Proteomic signatures of physical, cognitive, and imaging outcomes in multiple sclerosis.


Journal

Annals of clinical and translational neurology
ISSN: 2328-9503
Titre abrégé: Ann Clin Transl Neurol
Pays: United States
ID NLM: 101623278

Informations de publication

Date de publication:
17 Jan 2024
Historique:
revised: 21 12 2023
received: 30 08 2023
accepted: 25 12 2023
medline: 18 1 2024
pubmed: 18 1 2024
entrez: 18 1 2024
Statut: aheadofprint

Résumé

A quantitative measurement of serum proteome biomarkers that would associate with disease progression endpoints can provide risk stratification for persons with multiple sclerosis (PwMS) and supplement the clinical decision-making process. In total, 202 PwMS were enrolled in a longitudinal study with measurements at two time points with an average follow-up time of 5.4 years. Clinical measures included the Expanded Disability Status Scale, Timed 25-foot Walk, 9-Hole Peg, and Symbol Digit Modalities Tests. Subjects underwent magnetic resonance imaging to determine the volumetric measures of the whole brain, gray matter, deep gray matter, and lateral ventricles. Serum samples were analyzed using a custom immunoassay panel on the Olink™ platform, and concentrations of 18 protein biomarkers were measured. Linear mixed-effects models and adjustment for multiple comparisons were performed. Subjects had a significant 55.6% increase in chemokine ligand 20 (9.7 pg/mL vs. 15.1 pg/mL, p < 0.001) and neurofilament light polypeptide (10.5 pg/mL vs. 11.5 pg/mL, p = 0.003) at the follow-up time point. Additional changes in CUB domain-containing protein 1, Contactin 2, Glial fibrillary acidic protein, Myelin oligodendrocyte glycoprotein, and Osteopontin were noted but did not survive multiple comparison correction. Worse clinical performance in the 9-HPT was associated with neurofilament light polypeptide (p = 0.001). Increases in several biomarker candidates were correlated with greater neurodegenerative changes as measured by different brain volumes. Multiple proteins, selected from a disease activity test that represent diverse biological pathways, are associated with physical, cognitive, and radiographic outcomes. Future studies should determine the utility of multiple protein assays in routine clinical care.

Sections du résumé

BACKGROUND BACKGROUND
A quantitative measurement of serum proteome biomarkers that would associate with disease progression endpoints can provide risk stratification for persons with multiple sclerosis (PwMS) and supplement the clinical decision-making process.
MATERIALS AND METHODS METHODS
In total, 202 PwMS were enrolled in a longitudinal study with measurements at two time points with an average follow-up time of 5.4 years. Clinical measures included the Expanded Disability Status Scale, Timed 25-foot Walk, 9-Hole Peg, and Symbol Digit Modalities Tests. Subjects underwent magnetic resonance imaging to determine the volumetric measures of the whole brain, gray matter, deep gray matter, and lateral ventricles. Serum samples were analyzed using a custom immunoassay panel on the Olink™ platform, and concentrations of 18 protein biomarkers were measured. Linear mixed-effects models and adjustment for multiple comparisons were performed.
RESULTS RESULTS
Subjects had a significant 55.6% increase in chemokine ligand 20 (9.7 pg/mL vs. 15.1 pg/mL, p < 0.001) and neurofilament light polypeptide (10.5 pg/mL vs. 11.5 pg/mL, p = 0.003) at the follow-up time point. Additional changes in CUB domain-containing protein 1, Contactin 2, Glial fibrillary acidic protein, Myelin oligodendrocyte glycoprotein, and Osteopontin were noted but did not survive multiple comparison correction. Worse clinical performance in the 9-HPT was associated with neurofilament light polypeptide (p = 0.001). Increases in several biomarker candidates were correlated with greater neurodegenerative changes as measured by different brain volumes.
CONCLUSION CONCLUSIONS
Multiple proteins, selected from a disease activity test that represent diverse biological pathways, are associated with physical, cognitive, and radiographic outcomes. Future studies should determine the utility of multiple protein assays in routine clinical care.

Identifiants

pubmed: 38234075
doi: 10.1002/acn3.51996
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.

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Auteurs

Kian Jalaleddini (K)

Octave Biosciences, Menlo Park, California, USA.

Dejan Jakimovski (D)

Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.

Anisha Keshavan (A)

Octave Biosciences, Menlo Park, California, USA.

Shannon McCurdy (S)

Octave Biosciences, Menlo Park, California, USA.

Kelly Leyden (K)

Octave Biosciences, Menlo Park, California, USA.

Ferhan Qureshi (F)

Octave Biosciences, Menlo Park, California, USA.

Atiyeh Ghoreyshi (A)

Octave Biosciences, Menlo Park, California, USA.

Niels Bergsland (N)

Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.

Michael G Dwyer (MG)

Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.

Murali Ramanathan (M)

Department of Pharmaceutical Sciences, State University of New York, Buffalo, Buffalo, New York, USA.

Bianca Weinstock-Guttman (B)

Jacobs MS Center, Department of Neurology, Jacobs School of Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.

Ralph Hb Benedict (RH)

Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.

Robert Zivadinov (R)

Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA.
Center for Biomedical Imaging at the Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, New York, USA.

Classifications MeSH