2. Academic Validation
  3. Metabolomic and proteomic characterization of sng and pain phenotypes in fibromyalgia

Metabolomic and proteomic characterization of sng and pain phenotypes in fibromyalgia

  • Eur J Pain. 2022 Feb;26(2):445-462. doi: 10.1002/ejp.1871.
Wei-Hsiang Hsu 1,  Der-Sheng Han 2 3 4 5,  Wei-Chi Ku 6,  Yen-Ming Chao 1,  Chih-Cheng Chen 7 8 9,  Yun-Lian Lin 1 10
Affiliations

Affiliations

  • 1 Department of Chinese Pharmaceutical Sciences and Chinese Medicine Resources, China Medical University, Taichung, Taiwan.
  • 2 Department of Physical Medicine and Rehabilitation, National Taiwan University Hospital, Bei-Hu Branch, Taipei, Taiwan.
  • 3 Community and Geriatric Medicine Research Center, National Taiwan University Hospital, Bei-Hu Branch, Taipei, Taiwan.
  • 4 Department of Physical Medicine and Rehabilitation, National Taiwan University College of Medicine, Taipei, Taiwan.
  • 5 Health Science and Wellness Center, National Taiwan University, Taipei, Taiwan.
  • 6 School of Medicine, College of Medicine, Fu Jen Catholic University, New Taipei, Taiwan.
  • 7 Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.
  • 8 Neuroscience Program of Academia Sinica, Academia Sinica, Taipei, Taiwan.
  • 9 Taiwan Mouse Clinic, Biomedical Translation Research Center, Academia Sinica, Taipei, Taiwan.
  • 10 Department of Pharmacy, National Taiwan University, Taipei, Taiwan.
PMID: 34608709 DOI: 10.1002/ejp.1871
Abstract

Background: Fibromyalgia (FM) is characterized by chronic widespread pain. Its pathophysiological mechanisms remain poorly understood, and effective diagnosis and treatments are lacking. This study aimed to identify significantly changed biosignatures in FM and propose a novel classification for FM based on pain and soreness (sng) symptoms.

Methods: Urine and serum samples from 30 FM patients and 25 controls underwent metabolomic and proteomic profiling.

Results: Compared with controls, FM patients showed significant differential expression of three metabolites in urine and five metabolites and eight proteins in serum. Of them, DETP, 4-guanidinobutanoic acid, SM(d18:1/18:0), PC(20:1(11Z)/18:0), S100A7, SERPINB3, galectin-7 and LYVE1 were first reported as potential biomarkers for FM. Furthermore, lactate, 2-methylmaleate and cotinine in urine and lactate, SM(d18:1/25:1), SM(d18:1/26:1) and prostaglandin D2 (PGD2) and PCYOX1, ITIH4, PFN1, LRG1, C8G, C8A, CP, CDH5 and DBH in serum could differentiate pain- (PG) and sng-dominant groups (SG). Lactate, 2-methylmaleate, cotinine, PCYOX1, ITIH4, PFN1 and DBH have a higher level in SG. SM(d18:1/25:1), SM(d18:1/26:1), PGD2, LRG1, C8G, C8A, CP and CDH5 in SG are lower than PG. The omics results indicated disordered free radical scavenging, and lipid and amino acid metabolism networks and resulting NF-κB-dependent cytokine generation in FM. Lactate level was altered simultaneously in urine and serum and significantly higher in sng-dominant patients than Others.

Conclusions: In this study, we identified potential biomarkers from FM patients. The selected biomarkers could discriminate sng and pain phenotypes in FM patients. These results could help elucidate the underlying pathological mechanisms for more effective diagnosis and therapy for FM.

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