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De Rosa AP, d'Ambrosio A, Bisecco A, Altieri M, Cirillo M, Gallo A, Esposito F. Functional gradients reveal cortical hierarchy changes in multiple sclerosis. Hum Brain Mapp 2024; 45:e26678. [PMID: 38647001 PMCID: PMC11033924 DOI: 10.1002/hbm.26678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 02/26/2024] [Accepted: 03/25/2024] [Indexed: 04/25/2024] Open
Abstract
Functional gradient (FG) analysis represents an increasingly popular methodological perspective for investigating brain hierarchical organization but whether and how network hierarchy changes concomitant with functional connectivity alterations in multiple sclerosis (MS) has remained elusive. Here, we analyzed FG components to uncover possible alterations in cortical hierarchy using resting-state functional MRI (rs-fMRI) data acquired in 122 MS patients and 97 healthy control (HC) subjects. Cortical hierarchy was assessed by deriving regional FG scores from rs-fMRI connectivity matrices using a functional parcellation of the cerebral cortex. The FG analysis identified a primary (visual-to-sensorimotor) and a secondary (sensory-to-transmodal) component. Results showed a significant alteration in cortical hierarchy as indexed by regional changes in FG scores in MS patients within the sensorimotor network and a compression (i.e., a reduced standard deviation across all cortical parcels) of the sensory-transmodal gradient axis, suggesting disrupted segregation between sensory and cognitive processing. Moreover, FG scores within limbic and default mode networks were significantly correlated (ρ = 0.30 $$ \rho =0.30 $$ , p < .005 after Bonferroni correction for both) with the symbol digit modality test (SDMT) score, a measure of information processing speed commonly used in MS neuropsychological assessments. Finally, leveraging supervised machine learning, we tested the predictive value of network-level FG features, highlighting the prominent role of the FG scores within the default mode network in the accurate prediction of SDMT scores in MS patients (average mean absolute error of 1.22 ± 0.07 points on a hold-out set of 24 patients). Our work provides a comprehensive evaluation of FG alterations in MS, shedding light on the hierarchical organization of the MS brain and suggesting that FG connectivity analysis can be regarded as a valuable approach in rs-fMRI studies across different MS populations.
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Affiliation(s)
- Alessandro Pasquale De Rosa
- Advanced MRI Neuroimaging Centre, Department of Advanced Medical and Surgical SciencesUniversity of Campania “Luigi Vanvitelli”NaplesItaly
| | - Alessandro d'Ambrosio
- Advanced MRI Neuroimaging Centre, Department of Advanced Medical and Surgical SciencesUniversity of Campania “Luigi Vanvitelli”NaplesItaly
| | - Alvino Bisecco
- Advanced MRI Neuroimaging Centre, Department of Advanced Medical and Surgical SciencesUniversity of Campania “Luigi Vanvitelli”NaplesItaly
| | - Manuela Altieri
- Advanced MRI Neuroimaging Centre, Department of Advanced Medical and Surgical SciencesUniversity of Campania “Luigi Vanvitelli”NaplesItaly
| | - Mario Cirillo
- Advanced MRI Neuroimaging Centre, Department of Advanced Medical and Surgical SciencesUniversity of Campania “Luigi Vanvitelli”NaplesItaly
| | - Antonio Gallo
- Advanced MRI Neuroimaging Centre, Department of Advanced Medical and Surgical SciencesUniversity of Campania “Luigi Vanvitelli”NaplesItaly
| | - Fabrizio Esposito
- Advanced MRI Neuroimaging Centre, Department of Advanced Medical and Surgical SciencesUniversity of Campania “Luigi Vanvitelli”NaplesItaly
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Rocca MA, D’Amore G, Valsasina P, Tedone N, Meani A, Filippi M. 2.5-Year changes of connectivity dynamism are relevant for physical and cognitive deterioration in multiple sclerosis. Mult Scler 2024; 30:546-557. [PMID: 38372039 PMCID: PMC11010569 DOI: 10.1177/13524585241231155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 01/11/2024] [Accepted: 01/20/2024] [Indexed: 02/20/2024]
Abstract
