Malatji, Bontle G.Meyer, Helgard PieterMason, ShayneEngelke, Udo F.H.Wevers, Ron A.Van Reenen, MariReinecke, Carolus J.2017-07-252017-07-252017-05Malatji, BG, Meyer, H, Mason, S, Engelke, UFH, Wevers, RA, Van Reenen, M & Reinecke, CJ 2017, 'A diagnostic biomarker profile for fibromyalgia syndrome based on an NMR metabolomics study of selected patients and controls', BMC Neurology, vol. 17, art. no. 88, pp. 1-15.1471-2377 (online)10.1186/s12883-017-0863-9http://hdl.handle.net/2263/61434Additional file 1: Supplementary information (SI) (PDF providing detailed descriptions of methods and additional information – clinical, spectral and statistical – to support the manuscript).Additional file 2: Raw data matrix (Raw NMR spectral data (Excel format) normalized relative to the CH3 singlet of creatinine at 3.13 ppm).BACKGROUND : Fibromyalgia syndrome (FMS) is a chronic pain syndrome. A plausible pathogenesis of the disease is uncertain and the pursuit of measurable biomarkers for objective identification of affected individuals is a continuing endeavour in FMS research. Our objective was to perform an explorative metabolomics study (1) to elucidate the global urinary metabolite profile of patients suffering from FMS, and (2) to explore the potential of this metabolite information to augment existing medical practice in diagnosing the disease. METHODS : We selected patients with a medical history of persistent FMS (n = 18), who described their recent state of the disease through the Fibromyalgia Impact Questionnaire (FIQR) and an in-house clinical questionnaire (IHCQ). Three control groups were used: first-generation family members of the patients (n = 11), age-related individuals without any indications of FMS or related conditions (n = 10), and healthy young (18–22 years) individuals (n = 20). All subjects were female and the biofluid under investigation was urine. Correlation analysis of the FIQR showed the FMS patients represented a well-defined disease group for this metabolomics study. Spectral analyses of urine were conducted using a 500 MHz 1H nuclear magnetic resonance (NMR) spectrometer; data processing and analyses were performed using Matlab, R, SPSS and SAS software. RESULTS AND DISCUSSION : Unsupervised and supervised multivariate analyses distinguished all three control groups and the FMS patients, and significant increases in metabolites related to the gut microbiome (hippuric, succinic and lactic acids) were observed. We have developed an algorithm for the diagnosis of FMS consisting of three metabolites — succinic acid, taurine and creatine — that have a good level of diagnostic accuracy (Receiver Operating Characteristic (ROC) analysis — area under the curve 90%) and on the pain and fatigue symptoms for the selected FMS patient group. CONCLUSION : Our data and comparative analyses indicated an altered metabolic profile of patients with FMS, analytically detectable within their urine. Validation studies may substantiate urinary metabolites to supplement information from medical assessment, tender-point measurements and FIQR questionnaires for an improved objective diagnosis of FMS.en© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License.Proton nuclear magnetic resonance (1H–NMR) spectroscopyMetabolomicsMetabolite markersPainFibromyalgia syndrome (FMS)Health sciences articles SDG-03SDG-03: Good health and well-beingArticle