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Multimodal predictors of disability progression and processing speed decline in relapsing-remitting multiple
Max Korbmacher1,2,3, Ingrid Anne Lie4, Kristin Wesnes5
1Department for Radiography, Western Norway University of Applied Sciences, Bergen, Norway. max.korbmacher@hvl.no.
Scientific Reports
|October 16, 2025
Summary
This study predicts multiple sclerosis disability progression using multi-omics and neuroimaging. Disease-modifying treatments and baseline factors like age and vitamin levels influence outcomes, highlighting areas for further research.
Area of Science:
- Neuroscience
- Immunology
- Biostatistics
Background:
- Multiple sclerosis (MS) neurodegeneration mechanisms are complex and not fully understood.
- Multivariate and multimodal data integration offers insights into disease progression markers.
Purpose of the Study:
- To predict future functional and cognitive disability in MS using diverse baseline data.
- To identify key predictors for progressive disability and processing speed decline.
Main Methods:
- Longitudinal analysis of 88 MS patients over 12 years.
- Integration of multi-omics, neuroimaging (T1-weighted MRI), clinical data, and demographics.
- Multiverse approach to identify predictive variables for disability progression and processing speed decline.
Main Results:
- Accurate classification of future disability (mAUC = 0.83) and processing speed loss (mAUC = 0.89).
- Predictors for stable disability include disease-modifying treatment, lower baseline EDSS, higher age, and lower vitamin A/D levels.
- Predictors for stable processing speed include disease-modifying treatment and higher baseline PASAT scores.
Conclusions:
- Disease-modifying treatments significantly impact MS disability progression.
- Baseline EDSS, age, and vitamin levels are associated with future disability.
- Further validation is needed for the observed effects of vitamin A and D levels.
