Liu Hui, Xiang Chunhua, Wang Zhaohui, Song Yi
Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Int J Gen Med. 2022 Mar 14;15:2979-2990. doi: 10.2147/IJGM.S346482. eCollection 2022.
Ferroptosis is a specific subtype of programmed cell death, which plays an essential role in the immune-associated disease, atherosclerosis (AS). The purpose of this study was to identify potential ferroptosis-related gene biomarkers and its association with immune infiltration characteristics in atherosclerosis with bioinformatics methods.
Differentially expressed genes (DEGs) between AS and control groups were screened from GSE40231, analyzed for functional enrichment and then intersected with ferroptosis-related genes. Then, a random forest model was constructed based on these differentially expressed ferroptosis-related genes (DE-FRGs) and validated with dataset GSE132651. The performance of the models was evaluated with the area under receiver operating characteristic curves (AUC). Finally, we analyzed the correlation between DE-FRGs above and the characteristics of immune infiltration via CIBERSORT method.
Six DE-FRGs (IL6, ANGPTL7, CDKN1A, AKR1C3, NOX4 and VLDLR) were detected based on dataset of GSE40231. Furthermore, a random forest model was constructed based on them with a compelling diagnostic performance of AUC = 0.8974 in the validation dataset GSE132651. In addition, the proportion of follicular helper T (Tfh) cells was significantly higher in AS group (P < 0.001). And we found significant correlation relationship between Tfh and expression level of ANGPTL7 (R = 0.35, P < 0.01), CDKN1A (R = 0.4, P < 0.0001), AKR1C3 (R = 0.64, P < 0.0001), NOX4 (R = 0.32, P < 0.01) and VLDLR (R = -0.43, P < 0.0001).
This study identified 6 DE-FRGs and validated a predicted model for the early prediction of AS, which also proved the close relationship between ferroptosis and immunity in the pathogenesis of AS.
铁死亡是程序性细胞死亡的一种特殊亚型，在免疫相关疾病动脉粥样硬化（AS）中起重要作用。本研究旨在通过生物信息学方法鉴定潜在的铁死亡相关基因生物标志物及其与动脉粥样硬化免疫浸润特征的关联。
从GSE40231中筛选AS组和对照组之间的差异表达基因（DEG），进行功能富集分析，然后与铁死亡相关基因进行交集分析。然后，基于这些差异表达的铁死亡相关基因（DE-FRG）构建随机森林模型，并用数据集GSE132651进行验证。通过受试者操作特征曲线（AUC）下的面积评估模型的性能。最后，我们通过CIBERSORT方法分析上述DE-FRG与免疫浸润特征之间的相关性。
基于GSE40231数据集检测到6个DE-FRG（IL6、ANGPTL7、CDKN1A、AKR1C3、NOX4和VLDLR）。此外，基于它们构建了一个随机森林模型，在验证数据集GSE132651中具有令人信服的诊断性能，AUC = 0.8974。此外，AS组中滤泡辅助性T（Tfh）细胞的比例显著更高（P < 0.001）。并且我们发现Tfh与ANGPTL7（R = 0.35，P < 0.01）、CDKN1A（R = 0.4，P < 0.0001）、AKR1C3（R = 0.64，P < 0.0001）、NOX4（R = 0.32，P < 0.01）和VLDLR（R = -0.43，P < 0.0001）的表达水平之间存在显著的相关性。
本研究鉴定了6个DE-FRG，并验证了一个用于AS早期预测的预测模型，这也证明了铁死亡与AS发病机制中的免疫之间的密切关系。
