Identification of ferroptosis biomarkers and immune infiltration landscapes in atrial fibrillation: A bioinformatics analysis.

ABSTRACT: Ferroptosis has been recognized as a critical factor in the development of atrial fibrillation (AF), but its precise mechanisms remain unclear. We downloaded the GSE115574 dataset from the gene expression omnibus database to analyze the expression levels of ferroptosis-related genes (FRGs) and identify differentially expressed genes (DEGs). Least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) machine learning techniques were employed to identify key genes associated with AF. The diagnostic performance of these genes was evaluated using Receiver operating characteristic curves (ROC) and validated in an independent AF dataset. miRNA and lncRNA predictions for potential binding to these key genes were conducted using miRBas

SUBMITTER: Peng S 

PROVIDER: S-EPMC11441859 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature