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Jellinger KA. Cognitive impairment in multiple sclerosis: from phenomenology to neurobiological mechanisms. J Neural Transm (Vienna) 2024; 131:871-899. [PMID: 38761183 DOI: 10.1007/s00702-024-02786-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Accepted: 05/08/2024] [Indexed: 05/20/2024]
Abstract
Multiple sclerosis (MS) is an autoimmune-mediated disease of the central nervous system characterized by inflammation, demyelination and chronic progressive neurodegeneration. Among its broad and unpredictable range of clinical symptoms, cognitive impairment (CI) is a common and disabling feature greatly affecting the patients' quality of life. Its prevalence is 20% up to 88% with a wide variety depending on the phenotype of MS, with highest frequency and severity in primary progressive MS. Involving different cognitive domains, CI is often associated with depression and other neuropsychiatric symptoms, but usually not correlated with motor and other deficits, suggesting different pathophysiological mechanisms. While no specific neuropathological data for CI in MS are available, modern research has provided evidence that it arises from the disease-specific brain alterations. Multimodal neuroimaging, besides structural changes of cortical and deep subcortical gray and white matter, exhibited dysfunction of fronto-parietal, thalamo-hippocampal, default mode and cognition-related networks, disruption of inter-network connections and involvement of the γ-aminobutyric acid (GABA) system. This provided a conceptual framework to explain how aberrant pathophysiological processes, including oxidative stress, mitochondrial dysfunction, autoimmune reactions and disruption of essential signaling pathways predict/cause specific disorders of cognition. CI in MS is related to multi-regional patterns of cerebral disturbances, although its complex pathogenic mechanisms await further elucidation. This article, based on systematic analysis of PubMed, Google Scholar and Cochrane Library, reviews current epidemiological, clinical, neuroimaging and pathogenetic evidence that could aid early identification of CI in MS and inform about new therapeutic targets and strategies.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, Vienna, A-1150, Austria.
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2
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Pontillo G, Cepas MB, Broeders TAA, Koubiyr I, Schoonheim MM. Network Analysis in Multiple Sclerosis and Related Disorders. Neuroimaging Clin N Am 2024; 34:375-384. [PMID: 38942522 DOI: 10.1016/j.nic.2024.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
Multiple sclerosis (MS) is a neuroinflammatory and neurodegenerative disease of the central nervous system, commonly featuring disability and cognitive impairment. The pathologic hallmark of MS lies in demyelination and hence impaired structural and functional neuronal pathways. Recent studies have shown that MS shows extensive structural disconnection of key network hub areas like the thalamus, combined with a functional network reorganization that can mostly be related to poorer clinical functioning. As MS can, therefore, be considered a network disorder, this review outlines recent innovations in the field of network neuroscience in MS.
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Affiliation(s)
- Giuseppe Pontillo
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands; MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands.
| | - Mar Barrantes Cepas
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands
| | - Tommy A A Broeders
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands
| | - Ismail Koubiyr
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, De Boelelaan 1117, 1081 HV Amsterdam, Postbus 7057, 1007 MB, Amsterdam, The Netherlands
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3
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Koubiyr I, Krijnen EA, Eijlers AJC, Dekker I, Hulst HE, Uitdehaag BMJ, Barkhof F, Geurts JJG, Schoonheim MM. Longitudinal fibre-specific white matter damage predicts cognitive decline in multiple sclerosis. Brain Commun 2024; 6:fcae018. [PMID: 38344654 PMCID: PMC10853982 DOI: 10.1093/braincomms/fcae018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 12/21/2023] [Accepted: 01/23/2024] [Indexed: 03/02/2024] Open
Abstract
During the course of multiple sclerosis, many patients experience cognitive deficits which are not simply driven by lesion number or location. By considering the full complexity of white matter structure at macro- and microstructural levels, our understanding of cognitive impairment in multiple sclerosis may increase substantially. Accordingly, this study aimed to investigate specific patterns of white matter degeneration, the evolution over time, the manifestation across different stages of the disease and their role in cognitive impairment using a novel fixel-based approach. Neuropsychological test scores and MRI scans including 30-direction diffusion-weighted images were collected from 327 multiple sclerosis patients (mean age = 48.34 years, 221 female) and 95 healthy controls (mean age = 45.70 years, 55 female). Of those, 233 patients and 61 healthy controls had similar follow-up assessments 5 years after. Patients scoring 1.5 or 2 standard deviations below healthy controls on at least two out of seven cognitive domains (from the Brief Repeatable Battery of Neuropsychological Tests, BRB-N) were classified as mildly cognitively impaired or cognitively impaired, respectively, or otherwise cognitively preserved. Fixel-based analysis of diffusion data was used to calculate fibre-specific measures (fibre density, reflecting microstructural diffuse axonal damage; fibre cross-section, reflecting macrostructural tract atrophy) within atlas-based white matter tracts at each visit. At baseline, all fixel-based measures were significantly worse in multiple sclerosis compared with healthy controls (P < 0.05). For both fibre density and fibre cross-section, a similar pattern was observed, with secondary progressive multiple sclerosis patients having the most severe damage, followed by primary progressive and relapsing-remitting multiple sclerosis. Similarly, damage was least severe in cognitively preserved (n = 177), more severe in mildly cognitively impaired (n = 63) and worst in cognitively impaired (n = 87; P < 0.05). Microstructural damage was most pronounced in the cingulum, while macrostructural alterations were most pronounced in the corticospinal tract, cingulum and superior longitudinal fasciculus. Over time, white matter alterations worsened most severely in progressive multiple sclerosis (P < 0.05), with white matter atrophy progression mainly seen in the corticospinal tract and microstructural axonal damage worsening in cingulum and superior longitudinal fasciculus. Cognitive decline at follow-up could be predicted by baseline fixel-based measures (R2 = 0.45, P < 0.001). Fixel-based approaches are sensitive to white matter degeneration patterns in multiple sclerosis and can have strong predictive value for cognitive impairment. Longitudinal deterioration was most marked in progressive multiple sclerosis, indicating that degeneration in white matter remains important to characterize further in this phenotype.
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Affiliation(s)
- Ismail Koubiyr
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Eva A Krijnen
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States
| | - Anand J C Eijlers
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Iris Dekker
- MS Center Amsterdam, Rehabilitation, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Hanneke E Hulst
- Health, Medical and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden 2333 AK, The Netherlands
| | - Bernard M J Uitdehaag
- MS Center Amsterdam, Neurology, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Frederik Barkhof
- MS Center Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Jeroen J G Geurts
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
| | - Menno M Schoonheim
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam 1081 HV, The Netherlands
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4
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Li F, Zong W, Xin C, Ren F, Li N, Li H, Li X, Wu L, Dai Z, Chen W, Li M, Gao F, Wang G. Unlocking the link: how hippocampal glutathione-glutamate coupling predicts cognitive impairment in multiple sclerosis patients. Cereb Cortex 2024; 34:bhad400. [PMID: 37943724 DOI: 10.1093/cercor/bhad400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/24/2023] [Accepted: 10/02/2023] [Indexed: 11/12/2023] Open
Abstract
Cognitive impairment is a common symptom of multiple sclerosis and profoundly impacts quality of life. Glutathione (GSH) and glutamate (Glu) are tightly linked in the brain, participating in cognitive function. However, GSH-Glu couplings in cognitive brain regions and their relationship with cognitive impairment in relapsing-remitting multiple sclerosis (RRMS) remains unclear. Forty-one RRMS patients and 43 healthy controls underwent magnetic resonance spectroscopy to measure GSH and Glu levels in the posterior cingulate cortex, medial prefrontal cortex and left hippocampus. Neuropsychological tests were used to evaluate the cognitive function. The Glu/GSH ratio was used to indicate the coupling between GSH and Glu and was tested as a predictor of cognitive performance. The results show that RRMS patients exhibited reduced hippocampal GSH and Glu levels, which were found to be significant predictors of worse verbal and visuospatial memory, respectively. Moreover, GSH levels were dissociated from Glu levels in the left hippocampus of RRMS patients. Hippocampal Glu/GSH ratio is significantly correlated with processing speed and has a greater predictive effect. Here we show the hippocampal Glu/GSH ratio could serve as a new potential marker for characterizing cognitive impairment in RRMS, providing a new direction for clinical detection of cognitive impairment.
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Affiliation(s)
- Fuyan Li
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jing-wu Road No. 324, Jinan 250021, China
| | - Wei Zong
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jing-wu Road No. 324, Jinan 250021, China
| | - Chenxi Xin
- School of International Education, Xinxiang Medical University, No. 601, Jinsui Avenue, Hongqi District, Xinxiang 453003, China
| | - Fuxin Ren
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jing-wu Road No. 324, Jinan 250021, China
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jing-wu Road No. 324, Jinan,250021 China
| | - Ning Li
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jing-wu Road No. 324, Jinan 250021, China
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jing-wu Road No. 324, Jinan,250021 China
| | - Honghao Li
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jing-wu Road No. 324, Jinan 250021, China
| | - Xiao Li
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jing-wu Road No. 324, Jinan 250021, China
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jing-wu Road No. 324, Jinan,250021 China
| | - Lili Wu
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, No. 16, Lincui Road, Beijing 100101, China
| | - Zongrui Dai
- Department of Biostatistics, University of Michigan, 500 S. State Street, Ann Arbor, Ann Arbor, MI 48109, United States
| | - Weibo Chen
- Philips Healthcare, Building 718, Lingshi Road, Jing'an District, Shanghai 200072, China
| | - Muwei Li
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States
| | - Fei Gao
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jing-wu Road No. 324, Jinan 250021, China
| | - Guangbin Wang
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jing-wu Road No. 324, Jinan 250021, China
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5
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Schwarz K, Schmitz F. Synapse Dysfunctions in Multiple Sclerosis. Int J Mol Sci 2023; 24:ijms24021639. [PMID: 36675155 PMCID: PMC9862173 DOI: 10.3390/ijms24021639] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 01/11/2023] [Accepted: 01/12/2023] [Indexed: 01/18/2023] Open
Abstract
Multiple sclerosis (MS) is a chronic neuroinflammatory disease of the central nervous system (CNS) affecting nearly three million humans worldwide. In MS, cells of an auto-reactive immune system invade the brain and cause neuroinflammation. Neuroinflammation triggers a complex, multi-faceted harmful process not only in the white matter but also in the grey matter of the brain. In the grey matter, neuroinflammation causes synapse dysfunctions. Synapse dysfunctions in MS occur early and independent from white matter demyelination and are likely correlates of cognitive and mental symptoms in MS. Disturbed synapse/glia interactions and elevated neuroinflammatory signals play a central role. Glutamatergic excitotoxic synapse damage emerges as a major mechanism. We review synapse/glia communication under normal conditions and summarize how this communication becomes malfunctional during neuroinflammation in MS. We discuss mechanisms of how disturbed glia/synapse communication can lead to synapse dysfunctions, signaling dysbalance, and neurodegeneration in MS.
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Baghdadi M, Badwey ME, Khalil M, Dawoud RM. Brain magnetic resonance imaging surface-based analysis and cortical thickness measurement in relapsing remission multiple sclerosis. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2022. [DOI: 10.1186/s43055-021-00686-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Damage occurs in the brain tissue in MS which appears normal on standard conventional imaging (normal appearing brain tissue). This slow, evolving damage can be monitored by nonconventional advanced MR imaging techniques. New techniques for the measurement of cortical thickness have been validated against histological analysis and manual measurements. The aim of our study was to study the role of MRI surface-based analysis and cortical thickness measurement in the evaluation of patients with Relapsing Remitting Multiple Sclerosis and to detect if there is localized rather than generalized cortical atrophy in Multiple Sclerosis patients and correlating these findings with clinical data.
Results
30 patients and 30 healthy control were included in this study and they were subjected to cortical thickness analysis using MRI. The patients in our study showed decreased thickness of the precentral, paracentral, postcentral, posterior cingulate cortices and mean cortical thickness in both hemispheres when compared with the normal control group. Statistical analysis was significant (P value < 0.05) for the precentral, paracentral, postcentral, posterior cingulate cortices and mean cortical thickness in both hemispheres. On the other hand, statistical analysis was not significant (P value > 0.05) for other cortices. There was a significant negative correlation between the precentral, paracentral, postcentral, posterior cingulate cortices and mean cortical thickness in both hemispheres and EDSS scores with correlation coefficients ranging from − 0.9878 to − 0.7977.
Conclusions
MRI and post-processing segmentation analysis for cortical thickness is non-invasive imaging techniques that can increase the level of diagnostic confidence in diagnosis of MS patients and should be included as routine modality when evaluating patients with MS.
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Al-Iedani O, Lea R, Ribbons K, Ramadan S, Lechner-Scott J. Neurometabolic changes in multiple sclerosis: Fingolimod versus beta interferon or glatiramer acetate therapy. J Neuroimaging 2022; 32:1109-1120. [PMID: 35922880 DOI: 10.1111/jon.13032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 07/20/2022] [Accepted: 07/22/2022] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND AND PURPOSE Fingolimod has been shown to be more effective in reducing relapse rate and disability than injectable therapies in clinical trials. An increase in N-acetylaspartate (NAA) as measured by MR spectroscopy is correlated with maintaining axonal metabolic functions. This study compared the neurometabolic and volumetric changes in relapsing-remitting multiple sclerosis (RRMS) patients on fingolimod or injectable therapies with healthy controls (HCs). METHODS Ninety-eight RRMS (52 on fingolimod, 46 on injectable therapies (27 on glatiramer acetate and 19 on interferon) were age and sex-matched to 51 HCs. RRMS patients underwent cognitive, fatigue, and mental health assessments, as well as an Expanded disability status scale (EDSS). MRI/S was acquired from the hippocampus, posterior cingulate gyrus (PCG), and prefrontal cortex (PFC). Volumetric and neurometabolic measures were compared across cohorts using a univariate general linear model and correlated with clinical severity and neuropsychological scores. RESULTS Clinical parameters, MR-volumetric, and neurometabolic profiles showed no differences between treatment groups (p > .05). Compared to HCs, both RRMS cohorts showed volume changes in white matter (-13%), gray matter (-16%), and cerebral spinal fluid (CSF) (+17-23%), as well as reduced NAA (-17%, p = .001, hippocampus), (-7%, p = .001, PCG), and (-9%, p = .001, PFC). MRI/S metrics in three regions were moderately correlated with cognition and fatigue functions. CONCLUSION While both treatment arms showed overall similar volumetric and neurometabolic profiles, longitudinal studies are warranted to clarify neurometabolic changes and associations with treatment efficacy.
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Affiliation(s)
- Oun Al-Iedani
- School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia.,Hunter Medical Research Institute, New Lambton, New South Wales, Australia
| | - Rodney Lea
- Hunter Medical Research Institute, New Lambton, New South Wales, Australia.,Institute of Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Karen Ribbons
- Hunter Medical Research Institute, New Lambton, New South Wales, Australia
| | - Saadallah Ramadan
- Hunter Medical Research Institute, New Lambton, New South Wales, Australia.,School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, New Lambton, New South Wales, Australia.,School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia.,Department of Neurology, John Hunter Hospital, New Lambton Heights, New South Wales, Australia
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8
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Manglani HR, Fountain-Zaragoza S, Shankar A, Nicholas JA, Prakash RS. Employing Connectome-Based Models to Predict Working Memory in Multiple Sclerosis. Brain Connect 2022; 12:502-514. [PMID: 34309408 PMCID: PMC10039278 DOI: 10.1089/brain.2021.0037] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Introduction: Individuals with multiple sclerosis (MS) are vulnerable to deficits in working memory (WM), but the search for neural correlates of WM within circumscribed areas has been inconclusive. Given the widespread neural alterations observed in MS, predictive modeling approaches that capitalize on whole-brain connectivity may better capture individual differences in WM. Materials and Methods: We applied connectome-based predictive modeling to functional magnetic resonance imaging data from WM tasks in two independent samples with relapsing-remitting MS. In the internal sample (ninternal = 36), cross-validation was used to train a model to predict accuracy on the Paced Visual Serial Addition Test from functional connectivity. We hypothesized that this MS-specific model would successfully predict performance on the N-back task in the validation cohort (nvalidation = 36). In addition, we assessed the generalizability of existing WM networks derived in healthy young adults to these samples, and we explored anatomical differences between the healthy and MS networks. Results: We successfully derived an MS-specific predictive model of WM in the internal sample (full: rs = 0.47, permuted p = 0.011), but the predictions were not significant in the validation cohort (rs = -0.047; p = 0.78, mean squared error [MSE] = 0.006, R2 = -2.21%). In contrast, the healthy networks successfully predicted WM in both MS samples (internal: rs = 0.33 p = 0.049, MSE = 0.009, R2 = 13.4%; validation cohort: rs = 0.46, p = 0.005, MSE = 0.005, R2 = 16.9%), demonstrating their translational potential. Discussion: Functional networks identified in a large sample of healthy individuals predicted significant variance in WM in MS. Networks derived in small samples of people with MS may have limited generalizability, potentially due to disease-related heterogeneity. The robustness of models derived in large clinical samples warrants further investigation. ClinicalTrials.gov ID: NCT03244696.
