Rna-seq And Machine Learning Identifies Hub Genes For Hfref

This study aimed to analyze the hub genes of heart failure with reduced ejection fraction (HFrEF) treated with Empagliflozin using RNA sequencing (RNA-seq) and bioinformatics methods, including machine learning. Nine patients with HFrEF were enrolled from a hospital’s cardiovascular department and received 10 mg of Empagliflozin once daily for two months. Differential gene expression analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, immune infiltration analysis, machine learning, immune cell correlation analysis and clinical indicator correlation analysis were performed on the transcriptome from the treatment groups. 42 differentially expressed genes were identified, and the results showed that Empagliflozin could improve the symptoms of HFrEF.