Author Of 2 Presentations
P0445 - Cohort description of Project Y: Searching for the cause of phenotype diversity in MS (ID 1352)
Abstract
Background
Detecting factors that influence disease variability in MS patients is crucial to provide novel insights into the etiology of the disease and guide the search for effective therapies. To study the phenotypic variability, well-defined unbiased cohort studies are necessary. The most common and arguably most important variable to be considered as a confounding factor when studying variability of disease course in MS, is age.
Objectives
To identify determinants that explain phenotypic variability in MS, while eliminating the undesirable effect of age variation between MS patients.
Methods
Project Y is an ongoing population-based cross-sectional study of all people with MS born in the Netherlands in 1966. Participants are subjected to extensive examinations of a wide array of potential determinants and outcome measures: functional and static imaging, biomarkers in body fluid, physical and cognitive measurements, and lifestyle factors early and later in life. Age and sex matched controls are included.
Results
As for July 2020, a total of 386 eligible MS patients were identified, of which 31 refused to participate and 86 patients awaiting inclusion. Thirteen patients had passed away prior to study inclusion. Between December 2017 and July 2020, 269 MS patients participated with either a full or partial data collection, together with 125 healthy controls. The total number of identified cases (386) results in a prevalence of at least 1.7/1000 in the birth year 1966.
Conclusions
The first preliminary data of our unique cohort indicate that the previously presumed prevalence of MS in the Netherlands (1/1000) is a serious underestimation of the actual prevalence.
P0615 - Physical disability is related to resting-state network atrophy and altered MEG-based functional network topology in multiple sclerosis. (ID 1350)
Abstract
Background
Clinical disability in multiple sclerosis (MS) is insufficiently explained by structural damage as measured with standard magnetic resonance imaging (MRI) measures. More advanced measures of brain network atrophy and functional network changes might better explain symptoms and clinical deterioration.
Objectives
To investigate the relevance of functional network alterations in addition to network atrophy for explaining physical disability in MS.
Methods
In this cross-sectional study 143 MS patients and 36 healthy control participants underwent resting-state magnetoencephalography (MEG) and structural MRI. Functional connectivity between regions was estimated using the phase lag index, from which the minimum spanning tree (MST) was constructed, representing the backbone of the functional network. The topology of the MST was described using the so-called tree hierarchy (MST-Th). Gray matter (GM) volume was calculated within literature-based resting-state network maps (i.e. visual, sensorimotor, dorsal attention, ventral attention, limbic, fronto-parietal, default mode, deep gray matter, and cerebellar networks). Physical disability was quantified with the Expanded Disability Status Scale (EDSS), Nine Hole Peg Test (9HPT) and Timed 25-Foot Walk Test (TWT). Network atrophy and topology were compared between groups and related to disability.
Results
Atrophy was apparent in all resting-state networks. All volumes correlated positively (p<.001) with EDSS and 9HPT: Spearman’s ρ between .289 and .567, highest correlations for sensorimotor, default mode, fronto-parietal and dorsal attention networks. EDSS correlated negatively with MST-Th in the lower alpha band (α1) (p < 0.008), while 9HPT correlated negatively with MST-Th in the upper and lower alpha, gamma, delta and theta bands (p <0.05), indicating a less efficient network relating to worse disability. TWT was related to atrophy in all networks, but not network topology. Together, MST-Th-α1, age, cerebellar and fronto-parietal atrophy explained 36% of EDSS variance, while 19% of 9HPT variance was explained by deep GM atrophy and MST-Th-α1. Lesion volume had no added significant effect on variance.
Conclusions
These results suggest that more advanced measures of network atrophy and functional network topology can explain a significant degree of disability variance in MS. In addition, mobility scores were not related to network changes, which could imply different underlying pathological substrates compared to those that underlie upper limb dexterity.
Presenter Of 1 Presentation
P0615 - Physical disability is related to resting-state network atrophy and altered MEG-based functional network topology in multiple sclerosis. (ID 1350)
Abstract
Background
Clinical disability in multiple sclerosis (MS) is insufficiently explained by structural damage as measured with standard magnetic resonance imaging (MRI) measures. More advanced measures of brain network atrophy and functional network changes might better explain symptoms and clinical deterioration.
Objectives
To investigate the relevance of functional network alterations in addition to network atrophy for explaining physical disability in MS.
Methods
In this cross-sectional study 143 MS patients and 36 healthy control participants underwent resting-state magnetoencephalography (MEG) and structural MRI. Functional connectivity between regions was estimated using the phase lag index, from which the minimum spanning tree (MST) was constructed, representing the backbone of the functional network. The topology of the MST was described using the so-called tree hierarchy (MST-Th). Gray matter (GM) volume was calculated within literature-based resting-state network maps (i.e. visual, sensorimotor, dorsal attention, ventral attention, limbic, fronto-parietal, default mode, deep gray matter, and cerebellar networks). Physical disability was quantified with the Expanded Disability Status Scale (EDSS), Nine Hole Peg Test (9HPT) and Timed 25-Foot Walk Test (TWT). Network atrophy and topology were compared between groups and related to disability.
Results
Atrophy was apparent in all resting-state networks. All volumes correlated positively (p<.001) with EDSS and 9HPT: Spearman’s ρ between .289 and .567, highest correlations for sensorimotor, default mode, fronto-parietal and dorsal attention networks. EDSS correlated negatively with MST-Th in the lower alpha band (α1) (p < 0.008), while 9HPT correlated negatively with MST-Th in the upper and lower alpha, gamma, delta and theta bands (p <0.05), indicating a less efficient network relating to worse disability. TWT was related to atrophy in all networks, but not network topology. Together, MST-Th-α1, age, cerebellar and fronto-parietal atrophy explained 36% of EDSS variance, while 19% of 9HPT variance was explained by deep GM atrophy and MST-Th-α1. Lesion volume had no added significant effect on variance.
Conclusions
These results suggest that more advanced measures of network atrophy and functional network topology can explain a significant degree of disability variance in MS. In addition, mobility scores were not related to network changes, which could imply different underlying pathological substrates compared to those that underlie upper limb dexterity.