Department of Emergency, The Affiliated Huai'an Hospital of Xuzhou Medical University and The Second People's Hospital of Huai'an, Huai'an, P.R. China.
Department of Emergency, Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, P.R. China.
J Cell Biochem. 2018 Jan;119(1):650-658. doi: 10.1002/jcb.26226. Epub 2017 Aug 3.
Acute myocardial infarction (AMI) is a common disease with serious consequences in mortality and cost. Here we aim to screen the differentially expressed genes (DEGs) as biomarkers for early diagnosis of AMI. The microarray data of AMI was downloaded from Gene Expression Omnibus (GEO), including two independent types of research GSE66360 and GSE62646. The DEGs between control and processed samples were screened out by using limma package. Meanwhile, we performed functional analysis of GO terms and/or KEGG pathways to observe the enriched pathways of the DEGs. Finally, regression analysis of raw data was performed by using packet affyPLM in R language. Dataset GSE62646 contained 53 DEGs (FC log2>1 and P value <0.05) between first-day samples from 28 STEMI patients and control samples from 14 patients without myocardial infarction history. There were 12 up-regulated and 41 down-regulated genes, 35 DEGs annotated. In GSE66360, a total of 3034 DEGs between 32 AMI patients and 38 healthy persons were obtained, including 1861 up-regulated and 1173 down-regulated DEGs. The comparison of the DEGs in two datasets revealed four common up-regulated genes (EGR1, STAB1, SOCS3, TMEM176A). In enrichment analysis, STAB1, SOCS3, EGR1 involved in metabolic regulation and signaling pathways related to coronary artery disease with a characteristic change (P < 0.05). The DEGs, especially the four up-regulated common genes, could serve as biomarkers for early diagnosis of AMI. Additionally, the relative biological pathways these DEGs enriched in might provide a good reference to explore the molecular expression mechanism of AMI. J. Cell. Biochem. 119: 650-658, 2018. © 2017 Wiley Periodicals, Inc.
急性心肌梗死(AMI)是一种常见疾病,死亡率和医疗费用都很高。本研究旨在筛选差异表达基因(DEGs)作为 AMI 早期诊断的生物标志物。从基因表达综合数据库(GEO)中下载 AMI 的微阵列数据,包括两个独立的研究类型 GSE66360 和 GSE62646。使用 limma 包筛选对照和处理样本之间的 DEGs。同时,我们进行了 GO 术语和/或 KEGG 通路的功能分析,以观察 DEGs 富集的通路。最后,使用 R 语言中的包 affyPLM 对原始数据进行回归分析。数据集 GSE62646 包含 28 例 ST 段抬高型心肌梗死患者第 1 天样本和 14 例无心肌梗死史对照样本之间的 53 个 DEGs(FC log2>1 和 P 值 <0.05)。有 12 个上调基因和 41 个下调基因,有 35 个 DEGs 注释。在 GSE66360 中,在 32 例 AMI 患者和 38 例健康对照者之间共获得 3034 个 DEGs,包括 1861 个上调基因和 1173 个下调基因。两个数据集的 DEGs 比较显示四个共同上调基因(EGR1、STAB1、SOCS3、TMEM176A)。在富集分析中,STAB1、SOCS3、EGR1 参与与冠状动脉疾病相关的代谢调节和信号通路的特征性变化(P<0.05)。DEGs,尤其是四个上调的共同基因,可作为 AMI 早期诊断的生物标志物。此外,这些 DEGs 富集的相关生物通路为探索 AMI 的分子表达机制提供了良好的参考。J. Cell. Biochem. 119: 650-658, 2018. © 2017 Wiley Periodicals, Inc.