Browse
Submit Data
Databases
API
Help

Dataset Information

23 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

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 |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Microstructural MRI Correlates of Cognitive Impairment in Multiple Sclerosis: The Role of Deep Gray Matter.

Project description:Although cognitive impairment (CI) is frequently observed in people with multiple sclerosis (pwMS), its pathogenesis is still controversial. Conflicting results emerged concerning the role of microstructural gray matter (GM) damage especially when involving the deep GM structures. In this study, we aimed at evaluating whether differences in cortical and deep GM structures between apparently cognitively normal (ACN) and CI pwMS (36 subjects in total) are present, using an extensive set of diffusion MRI (dMRI) indices and conventional morphometry measures. The results revealed increased anisotropy and restriction over several deep GM structures in CI compared with ACN pwMS, while no changes in volume were present in the same areas. Conversely, reduced anisotropy/restriction values were detected in cortical regions, mostly the pericalcarine cortex and precuneus, combined with reduced thickness of the superior frontal gyrus and insula. Most of the dMRI metrics but none of the morphometric indices correlated with the Symbol Digit Modality Test. These results suggest that deep GM microstructural damage can be a strong anatomical substrate of CI in pwMS and might allow identifying pwMS at higher risk of developing CI.

| S-EPMC8234586 | biostudies-literature

Apolipoprotein E allele 4 effects on Single-Subject Gray Matter Networks in Mild Cognitive Impairment.

Project description:There is evidence that gray matter networks are disrupted in Mild Cognitive Impairment (MCI) and associated with cognitive impairment and faster disease progression. However, it remains unknown how these alterations are related to the presence of Apolipoprotein E isoform E4 (ApoE4), the most prominent genetic risk factor for late-onset Alzheimer's disease (AD). To investigate this topic at the individual level, we explore the impact of ApoE4 and the disease progression on the Single-Subject Gray Matter Networks (SSGMNets) using the graph theory approach. Our data sample comprised 200 MCI patients selected from the ADNI database, classified as non-Converters and Converters (will progress into AD). Each group included 50 ApoE4-positive ('Carriers', ApoE4 + ) and 50 ApoE4-negative ('non-Carriers', ApoE4-). The SSGMNets were estimated from structural MRIs at two-time points: baseline and conversion. We investigated whether altered network topological measures at baseline and their rate of change (RoC) between baseline and conversion time points were associated with ApoE4 and disease progression. We also explored the correlation of SSGMNets attributes with general cognition score (MMSE), memory (ADNI-MEM), and CSF-derived biomarkers of AD (Aβ42, T-tau, and P-tau). Our results showed that ApoE4 and the disease progression modulated the global topological network properties independently but not in their RoC. MCI converters showed a lower clustering index in several regions associated with neurodegeneration in AD. The SSGMNets' topological organization was revealed to be able to predict cognitive and memory measures. The findings presented here suggest that SSGMNets could indeed be used to identify MCI ApoE4 Carriers with a high risk for AD progression.

| S-EPMC8405842 | biostudies-literature

Gray Matter Correlates of Cognitive Performance Differ between Relapsing-Remitting and Primary-Progressive Multiple Sclerosis.

Project description:Multiple Sclerosis (MS) is a chronic inflammatory/demyelinating and neurodegenerative disease of the central nervous system (CNS). Most patients experience a relapsing-remitting (RR) course, while about 15-20% of patients experience a primary progressive (PP) course. Cognitive impairment affects approximately 40-70% of all MS patients and differences in cognitive impairment between RR-MS and PP-MS have been found. We aimed to compare RR-MS and PP-MS patients in terms of cognitive performance, and to investigate the MRI correlates of cognitive impairment in the two groups using measures of brain volumes and cortical thickness. Fifty-seven patients (42 RR-MS, 15 PP-MS) and thirty-eight matched controls underwent neuropsychological (NP) testing and MRI. PP-MS patients scored lower than RR-MS patients on most of the NP tests in absence of any specific pattern. PP-MS patients showed significantly lower caudate volume. There was no significant difference in MRI correlates of cognitive impairment between the two groups except for a prevalent association with MRI measures of cortical GM injury in RR-MS patients and with MRI measures of subcortical GM injury in PP-MS patients. This suggests that although cognitive impairment results from several factors, cortical and subcortical GM injury may play a different role depending on the disease course.

| S-EPMC4616346 | biostudies-other

Voxel-based analysis of gray matter relaxation rates shows different correlation patterns for cognitive impairment and physical disability in relapsing-remitting multiple sclerosis.

