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Metabolic signatures of osteoarthritis in urine using liquid chromatography‐high resolution tandem mass spectrometry
INTRODUCTION: Osteoarthritis (OA) is a common cause of disability in older people, but its aetiology is not yet fully understood. Biomarkers of OA from metabolomics studies have shown potential use in understanding the progression and pathophysiology of OA. OBJECTIVES: To investigate possible surrog...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7925472/ https://www.ncbi.nlm.nih.gov/pubmed/33655418 http://dx.doi.org/10.1007/s11306-021-01778-3 |
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author | Abdelrazig, Salah Ortori, Catharine A. Doherty, Michael Valdes, Ana M. Chapman, Victoria Barrett, David A. |
author_facet | Abdelrazig, Salah Ortori, Catharine A. Doherty, Michael Valdes, Ana M. Chapman, Victoria Barrett, David A. |
author_sort | Abdelrazig, Salah |
collection | PubMed |
description | INTRODUCTION: Osteoarthritis (OA) is a common cause of disability in older people, but its aetiology is not yet fully understood. Biomarkers of OA from metabolomics studies have shown potential use in understanding the progression and pathophysiology of OA. OBJECTIVES: To investigate possible surrogate biomarkers of knee OA in urine using metabolomics to contribute towards a better understanding of OA progression and possible targeted treatment. METHOD: Liquid chromatography-high resolution mass spectrometry (LC-HRMS) was applied in a case–control approach to explore the possible metabolic differences between the urinary profiles of symptomatic knee OA patients (n = 74) (subclassified into inflammatory OA, n = 22 and non-inflammatory OA, n = 52) and non-OA controls (n = 68). Univariate, multivariate and pathway analyses were performed with a rigorous validation including cross-validation, permutation test, prediction and receiver operating characteristic curve to identify significantly altered metabolites and pathways in OA. RESULTS: OA datasets generated 7405 variables and multivariate analysis showed clear separation of inflammatory OA, but not non-inflammatory OA, from non-OA controls. Adequate cross-validation (R(2)Y = 0.874, Q(2) = 0.465) was obtained. The prediction model and the ROC curve showed satisfactory results with a sensitivity of 88%, specificity of 71% and accuracy of 77%. 26 metabolites were identified as potential biomarkers of inflammatory OA using HMDB, authentic standards and/or MS/MS database. CONCLUSION: Urinary metabolic profiles were altered in inflammatory knee OA subjects compared to those with non-inflammatory OA and non-OA controls. These altered profiles associated with perturbed activity of the TCA cycle, pyruvate and amino acid metabolism linked to inflammation, oxidative stress and collagen destruction. Of note, 2-keto-glutaramic acid level was > eightfold higher in the inflammatory OA patients compared to non-OA control, signalling a possible perturbation in glutamine metabolism related to OA progression. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11306-021-01778-3. |
format | Online Article Text |
id | pubmed-7925472 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-79254722021-03-19 Metabolic signatures of osteoarthritis in urine using liquid chromatography‐high resolution tandem mass spectrometry Abdelrazig, Salah Ortori, Catharine A. Doherty, Michael Valdes, Ana M. Chapman, Victoria Barrett, David A. Metabolomics Original Article INTRODUCTION: Osteoarthritis (OA) is a common cause of disability in older people, but its aetiology is not yet fully understood. Biomarkers of OA from metabolomics studies have shown potential use in understanding the progression and pathophysiology of OA. OBJECTIVES: To investigate possible surrogate biomarkers of knee OA in urine using metabolomics to contribute towards a better understanding of OA progression and possible targeted treatment. METHOD: Liquid chromatography-high resolution mass spectrometry (LC-HRMS) was applied in a case–control approach to explore the possible metabolic differences between the urinary profiles of symptomatic knee OA patients (n = 74) (subclassified into inflammatory OA, n = 22 and non-inflammatory OA, n = 52) and non-OA controls (n = 68). Univariate, multivariate and pathway analyses were performed with a rigorous validation including cross-validation, permutation test, prediction and receiver operating characteristic curve to identify significantly altered metabolites and pathways in OA. RESULTS: OA datasets generated 7405 variables and multivariate analysis showed clear separation of inflammatory OA, but not non-inflammatory OA, from non-OA controls. Adequate cross-validation (R(2)Y = 0.874, Q(2) = 0.465) was obtained. The prediction model and the ROC curve showed satisfactory results with a sensitivity of 88%, specificity of 71% and accuracy of 77%. 26 metabolites were identified as potential biomarkers of inflammatory OA using HMDB, authentic standards and/or MS/MS database. CONCLUSION: Urinary metabolic profiles were altered in inflammatory knee OA subjects compared to those with non-inflammatory OA and non-OA controls. These altered profiles associated with perturbed activity of the TCA cycle, pyruvate and amino acid metabolism linked to inflammation, oxidative stress and collagen destruction. Of note, 2-keto-glutaramic acid level was > eightfold higher in the inflammatory OA patients compared to non-OA control, signalling a possible perturbation in glutamine metabolism related to OA progression. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11306-021-01778-3. Springer US 2021-03-03 2021 /pmc/articles/PMC7925472/ /pubmed/33655418 http://dx.doi.org/10.1007/s11306-021-01778-3 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Article Abdelrazig, Salah Ortori, Catharine A. Doherty, Michael Valdes, Ana M. Chapman, Victoria Barrett, David A. Metabolic signatures of osteoarthritis in urine using liquid chromatography‐high resolution tandem mass spectrometry |
title | Metabolic signatures of osteoarthritis in urine using liquid chromatography‐high resolution tandem mass spectrometry |
title_full | Metabolic signatures of osteoarthritis in urine using liquid chromatography‐high resolution tandem mass spectrometry |
title_fullStr | Metabolic signatures of osteoarthritis in urine using liquid chromatography‐high resolution tandem mass spectrometry |
title_full_unstemmed | Metabolic signatures of osteoarthritis in urine using liquid chromatography‐high resolution tandem mass spectrometry |
title_short | Metabolic signatures of osteoarthritis in urine using liquid chromatography‐high resolution tandem mass spectrometry |
title_sort | metabolic signatures of osteoarthritis in urine using liquid chromatography‐high resolution tandem mass spectrometry |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7925472/ https://www.ncbi.nlm.nih.gov/pubmed/33655418 http://dx.doi.org/10.1007/s11306-021-01778-3 |
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