Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology
BackgroundMajor depressive disorder (MDD) is a severe psychiatric disorder characterized by complex etiology, with genetic determinants that are not fully understood. The objective of this study was to investigate the pathogenesis of MDD and to explore its association with the immune system by ident...
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Frontiers Media S.A.
2024-12-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1485957/full |
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| author | Shasha Wu Shasha Wu Qing Jiang Jinhui Wang Jinhui Wang Daming Wu Yan Ren |
| author_facet | Shasha Wu Shasha Wu Qing Jiang Jinhui Wang Jinhui Wang Daming Wu Yan Ren |
| author_sort | Shasha Wu |
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| description | BackgroundMajor depressive disorder (MDD) is a severe psychiatric disorder characterized by complex etiology, with genetic determinants that are not fully understood. The objective of this study was to investigate the pathogenesis of MDD and to explore its association with the immune system by identifying hub biomarkers using bioinformatics analyses and examining immune infiltrates in human autopsy samples.MethodsGene microarray data were obtained from the Gene Expression Omnibus (GEO) datasets GSE32280, GSE76826, GSE98793, and GSE39653. Our approach included differential expression analysis, weighted gene co-expression network analysis (WGCNA), and protein-protein interaction (PPI) network analysis to identify hub genes associated with MDD. Subsequently, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cytoscape plugin CluGO, and Gene Set Enrichment Analysis (GSEA) were utilized to identify immune-related genes. The final selection of immune-related hub genes was determined through the least absolute shrinkage and selection operator (Lasso) regression analysis and PPI analysis. Immune cell infiltration in MDD patients was analyzed using CIBERSORT, and correlation analysis was performed between key immune cells and genes. The diagnostic accuracy of the identified hub genes was evaluated using receiver operating characteristic (ROC) curve analysis. Furthermore, we conducted a study involving 10 MDD patients and 10 healthy controls (HCs) meeting specific criteria to assess the expression levels of these hub genes in their peripheral blood mononuclear cells (PBMCs). The Herbal Ingredient Target Database (HIT) was employed to screen for herbal components that target these genes, potentially identifying novel therapeutic agents.ResultsA total of 159 down-regulated and 51 up-regulated genes were identified for further analysis. WGCNA revealed 12 co-expression modules, with modules “darked”, “darkurquoise” and “light yellow” showing significant positive associations with MDD. Functional enrichment pathway analysis indicated that these differential genes were associated with immune functions. Integration of differential and immune-related gene analysis identified 21 common genes. The Lasso algorithm confirmed 4 hub genes as potential biomarkers for MDD. GSEA analysis suggested that these genes may be involved in biological processes such as protein export, RNA degradation, and fc gamma r mediated cytotoxis. Pathway enrichment analysis identified three highly enriched immune-related pathways associated with the 4 hub genes. ROC curve analysis indicated that these hub genes possess good diagnostic value. Quantitative reverse transcription-polymerase chain reaction (RT-qPCR) demonstrated significant expression differences of these hub genes in PBMCs between MDD patients and HCs. Immune infiltration analysis revealed significant correlations between immune cells, including Mast cells resting, T cells CD8, NK cells resting, and Neutrophils, which were significantly correlated with the hub genes expression. HIT identified one herb target related to IL7R and 14 targets related to TLR2.ConclusionsThe study identified four immune-related hub genes (TLR2, RETN, HP, and IL7R) in MDD that may impact the diagnosis and treatment of the disorder. By leveraging the GEO database, our findings contribute to the understanding of the relationship between MDD and immunity, presenting potential therapeutic targets. |
| format | Article |
| id | doaj-art-21f8bf806d754caaa103dc9a3bac8da8 |
| institution | OA Journals |
| issn | 1664-0640 |
| language | English |
| publishDate | 2024-12-01 |
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| series | Frontiers in Psychiatry |
