Clustering analysis to identify key genes associated with motor neuron excitability following spinal cord injury

Purpose: As a neurodegenerative disease, spinal cord injury can lead to the loss of autonomic function, muscle function, or sensation. This study is designed to identify the key genes implicated in the excitability of motor neurons following spinal cord injury. Materials and methods: The GSE19701 dataset was obtained from Gene Expression Omnibus. It includes a total of 31 motor neurons after spinal cord injury (samples at day 0, 2, 7, 21 and 60 following injury). After the data were preprocessed by the Robust Multi-array Average method, soft clustering analysis was conducted by the Fuzzy C-Means method in the Mfuzz package to identify the differentially expressed genes. Afterward, the differentially expressed genes were analyzed with enrichment analysis using the DAVID online tool. Based on Cytoscape software, a protein-protein interaction network was constructed and then module analysis was carried out. Furthermore, miRNA-differentially expressed gene pairs were downloaded from the miRWalk2.0 database and the miRNA regulatory network was visualized by Cytoscape software. Results: We found 218 upregulated genes and 526 downregulated genes. In the protein-protein interaction network, Uba3, Sumo1, and Pik3ca had higher scores, and Uba3 interacted with Sumo1. Among the eight modules identified from the protein-protein interaction network, module 1 and 8 were significantly enriched in pathways related to degenerative diseases of the nervous system. Additionally, Pdcd4 was targeted by miR-21 in the miRNA regulatory network. Conclusion: Uba3, Sumo1, Pik3ca and miR-21 targeting Pdcd4 might be responsible for the excitability of motor neurons after spinal cord injury.