NMR-based metabolic profiling of children with premature adrenarche
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Published:2022-10-14
Issue:10
Volume:18
Page:
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ISSN:1573-3890
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Container-title:Metabolomics
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language:en
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Short-container-title:Metabolomics
Author:
Matzarapi Konstantina,Giannakopoulos Aristeidis,Chasapi Styliani A.,Kritikou Dimitra,Efthymiadou Alexandra,Chrysis Dionisios,Spyroulias Georgios A.
Abstract
Abstract
Introduction
Premature adrenarche (PA) for long time was considered a benign condition but later has been connected to various diseases in childhood and adulthood which remains controversial.
Objective
To investigate the effect of premature adrenarche on the metabolic phenotype, and correlate the clinical and biochemical data with the metabolic profile of children with PA.
Methods
Nuclear magnetic resonance (NMR)-based untargeted and targeted metabolomic approach in combination with multivariate and univariate statistical analysis applied to study the metabolic profiles of children with PA. Plasma, serum, and urine samples were collected from fifty-two children with Idiopathic PA and forty-eight age-matched controls from the division of Pediatric Endocrinology of the University Hospital of Patras were enrolled.
Results
Metabolomic results showed that plasma and serum glucose, myo-inositol, amino acids, a population of unsaturated lipids, and esterified cholesterol were higher and significantly different in PA children. In the metabolic profiles of children with PA and age-matched control group a gradual increase of glucose and myo-inositol levels was observed in serum and plasma, which was positively correlated their body mass index standard deviation score (BMI SDS) values respectively. Urine 1H NMR metabolic fingerprint of PA children showed positive correlation and a clustering-dependent relationship with their BMI and bone age (BA) respectively.
Conclusion
This study provides evidence that PA driven metabolic changes begin during the childhood and PA may has an inductive role in a BMI–driven increase of specific metabolites. Finally, urine may be considered as the best biofluid for identification of the PA metabolism as it reflects more clearly the PA metabolic fingerprint.
Funder
University of Patras
Publisher
Springer Science and Business Media LLC
Subject
Clinical Biochemistry,Biochemistry,Endocrinology, Diabetes and Metabolism
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