小桶
基因
生物
微阵列分析技术
计算生物学
微阵列
遗传学
生物信息学
转录组
基因表达
作者
Lijuan Gao,Xin Zhao,Jianguo Li,Yong Xu,Yu Zhang
出处
期刊:PubMed
日期:2018-08-25
卷期号:70 (4): 361-368
被引量:3
摘要
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.
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