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Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels
Aortic valve stenosis (AVS) is a prevalent condition among the elderly population that eventually requires aortic valve replacement. The lack of reliable biomarkers for AVS poses a challenge for its early diagnosis and the application of preventive measures. Untargeted gas chromatography mass spectr...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688110/ https://www.ncbi.nlm.nih.gov/pubmed/33237940 http://dx.doi.org/10.1371/journal.pone.0242019 |
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author | Al Hageh, Cynthia Rahy, Ryan Khazen, Georges Brial, Francois Khnayzer, Rony S. Gauguier, Dominique Zalloua, Pierre A. |
author_facet | Al Hageh, Cynthia Rahy, Ryan Khazen, Georges Brial, Francois Khnayzer, Rony S. Gauguier, Dominique Zalloua, Pierre A. |
author_sort | Al Hageh, Cynthia |
collection | PubMed |
description | Aortic valve stenosis (AVS) is a prevalent condition among the elderly population that eventually requires aortic valve replacement. The lack of reliable biomarkers for AVS poses a challenge for its early diagnosis and the application of preventive measures. Untargeted gas chromatography mass spectrometry (GC-MS) metabolomics was applied in 46 AVS cases and 46 controls to identify plasma and urine metabolites underlying AVS risk. Multivariate data analyses were performed on pre-processed data (e.g. spectral peak alignment), in order to detect changes in metabolite levels in AVS patients and to evaluate their performance in group separation and sensitivity of AVS prediction, followed by regression analyses to test for their association with AVS. Through untargeted analysis of 190 urine and 130 plasma features that could be detected and quantified in the GC-MS spectra, we identified contrasting levels of 22 urine and 21 plasma features between AVS patients and control subjects. Following metabolite assignment, we observed significant changes in the concentration of known metabolites in urine (n = 14) and plasma (n = 15) that distinguish the metabolomic profiles of AVS patients from healthy controls. Associations with AVS were replicated in both plasma and urine for about half of these metabolites. Among these, 2-Oxovaleric acid, elaidic acid, myristic acid, palmitic acid, estrone, myo-inositol showed contrasting trends of regulation in the two biofluids. Only trans-Aconitic acid and 2,4-Di-tert-butylphenol showed consistent patterns of regulation in both plasma and urine. These results illustrate the power of metabolomics in identifying potential disease-associated biomarkers and provide a foundation for further studies towards early diagnostic applications in severe heart conditions that may prevent surgery in the elderly. |
format | Online Article Text |
id | pubmed-7688110 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-76881102020-12-05 Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels Al Hageh, Cynthia Rahy, Ryan Khazen, Georges Brial, Francois Khnayzer, Rony S. Gauguier, Dominique Zalloua, Pierre A. PLoS One Research Article Aortic valve stenosis (AVS) is a prevalent condition among the elderly population that eventually requires aortic valve replacement. The lack of reliable biomarkers for AVS poses a challenge for its early diagnosis and the application of preventive measures. Untargeted gas chromatography mass spectrometry (GC-MS) metabolomics was applied in 46 AVS cases and 46 controls to identify plasma and urine metabolites underlying AVS risk. Multivariate data analyses were performed on pre-processed data (e.g. spectral peak alignment), in order to detect changes in metabolite levels in AVS patients and to evaluate their performance in group separation and sensitivity of AVS prediction, followed by regression analyses to test for their association with AVS. Through untargeted analysis of 190 urine and 130 plasma features that could be detected and quantified in the GC-MS spectra, we identified contrasting levels of 22 urine and 21 plasma features between AVS patients and control subjects. Following metabolite assignment, we observed significant changes in the concentration of known metabolites in urine (n = 14) and plasma (n = 15) that distinguish the metabolomic profiles of AVS patients from healthy controls. Associations with AVS were replicated in both plasma and urine for about half of these metabolites. Among these, 2-Oxovaleric acid, elaidic acid, myristic acid, palmitic acid, estrone, myo-inositol showed contrasting trends of regulation in the two biofluids. Only trans-Aconitic acid and 2,4-Di-tert-butylphenol showed consistent patterns of regulation in both plasma and urine. These results illustrate the power of metabolomics in identifying potential disease-associated biomarkers and provide a foundation for further studies towards early diagnostic applications in severe heart conditions that may prevent surgery in the elderly. Public Library of Science 2020-11-25 /pmc/articles/PMC7688110/ /pubmed/33237940 http://dx.doi.org/10.1371/journal.pone.0242019 Text en © 2020 Al Hageh et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Al Hageh, Cynthia Rahy, Ryan Khazen, Georges Brial, Francois Khnayzer, Rony S. Gauguier, Dominique Zalloua, Pierre A. Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels |
title | Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels |
title_full | Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels |
title_fullStr | Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels |
title_full_unstemmed | Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels |
title_short | Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels |
title_sort | plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688110/ https://www.ncbi.nlm.nih.gov/pubmed/33237940 http://dx.doi.org/10.1371/journal.pone.0242019 |
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