Weighted correlation network analysis of gene expression profiling data after traumatic brain injury
10.3760/cma.j.cn501098-20211214-00658
- VernacularTitle:创伤性脑损伤后基因表达谱数据的权重基因共表达网络分析
- Author:
Qilin TANG
1
;
Hao XUE
;
Rongrong ZHAO
;
Gang LI
Author Information
1. 山东大学齐鲁医院神经外科，山东大学脑与类脑科学研究院，山东省脑功能重构重点实验室，济南 250012
- Keywords:
Craniocerebral trauma;
Immunity;
Inflammation;
Energy metabolism;
Autophagy;
Apoptosis
- From:
Chinese Journal of Trauma
2022;38(5):413-419
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To screen important genes and characterize their functions and signaling pathways by weighted gene co-expression network analysis (WGCNA) on the gene expression profile of brain tissue after traumatic brain injury (TBI) so as to provide a reference for the mechanism research and treatment of TBI.Methods:The rat TBI gene expression profile GSE2871 was downloaded from the Gene Expression Omnibus (GEO). The expression profile of 8 799 genes of all 47 rat brain tissue samples was analyzed by WGCNA. After calculating and selecting the β-weighted soft threshold, undirected weighted gene network was constructed to identify gene sets with a high degree of correlation. Sample information was obtained from the database to calculate the correlation between each trait of the samples and modules. Gene ontology (GO) analysis and KEGG pathway analysis were performed for the genes in modules related to injury severity and sampling side in order to unvail the biological processes and pathways involved. The gene-module correlation and gene-trait correlation in these key modules were calculated and hub genes were selected.Results:All the rat brain tissue samples and genes in GSE2871 were included in the WGCNA analysis. A total of 22 modules were obtained, which were marked as modules A to V. Modules E, G, T and U were significantly associated with the sampling side. Modules E and G were significantly related to injury severity . GO analysis and KEGG pathway analysis indicated that the genes in modules E and G with significant relation to injury severity and sampling side were mainly implicated in leukocyte migration, cell chemotaxis, various immune response regulation, etc. The involved pathways included antigen processing and presentation pathways, cell factor-cytokine receptor interaction, interleukin-17 signaling pathway, etc. While modules T and U with significant relation to the sampling side were mainly implicated in hypoxia response, cell metabolism, cell membrane ion channel regulation, signal transduction, etc. The pathways involved were neurodegenerative disease signaling pathways, ribosomes, autophagy, neuroactive ligand-receptor interactions, etc. Among the key modules significantly relating to traits, Tuba1b/1c, Ifitm3, Cebpd, Nfkbia, Serinc3, Pmpcb and Cyp4a8 were selected as hub genes of the above key modules.Conclusion:The genes significantly relating to rat TBI are mainly involved in pathophysiological links such as immune activation, inflammatory response, abnormal energy metabolism, calcium channel disorders, abnormal autophagy and cell apoptosis.