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Affiliation(s)
- Heena R Manglani
- Department of Psychology, The Ohio State University, Columbus, Ohio, USA
- Center for Cognitive and Behavioral Brain Imaging, The Ohio State University, Columbus, Ohio, USA
| | - Stephanie Fountain-Zaragoza
- Department of Psychology, The Ohio State University, Columbus, Ohio, USA
- Center for Cognitive and Behavioral Brain Imaging, The Ohio State University, Columbus, Ohio, USA
| | - Anita Shankar
- Department of Psychology, The Ohio State University, Columbus, Ohio, USA
- Center for Cognitive and Behavioral Brain Imaging, The Ohio State University, Columbus, Ohio, USA
| | | | - Ruchika Shaurya Prakash
- Department of Psychology, The Ohio State University, Columbus, Ohio, USA
- Center for Cognitive and Behavioral Brain Imaging, The Ohio State University, Columbus, Ohio, USA
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Ruiz-Rizzo AL, Bublak P, Kluckow S, Finke K, Gaser C, Schwab M, Güllmar D, Müller HJ, Witte OW, Rupprecht S. Neural distinctiveness of fatigue and low sleep quality in multiple sclerosis. Eur J Neurol 2022; 29:3017-3027. [PMID: 35699354 DOI: 10.1111/ene.15445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 06/08/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND PURPOSE Fatigue and low sleep quality in multiple sclerosis (MS) are closely related symptoms. Here, the associations between the brain's functional connectivity (FC) and fatigue and low sleep quality were investigated to determine the degree of neural distinctiveness of these symptoms. METHOD A hundred and four patients with relapsing-remitting MS (age 38.9 ± 10.2 years, 66 females) completed the Modified Fatigue Impact Scale and the Pittsburgh Sleep Quality Index and underwent resting-state functional magnetic resonance imaging. FC was analyzed using independent-component analysis in sensorimotor, default-mode, fronto-parietal and basal-ganglia networks. Multiple linear regression models allowed us to test the association between FC and fatigue and sleep quality whilst controlling for one another as well as for demographic, disease-related and imaging variables. RESULTS Higher fatigue correlated with lower sleep quality (r = 0.54, p < 0.0001). Higher fatigue was associated with lower FC of the precentral gyrus in the sensorimotor network, the precuneus in the posterior default-mode network and the superior frontal gyrus in the left fronto-parietal network, independently of sleep quality. Lower sleep quality was associated with lower FC of the left intraparietal sulcus in the left fronto-parietal network, independently of fatigue. Specific associations were found between fatigue and the sensorimotor network's global FC and between low sleep quality and the left fronto-parietal network's global FC. CONCLUSION Despite the high correlation between fatigue and low sleep quality in the clinical picture, our findings clearly indicate that, on the neural level, fatigue and low sleep quality in MS are associated with decreased FC in distinct functional brain networks.
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Affiliation(s)
- Adriana L Ruiz-Rizzo
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich, Germany.,Department of Neurology, Jena University Hospital, Jena, Germany
| | - Peter Bublak
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Steffen Kluckow
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Kathrin Finke
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich, Germany.,Department of Neurology, Jena University Hospital, Jena, Germany
| | - Christian Gaser
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Matthias Schwab
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Daniel Güllmar
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Hermann J Müller
- Department of Psychology, General and Experimental Psychology Unit, LMU Munich, Munich, Germany
| | - Otto W Witte
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - Sven Rupprecht
- Department of Neurology, Jena University Hospital, Jena, Germany
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10
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Chitnis T, Vandercappellen J, King M, Brichetto G. Symptom Interconnectivity in Multiple Sclerosis: A Narrative Review of Potential Underlying Biological Disease Processes. Neurol Ther 2022; 11:1043-1070. [PMID: 35680693 PMCID: PMC9338216 DOI: 10.1007/s40120-022-00368-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 05/16/2022] [Indexed: 11/18/2022] Open
Abstract
Introduction Fatigue, cognitive impairment, depression, and pain are highly prevalent symptoms in multiple sclerosis (MS). These often co-occur and may be explained by a common etiology. By reviewing existing literature, we aimed to identify potential underlying biological processes implicated in the interconnectivity between these symptoms. Methods A literature search was conducted to identify articles reporting research into the biological mechanisms responsible for the manifestation of fatigue, cognitive impairment, depression, and pain in MS. PubMed was used to search for articles published from July 2011 to July 2021. We reviewed and assessed findings from the literature to identify biological processes common to the symptoms of interest. Results Of 693 articles identified from the search, 252 were selected following screening of titles and abstracts and assessing reference lists of review articles. Four biological processes linked with two or more of the symptoms of interest were frequently identified from the literature: (1) direct neuroanatomical changes to brain regions linked with symptoms of interest (e.g., thalamic injury associated with cognitive impairment, fatigue, and depression), (2) pro-inflammatory cytokines associated with so-called ‘sickness behavior,’ including manifestation of fatigue, transient cognitive impairment, depression, and pain, (3) dysregulation of monoaminergic pathways leading to depressive symptoms and fatigue, and (4) hyperactivity of the hypothalamic–pituitary-adrenal (HPA) axis as a result of pro-inflammatory cytokines promoting the release of brain noradrenaline, serotonin, and tryptophan, which is associated with symptoms of depression and cognitive impairment. Conclusion The co-occurrence of fatigue, cognitive impairment, depression, and pain in MS appears to be associated with a common set of etiological factors, namely neuroanatomical changes, pro-inflammatory cytokines, dysregulation of monoaminergic pathways, and a hyperactive HPA axis. This association of symptoms and biological processes has important implications for disease management strategies and, eventually, could help find a common therapeutic pathway that will impact both inflammation and neuroprotection. Supplementary Information The online version contains supplementary material available at 10.1007/s40120-022-00368-2.
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Affiliation(s)
- Tanuja Chitnis
- Department of Neurology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.
| | | | - Miriam King
- Novartis Pharma AG, Fabrikstrasse 12-2, 4056, Basel, Switzerland
| | - Giampaolo Brichetto
- Associazione Italiana Sclerosi Multipla Rehabilitation Center, Via Operai, 30, 16149, Genoa, GE, Italy
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Rocca MA, Schoonheim MM, Valsasina P, Geurts JJG, Filippi M. Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective. Neuroimage Clin 2022; 35:103076. [PMID: 35691253 PMCID: PMC9194954 DOI: 10.1016/j.nicl.2022.103076] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/01/2022] [Accepted: 06/02/2022] [Indexed: 01/12/2023]
Abstract
Functional MRI is able to detect adaptive and maladaptive abnormalities at different MS stages. Increased fMRI activity is a feature of early MS, while progressive exhaustion of adaptive mechanisms is detected later on in the disease. Collapse of long-range connections and impaired hub integration characterize MS network reorganization. Time-varying connectivity analysis provides useful and complementary pieces of information to static functional connectivity. New perspectives might be the use of multimodal MRI and artificial intelligence.
Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.
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Affiliation(s)
- Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy.
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
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12
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Siyah Mansoory M, Chehreh A, Khoshgard K, Rashidi I, Ebrahiminia A. Effective Connectivity within the Papez Circuit in the Multiple Sclerosis Patients: A Comparative Study Using Resting-State fMRI. J Biomed Phys Eng 2022; 12:149-160. [PMID: 35433517 PMCID: PMC8995756 DOI: 10.31661/jbpe.v0i0.2003-1090] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 05/06/2020] [Indexed: 06/14/2023]
Abstract
Background Multiple sclerosis (MS) disease causes structural and functional damage to brain. Structural imaging of the MS-induced damage cannot adequately describe the functional impairment of the brain in MS patients. Therefore, it seems that advanced functional imaging analysis such as functional magnetic resonance imaging (fMRI) data is needed for better management of this disease. Objective The aim of present study was to evaluate the effective connectivity within the Papez circuit in MS patients using resting-state fMRI. Material and Methods In this cross-sectional analytical study, 22 healthy individuals and 24 patients with MS underwent resting-state fMRI. After pre-processing of the obtained data, the time series of Cingulate gyrus (CG), Para hippocampus gyrus (PHG), anterior thalamic nuclei (ATN), Mammillary body (MB), and Hippocampus (HPC) were extracted as the main Papez circuit components. The obtained time series were statistically analyzed as an input of the dynamic causal model in order to evaluate the effective connectivity in the Papez circuit. Results The power of effective connectivity between each pair of tested nodes in Papez circuit was significantly lower in MS patients than healthy subjects. Also, the effective connectivity level of MS patients in direction of HPC→ATN was higher in men than women. In addition, effective self-connection in CG→CG and MB→MB regions in healthy subjects were higher in women than them in men. Conclusion The present study reveals significant difference in effective connectivity of the Papez nodes in MS patients than control group, which can be exploited to diagnosis and predict or evaluate the treatment response of these patients.
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Affiliation(s)
- Meysam Siyah Mansoory
- PhD, Department of Biomedical Engineering, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Ava Chehreh
- MSc Student, Student Research Committee, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Karim Khoshgard
- PhD, Department of Medical Physics, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Iraj Rashidi
- PhD, Department of Anatomy, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Ali Ebrahiminia
- PhD, Department of Biochemistry & Biophysics, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran
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Ye C, Huang J, Liang L, Yan Z, Qi Z, Kang X, Liu Z, Dong H, Lv H, Ma T, Lu J. Coupling of brain activity and structural network in multiple sclerosis: A graph frequency analysis study. J Neurosci Res 2022; 100:1226-1238. [PMID: 35184336 DOI: 10.1002/jnr.25028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 12/06/2021] [Accepted: 01/27/2022] [Indexed: 11/10/2022]
Affiliation(s)
| | - Jing Huang
- Department of Radiology and Nuclear Medicine Xuanwu Hospital, Capital Medical University Beijing China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics Capital Medical University Beijing China
| | - Li Liang
- Department of Electronic and Information Engineering Harbin Institute of Technology at Shenzhen Shenzhen China
| | - Zehong Yan
- Department of Electronic and Information Engineering Harbin Institute of Technology at Shenzhen Shenzhen China
| | - Zhigang Qi
- Department of Radiology and Nuclear Medicine Xuanwu Hospital, Capital Medical University Beijing China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics Capital Medical University Beijing China
| | - Xiong Kang
- Department of Radiology and Nuclear Medicine Xuanwu Hospital, Capital Medical University Beijing China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics Capital Medical University Beijing China
| | - Zheng Liu
- Department of Neurology Xuanwu Hospital, Capital Medical University Beijing China
| | - Huiqing Dong
- Department of Neurology Xuanwu Hospital, Capital Medical University Beijing China
| | - Haiyan Lv
- Mindsgo Life Science Shenzhen Co. Ltd Shenzhen China
| | - Ting Ma
- Peng Cheng Laboratory Shenzhen China
- Department of Electronic and Information Engineering Harbin Institute of Technology at Shenzhen Shenzhen China
- Advanced Innovation Center for Human Brain Protection Capital Medical University Beijing China
- National Clinical Research Center for Geriatric Disorders Xuanwu Hospital Capital Medical University Beijing China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine Xuanwu Hospital, Capital Medical University Beijing China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics Capital Medical University Beijing China
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14
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Physical exercise may improve problem-solving skills and emotional intelligence in patients with relapsing-remitting multiple sclerosis: A cross-sectional study. Mult Scler Relat Disord 2022; 59:103641. [DOI: 10.1016/j.msard.2022.103641] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 01/03/2022] [Accepted: 01/27/2022] [Indexed: 11/19/2022]
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Jandric D, Lipp I, Paling D, Rog D, Castellazzi G, Haroon H, Parkes L, Parker GJM, Tomassini V, Muhlert N. Mechanisms of Network Changes in Cognitive Impairment in Multiple Sclerosis. Neurology 2021; 97:e1886-e1897. [PMID: 34649879 PMCID: PMC8601205 DOI: 10.1212/wnl.0000000000012834] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 09/13/2021] [Indexed: 12/14/2022] Open
Abstract
Background and Objectives Cognitive impairment in multiple sclerosis (MS) is associated with functional connectivity abnormalities. While there have been calls to use functional connectivity measures as biomarkers, there remains to be a full understanding of why they are affected in MS. In this cross-sectional study, we tested the hypothesis that functional network regions may be susceptible to disease-related “wear and tear” and that this can be observable on co-occurring abnormalities on other magnetic resonance metrics. We tested whether functional connectivity abnormalities in cognitively impaired patients with MS co-occur with (1) overlapping, (2) local, or (3) distal changes in anatomic connectivity and cerebral blood flow abnormalities. Methods Multimodal 3T MRI and assessment with the Brief Repeatable Battery of Neuropsychological tests were performed in 102 patients with relapsing-remitting MS and 27 healthy controls. Patients with MS were classified as cognitively impaired if they scored ≥1.5 SDs below the control mean on ≥2 tests (n = 55) or as cognitively preserved (n = 47). Functional connectivity was assessed with Independent Component Analysis and dual regression of resting-state fMRI images. Cerebral blood flow maps were estimated, and anatomic connectivity was assessed with anatomic connectivity mapping and fractional anisotropy of diffusion-weighted MRI. Changes in cerebral blood flow and anatomic connectivity were assessed within resting-state networks that showed functional connectivity abnormalities in cognitively impaired patients with MS. Results Functional connectivity was significantly decreased in the anterior and posterior default mode networks and significantly increased in the right and left frontoparietal networks in cognitively impaired relative to cognitively preserved patients with MS (threshold-free cluster enhancement corrected at p ≤ 0.05, 2 sided). Networks showing functional abnormalities showed altered cerebral blood flow and anatomic connectivity locally and distally but not in overlapping locations. Discussion We provide the first evidence that functional connectivity abnormalities are accompanied by local cerebral blood flow and structural connectivity abnormalities but also demonstrate that these effects do not occur in exactly the same location. Our findings suggest a possibly shared pathologic mechanism for altered functional connectivity in brain networks in MS.
