疫， ME/CFS病因学的代谢和微生物组数据库，以产生免疫功能障碍的假设 ME/CFS发病机制。鉴于ME/CFS缺乏诊断分子标志物， 了解其病因，迫切需要确定ME/CFS的新危险因素和机制 易感性和严重性。虽然早期的研究表明，在确定不同的代谢，免疫， 或ME/CFS的微生物生物标志物，这些研究在范围、样本量或重要的整合方面受到限制。 跨数据类型，一次检查一个或少数相关项。虽然这可能足以 ME/CFS的复合症状和潜在病因需要 集成了多个数据库的综合分析。此外，纵向和前瞻性研究也 需要确定疾病进展和严重程度的机制。我们假设免疫 功能障碍是ME/CFS的中心病因，由于其倾向于异常反应， 环境刺激及其对ME/CFS微生物组和/或其 代谢物。我们的目标是确定ME/CFS疾病的可能临床相关性，以微生物组为中心， 代谢组作为免疫触发器我们将解决中心的多个中心目标，最值得注意的是 应用计算建模和机器学习方法来整合详细的临床，免疫， 代谢组学和微生物组学数据库来表征和预测所触发的免疫反应， 相关临床相关因素。此外，本研究将提供，除了有价值的假设，以指导 在基础研究项目中提出的机械工作，一组不同的免疫，代谢组学， 与不同ME/CFS亚型和疾病严重程度相关的微生物生物标志物。该项目得益于 贝特曼霍恩中心和犹他州CTSA大学的深厚临床研究专业知识， 服务在杰克逊实验室，和世界一流的计算和生物统计团队聚集在这里， 具有临床研究设计和大规模复杂基因组学队列综合建模方面的专业知识。我们 具体目的是：1）前瞻性评估免疫异常和血液代谢组学变化， 大型ME/CFS患者队列; 2）定义微生物组生态分布与临床 ME/CFS的状态;和3）通过计算和生物统计分析建立ME/CFS临床本体， 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程，可以容纳来自多个 中心.鉴定的相关物将是疾病的机制生物标志物的强有力的候选物，并将提供 将微生物组与免疫和代谢生态失调联系起来的机制后续研究的假设， ME/CFS。