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March 07, 2017; 88 (10) Article

Increased default-mode network centrality in cognitively impaired multiple sclerosis patients

Anand J.C. Eijlers, Kim A. Meijer, Thomas M. Wassenaar, Martijn D. Steenwijk, Bernard M.J. Uitdehaag, Frederik Barkhof, Alle M. Wink, Jeroen J.G. Geurts, Menno M. Schoonheim
First published February 8, 2017, DOI: https://doi.org/10.1212/WNL.0000000000003689
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Abstract

Objective: To investigate how changes in functional network hierarchy determine cognitive impairment in multiple sclerosis (MS).

Methods: A cohort consisting of 332 patients with MS (age 48.1 ± 11.0 years, symptom duration 14.6 ± 8.4 years) and 96 healthy controls (HCs; age 45.9 ± 10.4 years) underwent structural MRI, fMRI, and extensive neuropsychological testing. Patients were divided into 3 groups: cognitively impaired (CI; n = 87), mildly cognitively impaired (MCI; n = 65), and cognitively preserved (CP; n = 180). The functional importance of brain regions was quantified with degree centrality, the average strength of the functional connections of a brain region with the rest of the brain, and eigenvector centrality, which adds to this concept by adding additional weight to connections with brain hubs because these are known to be especially important. Centrality values were calculated for each gray matter voxel based on resting-state fMRI data, registered to standard space. Group differences were assessed with a cluster-wise permutation-based method corrected for age, sex, and education.

Results: CI patients demonstrated widespread centrality increases compared to both HCs and CP patients, mainly in regions making up the default-mode network. Centrality decreases were similar in all patient groups compared to HCs, mainly in occipital and sensorimotor areas. Results were robust across centrality measures.

Conclusions: Patients with MS with cognitive impairment show hallmark alterations in functional network hierarchy with increased relative importance (centrality) of the default-mode network.

GLOSSARY

CI=
cognitively impaired;
CP=
cognitively preserved;
EDSS=
Expanded Disability Status Scale;
HADS=
Hospital Anxiety and Depression Scale;
HC=
healthy control;
MCI=
mildly cognitively impaired;
MS=
multiple sclerosis

Cognitive deficits are present in 40% to 70% of patients with multiple sclerosis (MS) and have strongly deleterious effects on psychosocial functioning.1 Correlations between conventional MRI measures of structural damage such as lesion load and cognitive impairment are generally poor,2 while more advanced measures such as thalamic atrophy show stronger correlations.3 To further enhance our understanding of cognitive impairment in MS, it is, however, essential to study brain function.

The discovery of cognitively relevant brain networks at rest has led to a surge in network studies using fMRI, showing both increases and decreases in connectivity.4 To bring all these findings together, the graph theoretical concept of centrality can be used, which measures the overall importance of individual brain regions. Degree centrality measures the quantity (strength) of functional connections of a region, while eigenvector centrality also takes into account the quality of these connections, assigning a higher weighting to connections with brain hubs. Eigenvector centrality was recently investigated in an MS pilot study, showing a decreased importance of the ventral stream and sensorimotor cortex and an increased importance of the posterior cingulate cortex and thalamus,5 and has also been used in Alzheimer disease.6 These pilot studies have indicated the potential of centrality measures, but they have not been used in patients with MS with more severe cognitive impairment.

The aim of the current study was to study cognitive impairment in MS by investigating changes in degree and eigenvector centrality in a large sample of patients with MS with different severities of cognitive impairment.

METHODS

Participants.

For this study, a total of 332 patients with MS (32% men, age 48.1 ± 11.0 years, symptom duration 14.6 ± 8.4 years), part of the Amsterdam MS cohort,7,8 and 96 healthy controls (HCs; 42% men, age 45.9 ± 10.4 years) were included. All patients were diagnosed with clinically definite MS according to the revised McDonald criteria.9 Of all patients, 243 were diagnosed with relapsing-remitting, 53 with secondary progressive, and 36 with primary progressive MS. Disease-modifying treatments included β-interferons (n = 74), glatiramer acetate (n = 16), natalizumab (n = 23), or other immunosuppressive therapy (n = 6). The Expanded Disability Status Scale (EDSS)10 was used to measure overall disability, and anxiety and depression were assessed with the Hospital Anxiety and Depression Scale (HADS)11 questionnaire. Patients were relapse-free and without steroid treatment for at least 2 months before participating in the study.

Standard protocol approvals, registrations, and patient consents.