BACKGROUND In MS, functional connectivity (FC) dynamism may influence disease evolution. OBJECTIVES The objective is to assess time-varying functional connectivity (TVFC) changes over time at 2.5-year follow-up in MS patients according to physical and cognitive worsening. METHODS We collected 3T magnetic resonance imaging (MRI) for TVFC assessment (performed using sliding-window analysis of centrality) and clinical evaluations at baseline and 2.5-year follow-up from 28 healthy controls and 129 MS patients. Of these, 79 underwent baseline and follow-up neuropsychological assessment. At 2.5 years, physical/cognitive worsening was defined according to disability/neuropsychological score changes. RESULTS At follow-up, 25/129 (19.3%) MS patients worsened physically and 14/79 (17.7%) worsened cognitively. At baseline, MS patients showed reduced TVFC versus controls. At 2.5-year follow-up, no TVFC changes were detected in controls. Conversely, TVFC decreased over time in parieto-temporal regions in stable MS patients and in default-mode network in worsened MS. In physically worsened MS, basal ganglia TVFC reductions were also found. Reduced TVFC over time in the putamen in physically worsened and reduced TVFC in the precuneus in cognitively worsened were significant versus stable MS. DISCUSSION At 2.5-year follow-up, default-mode network TVFC reductions were found in worsening MS. Moreover, reduced deep gray matter TVFC characterized physically worsened patients, whereas precuneus involvement characterized cognitively worsened MS patients.
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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
| | - Giulia D’Amore
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Nicolò Tedone
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandro Meani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- 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
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Formica C, Bonanno M, Sorbera C, Quartarone A, Giambò FM, Marra A, Calabrò RS. Smartphone-Based Cognitive Telerehabilitation: A Usability and Feasibility Study Focusing on Mild Cognitive Impairment. Sensors (Basel) 2024; 24:525. [PMID: 38257618 PMCID: PMC10820398 DOI: 10.3390/s24020525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/03/2024] [Accepted: 01/12/2024] [Indexed: 01/24/2024]
Abstract
The implementation of cognitive health apps in patients with mild cognitive impairment (MCI) is challenging because of their cognitive, age, and other clinical characteristics. In this project, we aimed to evaluate the usability and feasibility of the Rehastart app tested in MCI patients. Eighteen subjects affected by MCI due to neurodegenerative disorders (including Parkinson's disease, multiple sclerosis, and amnestic/multidomain MCI) and eighteen healthcare professionals were recruited to this study. Patients were registered on the app by clinicians and they were assigned a protocol of specific cognitive exercises. The recruitment was conducted in the period between March and June 2023. The trial testing of the app consisted of three sessions per week for three weeks, with each session lasting about 30 min. After three weeks, the participants as well as medical personnel were invited to rate the usability and feasibility of the Rehastart mobile application. The instruments employed to evaluate the usability and feasibility of the app were the System Usability Scale (SUS), The Intrinsic Motivation Inventory (IMI) and the Client Satisfaction Questionnaire (CSQ). We did not find statistically significant differences on the SUS (p = 0.07) between healthcare professionals and patients. In addition, we found promising results on subscales of the Intrinsic Motivation Inventory, suggesting high levels of interest and enjoyment when using the Rehastart app. Our study demonstrated that smartphone-based telerehabilitation could be a suitable tool for people with MCI due to neurodegenerative disorders, since the Rehastart app was easy to use and motivating for both patients and healthy people.
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Affiliation(s)
| | - Mirjam Bonanno
- IRCCS Centro Neurolesi Bonino-Pulejo, Cda Casazza, S.S. 113, 98124 Messina, Italy; (C.F.); (C.S.); (A.Q.); (F.M.G.); (A.M.); (R.S.C.)
