Cardiology Department, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong China.
NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, Guangdong China.
Int J Med Sci. 2024 Aug 12;21(11):2127-2138. doi: 10.7150/ijms.94179. eCollection 2024.
Identification of the unknown pathogenic factor driving atherosclerosis not only enhances the development of disease biomarkers but also facilitates the discovery of new therapeutic targets, thus contributing to the improved management of coronary artery disease (CAD). We aimed to identify causative protein biomarkers in CAD etiology based on proteomics and 2-sample Mendelian randomization (MR) design. Serum samples from 33 first-onset CAD patients and 31 non-CAD controls were collected and detected using protein array. Differentially expressed analyses were used to identify candidate proteins for causal inference. We used 2-sample MR to detect the causal associations between the candidate proteins and CAD. Network MR was performed to explore whether metabolic risk factors for CAD mediated the risk of identified protein. Vascular expression of candidate protein was also detected. Among the differentially expressed proteins identified utilizing proteomics, we found that circulating Golgi protein 73 (GP73) was causally associated with incident CAD and other atherosclerotic events sharing similar etiology. Network MR approach showed low-density lipoprotein cholesterol and glycated hemoglobin serve as mediators in the causal pathway, transmitting 42.1% and 8.7% effects from GP73 to CAD, respectively. Apart from the circulating form of GP73, both mouse model and human specimens imply that vascular GP73 expression was also upregulated in atherosclerotic lesions and concomitant with markers of macrophage and phenotypic switching of vascular smooth muscle cells (VSMCs). Our study supported GP73 as a biomarker and causative for CAD. GP73 may involve in CAD pathogenesis mainly via dyslipidemia and hyperglycemia, which may enrich the etiological information and suggest future research direction on CAD.
鉴定导致动脉粥样硬化的未知致病因素不仅可以增强疾病生物标志物的开发,还可以促进新的治疗靶点的发现,从而有助于改善冠心病(CAD)的管理。我们旨在基于蛋白质组学和双样本孟德尔随机化(MR)设计,鉴定 CAD 病因中的因果蛋白生物标志物。收集 33 例首发 CAD 患者和 31 例非 CAD 对照的血清样本,并使用蛋白质芯片进行检测。差异表达分析用于鉴定因果推断的候选蛋白。我们使用双样本 MR 检测候选蛋白与 CAD 之间的因果关联。网络 MR 用于探讨 CAD 的代谢危险因素是否介导了鉴定蛋白的风险。还检测了候选蛋白的血管表达。在利用蛋白质组学鉴定的差异表达蛋白中,我们发现循环高尔基蛋白 73(GP73)与 CAD 及其他具有相似病因的动脉粥样硬化事件的发病存在因果关系。网络 MR 方法表明,低密度脂蛋白胆固醇和糖化血红蛋白作为因果途径的中介物,分别将 GP73 对 CAD 的影响传递 42.1%和 8.7%。除了 GP73 的循环形式外,小鼠模型和人类标本均表明,血管 GP73 表达在动脉粥样硬化病变中也上调,并与巨噬细胞标志物和血管平滑肌细胞(VSMCs)表型转换的标志物同时存在。我们的研究支持 GP73 作为 CAD 的生物标志物和病因。GP73 可能主要通过血脂异常和高血糖参与 CAD 的发病机制,这可能丰富 CAD 的病因信息,并为未来的研究方向提供建议。