Circulating cell-free DNA methylation profiles as candidate noninvasive multiple sclerosis biomarkers

In multiple sclerosis (MS), there is a critical need for cost-effective blood biomarkers that can concurrently classify disease subtypes, monitor disability severity, and predict long-term disability progression. In this proof-of-concept study, we performed low-coverage whole-genome bisulfite sequencing (WGBS) on 75 plasma cell-free DNA (cfDNA) samples collected from a prospective clinic cohort with longitudinal disability outcomes. We assessed the utility of cfDNA methylation profiles for differentiating MS patients from controls, classifying MS subtypes, estimating disability severity, and predicting disease trajectories. We identify hundreds of differentially methylated regions (DMRs) that significantly distinguish MS from controls, separate MS subtypes, and stratify disability severity levels. These DMRs are highly enriched in immunologically and neurologically relevant cis-regulatory elements and in motifs associated with neuronal function and T-cell differentiation. To distinguish MS subtypes and disability severity, models using DMRs achieve area-under-the-curve (AUC) values ranging from 0.75 to 0.95, and models using inferred tissue-of-origin patterns from cfDNA methylation achieve AUC values of 0.69 to 0.72, performing better than historical benchmark neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) measures in the same cohort. Finally, a linear mixed-effects model identifies “prognostic regions” where baseline cfDNA methylation levels are associated with subsequent disability progression and predict future disability severity (AUC = 0.74) within a 3-year evaluation window. Using these prognostic regions, we generate a cfDNA methylation-based progression risk score and stratify patient groups by differential progression risks. These findings highlight circulating cfDNA methylation profiles as promising clinical MS biomarkers, warranting future validation using higher-depth WGBS data. Multiple sclerosis (MS) is a disabling disease that damages cells in the brain and spinal cord. When these cells die, small pieces of DNA enter the bloodstream, carrying biochemical signatures about the tissue of origin and their behavior. In this early-stage study, we analyzed blood samples from 75 people to address the lack of reliable blood tests for predicting how MS will progress. We found blood markers that can distinguish MS subtypes, monitor current disability levels, and help predict future worsening. We will refine our approach and confirm the findings in more patients. If confirmed, these blood tests could help tailor treatment and improve care for people with MS. Fu et al. profile plasma cfDNA methylation in MS using low-coverage whole-genome bisulfite sequencing to classify subtypes, disability severity, and predict progression. They find that methylation profiles distinguish MS states with reasonable accuracy, and identify prognostic regions predicting 3-year disability progression.