Niiranen Teemu J, Vasan Ramachandran S
a National Heart, Blood and Lung Institute's and Boston University's Framingham Heart Study , Framingham , MA , USA.
Expert Rev Cardiovasc Ther. 2016 Jul;14(7):855-69. doi: 10.1080/14779072.2016.1176528. Epub 2016 Apr 25.
Cardiovascular (CVD) risk assessment with traditional risk factors (age, sex, blood pressure, lipids, smoking and diabetes) has remained relatively invariant over the past decades despite some inaccuracies associated with this approach. However, the search for novel, robust and cost-effective risk markers of CVD risk is ongoing.
A large share of the major developments in CVD risk prediction during the past five years has been made in large-scale biomarker discovery and the so called 'omics' - the rapidly growing fields of genomics, transcriptomics, epigenetics and metabolomics. This review focuses on how these new technologies are helping drive primary CVD risk estimation forward in recent years, and speculates on how they could be utilized more effectively for discovering novel risk factors in the future. Expert commentary: The search for new CVD risk factors is currently undergoing a significant revolution as the simple relationship between single risk factors and disease will have to be replaced by models that strive to integrate the whole field of omics into medicine.
尽管传统心血管疾病（CVD）风险评估方法（年龄、性别、血压、血脂、吸烟和糖尿病）存在一些不准确之处，但在过去几十年中，其相对保持不变。然而，寻找新的、可靠且具有成本效益的CVD风险标志物的工作仍在进行。
在过去五年中，CVD风险预测的重大进展很大一部分来自大规模生物标志物发现以及所谓的“组学”——基因组学、转录组学、表观遗传学和代谢组学等快速发展的领域。本综述重点关注这些新技术近年来如何推动原发性CVD风险评估的发展，并推测它们未来如何能更有效地用于发现新的风险因素。专家评论：目前，寻找新的CVD风险因素正经历一场重大变革，因为单一风险因素与疾病之间的简单关系将不得不被努力将整个组学领域整合到医学中的模型所取代。