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Affiliation(s)
- Danka Jandric
- From the Division of Neuroscience & Experimental Psychology (D.J., H.H., L.P., G.P., N.M.), School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, UK; Department of Neurophysics (I.L.), Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany; Royal Hallamshire Hospital (D.P.), Sheffield Teaching Hospitals, NHS UK; Salford Royal Hospital (D.R.), Salford Royal NHS Foundation Trust, NHS UK; NMR Research Unit (G.C.), Queens Square Multiple Sclerosis Centre, and Centre for Medical Image Computing (G.C., G.P.), Department of Computer Science and Department of Neuroinflammation, Queen Square Institute of Neurology, University College London; Cardiff University Brain Research Imaging Centre (V.T.), Cardiff University, UK; Institute for Advanced Biomedical Technologies (ITAB) (V.T.), Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara; and Multiple Sclerosis Centre (V.T.), Department of Neurology, SS Annunziata University Hospital, Chieti, Italy
| | - Ilona Lipp
- From the Division of Neuroscience & Experimental Psychology (D.J., H.H., L.P., G.P., N.M.), School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, UK; Department of Neurophysics (I.L.), Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany; Royal Hallamshire Hospital (D.P.), Sheffield Teaching Hospitals, NHS UK; Salford Royal Hospital (D.R.), Salford Royal NHS Foundation Trust, NHS UK; NMR Research Unit (G.C.), Queens Square Multiple Sclerosis Centre, and Centre for Medical Image Computing (G.C., G.P.), Department of Computer Science and Department of Neuroinflammation, Queen Square Institute of Neurology, University College London; Cardiff University Brain Research Imaging Centre (V.T.), Cardiff University, UK; Institute for Advanced Biomedical Technologies (ITAB) (V.T.), Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara; and Multiple Sclerosis Centre (V.T.), Department of Neurology, SS Annunziata University Hospital, Chieti, Italy
| | - David Paling
- From the Division of Neuroscience & Experimental Psychology (D.J., H.H., L.P., G.P., N.M.), School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, UK; Department of Neurophysics (I.L.), Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany; Royal Hallamshire Hospital (D.P.), Sheffield Teaching Hospitals, NHS UK; Salford Royal Hospital (D.R.), Salford Royal NHS Foundation Trust, NHS UK; NMR Research Unit (G.C.), Queens Square Multiple Sclerosis Centre, and Centre for Medical Image Computing (G.C., G.P.), Department of Computer Science and Department of Neuroinflammation, Queen Square Institute of Neurology, University College London; Cardiff University Brain Research Imaging Centre (V.T.), Cardiff University, UK; Institute for Advanced Biomedical Technologies (ITAB) (V.T.), Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara; and Multiple Sclerosis Centre (V.T.), Department of Neurology, SS Annunziata University Hospital, Chieti, Italy
| | - David Rog
- From the Division of Neuroscience & Experimental Psychology (D.J., H.H., L.P., G.P., N.M.), School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, UK; Department of Neurophysics (I.L.), Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany; Royal Hallamshire Hospital (D.P.), Sheffield Teaching Hospitals, NHS UK; Salford Royal Hospital (D.R.), Salford Royal NHS Foundation Trust, NHS UK; NMR Research Unit (G.C.), Queens Square Multiple Sclerosis Centre, and Centre for Medical Image Computing (G.C., G.P.), Department of Computer Science and Department of Neuroinflammation, Queen Square Institute of Neurology, University College London; Cardiff University Brain Research Imaging Centre (V.T.), Cardiff University, UK; Institute for Advanced Biomedical Technologies (ITAB) (V.T.), Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara; and Multiple Sclerosis Centre (V.T.), Department of Neurology, SS Annunziata University Hospital, Chieti, Italy
| | - Gloria Castellazzi
- From the Division of Neuroscience & Experimental Psychology (D.J., H.H., L.P., G.P., N.M.), School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, UK; Department of Neurophysics (I.L.), Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany; Royal Hallamshire Hospital (D.P.), Sheffield Teaching Hospitals, NHS UK; Salford Royal Hospital (D.R.), Salford Royal NHS Foundation Trust, NHS UK; NMR Research Unit (G.C.), Queens Square Multiple Sclerosis Centre, and Centre for Medical Image Computing (G.C., G.P.), Department of Computer Science and Department of Neuroinflammation, Queen Square Institute of Neurology, University College London; Cardiff University Brain Research Imaging Centre (V.T.), Cardiff University, UK; Institute for Advanced Biomedical Technologies (ITAB) (V.T.), Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara; and Multiple Sclerosis Centre (V.T.), Department of Neurology, SS Annunziata University Hospital, Chieti, Italy
| | - Hamied Haroon
- From the Division of Neuroscience & Experimental Psychology (D.J., H.H., L.P., G.P., N.M.), School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, UK; Department of Neurophysics (I.L.), Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany; Royal Hallamshire Hospital (D.P.), Sheffield Teaching Hospitals, NHS UK; Salford Royal Hospital (D.R.), Salford Royal NHS Foundation Trust, NHS UK; NMR Research Unit (G.C.), Queens Square Multiple Sclerosis Centre, and Centre for Medical Image Computing (G.C., G.P.), Department of Computer Science and Department of Neuroinflammation, Queen Square Institute of Neurology, University College London; Cardiff University Brain Research Imaging Centre (V.T.), Cardiff University, UK; Institute for Advanced Biomedical Technologies (ITAB) (V.T.), Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara; and Multiple Sclerosis Centre (V.T.), Department of Neurology, SS Annunziata University Hospital, Chieti, Italy
| | - Laura Parkes
- From the Division of Neuroscience & Experimental Psychology (D.J., H.H., L.P., G.P., N.M.), School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, UK; Department of Neurophysics (I.L.), Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany; Royal Hallamshire Hospital (D.P.), Sheffield Teaching Hospitals, NHS UK; Salford Royal Hospital (D.R.), Salford Royal NHS Foundation Trust, NHS UK; NMR Research Unit (G.C.), Queens Square Multiple Sclerosis Centre, and Centre for Medical Image Computing (G.C., G.P.), Department of Computer Science and Department of Neuroinflammation, Queen Square Institute of Neurology, University College London; Cardiff University Brain Research Imaging Centre (V.T.), Cardiff University, UK; Institute for Advanced Biomedical Technologies (ITAB) (V.T.), Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara; and Multiple Sclerosis Centre (V.T.), Department of Neurology, SS Annunziata University Hospital, Chieti, Italy
| | - Geoff J M Parker
- From the Division of Neuroscience & Experimental Psychology (D.J., H.H., L.P., G.P., N.M.), School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, UK; Department of Neurophysics (I.L.), Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany; Royal Hallamshire Hospital (D.P.), Sheffield Teaching Hospitals, NHS UK; Salford Royal Hospital (D.R.), Salford Royal NHS Foundation Trust, NHS UK; NMR Research Unit (G.C.), Queens Square Multiple Sclerosis Centre, and Centre for Medical Image Computing (G.C., G.P.), Department of Computer Science and Department of Neuroinflammation, Queen Square Institute of Neurology, University College London; Cardiff University Brain Research Imaging Centre (V.T.), Cardiff University, UK; Institute for Advanced Biomedical Technologies (ITAB) (V.T.), Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara; and Multiple Sclerosis Centre (V.T.), Department of Neurology, SS Annunziata University Hospital, Chieti, Italy
| | - Valentina Tomassini
- From the Division of Neuroscience & Experimental Psychology (D.J., H.H., L.P., G.P., N.M.), School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, UK; Department of Neurophysics (I.L.), Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany; Royal Hallamshire Hospital (D.P.), Sheffield Teaching Hospitals, NHS UK; Salford Royal Hospital (D.R.), Salford Royal NHS Foundation Trust, NHS UK; NMR Research Unit (G.C.), Queens Square Multiple Sclerosis Centre, and Centre for Medical Image Computing (G.C., G.P.), Department of Computer Science and Department of Neuroinflammation, Queen Square Institute of Neurology, University College London; Cardiff University Brain Research Imaging Centre (V.T.), Cardiff University, UK; Institute for Advanced Biomedical Technologies (ITAB) (V.T.), Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara; and Multiple Sclerosis Centre (V.T.), Department of Neurology, SS Annunziata University Hospital, Chieti, Italy
| | - Nils Muhlert
- From the Division of Neuroscience & Experimental Psychology (D.J., H.H., L.P., G.P., N.M.), School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, UK; Department of Neurophysics (I.L.), Max Planck Institute for Human Cognitive & Brain Sciences, Leipzig, Germany; Royal Hallamshire Hospital (D.P.), Sheffield Teaching Hospitals, NHS UK; Salford Royal Hospital (D.R.), Salford Royal NHS Foundation Trust, NHS UK; NMR Research Unit (G.C.), Queens Square Multiple Sclerosis Centre, and Centre for Medical Image Computing (G.C., G.P.), Department of Computer Science and Department of Neuroinflammation, Queen Square Institute of Neurology, University College London; Cardiff University Brain Research Imaging Centre (V.T.), Cardiff University, UK; Institute for Advanced Biomedical Technologies (ITAB) (V.T.), Department of Neurosciences, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara; and Multiple Sclerosis Centre (V.T.), Department of Neurology, SS Annunziata University Hospital, Chieti, Italy.
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Groppa S, Gonzalez-Escamilla G, Eshaghi A, Meuth SG, Ciccarelli O. Linking immune-mediated damage to neurodegeneration in multiple sclerosis: could network-based MRI help? Brain Commun 2021; 3:fcab237. [PMID: 34729480 PMCID: PMC8557667 DOI: 10.1093/braincomms/fcab237] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/21/2021] [Indexed: 01/04/2023] Open
Abstract
Inflammatory demyelination characterizes the initial stages of multiple sclerosis, while progressive axonal and neuronal loss are coexisting and significantly contribute to the long-term physical and cognitive impairment. There is an unmet need for a conceptual shift from a dualistic view of multiple sclerosis pathology, involving either inflammatory demyelination or neurodegeneration, to integrative dynamic models of brain reorganization, where, glia-neuron interactions, synaptic alterations and grey matter pathology are longitudinally envisaged at the whole-brain level. Functional and structural MRI can delineate network hallmarks for relapses, remissions or disease progression, which can be linked to the pathophysiology behind inflammatory attacks, repair and neurodegeneration. Here, we aim to unify recent findings of grey matter circuits dynamics in multiple sclerosis within the framework of molecular and pathophysiological hallmarks combined with disease-related network reorganization, while highlighting advances from animal models (in vivo and ex vivo) and human clinical data (imaging and histological). We propose that MRI-based brain networks characterization is essential for better delineating ongoing pathology and elaboration of particular mechanisms that may serve for accurate modelling and prediction of disease courses throughout disease stages.
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Affiliation(s)
- Sergiu Groppa
- Imaging and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Gabriel Gonzalez-Escamilla
- Imaging and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Arman Eshaghi
- Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London WC1E 6BT, UK.,Department of Computer Science, Centre for Medical Image Computing (CMIC), University College London, London WC1E 6BT, UK
| | - Sven G Meuth
- Department of Neurology, Medical Faculty, Heinrich Heine University, Düsseldorf 40225, Germany
| | - Olga Ciccarelli
- Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London WC1E 6BT, UK
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Huiskamp M, Eijlers AJC, Broeders TAA, Pasteuning J, Dekker I, Uitdehaag BMJ, Barkhof F, Wink AM, Geurts JJG, Hulst HE, Schoonheim MM. Longitudinal Network Changes and Conversion to Cognitive Impairment in Multiple Sclerosis. Neurology 2021; 97:e794-e802. [PMID: 34099528 PMCID: PMC8397585 DOI: 10.1212/wnl.0000000000012341] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 05/17/2021] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVE To characterize functional network changes related to conversion to cognitive impairment in a large sample of patients with multiple sclerosis (MS) over a period of 5 years. METHODS Two hundred twenty-seven patients with MS and 59 healthy controls of the Amsterdam MS cohort underwent neuropsychological testing and resting-state fMRI at 2 time points (time interval 4.9 ± 0.9 years). At both baseline and follow-up, patients were categorized as cognitively preserved (CP; n = 123), mildly impaired (MCI; z < -1.5 on ≥2 cognitive tests, n = 32), or impaired (CI; z < -2 on ≥2 tests, n = 72), and longitudinal conversion between groups was determined. Network function was quantified with eigenvector centrality, a measure of regional network importance, which was computed for individual resting-state networks at both time points. RESULTS Over time, 18.9% of patients converted to a worse phenotype; 22 of 123 patients who were CP (17.9%) converted from CP to MCI, 10 of 123 from CP to CI (8.1%), and 12 of 32 patients with MCI converted to CI (37.5%). At baseline, default-mode network (DMN) centrality was higher in CI individuals compared to controls (p = 0.05). Longitudinally, ventral attention network (VAN) importance increased in CP, driven by stable CP and CP-to-MCI converters (p < 0.05). CONCLUSIONS Of all patients, 19% worsened in their cognitive status over 5 years. Conversion from intact cognition to impairment is related to an initial disturbed functioning of the VAN, then shifting toward DMN dysfunction in CI. Because the VAN normally relays information to the DMN, these results could indicate that in MS normal processes crucial for maintaining overall network stability are progressively disrupted as patients clinically progress.
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Affiliation(s)
- Marijn Huiskamp
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK.
| | - Anand J C Eijlers
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Tommy A A Broeders
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Jasmin Pasteuning
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Iris Dekker
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Bernard M J Uitdehaag
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Frederik Barkhof
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Alle-Meije Wink
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Jeroen J G Geurts
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Hanneke E Hulst
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Menno M Schoonheim
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
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Jandric D, Doshi A, Scott R, Paling D, Rog D, Chataway J, Schoonheim M, Parker G, Muhlert N. A systematic review of resting state functional MRI connectivity changes and cognitive impairment in multiple sclerosis. Brain Connect 2021; 12:112-133. [PMID: 34382408 DOI: 10.1089/brain.2021.0104] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
INTRODUCTION Cognitive impairment in multiple sclerosis (MS) is increasingly being investigated with resting state functional MRI (rs-fMRI) functional connectivity (FC) . However, results remain difficult to interpret, showing both high and low FC associated with cognitive impairment. We conducted a systematic review of rs-fMRI studies in MS to understand whether the direction of FC change relates to cognitive dysfunction, and how this may be influenced by the choice of methodology. METHODS Embase, Medline and PsycINFO were searched for studies assessing cognitive function and rs-fMRI FC in adults with MS. RESULTS Fifty-seven studies were included in a narrative synthesis. Of these, 50 found an association between cognitive impairment and FC abnormalities. Worse cognition was linked to high FC in 18 studies, and to low FC in 17 studies. Nine studies found patterns of both high and low FC related to poor cognitive performance, in different regions or for different MR metrics. There was no clear link to increased FC during early stages of MS and reduced FC in later stages, as predicted by common models of MS pathology. Throughout, we found substantial heterogeneity in study methodology, and carefully consider how this may impact on the observed findings. DISCUSSION These results indicate an urgent need for greater standardisation in the field - in terms of the choice of MRI analysis and the definition of cognitive impairment. This will allow us to use rs-fMRI FC as a biomarker in future clinical studies, and as a tool to understand mechanisms underpinning cognitive symptoms in MS.
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Affiliation(s)
- Danka Jandric
- The University of Manchester, 5292, Oxford Road, Manchester, United Kingdom of Great Britain and Northern Ireland, M13 9PL;
| | - Anisha Doshi
- University College London, 4919, London, London, United Kingdom of Great Britain and Northern Ireland;
| | - Richelle Scott
- The University of Manchester, 5292, Manchester, United Kingdom of Great Britain and Northern Ireland;
| | - David Paling
- Royal Hallamshire Hospital, 105629, Sheffield, Sheffield, United Kingdom of Great Britain and Northern Ireland;
| | - David Rog
- Salford Royal Hospital, 105621, Salford, Salford, United Kingdom of Great Britain and Northern Ireland;
| | - Jeremy Chataway
- University College London, 4919, London, London, United Kingdom of Great Britain and Northern Ireland;
| | - Menno Schoonheim
- Amsterdam UMC Locatie VUmc, 1209, Anatomy & Neurosciences, Amsterdam, Noord-Holland, Netherlands;
| | - Geoff Parker
- University College London, 4919, London, London, United Kingdom of Great Britain and Northern Ireland.,The University of Manchester, 5292, Manchester, United Kingdom of Great Britain and Northern Ireland;
| | - Nils Muhlert
- The University of Manchester, 5292, Manchester, United Kingdom of Great Britain and Northern Ireland;
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Zhang J, Cortese R, De Stefano N, Giorgio A. Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis. Front Neurol 2021; 12:671894. [PMID: 34305785 PMCID: PMC8297166 DOI: 10.3389/fneur.2021.671894] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 05/19/2021] [Indexed: 02/05/2023] Open
Abstract
Cognitive impairment (CI) occurs in 43 to 70% of multiple sclerosis (MS) patients at both early and later disease stages. Cognitive domains typically involved in MS include attention, information processing speed, memory, and executive control. The growing use of advanced magnetic resonance imaging (MRI) techniques is furthering our understanding on the altered structural connectivity (SC) and functional connectivity (FC) substrates of CI in MS. Regarding SC, different diffusion tensor imaging (DTI) measures (e.g., fractional anisotropy, diffusivities) along tractography-derived white matter (WM) tracts showed relevance toward CI. Novel diffusion MRI techniques, including diffusion kurtosis imaging, diffusion spectrum imaging, high angular resolution diffusion imaging, and neurite orientation dispersion and density imaging, showed more pathological specificity compared to the traditional DTI but require longer scan time and mathematical complexities for their interpretation. As for FC, task-based functional MRI (fMRI) has been traditionally used in MS to brain mapping the neural activity during various cognitive tasks. Analysis methods of resting fMRI (seed-based, independent component analysis, graph analysis) have been applied to uncover the functional substrates of CI in MS by revealing adaptive or maladaptive mechanisms of functional reorganization. The relevance for CI in MS of SC–FC relationships, reflecting common pathogenic mechanisms in WM and gray matter, has been recently explored by novel MRI analysis methods. This review summarizes recent advances on MRI techniques of SC and FC and their potential to provide a deeper understanding of the pathological substrates of CI in MS.
