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Bioinformatics Analysis of Potential Biomarkers and Pathway Identification for Major Depressive Disorder.

ABSTRACT: Aiming at a more comprehensive understanding of the molecular biomarkers and potential mechanisms of major depressive disorder (MDD), from the Gene Expression Omnibus (GEO) database, we first obtained mRNA expression profiles and identified 585 differentially expressed genes (DEGs) through the R software, including 263 upregulated genes and 322 downregulated genes. Then, through the Kyoto Encyclopedia of Genome and Genome (KEGG) pathway and biological process (BP) analysis, we found that the upregulated and downregulated DEGs were abundant in different pathways, respectively. It was noteworthy that upregulated DEGs were the most significantly enriched in the mTOR signaling pathway. Subsequently, through the protein-protein interaction (PPI) network, we identified seven hub genes, namely, EXOSC2, CAMK2A, PRIM1, SMC4, TYMS, CDK6, and RPA2. Finally, through gene set enrichment analysis (GSEA), we obtained that hypoxia, epithelial-mesenchymal transition, hedgehog signaling, and reactive oxygen species pathway were the enriched pathways for MDD patients. The above data results would provide a new direction for the treatment of MDD patients.

SUBMITTER: Qi D

PROVIDER: S-EPMC8357473 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.

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Bioinformatics Analysis of Potential Biomarkers and Pathway Identification for Major Depressive Disorder.

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