Metabolomic and proteomic characterization of sng and pain phenotypes in fibromyalgia

• Published in: European journal of pain Vol. 26; no. 2; pp. 445 - 462
• Main Authors: Hsu, Wei‐Hsiang, Han, Der‐Sheng, Ku, Wei‐Chi, Chao, Yen‐Ming, Chen, Chih‐Cheng, Lin, Yun‐Lian
• Format: Journal Article
• Language: English
• Published: England 01.02.2022
• Subjects: Biomarkers; Chronic Pain - metabolism; Fibromyalgia; Humans; Phenotype; Profilins; Proteomics - methods
• ISSN: 1090-3801; 1532-2149
• DOI: 10.1002/ejp.1871

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.