RESUMO
Gene expression data acquired at different times after traumatic brain injury (TBI) were analyzed to identify differentially expressed genes (DEGs). Interaction network analysis and functional enrichment analysis were performed to extract valuable information, which may benefit diagnosis and treatment of TBI. Microarray data were downloaded from Gene Expression Omnibus and pre-treated with MATLAB. DEGs were screened out with the SAM method. Interaction networks of the DEGs were established, followed by module analysis and functional enrichment analysis to obtain insight into the molecular mechanisms. A total of 39 samples at six time points (30 min, 4, 8, 24 , 72 h, and 21 days) were analyzed and generated 377 DEGs. Eight modules were identified from the networks and network ontology analysis revealed that cell surface receptor-linked signaling pathway, response to wounding and signaling pathway were significantly overrepresented. Altered risk genes and modules in TBI were uncovered through comparing the gene expression data acquired at various time points. These genes or modules could be potential biomarkers for diagnosis and treatment of TBI.