ArticleBMC oral health2025
Integrated bioinformatics analysis identifies glutathione metabolism-related genes as diagnostic biomarkers for periodontitis.
Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Loss of GGT6 promotes colorectal cancer progression and correlates with poor prognosis: a study based on multi-database mining and functional validation.Translational cancer research · 2026Article
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Abstract
backgroundPeriodontitis affects over 1 billion people globally, with oxidative stress and glutathione depletion playing crucial roles in disease progression. This study aimed to identify glutathione metabolism-related genes as diagnostic biomarkers for periodontitis using integrated bioinformatics approaches.
methodsWeighted Gene Co-expression Network Analysis (WGCNA) was performed on independent datasets. Key genes were identified in combination with GSE16134 dataset differential expression analysis, which were then validated in the GSE10334 dataset. Immune infiltration analysis using CIBERSORT algorithm, consensus clustering for molecular subtyping, and competing endogenous RNA (ceRNA) network construction were conducted to explore regulatory mechanisms. Drug-gene interaction analysis and molecular docking studies identified potential therapeutic compounds. Experimental validation was performed using ligature-induced periodontitis in rats.
resultsThree key glutathione metabolism-related genes were identified: GSTA4 and GGT6 (downregulated) and SLC7A11 (upregulated) in periodontitis patients. The diagnostic model achieved superior performance with AUC values exceeding 0.8. Two distinct molecular subtypes were identified based on immune infiltration patterns. ceRNA regulatory network analysis revealed complex interactions involving all three genes. Drug-gene interaction analysis revealed erastin as a potential therapeutic compound targeting SLC7A11. Experimental validation in rat periodontitis confirmed the upregulation of SLC7A11 in periodontal tissues.
conclusionsOur study identifies SLC7A11, GSTA4, and GGT6 as robust periodontitis biomarkers with excellent diagnostic accuracy. The continuous up-regulation and experimental verification of SLC7A11 genes have established them as promising therapeutic targets, laying the foundation for precision medicine in the field of periodontal therapy.
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