New Enhancing MRI Lesions Associate with IL-17, Neutrophil Degranulation and Integrin Microparticles: Multi-Omics Combined with Frequent MRI in Multiple Sclerosis.

EV array IL-17 IL-1β MRI biomarker blood brain barrier coagulation complement endothelial stress enhancing lesion gadolinium mass spectrometry multiple sclerosis plasma

Journal

Biomedicines
ISSN: 2227-9059
Titre abrégé: Biomedicines
Pays: Switzerland
ID NLM: 101691304

Informations de publication

Date de publication:
28 Nov 2023
Historique:
received: 09 08 2023
revised: 16 11 2023
accepted: 24 11 2023
medline: 23 12 2023
pubmed: 23 12 2023
entrez: 23 12 2023
Statut: epublish

Résumé

Blood-barrier (BBB) breakdown and active inflammation are hallmarks of relapsing multiple sclerosis (RMS), but the molecular events contributing to the development of new lesions are not well explored. Leaky endothelial junctions are associated with increased production of endothelial-derived extracellular microvesicles (EVs) and result in the entry of circulating immune cells into the brain. MRI with intravenous gadolinium (Gd) can visualize acute blood-barrier disruption as the initial event of the evolution of new lesions. Here, weekly MRI with Gd was combined with proteomics, multiplex immunoassay, and endothelial stress-optimized EV array to identify early markers related to BBB disruption. Five patients with RMS with no disease-modifying treatment were monitored weekly using high-resolution 3T MRI scanning with intravenous gadolinium (Gd) for 8 weeks. Patients were then divided into three groups (low, medium, or high MRI activity) defined by the number of new, total, and maximally enhancing Gd-enhancing lesions and the number of new FLAIR lesions. Plasma samples taken at each MRI were analyzed for protein biomarkers of inflammation by quantitative proteomics, and cytokines using multiplex immunoassays. EVs were characterized with an optimized endothelial stress EV array based on exosome surface protein markers for the detection of soluble secreted EVs. Proteomics analysis of plasma yielded quantitative information on 208 proteins at each patient time point ( Combination of serial frequent MRI with proteome, neuroinflammation markers, and protein array data of EVs enabled assessment of temporal changes in inflammation and endothelial dysfunction in RMS related to the evolution of new and enhancing lesions. Particularly, the Th17 pathway and IL-1β clustered and correlated with new lesions and Gd enhancement, indicating their importance in BBB disruption and initiating acute brain inflammation in MS. In addition to the Th17 pathway, abundant protein changes between MRI activity groups suggested the role of EVs and the coagulation system along with innate immune responses including acute phase proteins, complement components, and neutrophil degranulation.

Sections du résumé

BACKGROUND BACKGROUND
Blood-barrier (BBB) breakdown and active inflammation are hallmarks of relapsing multiple sclerosis (RMS), but the molecular events contributing to the development of new lesions are not well explored. Leaky endothelial junctions are associated with increased production of endothelial-derived extracellular microvesicles (EVs) and result in the entry of circulating immune cells into the brain. MRI with intravenous gadolinium (Gd) can visualize acute blood-barrier disruption as the initial event of the evolution of new lesions.
METHODS METHODS
Here, weekly MRI with Gd was combined with proteomics, multiplex immunoassay, and endothelial stress-optimized EV array to identify early markers related to BBB disruption. Five patients with RMS with no disease-modifying treatment were monitored weekly using high-resolution 3T MRI scanning with intravenous gadolinium (Gd) for 8 weeks. Patients were then divided into three groups (low, medium, or high MRI activity) defined by the number of new, total, and maximally enhancing Gd-enhancing lesions and the number of new FLAIR lesions. Plasma samples taken at each MRI were analyzed for protein biomarkers of inflammation by quantitative proteomics, and cytokines using multiplex immunoassays. EVs were characterized with an optimized endothelial stress EV array based on exosome surface protein markers for the detection of soluble secreted EVs.
RESULTS RESULTS
Proteomics analysis of plasma yielded quantitative information on 208 proteins at each patient time point (
CONCLUSIONS CONCLUSIONS
Combination of serial frequent MRI with proteome, neuroinflammation markers, and protein array data of EVs enabled assessment of temporal changes in inflammation and endothelial dysfunction in RMS related to the evolution of new and enhancing lesions. Particularly, the Th17 pathway and IL-1β clustered and correlated with new lesions and Gd enhancement, indicating their importance in BBB disruption and initiating acute brain inflammation in MS. In addition to the Th17 pathway, abundant protein changes between MRI activity groups suggested the role of EVs and the coagulation system along with innate immune responses including acute phase proteins, complement components, and neutrophil degranulation.

Identifiants

pubmed: 38137391
pii: biomedicines11123170
doi: 10.3390/biomedicines11123170
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Scleroseforeningen
ID : A25341

Auteurs

Zsolt Illes (Z)

Department of Neurology, Odense University Hospital, 5000 Odense, Denmark.
Department of Clinical Medicine, University of Southern Denmark, 5230 Odense, Denmark.
Institute of Molecular Medicine, University of Southern Denmark, 5230 Odense, Denmark.
Brain Research-Inter Disciplinary Guided Excellence (BRIDGE), University of Southern Denmark, 5230 Odense, Denmark.

Malene Møller Jørgensen (MM)

Department of Clinical Immunology, Aalborg University Hospital, 9220 Aalborg, Denmark.

Rikke Bæk (R)

Department of Clinical Immunology, Aalborg University Hospital, 9220 Aalborg, Denmark.

Lisa-Marie Bente (LM)

Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, 38106 Braunschweig, Germany.
Braunschweig Integrated Centre for Systems Biology (BRICS), TU Braunschweig, 38106 Braunschweig, Germany.

Jørgen T Lauridsen (JT)

Department of Business and Economics, University of Southern Denmark, 5230 Odense, Denmark.

Kirsten H Hyrlov (KH)

Department of Neurology, Odense University Hospital, 5000 Odense, Denmark.

Christopher Aboo (C)

Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark.
Sino-Danish Center for Education and Research, University of Chinese Academy of Sciences, 101408 Beijing, China.

Jan Baumbach (J)

Department of Mathematics and Computer Science, University of Southern Denmark, 5230 Odense, Denmark.
Institute for Computational Systems Biology, University of Hamburg, 20148 Hamburg, Germany.

Tim Kacprowski (T)

Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, 38106 Braunschweig, Germany.
Braunschweig Integrated Centre for Systems Biology (BRICS), TU Braunschweig, 38106 Braunschweig, Germany.

Francois Cotton (F)

Service de Radiologie, Centre Hospitalier Lyon-Sud, France/CREATIS, Université de Lyon, 69007 Lyon, France.

Charles R G Guttmann (CRG)

Center for Neurological Imaging, Brigham and Women's Hospital, Boston, MA 02115, USA.

Allan Stensballe (A)

Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark.
Clinical Cancer Center, Aalborg University Hospital, 9220 Aalborg, Denmark.

Classifications MeSH