Characterizing the Extended Language Network in Individuals with Multiple Sclerosis

Background Cognitive impairment is a pervasive, functionally limiting symptom of multiple sclerosis (MS), a disease of the central nervous system that is the most common non-traumatic cause of neurologic disability in young adults. Recently, language dysfunction has received increased attention as a prevalent and early affected cognitive domain in individuals with MS. Objectives To establish a network-level model of language dysfunction in MS. Methods Cognitive data and 3T structural and functional brain magnetic resonance imaging (MRI) scans were acquired from 54 MS patients and 54 healthy controls (HCs). Summary measures of the extended language network (ELN) and structural imaging metrics were calculated. Group differences in ELN summary measures were evaluated. Associations between ELN summary measures and language performance were assessed in both groups; in the MS group, a two-step regression analysis was applied to assess relationships between additional language-specific imaging measures and language performance. Results In comparison to the HC group, the MS group performed significantly worse on the semantic fluency and rapid automized naming tests ( p < 0.005). Concerning the ELN summary measures, the MS group exhibited higher within-ELN connectivity than the HCs (0.11 ± 0.02 vs. 0.10 ± 0.01, p < 0.05, respectively). While no significant relationships between ELN summary measures and language function were observed in either group, the regression analysis identified a set of 17 imaging features that predicted performance on the rapid automized naming test ( p < 0.05) and identified key white matter tracts predicting language function in individuals with MS. Conclusion The derived functional network-level measures, combined with the identified structural neuroimaging metrics, constitute a comprehensive set of imaging features to characterize language dysfunction in MS. Further studies leveraging these features may uncover underlying mechanisms and clinically relevant predictors of language dysfunction, potentially leading to improved precision treatment strategies for cognitively impaired patients with multiple sclerosis. ### Competing Interest Statement Disclosure: VML has been compensated for advisory or consulting services by the following entities in the last year: Novartis, Biogen. CSR has been compensated for advisory or consulting services by the following entities in the last year: EMD Serono, TG Therapeutics, Horizon, Novartis, Viracta, Genentech. ASR has nothing to disclose. JDD has nothing to disclose. KB has nothing to disclose.LS has nothing to disclose. ### Funding Statement This study was funded by the United States Department of Defense Congressionally Directed Medical Research Program (W81XWH-20-1-0503). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee/IRB of Columbia University Medical Center gave ethical approval for this work I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Reach out to corresponding author for requests regarding data availability.