Urinary Metabolomics Study of Patients with Bicuspid Aortic Valve Disease.
Adolescent
Adult
Aged
Bicuspid Aortic Valve Disease
/ metabolism
Biomarkers
/ urine
Discriminant Analysis
Female
Humans
Least-Squares Analysis
Magnetic Resonance Imaging
/ methods
Magnetic Resonance Spectroscopy
/ methods
Male
Metabolic Networks and Pathways
/ physiology
Metabolome
/ physiology
Metabolomics
/ methods
Middle Aged
ROC Curve
Young Adult
BAV
NMR
metabolomics
urine
Journal
Molecules (Basel, Switzerland)
ISSN: 1420-3049
Titre abrégé: Molecules
Pays: Switzerland
ID NLM: 100964009
Informations de publication
Date de publication:
12 Jul 2021
12 Jul 2021
Historique:
received:
29
05
2021
revised:
06
07
2021
accepted:
07
07
2021
entrez:
24
7
2021
pubmed:
25
7
2021
medline:
18
9
2021
Statut:
epublish
Résumé
Bicuspid aortic valve (BAV) is the most common congenital heart defect responsible for valvular and aortic complications in affected patients. Causes and mechanisms of this pathology are still elusive and thus the lack of early detection biomarkers leads to challenges in its diagnosis and prevention of associated cardiovascular anomalies. The aim of this study was to explore the potential use of urine Nuclear Magnetic Resonance (NMR) metabolomics to evaluate a molecular fingerprint of BAV. Both multivariate and univariate statistical analyses were performed to compare the urinary metabolome of 20 patients with BAV with that of 24 matched controls. Orthogonal partial least squared discriminant analysis (OPLS-DA) showed statistically significant discrimination between cases and controls, suggesting seven metabolites (3-hydroxybutyrate, alanine, betaine, creatine, glycine, hippurate, and taurine) as potential biomarkers. Among these, glycine, hippurate and taurine individually displayed medium sensitivity and specificity by receiver operating characteristic (ROC) analysis. Pathway analysis indicated two metabolic pathways likely perturbed in BAV subjects. Possible contributions of gut microbiota activity and energy imbalance are also discussed. These results constitute encouraging preliminary findings in favor of the use of urine-based metabolomics for early diagnosis of BAV.
Identifiants
pubmed: 34299495
pii: molecules26144220
doi: 10.3390/molecules26144220
pmc: PMC8304733
pii:
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
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