Approval was obtained from the institutional ethics review board of the VU University Medical Center, and participants gave written informed consent prior to participation.

Neuropsychological evaluation.

Participants underwent extensive neuropsychological evaluation on the day of MRI scanning with an expanded Brief Repeatable Battery of Neuropsychological tests12 as previously described.7 The following cognitive domains were assessed: executive functioning (concept shifting test), verbal memory (selective reminding test), verbal fluency (word list generation), information processing speed (symbol digit modalities test), visuospatial memory (spatial recall test), attention (Stroop Color and Word Test), and working memory (memory comparison test). The raw cognitive scores of all participants were corrected for effects of sex, age, and education observed in the HC sample with the use of a previously published method.13 These corrected scores were then transformed into domain-specific z scores based on the mean and SDs of the normally distributed HC group scores and used to create patient groups.

Patient groups.

Severity of cognitive impairment.

The total patient group was subdivided into 3 subgroups based on the severity of their cognitive impairment, as was previously done.7,14 Patients who scored 2 SDs (i.e., z ≤ −2) below the average of the HC group on at least 2 cognitive domains were classified as cognitively impaired (CI). Patients who scored 1.5 SDs below the average of HCs on at least 2 cognitive domains but did not fulfill the CI criterion were classified as mildly cognitively impaired (MCI). The remaining patients were classified as cognitively preserved (CP).

Magnetic resonance imaging.

All participants were scanned on a 3T whole-body magnetic resonance system (GE Signa-HDxt, Milwaukee, WI) with an 8-channel phased-array head coil. The protocol included a 3-dimension T1-weighted fast spoiled gradient echo sequence for volumetric measurements, a 3-dimensional fluid-attenuated inversion recovery sequence for lesion detection, and a resting-state fMRI scan covering the entire brain. See e-Methods at Neurology.org for acquisition parameters.

Image processing.

White matter lesions were segmented on the fluid-attenuated inversion recovery sequence images with the use of k nearest neighbor classification with tissue-type priors15 and registered to the 3-dimensional T1 images, where lesion filling was applied with Lesion Automated Preprocessing.16 Lesion maps were nonlinearly registered to Montreal Neurological Institute space to obtain lesion probability maps. Total brain volumes and deep gray matter volumes were calculated on the lesion-filled images with SIENAX and FIRST, respectively (both part of FSL 5, fmrib.ox.ac.uk/fsl). Lesion and brain volumes were normalized for head size. Resting-state fMRI images were preprocessed with the MELODIC pipeline (part of FSL, using standard settings), nonlinearly registered to Montreal Neurological Institute standard space, and resampled to a resolution of 4 mm isotropic. See e-Methods for additional image processing details.

Mask construction and centrality computation.

All functional data were masked to exclude all white matter voxels and gray matter voxels without reliable fMRI signal (e.g., orbitofrontal areas sensitive to distortion artifacts) for the voxel-wise centrality computation, as depicted in the e-Methods and figure e-1. Individual participants' weighted degree and eigenvector centrality values were computed for all included voxels separately in standard space with fastECM (github.com/amwink/bias/tree/master/matlab/fastECM).17 Because the focus was on relative shifts in importance of brain regions and to ensure comparability with eigenvector centrality, degree centrality was made relative by dividing the degree centrality for each voxel by the whole-brain average voxel degree.

Statistical analysis.

Statistical analyses of the demographic, clinical, and global MRI variables were performed in SPSS version 22 (Chicago, IL). All demographic, clinical, and MRI variables were checked for normality with the Kolmogorov-Smirnov test and histogram inspection. Lesion volumes and normalized lesion volumes were log-transformed. Nonparametric testing was used to assess group differences in demographic variables and EDSS. Multivariate general linear model analyses were performed to assess group differences in global MRI and cognitive variables, with sex, age, and education entered as covariates. Bonferroni-corrected values of p < 0.05 were considered statistically significant.

Voxel-wise centrality values were compared between groups with general linear model testing using a cluster-wise permutation-based method18 at p < 0.05, with sex, age, and education as covariates. To reduce the number of statistical tests, all cognitive groups were compared to HCs only, except for a direct comparison between CI and CP patients. We evaluated the effect size of mean centrality changes within the brain regions that were abnormal in CI patients compared to HCs for each patient group by calculating the z scores compared to HCs.

RESULTS

Demographic, clinical, and MRI characteristics.

All patients.

