Metabolic Biomarkers for Fibromyalgia

纤维肌痛的代谢生物标志物

• 批准号: 10698038
• 负责人: Laura A Frey Law
• 金额: $ 30.66万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10698038
• 关键词: 6-phosphogluconate; Address; Aerobic; Affect; Basic Science; Biological; Biological Markers; Blood specimen; Carpal Tunnel Syndrome; Cellular Metabolic Process; Cerebrospinal Fluid; Citric Acid; Clinical; Clinical Trials; Cohort Studies; Complex; Cysteine; Data; Data Collection; Degenerative polyarthritis; Development; Diagnosis; Diagnostic; Diagnostic tests; Disease; Early treatment; Energy Metabolism; Evaluation; Fatigue; Fibromyalgia; Fumarates; Funding; Goals; Human; Hydration status; Hydrogen; Individual; Institution; Investigation; Magnesium; Malate Dehydrogenase; Malates; Metabolic; Metabolic Pathway; Michigan; Nicotinamide adenine dinucleotide; Oxaloacetates; Pain; Pathogenicity; Patient Self-Report; Patients; Phenotype; Physical Function; Physicians; Plasma; Population; Primary Fibromyalgias; Process; Production; Proteomics; Psychological Factors; ROC Curve; Research; Rheumatoid Arthritis; Role; Sampling; Secondary Fibromyalgias; Sensitivity and Specificity; Severity of illness; Site; Sleep; Sleep Disorders; Specificity; Symptoms; Testing; Therapeutic; United States National Institutes of Health; Universities; Woman; associated symptom; biosignature; candidate marker; candidate validation; chronic pain; chronic painful condition; cohort; design; diagnostic criteria; disability; disease phenotype; improved; improved outcome; inflammatory pain; intervention effect; metabolomics; multidisciplinary; novel; open label; oxidation; painful neuropathy; phenotypic data; potential biomarker; specific biomarkers; therapeutic biomarker; therapeutic target

Project Summary Fibromyalgia (FM) is a complex condition characterized by widespread pain and fatigue that is associated with sleep dysfunction and reduced function that affects 2-4% of the population (Heidari et al., 2017). Current 2016 diagnostic criteria are by symptomology only, as there are no validated chronic pain biomarkers to assist with diagnosis, or treatment evaluation endpoints (Wolfe et al., 2016). Diagnosing FM often takes years with patients seeing multiple physicians, which delays treatment (Choy, 2010). This delayed diagnosis and treatment initiation would be dramatically reduced with the identification of FM biomarkers. The long-term goal of this line of research is to identify unique biomarkers for FM to improve the diagnosis and/or develop therapeutic targets for individuals with widespread pain. Using a semi-targeted metabolomics approach, our preliminary data from women with FM (n=59), compared to healthy controls (n=38), show 18 potential candidates that differ significantly between cohorts with several metabolites showing good-excellent sensitivity (>90%) and specificity (>90%). The primary goal of this proposed research is to assess and validate candidate metabolic biomarkers in a new, larger cohort of individuals and compared to other chronic pain populations. The proposed study will use a multi-site, cross-sectional design to identify and characterize metabolic biomarkers, biosignatures, and their associations with multiple symptomology domains to address the following two specific aims: Aim 1: We will characterize diagnostic test metrics for candidate biomarkers using receiver operating curves (ROCs), i.e. sensitivity and specificity, and test-retest reliability, to correctly identify individuals with FM from healthy controls and other chronic pain conditions: osteoarthritis, carpal tunnel syndrome, and rheumatoid arthritis. Aim 2: We will determine associations between putative metabolic biomarkers and multiple self-reported symptom domains in those with FM: a) pain; b) fatigue; c) sleep; d) physical function; e) psychological factors, and f) disease impact/disability. We have identified several promising metabolic biomarkers that may serve as diagnostic or within-disease phenotype identifiers. Once completed, we will examine potential mechanistic and therapeutic targets for the candidate biomarkers in subsequent studies. These novel studies have the potential to identify a diagnostic, and potentially a therapeutic, biomarker of FM associated with cell metabolism. To accomplish this study, we have developed a strong multidisciplinary and multi-site team, leveraging blood samples and phenotype data collected as part of an on-going funded study, as well as additional data collection for repeatability analyses. The study team has the necessary expertise in human, basic science and metabolomics investigations to successfully complete these aims.

项目概要 纤维肌痛 (FM) 是一种复杂的疾病，其特征是广泛的疼痛和疲劳，与 睡眠障碍和功能下降影响了 2-4% 的人口（Heidari 等人，2017）。当前2016年 诊断标准仅根据症状学，因为没有经过验证的慢性疼痛生物标志物来辅助 诊断或治疗评估终点（Wolfe 等，2016）。诊断 FM 通常需要数年时间 患者去看多名医生，从而延误了治疗（Choy，2010）。这延误了诊断并 随着 FM 生物标志物的识别，治疗起始时间将大大减少。长期目标 这一系列研究的重点是确定 FM 的独特生物标志物，以改善诊断和/或开发 患有广泛疼痛的个体的治疗目标。使用半靶向代谢组学方法，我们 与健康对照组 (n=38) 相比，患有 FM 的女性 (n=59) 的初步数据显示 18 种潜在的 候选者在具有多种代谢物的队列之间存在显着差异，表现出良好的敏感性 (>90%) 和特异性 (>90%)。这项拟议研究的主要目标是评估和验证 候选代谢生物标志物在一个新的、更大的人群中进行比较，并与其他慢性疼痛进行比较 人口。拟议的研究将使用多地点、横断面设计来识别和表征 代谢生物标志物、生物特征及其与多个症状学领域的关联，以解决 以下两个具体目标： 目标 1：我们将表征候选生物标志物的诊断测试指标 使用受试者工作曲线（ROC），即敏感性和特异性以及重测可靠性，以正确 从健康对照和其他慢性疼痛病症中识别 FM 个体：骨关节炎、腕管 综合征和类风湿性关节炎。目标 2：我们将确定假定的代谢之间的关联 FM 患者的生物标志物和多种自我报告的症状范围：a) 疼痛； b) 疲劳； c) 睡觉； d) 身体机能； e) 心理因素，以及 f) 疾病影响/残疾。我们已经确定了几个 有前景的代谢生物标志物，可作为诊断或疾病内表型标识符。一次 完成后，我们将检查候选生物标志物的潜在机制和治疗靶点 后续研究。这些新颖的研究有可能确定诊断方法，并有可能确定 与细胞代谢相关的 FM 治疗性生物标志物。为了完成这项研究，我们开发了一个 强大的多学科和多地点团队，利用收集的血液样本和表型数据 正在进行的资助研究，以及用于重复性分析的额外数据收集。研究小组有 成功完成人类、基础科学和代谢组学研究所需的专业知识 这些目标。