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Untargeted Metabolomics-Based Screening Method for Inborn Errors of Metabolism using Semi-Automatic Sample Preparation with an UHPLC- Orbitrap-MS Platform.
Metabolites ( IF 3.4 ) Pub Date : 2019-11-26 , DOI: 10.3390/metabo9120289
Ramon Bonte 1 , Michiel Bongaerts 1 , Serwet Demirdas 1 , Janneke G Langendonk 2 , Hidde H Huidekoper 3 , Monique Williams 3 , Willem Onkenhout 1 , Edwin H Jacobs 1 , Henk J Blom 1 , George J G Ruijter 1
Affiliation  

Routine diagnostic screening of inborn errors of metabolism (IEM) is currently performed by different targeted analyses of known biomarkers. This approach is time-consuming, targets a limited number of biomarkers and will not identify new biomarkers. Untargeted metabolomics generates a global metabolic phenotype and has the potential to overcome these issues. We describe a novel, single platform, untargeted metabolomics method for screening IEM, combining semi-automatic sample preparation with pentafluorophenylpropyl phase (PFPP)-based UHPLC- Orbitrap-MS. We evaluated analytical performance and diagnostic capability of the method by analysing plasma samples of 260 controls and 53 patients with 33 distinct IEM. Analytical reproducibility was excellent, with peak area variation coefficients below 20% for the majority of the metabolites. We illustrate that PFPP-based chromatography enhances identification of isomeric compounds. Ranked z-score plots of metabolites annotated in IEM samples were reviewed by two laboratory specialists experienced in biochemical genetics, resulting in the correct diagnosis in 90% of cases. Thus, our untargeted metabolomics platform is robust and differentiates metabolite patterns of different IEMs from those of controls. We envision that the current approach to diagnose IEM, using numerous tests, will eventually be replaced by untargeted metabolomics methods, which also have the potential to discover novel biomarkers and assist in interpretation of genetic data.

中文翻译:

使用UHPLC-Orbitrap-MS平台的半自动样品前处理,基于先天性代谢组学的代谢错误筛查方法。

目前,对先天性代谢错误(IEM)的常规诊断筛查是通过对已知生物标记物进行不同的靶向分析来进行的。这种方法很耗时,只针对有限数量的生物标志物,并且不会识别新的生物标志物。非靶向代谢组学可产生整体代谢表型,并有可能克服这些问题。我们描述了一种新颖的,单一平台,无目标的代谢组学方法,用于筛选IEM,将半自动样品制备与基于五氟苯基丙基相(PFPP)的UHPLC-Orbitrap-MS相结合。我们通过分析260例对照和53例具有33种不同IEM的患者的血浆样本,评估了该方法的分析性能和诊断能力。分析重现性极好,大多数代谢物的峰面积变异系数均低于20%。我们说明了基于PFPP的色谱法可增强同分异构化合物的鉴定。由两名具有生化遗传经验的实验室专家审查了IEM样品中注释的代谢物的排名Z评分图,从而在90%的病例中得出了正确的诊断结果。因此,我们的非靶向代谢组学平台功能强大,可将不同IEM的代谢物模式与对照区分开。我们设想,目前使用多种测试方法诊断IEM的方法最终将被无针对性的代谢组学方法所取代,这种方法也具有发现新的生物标记物和辅助遗传数据解释的潜力。由两名具有生化遗传经验的实验室专家审查了IEM样品中注释的代谢物的排名Z评分图,从而在90%的病例中得出了正确的诊断结果。因此,我们的非靶向代谢组学平台功能强大,可将不同IEM的代谢物模式与对照区分开。我们设想,目前使用多种测试方法诊断IEM的方法最终将被无针对性的代谢组学方法所取代,这种方法也具有发现新的生物标记物和辅助遗传数据解释的潜力。由两名具有生化遗传经验的实验室专家审查了IEM样品中注释的代谢物的排名Z评分图,从而在90%的病例中得出了正确的诊断结果。因此,我们的非靶向代谢组学平台功能强大,可将不同IEM的代谢物模式与对照区分开。我们设想,目前使用多种测试方法诊断IEM的方法最终将被无针对性的代谢组学方法所取代,这种方法也具有发现新的生物标记物和辅助遗传数据解释的潜力。
更新日期:2019-11-27
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