Li Junsheng, He Qiheng, Zheng Zhiyao, Liu Chenglong, Zhang Bojian, Mou Siqi, Zeng Chaofan, Sun Wei, Liu Wei, Ge Peicong, Zhang Dong, Zhao Jizong
Department of Neurosurgery, Fengtai District, Beijing Tiantan Hospital, Capital Medical University, No. 119 Nan Si Huan Xi Road, Beijing, 100070, China.
China National Clinical Research Center for Neurological Diseases, Beijing, China.
Mol Neurobiol. 2025 Feb;62(2):2515-2529. doi: 10.1007/s12035-024-04423-x. Epub 2024 Aug 12.
Moyamoya disease (MMD) is a rare, chronic, and progressive cerebrovascular disorder with unclear underlying causes and mechanisms. Previous studies suggest a potential involvement of endothelial-mesenchymal transition (EndMT) in the pathogenesis of MMD. This study aimed to explore the contribution of EndMT-related genes (ERGs) in MMD. Two datasets, GSE141022 and GSE157628, were integrated as the training set after batch effects removal. Differentially expressed ERGs were identified between MMD and control groups. Functional enrichment analysis and immune infiltration analysis were further performed. LASSO regression was used for hub MMD-related ERG selection. Consensus clustering was used for MMD subtype classification based on these hub MMD-related ERGs. Molecular characteristics between MMD subtypes were analyzed using WGCNA. PPI network was used to illuminate the genetic relationship. The hub MMD-related ERGs were validated in an independent testing set, GSE189993. The nomogram model was constructed and evaluated using ROC curves and calibration plots. Additionally, CCK-8, EdU, wound healing, and western blot were performed to confirm the function of the hub MMD-related ERGs. A total of 107 DE-ERGs were identified. Functional enrichment analysis showed these genes were associated with EndMT and immune response. The infiltrating levels of immune cells were commonly higher in the MMD group. LASSO regression identified 12 hub MMD-related ERGs, leading to the identification of two MMD subtypes. Four ERGs emerged as the final hub MMD-related ERGs after validation in the testing set, including CCL21, CEBPA, KRT18, and TNFRSF11A. The nomogram model exhibited excellent discrimination ability. In vitro experiments showed that CCL21, CEBPA, KRT18, and TNFRSF11A could promote proliferation, migration, and EndMT. This study investigated the potential role of EndMT in MMD and identified four hub MMD-related ERGs, providing potential therapeutic targets for MMD treatment.
烟雾病（MMD）是一种罕见的、慢性的、进行性的脑血管疾病，其潜在病因和发病机制尚不清楚。先前的研究表明，内皮-间充质转化（EndMT）可能参与烟雾病的发病机制。本研究旨在探讨EndMT相关基因（ERGs）在烟雾病中的作用。去除批次效应后，将两个数据集GSE141022和GSE157628整合为训练集。确定烟雾病组和对照组之间差异表达的ERGs。进一步进行功能富集分析和免疫浸润分析。采用LASSO回归选择与烟雾病相关的关键ERGs。基于这些与烟雾病相关的关键ERGs，采用一致性聚类进行烟雾病亚型分类。利用加权基因共表达网络分析（WGCNA）分析烟雾病亚型之间的分子特征。使用蛋白质-蛋白质相互作用（PPI）网络阐明遗传关系。在独立测试集GSE189993中验证与烟雾病相关的关键ERGs。构建列线图模型，并使用ROC曲线和校准图进行评估。此外，进行CCK-8、EdU、伤口愈合实验和蛋白质免疫印迹法以证实与烟雾病相关的关键ERGs的功能。共鉴定出107个差异表达的ERGs。功能富集分析表明，这些基因与EndMT和免疫反应相关。烟雾病组免疫细胞浸润水平通常较高。LASSO回归鉴定出12个与烟雾病相关的关键ERGs，从而确定了两种烟雾病亚型。在测试集中验证后，四个ERGs成为最终与烟雾病相关的关键ERGs，包括CCL21、CEBPA、KRT18和TNFRSF11A。列线图模型具有良好的区分能力。体外实验表明，CCL21、CEBPA、KRT18和TNFRSF11A可促进细胞增殖、迁移和EndMT。本研究探讨了EndMT在烟雾病中的潜在作用，并鉴定出四个与烟雾病相关的关键ERGs，为烟雾病治疗提供了潜在的治疗靶点。
