Multimodal predictors of disability progression and processing speed decline in relapsing-remitting multiple sclerosis

The underlying mechanisms for neurodegeneration in multiple sclerosis are complex and incompletely understood. Multivariate and multimodal investigations integrating demographic, clinical, multi-omics, and neuroimaging data provide opportunities for nuanced analyses, aimed to define disease progression markers. We used data from a 12-year longitudinal multicenter cohort of 88 people with multiple sclerosis, to test the predictive value of multi-omics, T ₁ -weighted MRI (lesion count and volume, lesion-filled brain-predicted age), clinical examinations, self-reports on quality of life, demographics, and general health-related variables for future functional and cognitive disability. Systematic increases in Expanded Disability Status Scale (EDSS) scores were used to stratify a progressive disability group (PDG) from relatively stabile disability. A processing speed decline group (PSDG) was defined by a ≥20% decrease from the maximum (cognitive) Paced Auditory Serial Addition Test score. We used a multiverse approach to identify which baseline variables were most predictive for PDG and PSDG memberships, considering multiple analysis paths.

Future disability (median area under the curve: mAUC=0.83±0.04, median Brier score: mBS=0.16±0.02) and the loss of processing speed (mAUC=0.89±0.05, mBS=0.10±0.03) could be successfully classified across models. Varibles significantly (median p-values<0.05) predicting stable disability included receiving disease modifying treatment at 12-year follow-up (median Odds Ratio: mOR _PDG =7.44±4.07, p _median =0.013, proportion of the OR’s directionality: PORSD=100%), lower baseline EDSS for each 1-unit (mOR _PDG =0.25±0.11, p _median =0.013, PORSD=100%), and counter-intuitively every year increase in baseline age (mOR _PDG =1.12±0.04, p _median =0.020, PORSD=100%), and lower vitamin A per 1 umol/L (mOR _PDG =0.10±0.05, p _median =0.016, PORSD=99.7%) and D levels per 1 nmol/L (mOR _PDG =0.95±0.02, p _median =0.025, PORSD=100%). Variables significantly predicting stable processing speed were receiving disease modifying treatment at 12-year follow-up (mOR _PSDG =0.10±0.08, p _median =0.013, PORSD=100%) and baseline PASAT score (mOR _PSDG =0.86±0.03, p _median =0.005, PORSD=99.73%). These findings were supported by an additional simulation study.

Concordant with the literature, disease modifying treatments influence disability progression, as well as a higher EDSS and PASAT scores at measurement start. Experimental and counterintuitive findings on vitamin A and D levels require further validation. The large variability across models suggests a strong influence of analytic flexibility, such as the selection of covariates.