Integrative bulk and single-cell transcriptome analyses reveal integrated stress response-related biomarkers in periodontitis with experimental validation

Linling DuJie PanNan XuFeng YanWeiyi TianQiyan Li^*

• The First People's Hospital of Yunnan Province, Kunming, China

Periodontitis (PD) is a chronic, site-specific inflammatory disorder, serving as a primary etiological factor for tooth loss. The integrated stress response (ISR), which is intricately linked to inflammation, remains poorly understood in the context of PD. This study aims to investigate the role of ISR-related biomarkers in PD. Transcriptomic data related to PD were sourced from publicly available repositories, and a robust bioinformatics approach was used to identify ISR-associated molecular markers relevant to PD pathogenesis, incorporating machine learning techniques and expression pattern validation methods. Pathway enrichment analyses and immune landscape characterization were performed to uncover the molecular mechanisms by which these markers contribute to PD progression. Single-cell RNA sequencing (scRNA-seq) was employed to delineate distinct cell populations and investigate the expression patterns of candidate biomarkers. To validate the expression profiles, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assays were conducted. BTG2, DERL3, FOS, HSPA13, and YOD1 were identified as potential PD biomarkers. Notably, BTG2, DERL3, FOS, and HSPA13 were co-enriched in the "osteoclast differentiation" pathway. Among all correlations examined, DERL3 showed the highest positive correlation with plasma cells and the strongest negative correlation with resting dendritic cells (|cor| > 0.3, P < 0.05). Furthermore, scRNA-seq analysis highlighted T cells as the key cell type. During T cell differentiation, BTG2 expression initially increased, then decreased, followed by a subsequent rise in mid-to-late stages; DERL3 exhibited a transient increase before returning to baseline, while FOS expression increased gradually throughout the process. RT-qPCR results confirmed significantly elevated expression levels of BTG2, DERL3, FOS, and HSPA13, along with reduced YOD1 expression in the PD group (P < 0.05), consistent with database-predicted expression patterns. This study integrates bulk and scRNA-seq analyses to identify BTG2, DERL3, FOS, HSPA13, and YOD1 as biomarkers, with T cells as the central cell type, offering novel diagnostic approaches for PD.