Section on Cardiovascular Medicine, Department of Internal Medicine (D.M.H., C.F.Z., G.S.)
Biocomplexity Institute of Virginia Tech, Virginia Tech, Blacksburg (C.M.).
Circulation. 2018 Jun 19;137(25):2741-2756. doi: 10.1161/CIRCULATIONAHA.118.034365.
The inability to detect premature atherosclerosis significantly hinders implementation of personalized therapy to prevent coronary heart disease. A comprehensive understanding of arterial protein networks and how they change in early atherosclerosis could identify new biomarkers for disease detection and improved therapeutic targets.
Here we describe the human arterial proteome and proteomic features strongly associated with early atherosclerosis based on mass spectrometry analysis of coronary artery and aortic specimens from 100 autopsied young adults (200 arterial specimens). Convex analysis of mixtures, differential dependent network modeling, and bioinformatic analyses defined the composition, network rewiring, and likely regulatory features of the protein networks associated with early atherosclerosis and how they vary across 2 anatomic distributions.
The data document significant differences in mitochondrial protein abundance between coronary and aortic samples (coronary>>aortic), and between atherosclerotic and normal tissues (atherosclerotic<<normal), and major alterations in tumor necrosis factor, insulin receptor, peroxisome proliferator-activated receptor-α, and peroxisome proliferator-activated receptor-γ protein networks, as well, in the setting of early disease. In addition, a subset of tissue protein biomarkers indicative of early atherosclerosis was shown to predict anatomically defined coronary atherosclerosis when measured in plasma samples in a separate clinical cohort (area under the curve=0.92 [0.83-0.96]), thereby validating the use of human tissue proteomics to discover relevant plasma biomarkers for clinical applications. In addition to the specific proteins and pathways identified here, the publicly available data resource and the analysis pipeline used illustrate a strategy for interrogating and interpreting the proteomic architecture of tissues that may be relevant for other chronic diseases characterized by multicellular tissue phenotypes.
The human arterial proteome can be viewed as a complex network whose architectural features vary considerably as a function of anatomic location and the presence or absence of atherosclerosis. The data suggest important reductions in mitochondrial protein abundance in early atherosclerosis and also identify a subset of plasma proteins that are highly predictive of angiographically defined coronary disease.
无法早期检测动脉粥样硬化极大地阻碍了实施预防冠心病的个性化治疗。全面了解动脉蛋白网络及其在早期动脉粥样硬化中的变化，可以为疾病检测和改善治疗靶点发现新的生物标志物。
我们在这里描述了基于 100 例尸检年轻成年人（200 个动脉标本）的冠状动脉和主动脉标本的质谱分析，确定了与早期动脉粥样硬化强烈相关的人类动脉蛋白质组和蛋白质组特征。混合物的凸分析、差异依赖网络建模和生物信息学分析定义了与早期动脉粥样硬化相关的蛋白质网络的组成、网络重布线以及可能的调控特征，以及它们在 2 个解剖分布中的变化。
数据表明，冠状动脉和主动脉样本之间（冠状动脉>主动脉）以及动脉粥样硬化和正常组织之间（动脉粥样硬化<正常组织）的线粒体蛋白丰度存在显著差异，肿瘤坏死因子、胰岛素受体、过氧化物酶体增殖物激活受体-α和过氧化物酶体增殖物激活受体-γ蛋白网络也发生了重大改变，在疾病早期也是如此。此外，在另一临床队列的血浆样本中测量时，一组表明早期动脉粥样硬化的组织蛋白生物标志物可预测解剖定义的冠状动脉粥样硬化（曲线下面积=0.92 [0.83-0.96]），从而验证了使用人类组织蛋白质组学来发现相关的临床应用的血浆生物标志物。除了这里确定的特定蛋白质和途径之外，公开可用的数据资源和使用的分析管道说明了一种用于研究和解释与以多细胞组织表型为特征的其他慢性疾病相关的组织蛋白质组学结构的策略。
人类动脉蛋白质组可以被视为一个复杂的网络，其结构特征随着解剖位置和动脉粥样硬化的存在与否而有很大的变化。数据表明，早期动脉粥样硬化中存在线粒体蛋白丰度的重要降低，并且还确定了一组高度预测血管造影定义的冠心病的血浆蛋白。
