AUTHOR=Yao Ping-An , Sun Hai-Ju , Li Xiao-Yu 

TITLE=Identification of key genes in late-onset major depressive disorder through a co-expression network module

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.1048761

DOI=10.3389/fgene.2022.1048761

ISSN=1664-8021

ABSTRACT=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 ten LOD patients and twelve 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 the most clinically significant modules through the weighted gene co-expression network analysis (WGCNA). Functional analysis of the genes in the most clinically significant modules were taken to explore the potential mechanism of LOD, followed by protein – protein interaction (PPI) analysis and hub genes identification in the core area of PPI network. Furthermore, we identified immune infiltrating cells through cells estimating relative subsets of RNA transcripts (CIBERSORT) algorithm between healthy subjects and LOD patients with GSE98793 dataset. Next, six hub genes (CD27, IL7R, CXCL1, CCR7, IGLL5 and CD79A) were obtained by intersecting hub genes with DEGs, followed by verifying diagnostic accuracy with receiver operating characteristic curve (ROC). In addition, we constructed the least absolute contraction 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 of 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.