Investigation of key ferroptosis-associated genes and potential therapeutic drugs for asthma based on machine learning and regression models

作者：Yuhang Chen, Jie Wang, Ye Zhang, Ziwei Zhang, Hong Chen, Jiaojiao Hu, Ke Zhu, Liqun Wu, Fangwei Xu · 发表于：Scientific Reports · 年份：2025 · DOI：10.1038/s41598-025-06122-6 · 被引用次数：5 · 研究领域：Ferroptosis and cancer prognosis、Cancer-related molecular mechanisms research、RNA modifications and cancer

Bronchial asthma is a complex and heterogeneous disease, with ferroptosis, a form of non-apoptotic cell death, contributing to its pathogenesis by inducing airway epithelial damage, inflammatory infiltration, and airway remodeling. Investigating ferroptosis-related characteristic genes and potential therapeutic compounds may enhance asthma management. This study employed differential analysis and machine learning to identify ferroptosis-related characteristic genes in asthma using the GSE179156 dataset and FerrDb V2 database. Immune infiltration analysis explored the associations between these genes and immune cells, while potential small-molecule drugs were screened through the Connectivity Map (CMap) database and evaluated via molecular docking and molecular dynamics simulations. Two ferroptosis-related characteristic genes, AGPS and APELA, were identified, with AGPS upregulated and APELA downregulated in asthma, both significantly correlated with various immune cells. A diagnostic model based on these genes demonstrated high predictive accuracy. Additionally, KU-55933 was identified as a potential small-molecule inhibitor of AGPS, with stable binding confirmed through computational simulations. These findings emphasize the role of ferroptosis-related genes in asthma and propose promising therapeutic candidates, providing novel insights into its diagnosis and treatment.