Identification and characterization of fibroblast-related biomarkers and pro-inflammatory subpopulations in...

Periodontitis is a common inflammatory disease that severely impairs oral health and may contribute to systemic complications such as cardiovascular diseases. Fibroblasts play a crucial role in the progression and repair processes of periodontitis. Exploring related biomarkers and pro-inflammatory fibroblast (PIF) subpopulations may offer potential therapeutic strategies for periodontitis. We integrated transcriptomic and single-cell RNA sequencing (scRNA-seq) data to identify hub fibroblast genes via Least Absolute Shrinkage and Selection Operator (LASSO) regression. Diagnostic models and nomograms were developed and validated based on these genes. Fibroblast molecular patterns were defined using ConsensusClusterPlus package, and pseudotime analysis was performed with Monocle package. Fibroblast-related genes (FRGs) and PIF subsets were confirmed by quantitative real-time PCR (qRT-PCR), immunohistochemistry (IHC), and fluorescence in situ hybridization (FISH). By integrating bulk transcriptomic and single-cell RNA sequencing data, six FRGs (XBP1, SELL, ST6GAL1, IGHG1, CD79A, and PIM2) were identified using LASSO regression to construct a diagnostic model. The area under the curve (AUC) values for the model were 0.894, 0.919, and 0.746 in the GSE10334, GSE16134, and GSE173078 datasets, respectively. A predictive nomogram was also developed and validated. Based on these FRGs, periodontitis samples were clustered into three groups. Enrichment analysis revealed involvement of classical inflammatory pathways such as KRAS/p53 and IL-6/JAK/STAT. Immune infiltration analysis showed that cluster 1 exhibited a pro-inflammatory microenvironment. CXCL13⁺ fibroblasts were significantly increased in periodontitis tissues. qRT-PCR confirmed significantly elevated expression of SELL, CD79A, and ST6GAL1 in periodontitis tissues. IHC demonstrated increased SELL expression in periodontitis samples, and FISH analysis revealed a marked increase of CXCL13⁺ fibroblasts in periodontitis tissues, consistent with the bioinformatics findings. This study not only confirms the critical role of fibroblasts in periodontitis but also identifies FRGs and a PIF subset, CXCL13⁺ fibroblasts. Our findings provide novel insights into the pathogenic mechanisms of fibroblasts in periodontitis and may inform the development of targeted diagnostic and therapeutic strategies.