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Affiliation(s)
- Jian Zhang
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Antonio Giorgio
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
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20
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Shahrampour S, Heholt J, Wang A, Vedaei F, Mohamed FB, Alizadeh M, Wang Z, Zabrecky G, Wintering N, Bazzan AJ, Leist TP, Monti DA, Newberg AB. N-acetyl cysteine administration affects cerebral blood flow as measured by arterial spin labeling MRI in patients with multiple sclerosis. Heliyon 2021; 7:e07615. [PMID: 34377857 PMCID: PMC8327674 DOI: 10.1016/j.heliyon.2021.e07615] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 02/23/2021] [Accepted: 07/14/2021] [Indexed: 10/26/2022] Open
Abstract
BACKGROUND The purpose of this study was to explore if administration of N-acetyl-cysteine (NAC) in patients with multiple sclerosis (MS) resulted in altered cerebral blood flow (CBF) based on Arterial Spin Labeling (ASL) magnetic resonance imaging (MRI). METHODS Twenty-three patients with mild to moderate MS, (17 relapsing remitting and 6 primary progressive) were randomized to either NAC plus standard of care (N = 11), or standard of care only (N = 12). The experimental group received NAC intravenously (50 mg/kg) once per week and orally (500mg 2x/day) the other six days. Patients in both groups were evaluated initially and after 2 months (of receiving the NAC or waitlist control) with ASL MRI to measure CBF. Clinical symptom questionnaires were also completed at both time points. RESULTS The CBF data showed significant differences in several brain regions including the pons, midbrain, left temporal and frontal lobe, left thalamus, right middle frontal lobe and right temporal/hippocampus (p < 0.001) in the MS group after treatment with NAC, when compared to the control group. Self-reported scores related to cognition and attention were also significantly improved in the NAC group as compared to the control group. CONCLUSIONS The results of this study suggest that NAC administration alters resting CBF in MS patients, and this is associated with qualitative improvements in cognition and attention. Given these findings, large scale efficacy studies will be of value to determine the potential clinical impact of NAC over the course of illness in patients with MS, as well as the most effective dosages and differential effects across subpopulations.
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Affiliation(s)
- Shiva Shahrampour
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Justin Heholt
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Andrew Wang
- Charles E. Schmidt College of Medicine, Marcus Institute of Integrative Health at FAU Medicine, Florida Atlantic University, Boca Raton, FL USA
| | - Faezeh Vedaei
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Feroze B. Mohamed
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Mahdi Alizadeh
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Ze Wang
- Department of Radiology, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - George Zabrecky
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative Health, Thomas Jefferson University, Philadelphia, PA, USA
| | - Nancy Wintering
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative Health, Thomas Jefferson University, Philadelphia, PA, USA
| | - Anthony J. Bazzan
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative Health, Thomas Jefferson University, Philadelphia, PA, USA
| | - Thomas P. Leist
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Daniel A. Monti
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative Health, Thomas Jefferson University, Philadelphia, PA, USA
| | - Andrew B. Newberg
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Integrative Medicine and Nutritional Sciences, Marcus Institute of Integrative Health, Thomas Jefferson University, Philadelphia, PA, USA
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21
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Microstructural MRI Correlates of Cognitive Impairment in Multiple Sclerosis: The Role of Deep Gray Matter. Diagnostics (Basel) 2021; 11:diagnostics11061103. [PMID: 34208650 PMCID: PMC8234586 DOI: 10.3390/diagnostics11061103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 06/07/2021] [Accepted: 06/10/2021] [Indexed: 11/24/2022] Open
Abstract
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.
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22
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Alterations in functional connectivity are associated with white matter lesions and information processing efficiency in multiple sclerosis. Brain Imaging Behav 2021; 15:375-388. [PMID: 32114647 DOI: 10.1007/s11682-020-00264-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Functional connectivity (FC) is typically altered in individuals with Multiple Sclerosis (MS). However, in relapsing-remitting multiple sclerosis (RRMS) patients, the relationship between brain FC, tissue integrity and cognitive impairment is still unclear as contradictory findings have been documented. In this exploratory study we compared both the whole brain connectome and resting state networks (RSNs) FC of twenty-one RRMS and seventeen healthy controls (HCs), using combined network based statistics and independent component analyses. The total white matter (WM) lesion volume and information processing efficiency were also correlated with FC in the RRMS group. Both whole brain connectome and individual RSNs FC were diminished in patients with RRMS compared to HC. Additionally, the reduction in FC was found to be a function of the total WM lesion volume, with greatest impact in those harboring the largest lesion volume. Finally, a positive correlation between FC and information processing efficiency was observed in RRMS. This complimentary whole brain and RSNs FC approach can contribute to clarify literature inconsistencies regarding FC alterations and provide new insights on the white matter structural damage in explaining functional abnormalities in RRMS.
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23
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Effect of blast-related mTBI on the working memory system: a resting state fMRI study. Brain Imaging Behav 2021; 14:949-960. [PMID: 30519997 DOI: 10.1007/s11682-018-9987-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Reduced working memory is frequently reported by Veterans with a history of blast-related mild traumatic brain injury (mTBI), but can be difficult to quantify on neuropsychological measures. This study aimed to improve our understanding of the impact of blast-related mTBI on the working memory system by using resting state functional magnetic resonance imaging (fMRI) to explore differences in functional connectivity between OEF/OIF/OND Veterans with and without a history of mTBI. Participants were twenty-four Veterans with a history of blast-related mTBI and 17 Veterans who were deployed but had no lifetime history of TBI. Working memory ability was evaluated with the Auditory Consonants Trigrams (ACT) task. Resting state fMRI was used to evaluate intrinsic functional connectivity from frontal seed regions that are known components of the working memory network. No significant group differences were found on the ACT, but the imaging analyses revealed widespread hyper-connectivity from the frontal seed regions in the Veterans with a history of mTBI relative to the deployed control group. Further, within the mTBI group, but not the control group, better performance on the ACT was associated with increased functional connectivity to multiple brain regions, including cerebellar components of the working memory network. These results were present after controlling for age, PTSD symptoms, and estimated premorbid IQ, and suggest that long-term alterations in the functional connectivity of the working memory network following blast-related mTBI may reflect a compensatory change that contributes to intact performance on an objective measure of working memory.
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24
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Gromisch ES, Dhari Z. Identifying Early Neuropsychological Indicators of Cognitive Involvement in Multiple Sclerosis. Neuropsychiatr Dis Treat 2021; 17:323-337. [PMID: 33574669 PMCID: PMC7872925 DOI: 10.2147/ndt.s256689] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 01/22/2021] [Indexed: 12/19/2022] Open
Abstract
Multiple sclerosis (MS) is a debilitating disease of the central nervous system that is most commonly seen in early to middle adulthood, although it can be diagnosed during childhood or later in life. While cognitive impairment can become more prevalent and severe as the disease progresses, signs of cognitive involvement can be apparent in the early stages of the disease. In this review, we discuss the prevalence and types of cognitive impairment seen in early MS, including the specific measures used to identify them, as well as the challenges in characterizing their frequency and progression. In addition to examining the progression of early cognitive involvement over time, we explore the clinical factors associated with early cognitive involvement, including demographics, level of physical disability, disease modifying therapy use, vocational status, and psychological and physical symptoms. Given the prevalence and functional impact these impairments can have for persons with MS, considerations for clinicians are provided, such as the role of early cognitive screenings and the importance of comprehensive neuropsychological assessments.
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Affiliation(s)
- Elizabeth S Gromisch
- Mandell Center for Multiple Sclerosis, Mount Sinai Rehabilitation Hospital, Trinity Health Of New England, Hartford, CT, USA
- Department of Rehabilitative Medicine, Frank H. Netter MD School of Medicine at Quinnipiac University, North Haven, CT, USA
- Department of Medical Sciences, Frank H. Netter MD School of Medicine at Quinnipiac University, North Haven, CT, USA
- Department of Neurology, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Zaenab Dhari
- Mandell Center for Multiple Sclerosis, Mount Sinai Rehabilitation Hospital, Trinity Health Of New England, Hartford, CT, USA
- Department of Rehabilitative Medicine, Frank H. Netter MD School of Medicine at Quinnipiac University, North Haven, CT, USA
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25
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Zhuo Z, Li Y, Duan Y, Cao G, Zheng F, Ding J, Tian D, Wang X, Wang J, Zhang X, Li K, Zhou F, Huang M, Li Y, Li H, Zeng C, Zhang N, Sun J, Yu C, Han X, Haller S, Barkhof F, Shi F, Liu Y. Subtyping relapsing-remitting multiple sclerosis using structural MRI. J Neurol 2021; 268:1808-1817. [PMID: 33387013 DOI: 10.1007/s00415-020-10376-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 12/08/2020] [Accepted: 12/16/2020] [Indexed: 11/26/2022]
Abstract
BACKGROUND AND PURPOSE Subtyping relapsing-remitting multiple sclerosis (RRMS) patients may help predict disease progression and triage patients for treatment. We aimed to subtype RRMS patients by structural MRI and investigate their clinical significances. METHODS 155 relapse-remitting MS (RRMS) and 210 healthy controls (HC) were retrospectively enrolled with structural 3DT1, diffusion tensor imaging (DTI) and resting-state functional MRI. Z scores of cortical and deep gray matter volumes (CGMV and DGMV) and white matter fractional anisotropy (WM-FA) in RRMS patients were calculated based on means and standard deviations of HC. We defined RRMS as "normal" (- 2 < z scores of both GMV and WM-FA), DGM (z scores of DGMV < - 2), and DGM-plus types (z scores of DGMV and [CGMV or WM-FA] < - 2) according to combinations of z scores compared to HC. Expanded disability status scale (EDSS), cognitive and functional MRI measurements, and conversion rate to secondary progressive MS (SPMS) at 5-year follow-up were compared between subtypes. RESULTS 77 (49.7%) patients were "normal" type, 37 (23.9%) patients were DGM type and 34 (21.9%) patients were DGM-plus type. 7 (4.5%) patients who were not categorized into the above types were excluded. DGM-plus type had the highest EDSS. Both DGM and DGM-plus types had more severe cognitive impairment than "normal" type. Only DGM-plus type showed decreased functional MRI measures compared to HC. A higher conversion ratio to SPMS in DGM-plus type (55%) was identified compared to "normal" type (14%, p < 0.001) and DGM type (20%, p = 0.005). CONCLUSION Three MRI-subtypes of RRMS were identified with distinct clinical and imaging features and different prognosis.
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Affiliation(s)
- Zhizheng Zhuo
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119, The West Southern 4th Ring Road, Fengtai District, Beijing, 100070, China
| | - Yongmei Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Yunyun Duan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119, The West Southern 4th Ring Road, Fengtai District, Beijing, 100070, China
| | - Guanmei Cao
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119, The West Southern 4th Ring Road, Fengtai District, Beijing, 100070, China
| | - Fenglian Zheng
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119, The West Southern 4th Ring Road, Fengtai District, Beijing, 100070, China
| | - Jinli Ding
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119, The West Southern 4th Ring Road, Fengtai District, Beijing, 100070, China
| | - Decai Tian
- Center for Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Xinli Wang
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jinhui Wang
- Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China
| | - Xinghu Zhang
- Center for Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Kuncheng Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Fuqing Zhou
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, 330006, Jiangxi Province, China
| | - Muhua Huang
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, 330006, Jiangxi Province, China
| | - Yuxin Li
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Haiqing Li
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Chun Zeng
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Ningnannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jie Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xuemei Han
- Department of Neurology, China-Japan Union Hospital of Jilin University, Changchun, 130031, Jilin Province, China
| | - Sven Haller
- Department of Imaging and Medical Informatics, University Hospitals of Geneva and Faculty of Medicine of the University of Geneva, Geneva, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Center for Medical Image Computing, University College London, London, UK
| | - Fudong Shi
- Center for Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119, The West Southern 4th Ring Road, Fengtai District, Beijing, 100070, China.
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China.
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26
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Lashkari A, Davoodi-Bojd E, Fahmy L, Li L, Nejad-Davarani SP, Chopp M, Jiang Q, Cerghet M. Impairments of white matter tracts and connectivity alterations in five cognitive networks of patients with multiple sclerosis. Clin Neurol Neurosurg 2020; 201:106424. [PMID: 33348120 DOI: 10.1016/j.clineuro.2020.106424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 12/04/2020] [Accepted: 12/05/2020] [Indexed: 01/01/2023]
Abstract
INTRODUCTION MS is associated with structural and functional brain alterations leading to cognitive impairments across multiple domains including attention, memory, and speed of information processing. Here, we analyzed the white matter damage and topological organization of white matter tracts in specific brain regions responsible for cognition in MS. METHODS Brain DTI, rs-fMRI, T1, T2, and T2-FLAIR were acquired for 22 MS subjects and 22 healthy controls. Automatic brain parcellation was performed on T1-weighted images. Skull-stripped T1-weighted intensity inverted images were co-registered to the b0 image. Diffusion-weighted images were processed to perform whole brain tractography. The rs-fMRI data were processed, and the connectivity matrixes were analyzed to identify significant differences in the network of nodes between the two groups using NBS analysis. In addition, diffusion entropy maps were produced from DTI data sets using in-house software. RESULTS MS subjects exhibited significantly reduced mean FA and entropy in 38 and 34 regions, respectively, out of a total of 54 regions. The connectivity values in both structural and functional analyses were decreased in most regions of the default mode network and in four other cognitive networks in MS subjects compared to healthy controls. MS also induced significant reduction in the normalized hippocampus and corpus callosum volumes; the normalized hippocampus volume was significantly correlated with EDSS scores. CONCLUSION MS subjects have significant white matter damage and reduction of FA and entropy in various brain regions involved in cognitive networks. Structural and functional connectivity within the default mode network and an additional four cognitive networks exhibited significant changes compared with healthy controls.
