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Tytuł pozycji:

Unveiling metabolic remodeling in mucopolysaccharidosis type III through integrative metabolomics and pathway analysis

Tytuł:
Unveiling metabolic remodeling in mucopolysaccharidosis type III through integrative metabolomics and pathway analysis
Autorzy:
Abdellah Tebani
Lenaig Abily-Donval
Isabelle Schmitz-Afonso
Bénédicte Héron
Monique Piraud
Jérôme Ausseil
Farid Zerimech
Bruno Gonzalez
Stéphane Marret
Carlos Afonso
Soumeya Bekri
Temat:
Metabolomics
Inborn errors of metabolism
Mucopolysaccharidosis type III
Lysosomal storage diseases
Mass spectrometry
Ion mobility
Medicine
Źródło:
Journal of Translational Medicine, Vol 16, Iss 1, Pp 1-14 (2018)
Wydawca:
BMC, 2018.
Rok publikacji:
2018
Kolekcja:
LCC:Medicine
Typ dokumentu:
article
Opis pliku:
electronic resource
Język:
English
ISSN:
1479-5876
Relacje:
http://link.springer.com/article/10.1186/s12967-018-1625-1; https://doaj.org/toc/1479-5876
DOI:
10.1186/s12967-018-1625-1
Dostęp URL:
https://doaj.org/article/2a82a7d9a17a4d6fa0fa6281709f1a3a  Link otwiera się w nowym oknie
Numer akcesji:
edsdoj.2a82a7d9a17a4d6fa0fa6281709f1a3a
Czasopismo naukowe
Abstract Background Metabolomics represent a valuable tool to recover biological information using body fluids and may help to characterize pathophysiological mechanisms of the studied disease. This approach has not been widely used to explore inherited metabolic diseases. This study investigates mucopolysaccharidosis type III (MPS III). A thorough and holistic understanding of metabolic remodeling in MPS III may allow the development, improvement and personalization of patient care. Methods We applied both targeted and untargeted metabolomics to urine samples obtained from a French cohort of 49 patients, consisting of 13 MPS IIIA, 16 MPS IIIB, 13 MPS IIIC, and 7 MPS IIID, along with 66 controls. The analytical strategy is based on ultra-high-performance liquid chromatography combined with ion mobility and high-resolution mass spectrometry. Twenty-four amino acids have been assessed using tandem mass spectrometry combined with liquid chromatography. Multivariate data modeling has been used for discriminant metabolite selection. Pathway analysis has been performed to retrieve metabolic pathways impairments. Results Data analysis revealed distinct biochemical profiles. These metabolic patterns, particularly those related to the amino acid metabolisms, allowed the different studied groups to be distinguished. Pathway analysis unveiled major amino acid pathways impairments in MPS III mainly arginine–proline metabolism and urea cycle metabolism. Conclusion This represents one of the first metabolomics-based investigations of MPS III. These results may shed light on MPS III pathophysiology and could help to set more targeted studies to infer the biomarkers of the affected pathways, which is crucial for rare conditions such as MPS III.
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