Identifying potential biomarkers in acute myocardial infarction based on neutrophil extracellular traps associated genes

Abstract

Abstract Background Acute myocardial infarction (AMI) represents one of the major critical cardiovascular disorders due to its high mortality and morbidity. Neutrophil extracellular traps(NETs) are essential throughout the thrombotic process of AMI. However, genes associated with NETs in AMI have not been fully described.Methods NETs-associated gene candidates were identified by literature review. AMI-associated datasets(GSE66360) were retrieved from Gene Expression Omnibus (GEO) database. Differentially expressed NETs-associated genes were subjected to Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis. The marker genes were subsequently selected by the least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms and calculated based on the receiver operating characteristic (ROC) curve. To further probe the potential features of these marker genes, single-gene gene set enrichment analysis (GSEA) was performed. To further discuss immune microenvironment modulations, immune infiltration analysis was performed by CIBERSORT algorithms. Accordingly, an mRNA-miRNA-lncRNA network was constructed. Finally, gene expression levels of these marker gene were verified according to an external dataset (GSE66145).Results Forty-five differentially expressed NETs-associated genes were screened out from the GSE66360 dataset, which was closely linked to myeloid leukocyte activation and inflammatory response. FCAR, LILRB2, PDE4B, S100A12, DNASE1, IL1B, IL6, MMP9, and TLR2 were identified as marker genes. The AUC of marker genes was higher than 0.6 and the AUC of the marker genes-based logistic regression model was 0.981. Functional enrichment analysis results suggested that these marker genes might exert consequential effects in AMI through regulating immune responses. CIBERSORT analysis further revealed that the immune microenvironment alterations may be associated with TLR2, S100A12, LILRB2, IL1B, and FCAR. In addition, the ceRNA network demonstrated a complex regulatory interaction.Conclusion Here we identified and validated 9 NETs-associated genes (FCAR, LILRB2, PDE4B, S100A12, DNASE1, IL1B, IL6, MMP9, and TLR2) as novel biomarkers in AMI pathogenesis. These genes may be involved in the onset and development of AMI through NETs formation. Collectively, our findings have provided potential targets for the diagnosis and treatment of AMI.