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代谢组学在心血管疾病诊断和预后中的新兴作用。

The Emerging Role of Metabolomics in the Diagnosis and Prognosis of Cardiovascular Disease.

机构信息

Cardiovascular Research Centre, Department of Pediatrics, Mazankowski Alberta Heart Institute, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada; Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada.

Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.

出版信息

J Am Coll Cardiol. 2016 Dec 27;68(25):2850-2870. doi: 10.1016/j.jacc.2016.09.972.

DOI:10.1016/j.jacc.2016.09.972
PMID:28007146
Abstract

Perturbations in cardiac energy metabolism are major contributors to a number of cardiovascular pathologies. In addition, comorbidities associated with cardiovascular disease (CVD) can alter systemic and myocardial metabolism, often contributing to the worsening of cardiac function and health outcomes. State-of-the-art metabolomic technologies give us the ability to measure thousands of metabolites in biological fluids or biopsies, providing us with a metabolic fingerprint of individual patients. These metabolic profiles may serve as diagnostic and/or prognostic tools that have the potential to significantly alter the management of CVD. Herein, the authors review how metabolomics can assist in the interpretation of perturbed metabolic processes, and how this has improved our ability to understand the pathology of ischemic heart disease, atherosclerosis, and heart failure. Taken together, the integration of metabolomics with other "omics" platforms will allow us to gain insight into pathophysiological interactions of metabolites, proteins, genes, and disease states, while advancing personalized medicine.

摘要

心脏能量代谢的紊乱是许多心血管病理的主要原因。此外,与心血管疾病(CVD)相关的合并症会改变全身和心肌代谢,通常会导致心脏功能和健康状况恶化。最先进的代谢组学技术使我们能够测量生物液或活检中的数千种代谢物,为个体患者提供代谢指纹图谱。这些代谢特征可作为诊断和/或预后工具,有可能显著改变 CVD 的治疗管理。在此,作者回顾了代谢组学如何帮助解释代谢过程的紊乱,以及这如何提高我们理解缺血性心脏病、动脉粥样硬化和心力衰竭病理的能力。总之,代谢组学与其他“组学”平台的整合将使我们能够深入了解代谢物、蛋白质、基因和疾病状态的病理生理相互作用,同时推进个性化医疗。

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