ISSN 0371-0874, CN 31-1352/Q

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Bioinformatics analysis of genes related to pathogenesis of major depression disorder

GAO Li-Juan1,2, ZHAO Xin1,2, LI Jian-Guo1,2, XU Yong3, Zhang Yu1,2,*

1Department of Physiology, Shanxi Medical University, Taiyuan 030001, China;2Key Laboratory for Cellular Physiology of Ministry of Education, Shanxi Medical University, Taiyuan 030001, China;3Department of Psychiatry, First Hospital, Shanxi Medical University, Taiyuan 030001, China

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.

Key words: GEO database; major depression disorder; bioinformatics

Received: 2017-12-26  Accepted: 2018-07-12

Corresponding author: 张宇  E-mail: zhyucnm@163.com

DOI: 10.13294/j.aps.2018.0053

Citing This Article:

GAO Li-Juan, ZHAO Xin, LI Jian-Guo, XU Yong, Zhang Yu. Bioinformatics analysis of genes related to pathogenesis of major depression disorder. Acta Physiol Sin 2018; 70 (4): 361-368 (in Chinese with English abstract).