Xing Shun Min, Wang Jinxin, He Xiang, Lai Jin, Shen Lianbing, Chen Dechun, Fu Kai, Tan Junming
1Department of Orthopedics, the 98nd Hospital of PLA, Huzhou.
Int J Neurosci. 2015 Apr;125(4):270-6. doi: 10.3109/00207454.2014.930741. Epub 2014 Jul 14.
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.
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).
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.
MiRNAs identified in this study could be considered targets for SCI diagnosis and therapy.
本研究旨在利用 miRNA 微阵列数据构建 miRNA 共表达网络，并通过比较分析筛选出与脊髓损伤（SCI）相关的 miRNAs，这些 miRNAs 可被视为未来预测或治疗的分子标记。
我们首先从 GEO（基因表达综合数据库）下载 SCI 基因表达数据 GSE19890，然后构建三种不同状态下的 miRNA 共表达网络并分析网络的拓扑属性。之后，筛选出与 SCI 相关的 miRNAs，并通过 DAVID（注释、可视化和综合发现数据库）进行功能分析。
在共表达网络中，miR-520a 和 miR-193b 分别在 SCI 组和假手术组中具有最大的度值。共鉴定出 22 个差异表达的 miRNAs。与对照组和假手术组相比，miR-32 和 miR-471 分别在 SCI 组中表达最为显著，本研究首次报道它们与 SCI 相关。对靶基因的功能富集分析表明，筛选出的 miRNA 与细胞黏附、细胞质囊泡等相关。
本研究中鉴定出的 miRNAs 可被视为 SCI 诊断和治疗的靶点。
