医学
生物标志物
冠状动脉疾病
蛋白质组学
纤维蛋白原
冠状动脉粥样硬化
病理
蛋白质组
易损斑块
病态的
细胞外基质
生物标志物发现
生物信息学
内科学
纤维帽
发病机制
心脏病学
免疫组织化学
动脉
炎症
诊断生物标志物
作者
Xinjie Xu,Zhongli Chen,Sifei Chen,Jiansong Huang,Jiali Chen,Jiaying Cao,Hang Gao,Enhao Huang,Yibo Zhang,Xiangjie Li,Yi-Feng Zhang,Xiaorui Liu,Shengkang Huang,Ke Yang,Yang Yang,Wenjia Zhang,Ying Song,Liang Chen,Zhan Hu
标识
DOI:10.1186/s40364-025-00846-3
摘要
The molecular features of coronary atherosclerosis progression remain incompletely understood. A comprehensive characterization of coronary proteome dynamics during atherosclerosis progression could facilitate the identification of novel biomarkers for early detection of plaque initiation and risk assessment of plaque destabilization. We performed proteomics on human coronary artery specimens representing five progressive histopathologic stages of atherosclerosis according to the modified AHA classification, including adaptive intimal thickening (AIT), pathological intimal thickening (PIT), fibroatheroma (FA), thin cap fibroatheroma (TCFA), and ruptured plaque (RP). The results revealed progressive dysregulation of complement and coagulation cascades and extracellular matrix (ECM) organization during histopathologic progression, particularly in plaque initiation and destabilization. Integrated single-cell RNA sequencing data showed that complement and coagulation pathways were predominantly upregulated in fibroblasts and macrophages, while ECM organization was elevated in fibroblasts and smooth muscle cells. Plasma proteomics in a discovery cohort identified THBS1, ECM2, and C1R proteins as robust diagnostic biomarkers from among the overlapping complement and ECM proteins found in the tissue proteomics. The combination of these biomarkers achieved area under the curve (AUC) values of 0.831 in the training set and 0.764 in the test set for identifying coronary artery disease (CAD). In both the discovery cohort and the external validation cohort, this biomarker panel distinguished stable CAD from non-stenosis controls (AUC: 0.765 and 0.841, respectively) and identified ACS patients (AUC: 0.786 and 0.822, respectively). These findings elucidate the proteomic landscape of atherosclerosis progression and establish a three-protein biomarker panel with potential for CAD diagnosis.
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