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Zhu X, Zhou Y, Zhong W, Li Y, Wang J, Chen Y, Zhang R, Sun J, Sun Y, Lou M. Higher Functional Connectivity of Ventral Attention and Visual Network to Maintain Cognitive Performance in White Matter Hyperintensity. Aging Dis 2023:AD.2022.1206. [PMID: 37163435 PMCID: PMC10389834 DOI: 10.14336/ad.2022.1206] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 12/06/2022] [Indexed: 05/12/2023] Open
Abstract
Ventral attention network (VAN), associated with cognitive performance, is one of the functional networks that are most vulnerable in white matter hyperintensity (WMH). Considering the global interaction of networks for cognitive performance, we hypothesized that VAN-related between-network connectivity might play a role in maintaining cognition in patients with WMH. We included 139 participants for both cross-sectional and longitudinal analysis from CIRCLE study (ClinicalTrials.gov ID: NCT03542734) between January 2014 and January 2021. Differences of VAN-related between-network connectivity were compared between normal-cognition (NC) and cognitive-impairment (CI) groups cross-sectionally, and between cognitive-decline (CD) and cognitive non-decline (CND) groups longitudinally by using t-test. False Discovery Rate was used for multiple comparison correction. The relationship between the network connectivity and WMH was tested on linear and quadratic models. Subgroup analysis of different WMH burdens were performed to test the difference of network connectivity between NC and CI groups. Among VAN-related between-network connectivity, only VAN-Visual Network (VN) connectivity was higher both in NC (n = 106) and CND (n = 113) groups versus CI (n = 33) and CD groups (n = 26), respectively. There was an inverted U-shaped relation between periventricular WMH (PWMH) burden and VAN-VN connectivity. Normal-cognition participants had higher VAN-VN connectivity among high, but not low PWMH burden subgroups. These findings suggest that the VAN-VN connectivity plays an important role in maintaining cognitive performance in WMH patients. It may serve as a unique marker for cognitive prediction and a potential target for intervention to prevent cognitive decline in WMH patients.
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Affiliation(s)
- Xiao Zhu
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Ying Zhou
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Wansi Zhong
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Yifei Li
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Junjun Wang
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
- Department of Neurology, Zhejiang Hospital, Hangzhou, China
| | - Yuping Chen
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Ruoxia Zhang
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Jianzhong Sun
- Department of Radiology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
| | - Yu Sun
- Key Laboratory for Biomedical Engineering of Ministry of Education of China, Zhejiang University, Zhejiang, China
| | - Min Lou
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
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Colato E, Prados F, Stutters J, Bianchi A, Narayanan S, Arnold DL, Wheeler-Kingshott C, Barkhof F, Ciccarelli O, Chard DT, Eshaghi A. Networks of microstructural damage predict disability in multiple sclerosis. J Neurol Neurosurg Psychiatry 2023; 94:992-1003. [PMID: 37468305 DOI: 10.1136/jnnp-2022-330203] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 06/13/2023] [Indexed: 07/21/2023]
Abstract
BACKGROUND Network-based measures are emerging MRI markers in multiple sclerosis (MS). We aimed to identify networks of white (WM) and grey matter (GM) damage that predict disability progression and cognitive worsening using data-driven methods. METHODS We analysed data from 1836 participants with different MS phenotypes (843 in a discovery cohort and 842 in a replication cohort). We calculated standardised T1-weighted/T2-weighted (sT1w/T2w) ratio maps in brain GM and WM, and applied spatial independent component analysis to identify networks of covarying microstructural damage. Clinical outcomes were Expanded Disability Status Scale worsening confirmed at 24 weeks (24-week confirmed disability progression (CDP)) and time to cognitive worsening assessed by the Symbol Digit Modalities Test (SDMT). We used Cox proportional hazard models to calculate predictive value of network measures. RESULTS We identified 8 WM and 7 GM sT1w/T2w networks (of regional covariation in sT1w/T2w measures) in both cohorts. Network loading represents the degree of covariation in regional T1/T2 ratio within a given network. The loading factor in the anterior corona radiata and temporo-parieto-frontal components were associated with higher risks of developing CDP both in the discovery (HR=0.85, p<0.05 and HR=0.83, p<0.05, respectively) and replication cohorts (HR=0.84, p<0.05 and HR=0.80, p<0.005, respectively). The decreasing or increasing loading factor in the arcuate fasciculus, corpus callosum, deep GM, cortico-cerebellar patterns and lesion load were associated with a higher risk of developing SDMT worsening both in the discovery (HR=0.82, p<0.01; HR=0.87, p<0.05; HR=0.75, p<0.001; HR=0.86, p<0.05 and HR=1.27, p<0.0001) and replication cohorts (HR=0.82, p<0.005; HR=0.73, p<0.0001; HR=0.80, p<0.005; HR=0.85, p<0.01 and HR=1.26, p<0.0001). CONCLUSIONS GM and WM networks of microstructural changes predict disability and cognitive worsening in MS. Our approach may be used to identify patients at greater risk of disability worsening and stratify cohorts in treatment trials.