| spelling | doaj-art-21f8bf806d754caaa103dc9a3bac8da82025-08-20T02:19:38ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402024-12-011510.3389/fpsyt.2024.14859571485957Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacologyShasha Wu0Shasha Wu1Qing Jiang2Jinhui Wang3Jinhui Wang4Daming Wu5Yan Ren6Department of Psychiatry, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, ChinaTongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaThird Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, ChinaDepartment of Pharmacy, Shanxi Medical University, Taiyuan, ChinaAcademy of Medical Sciences, Shanxi Medical University, Taiyuan, ChinaDepartment of Psychiatry, Xiaoyi City Central Hospital, Xiaoyi, ChinaDepartment of Psychiatry, The Fifth Hospital of Shanxi Medical University, The Fifth Clinical Medical College of Shanxi Medical University, Shanxi Provincial People’s Hospital, Taiyuan, ChinaBackgroundMajor depressive disorder (MDD) is a severe psychiatric disorder characterized by complex etiology, with genetic determinants that are not fully understood. The objective of this study was to investigate the pathogenesis of MDD and to explore its association with the immune system by identifying hub biomarkers using bioinformatics analyses and examining immune infiltrates in human autopsy samples.MethodsGene microarray data were obtained from the Gene Expression Omnibus (GEO) datasets GSE32280, GSE76826, GSE98793, and GSE39653. Our approach included differential expression analysis, weighted gene co-expression network analysis (WGCNA), and protein-protein interaction (PPI) network analysis to identify hub genes associated with MDD. Subsequently, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cytoscape plugin CluGO, and Gene Set Enrichment Analysis (GSEA) were utilized to identify immune-related genes. The final selection of immune-related hub genes was determined through the least absolute shrinkage and selection operator (Lasso) regression analysis and PPI analysis. Immune cell infiltration in MDD patients was analyzed using CIBERSORT, and correlation analysis was performed between key immune cells and genes. The diagnostic accuracy of the identified hub genes was evaluated using receiver operating characteristic (ROC) curve analysis. Furthermore, we conducted a study involving 10 MDD patients and 10 healthy controls (HCs) meeting specific criteria to assess the expression levels of these hub genes in their peripheral blood mononuclear cells (PBMCs). The Herbal Ingredient Target Database (HIT) was employed to screen for herbal components that target these genes, potentially identifying novel therapeutic agents.ResultsA total of 159 down-regulated and 51 up-regulated genes were identified for further analysis. WGCNA revealed 12 co-expression modules, with modules “darked”, “darkurquoise” and “light yellow” showing significant positive associations with MDD. Functional enrichment pathway analysis indicated that these differential genes were associated with immune functions. Integration of differential and immune-related gene analysis identified 21 common genes. The Lasso algorithm confirmed 4 hub genes as potential biomarkers for MDD. GSEA analysis suggested that these genes may be involved in biological processes such as protein export, RNA degradation, and fc gamma r mediated cytotoxis. Pathway enrichment analysis identified three highly enriched immune-related pathways associated with the 4 hub genes. ROC curve analysis indicated that these hub genes possess good diagnostic value. Quantitative reverse transcription-polymerase chain reaction (RT-qPCR) demonstrated significant expression differences of these hub genes in PBMCs between MDD patients and HCs. Immune infiltration analysis revealed significant correlations between immune cells, including Mast cells resting, T cells CD8, NK cells resting, and Neutrophils, which were significantly correlated with the hub genes expression. HIT identified one herb target related to IL7R and 14 targets related to TLR2.ConclusionsThe study identified four immune-related hub genes (TLR2, RETN, HP, and IL7R) in MDD that may impact the diagnosis and treatment of the disorder. By leveraging the GEO database, our findings contribute to the understanding of the relationship between MDD and immunity, presenting potential therapeutic targets.https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1485957/fullmajor depressive disorderimmune-related hub genesdiagnosticnetwork pharmacologybioinformatics |
| spellingShingle | Shasha Wu Shasha Wu Qing Jiang Jinhui Wang Jinhui Wang Daming Wu Yan Ren Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology Frontiers in Psychiatry major depressive disorder immune-related hub genes diagnostic network pharmacology bioinformatics |
| title | Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology |
| title_full | Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology |
| title_fullStr | Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology |
| title_full_unstemmed | Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology |
| title_short | Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology |
| title_sort | immune related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology |
| topic | major depressive disorder immune-related hub genes diagnostic network pharmacology bioinformatics |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1485957/full |
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