Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.
Department of Respiratory and Critical Care Medicine, Liuzhou People's Hospital, LiuZhou, Guangxi, People's Republic of China.
Int J Chron Obstruct Pulmon Dis. 2022 Mar 3;17:439-456. doi: 10.2147/COPD.S353765. eCollection 2022.
Smoking is recognized as a risk factor for Chronic Obstructive Pulmonary Disease (COPD), yet only 20-25% of smokers eventually develop COPD. Since its molecular pathogenesis remains unclear, there is an important need to further understand genetic differences between smokers with COPD and healthy smokers, screen out high-risk and susceptible groups among smokers, and find effective therapeutic targets.
Bioinformatics tools were used to screen biomarkers that were significantly associated with COPD smokers and healthy smokers. qRT-PCR and Western blotting analysis were used to detect hub gene expression in CSE-treated BEAS-2B cells and lung tissue of COPD mouse models.
Our study identified 132 DEGs. The GO and KEGG analyses suggested that the ECM-receptor interaction, MAPK signaling pathway, Chemokine signaling pathway, PI3K-Akt signaling pathway, extracellular matrix organization and collagen fibril organization were associated with the occurrence and development of COPD. In addition, WGCNA analysis of GSE1650 showed that the brown module was most correlated with COPD. The intersection between the brown module and DEGs was used to identify 9 HUB genes (COL14A1, SULF1, MOXD1, CXCL12, CHRNA1, COMP, POU2AF1, MMP11, THBS2) that showed consistent expression and upregulation. Both the mRNA and protein expression levels of the Hub genes (except that of MMP11) were significantly upregulated in tobacco smoke exposed mouse emphysema models and CSE treated BEAS-2B cells.
Our results suggest that COL14A1, SULF1, MOXD1, CXCL12, CHRNA1, COMP, POU2AF1, and THBS2 may be potentially useful biomarkers for identifying smokers with a risk of developing COPD. The GO and KEGG functional enrichment analyses further confirmed the significant role played by ECM in the pathogenesis of COPD. The results of this study may provide further insights into the pathogenetic mechanisms involved in COPD.
吸烟被认为是慢性阻塞性肺疾病（COPD）的一个危险因素，但只有 20-25%的吸烟者最终会发展为 COPD。由于其分子发病机制尚不清楚，因此迫切需要进一步了解 COPD 吸烟者和健康吸烟者之间的遗传差异，筛选出吸烟者中的高危和易感人群，并找到有效的治疗靶点。
使用生物信息学工具筛选与 COPD 吸烟者和健康吸烟者显著相关的生物标志物。qRT-PCR 和 Western blot 分析用于检测 CSE 处理的 BEAS-2B 细胞和 COPD 小鼠模型肺组织中关键基因的表达。
本研究共鉴定出 132 个 DEGs。GO 和 KEGG 分析表明，ECM-受体相互作用、MAPK 信号通路、趋化因子信号通路、PI3K-Akt 信号通路、细胞外基质组织和胶原纤维组织与 COPD 的发生和发展有关。此外，对 GSE1650 的 WGCNA 分析表明，棕色模块与 COPD 相关性最强。棕色模块与 DEGs 的交集用于鉴定 9 个关键基因（COL14A1、SULF1、MOXD1、CXCL12、CHRNA1、COMP、POU2AF1、MMP11、THBS2），这些基因的表达一致上调。在烟草烟雾暴露的小鼠肺气肿模型和 CSE 处理的 BEAS-2B 细胞中，这些关键基因（除 MMP11 外）的 mRNA 和蛋白表达水平均显著上调。
本研究结果表明，COL14A1、SULF1、MOXD1、CXCL12、CHRNA1、COMP、POU2AF1 和 THBS2 可能是识别有发生 COPD 风险的吸烟者的潜在有用生物标志物。GO 和 KEGG 功能富集分析进一步证实了 ECM 在 COPD 发病机制中的重要作用。本研究结果可能为 COPD 的发病机制提供进一步的见解。
