Metabolomics with LC-QTOF-MS permits the prediction of disease stage in aortic abdominal aneurysm based on plasma metabolic fingerprint
Entity
UAM. Departamento de MedicinaPublisher
Public Library of ScienceDate
2012-02-24Citation
10.1371/journal.pone.0031982
Plos One 7.2 (2012): e31982
ISSN
1932-6203 (online)DOI
10.1371/journal.pone.0031982Funded by
The paper has been supported by Comunidad Autónoma de Madrid (CAM) (S2006/GEN-0247), the European Community Fighting Aneurysmal Disease (FAD) project (FP-7, HEALTH F2-2008-200647), the Spanish Ministerio de Ciencia y Tecnología (SAF2010/21852 and CTQ2008-03779), Ministerio de Sanidad y Consumo, Instituto de Salud Carlos III, Redes Red Temática de Investigación Cooperativa en Enfermedades Cardiovasculares (RECAVA) (RD06/0014/0035), European Aeronautic Defence and Space Company - Construcciones Aeronáuticas Sociedad Anónima (EADSCASA), and EUS2008-03565Project
Comunidad de Madrid. S2006/GEN-0247/PROTEOMARKERS-CM; info:eu-repo/grantAgreement/EC/FP7/200647Subjects
Aorta; Biological Markers; Lysophospholipids; Inflammation; Spectrometry; High Pressure Liquid; MedicinaRights
© 2012 Ciborowski et al.Abstract
Abdominal aortic aneurysm (AAA) is a permanent and localized aortic dilation, defined as aortic diameter ≥3 cm. It is an asymptomatic but potentially fatal condition because progressive enlargement of the abdominal aorta is spontaneously evolving towards rupture. Biomarkers may help to explain pathological processes of AAA expansion, and allow us to find novel therapeutic strategies or to determine the efficiency of current therapies. Metabolomics seems to be a good approach to find biomarkers of AAA. In this study, plasma samples of patients with large AAA, small AAA, and controls were fingerprinted with LC-QTOF-MS. Statistical analysis was used to compare metabolic fingerprints and select metabolites that showed a significant change. Results presented here reveal that LC-QTOF-MS based fingerprinting of plasma from AAA patients is a very good technique to distinguish small AAA, large AAA, and controls. With the use of validated PLS-DA models it was possible to classify patients according to the disease stage and predict properly the stage of additional AAA patients. Identified metabolites indicate a role for sphingolipids, lysophospholipids, cholesterol metabolites, and acylcarnitines in the development and progression of AAA. Moreover, guanidinosuccinic acid, which mimics nitric oxide in terms of its vasodilatory action, was found as a strong marker of large AAA
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Google Scholar:Ciborowski, Michał
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Teul, Joanna
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Martín Ventura, José Luis
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Egido, Jesús
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Barbas, Coral
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