Ferroptosis genes and ST-segment elevation myocardial infarction outcomes: A predictive signature

Objective: The aim of this paper is to discover differentially expressed genes related to ferroptosis (DEFRGs) in patients with ST-segment elevation myocardial infarction (STEMI) and to construct a reliable prognostic signature that incorporates key DEFRGs and easily accessible clinical factors.

Methods: We did a systematic review of Gene Expression Omnibus datasets and picked datasets SE49925, GSE60993, and GSE61144 for analysis. We applied GEO2R to find DEFRGs and overlapped them among the picked datasets. We performed functional enrichment analysis to explore their biological functions. We built an optimal model with least absolute shrinkage and selection operator (LASSO) penalized Cox proportional hazards regression. We tested the clinical value of the signature with survival analysis, ROC curve, decision curve analysis and a prognostic nomogram. We also confirmed the model externally with plasma samples from our center's patients.

Results: A prognostic signature combining three overexpressed DEFRGs (ACSL1, ACSL4, TSC22D3) and two clinical variables (serum creatinine level, Gensini score) was established. The signature effectively classified patients into low- and high-risk groups. Survival analysis, ROC curve analysis, and DCA showed its robust predictive performance and clinical utility of the signature within two years after the onset of the disease. The external validation cohort confirmed the significant difference in major adverse cardiovascular events (MACEs) between the low- and high-risk groups.

Conclusion: This study revealed DEFRGs in patients with STEMI and developed a prognostic signature that integrates gene expression levels and clinical factors for stratifying patients and predicting the risk of MACEs.