AUTHOR=Wang Dangdang , Pu Yanyu , Tan Sisi , Wang Xiaochen , Zeng Lihong , Lei Junqin , Gao Xi , Li Hong 

TITLE=Identification of immune-related biomarkers for glaucoma using gene expression profiling

JOURNAL=Frontiers in Genetics

VOLUME=Volume 15 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2024.1366453

DOI=10.3389/fgene.2024.1366453

ISSN=1664-8021

ABSTRACT=Glaucoma, a primary cause of irreversible vision loss, is characterized by complex optic neuropathy in which immune mechanisms play a crucial role. This research focused on investigating the molecular intricacies of glaucoma, particularly its immune-related aspects. By analyzing gene expression profiles from glaucoma patients, our objective was to identify differentially expressed genes (DEGs) that are associated with immune responses. We utilized weighted gene co-expression network analysis (WGCNA) and various machine learning algorithms to successfully identify key biomarkers and establish distinct subclusters related to immune reactions in glaucoma. Additionally, we employed single-sample gene set enrichment analysis (ssGSEA) to assess the relationship between hub genes and specific immune cell infiltration, as well as the activation of immune pathways. To validate our findings, we developed an NMDAinduced cell excitotoxic model of glaucoma and performed real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) assays to determine the expression levels of these hub genes in glaucoma. Our analysis revealed 409 DEGs that effectively differentiate between healthy individuals and glaucoma patients, emphasizing the significant role of immune responses in the development of the disease. Furthermore, the analysis of immune cell infiltration demonstrated elevated levels of activated dendritic cells, natural killer cells, monocytes, and immature dendritic cells in glaucoma samples. Through machine learning, we identified three hub genes -CD40LG, TEK, and MDK -that exhibit a synergistic or antagonistic interaction with glaucoma. These genes were further validated as potential diagnostic biomarkers capable of identifying individuals at high risk for glaucoma. Notably, in the NMDA-induced cell excitotoxicity model, these genes showed increased expression. In conclusion, our study utilizes various bioinformatics methods to propose three immune-related genes (IRGs) as potential diagnostic markers for glaucoma. This discovery opens up new opportunities for investigating the pathogenesis of glaucoma and developing targeted therapies.