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Open AccessArticle

Untargeted Metabolomics-Based Screening Method for Inborn Errors of Metabolism using Semi-Automatic Sample Preparation with an UHPLC- Orbitrap-MS Platform

1
Center for Lysosomal and Metabolic Diseases, Department of Clinical Genetics, Erasmus University Medical Center, Dr. Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
2
Center for Lysosomal and Metabolic Diseases, Department of Internal Medicine, Erasmus University Medical Center, Dr. Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
3
Center for Lysosomal and Metabolic Diseases, Department of Pediatrics, Erasmus University Medical Center, Dr. Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
*
Authors to whom correspondence should be addressed.
Metabolites 2019, 9(12), 289; https://doi.org/10.3390/metabo9120289
Received: 30 September 2019 / Revised: 19 November 2019 / Accepted: 22 November 2019 / Published: 26 November 2019
(This article belongs to the Special Issue Genetic Metabolic Diagnostics)
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. View Full-Text
Keywords: metabolomics; inborn errors of metabolism; LC-MS; HRAM-MS; Orbitrap; PFPP; IEM; organic aciduria; urea cycle defects; PKU metabolomics; inborn errors of metabolism; LC-MS; HRAM-MS; Orbitrap; PFPP; IEM; organic aciduria; urea cycle defects; PKU
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Bonte, R.; Bongaerts, M.; Demirdas, S.; Langendonk, J.G.; Huidekoper, H.H.; Williams, M.; Onkenhout, W.; Jacobs, E.H.; Blom, H.J.; Ruijter, G.J.G. Untargeted Metabolomics-Based Screening Method for Inborn Errors of Metabolism using Semi-Automatic Sample Preparation with an UHPLC- Orbitrap-MS Platform. Metabolites 2019, 9, 289.

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