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

Tsagkas, Charidimos and Parmar, Katrin and Pezold, Simon and Barro, Christian and Chakravarty, Mallar M. and Gaetano, Laura and Naegelin, Yvonne and Amann, Michael and Papadopoulou, Athina and Wuerfel, Jens and Kappos, Ludwig and Kuhle, Jens and Sprenger, Till and Granziera, Cristina and Magon, Stefano. (2021) Classification of multiple sclerosis based on patterns of CNS regional atrophy covariance. Human brain mapping, 42 (8). pp. 2399-2415.

Full text not available from this repository.

Official URL: https://edoc.unibas.ch/84565/

Downloads: Statistics Overview


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.
Faculties and Departments:03 Faculty of Medicine
UniBasel Contributors:Tsagkas, Charidimos
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Wiley Periodicals LLC
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:28 Jan 2022 15:16
Deposited On:28 Jan 2022 15:16

Repository Staff Only: item control page