Zhao Huabin, Wang Jiawei, Li Zhongzheng, Wang Shenghui, Yu Guoying, Wang Lan
State Key Laboratory of Cell Differentiation and Regulation, Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, College of Life Sciences, Institute of Biomedical Science, Henan Normal University, Xinxiang, Henan, China.
Front Mol Neurosci. 2023 Oct 30;16:1280639. doi: 10.3389/fnmol.2023.1280639. eCollection 2023.
Ferroptosis is a newly defined form of programmed cell death and plays an important role in Alzheimer's disease (AD) pathology. This study aimed to integrate bioinformatics techniques to explore biomarkers to support the correlation between ferroptosis and AD. In addition, further investigation of ferroptosis-related biomarkers was conducted on the transcriptome characteristics in the asymptomatic AD (AsymAD).
The microarray datasets GSE118553, GSE132903, GSE33000, and GSE157239 on AD were downloaded from the GEO database. The list of ferroptosis-related genes was extracted from the FerrDb website. Differentially expressed genes (DEGs) were identified by R "limma" package and used to screen ferroptosis-related hub genes. The random forest algorithm was used to construct the diagnostic model through hub genes. The immune cell infiltration was also analyzed by CIBERSORTx. The miRNet and DGIdb database were used to identify microRNAs (miRNAs) and drugs which targeting hub genes.
We identified 18 ferroptosis-related hub genes anomalously expressed in AD, and consistent expression trends had been observed in both AsymAD The random forest diagnosis model had good prediction results in both training set (AUC = 0.824) and validation set (AUC = 0.734). Immune cell infiltration was analyzed and the results showed that CD4+ T cells resting memory, macrophages M2 and neutrophils were significantly higher in AD. A significant correlation of hub genes with immune infiltration was observed, such as DDIT4 showed strong positive correlation with CD4+ T cells memory resting and AKR1C2 had positive correlation with Macrophages M2. Additionally, the microRNAs (miRNAs) and drugs which targeting hub genes were screened.
These results suggest that ferroptosis-related hub genes we screened played a part in the pathological progression of AD. We explored the potential of these genes as diagnostic markers and their relevance to immune cells which will help in understanding the development of AD. Targeting miRNAs and drugs provides new research clues for preventing the development of AD.
铁死亡是一种新定义的程序性细胞死亡形式，在阿尔茨海默病（AD）病理过程中起重要作用。本研究旨在整合生物信息学技术，探索支持铁死亡与AD之间相关性的生物标志物。此外，还对无症状AD（AsymAD）的转录组特征进行了铁死亡相关生物标志物的进一步研究。
从GEO数据库下载AD的微阵列数据集GSE118553、GSE132903、GSE33000和GSE157239。从FerrDb网站提取铁死亡相关基因列表。使用R“limma”包识别差异表达基因（DEG），并用于筛选铁死亡相关的枢纽基因。通过枢纽基因使用随机森林算法构建诊断模型。还通过CIBERSORTx分析免疫细胞浸润情况。使用miRNet和DGIdb数据库识别靶向枢纽基因的 microRNA（miRNA）和药物。
我们鉴定出18个在AD中异常表达的铁死亡相关枢纽基因，并且在AsymAD中均观察到一致的表达趋势。随机森林诊断模型在训练集（AUC = 0.824）和验证集（AUC = 0.734）中均具有良好的预测结果。分析免疫细胞浸润情况，结果显示AD中静息记忆CD4 + T细胞、M2巨噬细胞和中性粒细胞显著升高。观察到枢纽基因与免疫浸润存在显著相关性，例如DDIT4与静息记忆CD4 + T细胞呈强正相关，AKR1C2与M2巨噬细胞呈正相关。此外，还筛选了靶向枢纽基因的 microRNA（miRNA）和药物。
这些结果表明，我们筛选出的铁死亡相关枢纽基因在AD的病理进展中发挥了作用。我们探索了这些基因作为诊断标志物的潜力及其与免疫细胞的相关性，这将有助于理解AD的发展。靶向miRNA和药物为预防AD的发展提供了新的研究线索。
