Dataset Information

Bioinformatic Analysis of Potential Biomarkers for Spinal Cord-injured Patients with Intractable Neuropathic Pain.

ABSTRACT: BACKGROUND:Neuropathic pain is one of the common complications after spinal cord injury (SCI), affecting individuals' quality of life. The molecular mechanism for neuropathic pain after SCI is still unclear. We aimed to discover potential genes and microRNAs (miRNAs) related to neuropathic pain by the bioinformatics method. METHODS:Microarray data of GSE69901 were obtained from Gene Expression Omnibus (GEO) database. Peripheral blood samples from individuals with or without neuropathic pain after SCI were collected. Twelve samples from individuals with neuropathic pain and 13 samples from individuals without pain as controls were included in the downloaded microarray. Differentially expressed genes (DEGs) between the neuropathic pain group and the control group were detected using the GEO2R online tool. Functional enrichment analysis of DEGs was performed using the DAVID database. Protein-protein interaction network was constructed from the STRING database. MiRNAs targeting these DEGs were obtained from the miRNet database. A merged miRNA-DEG network was constructed and analyzed with Cytoscape software. RESULTS:In total, 1134 DEGs were identified between individuals with or without neuropathic pain (case and control), and 454 biological processes were enriched. We identified 4 targeted miRNAs, including mir-204-5p, mir-519d-3p, mir-20b-5p, mir-6838-5p, which may be potential biomarkers for SCI patients. CONCLUSION:Protein modification and regulation of the biological process of the central nervous system may be a risk factor in SCI. Certain genes and miRNAs may be potential biomarkers for the prediction of and potential targets for the prevention and treatment of neuropathic pain after SCI.

SUBMITTER: Wang Y

PROVIDER: S-EPMC6078488 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Bioinformatic Analysis of Potential Biomarkers for Spinal Cord-injured Patients with Intractable Neuropathic Pain.

Wang Yimin Y Ye Fang F Huang Chanyan C Xue Faling F Li Yingyuan Y Gao Shaowei S Qiu Zeting Z Li Si S Chen Qinchang Q Zhou Huaqiang H Song Yiyan Y Huang Wenqi W Tan Wulin W Wang Zhongxing Z

The Clinical journal of pain 20180901 9

<h4>Background</h4>Neuropathic pain is one of the common complications after spinal cord injury (SCI), affecting individuals' quality of life. The molecular mechanism for neuropathic pain after SCI is still unclear. We aimed to discover potential genes and microRNAs (miRNAs) related to neuropathic pain by the bioinformatics method.<h4>Methods</h4>Microarray data of GSE69901 were obtained from Gene Expression Omnibus (GEO) database. Peripheral blood samples from individuals with or without neurop ...[more]

PMID: 29547407

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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.

Dataset Information

Bioinformatic Analysis of Potential Biomarkers for Spinal Cord-injured Patients with Intractable Neuropathic Pain.

Publications

Bioinformatic Analysis of Potential Biomarkers for Spinal Cord-injured Patients with Intractable Neuropathic Pain.

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