Journal of International Research in Medical and Pharmaceutical Sciences

Periodontitis arises from dysregulated crosstalk among epithelial, immune, and stromal compartments, ultimately driving connective-tissue and alveolar-bone loss. While single-cell RNA-seq (scRNA-seq) has mapped this heterogeneity, insights are fragmented across studies with differing cohorts and preprocessing. Here we harmonize two independent gingival scRNA-seq datasets (Chen et al., 2022; Easter et al., 2024) into a unified, patient-aware atlas. We standardize gene identifiers and metadata, then integrate with Harmony while preserving patient labels to minimize batch effects without erasing biological variation. The integrated embedding recovers diverse immune and stromal populations—including fibroblast subsets, macrophages, T cells, endothelial and epithelial lineages—and supports consistent cell-state annotations across cohorts. To identify robust disease signals, we aggregate counts into patient-level pseudobulk profiles and perform differential expression contrasting periodontitis versus non-periodontitis samples. This reveals conserved programs marked by upregulation of inflammatory and tissue-remodeling pathways and downregulation of protective homeostatic processes. Cell type–resolved boxplots highlight lineage-specific shifts across endothelial, fibroblast, keratinocyte, pericyte, plasma-cell, and T-cell compartments, underscoring coordinated immune–stromal remodeling in disease. Collectively, this cross-cohort, patient-preserving harmonization establishes a stable reference for periodontal biology and a framework for biomarker nomination and therapeutic target discovery.