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Affiliation(s)
- Elisa Colato
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Ferran Prados
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Jonathan Stutters
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Alessia Bianchi
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Douglas L Arnold
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Claudia Wheeler-Kingshott
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Brain Connectivity Centre, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Frederik Barkhof
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, location Vrije Universiteit, Amsterdam, Netherlands
- Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre (BRC), London, UK
| | - Olga Ciccarelli
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre (BRC), London, UK
| | - Declan T Chard
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre (BRC), London, UK
| | - Arman Eshaghi
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
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Azzimonti M, Preziosa P, Pagani E, Valsasina P, Tedone N, Vizzino C, Rocca MA, Filippi M. Functional and structural brain MRI changes associated with cognitive worsening in multiple sclerosis: a 3-year longitudinal study. J Neurol 2023; 270:4296-4308. [PMID: 37202603 DOI: 10.1007/s00415-023-11778-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/08/2023] [Accepted: 05/11/2023] [Indexed: 05/20/2023]
Abstract
BACKGROUND Heterogeneous processes may contribute to cognitive impairment in multiple sclerosis (MS). OBJECTIVE To apply a longitudinal multiparametric MRI approach to identify mechanisms associated with cognitive worsening in MS patients. METHODS 3 T brain functional and structural MRI scans were acquired at baseline and after a median follow-up of 3.4 years in 35 MS patients and 22 healthy controls (HC). Associations between cognitive worsening (reliable change index score < - 1.25 at the Rao's battery) and longitudinal changes in regional T2-hyperintense white matter (WM) lesions, diffusion tensor microstructural WM damage, gray matter (GM) atrophy and resting state (RS) functional connectivity (FC) were explored. RESULTS At follow-up, HC showed no clusters of significant microstructural WM damage progression, GM atrophy or changes in RS FC. At follow-up, 10 MS patients (29%) showed cognitive worsening. Compared to cognitively stable, cognitively worsened MS patients showed more severe GM atrophy of the right anterior cingulate cortex and bilateral supplementary motor area (p < 0.001). Cognitively worsened vs cognitively stable MS patients showed also decreased RS FC in the right hippocampus of the right working memory network and in the right insula of the default mode network. Increased RS FC in the left insula of the executive control network was found in the opposite comparison (p < 0.001). No significant regional accumulation of focal WM lesions nor microstructural WM abnormalities occurred in both patients' groups. CONCLUSIONS GM atrophy progression in cognitively relevant brain regions combined with functional impoverishment in networks involved in cognitive functions may represent the substrates underlying cognitive worsening in MS.
