Objective. Peri-implantitis (PI) is one of the main reasons for dental implant failure. Until now, the etiology and pathogenesis of PI remain unclear. Methods. In this study, we used differentially expressed genes (DEGs) analysis and gene function enrichment analysis to assess the expression profile of peri-implant bone tissue and gingiva in PI public data from the Gene Expression Omnibus (GEO) database. Then, we used gingival tissues from patients with PI and healthy individual to construct gene coexpression networks to reveal the biological functions of the genes in PI using RNA sequencing data. Afterward, key gene modules were selected to reveal the critical biological process or signaling pathway using Hallmark’s gene enrichment and expression analysis of the related pathway members in PI. Results. DEGs were enriched in the formation of cellular responses to external stimuli in bone tissue. Cytokine production, lymphocyte activation, immune response-regulating signaling pathway, and blood vessel development were the top GO biology process or pathways of the DEGs in gingival tissue. Weighted gene coexpression network analysis (WGCNA) of RNA-seq data was used to assess the results of correlation analysis between modules and traits and correlation analysis between modules and functions. kMEpurple, kMEgreen, and kMEred modules were selected as the key gene modules. Signaling pathways and gene expression analysis were performed on selected modules, such as IL2/STAT5 signaling pathway, TNFα signaling pathway via NFκB, and angiogenesis were enriched in kMEpurple module. Hedgehog signaling pathway, Wnt β-catenin signaling pathway, and IL2/STAT5 signaling pathway were enriched in kMEgreen module. Peroxisome, IL2/STAT5 signaling pathway, and epithelial-mesenchymal transformation process were enriched in kMEred module. All the enrichment results of key modules contained IL2/STAT5 signaling pathway. Conclusion. Differential gene and enrichment analysis based on public data showed differences in gene expression patterns and biological process between bone and gingival tissues in PI. This spatial-temporal heterogeneity is reflected in the formation of cellular responses to external stimuli, which was enriched in bone tissue, but cytokine production, lymphocyte activation, immune response regulating signaling pathway, and blood vessel development were enriched in gingival tissue. WGCNA and Hallmark gene sets enrichment analysis of the gingival tissue expression profile and showed that IL2-mediated activation of immune cells could be a critical mechanism in PI. As a new clinical treatment alternative, we suggest that IL2/STAT5 pathway blockers could be helpful in the treatment of PI.

中文翻译：

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加权基因共表达网络分析确定 IL2/STAT5 信号通路是种植体周围炎的重要决定因素

客观。种植体周围炎（PI）是种植牙失败的主要原因之一。迄今为止，PI的病因和发病机制仍不清楚。方法。在这项研究中，我们使用差异表达基因 (DEGs) 分析和基因功能富集分析来评估来自基因表达综合 (GEO) 数据库的 PI 公共数据中种植体周围骨组织和牙龈的表达谱。然后，我们使用来自 PI 患者和健康个体的牙龈组织构建基因共表达网络，以利用 RNA 测序数据揭示 PI 中基因的生物学功能。之后，利用 Hallmark 对 PI 中相关通路成员的基因富集和表达分析，选择关键基因模块来揭示关键的生物过程或信号通路。结果。DEG 富集于骨组织中对外部刺激的细胞反应的形成。细胞因子产生、淋巴细胞活化、免疫反应调节信号通路和血管发育是牙龈组织中 DEGs 的顶级 GO 生物学过程或通路。RNA-seq数据的加权基因共表达网络分析（WGCNA）用于评估模块与性状之间的相关性分析以及模块与功能之间的相关性分析的结果。kMEpurple、kMEgreen 和 kMEred 模块被选为关键基因模块。对选定的模块进行信号通路和基因表达分析，例如通过 NF κ的 IL2/STAT5 信号通路、TNF α信号通路B，血管生成富集在 kMEpurple 模块中。Hedgehog信号通路、Wntβ -catenin信号通路和IL2/STAT5信号通路在kMEgreen模块中富集。过氧化物酶体、IL2/STAT5 信号通路和上皮间质转化过程在 kMEred 模块中富集。关键模块的所有富集结果均包含IL2/STAT5信号通路。结论. 基于公开数据的差异基因和富集分析表明，PI中骨和牙龈组织之间的基因表达模式和生物学过程存在差异。这种时空异质性反映在细胞对外部刺激的反应形成中，其在骨组织中富集，而细胞因子的产生、淋巴细胞活化、免疫反应调节信号通路和血管发育则在牙龈组织中富集。WGCNA 和 Hallmark 基因组对牙龈组织表达谱的富集分析表明，IL2 介导的免疫细胞激活可能是 PI 的关键机制。作为一种新的临床治疗替代方案，我们建议 IL2/STAT5 通路阻滞剂可能有助于治疗 PI。