STUDY DESIGN: This is a bioinformatic study designed to investigate the time-course expression changes of microRNAs (miRNAs) after spinal cord injury (SCI). OBJECTIVE: To investigate the mechanism of SCI self-repair at miRNAs level and target genes level. SUMMARY OF BACKGROUND DATA: SCI results in loss of sensory and locomotor function, and SCI self-repair might provide clinical therapies; however, the mechanism of SCI self-repair remains unclear. METHODS: The miRNA expression profile (GSE19890) of adult female Wistar brown rats (Rattus norvegicus) in SCI (laminectony and contusion), sham (laminectony but no contusion), and control (untreated) groups was downloaded from Gene Expression Omnibus. Totally, 35 chips were available, including five controls, five SCI-1-day, five SCI-3-day, five SCI-7-day, five sham-1-day, five sham-3-day, and five sham-7-day. Betr and limma package were used to screen time-course differentially expressed miRNAs (DEmiRNAs), followed by Bayesian hierarchical clustering (BHC), synergetic and functional enrichment analysis through BHC and cluster Profiler packages, respectively. Furthermore, STRING database and Cytoscape software were used to construct interaction networks between time-course DEmiRNAs, and GenCLip2.0 software was applied to pathway enrichment for key genes associated with nervous system. RESULTS: Totally, 68 time-course DEmiRNAs were identified and divided into 15 BHC clusters. Then, 100 time-course DEmiRNA pairs with synergetic function were identified, and time-course DEmiRNAs and target genes interaction networks were constructed, in which 10 genes (AKT1, VEGFA, CTNNB1, IGF1, APP, PTEN, CDC42, BDNF, SOD2, and IFNG) with highest degrees were found. Furthermore, key genes were significantly enriched in neurotrophin signaling pathway. CONCLUSION: After SCI, miRNAs might collectively regulate target genes, facilitating or inhibiting self-repair. Modulation of these miRNAs might provide novel therapies for SCI treatment. LEVEL OF EVIDENCE: N/A.
STUDY DESIGN: This is a bioinformatic study designed to investigate the time-course expression changes of microRNAs (miRNAs) after spinal cord injury (SCI). OBJECTIVE: To investigate the mechanism of SCI self-repair at miRNAs level and target genes level. SUMMARY OF BACKGROUND DATA: SCI results in loss of sensory and locomotor function, and SCI self-repair might provide clinical therapies; however, the mechanism of SCI self-repair remains unclear. METHODS: The miRNA expression profile (GSE19890) of adult female Wistar brown rats (Rattus norvegicus) in SCI (laminectony and contusion), sham (laminectony but no contusion), and control (untreated) groups was downloaded from Gene Expression Omnibus. Totally, 35 chips were available, including five controls, five SCI-1-day, five SCI-3-day, five SCI-7-day, five sham-1-day, five sham-3-day, and five sham-7-day. Betr and limma package were used to screen time-course differentially expressed miRNAs (DEmiRNAs), followed by Bayesian hierarchical clustering (BHC), synergetic and functional enrichment analysis through BHC and cluster Profiler packages, respectively. Furthermore, STRING database and Cytoscape software were used to construct interaction networks between time-course DEmiRNAs, and GenCLip2.0 software was applied to pathway enrichment for key genes associated with nervous system. RESULTS: Totally, 68 time-course DEmiRNAs were identified and divided into 15 BHC clusters. Then, 100 time-course DEmiRNA pairs with synergetic function were identified, and time-course DEmiRNAs and target genes interaction networks were constructed, in which 10 genes (AKT1, VEGFA, CTNNB1, IGF1, APP, PTEN, CDC42, BDNF, SOD2, and IFNG) with highest degrees were found. Furthermore, key genes were significantly enriched in neurotrophin signaling pathway. CONCLUSION: After SCI, miRNAs might collectively regulate target genes, facilitating or inhibiting self-repair. Modulation of these miRNAs might provide novel therapies for SCI treatment. LEVEL OF EVIDENCE: N/A.
Authors: Redin A Spann; William J Lawson; Raymond J Grill; Michael R Garrett; Bernadette E Grayson Journal: Physiol Genomics Date: 2017-08-18 Impact factor: 3.107
Authors: Nikolay L Martirosyan; Alessandro Carotenuto; Arpan A Patel; M Yashar S Kalani; Kaan Yagmurlu; G Michael Lemole; Mark C Preul; Nicholas Theodore Journal: Front Surg Date: 2016-11-08