Diagnostic and treatment value of in acute myocardial infarction.

BACKGROUND

At present, acute myocardial infarction (AMI) is a serious cardiovascular disease with high morbidity and mortality. Discovering biomarkers of AMI is important for clinical diagnosis and needs. Therefore, this study aimed to elucidate the role of as a potential biomarker for AMI.

METHODS

Expression profiling data were downloaded for AMI patients and healthy patients in the GSE24548 and GSE24519 datasets, respectively. The limma package in R was conducted to determine differentially expressed microRNA (DEmiRNA)/messenger RNA (mRNA) [differentially expressed genes (DEGs)]. TargetScan and Cytoscape were used to build regulatory network of miRNA-mRNA. The Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) were applied to determine immune cell score. The gene set variation analysis (GSVA) package was used to calculate pathway score. Key drugs were determined by protein-protein interaction (PPI) and molecular docking.

RESULTS

Totals of 36 DEmiRNAs and 63 DEGs were determined in the GSE24584 dataset and GSE24519 dataset, respectively, and then we constructed a miRNA-mRNA network including 31 DEmiRNAs and 47 DEGs. The correlation analysis between immune cells and 47 DEGs identified that was most associated with AMI. Furthermore, was negatively correlated with inflammatory response score. A diagnosis model based on expression showed an area under the curve (AUC) of 93.38%, and 159 genes were highly correlated with . Molecular docking analysis showed that DB06909 had the lowest docking score with XPNPEP3, revealing it to be a potential XPNPEP3 inhibitor.

CONCLUSIONS

This work discovered that is correlated with the development of AMI. These findings may provide theoretical basis for the diagnosis and treatment of AMI.