Diagnosis of Periodontitis via Neutrophil Degranulation Signatures Identified by Integrated scRNA-Seq and Deep Learning.

Background and objective: Periodontitis, a chronic inflammatory disease driven by host immune dysregulation, leads to progressive destruction of periodontal tissues. This study employed an integrative approach combining single-cell transcriptomics, hierarchical weighted gene co-expression network analysis (hdWGCNA), and deep learning algorithms to identify key biomarkers associated with neutrophil degranulation in periodontitis, aiming to establish diagnostic models for early detection and precision interventions.

Methods

We integrated single-cell RNA sequencing (scRNA-seq) data from human gingival tissues with bulk transcriptomic datasets. Pathogenic neutrophil subsets were characterized via pseudotime trajectory and cell-cell communication analyses. Hierarchical weighted gene co-expression network analysis (hdWGCNA) identified functional modules linked to degranulation. Machine learning and a convolutional neural network (CNN) model combining gene expression and immune cell profiles were developed for diagnosis.

Results

scRNA-seq revealed a neutrophil subpopulation significantly increased infiltration in periodontitis, with cell-cell communication and pseudotime trajectory analyses demonstrating amplified inflammatory crosstalk. hdWGCNA identified the turquoise module enriched in PD-KEY-Neutrophils, containing hub genes linked to neutrophil degranulation and complement activation. Immune infiltration and non-negative matrix factorization linked high-degranulation neutrophil signatures to the periodontal immunity microenvironment. Machine learning demonstrated that the neutrophil degranulation-associated genes effectively distinguish diseased gingival tissue, suggesting their potential to predict periodontitis. Finally, integrating transcriptomic and immunological data, we developed a gene-immune CNN deep learning model accurately diagnosed periodontitis in diverse cohorts (AUC = 0.922).

Conclusions

Our study identified a pathogenic neutrophil subpopulation driving periodontitis through degranulation and inflammation. The neutrophil degranulation genes serve as critical biomarkers, offering new insights for clinical diagnosis and treatment of periodontitis.