The overall patient cohort was mildly disabled, yielding a median EDSS score of 3.0 and a mean average cognition z score of −0.80. The 3 cognitive domains most commonly impaired (scoring below 2 SDs compared to HCs) were information processing speed (24% of patients, mean z = −1.18), working memory (20%, mean z = −1.08), and executive functioning (19%, mean z = −1.02). Figure 1 depicts mean cognitive z scores for the entire patient group and patient subgroups.

Figure 1
Figure 1 Severity of cognitive impairments in patient groups compared to healthy controls

CI = cognitively impaired patient group; CP = cognitively preserved patient group; MCI = mildly cognitively impaired patient group.

Patient groups.

Of all 332 patients, 87 patients were CI (26%), 65 were MCI (20%), and 180 were CP (54%). Demographic, clinical, and MRI scores for the different patient groups are shown in table 1. The CI group was significantly older than the CP group (51 vs 46 years, respectively, p < 0.01), contained more men (40% vs 26%, respectively), and had a longer symptom duration (17 vs 14 years, respectively, p = 0.02), higher EDSS (median 4.0 vs 3.0, respectively, p < 0.01), higher HADS depression score (median 3 vs 2, respectively, p = 0.02), lower normalized brain volume (1.40 ± 0.09 vs 1.48 ± 0.06 L, respectively, p < 0.01), and higher lesion volumes (median 19 vs 8 mL, respectively, p < 0.01). Lesion probability maps for the different patient groups showed similar lesion locations for all groups, although a more extensive lesion distribution in CI (figure e-2). For patients who ever used disease-modifying treatment, current type or total duration was not significantly different between CI and CP patients.

View this table:
Table 1

Demographic, clinical, and MRI characteristics for patient groups

Centrality changes in patient groups.

The results of the voxel-wise comparisons between groups are shown for eigenvector centrality in figure 2 and for degree centrality in figure 3, which were very similar. Therefore, all other figures and tables focus on eigenvector centrality only. The mean eigenvector centrality maps for the different patient groups and HC group are shown in figure e-3. The mean eigenvector centrality values are shown in table e-1, and effect sizes are given in figure 4 for the significantly abnormal brain regions in CI patients compared to HCs.

Figure 2
Figure 2 Eigenvector centrality changes in patient groups

Red/yellow: voxels with significantly higher centrality. Blue/light blue: voxels with significantly lower centrality (x = 2, y = −10, z = 40). Outside of the masks, translucent colors depict the directionality of nonsignificant changes. Images adhere to the radiologic anatomic convention. CI = cognitively impaired patient group; CP = cognitively preserved patient group; HC = healthy controls; MCI = mildly cognitively impaired patient group.

Figure 3
Figure 3 Degree centrality changes in patient groups

Red/yellow: voxels with significantly higher centrality. Blue/light blue: voxels with significantly lower centrality (x = 2, y = −10, z = 40). Outside of the masks, translucent colors depict the directionality of nonsignificant changes. Images adhere to the radiologic anatomic convention. CI = cognitively impaired patient group; CP = cognitively preserved patient group; HC = healthy controls; MCI = mildly cognitively impaired patient group.

Figure 4
Figure 4 Effect sizes of eigenvector centrality changes

(A) Mean centrality z scores in increased centrality regions for patient groups compared to healthy controls (HCs). (B) Mean centrality z scores in decreased centrality regions for patient groups compared to HCs. Note that the selection of regions for the effect size calculation (z scores compared to HCs) was based on the CI vs HC contrast to ensure comparability of the bars. CI = cognitively impaired patient group; CP = cognitively preserved patient group; MCI = mildly cognitively impaired patient group.

CI patients vs HCs.

Compared to HCs, the CI patient group displayed regions with increased and decreased centrality. A significant increase was found in the posterior cingulate gyrus, precuneus, bilateral angular gyrus, and dorsomedial prefrontal cortex (i.e., regions that form the so-called default-mode network). Other regions with increased centrality included the anterior part of the thalamus, the anterior cerebellar lobe, and several frontal areas including the right frontal operculum, the bilateral frontal pole, the middle parts of the superior gyrus, and the middle frontal gyrus. Decreased centrality was found in a large part of the occipital lobe, the bilateral sensorimotor cortex, the bilateral hippocampi, the right caudate nucleus, and the right middle temporal lobe. The left caudate nucleus additionally showed decreased centrality but only with the use of eigenvector centrality.

MCI patients vs HCs.

