Identification of key genes in late-onset major depressive disorder through a co-expression network module
Late-onset major depressive disorder (LOD) increases the risk of disability and suicide in elderly patients. However, the complex pathological mechanism of LOD still remains unclear. We selected 10 LOD patients and 12 healthy control samples from the GSE76826 dataset for statistical analysis. Under...
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| Format: | Article |
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Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.1048761/full |
| _version_ | 1811178494500012032 |
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| author | Ping-An Yao Ping-An Yao Hai-Ju Sun Xiao-Yu Li Xiao-Yu Li |
| author_facet | Ping-An Yao Ping-An Yao Hai-Ju Sun Xiao-Yu Li Xiao-Yu Li |
| author_sort | Ping-An Yao |
| collection | DOAJ |
| description | Late-onset major depressive disorder (LOD) increases the risk of disability and suicide in elderly patients. However, the complex pathological mechanism of LOD still remains unclear. We selected 10 LOD patients and 12 healthy control samples from the GSE76826 dataset for statistical analysis. Under the screening criteria, 811 differentially expressed genes (DEGs) were screened. We obtained a total of two most clinically significant modules through the weighted gene co-expression network analysis (WGCNA). Functional analysis of the genes in the most clinically significant modules was performed to explore the potential mechanism of LOD, followed by protein–protein interaction (PPI) analysis and hub gene identification in the core area of the PPI network. Furthermore, we identified immune infiltrating cells using the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm between healthy subjects and LOD patients with the GSE98793 dataset. Next, six hub genes (CD27, IL7R, CXCL1, CCR7, IGLL5, and CD79A) were obtained by intersecting hub genes with DEGs, followed by verifying the diagnostic accuracy with the receiver operating characteristic curve (ROC). In addition, we constructed the least absolute shrinkage and selection operator (LASSO) regression model for hub gene cross-validation. Finally, we found that CD27 and IGLL5 were good diagnostic indicators of LOD, and CD27 may be the key gene of immune function change in LOD. In conclusion, our research shows that the changes in the immune function may be an important mechanism in the development of LOD, which can provide some guidance for the related research of LOD in the future. |
| first_indexed | 2024-04-11T06:19:19Z |
| format | Article |
| id | doaj.art-2f8e634fddad400f8cf46e302884d0ad |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-11T06:19:19Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-2f8e634fddad400f8cf46e302884d0ad2022-12-22T04:40:49ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-12-011310.3389/fgene.2022.10487611048761Identification of key genes in late-onset major depressive disorder through a co-expression network modulePing-An Yao0Ping-An Yao1Hai-Ju Sun2Xiao-Yu Li3Xiao-Yu Li4School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, ChinaDepartment of Neurobiology and Acupuncture Research, The Third Clinical Medical College, Zhejiang Chinese Medical University, Key Laboratory of Acupuncture and Neurology of Zhejiang Province, Hangzhou, ChinaDepartment of Neurobiology and Acupuncture Research, The Third Clinical Medical College, Zhejiang Chinese Medical University, Key Laboratory of Acupuncture and Neurology of Zhejiang Province, Hangzhou, ChinaDepartment of Neurobiology and Acupuncture Research, The Third Clinical Medical College, Zhejiang Chinese Medical University, Key Laboratory of Acupuncture and Neurology of Zhejiang Province, Hangzhou, ChinaThe Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, ChinaLate-onset major depressive disorder (LOD) increases the risk of disability and suicide in elderly patients. However, the complex pathological mechanism of LOD still remains unclear. We selected 10 LOD patients and 12 healthy control samples from the GSE76826 dataset for statistical analysis. Under the screening criteria, 811 differentially expressed genes (DEGs) were screened. We obtained a total of two most clinically significant modules through the weighted gene co-expression network analysis (WGCNA). Functional analysis of the genes in the most clinically significant modules was performed to explore the potential mechanism of LOD, followed by protein–protein interaction (PPI) analysis and hub gene identification in the core area of the PPI network. Furthermore, we identified immune infiltrating cells using the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm between healthy subjects and LOD patients with the GSE98793 dataset. Next, six hub genes (CD27, IL7R, CXCL1, CCR7, IGLL5, and CD79A) were obtained by intersecting hub genes with DEGs, followed by verifying the diagnostic accuracy with the receiver operating characteristic curve (ROC). In addition, we constructed the least absolute shrinkage and selection operator (LASSO) regression model for hub gene cross-validation. Finally, we found that CD27 and IGLL5 were good diagnostic indicators of LOD, and CD27 may be the key gene of immune function change in LOD. In conclusion, our research shows that the changes in the immune function may be an important mechanism in the development of LOD, which can provide some guidance for the related research of LOD in the future.https://www.frontiersin.org/articles/10.3389/fgene.2022.1048761/fulllate-onset major depressive disorderweighted gene co-expression network analysisdifferentially expressed genesimmune infiltrationhub genereceiver operating characteristic |
| spellingShingle | Ping-An Yao Ping-An Yao Hai-Ju Sun Xiao-Yu Li Xiao-Yu Li Identification of key genes in late-onset major depressive disorder through a co-expression network module Frontiers in Genetics late-onset major depressive disorder weighted gene co-expression network analysis differentially expressed genes immune infiltration hub gene receiver operating characteristic |
| title | Identification of key genes in late-onset major depressive disorder through a co-expression network module |
| title_full | Identification of key genes in late-onset major depressive disorder through a co-expression network module |
| title_fullStr | Identification of key genes in late-onset major depressive disorder through a co-expression network module |
| title_full_unstemmed | Identification of key genes in late-onset major depressive disorder through a co-expression network module |
| title_short | Identification of key genes in late-onset major depressive disorder through a co-expression network module |
| title_sort | identification of key genes in late onset major depressive disorder through a co expression network module |
| topic | late-onset major depressive disorder weighted gene co-expression network analysis differentially expressed genes immune infiltration hub gene receiver operating characteristic |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.1048761/full |
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