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Affiliation(s)
- Matteo Azzimonti
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
| | - Nicolò Tedone
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
| | - Carmen Vizzino
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, 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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8
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Mantwill M, Asseyer S, Chien C, Kuchling J, Schmitz-Hübsch T, Brandt AU, Haynes JD, Paul F, Finke C. Functional connectome fingerprinting and stability in multiple sclerosis. Mult Scler J Exp Transl Clin 2023; 9:20552173231195879. [PMID: 37641618 PMCID: PMC10460476 DOI: 10.1177/20552173231195879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 08/02/2023] [Indexed: 08/31/2023] Open
Abstract
Background Functional connectome fingerprinting can identify individuals based on their functional connectome. Previous studies relied mostly on short intervals between fMRI acquisitions. Objective This cohort study aimed to determine the stability of connectome-based identification and their underlying signatures in patients with multiple sclerosis and healthy individuals with long follow-up intervals. Methods We acquired resting-state fMRI in 70 patients with multiple sclerosis and 273 healthy individuals with long follow-up times (up to 4 and 9 years, respectively). Using functional connectome fingerprinting, we examined the stability of the connectome and additionally investigated which regions, connections and networks supported individual identification. Finally, we predicted cognitive and behavioural outcome based on functional connectivity. Results Multiple sclerosis patients showed connectome stability and identification accuracies similar to healthy individuals, with longer time delays between imaging sessions being associated with accuracies dropping from 89% to 76%. Lesion load, brain atrophy or cognitive impairment did not affect identification accuracies within the range of disease severity studied. Connections from the fronto-parietal and default mode network were consistently most distinctive, i.e., informative of identity. The functional connectivity also allowed the prediction of individual cognitive performances. Conclusion Our results demonstrate that discriminatory signatures in the functional connectome are stable over extended periods of time in multiple sclerosis, resulting in similar identification accuracies and distinctive long-lasting functional connectome fingerprinting signatures in patients and healthy individuals.
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Affiliation(s)
- Maron Mantwill
- Maron Mantwill, Hertzbergstraße 12, 12055 Berlin, Germany.
| | - Susanna Asseyer
- A cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin, Experimental and Clinical Research Center, Berlin, Germany
- Neuroscience Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Claudia Chien
- A cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin, Experimental and Clinical Research Center, Berlin, Germany
- Neuroscience Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, Charitéplatz, Berlin, Germany
| | - Joseph Kuchling
- Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
- A cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin, Experimental and Clinical Research Center, Berlin, Germany
- Neuroscience Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Tanja Schmitz-Hübsch
- A cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin, Experimental and Clinical Research Center, Berlin, Germany
- Neuroscience Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Alexander U Brandt
- A cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin, Experimental and Clinical Research Center, Berlin, Germany
- Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Department of Neurology, University of California, Irvine, CA, USA
| | - John-Dylan Haynes
- Faculty of Philosophy, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin Berlin, Berlin, Germany
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9
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Tozlu C, Card S, Jamison K, Gauthier SA, Kuceyeski A. Larger lesion volume in people with multiple sclerosis is associated with increased transition energies between brain states and decreased entropy of brain activity. Netw Neurosci 2023; 7:539-556. [PMID: 37397885 PMCID: PMC10312270 DOI: 10.1162/netn_a_00292] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 11/07/2022] [Indexed: 01/10/2024] Open
Abstract
Quantifying the relationship between the brain's functional activity patterns and its structural backbone is crucial when relating the severity of brain pathology to disability in multiple sclerosis (MS). Network control theory (NCT) characterizes the brain's energetic landscape using the structural connectome and patterns of brain activity over time. We applied NCT to investigate brain-state dynamics and energy landscapes in controls and people with MS (pwMS). We also computed entropy of brain activity and investigated its association with the dynamic landscape's transition energy and lesion volume. Brain states were identified by clustering regional brain activity vectors, and NCT was applied to compute the energy required to transition between these brain states. We found that entropy was negatively correlated with lesion volume and transition energy, and that larger transition energies were associated with pwMS with disability. This work supports the notion that shifts in the pattern of brain activity in pwMS without disability results in decreased transition energies compared to controls, but, as this shift evolves over the disease, transition energies increase beyond controls and disability occurs. Our results provide the first evidence in pwMS that larger lesion volumes result in greater transition energy between brain states and decreased entropy of brain activity.
