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.

项目摘要 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，与之相关 睡眠功能障碍和功能降低，影响2-4％的人群（Heidari等，2017）。当前2016年 诊断标准仅通过症状学，因为没有经过验证的慢性疼痛生物标志物可以协助 诊断或治疗评估终点（Wolfe等，2016）。诊断FM通常需要数年 患者看到了多个医生，这会延迟治疗（Choy，2010年）。这种延迟的诊断和 通过鉴定FM生物标志物，将大大减少治疗起始。长期目标 这一研究的方法是确定FM的独特生物标志物，以改善诊断和/或发展 患有广泛疼痛的个体的治疗靶标。使用半靶向代谢组学方法，我们 与健康对照组相比，FM女性（n = 59）的初步数据（n = 38）显示了18个潜力 在队列之间有显着差异的候选人，几个代谢物表现出良好的灵敏度 （> 90％）和特异性（> 90％）。这项拟议研究的主要目标是评估和验证 在新的，更大的个体中的候选代谢生物标志物，并与其他慢性疼痛进行比较 人群。拟议的研究将使用多站点的横截面设计来识别和表征 代谢生物标志物，生物签名及其与多个症状结构域的关联 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 使用接收器操作曲线（ROC），即灵敏度和特异性以及重测的可靠性，以正确 从健康对照和其他慢性疼痛状况中识别患有FM的人：骨关节炎，腕管 综合征和类风湿关节炎。目标2：我们将确定推定代谢之间的关联 FM患者中的生物标志物和多个自我报告的症状结构域：a）疼痛； b）疲劳； c）睡眠； d） 身体功能； e）心理因素和f）疾病影响/残疾。我们已经确定了几个 有希望的代谢生物标志物可以用作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械和治疗靶标 随后的研究。这些新型研究有可能识别诊断，并可能 治疗性，与细胞代谢相关的FM的生物标志物。为了完成这项研究，我们已经开发了 强大的多学科和多站点团队，利用血液样本和表型数据收集的一部分 一项正在进行的资助的研究以及用于可重复性分析的其他数据收集。学习团队有 人类，基础科学和代谢组学调查的必要专业知识，以成功完成 这些目标。