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靶向代谢组学的发展现状。

The evolving landscape of untargeted metabolomics.

机构信息

Dipartimento di Farmacia, Università Degli Studi di Napoli "Federico II", Napoli, 80131, Italy; CEINGE-Biotecnologie Avanzate, Naples, Italy.

CEINGE-Biotecnologie Avanzate, Naples, Italy; Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università di Napoli Federico II, Naples, Italy.

出版信息

Nutr Metab Cardiovasc Dis. 2021 Jun 7;31(6):1645-1652. doi: 10.1016/j.numecd.2021.01.008. Epub 2021 Jan 23.

Abstract

AIMS

Untargeted Metabolomics is a "hypothesis-generating discovery strategy" that compares groups of samples (e.g., cases vs controls); identifies the metabolome and establishes (early signs of) perturbations. Targeted Metabolomics helped gather key information in life sciences and disclosed novel strategies for the treatment of major clinical entities (e.g., malignancy, cardiovascular diabetes mellitus, drug toxicity). Because of its relevance in biomarker discovery, attention is now devoted to improving the translational potential of untargeted Metabolomics.

DATA SYNTHESIS

Expertise in laboratory medicine and in bioinformatics helps solve challenges/pitfalls that may bias metabolite profiling in untargeted Metabolomics. Clinical validation (availability/reliability of analytical instruments) and profitability (how many people will use the test) are mandatory steps for potential biomarkers. Biomarkers to predict individual patient response, patient populations that will best respond to specific strategies and/or approaches for an optimal response to treatment are now being developed. Additional help is expected from professional, and regulatory Agencies as to guidelines for study design and data acquisition and analysis, to be applied from the very beginning of a project. Evidence from food, plant, human, environmental, and animal research argues for the need of miniaturized approaches that employ low-cost, easy to use, mobile devices. ELISA kits with such characteristics that employ targeted metabolites are already available.

CONCLUSIONS

Improving knowledge of the mechanisms behind the disease status (pathophysiology) will help untargeted Metabolomics gather a direct positive impact on welfare and industrial advancements, and fade uncertainties perceived by regulators/payers and patients concerning variables related to miniaturised instruments and user-friendly software and databases.

摘要

目的

非靶向代谢组学是一种“产生假说的发现策略”,它比较了样本组(例如,病例与对照);确定代谢组并建立(早期迹象)扰动。靶向代谢组学有助于在生命科学中收集关键信息,并揭示治疗主要临床实体(如恶性肿瘤、心血管糖尿病、药物毒性)的新策略。由于其在生物标志物发现中的相关性,现在注意力集中在提高非靶向代谢组学的转化潜力上。

数据综合

实验室医学和生物信息学方面的专业知识有助于解决非靶向代谢组学中可能影响代谢物谱分析的挑战/陷阱。临床验证(分析仪器的可用性/可靠性)和盈利性(有多少人将使用该测试)是潜在生物标志物的必要步骤。现在正在开发用于预测个体患者反应的生物标志物、对特定策略反应最佳的患者群体,以及为获得最佳治疗反应而采用的方法。专业人员和监管机构将提供额外的帮助,制定研究设计和数据采集和分析的指南,从项目一开始就应用这些指南。来自食品、植物、人类、环境和动物研究的证据表明,需要采用小型化方法,使用低成本、易于使用、移动设备。已经有具有这种特性的、针对靶向代谢物的 ELISA 试剂盒。

结论

提高对疾病状态(病理生理学)背后机制的认识将有助于非靶向代谢组学直接对福利和工业进步产生积极影响,并消除监管机构/付款人和患者对与小型化仪器和用户友好的软件和数据库相关的变量的不确定性。

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