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...

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Main Authors: Rune Matthiesen, Chris Lauber, Julio L. Sampaio, Neuza Domingues, Liliana Alves, Mathias J. Gerl, Manuel S. Almeida, Gustavo Rodrigues, Pedro Araújo Gonçalves, Jorge Ferreira, Cláudia Borbinha, João Pedro Marto, Marisa Neves, Frederico Batista, Miguel Viana-Baptista, Jose Alves, Kai Simons, Winchil L.C. Vaz, Otilia V. Vieira
Format: Article
Language:English
Published: Elsevier 2021-08-01
Series:EBioMedicine
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396421002978
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author Rune Matthiesen
Chris Lauber
Julio L. Sampaio
Neuza Domingues
Liliana Alves
Mathias J. Gerl
Manuel S. Almeida
Gustavo Rodrigues
Pedro Araújo Gonçalves
Jorge Ferreira
Cláudia Borbinha
João Pedro Marto
Marisa Neves
Frederico Batista
Miguel Viana-Baptista
Jose Alves
Kai Simons
Winchil L.C. Vaz
Otilia V. Vieira
spellingShingle Rune Matthiesen
Chris Lauber
Julio L. Sampaio
Neuza Domingues
Liliana Alves
Mathias J. Gerl
Manuel S. Almeida
Gustavo Rodrigues
Pedro Araújo Gonçalves
Jorge Ferreira
Cláudia Borbinha
João Pedro Marto
Marisa Neves
Frederico Batista
Miguel Viana-Baptista
Jose Alves
Kai Simons
Winchil L.C. Vaz
Otilia V. Vieira
Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases
EBioMedicine
Vascular diseases
Systemic lupus erythematosus
Dyslipidemia
Lipid profiling
Lipid biomarker
author_facet Rune Matthiesen
Chris Lauber
Julio L. Sampaio
Neuza Domingues
Liliana Alves
Mathias J. Gerl
Manuel S. Almeida
Gustavo Rodrigues
Pedro Araújo Gonçalves
Jorge Ferreira
Cláudia Borbinha
João Pedro Marto
Marisa Neves
Frederico Batista
Miguel Viana-Baptista
Jose Alves
Kai Simons
Winchil L.C. Vaz
Otilia V. Vieira
author_sort Rune Matthiesen
title 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_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_sort shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases
publisher Elsevier
series EBioMedicine
issn 2352-3964
publishDate 2021-08-01
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.
topic Vascular diseases
Systemic lupus erythematosus
Dyslipidemia
Lipid profiling
Lipid biomarker
url http://www.sciencedirect.com/science/article/pii/S2352396421002978
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spelling doaj-e9aac57fdb384057a77778ba3f4739ca2021-07-25T04:43:34ZengElsevierEBioMedicine2352-39642021-08-0170103504Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseasesRune Matthiesen0Chris Lauber1Julio L. Sampaio2Neuza Domingues3Liliana Alves4Mathias J. Gerl5Manuel S. Almeida6Gustavo Rodrigues7Pedro Araújo Gonçalves8Jorge Ferreira9Cláudia Borbinha10João Pedro Marto11Marisa Neves12Frederico Batista13Miguel Viana-Baptista14Jose Alves15Kai Simons16Winchil L.C. Vaz17Otilia V. Vieira18iNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, Portugal; Corresponding authors.Lipotype GmbH, Tatzberg 47, 01307 Dresden, GermanyLipotype GmbH, Tatzberg 47, 01307 Dresden, GermanyiNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, PortugaliNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, PortugalLipotype GmbH, Tatzberg 47, 01307 Dresden, GermanyiNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, Portugal; Hospital Santa Cruz, Centro Hospitalar de Lisboa Ocidental, Av. Prof. Dr. Reinaldo dos Santos, 2790-134 Carnaxide, PortugalHospital Santa Cruz, Centro Hospitalar de Lisboa Ocidental, Av. Prof. Dr. Reinaldo dos Santos, 2790-134 Carnaxide, PortugaliNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, Portugal; Hospital Santa Cruz, Centro Hospitalar de Lisboa Ocidental, Av. Prof. Dr. Reinaldo dos Santos, 2790-134 Carnaxide, PortugalHospital Santa Cruz, Centro Hospitalar de Lisboa Ocidental, Av. Prof. Dr. Reinaldo dos Santos, 2790-134 Carnaxide, PortugalDepartment of Neurology, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Rua da Junqueira 126 1349-019 Lisboa, PortugalDepartment of Neurology, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Rua da Junqueira 126 1349-019 Lisboa, PortugalHospital Dr. Fernando da Fonseca, IC 19, 2720-276 Amadora, PortugalHospital Dr. Fernando da Fonseca, IC 19, 2720-276 Amadora, PortugalDepartment of Neurology, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Rua da Junqueira 126 1349-019 Lisboa, PortugalHospital Dr. Fernando da Fonseca, IC 19, 2720-276 Amadora, PortugalLipotype GmbH, Tatzberg 47, 01307 Dresden, GermanyiNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, PortugaliNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, Portugal; Corresponding authors.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.http://www.sciencedirect.com/science/article/pii/S2352396421002978Vascular diseasesSystemic lupus erythematosusDyslipidemiaLipid profilingLipid biomarker