Identification of Key Genes Involved in Lactic Acid Metabolism in Periodontitis Based on Bioinformatics Analysis.

Area of Science:

• Biochemistry
• Genetics
• Immunology

Background:

• Lactic acid metabolism is associated with periodontitis progression.
• Identifying reliable biomarkers is crucial for periodontitis diagnosis and treatment.

Purpose of the Study:

• To identify key genes associated with periodontitis using machine learning.
• To explore the diagnostic potential and therapeutic targets for periodontitis.

Main Methods:

• Machine learning algorithms (LASSO, SVM-RFE) were applied to analyze gene expression datasets (GSE16134, GSE173078).
• Gene Set Enrichment Analysis (GSEA) and immune infiltration analysis were performed.
• Molecular docking and experimental validation in cell and animal models were conducted.

Main Results:

• CFI and COQ2 were identified as key genes with diagnostic performance (AUC > 0.75).
• These genes are involved in MAPK signaling, endocytosis, and ubiquitin-mediated proteolysis.
• Periodontitis is characterized by increased plasma cells and decreased CD8 T cells.
• Amiodarone showed strong binding affinity to CFI and COQ2.
• CFI was upregulated and COQ2 downregulated in experimental models.

Conclusions:

• CFI and COQ2 show promise as diagnostic biomarkers for periodontitis.
• These genes represent potential therapeutic targets for periodontitis treatment.