The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Department of Cardiology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Health Management Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
J Int Med Res. 2020 Dec;48(12):300060520979856. doi: 10.1177/0300060520979856.
Coronary artery disease (CAD) is the leading cause of mortality worldwide. We aimed to screen out potential gene signatures and construct a diagnostic model for CAD.
We downloaded two mRNA profiles, GSE66360 and GSE60993, and performed analyses of differential expression, gene ontology terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The STRING database was used to identify protein-protein interactions (PPI). PPI network visualization and screening out of key genes were performed using Cytoscape software. Finally, a diagnostic model was constructed.
A total of 2127 differentially expressed genes (DEGs) were identified in GSE66360, and 527 DEGs in GSE60993. Of the 153 DEGs from both datasets that showed differential expression between CAD patients and controls, 471 biological process terms, 35 cellular component terms, 17 molecular function terms, and 49 KEGG pathways were significantly enriched. The top 20 key genes in the PPI network were identified, and a diagnostic model constructed from five optimal genes that could efficiently separate CAD patients from controls.
We identified several potential biomarkers for CAD and built a logistic regression model that will provide a valuable reference for future clinical diagnoses and guide therapeutic strategies.
冠心病（CAD）是全球范围内导致死亡的主要原因。我们旨在筛选出潜在的基因特征，并构建 CAD 的诊断模型。
我们下载了两个 mRNA 图谱 GSE66360 和 GSE60993，并进行了差异表达、基因本体论术语和京都基因与基因组百科全书（KEGG）通路的分析。STRING 数据库用于识别蛋白质-蛋白质相互作用（PPI）。使用 Cytoscape 软件进行 PPI 网络可视化和关键基因筛选。最后，构建了诊断模型。
在 GSE66360 中鉴定出 2127 个差异表达基因（DEGs），在 GSE60993 中鉴定出 527 个 DEGs。在两个数据集之间显示 CAD 患者和对照组之间差异表达的 153 个 DEG 中，有 471 个生物过程术语、35 个细胞成分术语、17 个分子功能术语和 49 个 KEGG 通路显著富集。确定了 PPI 网络中的前 20 个关键基因，并构建了一个从五个最佳基因中构建的诊断模型，该模型可以有效地将 CAD 患者与对照组区分开来。
我们鉴定出了一些 CAD 的潜在生物标志物，并构建了一个逻辑回归模型，该模型将为未来的临床诊断提供有价值的参考，并指导治疗策略。
