Aim and Objective: Despite the prevalence and burden of major depressive disorder
(MDD), our current understanding of the pathophysiology is still incomplete. Therefore, this paper
aims to explore genes and evaluate their diagnostic ability in the pathogenesis of MDD.
Methods: Firstly, the expression profiles of mRNA and microRNA were downloaded from the
gene expression database and analyzed by the GEO2R online tool to identify differentially
expressed genes (DEGs) and differentially expressed microRNAs (DEMs). Then, the DAVID tool
was used for functional enrichment analysis. Secondly, the comprehensive protein-protein
interaction (PPI) network was analyzed using Cytoscape, and the network MCODE was applied to
explore hub genes. Thirdly, the receiver operating characteristic (ROC) curve of the core gene was
drawn to evaluate clinical diagnostic ability. Finally, mirecords was used to predict the target genes
Results: A total of 154 genes were identified as DEGs, and 14 microRNAs were identified as
DEMs. Pathway enrichment analysis showed that DEGs were mainly involved in hematopoietic
cell lineage, PI3K-Akt signaling pathway, cytokine-cytokine receptor interaction, chemokine
signaling pathway, and JAK-STAT signaling pathway. Three important modules are identified and
selected by the MCODE clustering algorithm. The top 12 hub genes, including CXCL16, CXCL1,
GNB5, GNB4, OPRL1, SSTR2, IL7R, MYB, CSF1R, GSTM1, GSTM2, and GSTP1, were
identified as important genes for subsequent analysis. Among these important hub genes, GSTM2,
GNB4, GSTP1 and CXCL1 have the good diagnostic ability. Finally, by combining these four
genes, the diagnostic ability of MDD can be improved to 0.905, which is of great significance for
the clinical diagnosis of MDD.
Conclusion: Our results indicate that GSTM2, GNB4, GSTP1 and CXCL1 have potential
diagnostic markers and are of great significance in clinical research and diagnostic application of
MDD. This result needs a large sample study to further confirm the pathogenesis of MDD.