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Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases
BACKGROUND: Localized stress and cell death in chronic inflammatory diseases may release tissue-specific lipids into the circulation causing the blood plasma lipidome to reflect the type of inflammation. However, deep lipid profiles of major chronic inflammatory diseases have not been compared. METH...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8330692/ https://www.ncbi.nlm.nih.gov/pubmed/34311325 http://dx.doi.org/10.1016/j.ebiom.2021.103504 |
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author | Matthiesen, Rune Lauber, Chris Sampaio, Julio L. Domingues, Neuza Alves, Liliana Gerl, Mathias J. Almeida, Manuel S. Rodrigues, Gustavo Araújo Gonçalves, Pedro Ferreira, Jorge Borbinha, Cláudia Pedro Marto, João Neves, Marisa Batista, Frederico Viana-Baptista, Miguel Alves, Jose Simons, Kai Vaz, Winchil L.C. Vieira, Otilia V. |
author_facet | Matthiesen, Rune Lauber, Chris Sampaio, Julio L. Domingues, Neuza Alves, Liliana Gerl, Mathias J. Almeida, Manuel S. Rodrigues, Gustavo Araújo Gonçalves, Pedro Ferreira, Jorge Borbinha, Cláudia Pedro Marto, João Neves, Marisa Batista, Frederico Viana-Baptista, Miguel Alves, Jose Simons, Kai Vaz, Winchil L.C. Vieira, Otilia V. |
author_sort | Matthiesen, Rune |
collection | PubMed |
description | BACKGROUND: Localized stress and cell death in chronic inflammatory diseases may release tissue-specific lipids into the circulation causing the blood plasma lipidome to reflect the type of inflammation. However, deep lipid profiles of major chronic inflammatory diseases have not been compared. METHODS: Plasma lipidomes of patients suffering from two etiologically distinct chronic inflammatory diseases, atherosclerosis-related vascular disease, including cardiovascular (CVD) and ischemic stroke (IS), and systemic lupus erythematosus (SLE), were screened by a top-down shotgun mass spectrometry-based analysis without liquid chromatographic separation and compared to each other and to age-matched controls. Lipid profiling of 596 lipids was performed on a cohort of 427 individuals. Machine learning classifiers based on the plasma lipidomes were used to distinguish the two chronic inflammatory diseases from each other and from the controls. FINDINGS: Analysis of the lipidomes enabled separation of the studied chronic inflammatory diseases from controls based on independent validation test set classification performance (CVD vs control - Sensitivity: 0.94, Specificity: 0.88; IS vs control - Sensitivity: 1.0, Specificity: 1.0; SLE vs control – Sensitivity: 1, Specificity: 0.93) and from each other (SLE vs CVD ‒ Sensitivity: 0.91, Specificity: 1; IS vs SLE - Sensitivity: 1, Specificity: 0.82). Preliminary linear discriminant analysis plots using all data clearly separated the clinical groups from each other and from the controls, and partially separated CVD severities, as classified into five clinical groups. Dysregulated lipids are partially but not fully counterbalanced by statin treatment. INTERPRETATION: Dysregulation of the plasma lipidome is characteristic of chronic inflammatory diseases. Lipid profiling accurately identifies the diseases and in the case of CVD also identifies sub-classes. FUNDING: Full list of funding sources at the end of the manuscript. |
format | Online Article Text |
id | pubmed-8330692 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-83306922021-08-10 Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases Matthiesen, Rune Lauber, Chris Sampaio, Julio L. Domingues, Neuza Alves, Liliana Gerl, Mathias J. Almeida, Manuel S. Rodrigues, Gustavo Araújo Gonçalves, Pedro Ferreira, Jorge Borbinha, Cláudia Pedro Marto, João Neves, Marisa Batista, Frederico Viana-Baptista, Miguel Alves, Jose Simons, Kai Vaz, Winchil L.C. Vieira, Otilia V. EBioMedicine Research paper BACKGROUND: Localized stress and cell death in chronic inflammatory diseases may release tissue-specific lipids into the circulation causing the blood plasma lipidome to reflect the type of inflammation. However, deep lipid profiles of major chronic inflammatory diseases have not been compared. METHODS: Plasma lipidomes of patients suffering from two etiologically distinct chronic inflammatory diseases, atherosclerosis-related vascular disease, including cardiovascular (CVD) and ischemic stroke (IS), and systemic lupus erythematosus (SLE), were screened by a top-down shotgun mass spectrometry-based analysis without liquid chromatographic separation and compared to each other and to age-matched controls. Lipid profiling of 596 lipids was performed on a cohort of 427 individuals. Machine learning classifiers based on the plasma lipidomes were used to distinguish the two chronic inflammatory diseases from each other and from the controls. FINDINGS: Analysis of the lipidomes enabled separation of the studied chronic inflammatory diseases from controls based on independent validation test set classification performance (CVD vs control - Sensitivity: 0.94, Specificity: 0.88; IS vs control - Sensitivity: 1.0, Specificity: 1.0; SLE vs control – Sensitivity: 1, Specificity: 0.93) and from each other (SLE vs CVD ‒ Sensitivity: 0.91, Specificity: 1; IS vs SLE - Sensitivity: 1, Specificity: 0.82). Preliminary linear discriminant analysis plots using all data clearly separated the clinical groups from each other and from the controls, and partially separated CVD severities, as classified into five clinical groups. Dysregulated lipids are partially but not fully counterbalanced by statin treatment. INTERPRETATION: Dysregulation of the plasma lipidome is characteristic of chronic inflammatory diseases. Lipid profiling accurately identifies the diseases and in the case of CVD also identifies sub-classes. FUNDING: Full list of funding sources at the end of the manuscript. Elsevier 2021-07-24 /pmc/articles/PMC8330692/ /pubmed/34311325 http://dx.doi.org/10.1016/j.ebiom.2021.103504 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research paper Matthiesen, Rune Lauber, Chris Sampaio, Julio L. Domingues, Neuza Alves, Liliana Gerl, Mathias J. Almeida, Manuel S. Rodrigues, Gustavo Araújo Gonçalves, Pedro Ferreira, Jorge Borbinha, Cláudia Pedro Marto, João Neves, Marisa Batista, Frederico Viana-Baptista, Miguel Alves, Jose Simons, Kai Vaz, Winchil L.C. Vieira, Otilia V. Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases |
title | Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases |
title_full | Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases |
title_fullStr | Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases |
title_full_unstemmed | Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases |
title_short | Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases |
title_sort | shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases |
topic | Research paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8330692/ https://www.ncbi.nlm.nih.gov/pubmed/34311325 http://dx.doi.org/10.1016/j.ebiom.2021.103504 |
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