Li Maohua, Xiao Shasha, Qin Qi, Fu Keyun, Wang Lunchang, Li Xin, Shu Chang, Li Jiehua
Department of Vascular Surgery, The Second Xiangya Hospital of Central South University, Changsha, 410011, China; Molecular Biology Research Center, School of Life Sciences, Hunan Province Key Laboratory of Basic and Applied Hematology, Central South University, Changsha, 410013, China.
Department of Vascular Surgery, The Second Xiangya Hospital of Central South University, Changsha, 410011, China; Institute of Vascular Diseases, Central South University, Changsha, 410011, China.
Biochem Biophys Res Commun. 2025 Sep 30;782:152589. doi: 10.1016/j.bbrc.2025.152589. Epub 2025 Sep 3.
Abdominal aortic aneurysm (AAA) is a potentially life-threatening vascular condition that currently lacks effective pharmacological treatment. The disease is strongly associated with chronic inflammation, where immune cells like macrophages play a crucial role. Efferocytosis, the process by which apoptotic cells are cleared, is involved in regulating inflammation. However, the role of efferocytosis in AAA pathogenesis remains largely unexplored. A combination of bioinformatic analysis and experimental validation was employed to investigate the role of efferocytosis-related genes (EFRGs) in AAA pathogenesis. Differentially expressed efferocytosis-related genes (EFRDEGs) were identified using datasets such as GSE47472, GSE57691 and GSE7084. Machine learning techniques, including LASSO, Random Forest and XGBoost were used to identify key biomarkers. Single-cell RNA sequencing were used to explore the interactions between EFRGs and immune cells within the AAA microenvironment. Furthermore, the expression of UCP2 was validated in both human and mouse AAA tissues, and pharmacological inhibition of UCP2 was tested in elastase-induced AAA mouse models. The analysis identified 15 EFRDEGs associated with AAA. Machine learning methods identified UCP2, DUSP5, and IL1B as key diagnostic biomarkers, with the highest predictive accuracy (AUC of 1). Single-cell RNA sequencing revealed that UCP2 is highly expressed in macrophages within AAA tissue compared to controls. Moreover, UCP2 was significantly upregulated in both human AAA specimens and elastase-induced mouse AAA models. Immunofluorescence staining confirmed the colocalization of UCP2 with the macrophage marker F4/80 in AAA lesions. Pharmacological inhibition of UCP2 with Genipin significantly attenuated AAA progression in mice, reducing aortic dilation. This study offers a comprehensive exploration of efferocytosis-related genes in AAA and highlights UCP2 as a potential therapeutic target, providing novel strategies for medical intervention.
腹主动脉瘤（AAA）是一种潜在的危及生命的血管疾病，目前缺乏有效的药物治疗方法。该疾病与慢性炎症密切相关，巨噬细胞等免疫细胞在其中起着关键作用。胞葬作用是清除凋亡细胞的过程，参与炎症调节。然而，胞葬作用在AAA发病机制中的作用在很大程度上仍未得到探索。本研究采用生物信息学分析与实验验证相结合的方法，探讨胞葬作用相关基因（EFRGs）在AAA发病机制中的作用。利用GSE47472、GSE57691和GSE7084等数据集鉴定差异表达的胞葬作用相关基因（EFRDEGs）。使用包括LASSO、随机森林和XGBoost在内的机器学习技术来识别关键生物标志物。采用单细胞RNA测序技术探讨EFRGs与AAA微环境中免疫细胞之间的相互作用。此外，在人和小鼠AAA组织中验证了UCP2的表达，并在弹性蛋白酶诱导的AAA小鼠模型中测试了UCP2的药理学抑制作用。分析确定了15个与AAA相关的EFRDEGs。机器学习方法将UCP2、DUSP5和IL1B鉴定为关键诊断生物标志物，预测准确率最高（AUC为1）。单细胞RNA测序显示，与对照组相比，UCP2在AAA组织内的巨噬细胞中高表达。此外，UCP2在人AAA标本和弹性蛋白酶诱导的小鼠AAA模型中均显著上调。免疫荧光染色证实UCP2与AAA病变中巨噬细胞标志物F4/80共定位。用京尼平对UCP2进行药理学抑制可显著减轻小鼠AAA进展，减少主动脉扩张。本研究全面探讨了AAA中胞葬作用相关基因，并强调UCP2作为潜在治疗靶点，为医学干预提供了新策略。
