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，与 影响2-4%人口的睡眠功能障碍和功能下降(Heidari等人，2017年)。当前2016年 诊断标准仅限于症状学，因为没有经过验证的慢性疼痛生物标记物来辅助 诊断或治疗评估终点(Wolfe等人，2016)。诊断FM通常需要数年时间 患者看多个医生，延误了治疗(Choy，2010)。这一延迟的诊断和 随着FM生物标记物的识别，治疗的启动将大大减少。长期目标 这项研究的重点是为FM确定独特的生物标志物，以提高诊断和/或发展 针对有广泛疼痛的个人的治疗目标。使用半靶向代谢组学方法，我们的 来自患有FM的女性(n=59)与健康对照组(n=38)的初步数据显示，有18个潜在的 在具有几种代谢物的队列之间存在显著差异的候选对象表现出良好的-极佳的敏感性 (&gt；90%)和特异性(&gt；90%)。这项拟议研究的主要目标是评估和验证 新的、更大的个体队列中的候选代谢生物标记物以及与其他慢性疼痛的比较 人口。拟议的研究将使用多点、横断面设计来确定和表征 代谢生物标记物、生物特征及其与多个症状学域的关联 以下两个具体目标：目标1：我们将确定候选生物标志物的诊断测试指标 使用接收器操作曲线(ROC)，即灵敏度和特异度，以及重测可靠性，以正确 识别来自健康对照组和其他慢性疼痛状况的FM患者：骨关节炎、腕管 综合症和类风湿性关节炎。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个自我报告的症状域：a)疼痛；b)疲劳；c)睡眠；d) 身体机能；e)心理因素；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记物，可以作为诊断或疾病内的表型识别。一次 完成后，我们将研究候选生物标记物的潜在机制和治疗目标 后续研究。这些新颖的研究有可能确定一种诊断，并有可能 治疗，与细胞代谢相关的FM的生物标志物。为了完成这项研究，我们开发了一种 强大的多学科和多地点团队，利用作为一部分收集的血液样本和表型数据 一项正在进行的资助研究，以及为重复性分析收集的额外数据。研究小组已经 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。

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.