| Objective:Traumatic brain injury(TBI)is a surgical emergency with high mortality and disability,but the treatment is limited because of its complex pathophysiological mechanism.This research aims to explore the pathophysiological mechanism of TBI and to find potential diagnostic markers and therapeutic targets through bioinformatics.Methods:Data sets GSE131695 and GSE21854 of plasma mi RNA expression levels of TBI patients and matched healthy controls were downloaded from GEO public database,and data were normalized in R language(4.1.2).The differentially expressed micro RNAs(DEMs)was obtained by using R language DEseq2 and limma software package to analyze the expression differences in the two data sets and the analysis results were represented by volcano diagram.The common DEMs of the two data sets was obtained,and the target gene set of the intersection DEMs was predicted by using the R language multi Mi R software package.The enrichment analysis of target Gene sets was performed in GO(Gene Ontology),KEGG(Kyoto Encyclopedia of Genes and Genomes)and GSEA(Gene-set Enrichment Analysis).The protein-protein interaction(PPI)network of target gene set was established by STRING database,and the PPI network was visualized by Cytoscape software.Cytoscape plug-in MCODE was used to construct a subnetwork to identify important modules in the PPI network,and cyto Hubba was used to identify hub genes closely related to traumatic brain injury.Finally,using Cytoscape to establish mi RNA-m RNA regulation network.Results:Through variance analysis,there are 13 up-regulated and 6 down-regulated DEM between dataset GSE21854 and GSE131695(FDR < 0.05,logfc > | 1 |).We predicted the target genes of 19 differentiated mi RNA,including 296 predicted by 13 up-regulated mi RNAs and 12 predicted by 6 down-regulated mi RNA.GO enrichment analysis showed that the function of the target gene set was mainly enriched in monocyte differentiation and cell adhesion regulation,and KEGG enrichment showed that the target gene set was mainly enriched in pi3K-Akt signaling pathway and MAPK signaling pathway.KEGG enrichment results were verified by GSEA,and the results showed that the cell cycle pathway and p53 pathway were the most obvious enrichment at both ends of the gene set.Build PPI network according to STRING database,identify 4 important modules to build sub-network and screen out 10 hub genes(CDK4,E2F1,CCNE1,RB1,RBL1,CCND2,CDK6,E2F3,RBL2,CCND1).Mi RNA-m RNA regulatory network was constructed to screen the two key mi RNA hsa-mi R-106b-5p and hsa-mi R-34a-5p that regulate hub gene.We found that among these 10 hub genes,most were associated with cell cycle,which was consistent with the results obtained in MCONE module analysis of GSEA,KEGG and PPI networks.These results suggest that these hub genes and their upstream mi RNA mi R-106b-5p and mi R-34a-5p are closely related to the pathogenesis of traumatic brain injury.Conclusion:In this study,10 hub genes and their upstream mi RNA mi R-106b-5p and mi R-34a-5p related to traumatic brain injury were obtained through bioinformatics analysis,and they were found to be associated with abnormal activation of neuronal cell cycle after traumatic brain injury.The upstream mi RNA mir-106b-5p and mir-34A-5p may be potential biomarkers of TBI and hub genes CDK4,E2F1 and RB1 may become potential therapeutic targets of TBI. |
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