Mitochondrial Metabolic Biomarkers in Periodontitis: Discovery and Clinical Validation

Mitochondrial metabolic dysregulation is associated with periodontitis (PD); however, related biomarkers remain unclear. In this study, we identified key mitochondrial metabolism-related biomarkers in PD through integrated bioinformatics technology.

Transcriptomic and single-cell RNA sequencing data from the Gene Expression Omnibus database were analysed using machine learning to identify biomarkers. A diagnostic nomogram was constructed. Immune infiltration, drug prediction, and T-cell dynamic expression were assessed. Putative biomarkers were validated in clinical samples and a rat PD model by reverse transcription-quantitative polymerase chain reaction, immunohistochemistry, and Western blot analysis.

Six biomarkers were identified, which included ENTPD1, CYP24A1, ADA, TDO2 (upregulated), OSBPL6, and NUDT15 (downregulated). The nomogram exhibited excellent diagnostic efficacy (area under the curve [AUC] = 0.954). The biomarkers correlated with plasma cells and resting dendritic cells. Single-cell analysis revealed dynamic expression during T-cell differentiation. CTA018 exhibited strong binding to CYP24A1. Five biomarkers were validated in clinical samples, and the upregulation of ENTPD1, CYP24A1, and TDO2 protein and messenger RNA was confirmed in a rat model and correlated with PD progression.

ENTPD1, CYP24A1, and TDO2 are mitochondrial metabolism-related biomarkers with high diagnostic potential in PD and targets for therapy.

The identified biomarkers, particularly ENTPD1, CYP24A1, and TDO2, have strong diagnostic value. The nomogram contributed to PD risk stratification. Associations with immune infiltration and drug sensitivity may guide immunotherapy and targeted therapy.