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Affiliation(s)
- AmirEhsan Lashkari
- Department of Neurology, Henry Ford Health System, Detroit, MI, United States
| | | | - Lara Fahmy
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, United States
| | - Lian Li
- Department of Neurology, Henry Ford Health System, Detroit, MI, United States
| | | | - Michael Chopp
- Department of Neurology, Henry Ford Health System, Detroit, MI, United States; Oakland University, Department of Physics, Rochester, MI, United States; Department of Neurology, Wayne State University, Detroit, MI, United States
| | - Quan Jiang
- Department of Neurology, Henry Ford Health System, Detroit, MI, United States; Oakland University, Department of Physics, Rochester, MI, United States; Department of Neurology, Wayne State University, Detroit, MI, United States.
| | - Mirela Cerghet
- Department of Neurology, Henry Ford Health System, Detroit, MI, United States
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27
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Sjøgård M, Wens V, Van Schependom J, Costers L, D'hooghe M, D'haeseleer M, Woolrich M, Goldman S, Nagels G, De Tiège X. Brain dysconnectivity relates to disability and cognitive impairment in multiple sclerosis. Hum Brain Mapp 2020; 42:626-643. [PMID: 33242237 PMCID: PMC7814767 DOI: 10.1002/hbm.25247] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 09/10/2020] [Accepted: 09/29/2020] [Indexed: 12/27/2022] Open
Abstract
The pathophysiology of cognitive dysfunction in multiple sclerosis (MS) is still unclear. This magnetoencephalography (MEG) study investigates the impact of MS on brain resting-state functional connectivity (rsFC) and its relationship to disability and cognitive impairment. We investigated rsFC based on power envelope correlation within and between different frequency bands, in a large cohort of participants consisting of 99 MS patients and 47 healthy subjects. Correlations were investigated between rsFC and outcomes on disability, disease duration and 7 neuropsychological scores within each group, while stringently correcting for multiple comparisons and possible confounding factors. Specific dysconnections correlating with MS-induced physical disability and disease duration were found within the sensorimotor and language networks, respectively. Global network-level reductions in within- and cross-network rsFC were observed in the default-mode network. Healthy subjects and patients significantly differed in their scores on cognitive fatigue and verbal fluency. Healthy subjects and patients showed different correlation patterns between rsFC and cognitive fatigue or verbal fluency, both of which involved a shift in patients from the posterior default-mode network to the language network. Introducing electrophysiological rsFC in a regression model of verbal fluency and cognitive fatigue in MS patients significantly increased the explained variance compared to a regression limited to structural MRI markers (relative thalamic volume and lesion load). This MEG study demonstrates that MS induces distinct changes in the resting-state functional brain architecture that relate to disability, disease duration and specific cognitive functioning alterations. It highlights the potential value of electrophysiological intrinsic rsFC for monitoring the cognitive impairment in patients with MS.
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Affiliation(s)
- Martin Sjøgård
- Laboratoire de Cartographie fonctionnelle du Cerveau, UNI-ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Vincent Wens
- Laboratoire de Cartographie fonctionnelle du Cerveau, UNI-ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium.,Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB-Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Jeroen Van Schependom
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium.,National MS Center, Belgium
| | - Lars Costers
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Marie D'hooghe
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium.,National MS Center, Belgium
| | - Miguel D'haeseleer
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium.,National MS Center, Belgium
| | - Mark Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Serge Goldman
- Laboratoire de Cartographie fonctionnelle du Cerveau, UNI-ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium.,Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB-Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Guy Nagels
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium.,National MS Center, Belgium.,St Edmund Hall, University of Oxford, Oxford, UK
| | - Xavier De Tiège
- Laboratoire de Cartographie fonctionnelle du Cerveau, UNI-ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium.,Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB-Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
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28
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Veréb D, Tóth E, Bozsik B, Király A, Szabó N, Kincses B, Kocsis K, Faragó P, László V, Bencsik K, Klivényi P, Kincses ZT. Altered brain network function during attention-modulated visual processing in multiple sclerosis. Mult Scler 2020; 27:1341-1349. [PMID: 33016839 DOI: 10.1177/1352458520958360] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Multiple sclerosis may damage cognitive performance in several domains, including attention. Although attention network deficits were described during rest, studies that investigate their function during task performance are scarce. OBJECTIVE To investigate connectivity within and between task-related networks in multiple sclerosis during a visual attention task as a function of cognitive performance. METHODS A total of 23 relapsing-remitting multiple sclerosis (RRMS) patients and 29 healthy controls underwent task-functional magnetic resonance imaging (fMRI) scans using a visual attention paradigm on a 3T scanner. Scans were analysed using tensor-independent component analysis (TICA). Functional connectivity was calculated within and between components. We assessed cognitive function with the Brief International Cognitive Assessment for MS (BICAMS) battery. RESULTS TICA extracted components related to visual processing, attention, executive function and the default-mode network. Subject scores of visual/attention-related and executive components were greater in healthy controls (p < 0.032, p < 0.023). Connectivity between visual/attention-related and default-mode components was higher in patients (p < 0.043), correlating with Brief Visuospatial Memory Test-Revised (BVMT-R) scores (R = -0.48, p < 0.036). Patients showed reduced connectivity between the right intraparietal sulcus (rIPS) and frontal eye field (rFEF), and bilateral frontal eye fields (p < 0.012, p < 0.003). Reduced rIPS-rFEF connectivity came with lower Symbol Digit Modalities Test (SDMT)/BVMT-R scores in patients (R = 0.53, p < 0.02, R = 0.46, p < 0.049). CONCLUSION Attention-related networks show altered connectivity during task performance in RRMS patients, scaling with cognitive disability.
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Affiliation(s)
- Dániel Veréb
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Eszter Tóth
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Bence Bozsik
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - András Király
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Nikoletta Szabó
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Bálint Kincses
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Krisztián Kocsis
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Péter Faragó
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Vécsei László
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Krisztina Bencsik
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Péter Klivényi
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Zsigmond Tamás Kincses
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary/Neuroimaging Research Group, Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
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29
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Wu L, Huang M, Zhou F, Zeng X, Gong H. Distributed causality in resting-state network connectivity in the acute and remitting phases of RRMS. BMC Neurosci 2020; 21:37. [PMID: 32933478 PMCID: PMC7493168 DOI: 10.1186/s12868-020-00590-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 09/09/2020] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Although previous studies have shown that intra-network abnormalities in brain functional networks are correlated with clinical/cognitive impairment in multiple sclerosis (MS), there is little information regarding the pattern of causal interactions among cognition-related resting-state networks (RSNs) in different disease stages of relapsing-remitting MS (RRMS) patients. We hypothesized that abnormalities of causal interactions among RSNs occurred in RRMS patients in the acute and remitting phases. METHODS Seventeen patients in the acute phases of RRMS, 24 patients in the remitting phases of RRMS, and 23 appropriately matched healthy controls participated in this study. First, we used group independent component analysis to extract the time courses of the spatially independent components from all the subjects. Then, the Granger causality analysis was used to investigate the causal relationships among RSNs in the spectral domain and to identify correlations with clinical indices. RESULTS Compared with the patients in the acute phase of RRMS, patients in the remitting phase of RRMS showed a significantly lower expanded disability status scale, modified fatigue impact scale scores, and significantly higher paced auditory serial addition test (PASAT) scores. Compared with healthy subjects, during the acute phase, RRMS patients had significantly increased driving connectivity from the right executive control network (rECN) to the anterior salience network (aSN), and the causal coefficient was negatively correlated with the PASAT score. During the remitting phase, RRMS patients had significantly increased driving connectivity from the rECN to the aSN and from the rECN to the visuospatial network. CONCLUSIONS Together with the disease duration (mean disease duration < 5 years) and relatively better clinical scores than those in the acute phase, abnormal connections, such as the information flow from the rECN to the aSN and the rECN to the visuospatial network, might provide adaptive compensation in the remitting phase of RRMS.
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Affiliation(s)
- Lin Wu
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi, People's Republic of China.,Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
| | - Muhua Huang
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi, People's Republic of China.,Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
| | - Fuqing Zhou
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi, People's Republic of China. .,Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China.
| | - Xianjun Zeng
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi, People's Republic of China.,Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
| | - Honghan Gong
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi, People's Republic of China.,Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
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30
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Figueroa-Vargas A, Cárcamo C, Henríquez-Ch R, Zamorano F, Ciampi E, Uribe-San-Martin R, Vásquez M, Aboitiz F, Billeke P. Frontoparietal connectivity correlates with working memory performance in multiple sclerosis. Sci Rep 2020; 10:9310. [PMID: 32518271 PMCID: PMC7283327 DOI: 10.1038/s41598-020-66279-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Accepted: 05/18/2020] [Indexed: 12/16/2022] Open
Abstract
Working Memory (WM) impairment is the most common cognitive deficit of patients with Multiple Sclerosis (MS). However, evidence of its neurobiological mechanisms is scarce. Here we recorded electroencephalographic activity of twenty patients with relapsing-remitting MS and minimal cognitive deficit, and 20 healthy control (HC) subjects while they solved a WM task. In spite of similar performance, the HC group demonstrated both a correlation between temporoparietal theta activity and memory load, and a correlation between medial frontal theta activity and successful memory performances. MS patients did not show theses correlations leading significant differences between groups. Moreover, cortical connectivity analyses using granger causality and phase-amplitude coupling between theta and gamma revealed that HC group, but not MS group, presented a load-modulated progression of the frontal-to-parietal connectivity. This connectivity correlated with working memory capacity in MS groups. This early alterations in the oscillatory dynamics underlaying working memory could be useful for plan therapeutic interventions.
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Affiliation(s)
- Alejandra Figueroa-Vargas
- Laboratorio de Neurociencia Social y Neuromodulación, Centro de Investigación en Complejidad Social (neuroCICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago de Chile, Chile.
| | - Claudia Cárcamo
- Departamento de Neurología, Hospital Clínico de la Pontificia Universidad Católica de Chile, Santiago de Chile, Chile
| | - Rodrigo Henríquez-Ch
- Departamento de Psiquiatría, Escuela de Medicina, and Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago de Chile, Chile
| | - Francisco Zamorano
- Laboratorio de Neurociencia Social y Neuromodulación, Centro de Investigación en Complejidad Social (neuroCICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago de Chile, Chile
- Unidad de Imágenes Cuantitativas Avanzadas, Departamento de Imágenes, Clínica Alemana de Santiago, Universidad del Desarrollo, Santiago de Chile, Chile
| | - Ethel Ciampi
- Departamento de Neurología, Hospital Clínico de la Pontificia Universidad Católica de Chile, Santiago de Chile, Chile
- Servicio de Neurología, Hospital Dr. Sótero del Río, Santiago de Chile, Chile
| | - Reinaldo Uribe-San-Martin
- Departamento de Neurología, Hospital Clínico de la Pontificia Universidad Católica de Chile, Santiago de Chile, Chile
- Servicio de Neurología, Hospital Dr. Sótero del Río, Santiago de Chile, Chile
| | - Macarena Vásquez
- Departamento de Neurología, Hospital Clínico de la Pontificia Universidad Católica de Chile, Santiago de Chile, Chile
| | - Francisco Aboitiz
- Departamento de Psiquiatría, Escuela de Medicina, and Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago de Chile, Chile
| | - Pablo Billeke
- Laboratorio de Neurociencia Social y Neuromodulación, Centro de Investigación en Complejidad Social (neuroCICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago de Chile, Chile.
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31
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Koubiyr I, Besson P, Deloire M, Charre-Morin J, Saubusse A, Tourdias T, Brochet B, Ruet A. Dynamic modular-level alterations of structural-functional coupling in clinically isolated syndrome. Brain 2020; 142:3428-3439. [PMID: 31504228 DOI: 10.1093/brain/awz270] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 06/24/2019] [Accepted: 07/11/2019] [Indexed: 11/14/2022] Open
Abstract
Structural and functional connectivity abnormalities have been reported previously in multiple sclerosis. However, little is known about how each modality evolution relates to the other. Recent studies in other neurological disorders have suggested that structural-functional coupling may be more sensitive in detecting brain alterations than any single modality. Accordingly, this study aimed to investigate the longitudinal evolution of structural-functional coupling, both at the global and modular levels, in the first year following clinically isolated syndrome. We hypothesized that during the course of multiple sclerosis, patients exhibit a decoupling between functional and structural connectivity due to the disruptive nature of the disease. Forty-one consecutive patients with clinically isolated syndrome were prospectively enrolled in this study, along with 19 age-, sex- and educational level-matched healthy control subjects. These participants were followed for 1 year and underwent resting-state functional MRI and diffusion tensor imaging at each time point, along with an extensive neuropsychological assessment. Graph theory analysis revealed structural reorganization at baseline that appeared as an increase in the clustering coefficient in patients compared to controls (P < 0.05), as well as modular-specific alterations. After 1 year of follow-up, both structural and functional reorganization was depicted with abnormal modular-specific connectivity and an increase of the functional betweenness centrality in patients compared to controls (P < 0.01). More importantly, structural-functional decoupling was observed in the salience, visual and somatomotor networks. These alterations were present along with preserved cognitive performance at this stage. These results depict structural damage preceding functional reorganization at a global and modular level during the first year following clinically isolated syndrome along with normal cognitive performance, suggesting a compensation mechanism at this stage of the disease. Principally, structural-functional decoupling observed for the first time in multiple sclerosis suggests that functional reorganization occurs along indirect anatomical pathways.
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Affiliation(s)
- Ismail Koubiyr
- University of Bordeaux, F Bordeaux, France.,Inserm U1215 - Neurocentre Magendie, F Bordeaux, France
| | - Pierre Besson
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA.,Department of Neurological Surgery, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA
| | | | | | | | - Thomas Tourdias
- University of Bordeaux, F Bordeaux, France.,Inserm U1215 - Neurocentre Magendie, F Bordeaux, France.,CHU de Bordeaux, F Bordeaux, France
| | - Bruno Brochet
- University of Bordeaux, F Bordeaux, France.,Inserm U1215 - Neurocentre Magendie, F Bordeaux, France.,CHU de Bordeaux, F Bordeaux, France
| | - Aurélie Ruet
- University of Bordeaux, F Bordeaux, France.,Inserm U1215 - Neurocentre Magendie, F Bordeaux, France.,CHU de Bordeaux, F Bordeaux, France
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32
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Treatment and management of cognitive dysfunction in patients with multiple sclerosis. Nat Rev Neurol 2020; 16:319-332. [PMID: 32372033 DOI: 10.1038/s41582-020-0355-1] [Citation(s) in RCA: 97] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/30/2020] [Indexed: 01/19/2023]
Abstract
Cognitive impairment is a common and devastating manifestation of multiple sclerosis (MS). Although disease-modifying therapies have been efficacious for reducing relapse rates in MS, such treatments are ineffective for treating cognitive dysfunction. Alternative treatment approaches for mitigating cognitive problems are greatly needed in this population. To date, cognitive rehabilitation and exercise training have been identified as possible candidates for treating MS-related cognitive impairment; however, cognitive dysfunction is still often considered to be poorly managed in patients with MS. This Review provides a comprehensive overview of recent developments in the treatment and management of cognitive impairment in people with MS. We describe the theoretical rationales, current states of the science, field-wide challenges and recent advances in cognitive rehabilitation and exercise training for treating MS-related cognitive impairment. We also discuss future directions for research into the treatment of cognitive impairment in MS that should set the stage for the inclusion of cognitive rehabilitation and exercise training into clinical practice within the next decade.
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33
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Tommasin S, De Giglio L, Ruggieri S, Petsas N, Giannì C, Pozzilli C, Pantano P. Multi-scale resting state functional reorganization in response to multiple sclerosis damage. Neuroradiology 2020; 62:693-704. [PMID: 32189024 DOI: 10.1007/s00234-020-02393-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 02/27/2020] [Indexed: 11/26/2022]
Abstract
PURPOSE In multiple sclerosis (MS), how brain functional changes relate to clinical conditions is still a matter of debate. The aim of this study was to investigate how functional connectivity (FC) reorganization at three different scales, ranging from local to whole brain, is related to tissue damage and disability. METHODS One-hundred-nineteen patients with MS were clinically evaluated with the Expanded Disability Status Scale and the Multiple Sclerosis Functional Composite. Patients and 42 healthy controls underwent a multimodal 3 T MRI, including resting-state functional MRI. RESULTS We identified 16 resting-state networks via independent component analysis and measured within-network, between-network, and whole-brain (global efficiency and degree centrality) FC. Within-network FC was higher in patients than in controls in default mode, frontoparietal, and executive-control networks, and corresponded to low clinical impairment (default mode network versus Expanded Disability Status Scale r = - 0.31, p < 0.01; right frontoparietal network versus Paced Auditory Serial Addition Test r = 0.33, p < 0.01). All measures of between-network and whole-brain FC, except default mode network global efficiency, were lower in patients than in controls, and corresponded to high disability (i.e., basal ganglia global efficiency versus Timed 25-Foot Walk r = - 0.25, p < 0.03; default mode global efficiency versus Expanded Disability Status Scale r = - 0.44, p < 0.001). Altered measures of within-network, between-network, and whole-brain FC were combined in functional indices that were linearly related to disease duration, Paced Auditory Serial Addition Test and lesion load and non-linearly related to Expanded Disability Status Scale. CONCLUSION We suggest that the combined evaluation of functional alterations occurring at different levels, from local to whole brain, could exhaustively describe neuroplastic changes in MS, while increased within-network FC likely represents adaptive compensatory processes, decreased between-network and whole-brain FC likely represent loss of functional network integration consequent to structural disruption.
