The role of neutrophils, fibroblasts, and osteoclasts in periodontitis: A transcriptomic and single-cell analysis

This study aimed to elucidate the molecular mechanisms and regulatory pathways driving the onset and progression of periodontitis (PD). Four transcriptomic datasets from the Gene Expression Omnibus database were integrated to identify differentially expressed genes in gingival tissues of healthy individuals and patients with Pd. Common differentially expressed genes were determined using the RobustRankAggreg algorithm and subjected to pathway enrichment analysis. In parallel, transcriptome sequencing was performed on clinical gingival samples (three healthy controls and 3 patients with PD) to validate the findings. Single-cell RNA sequencing data from periodontal tissues, including healthy, diseased, and post-treatment groups, were further analyzed. Finally, in vitro experiments using human fibroblasts stimulated with Interleukin-1 beta were conducted to confirm key regulatory interactions. Core upregulated genes were enriched in pathways such as Staphylococcus aureus infection, osteoclast differentiation, and Nuclear factor kappa-light-chain-enhancer of activated B cells signaling. Validation with clinical samples supported these findings and highlighted key gene families including LILRB and FCGR. In monocytes, tumor necrosis factor receptor superfamily member 11A (RANK) expression was elevated in PD, with the highest levels in osteoclasts. Fibroblasts were identified as the predominant source of tumor necrosis factor ligand superfamily member 11 (RANKL) (TNFSF11), and Interleukin-1 beta secretion by neutrophils was shown to induce TNFSF11 expression in fibroblasts. Among fibroblast subpopulations, clusters 1, 6, and 8 displayed abnormal differentiation phenotypes characterized by elevated TNFSF11 and IL1R1 expression. Our results define a neutrophil-fibroblast-osteoclast axis that contributes to periodontal tissue destruction and bone resorption. This study provides mechanistic insights into PD and identifies potential molecular targets for precision therapy.