Li Lin, Zeng Ziwei, Yagublu Vugar, Rahbari Nuh, Reißfelder Christoph, Keese Michael
Department of Vascular Surgery, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
European Center of Angioscience ECAS, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
J Pers Med. 2023 Jun 13;13(6):990. doi: 10.3390/jpm13060990.
Aortic dissection (AD) is a life-threatening cardiovascular disease. Pathophysiologically, it has been shown that aortic wall inflammation promotes the occurrence and development of aortic dissection. Thus, the aim of the current research was to determine the inflammation-related biomarkers in AD. In this study, we conducted differentially expressed genes (DEGs) analysis using the GSE153434 dataset containing 10 type A aortic dissection (TAAD) and 10 normal samples downloaded from the Gene Expression Omnibus (GEO) database. The intersection of DEGs and inflammation-related genes was identified as differential expressed inflammation-related genes (DEIRGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for DEIRGs. We then constructed the protein-protein interaction (PPI) network using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and identified hub genes using the Cytoscape plugin MCODE. Finally, least absolute shrinkage and selection operator (LASSO) logistic regression was used to construct a diagnostic model. A total of 1728 DEGs were identified between the TAAD and normal samples. Thereafter, 61 DEIRGs are obtained by taking the intersection of DEGs and inflammation-related genes. The GO indicated that DEIRGs were mainly enriched in response to lipopolysaccharide, in response to molecules of bacterial origin, secretory granule membrane, external side of plasma, receptor ligand activity, and signaling receptor activator activity. KEGG analysis indicated that DEIRGs were mainly enriched in cytokine-cytokine receptor interaction, TNF signaling pathway, and proteoglycans in cancer. We identified , , , , , , , , , , , , and as hub genes using the MCODE plug-in. The ROC indicated these genes had a good diagnostic performance for TAAD. In conclusion, our study identified 13 hub genes in the TAAD. This study will be of significance for the future development of a preventive therapy of TAAD.
主动脉夹层（AD）是一种危及生命的心血管疾病。在病理生理学上，已表明主动脉壁炎症促进主动脉夹层的发生和发展。因此，当前研究的目的是确定AD中与炎症相关的生物标志物。在本研究中，我们使用从基因表达综合数据库（GEO）下载的包含10例A型主动脉夹层（TAAD）和10例正常样本的GSE153434数据集进行差异表达基因（DEG）分析。将DEG与炎症相关基因的交集确定为差异表达的炎症相关基因（DEIRG）。对DEIRG进行基因本体（GO）和京都基因与基因组百科全书（KEGG）通路分析。然后，我们使用检索相互作用基因/蛋白质的搜索工具（STRING）数据库构建蛋白质-蛋白质相互作用（PPI）网络，并使用Cytoscape插件MCODE识别枢纽基因。最后，使用最小绝对收缩和选择算子（LASSO）逻辑回归构建诊断模型。在TAAD和正常样本之间共鉴定出1728个DEG。此后，通过取DEG与炎症相关基因的交集获得61个DEIRG。GO表明，DEIRG主要富集于对脂多糖的反应、对细菌来源分子的反应、分泌颗粒膜、质膜外侧、受体配体活性和信号受体激活剂活性。KEGG分析表明，DEIRG主要富集于细胞因子-细胞因子受体相互作用、TNF信号通路和癌症中的蛋白聚糖。我们使用MCODE插件将 、 、 、 、 、 、 、 、 、 、 、 和 鉴定为枢纽基因。受试者工作特征曲线（ROC）表明这些基因对TAAD具有良好的诊断性能。总之，我们的研究在TAAD中鉴定出13个枢纽基因。本研究对TAAD预防性治疗的未来发展具有重要意义。
