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UCL-Led Study Identifies Two Biological MS Subtypes

The Brain paper pairs routine MRI with the sNfL blood marker via a machine-learning model to point toward more personalized monitoring pending further validation.

Overview

  • Researchers from University College London and Queen Square Analytics analyzed MRI scans and serum neurofilament light chain measurements from about 600 people with MS using the SuStaIn model.
  • The approach identified two distinct trajectories named early-sNfL and late-sNfL that are defined by different patterns in biomarkers and brain anatomy.
  • Early-sNfL features high sNfL early in the disease with corpus callosum damage and rapid lesion development, suggesting more aggressive activity.
  • Late-sNfL shows early cortical and deep grey matter atrophy with a later rise in sNfL, indicating slower progression with overt damage occurring later.
  • Authors and the MS Society say the findings could guide more tailored treatment and monitoring, though adoption in clinics will require replication and prospective testing.