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Urinary metabolic phenotyping of mucopolysaccharidosis type I combining untargeted and targeted strategies with data modeling

Abdellah Tebani 1 Isabelle Schmitz-Afonso 2 Lénaïg Abily-Donval 3, 4, 5 Bénédicte Héron 6 Monique Piraud 7 Jérome Ausseil 8 Anaïs Brassier 9 Pascale de Lonlay 10 Farid Zerimech 11 Frederic Vaz 12 Bruno Gonzalez 5, 4 Stéphane Marret 4, 5 Carlos Afonso 13 Soumeya Bekri 14
1 UNIROUEN - Université de Rouen Normandie
2 ICSN - Institut de Chimie des Substances Naturelles
3 Néovasc - Endothélium microcirculatoire cérébral et lésions du système nerveux central au cours du développement
4 Team 4 "NeoVasc" - INSERM U1245
GPMCND - Génomique et Médecine Personnalisée du Cancer et des Maladies Neuropsychiatriques
5 GPMCND - Génomique et Médecine Personnalisée du Cancer et des Maladies Neuropsychiatriques
6 Service de Neuropédiatrie [CHU Trousseau]
7 CBPE - Centre de Biologie et Pathologie Est
8 CHU Amiens-Picardie - Centre hospitalier universitaire d'Amiens
9 MaMEA Necker - Centre Référence des Maladies Héréditaires du Métabolisme de l'Enfant et de l'Adulte [CHU Necker]
10 IMAGINE - U1163 - Imagine - Institut des maladies génétiques
11 Pôle de Biologie Pathologie Génétique - Laboratoire de Biochimie et Biologie Moléculaire [CHRU Lille]
12 Laboratory Genetic Metabolic Disease
13 COBRA - Chimie Organique et Bioorganique : Réactivité et Analyse
14 Laboratoire de biochimie générale [Rouen]
Abstract : Background = Application of metabolic phenotyping could expand the pathophysiological knowledge of mucopolysaccharidoses (MPS) and may reveal the comprehensive metabolic impairments in MPS. However, few studies applied this approach to MPS. Methods = We applied targeted and untargeted metabolic profiling in urine samples obtained from a French cohort comprising 19 MPS I and 15 MPS I treated patients along with 66 controls. For that purpose, we used ultra-high-performance liquid chromatography combined with ion mobility and high-resolution mass spectrometry following a protocol designed for large-scale metabolomics studies regarding robustness and reproducibility. Furthermore, 24 amino acids have been quantified using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Keratan sulfate, Heparan sulfate and Dermatan sulfate concentrations have also been measured using an LC-MS/MS method. Univariate and multivariate data analyses have been used to select discriminant metabolites. The mummichog algorithm has been used for pathway analysis. Results = The studied groups yielded distinct biochemical phenotypes using multivariate data analysis. Univariate statistics also revealed metabolites that differentiated the groups. Specifically, metabolites related to the amino acid metabolism. Pathway analysis revealed that several major amino acid pathways were dysregulated in MPS. Comparison of targeted and untargeted metabolomics data with in silico results yielded arginine, proline and glutathione metabolisms being the most affected. Conclusion = This study is one of the first metabolic phenotyping studies of MPS I. The findings might help to generate new hypotheses about MPS pathophysiology and to develop further targeted studies of a smaller number of potentially key metabolites.
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Journal articles
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https://hal-normandie-univ.archives-ouvertes.fr/hal-02445369
Contributor : Bruno Gonzalez <>
Submitted on : Monday, January 20, 2020 - 10:41:44 AM
Last modification on : Saturday, September 19, 2020 - 3:37:12 AM

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COMUE-NORMANDIE | HCL | ICSN | INC-CNRS | UNIV-PARIS5 | INSA-ROUEN | UNIROUEN | COBRA | INSA-GROUPE | GPMCND | USPC | CNRS | UNIV-PARIS | UP-SANTE | ENSICAEN | UNILEHAVRE | UNICAEN

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Abdellah Tebani, Isabelle Schmitz-Afonso, Lénaïg Abily-Donval, Bénédicte Héron, Monique Piraud, et al.. Urinary metabolic phenotyping of mucopolysaccharidosis type I combining untargeted and targeted strategies with data modeling. Clinica Chimica Acta, Elsevier, 2017, 475, pp.7-14. ⟨10.1016/j.cca.2017.09.024⟩. ⟨hal-02445369⟩

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