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Affiliation(s)
- Silvia Tommasin
- Department of Human Neuroscience, Sapienza - University of Rome, Viale dell'Università 30, 00185, Rome, Italy
| | - Laura De Giglio
- Medicine Department, Neurology Unit, San Filippo Neri Hospital, Via Giovanni Martinotti, 20, 00135, Rome, RM, Italy
| | - Serena Ruggieri
- Department of Human Neuroscience, Sapienza - University of Rome, Viale dell'Università 30, 00185, Rome, Italy
| | - Nikolaos Petsas
- IRCCS Neuromed, (Pozzilli [IS], IT) Via Atinense, 18, 86077, Pozzilli, IS, Italy
| | - Costanza Giannì
- Department of Human Neuroscience, Sapienza - University of Rome, Viale dell'Università 30, 00185, Rome, Italy
| | - Carlo Pozzilli
- Department of Human Neuroscience, Sapienza - University of Rome, Viale dell'Università 30, 00185, Rome, Italy
- Sant'Andrea Hospital, MS Centre, Sapienza - University of Rome, Viale di Grottarossa 1035, 00189, Rome, Italy
| | - Patrizia Pantano
- Department of Human Neuroscience, Sapienza - University of Rome, Viale dell'Università 30, 00185, Rome, Italy.
- IRCCS Neuromed, (Pozzilli [IS], IT) Via Atinense, 18, 86077, Pozzilli, IS, Italy.
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Nasios G, Bakirtzis C, Messinis L. Cognitive Impairment and Brain Reorganization in MS: Underlying Mechanisms and the Role of Neurorehabilitation. Front Neurol 2020; 11:147. [PMID: 32210905 PMCID: PMC7068711 DOI: 10.3389/fneur.2020.00147] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 02/14/2020] [Indexed: 12/29/2022] Open
Abstract
Multiple sclerosis (MS) is a chronic, immune-mediated, inflammatory, and degenerative disease of the central nervous system (CNS) that affects both white and gray matter. Various mechanisms throughout its course, mainly regarding gray matter lesions and brain atrophy, result in cognitive network dysfunction and can cause clinically significant cognitive impairment in roughly half the persons living with MS. Altered cognition is responsible for many negative aspects of patients' lives, independently of physical disability, such as higher unemployment and divorce rates, reduced social activities, and an overall decrease in quality of life. Despite its devastating impact it is not included in clinical ratings and decision making in the way it should be. It is interesting that only half the persons with MS exhibit cognitive dysfunction, as this implies that the other half remain cognitively intact. It appears that a dynamic balance between brain destruction and brain reorganization is taking place. This balance acts in favor of keeping brain systems functioning effectively, but this is not so in all cases, and the effect does not last forever. When these systems collapse, functional brain reorganization is not effective anymore, and clinically apparent impairments are evident. It is therefore important to reveal which factors could make provision for the subpopulation of patients in whom cognitive impairment occurs. Even if we manage to detect this subpopulation earlier, effective pharmaceutical treatments will still be lacking. Nevertheless, recent evidence shows that cognitive rehabilitation and neuromodulation, using non-invasive techniques such as transcranial magnetic or direct current stimulation, could be effective in cognitively impaired patients with MS. In this Mini Review, we discuss the mechanisms underlying cognitive impairment in MS. We also focus on mechanisms of reorganization of cognitive networks, which occur throughout the disease course. Finally, we review theoretical and practical issues of neurorehabilitation and neuromodulation for cognition in MS as well as factors that influence them and prevent them from being widely applied in clinical settings.
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Affiliation(s)
- Grigorios Nasios
- Department of Speech and Language Therapy, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Christos Bakirtzis
- Department of Neurology, The Multiple Sclerosis Center, AHEPA University Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Lambros Messinis
- Neuropsychology Section, Departments of Neurology and Psychiatry, University of Patras Medical School, Patras, Greece
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35
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Hawkins R, Shatil AS, Lee L, Sengupta A, Zhang L, Morrow S, Aviv RI. Reduced Global Efficiency and Random Network Features in Patients with Relapsing-Remitting Multiple Sclerosis with Cognitive Impairment. AJNR Am J Neuroradiol 2020; 41:449-455. [PMID: 32079601 DOI: 10.3174/ajnr.a6435] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 01/11/2020] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Graph theory uses structural similarity to analyze cortical structural connectivity. We used a voxel-based definition of cortical covariance networks to quantify and assess the relationship of network characteristics to cognition in a cohort of patients with relapsing-remitting MS with and without cognitive impairment. MATERIALS AND METHODS We compared subject-specific structural gray matter network properties of 18 healthy controls, 25 patients with MS with cognitive impairment, and 55 patients with MS without cognitive impairment. Network parameters were compared, and predictive value for cognition was assessed, adjusting for confounders (sex, education, gray matter volume, network size and degree, and T1 and T2 lesion load). Backward stepwise multivariable regression quantified predictive factors for 5 neurocognitive domain test scores. RESULTS Greater path length (r = -0.28, P < .0057) and lower normalized path length (r = 0.36, P < .0004) demonstrated a correlation with average cognition when comparing healthy controls with patients with MS. Similarly, MS with cognitive impairment demonstrated a correlation between lower normalized path length (r = 0.40, P < .001) and reduced average cognition. Increased normalized path length was associated with better performance for processing (P < .001), learning (P < .001), and executive domain function (P = .0235), while reduced path length was associated with better executive (P = .0031) and visual domains. Normalized path length improved prediction for processing (R 2 = 43.6%, G2 = 20.9; P < .0001) and learning (R 2 = 40.4%, G2 = 26.1; P < .0001) over a null model comprising confounders. Similarly, higher normalized path length improved prediction of average z scores (G2 = 21.3; P < .0001) and, combined with WM volume, explained 52% of average cognition variance. CONCLUSIONS Patients with MS and cognitive impairment demonstrate more random network features and reduced global efficiency, impacting multiple cognitive domains. A model of normalized path length with normal-appearing white matter volume improved average cognitive z score prediction, explaining 52% of variance.
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Affiliation(s)
- R Hawkins
- From the Department of Medical Imaging (R.H., A.S.S., A.S., L.Z.)
| | - A S Shatil
- From the Department of Medical Imaging (R.H., A.S.S., A.S., L.Z.)
| | - L Lee
- Division of Neurology (L.L.), Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - A Sengupta
- From the Department of Medical Imaging (R.H., A.S.S., A.S., L.Z.)
| | - L Zhang
- From the Department of Medical Imaging (R.H., A.S.S., A.S., L.Z.)
| | - S Morrow
- Division of Neurology (S.M.), Lawson Health Research Institute, London Health Sciences Centre, University Hospital, London, Ontario, Canada
| | - R I Aviv
- Institute of Biomaterials and Biomedical Engineering (R.I.A.), University of Toronto, Toronto, Ontario, Canada .,Department of Radiology (R.I.A.), University of Ottawa, and Division of Neuroradiology, The Ottawa Hospital, Ottawa, Ontario, Canada
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36
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Hoxha A, Glassen M, DeLuca J, Kwasnica M, Yue G, Saleh S. Difference in Cortical Modulation of Walking between Persons with Multiple Sclerosis and Healthy Controls: An EEG pilot study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:3010-3013. [PMID: 31946522 DOI: 10.1109/embc.2019.8856643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The overall goal of this study is to investigate the role of parietal cortex in the control of walking in persons with Multiple Sclerosis (pwMS). We examined within-brain connectivity and cortico-muscular connectivity as pwMS and healthy control (HC) participants walked on an instrumented treadmill. Cortical activity was collected using EEG, muscle activity was collected using wireless EMG modules, and gait data were obtained by using the instrumented treadmill. Results show significant activation of sensorimotor and posterior parietal cortex during walking in both groups. Connectivity between parietal (posterior cingulate cortex PCC) and premotor regions (pars opercularis), and between PCC and contralateral muscles were higher in the healthy control group. Higher connectivity correlated with higher walking speed.
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Van Schependom J, Guldolf K, D'hooghe MB, Nagels G, D'haeseleer M. Detecting neurodegenerative pathology in multiple sclerosis before irreversible brain tissue loss sets in. Transl Neurodegener 2019; 8:37. [PMID: 31827784 PMCID: PMC6900860 DOI: 10.1186/s40035-019-0178-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Accepted: 11/07/2019] [Indexed: 12/29/2022] Open
Abstract
Background Multiple sclerosis (MS) is a complex chronic inflammatory and degenerative disorder of the central nervous system. Accelerated brain volume loss, or also termed atrophy, is currently emerging as a popular imaging marker of neurodegeneration in affected patients, but, unfortunately, can only be reliably interpreted at the time when irreversible tissue damage likely has already occurred. Timing of treatment decisions based on brain atrophy may therefore be viewed as suboptimal. Main body This Narrative Review focuses on alternative techniques with the potential of detecting neurodegenerative events in the brain of subjects with MS prior to the atrophic stage. First, metabolic and molecular imaging provide the opportunity to identify early subcellular changes associated with energy dysfunction, which is an assumed core mechanism of axonal degeneration in MS. Second, cerebral hypoperfusion has been observed throughout the entire clinical spectrum of the disorder but it remains an open question whether this serves as an alternative marker of reduced metabolic activity, or exists as an independent contributing process, mediated by endothelin-1 hyperexpression. Third, both metabolic and perfusion alterations may lead to repercussions at the level of network performance and structural connectivity, respectively assessable by functional and diffusion tensor imaging. Fourth and finally, elevated body fluid levels of neurofilaments are gaining interest as a biochemical mirror of axonal damage in a wide range of neurological conditions, with early rises in patients with MS appearing to be predictive of future brain atrophy. Conclusions Recent findings from the fields of advanced neuroradiology and neurochemistry provide the promising prospect of demonstrating degenerative brain pathology in patients with MS before atrophy has installed. Although the overall level of evidence on the presented topic is still preliminary, this Review may pave the way for further longitudinal and multimodal studies exploring the relationships between the abovementioned measures, possibly leading to novel insights in early disease mechanisms and therapeutic intervention strategies.
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Affiliation(s)
- Jeroen Van Schependom
- 1Neurology Department, Universitair Ziekenhuis Brussel; Center for Neurosciences, Vrije Universiteit Brussel, Laarbeeklaan 101, 1090 Brussel, Belgium.,2Radiology Department Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Kaat Guldolf
- 1Neurology Department, Universitair Ziekenhuis Brussel; Center for Neurosciences, Vrije Universiteit Brussel, Laarbeeklaan 101, 1090 Brussel, Belgium
| | - Marie Béatrice D'hooghe
- 1Neurology Department, Universitair Ziekenhuis Brussel; Center for Neurosciences, Vrije Universiteit Brussel, Laarbeeklaan 101, 1090 Brussel, Belgium.,Nationaal Multiple Sclerose Centrum, Melsbroek, Belgium
| | - Guy Nagels
- 1Neurology Department, Universitair Ziekenhuis Brussel; Center for Neurosciences, Vrije Universiteit Brussel, Laarbeeklaan 101, 1090 Brussel, Belgium.,Nationaal Multiple Sclerose Centrum, Melsbroek, Belgium
| | - Miguel D'haeseleer
- 1Neurology Department, Universitair Ziekenhuis Brussel; Center for Neurosciences, Vrije Universiteit Brussel, Laarbeeklaan 101, 1090 Brussel, Belgium.,Nationaal Multiple Sclerose Centrum, Melsbroek, Belgium
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Van Schependom J, Vidaurre D, Costers L, Sjøgård M, D'hooghe MB, D'haeseleer M, Wens V, De Tiège X, Goldman S, Woolrich M, Nagels G. Altered transient brain dynamics in multiple sclerosis: Treatment or pathology? Hum Brain Mapp 2019; 40:4789-4800. [PMID: 31361073 DOI: 10.1002/hbm.24737] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 07/13/2019] [Accepted: 07/16/2019] [Indexed: 11/07/2022] Open
Abstract
Multiple sclerosis (MS) is a demyelinating, neuroinflammatory, and -degenerative disease that affects the brain's neurophysiological functioning through brain atrophy, a reduced conduction velocity and decreased connectivity. Currently, little is known on how MS affects the fast temporal dynamics of activation and deactivation of the different large-scale, ongoing brain networks. In this study, we investigated whether these temporal dynamics are affected in MS patients and whether these changes are induced by the pathology or by the use of benzodiazepines (BZDs), an important symptomatic treatment that aims at reducing insomnia, spasticity and anxiety and reinforces the inhibitory effect of GABA. To this aim, we employed a novel method capable of detecting these fast dynamics in 90 MS patients and 46 healthy controls. We demonstrated a less dynamic frontal default mode network in male MS patients and a reduced activation of the same network in female MS patients, regardless of BZD usage. Additionally, BZDs strongly altered the brain's dynamics by increasing the time spent in the deactivating sensorimotor network and the activating occipital network. Furthermore, BZDs induced a decreased power in the theta band and an increased power in the beta band. The latter was strongly expressed in those states without activation of the sensorimotor network. In summary, we demonstrate gender-dependent changes to the brain dynamics in the frontal DMN and strong effects from BZDs. This study is the first to characterise the effect of multiple sclerosis and BZDs in vivo in a spatially, temporally and spectrally defined way.
