Identification of SLED1 as a Potential Predictive Biomarker and Therapeutic Target of Post-Infarct Heart Failure by Bioinformatics Analyses.

The aim of this study was to explore potential predictive biomarkers and therapeutic targets of post-infarct heart failure (HF) using bioinformatics analyses.CEL raw data of GSE59867 and GSE62646 were downloaded from the GEO database. Differentially expressed genes (DEGs) between patients with ST-segment elevation myocardial infarction (STEMI) and those with stable coronary artery disease (CAD) at admission and DEGs between admission and 6 months after myocardial infarction (MI) in patients with STEMI were analyzed. A gene ontology (GO) analysis and a gene set enrichment analysis (GSEA) were performed, and a protein-protein interaction network was constructed. Critical genes were further analyzed.In total, 147 DEGs were screened between STEMI and CAD at admission, and 62 DEGs were identified in patients with STEMI between admission and 6 months after MI. The results of GO and GSEA indicate that neutrophils, neutrophil-related immunity responses, and monocytes/macrophages play important roles in MI pathogenesis. SLED1 expression was higher in patients with HF than in those without HF at admission and 1 month after MI. GSEA indicates that mTORC1 activation, E2F targets, G2M checkpoint, and MYC targets v1 inhibition may play key roles in the development of post-infarct HF. Furthermore, SLED1 may be involved in the development of post-infarct HF by activating mTORC1 and inhibiting E2F targets, G2M checkpoint, and MYC targets v1.SLED1 may be a novel biomarker of post-infarct HF and may serve as a potential therapeutic target in this disease.