Project description:BackgroundRegional analyses of markers of microstructural gray matter (GM) changes, including relaxation rates, have shown inconsistent correlations with physical and cognitive impairment in MS.ObjectiveTo assess voxelwise the correlation of the R1 and R2 relaxation rates with the physical and cognitive impairment in MS.MethodsGM R1 and R2 relaxation rate maps were obtained in 241 relapsing-remitting MS patients by relaxometric segmentation of MRI studies. Correlations with the Expanded Disability Status Scale (EDSS) and the percentage of impaired cognitive test (Brief Repeatable Battery and Stroop Test, available in 186 patients) were assessed voxelwise, including voxel GM content as nuisance covariate to remove the effect of atrophy on the correlations.ResultsExtensive clusters of inverse correlation between EDSS and R2 were detected throughout the brain, while inverse correlations with R1 were mostly limited to perirolandic and supramarginal cortices. Cognitive impairment correlated negatively with R1, and to a lesser extent with R2, in the middle frontal, mesial temporal, midcingulate and medial parieto-occipital cortices.ConclusionIn relapsing-remitting MS patients, GM microstructural changes correlate diffusely with physical disability, independent of atrophy, with a preferential role of the sensorimotor cortices. Neuronal damage in the limbic system and dorsolateral prefrontal cortices correlates with cognitive dysfunction.

| S-EPMC7025083 | biostudies-literature

Gray matter is targeted in first-attack multiple sclerosis.

Project description:The cause of multiple sclerosis (MS), its driving pathogenesis at the earliest stages, and what factors allow the first clinical attack to manifest remain unknown. Some imaging studies suggest gray rather than white matter may be involved early, and some postulate this may be predictive of developing MS. Other imaging studies are in conflict. To determine if there was objective molecular evidence of gray matter involvement in early MS we used high-resolution mass spectrometry to identify proteins in the cerebrospinal fluid (CSF) of first-attack MS patients (two independent groups) compared to established relapsing remitting (RR) MS and controls. We found that the CSF proteins in first-attack patients were differentially enriched for gray matter components (axon, neuron, synapse). Myelin components did not distinguish these groups. The results support that gray matter dysfunction is involved early in MS, and also may be integral for the initial clinical presentation.

| S-EPMC3769274 | biostudies-literature

Gray matter in amnestic mild cognitive impairment: voxel-based morphometry.

Project description:Multiple regression voxel-based morphometry analyses were used to examine the relationship between regional gray matter volumes and neurocognitive performance in 10 patients with amnestic mild cognitive impairment and 20 healthy age-matched controls. Cognitive functioning was assessed with seven standardized neuropsychological tests. Patients with amnestic mild cognitive impairment exhibited impaired cognitive performance (on the Mini Mental State Examination, tests of verbal fluency, verbal and spatial learning and memory, and visual-motor abilities) and reduced gray matter volume in the right temporal pole. Across all participants, better performance on several neuropsychological tests was associated with higher regional gray matter volumes. Voxel-based morphometry provides an operator-unbiased means to investigate volumetric differences, which may be related to impaired neuropsychological functioning.

| S-EPMC3041512 | biostudies-literature

Modeling the relationship among gray matter atrophy, abnormalities in connecting white matter, and cognitive performance in early multiple sclerosis.

Project description:Background and purposeQuantitative assessment of clinical and pathologic consequences of white matter abnormalities in multiple sclerosis is critical in understanding the pathways of disease. This study aimed to test whether gray matter atrophy was related to abnormalities in connecting white matter and to identify patterns of imaging biomarker abnormalities that were related to patient processing speed.Materials and methodsImage data and Symbol Digit Modalities Test scores were collected from a cohort of patients with early multiple sclerosis. The Network Modification Tool was used to estimate connectivity irregularities by projecting white matter abnormalities onto connecting gray matter regions. Partial least-squares regression quantified the relationship between imaging biomarkers and processing speed as measured by the Symbol Digit Modalities Test.ResultsAtrophy in deep gray matter structures of the thalami and putamen had moderate and significant correlations with abnormalities in connecting white matter (r = 0.39-0.41, P < .05 corrected). The 2 models of processing speed, 1 for each of the WM imaging biomarkers, had goodness-of-fit (R(2)) values of 0.42 and 0.30. A measure of the impact of white matter lesions on the connectivity of occipital and parietal areas had significant nonzero regression coefficients.ConclusionsWe concluded that deep gray matter regions may be susceptible to inflammation and/or demyelination in white matter, possibly having a higher sensitivity to remote degeneration, and that lesions affecting visual processing pathways were related to processing speed. The Network Modification Tool may be used to quantify the impact of early white matter abnormalities on both connecting gray matter structures and processing speed.

| S-EPMC4951088 | biostudies-literature

Divergent Connectivity Changes in Gray Matter Structural Covariance Networks in Subjective Cognitive Decline, Amnestic Mild Cognitive Impairment, and Alzheimer's Disease.