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Affiliation(s)
- Jeroen Van Schependom
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium
- Radiology, Universitair Ziekenhuis Brussel, Brussels, Belgium
- National MS Center Melsbroek, Melsbroek, Belgium
| | - Diego Vidaurre
- Oxford Centre for Human Brain Activity (OHBA), University of Oxford, Oxford, UK
- Oxford University Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
| | - Lars Costers
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Martin Sjøgård
- Laboratoire de Cartographie fonctionnelle du Cerveau, UNI-ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Marie B D'hooghe
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium
- National MS Center Melsbroek, Melsbroek, Belgium
| | - Miguel D'haeseleer
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium
- National MS Center Melsbroek, Melsbroek, Belgium
| | - Vincent Wens
- Laboratoire de Cartographie fonctionnelle du Cerveau, UNI-ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium
- Magnetoencephalography Unit, Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB-Hôpital Erasme, Brussels, Belgium
| | - Xavier De Tiège
- Laboratoire de Cartographie fonctionnelle du Cerveau, UNI-ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium
- Magnetoencephalography Unit, Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB-Hôpital Erasme, Brussels, Belgium
| | - Serge Goldman
- Laboratoire de Cartographie fonctionnelle du Cerveau, UNI-ULB Neuroscience Institute, Université libre de Bruxelles (ULB), Brussels, Belgium
- Magnetoencephalography Unit, Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB-Hôpital Erasme, Brussels, Belgium
| | - Mark Woolrich
- Oxford Centre for Human Brain Activity (OHBA), University of Oxford, Oxford, UK
- Oxford University Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
| | - Guy Nagels
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium
- National MS Center Melsbroek, Melsbroek, Belgium
- St Edmund Hall, University of Oxford, Oxford, UK
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39
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Eijlers AJC, van Geest Q, Dekker I, Steenwijk MD, Meijer KA, Hulst HE, Barkhof F, Uitdehaag BMJ, Schoonheim MM, Geurts JJG. Predicting cognitive decline in multiple sclerosis: a 5-year follow-up study. Brain 2019; 141:2605-2618. [PMID: 30169585 DOI: 10.1093/brain/awy202] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Accepted: 06/15/2018] [Indexed: 11/14/2022] Open
Abstract
Cognitive decline is common in multiple sclerosis and strongly affects overall quality of life. Despite the identification of cross-sectional MRI correlates of cognitive impairment, predictors of future cognitive decline remain unclear. The objective of this study was to identify which MRI measures of structural damage, demographic and/or clinical measures at baseline best predict cognitive decline, during a 5-year follow-up period. A total of 234 patients with clinically definite multiple sclerosis and 60 healthy control subjects were examined twice, with a 5-year interval (mean = 4.9 years, standard deviation = 0.9). An extensive neuropsychological evaluation was performed at both time points and the reliable change index was computed to evaluate cognitive decline. Both whole-brain and regional MRI (3 T) measures were assessed at baseline, including white matter lesion volume, diffusion-based white matter integrity, cortical and deep grey matter volume. Logistic regression analyses were performed to determine which baseline measures best predicted cognitive decline in the entire sample as well as in early relapsing-remitting (symptom duration <10 years), late relapsing-remitting (symptom duration ≥10 years) and progressive phenotypes. At baseline, patients with multiple sclerosis had a mean disease duration of 14.8 (standard deviation = 8.4) years and 96/234 patients (41%) were classified as cognitively impaired. A total of 66/234 patients (28%) demonstrated cognitive decline during follow-up, with higher frequencies in progressive compared to relapsing-remitting patients: 18/33 secondary progressive patients (55%), 10/19 primary progressive patients (53%) and 38/182 relapsing-remitting patients (21%). A prediction model that included only whole-brain MRI measures (Nagelkerke R2 = 0.22, P < 0.001) showed cortical grey matter volume as the only significant MRI predictor of cognitive decline, while a prediction model that assessed regional MRI measures (Nagelkerke R2 = 0.35, P < 0.001) indicated integrity loss of the anterior thalamic radiation, lesions in the superior longitudinal fasciculus and temporal atrophy as significant MRI predictors for cognitive decline. Disease stage specific regressions showed that cognitive decline in early relapsing-remitting multiple sclerosis was predicted by white matter integrity damage, while cognitive decline in late relapsing-remitting and progressive multiple sclerosis was predicted by cortical atrophy. These results indicate that patients with more severe structural damage at baseline, and especially cortical atrophy, are more prone to suffer from cognitive decline. New studies now need to further elucidate the underlying mechanisms leading to cortical atrophy, evaluate the value of including cortical atrophy as a possible outcome marker in clinical trials as well as study its potential use in individual patient management.
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Affiliation(s)
- Anand J C Eijlers
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Quinten van Geest
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Iris Dekker
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Department of Neurology, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Kim A Meijer
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Hanneke E Hulst
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, UCL, London, UK
| | - Bernard M J Uitdehaag
- Department of Neurology, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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40
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Eijlers AJC, Wink AM, Meijer KA, Douw L, Geurts JJG, Schoonheim MM. Reduced Network Dynamics on Functional MRI Signals Cognitive Impairment in Multiple Sclerosis. Radiology 2019; 292:449-457. [PMID: 31237498 DOI: 10.1148/radiol.2019182623] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Background Previous studies have demonstrated extensive functional network disturbances in patients with multiple sclerosis (MS), showing a less efficient brain network. Recent studies indicate that the dynamic properties of the brain network show a strong correlation with cognitive function. Purpose To investigate network dynamics on functional MRI in cognitively impaired patients with MS. Materials and Methods In secondary analysis of prospectively acquired data, with imaging performed between 2008 and 2012, differences in regional functional network dynamics (ie, eigenvector centrality dynamics) between cognitively impaired and cognitively preserved participants with MS were investigated. Functional network dynamics were computed on images from functional MRI (3 T) by using a sliding-window approach. Cognitively impaired and preserved groups were compared by using a clusterwise permutation-based method. Results The study included 96 healthy control subjects and 332 participants with MS (including 226 women and 106 men; median age, 48.1 years ± 11.0). Among the 332 participants with MS, 87 were cognitively impaired and 180 had preserved cognitive function; mildly impaired patients (n = 65) were excluded. The cognitively impaired group included a higher proportion of men compared with the cognitively preserved group (35 of 87 [40%] vs 48 of 180 [27%], respectively; P = .02) and had a higher mean age (51.1 years vs 46.3 years, respectively; P < .01). The clusterwise permutation-based comparison at P less than .05 showed reduced centrality dynamics in default-mode, frontoparietal, and visual network regions on functional MRI in cognitively impaired participants versus cognitively preserved participants. A subsequent correlation and hierarchical clustering analysis revealed that the default-mode and visual networks normally demonstrate negatively correlated fluctuations in functional importance (r = -0.23 in healthy control subjects), with an almost complete loss of this negative correlation in cognitively impaired participants compared with cognitively preserved participants (r = -0.04 vs r = -0.14; corrected P = .02). Conclusion As shown on functional MRI, cognitively impaired patients with multiple sclerosis not only demonstrate reduced dynamics in default-mode, frontoparietal, and visual networks, but also show a loss of interplay between default-mode and visual networks. © RSNA, 2019 Online supplemental material is available for this article. See also the article by Eijlers et al and the editorial by Zivadinov and Dwyer in this issue.
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Affiliation(s)
- Anand J C Eijlers
- From the Departments of Anatomy and Neurosciences (A.J.C.E., K.A.M., L.D., J.J.G.G., M.M.S.) and Radiology and Nuclear Medicine (A.M.W.), MS Center Amsterdam, Amsterdam UMC, Locatie VUmc, Amsterdam Neuroscience, De Boelelaan 1117, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Alle Meije Wink
- From the Departments of Anatomy and Neurosciences (A.J.C.E., K.A.M., L.D., J.J.G.G., M.M.S.) and Radiology and Nuclear Medicine (A.M.W.), MS Center Amsterdam, Amsterdam UMC, Locatie VUmc, Amsterdam Neuroscience, De Boelelaan 1117, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Kim A Meijer
- From the Departments of Anatomy and Neurosciences (A.J.C.E., K.A.M., L.D., J.J.G.G., M.M.S.) and Radiology and Nuclear Medicine (A.M.W.), MS Center Amsterdam, Amsterdam UMC, Locatie VUmc, Amsterdam Neuroscience, De Boelelaan 1117, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Linda Douw
- From the Departments of Anatomy and Neurosciences (A.J.C.E., K.A.M., L.D., J.J.G.G., M.M.S.) and Radiology and Nuclear Medicine (A.M.W.), MS Center Amsterdam, Amsterdam UMC, Locatie VUmc, Amsterdam Neuroscience, De Boelelaan 1117, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Jeroen J G Geurts
- From the Departments of Anatomy and Neurosciences (A.J.C.E., K.A.M., L.D., J.J.G.G., M.M.S.) and Radiology and Nuclear Medicine (A.M.W.), MS Center Amsterdam, Amsterdam UMC, Locatie VUmc, Amsterdam Neuroscience, De Boelelaan 1117, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Menno M Schoonheim
- From the Departments of Anatomy and Neurosciences (A.J.C.E., K.A.M., L.D., J.J.G.G., M.M.S.) and Radiology and Nuclear Medicine (A.M.W.), MS Center Amsterdam, Amsterdam UMC, Locatie VUmc, Amsterdam Neuroscience, De Boelelaan 1117, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
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41
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Ternes AM, Clough M, Foletta P, White O, Fielding J. Executive control deficits correlate with reduced frontal white matter volume in multiple sclerosis. J Clin Exp Neuropsychol 2019; 41:723-729. [DOI: 10.1080/13803395.2019.1614536] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
- Anne-Marie Ternes
- School of Psychological Sciences and Monash Institute of Cognitive and Clinical Neurosciences, Monash University, Melbourne, Australia
| | - Meaghan Clough
- Department of Neurosciences, Central Clinical School, Monash University, Alfred Hospital, Melbourne, Australia
| | - Paige Foletta
- Department of Neurosciences, Central Clinical School, Monash University, Alfred Hospital, Melbourne, Australia
| | - Owen White
- Department of Neurosciences, Central Clinical School, Monash University, Alfred Hospital, Melbourne, Australia
| | - Joanne Fielding
- School of Psychological Sciences and Monash Institute of Cognitive and Clinical Neurosciences, Monash University, Melbourne, Australia
- Department of Neurosciences, Central Clinical School, Monash University, Alfred Hospital, Melbourne, Australia
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42
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Fleischer V, Koirala N, Droby A, Gracien RM, Deichmann R, Ziemann U, Meuth SG, Muthuraman M, Zipp F, Groppa S. Longitudinal cortical network reorganization in early relapsing-remitting multiple sclerosis. Ther Adv Neurol Disord 2019; 12:1756286419838673. [PMID: 31040880 PMCID: PMC6482642 DOI: 10.1177/1756286419838673] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 02/09/2019] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Network science provides powerful access to essential organizational principles of the brain. The aim of this study was to investigate longitudinal evolution of gray matter networks in early relapsing-remitting MS (RRMS) compared with healthy controls (HCs) and contrast network dynamics with conventional atrophy measurements. METHODS For our longitudinal study, we investigated structural cortical networks over 1 year derived from 3T MRI in 203 individuals (92 early RRMS patients with mean disease duration of 12.1 ± 14.5 months and 101 HCs). Brain networks were computed based on cortical thickness inter-regional correlations and fed into graph theoretical analysis. Network connectivity measures (modularity, clustering coefficient, local efficiency, and transitivity) were compared between patients and HCs, and between patients with and without disease activity. Moreover, we calculated longitudinal brain volume changes and cortical atrophy patterns. RESULTS Our analyses revealed strengthening of local network properties shown by increased modularity, clustering coefficient, local efficiency, and transitivity over time. These network dynamics were not detectable in the cortex of HCs over the same period and occurred independently of patients' disease activity. Most notably, the described network reorganization was evident beyond detectable atrophy as characterized by conventional morphometric methods. CONCLUSION In conclusion, our findings provide evidence for gray matter network reorganization subsequent to clinical disease manifestation in patients with early RRMS. An adaptive cortical response with increased local network characteristics favoring network segregation could play a primordial role for maintaining brain function in response to neuroinflammation.
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Affiliation(s)
- Vinzenz Fleischer
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Nabin Koirala
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Amgad Droby
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - René-Maxime Gracien
- Department of Neurology, and Brain Imaging Center, Goethe University, Frankfurt/Main, Frankfurt am Main, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt/Main, Frankfurt am Main, Germany
| | - Ulf Ziemann
- Department of Neurology and Stroke, and Hertie Institute for Clinical Brain Research, Eberhard-Karls University, Tübingen, Germany
| | - Sven G Meuth
- Department of Neurology, University of Muenster, Muenster, Germany
| | - Muthuraman Muthuraman
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Frauke Zipp
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main-Neuroscience Network (rmn), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr.1, 55131 Mainz, Germany
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Savini G, Pardini M, Castellazzi G, Lascialfari A, Chard D, D'Angelo E, Gandini Wheeler-Kingshott CAM. Default Mode Network Structural Integrity and Cerebellar Connectivity Predict Information Processing Speed Deficit in Multiple Sclerosis. Front Cell Neurosci 2019; 13:21. [PMID: 30853896 PMCID: PMC6396736 DOI: 10.3389/fncel.2019.00021] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 01/17/2019] [Indexed: 01/21/2023] Open
Abstract
Cognitive impairment affects about 50% of multiple sclerosis (MS) patients, but the mechanisms underlying this remain unclear. The default mode network (DMN) has been linked with cognition, but in MS its role is still poorly understood. Moreover, within an extended DMN network including the cerebellum (CBL-DMN), the contribution of cortico-cerebellar connectivity to MS cognitive performance remains unexplored. The present study investigated associations of DMN and CBL-DMN structural connectivity with cognitive processing speed in MS, in both cognitively impaired (CIMS) and cognitively preserved (CPMS) MS patients. 68 MS patients and 22 healthy controls (HCs) completed a symbol digit modalities test (SDMT) and had 3T brain magnetic resonance imaging (MRI) scans that included a diffusion weighted imaging protocol. DMN and CBL-DMN tracts were reconstructed with probabilistic tractography. These networks (DMN and CBL-DMN) and the cortico-cerebellar tracts alone were modeled using a graph theoretical approach with fractional anisotropy (FA) as the weighting factor. Brain parenchymal fraction (BPF) was also calculated. In CIMS SDMT scores strongly correlated with the FA-weighted global efficiency (GE) of the network [GE(CBL-DMN): ρ = 0.87, R2 = 0.76, p < 0.001; GE(DMN): ρ = 0.82, R2 = 0.67, p < 0.001; GE(CBL): ρ = 0.80, R2 = 0.64, p < 0.001]. In CPMS the correlation between these measures was significantly lower [GE(CBL-DMN): ρ = 0.51, R2 = 0.26, p < 0.001; GE(DMN): ρ = 0.48, R2 = 0.23, p = 0.001; GE(CBL): ρ = 0.52, R2 = 0.27, p < 0.001] and SDMT scores correlated most with BPF (ρ = 0.57, R2 = 0.33, p < 0.001). In a multivariable regression model where SDMT was the independent variable, FA-weighted GE was the only significant explanatory variable in CIMS, while in CPMS BPF and expanded disability status scale were significant. No significant correlation was found in HC between SDMT scores, MRI or network measures. DMN structural GE is related to cognitive performance in MS, and results of CBL-DMN suggest that the cerebellum structural connectivity to the DMN plays an important role in information processing speed decline.
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Affiliation(s)
| | - Matteo Pardini
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Genoa, Italy.,Ospedale Policlinico S. Martino, Genoa, Italy
| | - Gloria Castellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.,NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, University College London, London, United Kingdom
| | | | - Declan Chard
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, University College London, London, United Kingdom.,National Institute for Health Research, University College London Hospitals, Biomedical Research Centre, London, United Kingdom
| | - Egidio D'Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, University College London, London, United Kingdom.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Brain MRI 3T Mondino Research Center, IRCCS Mondino Foundation, Pavia, Italy
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44
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Matias-Guiu JA, Cortés-Martínez A, Montero P, Pytel V, Moreno-Ramos T, Jorquera M, Yus M, Arrazola J, Matías-Guiu J. Structural MRI correlates of PASAT performance in multiple sclerosis. BMC Neurol 2018; 18:214. [PMID: 30572821 PMCID: PMC6300910 DOI: 10.1186/s12883-018-1223-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 12/10/2018] [Indexed: 12/05/2022] Open
Abstract
Background The Paced Auditory Serial Addition Test (PASAT) is a useful cognitive test in patients with multiple sclerosis (MS), assessing sustained attention and information processing speed. However, the neural underpinnings of performance in the test are controversial. We aimed to study the neural basis of PASAT performance by using structural magnetic resonance imaging (MRI) in a series of 242 patients with MS. Methods PASAT (3-s) was administered together with a comprehensive neuropsychological battery. Global brain volumes and total T2-weighted lesion volumes were estimated. Voxel-based morphometry and lesion symptom mapping analyses were performed. Results Mean PASAT score was 42.98 ± 10.44; results indicated impairment in 75 cases (31.0%). PASAT score was correlated with several clusters involving the following regions: bilateral precuneus and posterior cingulate, bilateral caudate and putamen, and bilateral cerebellum. Voxel-based lesion symptom mapping showed no significant clusters. Region of interest–based analysis restricted to white matter regions revealed a correlation with the left cingulum, corpus callosum, bilateral corticospinal tracts, and right arcuate fasciculus. Correlations between PASAT scores and global volumes were weak. Conclusion PASAT score was associated with regional volumes of the posterior cingulate/precuneus and several subcortical structures, specifically the caudate, putamen, and cerebellum. This emphasises the role of both cortical and subcortical structures in cognitive functioning and information processing speed in patients with MS. Electronic supplementary material The online version of this article (10.1186/s12883-018-1223-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jordi A Matias-Guiu
- Department of Neurology, San Carlos Health Research Institute (IdISSC), Universidad Complutense de Madrid, C/ Profesor Martín Lagos s/n, 28040, Madrid, Spain.
