期刊
FRONTIERS IN CARDIOVASCULAR MEDICINE
卷 9, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fcvm.2022.863248
关键词
acute myocardial infarction; genomics; immune landscape; second-generation sequencing (SGS); diagnosis; bioinformatics
资金
- National Natural Science Foundation of China [82060074]
- Yunnan Provincial Department of Science and Technology-Kunming Medical University joint special project on applied basic research [2019FE001 (-113)]
- Yunnan Health Training Project of highlevel talents [D-2018045]
- Applied Basic Research of Clinical Medical Center of Cardiovascular and Cerebrovascular Diseases of Yunnan province [ZX2019-03-01]
This study utilizes genomic advances to identify and analyze genes associated with acute myocardial infarction (AMI). Differential and functional enrichment analyses were performed on microarray data, and immune landscape analysis was conducted on whole blood samples. Key genes related to AMI were identified through weighted gene co-expression network analysis, and diagnostic indicators were obtained. The study provides new insights and diagnostic indicators for AMI.
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. MethodsBased 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 patients with AMI and performed second-generation sequencing (SGS) analysis. Weighted gene co-expression network analysis (WGCNA) and cross-tabulation analysis identified AMI-related key genes. Receiver operating characteristic (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. ResultsA total of 53 AMI-related DEGs from a public database were obtained and found to be involved 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, and 754 DEGs were obtained from own SGS 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 cell cycle, immune response, cardiac developmental, and functional regulatory processes. ConclusionThe present study provides new diagnostic indicators for AMI and further confirms the feasibility of the results of genome-wide gene expression analysis.
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