Journal Article

FZJ-2026-05598

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Brain age gap in multiple sclerosis: associated with disability but independent of serum biomarkers

Pawlitzki, M. (Corresponding author) ; Kirschner, P. ; Masanneck, L. ; Hagler, R. ; Meier, E. ; Vach, M. ; Inojosa, H. ; Ziemssen, T. ; Ivan, V. L. ; More, S. ; Patil, K.FZJ* ; Firouzi-Memarpuri, P. ; Caspers, J. ; Repple, J. ; Dannlowski, U. ; Khalil, M. ; Meuth, S. G. ; Rubbert, C.

2026
Sage London [u.a.]

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Please use a persistent id in citations: doi:10.1177/17562864261458516  doi:10.34734/FZJ-2026-05598

Abstract: Background:Multiple sclerosis (MS) is influenced by age-related brain alterations and affects cellular aging mechanisms. Machine-learning models can estimate brain-predicted age from magnetic resonance imaging (MRI) to quantify these aging-related changes.Objectives:This study examines whether the difference between predicted and chronological age (BrainAGE) relates to clinical disability and biomarkers of neuro-axonal injury in MS.Design:This study analyzed brain-predicted age from structural 3D T1-weighted MRI in 82 patients with relapsing MS enrolled in three prospective clinical trials and 30 healthy controls.Methods:BrainAGE, calculated as MRI-predicted minus chronological age, was correlated with the Expanded Disability Status Scale (EDSS), MS Functional Composite subtests, and serum neurofilament light chain and glial fibrillary acidic protein.

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Contributing Institute(s):

1. Gehirn & Verhalten (INM-7)

Research Program(s):

1. 5251 - Multilevel Brain Organization and Variability (POF4-525) (POF4-525)

Appears in the scientific report 2026

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Database coverage:
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