免疫系统
牙周炎
转录组
CXCR4型
基因
医学
细胞
炎症
免疫学
基因表达
计算生物学
生物
趋化因子
遗传学
内科学
作者
Xuanwen Xu,Tiange Li,Jingqi Tang,Danlei Wang,Yi Zhou,Huiqing Gou,Lu Li,Yan Xu
标识
DOI:10.1016/j.cellsig.2024.111212
摘要
Periodontitis is a common oral disease closely related to immune response and this study is aimed to identify the key immune-related pathogenic genes and analyze the infiltration and function of immune cells in the disease using bioinformatics methods. Transcriptome datasets and single-cell RNA sequencing (scRNA-seq) datasets were downloaded from the GEO database. We utilized weighted correlation network analysis and least absolute selection and shrinkage operator, protein–protein interaction network construction to screen out key pathogenic genes as well as conducted the cell-type identification by estimating relative subsets of RNA transcripts algorithm to analyze and characterize immune cell types in periodontal tissues. In addition to bioinformatics validations, clinical and cell samples were collected and mouse periodontitis models were constructed to validate the important role of key genes in periodontitis. Bioinformatics analysis pointed out the positive correlation between CXCR4 expression and periodontitis, and revealed the increased infiltration of neutrophils in periodontal inflammatory. Similar results were obtained from clinical samples and animal models. In addition, the clustering and functional enrichment results based on CXCR4 expression levels included activation of immune response and cell migration, implying the possible function of CXCR4 on regulating neutrophil dynamics, which might contribute to periodontitis. Subsequent validation experiments confirmed that the increased expression of CXCR4 in neutrophils under periodontitis, where cell migration-related pathways also were activated. CXCR4 could be the key pathogenic gene of periodontitis and CXCR4/CXCL12 signal axial might contribute to the development of periodontitis by mediating neutrophil dynamics, suggesting that CXCR4 could be a potential target to help identify novel strategies for the clinical diagnosis and treatment of periodontitis.
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