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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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Autores principales: Yao, Ping-An, Sun, Hai-Ju, Li, Xiao-Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9763307/
https://www.ncbi.nlm.nih.gov/pubmed/36561317
http://dx.doi.org/10.3389/fgene.2022.1048761
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author Yao, Ping-An
Sun, Hai-Ju
Li, Xiao-Yu
author_facet Yao, Ping-An
Sun, Hai-Ju
Li, Xiao-Yu
author_sort Yao, Ping-An
collection PubMed
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.
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spelling pubmed-97633072022-12-21 Identification of key genes in late-onset major depressive disorder through a co-expression network module Yao, Ping-An Sun, Hai-Ju Li, Xiao-Yu Front Genet Genetics 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. Frontiers Media S.A. 2022-12-06 /pmc/articles/PMC9763307/ /pubmed/36561317 http://dx.doi.org/10.3389/fgene.2022.1048761 Text en Copyright © 2022 Yao, Sun and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Yao, Ping-An
Sun, Hai-Ju
Li, Xiao-Yu
Identification of key genes in late-onset major depressive disorder through a co-expression network module
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 Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9763307/
https://www.ncbi.nlm.nih.gov/pubmed/36561317
http://dx.doi.org/10.3389/fgene.2022.1048761
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