The Impact of Training on Sitting Time and Brain Volumes in Multiple Sclerosis.

Multiple Sclerosis is a progressive, autoimmune, neurodegenerative disorder of the central nervous system (CNS) that predominantly affects young to middle-aged adults. It is characterized by a chronic inflammatory process that causes demyelination, axonal damage and white matter lesions across the CNS. Furthermore, evidence also indicates grey matter (GM) atrophy which has been reported to be significantly correlated with both clinical and cognitive deterioration. Clinical manifestations include spasticity, tremor, paralysis, walking difficulties and cognitive abnormalities. Due to these primary disease symptoms, persons with MS (PwMS) appear to be susceptible to a sedentary lifestyle and inactivity, which consequently increases the risk of other important, health-related secondary deficits including respiratory, metabolic and cardiac dysfunction. These deficits further contribute to a decrease in cardiorespiratory fitness and quality of life (QoL), thereby causing a vicious circle of decreased exercise tolerance, greater disability and increased inactivity. Since pharmacological treatment has little impact on these secondary deficits, exercise therapy has become an important aspect of the treatment of MS. Hence, exercise therapy interventions in MS have been studied extensively and have already been proven to significantly improve cardiorespiratory fitness, muscle strength, balance, fatigue, cognition, quality of life, respiratory function and brain volumes. Moreover, a dose-response relationship has been reported for functional variables such as strength and endurance capacity. As such, high intensity interval training (HIIT) probably is exerts superior effects compared to traditional low/moderate intensity continuous training (MICT). However and in contrast with other populations, effects of HIIT on important health-related variables such as body composition, blood pressure and blood lipid profiles are less evident. Possibly, PwMS do not reach the exercise intensities required to improve such factors due to cardiovascular autonomic dysfunction, leading to impaired carotid baroreflex control, attenuated elevations in blood pressure and disturbed increases in heart rate, and abnormal muscle energy metabolism. Moreover, higher intensities might hamper longer-term implementation in real life, as an inverse relation between exercise intensity and training adherence has already been reported. Training periodization (alternating HIIT and MICT) offers a solution to overcome the barrier of adherence and concurrently augmenting training effects, but in contrast to other populations, the addition of a lower intensity training component does still not improve health-related variables. Therefore, other approaches are warranted. Recently, evidence is growing that sedentary time is an important health risk factor, independent of the (dis)practice of structured exercise. Hence, PwMS possibly compensate training effects with even more sedentary time, in addition to an already sedentary lifestyle as mentioned previously. As such, addressing sedentary time might be an interesting new approach to counteract the health-related deficits in PwMS. Therefore, the present study explores the impact of a structured exercise program on sedentary time and health-related variables. Furthermore, a secondary aim of the current project is to investigate the effect of a periodized training program on brain volumes and cognitive function. Recent evidence of physical training effects on cognitive variables is contradictory. So for exercise intervention studies that studied the latter only used short-term and laboratory-based training programs and included exercise modalities (type, intensity, duration) that are difficult to compare. Interestingly, a recent short-term randomized controlled trial reported superior effects of HIIT on cognitive functions compared to MICT. Hence, the current study aims to investigate the impact of a long-term, home-based training program with HIIT-components on cognitive variables.