Haijes Hanneke A, Willemsen Marcel, Van der Ham Maria, Gerrits Johan, Pras-Raves Mia L, Prinsen Hubertus C M T, Van Hasselt Peter M, De Sain-van der Velden Monique G M, Verhoeven-Duif Nanda M, Jans Judith J M
Section Metabolic Diagnostics, Department of Genetics, University Medical Centre Utrecht, Utrecht University, Lundlaan 6, 3584 EA Utrecht, The Netherlands.
Section Metabolic Diseases, Department of Child Health, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht University, Lundlaan 6, 3584 EA Utrecht, The Netherlands.
Metabolites. 2019 Jan 11;9(1):12. doi: 10.3390/metabo9010012.
In metabolic diagnostics, there is an emerging need for a comprehensive test to acquire a complete view of metabolite status. Here, we describe a non-quantitative direct-infusion high-resolution mass spectrometry (DI-HRMS) based metabolomics method and evaluate the method for both dried blood spots (DBS) and plasma. 110 DBS of 42 patients harboring 23 different inborn errors of metabolism (IEM) and 86 plasma samples of 38 patients harboring 21 different IEM were analyzed using DI-HRMS. A peak calling pipeline developed in R programming language provided Z-scores for ~1875 mass peaks corresponding to ~3835 metabolite annotations (including isomers) per sample. Based on metabolite Z-scores, patients were assigned a 'most probable diagnosis' by an investigator blinded for the known diagnoses of the patients. Based on DBS sample analysis, 37/42 of the patients, corresponding to 22/23 IEM, could be correctly assigned a 'most probable diagnosis'. Plasma sample analysis, resulted in a correct 'most probable diagnosis' in 32/38 of the patients, corresponding to 19/21 IEM. The added clinical value of the method was illustrated by a case wherein DI-HRMS metabolomics aided interpretation of a variant of unknown significance (VUS) identified by whole-exome sequencing. In summary, non-quantitative DI-HRMS metabolomics in DBS and plasma is a very consistent, high-throughput and nonselective method for investigating the metabolome in genetic disease.
在代谢诊断中，越来越需要一种全面的检测方法来全面了解代谢物状态。在此，我们描述了一种基于非定量直接进样高分辨率质谱（DI-HRMS）的代谢组学方法，并对干血斑（DBS）和血浆样本进行了评估。使用DI-HRMS分析了42例患有23种不同先天性代谢缺陷（IEM）患者的110份DBS样本以及38例患有21种不同IEM患者的86份血浆样本。用R编程语言开发的峰识别流程为每个样本中约1875个质量峰提供Z分数，这些峰对应约3835种代谢物注释（包括异构体）。根据代谢物Z分数，由对患者已知诊断情况不知情的研究人员为患者指定“最可能的诊断”。基于DBS样本分析，42例患者中的37例（对应23种IEM中的22种）能够被正确指定“最可能的诊断”。血浆样本分析中，38例患者中的32例（对应21种IEM中的19种）得到了正确的“最可能的诊断”。通过一个案例说明了该方法的附加临床价值，在该案例中，DI-HRMS代谢组学辅助解释了全外显子组测序鉴定出的意义未明变异（VUS）。总之，DBS和血浆中的非定量DI-HRMS代谢组学是一种非常一致、高通量且非选择性的研究遗传疾病代谢组的方法。
