PINK1 dominated mitochondria associated genes signature predicts abdominal aortic aneurysm with metabolic syndrome

粒体自噬 下调和上调 线粒体 品脱1 腹主动脉瘤 基因敲除 生物 基因 发病机制 CYP27A1 癌症研究 医学 内科学 细胞生物学 细胞凋亡 遗传学 动脉瘤 自噬 外科
作者
Kangjie Wang,Zhihao Zhou,Lin Huang,Qinghui Kan,Zhecun Wang,Weibin Wu,Chen Yao
出处
期刊:Biochimica Et Biophysica Acta: Molecular Basis Of Disease [Elsevier]
卷期号:1870 (2): 166919-166919
标识
DOI:10.1016/j.bbadis.2023.166919
摘要

Abdominal aortic aneurysm (AAA) is typically asymptomatic but a devastating cardiovascular disorder, with overall mortality exceeding 80 % once it ruptures. Some patients with AAA may also have comorbid metabolic syndrome (MS), suggesting a potential common underlying pathogenesis. Mitochondrial dysfunction has been reported as a key factor contributing to the deterioration of both AAA and MS. However, the intricate interplay between metabolism and mitochondrial function, both contributing to the development of AAA, has not been thoroughly explored. In this study, we identified candidate genes related to mitochondrial function in AAA and MS. Subsequently, we developed a nomoscore model comprising hub genes (PINK1, ACSL1, CYP27A1, and SLC25A11), identified through the application of two machine learning algorithms, to predict AAA. We observed a marked disparity in immune infiltration profiles between high- and low-nomoscore groups. Furthermore, we confirmed a significant upregulation of the expression of the four hub genes in AAA tissues. Among these, ACSL1 showed relatively higher expression in LPS-treated RAW264.7 cell lines, while CYP27A1 exhibited a notable decrease. Moreover, SLC25A11 displayed a significant upregulation in AngII-treated VSMCs. Conversely, the expression level of PINK1 declined in LPS-stimulated RAW264.7 cell lines but significantly increased in AngII-treated VSMCs. In vivo experiments revealed that the activation of PINK1-mediated mitophagy inhibited the development of AAA in mice. In this current study, we have innovatively identified four mitochondrial function-related genes through integrated bioinformatic analysis. This discovery sheds light on the regulatory mechanisms and unveils promising therapeutic targets for the comorbidity of AAA and MS.
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