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Affiliation(s)
- Ceren Tozlu
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Sophie Card
- Horace Greeley High School, Chappaqua, NY, USA
| | - Keith Jamison
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Susan A. Gauthier
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
- Judith Jaffe Multiple Sclerosis Center, Weill Cornell Medicine, New York, NY, USA
- Department of Neurology, Weill Cornell Medical College, New York, NY, USA
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
- Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
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10
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Gajofatto A, Cardobi N, Gobbin F, Calabrese M, Turatti M, Benedetti MD. Resting-state functional connectivity in multiple sclerosis patients receiving nabiximols for spasticity. BMC Neurol 2023; 23:128. [PMID: 36991352 DOI: 10.1186/s12883-023-03171-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 03/17/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND Nabiximols (Sativex®) is a cannabinoid approved for multiple sclerosis (MS)-related spasticity. Its mechanism of action is partially understood, and efficacy is variable. OBJECTIVE To conduct an exploratory analysis of brain networks connectivity changes on resting state (RS) functional MRI (fMRI) of MS patients treated with nabiximols. METHODS We identified a group of MS patients treated with Sativex® at Verona University Hospital, who underwent RS brain fMRI in the 4 weeks before (T0) and 4-8 weeks after (T1) treatment start. Sativex® response was defined as ≥ 20% spasticity Numerical Rating Scale score reduction at T1 vs. T0. Connectivity changes on fMRI were compared between T0 and T1 in the whole group and according to response status. ROI-to-ROI and seed-to-voxel connectivity were evaluated. RESULTS Twelve MS patients (7 males) were eligible for the study. Seven patients (58.3%) resulted Sativex® responders at T1. On fMRI analysis, Sativex® exposure was associated with global brain connectivity increase (particularly in responders), decreased connectivity of motor areas, and bidirectional connectivity changes of the left cerebellum with a number of cortical areas. CONCLUSIONS Nabiximols administration is associated with brain connectivity increase of MS patients with spasticity. Modulation of sensorimotor cortical areas and cerebellum connectivity could play a role in nabiximols effect.
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Affiliation(s)
- Alberto Gajofatto
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Piazzale L.A. Scuro 10, Verona, 37134, Italy.
- Unit of Neurology, Regional Multiple Sclerosis Center, Borgo Roma Hospital, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
| | - Nicolò Cardobi
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Piazzale L.A. Scuro 10, Verona, 37134, Italy
| | - Francesca Gobbin
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Piazzale L.A. Scuro 10, Verona, 37134, Italy
- Unit of Neurology, Regional Multiple Sclerosis Center, Borgo Roma Hospital, Azienda Ospedaliera Universitaria Integrata, Verona, Italy
| | - Massimiliano Calabrese
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Piazzale L.A. Scuro 10, Verona, 37134, Italy
- Unit of Neurology, Regional Multiple Sclerosis Center, Borgo Roma Hospital, Azienda Ospedaliera Universitaria Integrata, Verona, Italy
| | - Marco Turatti
- Unit of Neurology, Regional Multiple Sclerosis Center, Borgo Roma Hospital, Azienda Ospedaliera Universitaria Integrata, Verona, Italy
| | - Maria Donata Benedetti
- Unit of Neurology, Regional Multiple Sclerosis Center, Borgo Roma Hospital, Azienda Ospedaliera Universitaria Integrata, Verona, Italy
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11
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von Schwanenflug N, Koch SP, Krohn S, Broeders TAA, Lydon-Staley DM, Bassett DS, Schoonheim MM, Paul F, Finke C. Increased flexibility of brain dynamics in patients with multiple sclerosis. Brain Commun 2023; 5:fcad143. [PMID: 37188221 PMCID: PMC10176242 DOI: 10.1093/braincomms/fcad143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 03/08/2023] [Accepted: 04/28/2023] [Indexed: 05/17/2023] Open
Abstract
Patients with multiple sclerosis consistently show widespread changes in functional connectivity. Yet, alterations are heterogeneous across studies, underscoring the complexity of functional reorganization in multiple sclerosis. Here, we aim to provide new insights by applying a time-resolved graph-analytical framework to identify a clinically relevant pattern of dynamic functional connectivity reconfigurations in multiple sclerosis. Resting-state data from 75 patients with multiple sclerosis (N = 75, female:male ratio of 3:2, median age: 42.0 ± 11.0 years, median disease duration: 6 ± 11.4 years) and 75 age- and sex-matched controls (N = 75, female:male ratio of 3:2, median age: 40.2 ± 11.8 years) were analysed using multilayer community detection. Local, resting-state functional system and global levels of dynamic functional connectivity reconfiguration were characterized using graph-theoretical measures including flexibility, promiscuity, cohesion, disjointedness and entropy. Moreover, we quantified hypo- and hyper-flexibility of brain regions and derived the flexibility reorganization index as a summary measure of whole-brain reorganization. Lastly, we explored the relationship between clinical disability and altered functional