1. NMR-based metabolic profiling of children with premature adrenarche.
- Author
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Matzarapi K, Giannakopoulos A, Chasapi SA, Kritikou D, Efthymiadou A, Chrysis D, and Spyroulias GA
- Subjects
- Amino Acids, Cholesterol, Glucose, Inositol, Lipids, Magnetic Resonance Spectroscopy, Metabolomics, Adrenarche genetics
- 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
1 H 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., (© 2022. The Author(s).)- Published
- 2022
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