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Matthiesen R, Lauber C, Sampaio JL, Domingues N, Alves L, Gerl MJ, Almeida MS, Rodrigues G, Araújo Gonçalves P, Ferreira J, Borbinha C, Pedro Marto J, Neves M, Batista F, Viana-Baptista M, Alves J, Simons K, Vaz WLC, Vieira OV. Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases. EBioMedicine 2021; 70:103504. [PMID: 34311325 PMCID: PMC8330692 DOI: 10.1016/j.ebiom.2021.103504] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 06/12/2021] [Accepted: 07/12/2021] [Indexed: 12/19/2022] Open
Abstract
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.
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Affiliation(s)
- Rune Matthiesen
- iNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, Portugal.
| | - Chris Lauber
- Lipotype GmbH, Tatzberg 47, 01307 Dresden, Germany
| | | | - Neuza Domingues
- iNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, Portugal
| | - Liliana Alves
- iNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, Portugal
| | | | - Manuel S Almeida
- iNOVA4Health, 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, Portugal
| | - Gustavo Rodrigues
- Hospital Santa Cruz, Centro Hospitalar de Lisboa Ocidental, Av. Prof. Dr. Reinaldo dos Santos, 2790-134 Carnaxide, Portugal
| | - Pedro Araújo Gonçalves
- iNOVA4Health, 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, Portugal
| | - Jorge Ferreira
- Hospital Santa Cruz, Centro Hospitalar de Lisboa Ocidental, Av. Prof. Dr. Reinaldo dos Santos, 2790-134 Carnaxide, Portugal
| | - Cláudia Borbinha
- Department of Neurology, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Rua da Junqueira 126 1349-019 Lisboa, Portugal
| | - João Pedro Marto
- Department of Neurology, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Rua da Junqueira 126 1349-019 Lisboa, Portugal
| | - Marisa Neves
- Hospital Dr. Fernando da Fonseca, IC 19, 2720-276 Amadora, Portugal
| | | | - Miguel Viana-Baptista
- Department of Neurology, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Rua da Junqueira 126 1349-019 Lisboa, Portugal
| | - Jose Alves
- Hospital Dr. Fernando da Fonseca, IC 19, 2720-276 Amadora, Portugal
| | - Kai Simons
- Lipotype GmbH, Tatzberg 47, 01307 Dresden, Germany
| | - Winchil L C Vaz
- iNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, Portugal
| | - Otilia V Vieira
- iNOVA4Health, CEDOC, NOVA Medical School, NMS, Universidade Nova de Lisboa, 1169-056 Lisboa, Portugal.
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