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Screening and identification of key biomarkers of depression using bioinformatics
Xinru Kong1, Chuang Wang1, Qiaolan Wu1
1Shandong University of Traditional Chinese Medicine, Jinan, 250355, Shandong, China.
Abstract:
We aimed to identify the molecular biomarkers of MDD disease progression to uncover potential mechanisms of major depressive disorder (MDD). In this study, three microarray data sets, GSE44593, GSE12654, and GSE54563, were cited from the Gene Expression Omnibus database for performance evaluation. To perform molecular functional enrichment analyses, differentially expressed genes (DEGs) were identified, and a protein-protein interaction network was configured using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. To assess multi-purpose functions and pathways, such as signal transduction, plasma membrane, protein binding, and cancer pathways, a total of 220 DEGs, including 143 upregulated and 77 downregulated genes, were selected. Additionally, six central genes were observed, including electron transport system variant transcription factor 6, FMS-related receptor tyrosine kinase 3, carnosine synthetase 1, solute carrier family 22 member 13, prostaglandin endoperoxide synthetase 2, and protein serine kinase H1, which had a significant impact on cell proliferation, extracellular exosome, protein binding, and hypoxia-inducible factor 1 signaling pathway. This study enhances our understanding of the molecular mechanism of the occurrence and progression of MDD and provides candidate targets for its diagnosis and treatment.
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