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Brain age as a surrogate marker for cognitive performance in multiple sclerosis.
Stijn Denissen1,2, Denis Alexander Engemann3,4, Alexander De Cock1
1AIMS Lab, Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Brussels, Belgium.
European Journal of Neurology
|June 23, 2022
Summary
Brain age, estimated from neuroimaging, shows potential as a biomarker for cognitive decline in multiple sclerosis (MS). A younger brain age correlates with better cognitive performance in MS patients.
Area of Science:
- Neuroimaging
- Biomarker Discovery
- Cognitive Neuroscience
Background:
- Neuroimaging techniques enable estimation of brain age, offering a relatable metric for brain health communication.
- Brain age, representing 'how old the brain looks,' has potential clinical utility.
Purpose of the Study:
- To investigate the clinical utility of brain age estimation.
- To examine the relationship between brain age and cognitive performance in multiple sclerosis (MS).
Main Methods:
- A linear regression model trained on healthy controls predicted brain age from MRI volumetric features and sex.
- Brain-predicted age difference (BPAD) calculated as brain age minus chronological age.
- Cognitive performance assessed using the Symbol Digit Modalities Test (SDMT).
Main Results:
- Brain age was significantly associated with SDMT scores in the MS cohort (r = -0.46, p < 0.001).
- Brain age uniquely explained variance in SDMT performance beyond chronological age.
- A significant correlation was found between BPAD and SDMT (r = -0.24, p < 0.001).
Conclusions:
- Brain age is a potential biomarker for cognitive dysfunction in MS.
- Brain age serves as an easily understandable metric for brain health.