The MCI group showed increased centrality in regions similar to the CI group but less extensive. The significant clusters in the posterior cingulate gyrus, the angular gyri, and the frontal regions were smaller and showed a smaller effect size compared to the CI group, while the precuneus did not show increased centrality in this group. The anterior cerebellar lobe and right angular gyrus also showed increased centrality in this group, but only with the use of eigenvector centrality. Decreased centrality was seen mostly in the bilateral sensorimotor cortex and the occipital lobe.

CP patients vs HCs.

CP patients showed no increased centrality for eigenvector centrality and in only part of the posterior cingulate cortex for degree centrality. Two regions displayed decreased centrality, namely the bilateral sensorimotor cortex and the occipital lobe.

Cognitively impaired vs cognitively preserved patients.

When CI and CP patients were directly compared, CI patients displayed increased centrality, mostly in the default-mode network, i.e., the posterior cingulate gyrus, the precuneus, the bilateral angular gyrus, and in the middle parts of the superior and middle frontal gyri (figure 2). Decreased centrality was restricted mostly to the right middle temporal gyrus. Subsequently, we evaluated these results on possible effects of depression by excluding all patients scoring >8 on the HADS depression subscale (figure e-4), as well as brain atrophy, by adding normalized brain volume as a covariate, and clinical phenotypes, by assessing the (not significant) interaction between MS phenotypes (relapsing-remitting, secondary progressive, and primary progressive multiple sclerosis) and cognitive status (CI or CP). None of these additional analyses influenced the aforementioned results.

DISCUSSION

In this study, we examined changes in the centrality or importance of brain regions in a large cohort of patients with MS with various degrees of cognitive impairment. The cohort was subdivided into CP (54%), MCI (26%), and CI (20%) patients, percentages comparable to previous literature.19 Our functional network results showed more severe network abnormalities in patients with more advanced cognitive impairment. Most distinctive was the marked shift in functional network balance toward an increased importance of the default-mode network in CI patients compared to both CP patients and HCs.

The default-mode network was originally described as a group of brain regions exhibiting decreases from baseline activity during goal-directed behavior, suggesting the existence of a baseline default mode of brain function that is suspended during goal-directed behaviors.20 It was initially thought to be involved mainly in introspective and self-referential thought,21 but more recent studies also point out a role for this network as a structural core or connectivity backbone that facilitates cognitive processing22 and directs the balance between internal and external attention.23 The posterior cingulate gyrus, the central core of the default-mode network, has been described as one of the most important hubs in the brain24 and was indicated to be abnormal in MS in our initial centrality pilot study.5 Resting-state fMRI studies in patients with MS have shown increased25,26 and decreased14,27,28 default-mode network connectivity, and both these changes were found to be related to poorer cognitive performance in different patient groups.

A previous task-related fMRI study investigating the default-mode network in MS showed less deactivation of the default-mode network in patients who were CI during the N-back task.29 Together, these functional connectivity and functional (de)activation studies have established the importance of the default-mode network abnormalities in cognitive decline. The current study moves beyond these earlier studies by showing that, under pressure of disease, the hierarchy of the entire brain network shifts, and the default-mode network becomes more important in CI. The shifted balance toward the default-mode network at rest and the impaired adequate suspension of this network during the switch from rest to task-related processing could represent an overall default-mode network dysfunction underlying cognitive impairment in MS. A similar mechanism was also proposed to underlie cognitive decline in normal aging.30

Apart from the default-mode network, the thalamus and cerebellum also showed increased centrality in CI patients compared to HCs. These regions serve a wide array of functions, including the modulation of cognitive processes,31,32 and show extensive damage in MS. The thalamus seems to be specifically and severely affected, with high rates of atrophy and increased functional connectivity already observable early in the course of MS.7,31 Cerebellar changes have also been reported in MS, including extensive demyelination and atrophy.33,34 The increased centrality we observed in our study in both the thalamus and the cerebellum was just as severe (based on z-score deviation, figure 3) and even slightly more widespread (figure 2) in the MCI group compared to the CI group. This could indicate that an increased centrality of the thalamus and cerebellum is a relatively early phenomenon in the transition toward cognitive impairment, whereas an extensive involvement of the default-mode network occurs only in more severe cognitive impairment.

