Single-cell and bulk transcriptomic analyses reveal PANoptosis-associated immune dysregulation of fibroblasts in periodontitis

Erli WuQiangqiang ZhuoXuan YinJingjing LiHuijuan ZhangFeihan GuFeng LiangXianqing ZhouZiyang GaoBang Li^*Qingqing Wang^*Wei Shao^*

• Anhui Medical University, Hefei, China

Abstract Background: PANoptosis is a newly recognized form of programmed inflammatory cell death implicated in numerous inflammation-related diseases. However, its precise role and underlying mechanisms in periodontitis (PD) remain unclear. Methods: We analyzed single-cell RNA sequencing (scRNA-seq) on gingival tissues from PD patients and healthy individuals to profile cellular composition and quantify cell-type distributions. Functional enrichment analyses were used to explore PANoptosis and related pathways, with five gene set scoring methods applied to quantify PANoptosis activity in human gingival fibroblasts (HGFs). The expression of PANoptosis-related markers was validated by immunofluorescence staining and qPCR in HGFs and gingival tissues from PD model mice. Based on PANoptosis scores, HGFs were stratified into high- and low-activity groups. Cell-cell communication and spatial transcriptomic analyses were integrated to examine their interactions with immune cells in the periodontal microenvironment. Finally, bulk RNA-seq data were subjected to comprehensive analysis using 113 machine learning models to screen for core PANoptosis-associated genes, which were subsequently validated through qPCR and immunohistochemistry in gingival tissues. Results: scRNA-seq analysis revealed a decreased proportion of HGFs alongside enrichment of multiple PANoptosis-related pathways in PD samples. Further assessment demonstrated significantly elevated PANoptosis activity in HGFs from PD compared to controls, which was validated by tissue-level immunofluorescence staining. In vitro experiments using cultured HGFs and in vivo analyses in PD model mice further confirmed upregulation of PANoptosis-related markers via immunofluorescence and qPCR. Upon stratifying HGFs into high- and low-PANoptosis groups, cell-cell communication and spatial transcriptomic analyses indicated that high-PANoptosis HGFs exhibited enhanced interactions with immune cells within the periodontal microenvironment. Additionally, bulk transcriptomic profiling combined with machine learning approaches identified four key PANoptosis-associated genes, which were subsequently validated in human gingival tissues. Conclusion: Our findings demonstrate that PANoptosis is activated in HGFs in the context of PD, which may drive immune dysregulation and facilitate disease progression. By integrating bulk transcriptomic data with machine learning algorithms, we identified and validated key PANoptosis-related genes, highlighting their potential as novel therapeutic targets.