TY - JOUR
T1 - Dynamic functional connectivity as a neural correlate of fatigue in multiple sclerosis
AU - Tijhuis, Floris B.
AU - Broeders, Tommy A.A.
AU - Santos, Fernando A.N.
AU - Schoonheim, Menno M.
AU - Killestein, Joep
AU - Leurs, Cyra E.
AU - van Geest, Quinten
AU - Steenwijk, Martijn D.
AU - Geurts, Jeroen J.G.
AU - Hulst, Hanneke E.
AU - Douw, Linda
N1 - Funding Information: We would like to thank Julia Jelgerhuis for her assistance in the execution of this project. Funding: This study was funded by Novartis. F.B. Tijhuis, T.A.A. Broeders, F.A.N. Santos, C.E. Leurs, Q. van Geest, and L. Douw report no disclosures. M.M. Schoonheim serves on the editorial board of Frontiers in Neurology, receives research support from the Dutch MS Research Foundation and has served as a consultant for or received research support from Biogen, Celgene, Genzyme, MedDay and Merck. J. Killestein has accepted speaker and consulting fees from Merck, Biogen, Roche, Teva, Genzyme and Novartis. J.J.G. Geurts is an editor of MS journal and serves on the editorial boards of Neurology and Frontiers of Neurology and is president of the Netherlands organization for health research and innovation and has served as a consultant for Merck-Serono, Biogen, Novartis, Genzyme and Teva Pharmaceuticals. H.E. Hulst has received compensation for consulting services or speaker honoraria from Celgene, Sanofi Genzyme, Merck Serono and Biogen Idec and serves on the editorial board of the Multiple Sclerosis Journal. Funding Information: Funding: This study was funded by Novartis. Publisher Copyright: © 2021 The Author(s) Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/1
Y1 - 2021/1
N2 - Background: More than 80% of multiple sclerosis (MS) patients experience symptoms of fatigue. MS-related fatigue is only partly explained by structural (lesions and atrophy) and functional (brain activation and conventional static functional connectivity) brain properties. Objectives: To investigate the relationship of dynamic functional connectivity (dFC) with fatigue in MS patients and to compare dFC with commonly used clinical and MRI parameters. Methods: In 35 relapsing-remitting MS patients (age: 42.83 years, female/male: 20/15, disease duration: 11 years) and 19 healthy controls (HCs) (age: 41.38 years, female/male: 11/8), fatigue was measured using the CIS-20r questionnaire at baseline and at 6-month follow-up. All subjects underwent structural and resting-state functional MRI at baseline. Global static functional connectivity (sFC) and dynamic functional connectivity (dFC) were calculated. dFC was assessed using a sliding-window approach by calculating the summed difference (diff) and coefficient of variation (cv) across windows. Moreover, regional connectivity between regions previously associated with fatigue in MS was estimated (i.e. basal ganglia and regions of the Default Mode Network (DMN): medial prefrontal, posterior cingulate and precuneal cortices). Hierarchical regression analyses were performed with forward selection to identify the most important correlates of fatigue at baseline. Results were not corrected for multiple testing due to the exploratory nature of the study. Results: Patients were more fatigued than HCs at baseline (p = 0.001) and follow-up (p = 0.002) and fatigue in patients was stable over time (p = 0.213). Patients had significantly higher baseline global dFC than HCs, but no difference in basal ganglia-DMN dFC. In the regression model for baseline fatigue in patients, basal ganglia-DMN dFC-cv (standardized β = -0.353) explained 12.5% additional variance on top of EDSS (p = 0.032). Post-hoc analysis revealed higher basal ganglia-DMN dFC-cv in non-fatigued patients compared to healthy controls (p = 0.013), whereas fatigued patients and healthy controls showed similar basal ganglia-DMN dFC. Conclusions: Less dynamic connectivity between the basal ganglia and the cortex is associated with greater fatigue in MS patients, independent of disability status. Within patients, lower dynamics of these connections could relate to lower efficiency and increased fatigue. Increased dynamics in non-fatigued patients compared to healthy controls might represent a network organization that protects against fatigue or signal early network dysfunction.
AB - Background: More than 80% of multiple sclerosis (MS) patients experience symptoms of fatigue. MS-related fatigue is only partly explained by structural (lesions and atrophy) and functional (brain activation and conventional static functional connectivity) brain properties. Objectives: To investigate the relationship of dynamic functional connectivity (dFC) with fatigue in MS patients and to compare dFC with commonly used clinical and MRI parameters. Methods: In 35 relapsing-remitting MS patients (age: 42.83 years, female/male: 20/15, disease duration: 11 years) and 19 healthy controls (HCs) (age: 41.38 years, female/male: 11/8), fatigue was measured using the CIS-20r questionnaire at baseline and at 6-month follow-up. All subjects underwent structural and resting-state functional MRI at baseline. Global static functional connectivity (sFC) and dynamic functional connectivity (dFC) were calculated. dFC was assessed using a sliding-window approach by calculating the summed difference (diff) and coefficient of variation (cv) across windows. Moreover, regional connectivity between regions previously associated with fatigue in MS was estimated (i.e. basal ganglia and regions of the Default Mode Network (DMN): medial prefrontal, posterior cingulate and precuneal cortices). Hierarchical regression analyses were performed with forward selection to identify the most important correlates of fatigue at baseline. Results were not corrected for multiple testing due to the exploratory nature of the study. Results: Patients were more fatigued than HCs at baseline (p = 0.001) and follow-up (p = 0.002) and fatigue in patients was stable over time (p = 0.213). Patients had significantly higher baseline global dFC than HCs, but no difference in basal ganglia-DMN dFC. In the regression model for baseline fatigue in patients, basal ganglia-DMN dFC-cv (standardized β = -0.353) explained 12.5% additional variance on top of EDSS (p = 0.032). Post-hoc analysis revealed higher basal ganglia-DMN dFC-cv in non-fatigued patients compared to healthy controls (p = 0.013), whereas fatigued patients and healthy controls showed similar basal ganglia-DMN dFC. Conclusions: Less dynamic connectivity between the basal ganglia and the cortex is associated with greater fatigue in MS patients, independent of disability status. Within patients, lower dynamics of these connections could relate to lower efficiency and increased fatigue. Increased dynamics in non-fatigued patients compared to healthy controls might represent a network organization that protects against fatigue or signal early network dysfunction.
KW - Basal ganglia
KW - Default mode network
KW - Dynamic functional connectivity
KW - Fatigue
KW - Multiple sclerosis
KW - Resting-state fMRI
UR - http://www.scopus.com/inward/record.url?scp=85099456032&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.nicl.2020.102556
DO - https://doi.org/10.1016/j.nicl.2020.102556
M3 - Article
C2 - 33472144
VL - 29
JO - NeuroImage. Clinical
JF - NeuroImage. Clinical
SN - 2213-1582
M1 - 102556
ER -