Comprehensive Metabolomic Profiling and Incident Cardiovascular Disease: A Systematic Review.
Comprehensive Metabolomic Profiling and Incident Cardiovascular Disease: A Systematic Review.
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DOI：
10.1161/jaha.117.005705
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发表时间：
2017-09-28
影响因子：
5.4
通讯作者：
Hu FB
中科院分区：
文献类型：
--
作者：
Ruiz-Canela M;Hruby A;Clish CB;Liang L;Martínez-González MA;Hu FB
代谢组学是发现心血管生物标志物的一个有前途的工具。我们系统地回顾了与心血管疾病（CVD）相关的综合代谢组学分析的文献。我们检索了MEDLINE和EMBASE从成立到2016年1月的数据。如果研究涉及成年人;遵循不可知和/或综合方法;使用血清或血浆（而不是尿液或其他生物标本）;在检查前瞻性疾病的背景下进行基线代谢物分析;并在CVD结局定义中包括心肌梗死、卒中和/或CVD死亡，则研究合格。我们识别了12篇原始文献（9项队列研究和3项巢式病例对照研究）;受试者人数范围为67至7256人。质谱法是主要的分析方法。代谢物的数量和化学多样性非常不均匀，从31到>10 000个特征不等。四项研究使用了非针对性特征分析。不同类型的代谢物与CVD风险相关：酰基肉毒碱，二羧基酰基肉毒碱，以及几种氨基酸和脂质类。使用这些代谢物仅观察到CVD预测的微小改善，超出了传统的风险因素（C指数改善范围为0.006至0.05）。有有限数量的纵向研究评估综合代谢组学特征与CVD风险之间的关联。由于分析工具千差万别，方法和统计方法也多种多样，因此对文献进行量化综合是一项挑战。虽然有些结果是有希望的，但还需要更多的研究，特别是代谢组学技术和统计方法的标准化。新的和整体的方法论方法的复制和组合将推动该领域实现其承诺。
Metabolomics is a promising tool of cardiovascular biomarker discovery. We systematically reviewed the literature on comprehensive metabolomic profiling in association with incident cardiovascular disease (CVD). We searched MEDLINE and EMBASE from inception to January 2016. Studies were eligible if they pertained to adult humans; followed an agnostic and/or comprehensive approach; used serum or plasma (not urine or other biospecimens); conducted metabolite profiling at baseline in the context of examining prospective disease; and included myocardial infarction, stroke, and/or CVD death in the CVD outcome definition. We identified 12 original articles (9 cohort and 3 nested case‐control studies); participant numbers ranged from 67 to 7256. Mass spectrometry was the predominant analytical method. The number and chemical diversity of metabolites were very heterogeneous, ranging from 31 to >10 000 features. Four studies used untargeted profiling. Different types of metabolites were associated with CVD risk: acylcarnitines, dicarboxylacylcarnitines, and several amino acids and lipid classes. Only tiny improvements in CVD prediction beyond traditional risk factors were observed using these metabolites (C index improvement ranged from 0.006 to 0.05). There are a limited number of longitudinal studies assessing associations between comprehensive metabolomic profiles and CVD risk. Quantitatively synthesizing the literature is challenging because of the widely varying analytical tools and the diversity of methodological and statistical approaches. Although some results are promising, more research is needed, notably standardization of metabolomic techniques and statistical approaches. Replication and combinations of novel and holistic methodological approaches would move the field toward the realization of its promise.