Bioinformatic Analysis of Potential Biomarkers for Spinal Cord–injured Patients with Intractable Neuropathic Pain. Issue 9 (September 2018) - Wang, Yimin; Ye, Fang; Huang, Chanyan; Xue, Faling; Li, Yingyuan; Gao, Shaowei; Qiu, Zeting; Li, Si; Chen, Qinchang; Zhou, Huaqiang; Song, Yiyan; Huang, Wenqi; et al.
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.