Neural distinctiveness of fatigue and low sleep quality in multiple sclerosis

Abstract Background and purpose Fatigue and low sleep quality in multiple sclerosis (MS) are closely related symptoms. Here, the associations between the brain's functional connectivity (FC) and fatigue and low sleep quality were investigated to determine the degree of neural distinctiveness of these symptoms. Method A hundred and four patients with relapsing–remitting MS (age 38.9 ± 10.2 years, 66 females) completed the Modified Fatigue Impact Scale and the Pittsburgh Sleep Quality Index and underwent resting-state functional magnetic resonance imaging. FC was analyzed using independent-component analysis in sensorimotor, default-mode, fronto-parietal and basal-ganglia networks. Multiple linear regression models allowed us to test the association between FC and fatigue and sleep quality whilst controlling for one another as well as for demographic, disease-related and imaging variables. Results Higher fatigue correlated with lower sleep quality (r = 0.54, p < 0.0001). Higher fatigue was associated with lower FC of the precentral gyrus in the sensorimotor network, the precuneus in the posterior default-mode network and the superior frontal gyrus in the left fronto-parietal network, independently of sleep quality. Lower sleep quality was associated with lower FC of the left intraparietal sulcus in the left fronto-parietal network, independently of fatigue. Specific associations were found between fatigue and the sensorimotor network's global FC and between low sleep quality and the left fronto-parietal network's global FC. Conclusion Despite the high correlation between fatigue and low sleep quality in the clinical picture, our findings clearly indicate that, on the neural level, fatigue and low sleep quality in MS are associated with decreased FC in distinct functional brain networks.This study was funded by Novartis. This publication has received funding from the EU Framework Programme for Research and Innovation Horizon 2020 (2014–2020) under the Marie Skłodowska-Curie Grant Agreement no. 754388 (LMUResearchFellows) and from LMUexcellent, funded by the Federal Ministry of Education and Research (BMBF) and the Free State of Bavaria under the Excellence Strategy of the German Federal Government and the Länder