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Urinary Metabolomics Study of Patients with Bicuspid Aortic Valve Disease

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...

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Autores principales: Chessa, Massimo, Panebianco, Mario, Corbu, Sara, Lussu, Milena, Dessì, Angelica, Pintus, Roberta, Cesare Marincola, Flaminia, Fanos, Vassilios
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8304733/
https://www.ncbi.nlm.nih.gov/pubmed/34299495
http://dx.doi.org/10.3390/molecules26144220
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author Chessa, Massimo
Panebianco, Mario
Corbu, Sara
Lussu, Milena
Dessì, Angelica
Pintus, Roberta
Cesare Marincola, Flaminia
Fanos, Vassilios
author_facet Chessa, Massimo
Panebianco, Mario
Corbu, Sara
Lussu, Milena
Dessì, Angelica
Pintus, Roberta
Cesare Marincola, Flaminia
Fanos, Vassilios
author_sort Chessa, Massimo
collection PubMed
description 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.
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spelling pubmed-83047332021-07-25 Urinary Metabolomics Study of Patients with Bicuspid Aortic Valve Disease Chessa, Massimo Panebianco, Mario Corbu, Sara Lussu, Milena Dessì, Angelica Pintus, Roberta Cesare Marincola, Flaminia Fanos, Vassilios Molecules Article 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. MDPI 2021-07-12 /pmc/articles/PMC8304733/ /pubmed/34299495 http://dx.doi.org/10.3390/molecules26144220 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chessa, Massimo
Panebianco, Mario
Corbu, Sara
Lussu, Milena
Dessì, Angelica
Pintus, Roberta
Cesare Marincola, Flaminia
Fanos, Vassilios
Urinary Metabolomics Study of Patients with Bicuspid Aortic Valve Disease
title Urinary Metabolomics Study of Patients with Bicuspid Aortic Valve Disease
title_full Urinary Metabolomics Study of Patients with Bicuspid Aortic Valve Disease
title_fullStr Urinary Metabolomics Study of Patients with Bicuspid Aortic Valve Disease
title_full_unstemmed Urinary Metabolomics Study of Patients with Bicuspid Aortic Valve Disease
title_short Urinary Metabolomics Study of Patients with Bicuspid Aortic Valve Disease
title_sort urinary metabolomics study of patients with bicuspid aortic valve disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8304733/
https://www.ncbi.nlm.nih.gov/pubmed/34299495
http://dx.doi.org/10.3390/molecules26144220
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