Comprehensive bioinformatics analysis of co-expressed genes of post-traumatic stress disorder and major depressive disorder

Post-traumatic stress disorder (PTSD) is one of the most serious sequelae of trauma with serious impact worldwide. Studies have suggested an association between PTSD and major depressive disorder (MDD), but the underlying common mechanisms remain unclear. This study aimed to further explore the molecular mechanism between PTSD and MDD via comprehensive bioinformatics analysis. The microarray data of PTSD and MDD were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify the co-expressed genes associated with PTSD and MDD. Gene Set Enrichment Analysis (GSEA), enrichment analyses based on Disease Ontology (DO), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed using R software. Then, R software was used for single-sample gene set enrichment analysis (ssGSEA) and immune infiltration analysis on the co-expressed genes in the two datasets., Therefore, a logistic regression model was constructed to predict PTSD and MDD using the R language. Ultimately, this study employed PTSD and MDD models to assess alterations in the expression of target genes within the mouse hippocampus. Four core genes (GNAQ, DPEP3, ICAM2, PACSIN2) were obtained through different analyses, and these genes had predictive validity for PTSD and MDD, playing an important role in the common mechanism of PTSD and MDD. The study findings reveal decreased expression levels of DPEP3, GNAQ, and PACDIN2 in PTSD samples, accompanied by an increased expression of ICAM2. In MDD samples, the expression of DPEP3 and ICAM2 is reduced, whereas GNAQ and PACDIN2 show an increase in expression. This study provides a new perspective on the common molecular mechanisms of PTSD and MDD. These common pathways and core genes may provide promising clues for further experimental studies.