dc.contributor.author |
Malatji, Bontle G.
|
|
dc.contributor.author |
Meyer, Helgard Pieter
|
|
dc.contributor.author |
Mason, Shayne
|
|
dc.contributor.author |
Engelke, Udo F.H.
|
|
dc.contributor.author |
Wevers, Ron A.
|
|
dc.contributor.author |
Van Reenen, Mari
|
|
dc.contributor.author |
Reinecke, Carolus J.
|
|
dc.date.accessioned |
2017-07-25T10:00:16Z |
|
dc.date.available |
2017-07-25T10:00:16Z |
|
dc.date.issued |
2017-05 |
|
dc.description |
Additional file 1: Supplementary information (SI) (PDF providing detailed
descriptions of methods and additional information – clinical, spectral and
statistical – to support the manuscript). |
en_ZA |
dc.description |
Additional file 2: Raw data matrix (Raw NMR spectral data (Excel
format) normalized relative to the CH3 singlet of creatinine at 3.13 ppm). |
en_ZA |
dc.description.abstract |
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_ZA |
dc.description.department |
Family Medicine |
en_ZA |
dc.description.librarian |
am2017 |
en_ZA |
dc.description.sponsorship |
Research funding for this project was provided by the Technological Innovation Agency (TIA) of the South African Department of Science and Technology (DST) and from the Nuclear Technologies in Medicine and the Biosciences Initiative (NTeMBI) of the Nuclear Energy Corporation of South Africa (NECSA). BM received a post-graduate bursary from the National Research Foundation (NRF) of South Africa and a SAVUSA-SKILL stipend from the Embassy of the Netherlands in Pretoria, enabling her to pursue the NMR analyses at the Radboud University Medical Centre in Nijmegen |
en_ZA |
dc.description.uri |
https://bmcneurol.biomedcentral.com |
en_ZA |
dc.identifier.citation |
Malatji, 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. |
en_ZA |
dc.identifier.issn |
1471-2377 (online) |
|
dc.identifier.other |
10.1186/s12883-017-0863-9 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/61434 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
BioMed Central |
en_ZA |
dc.rights |
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License. |
en_ZA |
dc.subject |
Proton nuclear magnetic resonance (1H–NMR) spectroscopy |
en_ZA |
dc.subject |
Metabolomics |
en_ZA |
dc.subject |
Metabolite markers |
en_ZA |
dc.subject |
Pain |
en_ZA |
dc.subject |
Fibromyalgia syndrome (FMS) |
en_ZA |
dc.subject.other |
Health sciences article SDG-03 |
|
dc.subject.other |
SDG-03: Good health and well-being |
|
dc.title |
A diagnostic biomarker profile for fibromyalgia syndrome based on an NMR metabolomics study of selected patients and controls |
en_ZA |
dc.type |
Article |
en_ZA |