Several brain regions demonstrated decreased centrality in the patient groups compared to HCs, including the sensorimotor cortex and the occipital lobe, indicating a lower amount of communication between these regions and the rest of the brain network, possibly due to damaged structural connections. A decreased centrality in these regions was already found in our previous eigenvector centrality study investigating general MS effects5 on a smaller subset of the current cohort and in a recent report on Alzheimer disease using the same method.6 In the current study, these decreases were found in all patient groups, indicating a more general disease effect not specifically related to cognitive status. Our previous data already indicated a relation between decreased centrality in the sensorimotor areas and EDSS score, but the relation between decreased occipital centrality and disturbances in the visual system remains to be determined with newer technologies such as optical coherence tomography. In addition, the bilateral hippocampus, right caudate nucleus, and right middle temporal gyrus showed decreases in centrality that were specific to the CI group compared to HCs. Hippocampal pathology has been extensively reported in MS, including demyelination35 and atrophy,36 with clear relations to memory dysfunction.37 Atrophy of the caudate has also been related to cognition in MS, especially working memory.38

Several limitations apply to the current work. First, because the data used in this study were cross-sectional, it is difficult to disentangle the causal chain of events taking place when patients progress toward a state of cognitive impairment, highlighting the crucial need for future longitudinal studies. For example, although the observed changes in centrality were very expansive and severe only in CI, we cannot definitively exclude that these might still represent some ineffective form of compensatory reorganization or a loss of inhibition not directly related to cognition. Second, because progressive MS remains poorly understood, it would be interesting to see whether early network changes are predictive of earlier conversion to secondary progressive MS and to earlier or more severe cognitive impairment. Third, the application of a voxel-wise approach in this study resulted in a precise localization of changes on a functional level but might be more prone to artifacts due to registration errors, small regional differences in brain volume, or effects of signal distortion, indicating the continued need for optimized acquisition techniques and processing pipelines. Finally, the application of other functional brain imaging tools such as magnetoencephalography could also help further elucidate the underlying neuronal mechanisms that lead to changes in the centrality of brain regions at a much higher temporal resolution.

Using advanced network analysis, this study sheds new light on the complex network changes underlying cognitive impairment in MS. It stresses the importance of the default-mode network within the entire network of the brain, as well as the thalamus and cerebellum as key areas for cognition. Future (longitudinal) studies may now focus on eliciting or predicting the onset and temporal dynamics of these clinically eloquent network changes.

AUTHOR CONTRIBUTIONS

Drafting/revising the manuscript: all authors. Study concept or design: A.J.C.E., J.J.G.G., M.M.S. Acquisition of data: M.M.S., M.D.S. Analysis or interpretation of the data: A.J.C.E., K.A.M., T.M.W., M.M.S. Statistical analysis: A.J.C.E., K.A.M., T.M.W., A.M.W., M.M.S. Study supervision and coordination: J.J.G.G., M.M.S. Obtaining funding: B.M.J.U., F.B., J.J.G.G., M.M.S.

STUDY FUNDING

This study was supported by the Dutch MS Research Foundation, grants numbers 08-650, 13-820, and 14-358e.

DISCLOSURE

A. Eijlers receives research support from the Dutch MS Research Foundation, grant number 14-358e. K. Meijer receives research support from a research grant from Biogen Idec. T. Wassenaar and M. Steenwijk report no disclosures relevant to the manuscript. B. Uitdehaag has received consultation fees from Biogen Idec, Novartis, Merck-Serono, and Danone Research. F. Barkhof serves on the editorial boards of Brain, European Radiology, the Journal of Neurology, Neurosurgery & Psychiatry, Neurology, Multiple Sclerosis, and Neuroradiology and serves as a consultant for Bayer-Shering Pharma, Sanofi-Aventis, Biogen-Idec, TEVA Pharmaceuticals, Genzyme, Merck-Serono, Novartis, Roche, Synthon, Jansen Research, and Lundbeck. A. Wink reports no disclosures relevant to the manuscript. J. Geurts serves on the editorial boards of Multiple Sclerosis Journal, BMC Neurology, Multiple Sclerosis International, and Neurology and the Scientific Advisory Board of the Dutch MS Research Foundation, MS Academia, and Merck-Serono and has served as a consultant for Merck-Serono, Biogen Idec, Novartis, Genzyme, and Teva Pharmaceuticals. M. 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, Novartis, and Biogen. Go to Neurology.org for full disclosures.

Footnotes

  • ↵* These authors contributed equally to this work.

  • Go to Neurology.org for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.

  • Supplemental data at Neurology.org

  • Received July 25, 2016.
  • Accepted in final form December 12, 2016.

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