Contributions
Abstract: P515
Type: Poster
Abstract Category: Pathology and pathogenesis of MS - 21 Imaging
Introduction: Information processing speed (IPS) deficits are amongst the first cognitive symptoms in multiple sclerosis (MS) and are highly debilitating. Although both structural and functional alterations have been associated with IPS impairment, studies overarching both modalities are lacking. In this study, we examined the relative importance of functional and structural brain damage in explaining different levels of IPS impairment.
Methods: IPS was measured using the symbol digit modalities test (SDMT) in 330 MS patients and 96 healthy controls (HC), who also underwent advanced MRI. The severity of structural MRI-damage was measured using whole-brain white matter integrity, atrophy and lesion load. The severity of functional damage was determined by the level of increased and decreased resting-state functional connectivity relative to HC. After comparing all measures between groups, significantly different measures were entered in a backward regression model to select the main predictors of IPS. Selected predictors were then used to create subgroups with mild or severe structural and functional damage, between which IPS performance was compared.
Results: Deep gray matter volume, whole-brain white matter integrity and severity of increased functional connectivity were significant predictors of IPS. Our findings show that MS patients with mild structural and functional damage had the best IPS, albeit still lower than HC (Grade I: z-score of -0.5). MS patients with severe functional damage but only mild structural damage had better IPS performance (Grade II: z-score of -1.0) than patients with severe structural damage but only mild functional damage (Grade III: z-score of -1.5). Patients with both severe functional and structural damage were worst off (Grade IV: z-score of -2).
Conclusion: IPS impairment was worst in patients with both severe functional and structural damage. Damage on either functional or structural measures results in distinct levels of IPS performance. Our findings suggest that the IPS performance of MS patients relies on a complex interplay between GM atrophy, WM damage and functional network changes.
Disclosure:
KA Meijer receives a research grant from Biogen.
Q van Geest nothing to disclose
AJC Eijlers receives research support from the Dutch MS Research Foundation, grant number 14-358e.
JJG Geurts is an editor of Multiple Sclerosis Journal, a member of the editorial boards of BMC Neurology, Neurology and Frontiers in Neurology, and serves as a consultant for Biogen and Genzyme.
MM Schoonheim receives research support from the Dutch MS Research Foundation, grant number 13-820, and has received compensation for consulting services or speaker honoraria from ExceMed, Genzyme and Biogen, and serves on the editorial board of Frontiers in Neurology
HE Hulst receives research support from the Dutch MS Research Foundation, grant number 08-648 and serves as a consultant for Genzyme, Merck-Serono, Teva Pharmaceuticals and Novartis.
Abstract: P515
Type: Poster
Abstract Category: Pathology and pathogenesis of MS - 21 Imaging
Introduction: Information processing speed (IPS) deficits are amongst the first cognitive symptoms in multiple sclerosis (MS) and are highly debilitating. Although both structural and functional alterations have been associated with IPS impairment, studies overarching both modalities are lacking. In this study, we examined the relative importance of functional and structural brain damage in explaining different levels of IPS impairment.
Methods: IPS was measured using the symbol digit modalities test (SDMT) in 330 MS patients and 96 healthy controls (HC), who also underwent advanced MRI. The severity of structural MRI-damage was measured using whole-brain white matter integrity, atrophy and lesion load. The severity of functional damage was determined by the level of increased and decreased resting-state functional connectivity relative to HC. After comparing all measures between groups, significantly different measures were entered in a backward regression model to select the main predictors of IPS. Selected predictors were then used to create subgroups with mild or severe structural and functional damage, between which IPS performance was compared.
Results: Deep gray matter volume, whole-brain white matter integrity and severity of increased functional connectivity were significant predictors of IPS. Our findings show that MS patients with mild structural and functional damage had the best IPS, albeit still lower than HC (Grade I: z-score of -0.5). MS patients with severe functional damage but only mild structural damage had better IPS performance (Grade II: z-score of -1.0) than patients with severe structural damage but only mild functional damage (Grade III: z-score of -1.5). Patients with both severe functional and structural damage were worst off (Grade IV: z-score of -2).
Conclusion: IPS impairment was worst in patients with both severe functional and structural damage. Damage on either functional or structural measures results in distinct levels of IPS performance. Our findings suggest that the IPS performance of MS patients relies on a complex interplay between GM atrophy, WM damage and functional network changes.
Disclosure:
KA Meijer receives a research grant from Biogen.
Q van Geest nothing to disclose
AJC Eijlers receives research support from the Dutch MS Research Foundation, grant number 14-358e.
JJG Geurts is an editor of Multiple Sclerosis Journal, a member of the editorial boards of BMC Neurology, Neurology and Frontiers in Neurology, and serves as a consultant for Biogen and Genzyme.
MM Schoonheim receives research support from the Dutch MS Research Foundation, grant number 13-820, and has received compensation for consulting services or speaker honoraria from ExceMed, Genzyme and Biogen, and serves on the editorial board of Frontiers in Neurology
HE Hulst receives research support from the Dutch MS Research Foundation, grant number 08-648 and serves as a consultant for Genzyme, Merck-Serono, Teva Pharmaceuticals and Novartis.