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 of DEMs.
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, cytokinecytokine
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 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.