Guan Yao-Zong, Wang Huai, Huang Huan-Jie, Liang Dong-Yan, Liang Xiu-Yuan, Lu De-Sheng, Liu Hao
Department of Cardiology, The Second Affiliated Hospital, Guangxi Medical University, No.166, Daxue Dong Road, Nanning, 530007, Guangxi, People's Republic of China.
Eur J Med Res. 2025 Aug 26;30(1):805. doi: 10.1186/s40001-025-03092-3.
Atrial fibrillation (AF) is a common atrial arrhythmia in clinic, regulated by the immune system and associated with ferroptosis. We hypothesized that combining the analysis of ferroptosis and immune infiltration in AF will help identify more precise diagnostic biomarkers.
We analyzed two gene expression omnibus (GEO) data sets (GSE41177 and GSE122188) and extracted characteristic ferroptosis-related genes related to sinus rhythm and AF via bioinformatic analysis. CIBERSORT was used to identify ferroptosis/immune-related genes (FIRGs) in AF. LASSO model analysis was used to identify novel FIRGs. The GSE79768 data set and qRT-PCR were used to validate the FIRGs. ROC curves were then drawn to evaluate the diagnostic power of the FIRGs, and GSEA was used to detect the pathways enriched with the validated FIRGs.
A total of eight FIRGs were identified between the healthy and AF groups through LASSO model analysis. Four FIRGs (ALOX15, SNX5, CA9, and PROK2) were subsequently validated as novel FIRGs with high diagnostic power for AF (AUC = 0.851-0.911). They were enriched mainly in cytokine-cytokine receptor interactions, ascorbate and aldarate metabolism, the nod-like receptor signaling pathway, and the intestinal immune network for IgA production. In addition, ceRNA networks (mRNA-miRNA-lncRNA) such as SNX5-hsa-miR-185-3p-LINC01165 and PROK2-hsa-miR-125b-2-3p-RP11-333E1.2 were constructed. Candidate drugs, such as linoleic acid, which is targeted by ALOX15, and sulfamide, targeted by CA9, were also identified.
Our findings reveal the significant ferroptosis/immune-related genes and the potential pathways and biofunctions enriched with these genes in AF and provide new insights for the diagnosis and interference of AF.
心房颤动(AF)是临床上常见的房性心律失常,受免疫系统调节并与铁死亡相关。我们假设,综合分析AF中的铁死亡和免疫浸润将有助于识别更精确的诊断生物标志物。
我们分析了两个基因表达综合数据库(GEO)数据集(GSE41177和GSE122188),并通过生物信息学分析提取了与窦性心律和AF相关的特征性铁死亡相关基因。使用CIBERSORT识别AF中的铁死亡/免疫相关基因(FIRGs)。采用LASSO模型分析来识别新的FIRGs。使用GSE79768数据集和qRT-PCR验证FIRGs。然后绘制ROC曲线以评估FIRGs的诊断能力,并使用GSEA检测经验证的FIRGs所富集的通路。
通过LASSO模型分析,在健康组和AF组之间共鉴定出8个FIRGs。随后,4个FIRGs(ALOX15、SNX5、CA9和PROK2)被验证为对AF具有高诊断能力的新FIRGs(AUC = 0.851 - 0.911)。它们主要富集于细胞因子 - 细胞因子受体相互作用、抗坏血酸和醛糖代谢、NOD样受体信号通路以及IgA产生的肠道免疫网络。此外,还构建了如SNX5 - hsa-miR-185-3p-LINC01165和PROK2 - hsa-miR-125b-2-3p-RP11-333E1.2等ceRNA网络(mRNA - miRNA - lncRNA)。还鉴定了候选药物,如ALOX15靶向的亚油酸和CA9靶向的磺胺。
我们的研究结果揭示了AF中显著的铁死亡/免疫相关基因以及这些基因所富集的潜在通路和生物学功能,为AF的诊断和干预提供了新的见解。