Project description:Alzheimer's disease (AD) has a long preclinical stage that can last for decades prior to progressing toward amnestic mild cognitive impairment (aMCI) and/or dementia. Subjective cognitive decline (SCD) is characterized by self-experienced memory decline without any evidence of objective cognitive decline and is regarded as the later stage of preclinical AD. It has been reported that the changes in structural covariance patterns are affected by AD pathology in the patients with AD and aMCI within the specific large-scale brain networks. However, the changes in structural covariance patterns including normal control (NC), SCD, aMCI, and AD are still poorly understood. In this study, we recruited 42 NCs, 35 individuals with SCD, 43 patients with aMCI, and 41 patients with AD. Gray matter (GM) volumes were extracted from 10 readily identifiable regions of interest involved in high-order cognitive function and AD-related dysfunctional structures. The volume values were used to predict the regional densities in the whole brain by using voxel-based statistical and multiple linear regression models. Decreased structural covariance and weakened connectivity strength were observed in individuals with SCD compared with NCs. Structural covariance networks (SCNs) seeding from the default mode network (DMN), salience network, subfields of the hippocampus, and cholinergic basal forebrain showed increased structural covariance at the early stage of AD (referring to aMCI) and decreased structural covariance at the dementia stage (referring to AD). Moreover, the SCN seeding from the executive control network (ECN) showed a linearly increased extent of the structural covariance during the early and dementia stages. The results suggest that changes in structural covariance patterns as the order of NC-SCD-aMCI-AD are divergent and dynamic, and support the structural disconnection hypothesis in individuals with SCD.

| S-EPMC8415752 | biostudies-literature

Cortical and Deep Gray Matter Perfusion Associations With Physical and Cognitive Performance in Multiple Sclerosis Patients.

Project description:Background: Reports suggest presence of cerebral hypoperfusion in multiple sclerosis (MS). Currently there are no studies that examine if the cerebral MS perfusion is affected by presence of cardiovascular comorbidities. Objective: To investigate associations between cerebral perfusion and disease outcomes in MS patients with and without comorbid cardiovascular diseases (CVD). Materials: One hundred three MS patients (75.7% female) with average age of 54.4 years and 21.1 years of disease duration underwent 3T MRI dynamic susceptibility contrast (DSC) imaging and were tested with Expanded Disability Status Scale, Multiple Sclerosis Severity Score (MSSS), Timed 25-Foot Walk (T25FW), 9-Hole Peg Test (9HPT) and Symbol Digit Modalities Test (SDMT). Structural and perfusion-based normalized measures of cerebral blood flow (nCBF), cerebral blood volume (nCBV) and mean transit time (MTT) of global, tissue-specific and deep gray matter (DGM) areas were derived. CBV and CBF were normalized by the normal-appearing white matter counterpart. Results: In linear step-wise regression analysis, age- and sex-adjusted, MSSS (R 2 = 0.186) was associated with whole brain volume (WBV) (? = -0.244, p = 0.046) and gray matter (GM) nCBF (? = -0.22, p = 0.035). T25FW (R 2 = 0.278) was associated with WBV (? = -0.289, p = 0.012) and hippocampus nCBV (? = -0.225, p = 0.03). 9HPT (R 2 = 0.401) was associated with WBV (? = 0.195, p = 0.049) and thalamus MTT (? = -0.198, p=0.032). After adjustment for years of education, SDMT (R 2 = 0.412) was explained by T2-lesion volume (? = -0.305, p = 0.001), and GM nCBV (? = 0.236, p = 0.013). No differences in MTT, nCBF nor nCBV measures between patients with (n = 42) and without CVD (n = 61) were found. Perfusion-measures were also not able to distinguish CVD status in a logistic regression model. Conclusion: Decreased GM and deep GM perfusion is associated with poorer MS outcomes, but not with presence of CVD.

| S-EPMC7380109 | biostudies-literature

Impaired Self-Other Distinction and Subcortical Gray-Matter Alterations Characterize Socio-Cognitive Disturbances in Multiple Sclerosis.

Project description:Introduction: Recent studies of patients with multiple sclerosis (MS) have revealed disturbances in distinct components of social cognition, such as impaired mentalizing and empathy. The present study investigated this socio-cognitive profile in MS patients in more detail, by examining their performance on tasks measuring more fundamental components of social cognition and any associated disruptions to gray-matter volume (GMV). Methods: We compared 43 patients with relapse-remitting MS with 43 age- and sex-matched healthy controls (HCs) on clinical characteristics (depression, fatigue), cognitive processing speed, and three aspects of low-level social cognition; specifically, imitative tendencies, visual perspective taking, and emotion recognition. Using voxel-based morphometry, we then explored relationships between GMV and these clinical and behavioral measures. Results: Patients exhibited significantly slower processing speed, poorer perspective taking, and less imitation compared with HCs. These impairments were related to reduced GMV throughout the putamen, thalami, and anterior insula, predominantly in the left hemisphere. Surprisingly, differences between the groups in emotion recognition were not significant. Conclusion: Less imitation and poorer perspective taking indicate a cognitive self-bias when faced with conflicting self- and other-representations. This suggests that impaired self-other distinction, and an associated subcortical pattern of GM atrophy, might underlie the socio-cognitive disturbances observed in MS.

| S-EPMC6536606 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data