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Bioinformatics analysis of genes related to pathogenesis of major depression disorder / 生理学报
Acta Physiologica Sinica ; (6): 361-368, 2018.
Article in Chinese | WPRIM | ID: wpr-687817
ABSTRACT
The aim of this study was to screen the genes related to the pathogenesis of major depression disorder (MDD) by bioinformatics. Taking GSE98793 chip data from GEO public database of National Biotechnology Information Center (NCBI) website as the research object, 116 differentially expressed genes (DEGs) were screened by R language limma package. Among the 116 DEGs, 66 genes were up-regulated and 50 down-regulated. The results of gene functional annotation analysis of Gene Ontology (GO) showed that the DEGs were mainly distributed in mitochondria intima and mitochondria. They were involved in copper ion binding, cysteine-type endopeptidase activity, the cell response of interleukin-1, protein processing and other biological processes. KEGG pathway enrichment analysis results showed that the DEGs were mainly concentrated in oxidative phosphorylation, Parkinson's disease, non-alcoholic fatty liver disease, Alzheimer's disease and Huntington's disease etc. The results of protein interaction network analysis showed that there were interactions among proteins encoded by 54 DEGs. Combined with the analysis results of the above methods, 11 key genes were screened out, including UQCRC1, GZMB, NDUFB9, NSF, SLC17A5, CTSH, NDUFB10, UQCR10, ATOX1, CST7 and CTSW, which could be used as candidate genes for the diagnosis and treatment of MDD. Taken together, the key genes were obtained by analyzing the microarray and the DEGs of MDD in the present study, which would provide important clues for revealing the molecular mechanism and clinical targeted therapy of depression.
Full text: Available Index: WPRIM (Western Pacific) Type of study: Etiology study Language: Chinese Journal: Acta Physiologica Sinica Year: 2018 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Etiology study Language: Chinese Journal: Acta Physiologica Sinica Year: 2018 Type: Article