Institut für Prophylaxe und Epidemiologie der Kreislaufkrankheiten, Klinikum der Universität München, Pettenkoferstrasse 9, 80336 München, Germany.
Arterioscler Thromb Vasc Biol. 2012 Feb;32(2):182-95. doi: 10.1161/ATVBAHA.111.232686.
The greatest challenge of scientific research is to understand the causes and consequences of disease. In recent years, great efforts have been devoted to unraveling the basic mechanisms of atherosclerosis (the underlying pathology of cardiovascular disease), which remains a major cause of morbidity and mortality worldwide. Because of the complex and multifactorial pathophysiology of cardiovascular disease, different research techniques have increasingly been combined to unravel genetic aspects, molecular pathways, and cellular functions involved in atherogenesis, vascular inflammation, and dyslipidemia to gain a multifaceted picture addressing this complexity. Thanks to the rapid evolution of high-throughput technologies, we are now able to generate large-scale data on the DNA, RNA, and protein levels. With the help of sophisticated computational tools, these data sets are integrated to enhance information extraction and are being increasingly used in a systems biology approach to model biological processes as interconnected and regulated networks. This review exemplifies the use of high-throughput technologies-such as genomics, transcriptomics, proteomics, and epigenomics-and systems biology to explore pathomechanisms of vascular inflammation and atherosclerosis.
科学研究最大的挑战在于了解疾病的病因和后果。近年来，人们致力于揭示动脉粥样硬化（心血管疾病的潜在病理学）的基本机制，而动脉粥样硬化仍然是全球发病率和死亡率的主要原因。由于心血管疾病的病理生理学复杂且多因素，不同的研究技术越来越多地被结合起来，以揭示涉及动脉粥样形成、血管炎症和血脂异常的遗传方面、分子途径和细胞功能，从而全面了解这种复杂性。由于高通量技术的快速发展，我们现在能够在 DNA、RNA 和蛋白质水平上生成大规模数据。借助复杂的计算工具，这些数据集被整合以增强信息提取，并越来越多地用于系统生物学方法来模拟作为相互关联和调节网络的生物过程。这篇综述举例说明了高通量技术（如基因组学、转录组学、蛋白质组学和表观基因组学）和系统生物学在探索血管炎症和动脉粥样硬化发病机制中的应用。
