Metabolic Biomarkers for Fibromyalgia

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， 影响2-4%人口的睡眠功能障碍和功能降低（Heidari等人，2017年）的报告。当前2016年 诊断标准仅由神经病学确定，因为没有经过验证的慢性疼痛生物标志物来辅助诊断。 诊断或治疗评价终点（Wolfe等，2016年）。诊断FM通常需要数年时间， 患者看多个医生，这会延迟治疗（Choy，2010）。这种延迟诊断和 通过FM生物标志物的鉴定，治疗的开始将显著减少。远景目标 这项研究的目的是确定FM的独特生物标志物，以改善诊断和/或发展 广泛疼痛患者的治疗目标。使用半靶向代谢组学方法， 与健康对照组（n=38）相比，FM女性（n=59）的初步数据显示18种潜在的 具有几种代谢物的队列之间存在显著差异的候选物显示出良好-极好的灵敏度 （>90%）和特异性（>90%）。这项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，并与其他慢性疼痛 人口。拟议的研究将采用多中心、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生物学领域的关联，以解决 以下两个具体目标：目标1：我们将描述候选生物标志物的诊断测试指标 使用受试者工作曲线（ROC），即灵敏度和特异性以及重测信度， 从健康对照和其他慢性疼痛疾病中识别FM患者：骨关节炎、腕管综合征 综合征和类风湿性关节炎。目标2：我们将确定假定的代谢 FM患者的生物标志物和多个自我报告的症状领域：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。我们发现了几个 有前途的代谢生物标志物，可作为诊断或疾病内表型标识符。一旦 完成后，我们将研究候选生物标志物的潜在机制和治疗靶点， 随后的研究。这些新的研究有可能确定一种诊断方法， 与细胞代谢相关的FM的治疗性生物标志物。为了完成这项研究，我们开发了一个 强大的多学科和多中心团队，利用血液样本和表型数据收集，作为 一项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。研究小组已经 在人类，基础科学和代谢组学研究方面的必要专业知识，以成功完成 这些目标。

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.