Dataset Information

Gray matter networks and cognitive impairment in multiple sclerosis.

ABSTRACT: BACKGROUND:Coordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS). OBJECTIVE:To investigate whether single-subject gray matter network properties are related to impaired cognition in MS. METHODS:We studied 148 MS patients (99 female) and 33 healthy controls (HC, 21 female). Seven network parameters were computed and compared within MS between cognitively normal and impaired subjects, and associated with performance on neuropsychological tests in six cognitive domains with regression models. Analyses were controlled for age, gender, whole-brain gray matter volumes, and education level. RESULTS:Compared to MS subjects with normal cognition, MS subjects with cognitive impairment showed a more random network organization as indicated by lower lambda values (all p < 0.05). Worse average cognition and executive function were associated with lower lambda values. Impaired information processing speed, working memory, and attention were associated with lower clustering values. CONCLUSION:Our findings indicate that MS subjects with a more randomly organized gray matter network show worse cognitive functioning, suggesting that single-subject gray matter graphs may capture neurological dysfunction due to MS.

SUBMITTER: Rimkus CM

PROVIDER: S-EPMC6393954 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Gray matter networks and cognitive impairment in multiple sclerosis.

Rimkus Carolina M CM Schoonheim Menno M MM Steenwijk Martijn D MD Vrenken Hugo H Eijlers Anand Jc AJ Killestein Joep J Wattjes Mike P MP Leite Claudia C CC Barkhof Frederik F Tijms Betty M BM

Multiple sclerosis (Houndmills, Basingstoke, England) 20180111 3

<h4>Background</h4>Coordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS).<h4>Objective</h4>To investigate whether single-subject gray matter network properties are related to impaired cognition in MS.<h4>Methods</h4>We studied 148 MS patients (99 female) and 33 healthy controls (HC, 21 female). Seven network parameters were computed and compared within MS between cognitively norm ...[more]

PMID: 29320933

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Project description:Background and purposeDeep gray matter iron accumulation is increasingly recognized in association with multiple sclerosis and can be measured in vivo with MR imaging. The cognitive implications of this pathology are not well-understood, especially vis-à-vis deep gray matter atrophy. Our aim was to investigate the relationships between cognition and deep gray matter iron in MS by using 2 MR imaging-based iron-susceptibility measures.Materials and methodsForty patients with multiple sclerosis (relapsing-remitting, n = 16; progressive, n = 24) and 27 healthy controls were imaged at 4.7T by using the transverse relaxation rate and quantitative susceptibility mapping. The transverse relaxation rate and quantitative susceptibility mapping values and volumes (atrophy) of the caudate, putamen, globus pallidus, and thalamus were determined by multiatlas segmentation. Cognition was assessed with the Brief Repeatable Battery of Neuropsychological Tests. Relationships between cognition and deep gray matter iron were examined by hierarchic regressions.ResultsCompared with controls, patients showed reduced memory (P < .001) and processing speed (P = .02) and smaller putamen (P < .001), globus pallidus (P = .002), and thalamic volumes (P < .001). Quantitative susceptibility mapping values were increased in patients compared with controls in the putamen (P = .003) and globus pallidus (P = .003). In patients only, thalamus (P < .001) and putamen (P = .04) volumes were related to cognitive performance. After we controlled for volume effects, quantitative susceptibility mapping values in the globus pallidus (P = .03; trend for transverse relaxation rate, P = .10) were still related to cognition.ConclusionsQuantitative susceptibility mapping was more sensitive compared with the transverse relaxation rate in detecting deep gray matter iron accumulation in the current multiple sclerosis cohort. Atrophy and iron accumulation in deep gray matter both have negative but separable relationships to cognition in multiple sclerosis.

Dataset Information

Gray matter networks and cognitive impairment in multiple sclerosis.

Publications

Gray matter networks and cognitive impairment in multiple sclerosis.

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