ArticleInternational journal of genomics2025
Identification of Key Periodontitis Genes and Their Mechanisms of Action Using Comprehensive Multiple Microarray Analysis and Mendelian Randomization Methods.
Article in International journal of genomics, 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.
- Identification of Key Periodontitis Genes and Their Mechanisms of Action Using Comprehensive Multiple Microarray Analysis and Mendelian Randomization Methods.International journal of genomics · 2025Article
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Abstract
Background: Periodontitis, a chronic inflammatory disease, damages the soft tissues and bones around the teeth. Affecting adults, mild periodontitis is common, while severe cases impact up to 20% of individuals, with a prevalence of 45%-50%. This study was aimed at identifying and analyzing the functions of genes differentially expressed in periodontitis through bioinformatics. Additionally, we aimed to validate the causal relationships of these genes with periodontitis using Mendelian randomization. Methods: The investigation included 557 samples obtained from 210 patients suffering from periodontitis within the GEO database, focusing on the differential expression of genes and conducting a weighted gene coexpression network analysis (WGCNA). Hub genes associated with periodontitis were identified for subsequent functional enrichment and pathway analysis through Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The diagnostic performance of predictive models for the five most significant hub genes was assessed using receiver operating characteristic (ROC) curves. Finally, we performed Mendelian randomization analysis to evaluate the genetic causal links between the hub genes and periodontitis. Results: By intersecting WGCNA's most relevant module genes with significantly differentially expressed genes, we identified 98 hub genes. GO and KEGG analyses underscored the roles of these hub genes in immune cell activation, cytokine signaling, and inflammation. Cytoscape analysis of the top five hub genes, including CXCR4, CD19, CD27, FCGR3B, and CD79A, was conducted. ROC analysis demonstrated excellent performance of the linear predictor model in predicting the risk of periodontitis. Through the application of the inverse variance weighted (IVW) approach, our analysis revealed that the central gene CD27 is linked to periodontitis (OR = 0.7536, 95 Conclusion: Our analysis established a genetic link between the CD27 gene and periodontitis, indicating its potential as a diagnostic or therapeutic target.
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