| | - Ana Cortés-Martínez
- Department of Neurology, San Carlos Health Research Institute (IdISSC), Universidad Complutense de Madrid, C/ Profesor Martín Lagos s/n, 28040, Madrid, Spain
| | - Paloma Montero
- Department of Neurology, San Carlos Health Research Institute (IdISSC), Universidad Complutense de Madrid, C/ Profesor Martín Lagos s/n, 28040, Madrid, Spain
| | - Vanesa Pytel
- Department of Neurology, San Carlos Health Research Institute (IdISSC), Universidad Complutense de Madrid, C/ Profesor Martín Lagos s/n, 28040, Madrid, Spain
| | - Teresa Moreno-Ramos
- Department of Neurology, San Carlos Health Research Institute (IdISSC), Universidad Complutense de Madrid, C/ Profesor Martín Lagos s/n, 28040, Madrid, Spain
| | - Manuela Jorquera
- Department of Radiology, IdISSC, Universidad Complutense de Madrid, Madrid, Spain
| | - Miguel Yus
- Department of Radiology, IdISSC, Universidad Complutense de Madrid, Madrid, Spain
| | - Juan Arrazola
- Department of Radiology, IdISSC, Universidad Complutense de Madrid, Madrid, Spain
| | - Jorge Matías-Guiu
- Department of Neurology, San Carlos Health Research Institute (IdISSC), Universidad Complutense de Madrid, C/ Profesor Martín Lagos s/n, 28040, Madrid, Spain
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45
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Kiljan S, Meijer KA, Steenwijk MD, Pouwels PJW, Schoonheim MM, Schenk GJ, Geurts JJG, Douw L. Structural network topology relates to tissue properties in multiple sclerosis. J Neurol 2018; 266:212-222. [PMID: 30467603 PMCID: PMC6342882 DOI: 10.1007/s00415-018-9130-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 11/14/2018] [Accepted: 11/16/2018] [Indexed: 11/01/2022]
Abstract
OBJECTIVE Abnormalities in segregative and integrative properties of brain networks have been observed in multiple sclerosis (MS) and are related to clinical functioning. This study aims to investigate the micro-scale correlates of macro-scale network measures of segregation and integration in MS. METHODS Eight MS patients underwent post-mortem in situ whole-brain diffusion tensor (DT) imaging and subsequent brain dissection. Macro-scale structural network topology was derived from DT data using graph theory. Clustering coefficient and mean white matter (WM) fiber length were measures of nodal segregation and integration. Thirty-three tissue blocks were collected from five cortical brain regions. Using immunohistochemistry micro-scale tissue properties were evaluated, including, neuronal size, neuronal density, axonal density and total cell density. Nodal network properties and tissue properties were correlated. RESULTS A negative correlation between clustering coefficient and WM fiber length was found. Higher clustering coefficient was associated with smaller neuronal size and lower axonal density, and vice versa for fiber length. Higher whole-brain WM lesion load was associated with higher whole-brain clustering, shorter whole-brain fiber length, lower neuronal size and axonal density. CONCLUSION Structural network properties on MRI associate with neuronal size and axonal density, suggesting that macro-scale network measures may grasp cortical neuroaxonal degeneration in MS.
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Affiliation(s)
- Svenja Kiljan
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Location VU University Medical Center, De Boelelaan 1108, 1081 HZ, Amsterdam, The Netherlands.
| | - Kim A Meijer
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Location VU University Medical Center, De Boelelaan 1108, 1081 HZ, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Location VU University Medical Center, De Boelelaan 1108, 1081 HZ, Amsterdam, The Netherlands.,Department of Neurology, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Petra J W Pouwels
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Location VU University Medical Center, De Boelelaan 1108, 1081 HZ, Amsterdam, The Netherlands
| | - Geert J Schenk
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Location VU University Medical Center, De Boelelaan 1108, 1081 HZ, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Location VU University Medical Center, De Boelelaan 1108, 1081 HZ, Amsterdam, The Netherlands
| | - Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, Location VU University Medical Center, De Boelelaan 1108, 1081 HZ, Amsterdam, The Netherlands.,Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA, USA
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46
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Matías-Guiu JA, Cortés-Martínez A, Montero P, Pytel V, Moreno-Ramos T, Jorquera M, Yus M, Arrazola J, Matías-Guiu J. Identification of Cortical and Subcortical Correlates of Cognitive Performance in Multiple Sclerosis Using Voxel-Based Morphometry. Front Neurol 2018; 9:920. [PMID: 30420834 PMCID: PMC6216547 DOI: 10.3389/fneur.2018.00920] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2018] [Accepted: 10/10/2018] [Indexed: 12/02/2022] Open
Abstract
Objective: Cognitive impairment is an important feature in multiple sclerosis (MS) and has been associated to several Magnetic Resonance Imaging (MRI) markers, but especially brain atrophy. However, the relationship between specific neuropsychological tests examining several cognitive functions and brain volumes has been little explored. Furthermore, because MS frequently damage subcortical regions, it may be an interesting model to examine the role of subcortical areas in cognitive functioning. Our aim was to identify correlations between specific brain regions and performance in neuropsychological tests evaluating different cognitive functions in a large series of patients with MS. Methods: A total of 375 patients were evaluated with a comprehensive neuropsychological battery and with MRI. Voxel-based morphometry was conducted to analyse the correlation between cognitive performance and gray matter damage, using Statistical Parametric Mapping with the toolboxes VBM8 and Lesion Segmentation Tool. Results: The following correlations were found: Corsi block-tapping test with right insula; Trail Making Test with caudate nucleus, thalamus, and several cortical regions including the posterior cingulate and inferior frontal gyrus; Symbol Digit Modalities Test with caudate nucleus, thalamus, posterior cingulate, several frontal regions, insula, and cerebellum; Stroop Color and Word Test with caudate nucleus and putamen; Free and Cued Selective Reminding Test and Rey-Osterrieth Complex Figure with thalamus, precuneus, and parahippocampal gyrus; Boston Naming Test with thalamus, caudate nucleus, and hippocampus; semantic verbal fluency with thalamus and phonological verbal fluency with caudate nucleus; and Tower of London test with frontal lobe, caudate nucleus, and posterior cingulate. Conclusion: Our study provides valuable data on the cortical and subcortical basis of cognitive function in MS. Neuropsychological tests mainly assessing attention and executive function showed a stronger association with caudate volume, while tests primarily evaluating memory were more strongly correlated with the thalamus. Other relevant regions were the posterior cingulate/precuneus, which were associated with attentional tasks, and several frontal regions, which were found to be correlated with planning and higher order executive functioning. Furthermore, our study supports the brain vertical organization of cognitive functioning, with the participation of the cortex, thalamus, basal ganglia, and cerebellum.
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Affiliation(s)
- Jordi A Matías-Guiu
- Department of Neurology, San Carlos Institute for Health Research, Hospital Clinico San Carlos, Universidad Complutense de Madrid, Madrid, Spain
| | - Ana Cortés-Martínez
- Department of Neurology, San Carlos Institute for Health Research, Hospital Clinico San Carlos, Universidad Complutense de Madrid, Madrid, Spain
| | - Paloma Montero
- Department of Neurology, San Carlos Institute for Health Research, Hospital Clinico San Carlos, Universidad Complutense de Madrid, Madrid, Spain
| | - Vanesa Pytel
- Department of Neurology, San Carlos Institute for Health Research, Hospital Clinico San Carlos, Universidad Complutense de Madrid, Madrid, Spain
| | - Teresa Moreno-Ramos
- Department of Neurology, San Carlos Institute for Health Research, Hospital Clinico San Carlos, Universidad Complutense de Madrid, Madrid, Spain
| | - Manuela Jorquera
- Department of Radiology, San Carlos Institute for Health Research, Hospital Clinico San Carlos, Universidad Complutense de Madrid, Madrid, Spain
| | - Miguel Yus
- Department of Radiology, San Carlos Institute for Health Research, Hospital Clinico San Carlos, Universidad Complutense de Madrid, Madrid, Spain
| | - Juan Arrazola
- Department of Radiology, San Carlos Institute for Health Research, Hospital Clinico San Carlos, Universidad Complutense de Madrid, Madrid, Spain
| | - Jorge Matías-Guiu
- Department of Neurology, San Carlos Institute for Health Research, Hospital Clinico San Carlos, Universidad Complutense de Madrid, Madrid, Spain
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47
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Tahedl M, Levine SM, Greenlee MW, Weissert R, Schwarzbach JV. Functional Connectivity in Multiple Sclerosis: Recent Findings and Future Directions. Front Neurol 2018; 9:828. [PMID: 30364281 PMCID: PMC6193088 DOI: 10.3389/fneur.2018.00828] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 09/14/2018] [Indexed: 02/03/2023] Open
Abstract
Multiple sclerosis is a debilitating disorder resulting from scattered lesions in the central nervous system. Because of the high variability of the lesion patterns between patients, it is difficult to relate existing biomarkers to symptoms and their progression. The scattered nature of lesions in multiple sclerosis offers itself to be studied through the lens of network analyses. Recent research into multiple sclerosis has taken such a network approach by making use of functional connectivity. In this review, we briefly introduce measures of functional connectivity and how to compute them. We then identify several common observations resulting from this approach: (a) high likelihood of altered connectivity in deep-gray matter regions, (b) decrease of brain modularity, (c) hemispheric asymmetries in connectivity alterations, and (d) correspondence of behavioral symptoms with task-related and task-unrelated networks. We propose incorporating such connectivity analyses into longitudinal studies in order to improve our understanding of the underlying mechanisms affected by multiple sclerosis, which can consequently offer a promising route to individualizing imaging-related biomarkers for multiple sclerosis.
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Affiliation(s)
- Marlene Tahedl
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
- Institute for Experimental Psychology, University of Regensburg, Regensburg, Germany
| | - Seth M. Levine
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Mark W. Greenlee
- Institute for Experimental Psychology, University of Regensburg, Regensburg, Germany
| | - Robert Weissert
- Department of Neurology, University of Regensburg, Regensburg, Germany
| | - Jens V. Schwarzbach
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
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48
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Coric D, Nij Bijvank JA, van Rijn LJ, Petzold A, Balk LJ. The role of optical coherence tomography and infrared oculography in assessing the visual pathway and CNS in multiple sclerosis. Neurodegener Dis Manag 2018; 8:323-335. [DOI: 10.2217/nmt-2018-0011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
In this review, a current overview is provided of how optical coherence tomography and infrared oculography can aid in assessing the visual system and CNS in multiple sclerosis (MS). Both afferent and efferent visual disorders are common in MS and visual complaints can have a tremendous impact on daily functioning. Optical coherence tomography and infrared oculography can detect and quantify visual disorders with high accuracy, but could also serve as quantitative markers for inflammation, neurodegeneration and network changes including cognitive decline in MS patients. The assessment of the efferent and afferent visual pathways is relevant for monitoring and predicting the disease course, but is also potentially valuable as an outcome measure in therapeutic trials.
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Affiliation(s)
- Danko Coric
- Department of Neurology, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, The Netherlands
| | - Jenny A Nij Bijvank
- Department of Neurology, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, The Netherlands
- Department of Ophthalmology, VU University Medical Centre, Amsterdam, The Netherlands
| | - Laurentius J van Rijn
- Department of Ophthalmology, VU University Medical Centre, Amsterdam, The Netherlands
| | - Axel Petzold
- Department of Neurology, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, The Netherlands
- Moorfields Eye Hospital & The National Hospital for Neurology & Neurosurgery, London, UK
| | - Lisanne J Balk
- Department of Neurology, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, The Netherlands
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49
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Castellazzi G, Debernard L, Melzer TR, Dalrymple-Alford JC, D'Angelo E, Miller DH, Gandini Wheeler-Kingshott CAM, Mason DF. Functional Connectivity Alterations Reveal Complex Mechanisms Based on Clinical and Radiological Status in Mild Relapsing Remitting Multiple Sclerosis. Front Neurol 2018; 9:690. [PMID: 30177910 PMCID: PMC6109785 DOI: 10.3389/fneur.2018.00690] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 07/30/2018] [Indexed: 11/13/2022] Open
Abstract
Resting state functional MRI (rs-fMRI) has provided important insights into functional reorganization in subjects with Multiple Sclerosis (MS) at different stage of disease. In this cross-sectional study we first assessed, by means of rs-fMRI, the impact of overall T2 lesion load (T2LL) and MS severity score (MSSS) on resting state networks (RSNs) in 62 relapsing remitting MS (RRMS) patients with mild disability (MSSS < 3). Independent Component Analysis (ICA) followed by dual regression analysis confirmed functional connectivity (FC) alterations of many RSNs in RRMS subjects compared to healthy controls. The anterior default mode network (DMNa) and the superior precuneus network (PNsup) showed the largest areas of decreased FC, while the sensory motor networks area M1 (SMNm1) and the medial visual network (MVN) showed the largest areas of increased FC. In order to better understand the nature of these alterations as well as the mechanisms of functional alterations in MS we proposed a method, based on linear regression, that takes into account FC changes and their correlation with T2LL and MSSS. Depending on the sign of the correlation between FC and T2LL, and furthermore the sign of the correlation with MSSS, we suggested the following possible underlying mechanisms to interpret altered FC: (1) FC reduction driven by MS lesions, (2) "true" functional compensatory mechanism, (3a) functional compensation attempt, (3b) "false" functional compensation, (4a) neurodegeneration, (4b) pre-symptomatic condition (damage precedes MS clinical manifestation). Our data shows areas satisfying 4 of these 6 conditions (i.e., 1,2,3b,4b), supporting the suggestion that increased FC has a complex nature that may exceed the simplistic assumption of an underlying compensatory mechanism attempting to limit the brain damage caused by MS progression. Exploring differences between RRMS subjects with short disease duration (MSshort) and RRMS with similar disability but longer disease duration (MSlong), we found that MSshort and MSlong were characterized by clearly distinct pattern of FC, involving predominantly sensory and cognitive networks respectively. Overall, these results suggest that the analysis of FC alterations in multiple large-scale networks in relation to radiological (T2LL) and clinical (MSSS, disease duration) status may provide new insights into the pathophysiology of relapse onset MS evolution.
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Affiliation(s)
- Gloria Castellazzi
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, UCL Institute of Neurology, London, United Kingdom.,Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Laetitia Debernard
- New Zealand Brain Research Institute, Christchurch, New Zealand.,Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Tracy R Melzer
- New Zealand Brain Research Institute, Christchurch, New Zealand.,Department of Medicine, University of Otago, Christchurch, New Zealand.,Brain Research New Zealand, Auckland, New Zealand
| | - John C Dalrymple-Alford
- New Zealand Brain Research Institute, Christchurch, New Zealand.,Brain Research New Zealand, Auckland, New Zealand.,Department of Psychology, University of Canterbury, Christchurch, New Zealand
| | - Egidio D'Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy
| | - David H Miller
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, UCL Institute of Neurology, London, United Kingdom.,New Zealand Brain Research Institute, Christchurch, New Zealand.,Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, UCL Institute of Neurology, London, United Kingdom.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Brain MRI 3T Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Deborah F Mason
- New Zealand Brain Research Institute, Christchurch, New Zealand.,Department of Medicine, University of Otago, Christchurch, New Zealand.,Department of Neurology, Christchurch Hospital, Christchurch, New Zealand
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50
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Eijlers AJC, Meijer KA, van Geest Q, Geurts JJG, Schoonheim MM. Determinants of Cognitive Impairment in Patients with Multiple Sclerosis with and without Atrophy. Radiology 2018; 288:544-551. [DOI: 10.1148/radiol.2018172808] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Anand J. C. Eijlers
- From the Department of Anatomy & Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Kim A. Meijer
- From the Department of Anatomy & Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Quinten van Geest
- From the Department of Anatomy & Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Jeroen J. G. Geurts
- From the Department of Anatomy & Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Menno M. Schoonheim
- From the Department of Anatomy & Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
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