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临床代谢组学用于先天性代谢缺陷。

Clinical metabolomics for inborn errors of metabolism.

机构信息

Metabolon, Inc., Morrisville, NC, United States.

Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States.

出版信息

Adv Clin Chem. 2022;107:79-138. doi: 10.1016/bs.acc.2021.09.001. Epub 2021 Oct 5.

Abstract

Metabolism is a highly regulated process that provides nutrients to cells and essential building blocks for the synthesis of protein, DNA and other macromolecules. In healthy biological systems, metabolism maintains a steady state in which the concentrations of metabolites are relatively constant yet are subject to metabolic demands and environmental stimuli. Rare genetic disorders, such as inborn errors of metabolism (IEM), cause defects in regulatory enzymes or proteins leading to metabolic pathway disruption and metabolite accumulation or deficiency. Traditionally, the laboratory diagnosis of IEMs has been limited to analytical methods that target specific metabolites such as amino acids and acyl carnitines. This approach is effective as a screening method for the most common IEM disorders but lacks the comprehensive coverage of metabolites that is necessary to identify rare disorders that present with nonspecific clinical symptoms. Fortunately, advancements in technology and data analytics has introduced a new field of study called metabolomics which has allowed scientists to perform comprehensive metabolite profiling of biological systems to provide insight into mechanism of action and gene function. Since metabolomics seeks to measure all small molecule metabolites in a biological specimen, it provides an innovative approach to evaluating disease in patients with rare genetic disorders. In this review we provide insight into the appropriate application of metabolomics in clinical settings. We discuss the advantages and limitations of the method and provide details related to the technology, data analytics and statistical modeling required for metabolomic profiling of patients with IEMs.

摘要

代谢是一个高度调节的过程,为细胞提供营养物质和合成蛋白质、DNA 和其他大分子的必需构建块。在健康的生物系统中,代谢维持着一种稳定状态,其中代谢物的浓度相对恒定,但会受到代谢需求和环境刺激的影响。罕见的遗传疾病,如先天性代谢缺陷(IEM),会导致调节酶或蛋白质缺陷,从而导致代谢途径中断以及代谢物积累或缺乏。传统上,IEM 的实验室诊断仅限于针对特定代谢物(如氨基酸和酰基辅酶 A)的分析方法。这种方法作为最常见的 IEM 疾病的筛查方法非常有效,但缺乏识别具有非特异性临床症状的罕见疾病所需的代谢物全面覆盖。幸运的是,技术和数据分析的进步引入了一个新的研究领域,称为代谢组学,它使科学家能够对生物系统进行全面的代谢物分析,从而深入了解作用机制和基因功能。由于代谢组学旨在测量生物样本中的所有小分子代谢物,因此它为评估罕见遗传疾病患者的疾病提供了一种创新方法。在这篇综述中,我们深入探讨了代谢组学在临床环境中的适当应用。我们讨论了该方法的优点和局限性,并详细介绍了 IEM 患者代谢组学分析所需的技术、数据分析和统计建模。

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