Literature DB >> 34299495

Urinary Metabolomics Study of Patients with Bicuspid Aortic Valve Disease.

Massimo Chessa1, Mario Panebianco1, Sara Corbu2, Milena Lussu2, Angelica Dessì2, Roberta Pintus2, Flaminia Cesare Marincola3, Vassilios Fanos2.   

Abstract

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.

Entities:  

Keywords:  BAV; NMR; metabolomics; urine

Year:  2021        PMID: 34299495     DOI: 10.3390/molecules26144220

Source DB:  PubMed          Journal:  Molecules        ISSN: 1420-3049            Impact factor:   4.411


  1 in total

1.  Novelty detection for metabolic dynamics established on breast cancer tissue using 2D NMR TOCSY spectra.

Authors:  Lubaba Migdadi; Ahmad Telfah; Roland Hergenröder; Christian Wöhler
Journal:  Comput Struct Biotechnol J       Date:  2022-06-01       Impact factor: 6.155

  1 in total

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