Tweet
This gets a bit science, but I get it-ish. And the p values are low (anything smaller than 0.1 is quite good), which means a higher probability that the changes were not by chance. Looking forward to more results, but this is highly encouraging evidence that exercise has neuroprotective properties in multiple sclerosis. - D
Physical exercise-related changes in structural connectome architecture in patients with relapsing-remitting multiple sclerosis
S.C. Hodecker1,2, S. Siemonsen2,3, T. Kjølhede4, S. Ringgaard5, B.G. Pedersen5, E. Stenager6,7, T. Petersen8, C. Heesen1,2, K. Vissing4, U. Dalgas4, J.-P. Stellmann1,2 1Department of Neurology, University Medical Center Hamburg Eppendorf, 2Institute of Neuroimmunology and MS (INIMS), 3Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg Eppendorf, Hamburg, Germany, 4Section of Sport Science, Department of Public Health, Faculty of Health, Aarhus University, 5The MR Research Centre, Aarhus University Hospital, Aarhus, 6Institute of Regional Health Research, University of Southern Denmark, Odense, 7The Multiple Sclerosis Clinic of Southern Jutland, Department of Neurology, Hospital of Southern Jutland, Sønderborg, 8The Multiple Sclerosis Clinic, Department of Neurology, Aarhus University Hospital, Aarhus, Denmark
Background: From a neuroscience perspective, the brain can be considered a highly differentiated and connected network and Multiple Sclerosis (MS) can be seen as a network disease. Probabilistic tractography based on Diffusion Weighted Imaging (DWI) data from Magnet Resonance Imaging (MRI) allows to model individual structural brain connectivity networks. The analysis of such connectomes is a promising method to investigate neurodegeneration. The impact of physical exercise on connectome properties and architecture is unknown.
Objectives: To explore changes of connectome properties and architecture following a 24-week exercise intervention.
Methods: This study was a 24-week randomized controlled trial, with a training group (n=17, progressive resistance training (PRT)) and a waitlist group (n=12, continuing their habitual lifestyle). The waitlist group was offered the same PRT program afterwards. All patients (mean age 44y; median Expanded Disability Status Scale 3 [2-4]) were in the relapsing-remitting phase of the disease. Cranial MRIs were obtained at baseline, after 24 and 48 weeks. Whole-brain structural connectomes were reconstructed using FSL probabilistic tractography. Graph metrics (e.g. strength, shortest average path length, global efficiency) were computed. Network architecture was assessed by analysing the so called rich-club of brain regions with an important integrative role. We investigated changes in different connection classes: connections within the rich-club, between rich-club and non rich-club hubs (feeder connections) and peripheral connections.
Results: No significant differences were observed in global graph metrics between pre- and postinterventional connectomes. Organization of the connectomes showed a preserved rich-club architecture. The (absolute or relative) amount of connections within the rich-club did not change significantly after physical exercise. A significant increase in the relative amount of feeder connections (p< 0.05) and a significant decrease in the relative amount of peripheral connections (p< 0.05) were observed. During the waiting phase loss of connectivity was inversely pronounced in the feeder connections.
Conclusions: Connectivity within the “rich-club” is rather stable with or without exercise over six months. In contrast, loss of feeder connections between peripheral and “rich-club” regions might be reduced by exercise. These changes indicate a possible neuroprotective effect of physical exercise.
Physical exercise-related changes in structural connectome architecture in patients with relapsing-remitting multiple sclerosis
S.C. Hodecker1,2, S. Siemonsen2,3, T. Kjølhede4, S. Ringgaard5, B.G. Pedersen5, E. Stenager6,7, T. Petersen8, C. Heesen1,2, K. Vissing4, U. Dalgas4, J.-P. Stellmann1,2 1Department of Neurology, University Medical Center Hamburg Eppendorf, 2Institute of Neuroimmunology and MS (INIMS), 3Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg Eppendorf, Hamburg, Germany, 4Section of Sport Science, Department of Public Health, Faculty of Health, Aarhus University, 5The MR Research Centre, Aarhus University Hospital, Aarhus, 6Institute of Regional Health Research, University of Southern Denmark, Odense, 7The Multiple Sclerosis Clinic of Southern Jutland, Department of Neurology, Hospital of Southern Jutland, Sønderborg, 8The Multiple Sclerosis Clinic, Department of Neurology, Aarhus University Hospital, Aarhus, Denmark
Background: From a neuroscience perspective, the brain can be considered a highly differentiated and connected network and Multiple Sclerosis (MS) can be seen as a network disease. Probabilistic tractography based on Diffusion Weighted Imaging (DWI) data from Magnet Resonance Imaging (MRI) allows to model individual structural brain connectivity networks. The analysis of such connectomes is a promising method to investigate neurodegeneration. The impact of physical exercise on connectome properties and architecture is unknown.
Objectives: To explore changes of connectome properties and architecture following a 24-week exercise intervention.
Methods: This study was a 24-week randomized controlled trial, with a training group (n=17, progressive resistance training (PRT)) and a waitlist group (n=12, continuing their habitual lifestyle). The waitlist group was offered the same PRT program afterwards. All patients (mean age 44y; median Expanded Disability Status Scale 3 [2-4]) were in the relapsing-remitting phase of the disease. Cranial MRIs were obtained at baseline, after 24 and 48 weeks. Whole-brain structural connectomes were reconstructed using FSL probabilistic tractography. Graph metrics (e.g. strength, shortest average path length, global efficiency) were computed. Network architecture was assessed by analysing the so called rich-club of brain regions with an important integrative role. We investigated changes in different connection classes: connections within the rich-club, between rich-club and non rich-club hubs (feeder connections) and peripheral connections.
Results: No significant differences were observed in global graph metrics between pre- and postinterventional connectomes. Organization of the connectomes showed a preserved rich-club architecture. The (absolute or relative) amount of connections within the rich-club did not change significantly after physical exercise. A significant increase in the relative amount of feeder connections (p< 0.05) and a significant decrease in the relative amount of peripheral connections (p< 0.05) were observed. During the waiting phase loss of connectivity was inversely pronounced in the feeder connections.
Conclusions: Connectivity within the “rich-club” is rather stable with or without exercise over six months. In contrast, loss of feeder connections between peripheral and “rich-club” regions might be reduced by exercise. These changes indicate a possible neuroprotective effect of physical exercise.