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The spatial transcriptomic landscape of human gingiva in health and periodontitis

  • Zongshan Shen
  • , Ran Zhang
  • , Yunjia Huang
  • , Jiayao Chen
  • , Mengjun Yu
  • , Chunhua Li
  • , Yong Zhang
  • , Lingling Chen
  • , Xin Huang
  • , Jichen Yang
  • , Zhengmei Lin
  • , Songlin Wang
  • , Bin Cheng
  • Sun Yat-Sen University
  • Capital Medical University
  • Peking University
  • Chinese Academy of Medical Sciences
  • BGI-Shenzhen

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

The gingiva is a key oral barrier that protects oral tissues from various stimuli. A loss of gingival tissue homeostasis causes periodontitis, one of the most prevalent inflammatory diseases in humans. The human gingiva exists as a complex cell network comprising specialized structures. To understand the tissue-specific pathophysiology of the gingiva, we applied a recently developed spatial enhanced resolution omics-sequencing (Stereo-seq) technique to obtain a spatial transcriptome (ST) atlas of the gingiva in healthy individuals and periodontitis patients. By utilizing Stereo-seq, we identified the major cell types present in the gingiva, which included epithelial cells, fibroblasts, endothelial cells, and immune cells, as well as subgroups of epithelial cells and immune cells. We further observed that inflammation-related signalling pathways, such as the JAK-STAT and NF-κB signalling pathways, were significantly upregulated in the endothelial cells of the gingiva of periodontitis patients compared with those of healthy individuals. Additionally, we characterized the spatial distribution of periodontitis risk genes in the gingiva and found that the expression of IFI16 was significantly increased in endothelial cells of inflamed gingiva. In conclusion, our Stereo-seq findings may facilitate the development of innovative therapeutic strategies for periodontitis by mapping periodontitis-relevant genes and pathways and effector cells.

Original languageEnglish
Pages (from-to)720-732
Number of pages13
JournalScience China Life Sciences
Volume67
Issue number4
DOIs
StatePublished - Apr 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • gingiva
  • periodontal disease
  • periodontitis risk genes
  • spatial transcriptomics

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