Department of Orthopeadics, The 2nd Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Harbin 150081, China.
Department of Human Movement and Sport Science, Harbin Sport University, 1 Dacheng Street, Nangang District, Harbin 150008, China.
Dis Markers. 2021 Dec 29;2021:5074305. doi: 10.1155/2021/5074305. eCollection 2021.
The current study is aimed at identifying the cross-talk genes between periodontitis (PD) and rheumatoid arthritis (RA), as well as the potential relationship between cross-talk genes and pyroptosis-related genes.
Datasets for the PD (GSE106090, GSE10334, GSE16134) and RA (GSE55235, GSE55457, GSE77298, and GSE1919) were downloaded from the GEO database. After batch correction and normalization of datasets, differential expression analysis was performed to identify the differentially expressed genes (DEGs). The cross-talk genes linking PD and RA were obtained by overlapping the DEGs dysregulated in PD and DEGs dysregulated in RA. Genes involved in pyroptosis were summarized by reviewing literatures, and the correlation between pyroptosis genes and cross-talk genes was investigated by Pearson correlation coefficient. Furthermore, the weighted gene coexpression network analysis (WGCNA) was carried out to identify the significant modules which contained both cross-talk genes and pyroptosis genes in both PD data and RA data. Thus, the core cross-talk genes were identified from the significant modules. Receiver-operating characteristic (ROC) curve analysis was performed to identify the predictive accuracy of these core cross-talk genes in diagnosing PD and RA. Based on the core cross-talk genes, the experimentally validated protein-protein interaction (PPI) and gene-pathway network were constructed.
A total of 40 cross-talk genes were obtained. Most of the pyroptosis genes were not differentially expressed in disease and normal samples. By selecting the modules containing both cross-talk genes or pyroptosis genes, the blue module was identified to be significant module. Three genes, i.e., cross-talk genes (TIMP1, LGALS1) and pyroptosis gene-GPX4, existed in the blue module of PD network, while two genes (i.e., cross-talk gene-VOPP1 and pyroptosis gene-AIM2) existed in the blue module of RA network. ROC curve analysis showed that three genes (TIMP1, VOPP1, and AIM2) had better predictive accuracy in diagnosing disease compared with the other two genes (LGALS1 and GPX4).
This study revealed shared mechanisms between RA and PD based on cross-talk and pyroptosis genes, supporting the relationship between the two diseases. Thereby, five modular genes (TIMP1, LGALS1, GPX4, VOPP1, and AIM2) could be of relevance and might serve as potential biomarkers. These findings are a basis for future research in the field.
本研究旨在鉴定牙周炎（PD）和类风湿关节炎（RA）之间的串扰基因，以及串扰基因与细胞焦亡相关基因之间的潜在关系。
从 GEO 数据库中下载 PD（GSE106090、GSE10334、GSE16134）和 RA（GSE55235、GSE55457、GSE77298 和 GSE1919）数据集。对数据集进行批次校正和归一化后，通过比较 PD 中失调的差异表达基因（DEGs）和 RA 中失调的 DEGs，识别差异表达基因（DEGs）。通过回顾文献总结与细胞焦亡相关的基因，并通过皮尔逊相关系数研究细胞焦亡基因与串扰基因之间的相关性。此外，还进行了加权基因共表达网络分析（WGCNA），以鉴定 PD 数据和 RA 数据中同时包含串扰基因和细胞焦亡基因的显著模块。从而从显著模块中确定核心串扰基因。采用接收者操作特征（ROC）曲线分析来评估这些核心串扰基因在诊断 PD 和 RA 中的预测准确性。基于核心串扰基因，构建了经过实验验证的蛋白质-蛋白质相互作用（PPI）和基因通路网络。
共获得 40 个串扰基因。大多数细胞焦亡基因在疾病和正常样本中均无差异表达。通过选择包含串扰基因或细胞焦亡基因的模块，鉴定到蓝色模块为显著模块。在 PD 网络的蓝色模块中存在三个基因，即串扰基因（TIMP1、LGALS1）和细胞焦亡基因-GPX4，而在 RA 网络的蓝色模块中存在两个基因，即串扰基因-VOPP1 和细胞焦亡基因-AIM2。ROC 曲线分析表明，与其他两个基因（LGALS1 和 GPX4）相比，三个基因（TIMP1、VOPP1 和 AIM2）在诊断疾病方面具有更好的预测准确性。
本研究基于串扰和细胞焦亡基因揭示了 RA 和 PD 之间的共同机制，支持了这两种疾病之间的关系。因此，五个模块基因（TIMP1、LGALS1、GPX4、VOPP1 和 AIM2）可能具有相关性，并可能作为潜在的生物标志物。这些发现为该领域的进一步研究奠定了基础。