dynamics. Significant increases in global flexibility (t = 2.38, PFDR = 0.024), promiscuity (t = 1.94, PFDR = 0.038), entropy (t = 2.17, PFDR = 0.027) and cohesion (t = 2.45, PFDR = 0.024) were observed in patients and were driven by pericentral, limbic and subcortical regions. Importantly, these graph metrics were correlated with clinical disability such that greater reconfiguration dynamics tracked greater disability. Moreover, patients demonstrate a systematic shift in flexibility from sensorimotor areas to transmodal areas, with the most pronounced increases located in regions with generally low dynamics in controls. Together, these findings reveal a hyperflexible reorganization of brain activity in multiple sclerosis that clusters in pericentral, subcortical and limbic areas. This functional reorganization was linked to clinical disability, providing new evidence that alterations of multilayer temporal dynamics play a role in the manifestation of multiple sclerosis.
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Affiliation(s)
- Nina von Schwanenflug
- Department of Neurology and Experimental Neurology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 10098, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin 10117, Germany
| | - Stefan P Koch
- Department of Experimental Neurology, Center for Stroke Research Berlin, Berlin 10117, Germany
- NeuroCure Cluster of Excellence and Charité Core Facility 7T Experimental MRIs, Charité - Universitätsmedizin Berlin, Berlin 10117, Germany
| | - Stephan Krohn
- Department of Neurology and Experimental Neurology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 10098, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin 10117, Germany
| | - Tommy A A Broeders
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1007 MB, The Netherlands
| | - David M Lydon-Staley
- Annenberg School for Communication, University of Pennsylvania, Philadelphia 19104, PA, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia 19104, PA, USA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia 19104, PA, USA
| | - Dani S Bassett
- Department of Biological Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia 19104, PA, USA
- Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia 19104, PA, USA
- Department of Electrical & Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia 19104, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, PA, USA
- Santa Fe Institute, Santa Fe 87501, NM, USA
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1007 MB, The Netherlands
| | - Friedemann Paul
- Department of Neurology and Experimental Neurology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 10098, Germany
- Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité—Universitätsmedizin Berlin, Berlin 10117, Germany
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 10017, Germany
| | - Carsten Finke
- Correspondence to: Carsten Finke Charité - Universitätsklinikum Berlin Department of Neurology and Experimental Neurology Campus Mitte, Bonhoeffer Weg 3, 10098 Berlin, Germany E-mail:
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12
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Has Silemek AC, Nolte G, Pöttgen J, Engel AK, Heesen C, Gold SM, Stellmann JP. Topological reorganization of brain network might contribute to the resilience of cognitive functioning in mildly disabled relapsing remitting multiple sclerosis. J Neurosci Res 2023; 101:143-161. [PMID: 36263462 DOI: 10.1002/jnr.25135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 09/28/2022] [Accepted: 10/05/2022] [Indexed: 11/08/2022]
Abstract
Multiple sclerosis (MS) is an inflammatory and demyelinating disease which leads to impairment in several functional systems including cognition. Alteration of brain networks is linked to disability and its progression. However, results are mostly cross-sectional and yet contradictory as putative adaptive and maladaptive mechanisms were found. Here, we aimed to explore longitudinal reorganization of brain networks over 2-years by combining diffusion tensor imaging (DTI), resting-state functional MRI (fMRI), magnetoencephalography (MEG), and a comprehensive neuropsychological-battery. In 37 relapsing-remitting MS (RRMS) and 39 healthy-controls, cognition remained stable over-time. We reconstructed network models based on the three modalities and analyzed connectivity in relation to the hierarchical topology and functional subnetworks. Network models were compared across modalities and in their association with cognition using linear-mixed-effect-regression models. Loss of hub connectivity and global reduction was observed on a structural level over-years (p < .010), which was similar for functional MEG-networks but not for fMRI-networks. Structural hub connectivity increased in controls (p = .044), suggesting a physiological mechanism of healthy aging. Despite a general loss in structural connectivity in RRMS, hub connectivity was preserved (p = .002) over-time in default-mode-network (DMN). MEG-networks were similar to DTI and weakly correlated with fMRI in MS (p < .050). Lower structural (β between .23-.33) and both lower (β between .40-.59) and higher functional connectivity (β = -.54) in DMN was associated with poorer performance in attention and memory in RRMS (p < .001). MEG-networks involved no association with cognition. Here, cognitive stability despite ongoing neurodegeneration might indicate a resilience mechanism of DMN hubs mimicking a physiological reorganization observed in healthy aging.
