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.

项目总结