Chan Stephen Y, Loscalzo Joseph
Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Circ Res. 2012 Jul 20;111(3):359-74. doi: 10.1161/CIRCRESAHA.111.258541.
The molecular pathways that govern human disease consist of molecular circuits that coalesce into complex, overlapping networks. These network pathways are presumably regulated in a coordinated fashion, but such regulation has been difficult to decipher using only reductionistic principles. The emerging paradigm of "network medicine" proposes to utilize insights garnered from network topology (eg, the static position of molecules in relation to their neighbors) as well as network dynamics (eg, the unique flux of information through the network) to understand better the pathogenic behavior of complex molecular interconnections that traditional methods fail to recognize. As methodologies evolve, network medicine has the potential to capture the molecular complexity of human disease while offering computational methods to discern how such complexity controls disease manifestations, prognosis, and therapy. This review introduces the fundamental concepts of network medicine and explores the feasibility and potential impact of network-based methods for predicting individual manifestations of human disease and designing rational therapies. Wherever possible, we emphasize the application of these principles to cardiovascular disease.
调控人类疾病的分子途径由分子回路组成,这些回路汇聚成复杂且相互重叠的网络。这些网络途径可能是以协调的方式进行调控的,但仅使用还原论原则很难解读这种调控。新兴的“网络医学”范式提议利用从网络拓扑(例如分子相对于其邻居的静态位置)以及网络动力学(例如信息在网络中的独特流动)中获得的见解,来更好地理解传统方法未能识别的复杂分子相互连接的致病行为。随着方法的不断发展,网络医学有潜力捕捉人类疾病的分子复杂性,同时提供计算方法来辨别这种复杂性如何控制疾病表现、预后和治疗。本综述介绍了网络医学的基本概念,并探讨了基于网络的方法在预测人类疾病个体表现和设计合理治疗方案方面的可行性和潜在影响。只要有可能,我们就强调这些原则在心血管疾病中的应用。