代谢组学在先天性代谢紊乱诊断中的应用

IF 3.4 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Current Opinion in Systems Biology Pub Date : 2022-03-01 DOI:10.1016/j.coisb.2021.100409
Judith JM. Jans , Melissa H. Broeks , Nanda M. Verhoeven-Duif
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引用次数: 7

摘要

对患有罕见的先天性代谢紊乱的患者进行诊断可能是一条漫长而艰难的道路。虽然下一代测序现在是一种常用的方式,它显著地影响了诊断的产量和速度,但通过非靶向代谢组学进行下一代代谢筛查将证明其在诊断轨迹中的价值。非靶向代谢组学,通常基于质谱平台,是一种成熟的技术,用于鉴定新的疾病标志物。然而,作为罕见病的一线诊断手段,非靶向代谢组学现在只是逐渐进入临床实践。大多数回顾性研究表明,大多数先天性代谢紊乱可以通过非靶向代谢组学检测到。有些疾病仍未被发现,哪些诊断被遗漏取决于所选择的特定代谢组学方法;不存在单一的包罗万象的平台。因此,目前在前瞻性研究中对机会和局限性进行了仔细的评估,将诊断设置中的非靶向代谢组学与当前的金标准遗传和生化诊断模式相结合。这些研究表明,当实施非靶向代谢组学时,诊断率增加。鉴于技术的不断进步,在可预见的未来,确定各种诊断方式的最佳时间、地点和顺序将继续发展。
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Metabolomics in diagnostics of inborn metabolic disorders

Finding a diagnosis for patients with a rare inborn metabolic disorder can be a long and difficult path. Whereas next generation sequencing is now a commonly used modality, which has significantly impacted the diagnostic yield and speed, next generation metabolic screening through untargeted metabolomics is next in line to prove its value in the diagnostic trajectory.

Untargeted metabolomics, often based on mass spectrometry platforms, is a well-established technology for the identification of novel disease markers. However, untargeted metabolomics as first line diagnostics for rare disease is now only gradually making its way into clinical practice. Most retrospective studies show that the majority of inborn metabolic disorder can be detected through untargeted metabolomics. Some diseases will still go undetected, which diagnoses are missed depends on the specific metabolomics method chosen; there is no single all-encompassing platform. Therefore, careful assessments of the opportunities and limitations are currently undertaken in prospective studies, combining untargeted metabolomics in the diagnostics setting with the current gold standard genetic and biochemical diagnostic modalities. These studies show an increased diagnostic yield when implementing untargeted metabolomics. Given the continuing technological advances, defining the optimal timing, place, and order of the various diagnostic modalities will keep on evolving in the foreseen future.

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来源期刊
Current Opinion in Systems Biology
Current Opinion in Systems Biology Mathematics-Applied Mathematics
CiteScore
7.10
自引率
2.70%
发文量
20
期刊介绍: Current Opinion in Systems Biology is a new systematic review journal that aims to provide specialists with a unique and educational platform to keep up-to-date with the expanding volume of information published in the field of Systems Biology. It publishes polished, concise and timely systematic reviews and opinion articles. In addition to describing recent trends, the authors are encouraged to give their subjective opinion on the topics discussed. As this is such a broad discipline, we have determined themed sections each of which is reviewed once a year. The following areas will be covered by Current Opinion in Systems Biology: -Genomics and Epigenomics -Gene Regulation -Metabolic Networks -Cancer and Systemic Diseases -Mathematical Modelling -Big Data Acquisition and Analysis -Systems Pharmacology and Physiology -Synthetic Biology -Stem Cells, Development, and Differentiation -Systems Biology of Mold Organisms -Systems Immunology and Host-Pathogen Interaction -Systems Ecology and Evolution
期刊最新文献
From regulation of cell fate decisions towards patient-specific treatments, insights from mechanistic models of signalling pathways Editorial overview: Systems biology of ecological interactions across scales A critical review of multiscale modeling for predictive understanding of cancer cell metabolism Network modeling approaches for metabolic diseases and diabetes Contents
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