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Metabolic Fingerprinting For Diagnosis Of Fibromyalgia And Other Rheumatologic Disorders

Monday 10 December 2018


From the Journal of Biological Chemistry:



Metabolic fingerprinting for diagnosis of fibromyalgia and other rheumatologic disorders

Kevin V Hackshaw1*, Didem P. Aykas2, Gregory T Sigurdson2, Marcal Plans Pujolras2, Francesca Madiai3, Lianbo Yu 4, Charles A. T. Buffington5, M. Mónica Giusti6 and Luis Rodriguez-Saona2

Author Affiliations:
1Immunology/Rheumatology, Ohio State University, United States
2The Ohio State University, Food Science and Technology, United States
3Ohio State University
4Department of Biomedical Informatics, The Ohio State University College of Medicine
5University of California Davis, School of Veterinary Medicine, United States
6Ohio State University, Food Science and Technology, United States
*Corresponding author; email:

Received September 11, 2018.
Accepted December 6, 2018.

Published under license by The American Society for Biochemistry and Molecular Biology, Inc.
Copyright © 2018 American Society for Biochemistry and Molecular Biology.


Diagnosis and treatment of Fibromyalgia (FM) remains a challenge owing to the lack of reliable biomarkers.

Our objective was to develop a rapid biomarker-based method for diagnosing FM by using vibrational spectroscopy to differentiate patients with FM from those with Rheumatoid Arthritis (RA), Osteoarthritis (OA) or Systemic Lupus Erythematosus (SLE), and to identify metabolites associated with these differences.

Blood samples were collected from patients with a diagnosis of FM (n=50), RA (n=29), OA (n=19), or SLE (n=23). Bloodspot samples were prepared, and spectra collected with portable FT-IR and FT-Raman microspectroscopy and subjected to metabolomics analysis by ultra-HPLC (uHPLC), coupled to a photodiode array (PDA) and tandem MS/MS.

Unique IR and Raman spectral signatures were identified by pattern recognition analysis and clustered all study participants into classes (FM, RA and SLE) with no misclassifications (p < 0.05, and interclass distances > 2.5). Furthermore, the spectra correlated (R= 0.95 and 0.83 for IR and Raman, respectively) with FM pain severity measured with fibromyalgia impact questionnaire revised version (FIQR) assessments.

Protein backbones and pyridine-carboxylic acids dominated this discrimination and might serve as biomarkers for syndromes such as FM.

uHPLC-PDA-MS/MS provided insights into metabolites significantly differing among the disease groups, not only in molecular m/z+ and m/z- values but also in UV-vis chromatograms.

We conclude that vibrational spectroscopy may provide a reliable diagnostic test for differentiating FM from other disorders and for establishing serologic biomarkers of FM-associated pain.


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