Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction - Tan, Xiaobing; Dai, Qingli; Sun, Huang; Jiang, Wenqing; Lu, Si; Wang, Ruxian; Lv, Meirong; Sun, Xianfeng; Lv, Naying; Dai, Qingyuan (Frontiers in Cardiovascular Medicine, 2022)
Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases worldwide. Advances in genomics have provided new ideas for the development of novel molecular biomarkers of potential clinical value for AMI. Methods: Based on microarray data from a public database, differential analysis and functional enrichment analysis were performed to identify aberrantly expressed genes in AMI and their potential functions. CIBERSORT was used for immune landscape analysis. We also obtained whole blood samples of 3 AMI patients and performed second-generation sequencing analysis. WGCNA and cross-tabulation analysis identified AMI-related key genes. ROC curves were used to assess the diagnostic power of key genes. Single-gene gene set enrichment analysis (GSEA) revealed the molecular mechanisms of diagnostic indicators. Results: A total of 53 AMI-related DEGs from a public database were obtained and found involving in immune cell activation, immune response regulation and cardiac developmental processes. CIBERSORT confirmed that the immune microenvironment was altered between AMI and normal samples. A total of 77 hub genes were identified by WGCNA; 754 DEGs were obtained from own second-generation sequencing data. Seven diagnostic indicators of AMI were obtained, namely GZMA, NKG7, TBX21, TGFBR3, SMAD7, KLRC4, and KLRD1. The single-gene GSEA suggested that the diagnostic indicators seemed to be closely implicated in the cell cycle, immune response, and cardiac developmental and functional regulatory processes. Conclusion: The present study provides new diagnostic indicators for AMI and further confirms the feasibility of the results of genome-wide gene expression analysis.