Identification of disease-related miRNAs based on co-expression network in spinal cord injury

Abstract

Objective: This study aimed to construct miRNA co-expression network by using miRNA microarray data and screen the miRNAs associated with spinal cord injury (SCI) by comparative analysis, which might be considered as molecule labels for future forecasts or therapies. Methods: We first downloaded SCI gene expression data GSE19890 from GEO (Gene Expression Omnibus), then constructed the miRNA co-expression network under three different states and analyzed the topologic attributes of network. After that, miRNAs associated with SCI were screened and subjected to function analysis by DAVID (Database for Annotation, Visualization and Integrated Discovery). Results: In the co-expression network, miR-520a and miR-193b had the largest degree in the SCI and sham groups, respectively. A total of 22 differentially expressed miRNAs were identified. MiR-32 and miR-471 were the most significantly expressed in the SCI group compared with control and sham groups, respectively, which were newly reported to be related to SCI in this study. Function enrichment analysis of the target genes indicated that the screened miRNA were associated with cell adhesion, cytoplasmic vesicle and so on. Conclusions: MiRNAs identified in this study could be considered targets for SCI diagnosis and therapy.

KEYWORDS:

• spinal cord injury
• miRNA
• co-expression network