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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
Published on: January 10, 2019
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Integrating bulk and single-cell RNA data with machine learning to explore mitophagy in periodontitis
Qisheng Hu1,2, Yongheng Zhang1, Huawei Ming2
1Department of Stomatology, North Sichuan Medical College, Nanchong, Sichuan, China.
Medicine
|August 27, 2025
Summary
Periodontitis involves oxidative stress, and this study found increased mitophagy activity. Four core genes (BNIP3L, VPS13C, CTTN, MAP1LC3B) were identified, offering insights into periodontitis progression and potential therapies.
Area of Science:
- Cell Biology
- Genomics
- Immunology
Background:
- Periodontitis (PD) is a chronic inflammatory disease driven by oxidative stress.
- Mitophagy's role in PD pathogenesis and its regulatory mechanisms are not fully understood.
Purpose of the Study:
- To identify core mitophagy-related genes in periodontitis using multi-omics data.
- To elucidate the regulatory mechanisms of these genes in PD progression.
Main Methods:
- Utilized single-cell and bulk RNA sequencing data.
- Applied multiple algorithms for gene identification and screening, including machine learning.
- Integrated immune infiltration, cell communication, and gene interaction network analyses.
Main Results:
- Significantly elevated mitophagy activity was observed in PD tissues, especially in monocytes/macrophages and endothelial cells.
- Identified four core genes: BNIP3L, VPS13C, CTTN, and MAP1LC3B.
- Downregulated BNIP3L and CTTN, and upregulated VPS13C and MAP1LC3B correlated with PD severity and immune infiltration.
Conclusions:
- BNIP3L, VPS13C, CTTN, and MAP1LC3B are key mitophagy-related genes in periodontitis.
- Monocytes/macrophages and endothelial cells play critical roles in PD via intercellular communication mediated by these genes.
- Findings support mitophagy-targeted diagnostics and precision therapy for periodontitis.
