Song Liang, Yao Jueqi, He Zhijing, Xu Bin
Department of Stomatology, The Fifth People's Hospital of Shanghai, Fudan University, No.128, Ruili Rd, Minhang District, Shanghai, 200240, China.
Department of Endodontics, Shanghai Oral Disease Prevention and Cure Center, Shanghai, 200031, China.
BMC Oral Health. 2015 Sep 4;15:105. doi: 10.1186/s12903-015-0086-7.
Despite of numerous studies on periodontitis, the mechanism underlying the progression of periodontitis still remains largely unknown. This study aimed to have an expression profiling comparison between periodontitis and normal control and to identify more candidate genes involved in periodontitis and to gain more insights into the molecular mechanisms of periodontitis progression.
The gene expression profile of GSE16134, comprising 241 gingival tissue specimens and 69 healthy samples as control which were obtained from 120 systemically healthy patients with periodontitis (65 with chronic and 55 with aggressive periodontitis), was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in periodontitis samples were screened using the limma package in R compared with control samples. Gene Ontology (GO) and pathway enrichment analysis upon the DEGs were carried out using Hypergeometric Distribution test. Protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape, followed by module selection from the PPI network using MCODE plugin. Moreover, transcription factors (TFs) of these DEGs were identified based on TRANSFAC database and then a regulatory network was constructed.
Totally, 762 DEGs (507 up- and 255 down-regulated) in periodontitis samples were identified. DEGs were enriched in different GO terms and pathways, such as immune system process, cell activation biological processes, cytokine-cytokine receptor interaction, and metabolic pathways. Cathepsin S (CTSS) and pleckstrin (PLEK) were the hub proteins in the PPI network and 3 significant modules were selected. Moreover, 19 TFs were identified including interferon regulatory factor 8 (IRF8), and FBJ murine osteosarcoma viral oncogene homolog B (FOSB).
This study identified genes (CTSS, PLEK, IRF-8, PTGS2, and FOSB) that may be involved in the development and progression of periodontitis.
尽管对牙周炎进行了大量研究，但牙周炎进展的潜在机制仍 largely 未知。本研究旨在对牙周炎和正常对照进行表达谱比较，以鉴定更多参与牙周炎的候选基因，并更深入地了解牙周炎进展的分子机制。
从基因表达综合数据库（GEO）下载了 GSE16134 的基因表达谱，其中包括 241 份牙龈组织标本和 69 份作为对照的健康样本，这些样本来自 120 例全身健康的牙周炎患者（65 例慢性牙周炎和 55 例侵袭性牙周炎）。与对照样本相比，使用 R 语言中的 limma 包筛选牙周炎样本中的差异表达基因（DEGs）。使用超几何分布检验对 DEGs 进行基因本体论（GO）和通路富集分析。使用 Cytoscape 构建 DEGs 的蛋白质-蛋白质相互作用（PPI）网络，随后使用 MCODE 插件从 PPI 网络中选择模块。此外，基于 TRANSFAC 数据库鉴定这些 DEGs 的转录因子（TFs），然后构建调控网络。
共鉴定出牙周炎样本中的 762 个 DEGs（507 个上调和 255 个下调）。DEGs 富集于不同的 GO 术语和通路，如免疫系统过程、细胞激活生物学过程、细胞因子-细胞因子受体相互作用和代谢通路。组织蛋白酶 S（CTSS）和普列克底物蛋白（PLEK）是 PPI 网络中的枢纽蛋白，并选择了 3 个显著模块。此外，鉴定出 19 个 TFs，包括干扰素调节因子 8（IRF8）和 FBJ 小鼠骨肉瘤病毒癌基因同源物 B（FOSB）。
本研究鉴定出可能参与牙周炎发生和进展的基因（CTSS、PLEK、IRF-8、PTGS2 和 FOSB）。
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