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首页> 外文期刊>International Journal of Epidemiology: Official Journal of the International Epidemiological Association >Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future
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Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future

机译:将代谢组学应用于心脏代谢干预研究和试验:过去的经验和未来的路线图

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摘要

Metabolomics and lipidomics are emerging methods for detailed phenotyping of small molecules in samples. It is hoped that such data will: (i) enhance baseline prediction of patient response to pharmacotherapies (beneficial or adverse); (ii) reveal changes in metabolites shortly after initiation of therapy that may predict patient response, including adverse effects, before routine biomarkers are altered; and(iii) give new insights into mechanisms of drug action, particularly where the results of a trial of a new agent were unexpected, and thus help future drug development. In these ways, metabolomics could enhance research findings from intervention studies. This narrative review provides an overview of metabolomics and lipidomics in early clinical intervention studies for investigation of mechanisms of drug action and prediction of drug response (both desired and undesired). We highlight early examples from drug intervention studies associated with cardiometabolic disease. Despite the strengths of such studies, particularly the use of state-of-the-art technologies and advanced statistical methods, currently published studies in the metabolomics arena are largely underpowered and should be considered as hypothesis-generating. In order for metabolomics to meaningfully improve stratified medicine approaches to patient treatment, there is a need for higher quality studies, with better exploitation of biobanks from randomized clinical trials i.e. with large sample size, adjudicated outcomes, standardized procedures, validation cohorts, comparison witth routine biochemistry and both active and control/placebo arms. On the basis of this review, and based on our research experience using clinically established biomarkers, we propose steps to more speedily advance this area of research towards potential clinical impact.
机译:代谢组学和脂质组学是对样品中小分子进行详细表型分析的新兴方法。希望这些数据将:(i)增强患者对药物治疗(有益或不良反应)反应的基线预测; (ii)在治疗开始后不久就揭示代谢物的变化,这些变化可以预测患者的反应,包括不良反应,而常规的生物标志物则要改变; (iii)对药物作用机理提供新见解,特别是在新药试验结果出乎意料的情况下,从而有助于将来的药物开发。通过这些方式,代谢组学可以增强干预研究的研究结果。这篇叙述性综述概述了早期的临床干预研究中的代谢组学和脂质组学,以研究药物作用机制和预测药物反应(既需要的也不需要的)。我们重点介绍了与心脏代谢疾病相关的药物干预研究的早期实例。尽管此类研究具有优势,特别是使用最新技术和先进的统计方法,但目前在代谢组学领域发表的研究在很大程度上缺乏动力,应被视为产生假设的方法。为了使代谢组学有意义地改善用于患者治疗的分层医学方法,需要进行更高质量的研究,以更好地利用随机临床试验中的生物库,即具有大样本量,裁决结果,标准化程序,验证队列,与常规进行比较生物化学以及活性和对照/安慰剂组。在此综述的基础上,并基于我们使用临床建立的生物标志物的研究经验,我们提出了一些步骤,以更快地推动这一研究领域朝着潜在的临床影响发展。

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