Classification of multiple sclerosis based on patterns of CNS regional atrophy covariance

Charidimos Tsagkas, Katrin Parmar, Simon Pezold, Christian Barro, Mallar M. Chakravarty, Laura Gaetano, Yvonne Naegelin, Michael Amann, Athina Papadopoulou, Jens Wuerfel, Ludwig Kappos, Jens Kuhle, Till Sprenger, Cristina Granziera, Stefano Magon

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

There is evidence that multiple sclerosis (MS) pathology leads to distinct patterns of volume loss over time (VLOT) in different central nervous system (CNS) structures. We aimed to use such patterns to identify patient subgroups. MS patients of all classical disease phenotypes underwent annual clinical, blood, and MRI examinations over 6 years. Spinal, striatal, pallidal, thalamic, cortical, white matter, and T2-weighted lesion volumes as well as serum neurofilament light chain (sNfL) were quantified. CNS VLOT patterns were identified using principal component analysis and patients were classified using hierarchical cluster analysis. 225 MS patients were classified into four distinct Groups A, B, C, and D including 14, 59, 141, and 11 patients, respectively). These groups did not differ in baseline demographics, disease duration, disease phenotype distribution, and lesion-load expansion. Interestingly, Group A showed pronounced spinothalamic VLOT, Group B marked pallidal VLOT, Group C small between-structure VLOT differences, and Group D myelocortical volume increase and pronounced white matter VLOT. Neurologic deficits were more severe and progressed faster in Group A that also had higher mean sNfL levels than all other groups. Group B experienced more frequent relapses than Group C. In conclusion, there are distinct patterns of VLOT across the CNS in MS patients, which do not overlap with clinical MS subtypes and are independent of disease duration and lesion-load but are partially associated to sNfL levels, relapse rates, and clinical worsening. Our findings support the need for a more biologic classification of MS subtypes including volumetric and body-fluid markers.

Original languageEnglish
Pages (from-to)2399-2415
Number of pages17
JournalHuman Brain Mapping
Volume42
Issue number8
DOIs
StatePublished - 1 Jun 2021
Externally publishedYes

Keywords

  • MRI
  • atrophy
  • biomarkers
  • classification
  • demyelinating autoimmune diseases
  • multiple sclerosis
  • neurodegeneration

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