基于蛋白质组学和转录组学综合分析的急性心肌梗死分子特征鉴定

Identification of molecular signatures in acute myocardial infarction based on integrative analysis of proteomics and transcriptomics.

作者信息

Wu Jiawen, Yan Jiale, Hua Zheng, Jia Jingyi, Zhou Zhitong, Zhang Junfang, Li Jue, Zhang Jie

机构信息

Department of Gynecology, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China; Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China.

Department of Gynecology, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China.

出版信息

Genomics. 2023 Sep;115(5):110701. doi: 10.1016/j.ygeno.2023.110701. Epub 2023 Aug 18.

DOI:10.1016/j.ygeno.2023.110701

PMID:37597790

Abstract

BACKGROUND

Myocardial infarction (MI) is one of the most serious cardiovascular diseases, characterized by a rapid and irreversible decline in myocardial function. Early detection of patients with MI and prolonging the optimal therapeutic window of acute myocardial infarction (AMI) are particularly important. This study aimed to identify the diagnostic biomarkers and novel therapeutic targets for acute myocardial infarction.

METHOD

We generated the AMI mouse models by ligating the proximal left anterior descending coronary artery. Six time points-Sham, AMI 10-min, 1-h, 6-h, 24-h, and 72-h-were chosen to examine the molecular changes that occur during the AMI process. RNA-seq and DIA-MS were performed on the infarcted left ventricular tissues of AMI mice at each time point. Co-expression pattern genes were screened from myocardial infarction samples at different time points by time-series analysis. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to examine these genes. Using the Interactive Gene/Protein Retrieval Tool (STRING) database, the protein-protein interaction network (PPI) was constructed and the hub genes were identified. In order to evaluate the diagnostic value of hub genes, a receiver operating characteristic (ROC) curve was constructed. An independent data set, GSE163772, confirmed the diagnostic value of hub genes further.

RESULT

We obtained the expression profiles at different time points after the occurrence of heart failure through high-throughput sequencing, and found 167 genes with similar expression patterns through time series analysis. The immune response and immune-related pathways had the greatest enrichment of these genes. Among them, Itgb2 Syk, Tlr4, Tlr2, Itgax, and Lcp2 may play key roles as hub genes. Combined with the results of proteomic analysis, it was found that the expression of Coro1a in both omics increased with time. The results of external validation showed that TLR2, ITGAX, and LCP2 had good predictive ability for AMI diagnosis.

CONCLUSION

Itgb2, Syk, Tlr4, Tlr2, Itgax, Lcp2 and Coro1a are considered to be the seven key genes significantly associated with AMI. Our results may provide potential targets for the prevention of adverse ventricular remodeling and the treatment of AMI.

摘要

背景

心肌梗死（MI）是最严重的心血管疾病之一，其特征是心肌功能迅速且不可逆地下降。早期检测MI患者并延长急性心肌梗死（AMI）的最佳治疗窗口尤为重要。本研究旨在确定急性心肌梗死的诊断生物标志物和新的治疗靶点。

方法

我们通过结扎左冠状动脉前降支近端建立AMI小鼠模型。选择六个时间点——假手术组、AMI 10分钟、1小时、6小时、24小时和72小时——来检查AMI过程中发生的分子变化。对每个时间点的AMI小鼠梗死左心室组织进行RNA测序和数据独立分析（DIA-MS）。通过时间序列分析从不同时间点的心肌梗死样本中筛选共表达模式基因。使用基因本体（GO）功能和京都基因与基因组百科全书（KEGG）通路分析来研究这些基因。利用交互式基因/蛋白质检索工具（STRING）数据库构建蛋白质-蛋白质相互作用网络（PPI）并鉴定枢纽基因。为了评估枢纽基因的诊断价值，构建了受试者工作特征（ROC）曲线。一个独立数据集GSE163772进一步证实了枢纽基因的诊断价值。

结果

我们通过高通量测序获得了心力衰竭发生后不同时间点的表达谱，并通过时间序列分析发现了167个具有相似表达模式的基因。免疫反应和免疫相关通路在这些基因中富集程度最高。其中，整合素β2（Itgb2）、脾酪氨酸激酶（Syk）、Toll样受体4（Tlr4）、Toll样受体2（Tlr2）、整合素αX（Itgax）和淋巴细胞胞质蛋白2（Lcp2）可能作为枢纽基因发挥关键作用。结合蛋白质组学分析结果，发现这两个组学中冠蛋白1A（Coro1a）的表达均随时间增加。外部验证结果表明，Toll样受体2（TLR2）、整合素αX（ITGAX）和淋巴细胞胞质蛋白2（LCP2）对AMI诊断具有良好的预测能力。