Hou Xinhuang, Li Zhipeng, Lin Jun, Lin Wei, Li Luyao, Zheng Xiaoqi, Lai Xiaoling, Zhu Lin, Guo Pingfan, Cai Fanggang, Zhang Jinchi, Li Wanglong, Yang Changwei, Dai Yiquan
Department of Vascular Surgery, The First Affiliated Hospital, Fujian Medical University, 20 Chazhong Road, Fuzhou, 350005, China.
Department of Vascular Surgery, National Regional Medical Center, Binhai Campus of The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China.
Sci Rep. 2025 Apr 7;15(1):11812. doi: 10.1038/s41598-025-96434-4.
Carotid and femoral plaques exhibit varying degrees of stability; however, the relationships of different genes/cell types with plaque embolism are poorly understood. We evaluated differential gene/cell expression and investigated the cells/genes associated with carotid and femoral artery plaque embolism. sc-RNA-seq and bulk RNA data were obtained to identify differentially expressed genes (DEGs). Seven machine learning models were trained, and the top 10 DEGs across all models were selected. The most disturbed cells in carotid and femoral artery plaques were identified using Augur, while the genes and cells in the carotid plaque associated with embolism were analyzed through scPagwas. The differences in most disturbed cells and embolism-related cells were further analyzed. Compared with femoral plaques, carotid plaques had 80 downregulated and 90 upregulated genes. Machine learning identified the key DEGs between carotid and femoral plaques were predominantly from the HOX gene family. Natural Killer (NK) cells were the most significantly disturbed cells between carotid and femoral plaques, and they may be most strongly associated with plaque embolism. Among the differential genes in NK cells, CD2 was most associated with embolism. Our research may offer new insights into atherosclerosis at different locations.
颈动脉和股动脉斑块表现出不同程度的稳定性；然而，不同基因/细胞类型与斑块栓塞之间的关系却知之甚少。我们评估了差异基因/细胞表达，并研究了与颈动脉和股动脉斑块栓塞相关的细胞/基因。获取了单细胞RNA测序（sc-RNA-seq）和批量RNA数据以鉴定差异表达基因（DEGs）。训练了七个机器学习模型，并选择了所有模型中排名前10的DEGs。使用Augur鉴定颈动脉和股动脉斑块中受干扰最严重的细胞，同时通过单细胞全基因组关联研究（scPagwas）分析与颈动脉斑块栓塞相关的基因和细胞。进一步分析了受干扰最严重的细胞和与栓塞相关的细胞之间的差异。与股动脉斑块相比，颈动脉斑块有80个基因下调和90个基因上调。机器学习确定颈动脉和股动脉斑块之间的关键DEGs主要来自HOX基因家族。自然杀伤（NK）细胞是颈动脉和股动脉斑块之间受干扰最显著的细胞，它们可能与斑块栓塞关联最为密切。在NK细胞的差异基因中，CD2与栓塞关联最为紧密。我们的研究可能为不同部位的动脉粥样硬化提供新的见解。
