Identification and validation of diagnostic genes IFI44 and IRF9 in insomnia-associated autoimmune uveitis

ObjectiveInsomnia is increasingly recognized as a significant factor in the development of various autoimmune diseases, including autoimmune uveitis (AU). We investigated insomnia-associated genes that may contribute to AU pathogenesis and sought to identify potential biomarkers for insomnia-associa...

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Main Authors: Chao Wu, Hui Feng, Meng Tian, Baorui Chu, Xianyang Liu, Shuhao Zeng, Yakun Wang, Hong Wang, Shengping Hou, Qingfeng Liang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Immunology
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Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2025.1519371/full
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Summary:ObjectiveInsomnia is increasingly recognized as a significant factor in the development of various autoimmune diseases, including autoimmune uveitis (AU). We investigated insomnia-associated genes that may contribute to AU pathogenesis and sought to identify potential biomarkers for insomnia-associated AU.MethodsMicroarray data related to insomnia and AU were downloaded from the Gene Expression Omnibus (GEO) database and analyzed. The GEO2R tool was used to identify differentially expressed genes (DEGs) that were common between insomnia and AU. Weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI), functional enrichment, and CMap analyses were then performed to identify pathogenic genes, underlying mechanisms, and potential therapeutic drugs for insomnia-associated AU. Least absolute shrinkage and selection operator regression was employed to screen for candidate biomarkers, and their diagnostic performance was evaluated using receiver operating characteristic (ROC) curves and quantitative polymerase chain reaction (qPCR). Finally, molecular docking was applied to verify binding activities.ResultsWe identified 138 up-regulated and 85 down-regulated DEGs that were common to insomnia and AU. PPI network analysis highlighted 10 key genes, CMap analysis identified 30 compounds, and WGCNA revealed 54 key genes and 30 compounds. Intersection of the above-mentioned key genes and compounds identified six genes and five compounds. After verification by qPCR and ROC curve analysis, IFI44 and IRF9 were confirmed as hub genes. Finally, two compounds were selected based on docking scores of less than −7 kcal/mol.ConclusionOur study demonstrated involvement of the viral response in both insomnia and AU and identified the diagnostic significance of IFI44 and IRF9 in these conditions. These findings provide novel insights for future diagnostic and therapeutic strategies to treat insomnia-associated AU.
ISSN:1664-3224