Dataset Information

Serum proteomics of sng- and pain-trend fibromyalgia patients

ABSTRACT: Fibromyalgia (FM) is a chronic pain condition and consists of widespread pain with similarities to neuropathic pain in clinical findings, pathophysiology, and neuropharmacology. Its mechanisms are poorly understood and a lack of effective biomarkers for diagnosis and onset prediction. This study aimed to identify the metabolites to characterize pain and sngception (Sng) in FM.

INSTRUMENT(S): Orbitrap Eclipse

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Serum

DISEASE(S): Fibromyalgia

SUBMITTER: Wei-Chi Ku

LAB HEAD: Wei-Chi Ku

PROVIDER: PXD022886 | Pride | 2022-08-12

REPOSITORIES: Pride

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Publications

Metabolomic and proteomic characterization of sng and pain phenotypes in fibromyalgia.

Hsu Wei-Hsiang WH Han Der-Sheng DS Ku Wei-Chi WC Chao Yen-Ming YM Chen Chih-Cheng CC Lin Yun-Lian YL

European journal of pain (London, England) 20211026 2

<h4>Background</h4>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.<h4>Methods</h4>Urine and serum samples from 30 FM patients and 25 controls underwent metabolomic and proteomic profiling.<h4>Results</h4>Compared with ...[more]

PMID: 34608709

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Project description:Objective: Chronic pain is a major problem in patients with spinal cord injury (SCI). According to different studies, approximately 70% of patients with SCI experience persistent pain. Although previous gene expression profiling studies have been conducted in animal models, gene expression profiling study in human whole blood has not been reported yet. The objective of this study was to define the gene expression profile of neuropathic pain in spinal cord injured patients. Materials and Methods: We performed gene expression analysis including 20.000 genes using Affymetrix GeneChip® Primeview™ Human Gene Expression Arrays. For confirmation of expression levels of selected genes, we performed real time polymerase chain reaction. We gathered samples from periferic blood mononuclear cells. Data of twelve patients with intractable neuropathic pain was compared with thirteen patients who don’t have pain. All patients have complete injuries with a level of injury above T5. Results: A total of 16 differentially expressed genes including 9 up-regulated and 7 down-regulated were obtained with a cut-off degree at 4 fold change. EIF1AY, RPS4Y1, DDX3Y, RPL31, ETS1, KLF3, JUN, CYorf15B, and ERAP2 were in up-regulated and HLA-C, XIST, C4BPA, FAM118A, ZNF506, OVOS2, and C1D were in down-regulated group. KEGG pathway database showed that 14.6% of genes were enriched in the nodes of immune system. Real time polymerase chain reaction analyses did not increase to statistically significant levels for confirmation of gene expression analyze results. Conclusions: Considering these data, findings of this first gene expression study in humans with SCI might provide valuable information for future targets for understanding neuropathic pain pathogenesis. The results of gene expression analyses were not confirmed by real time polymerase chain reaction. Studies with larger sample size are needed for confirmation. This is a cross-sectional study with a control group. Patients were divided into two groups according to intractable neuropathic pain existence.There were 12 patients in group A (Patients with pain) and 13 patients in control group.

Project description:Peripheral nerve injury alters the expression of hundreds of proteins in dorsal root ganglia (DRG). Targeting some of these proteins has led to successful treatments for acute pain, but not for sustained postoperative neuropathic pain. The latter may require targeting multiple proteins. Since a single microRNA (miR) can affect the expression of multiple proteins, here, we describe an approach to identify chronic neuropathic pain-relevant miRs. We used two variants of the spared nerve injury (SNI): Sural-SNI and Tibial-SNI and found distinct pain phenotypes between the two. Both models induced strong mechanical allodynia, but only Sural-SNI rats maintained strong mechanical and cold allodynia, as previously reported. In contrast, we found that Tibial-SNI rats recovered from mechanical allodynia and never developed cold allodynia. Since both models involve nerve injury, we increased the probability of identifying differentially regulated miRs that correlated with the quality and magnitude of neuropathic pain and decreased the probability of detecting miRs that are solely involved in neuronal regeneration. We found seven such miRs in L3-L5 DRG. The expression of these miRs increased in Tibial-SNI. These miRs displayed a lower level of expression in Sural-SNI, with four having levels lower than those in sham animals. Bioinformatics analysis of how these miRs could affect the expression of some ion channels supports the view that, following a peripheral nerve injury, the increase of the 7 miRs may contribute to the recovery from neuropathic pain while the decrease of four of them may contribute to the development of chronic neuropathic pain. The approach used resulted in the identification of a small number of potentially neuropathic pain relevant miRs. Additional studies are required to investigate whether manipulating the expression of the identified miRs in primary sensory neurons can prevent or ameliorate chronic neuropathic pain following peripheral nerve injuries. To identify the miRs that were differentially dysregulated between Tibial-SNI and Sural-SNI, we first performed 12 microarrays in a limited number of samples (in four individual DRGs per group: Sham, Tibial-SNI and Sural-SNI; two L3-DRG and two L4-DRG). Then, miRs identified as having differential expression were corroborated with real time qRT-PCR in RNA isolated from individual DRGs (L3, L4 and L5) derived from 4 rats per group (not presented here, but in the manuscript).

Dataset Information

Serum proteomics of sng- and pain-trend fibromyalgia patients

Publications

Metabolomic and proteomic characterization of sng and pain phenotypes in fibromyalgia.

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