Bioinformatics analysis and population sample validation of ferroptosis-related genes in coronary heart disease: A case-control study

Abstract

The aim of this study was to investigate the association between coronary heart disease (CHD) and ferroptosis, furthermore, to identify the relevant genes and potential diagnostic biomarkers by bioinformatics analysis. We analyzed the CHD dataset GSE23561 from the gene expression omnibus database (http://www.ncbi.nlm.nih.gov/geo) and iron-death-related genes from the FerrDb database (http://www.zhounan.org/ferrdb/). By intersecting bioinformatics-identified differentially expressed genes with iron-death-related genes in FerrDb, we identified CHD associated genes linked to ferroptosis. These genes underwent gene ontology, Kyoto encyclopedia of genes and genomes pathway enrichment, and disease ontology analyses. Using LASSO logistic regression, we selected diagnostic biomarkers for coronary artery disease from these ferroptosis-related genes. Meta-analysis validated these biomarkers, followed by population sample validation recruited from our institution. This study has shown that genes associated with ferroptosis include PRKAA2, NOX4, GLS2, and G6PD. Further data analysis and meta-analysis revealed that NOX4 gene expression was significantly upregulated in patients with CHD ( P <.05), which may be related to coronary atherosclerosis and myocardial injury. Additionally, the upregulation of NOX4 expression was validated through RT-PCR. The study identified 122 ferroptosis-associated genes, emphasizing their roles in oxidative stress, cellular membrane functions, and cardiovascular diseases. LASSO regression pinpointed 4 diagnostic biomarkers: PRKAA2, NOX4, GLS2, and G6PD, notably with elevated NOX4 expression in CHD patients. Meta-analysis and experimental validation confirmed NOX4’s significance in CHD, providing insights into its mechanisms and implications for early diagnosis and treatment strategies.

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