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

TitleClassification of multiple sclerosis based on patterns of CNS regional atrophy covariance.
Publication TypeJournal Article
Year of Publication2021
AuthorsTsagkas C, Parmar K, Pezold S, Barro C, Chakravarty MM, Gaetano L, Naegelin Y, Amann M, Papadopoulou A, Wuerfel J, Kappos L, Kuhle J, Sprenger T, Granziera C, Magon S
JournalHum Brain Mapp
Volume42
Issue8
Pagination2399-2415
Date Published2021 Jun 01
ISSN1097-0193
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.

DOI10.1002/hbm.25375
Alternate JournalHum Brain Mapp
PubMed ID33624390
PubMed Central IDPMC8090784
Grant ListE!113682 / / H2020 European Research Council /
320030_156860 / / Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung /
P400PM_191077 / / Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung /
PP00P3_176984 / / Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung /
/ / Stiftung zur Förderung der gastroenterologischen und allgemeinen klinischen Forschung /