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Sci Rep. 2016 Oct 3;6:34453. doi: 10.1038/srep34453.

A capillary electrophoresis coupled to mass spectrometry pipeline for long term comparable assessment of the urinary metabolome.

Author information

1
Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Equipe 12, 1 avenue Jean Poulhès, BP 84225, 31432 Toulouse Cedex 4, France.
2
Université Toulouse III Paul-Sabatier Toulouse, France.
3
HybridStat Predictive Analytics, Athens, Greece.
4
Unité de Recherche Clinique Pédiatrique, Module Plurithématique Pédiatrique, Centre d'Investigation Clinique - Hôpital des Enfants, Toulouse, France.
5
CHU Toulouse, Hôpital des Enfants, Service de Néphrologie - Médecine Interne - Hypertension Pédiatrique, Toulouse, France.

Abstract

Although capillary electrophoresis coupled to mass spectrometry (CE-MS) has potential application in the field of metabolite profiling, very few studies actually used CE-MS to identify clinically useful body fluid metabolites. Here we present an optimized CE-MS setup and analysis pipeline to reproducibly explore the metabolite content of urine. We show that the use of a beveled tip capillary improves the sensitivity of detection over a flat tip. We also present a novel normalization procedure based on the use of endogenous stable urinary metabolites identified in the combined metabolome of 75 different urine samples from healthy and diseased individuals. This method allows a highly reproducible comparison of the same sample analyzed nearly 130 times over a range of 4 years. To demonstrate the use of this pipeline in clinical research we compared the urinary metabolome of 34 newborns with ureteropelvic junction (UPJ) obstruction and 15 healthy newborns. We identified 32 features with differential urinary abundance. Combination of the 32 compounds in a SVM classifier predicted with 76% sensitivity and 86% specificity UPJ obstruction in a separate validation cohort of 24 individuals. Thus, this study demonstrates the feasibility to use CE-MS as a tool for the identification of clinically relevant urinary metabolites.

PMID:
27694997
PMCID:
PMC5046087
DOI:
10.1038/srep34453
[Indexed for MEDLINE]
Free PMC Article

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