Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts 02215, USA; email:
Annu Rev Med. 2020 Jan 27;71:163-175. doi: 10.1146/annurev-med-042418-010924.
Risk assessments are integral for the prevention and management of cardiometabolic disease (CMD). However, individuals may develop CMD without traditional risk factors, necessitating the development of novel biomarkers to aid risk prediction. The emergence of omic technologies, including genomics, proteomics, and metabolomics, has allowed for assessment of orthogonal measures of cardiometabolic risk, potentially improving the ability for novel biomarkers to refine disease risk assessments. While omics has shed light on novel mechanisms for the development of CMD, its adoption in clinical practice faces significant challenges. We review select omic technologies and cardiometabolic investigations for risk prediction, while highlighting challenges and opportunities for translating findings to clinical practice.
风险评估是预防和管理心血管代谢疾病（CMD）的重要组成部分。然而，一些个体可能在没有传统风险因素的情况下患上 CMD，这就需要开发新的生物标志物来辅助风险预测。组学技术（包括基因组学、蛋白质组学和代谢组学）的出现，使得对心血管代谢风险的正交测量进行评估成为可能，这可能会提高新型生物标志物对疾病风险评估的细化能力。尽管组学为 CMD 的发生机制提供了新的认识，但它在临床实践中的应用仍面临着重大挑战。我们回顾了一些用于风险预测的组学技术和心血管代谢研究，同时强调了将研究结果转化为临床实践的挑战和机遇。