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Affiliation(s)
- Arzu Ceylan Has Silemek
- Institut für Neuroimmunologie und Multiple Sklerose, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Guido Nolte
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jana Pöttgen
- Institut für Neuroimmunologie und Multiple Sklerose, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany.,Klinik und Poliklinik für Neurologie, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Andreas K Engel
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christoph Heesen
- Institut für Neuroimmunologie und Multiple Sklerose, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany.,Klinik und Poliklinik für Neurologie, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Stefan M Gold
- Institut für Neuroimmunologie und Multiple Sklerose, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany.,Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt Universität zu Berlin, and Berlin Institute of Health (BIH), Klinik für Psychiatrie & Psychotherapie und Medizinische Klinik m.S. Psychosomatik, Campus Benjamin Franklin (CBF), Berlin, Germany
| | - Jan-Patrick Stellmann
- Institut für Neuroimmunologie und Multiple Sklerose, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany.,Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,APHM, Hopital de la Timone, CEMEREM, Marseille, France.,Aix-Marseille Université, CNRS, CRMBM, UMR 7339, Marseille, France
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13
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Schoonheim MM, Broeders TAA, Geurts JJG. The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics. Neuroimage Clin 2022; 35:103108. [PMID: 35917719 PMCID: PMC9421449 DOI: 10.1016/j.nicl.2022.103108] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/01/2022] [Accepted: 07/10/2022] [Indexed: 11/16/2022]
Abstract
Multiple sclerosis (MS) can be considered as a network disorder. This review discusses network concepts in order to understand progression in MS. Damage is hypothesized to lead to a “network collapse” and clinical progression. New concepts are discussed that will likely influence the field in the near future. These include brain wiring, how regions communicate and robustness to damage.
Multiple sclerosis is a neuroinflammatory and neurodegenerative disorder of the central nervous system that can be considered a network disorder. In MS, lesional pathology continuously disconnects structural pathways in the brain, forming a disconnection syndrome. Complex functional network changes then occur that are poorly understood but closely follow clinical status. Studying these structural and functional network changes has been and remains crucial to further decipher complex symptoms like cognitive impairment and physical disability. Recent insights especially implicate the importance of monitoring network hubs in MS, like the thalamus and default-mode network which seem especially hit hard. Such network insights in MS have led to the hypothesis that as the network continues to become disconnected and dysfunctional, exceeding a certain threshold of network efficiency loss leads to a “network collapse”. After this collapse, crucial network hubs become rigid and overloaded, and at the same time a faster neurodegeneration and accelerated clinical (and cognitive) progression can be seen. As network neuroscience has evolved, the MS field can now move towards a clearer classification of the network collapse itself and specific milestone events leading up to it. Such an updated network-focused conceptual framework of MS could directly impact clinical decision making as well as the design of network-tailored rehabilitation strategies. This review therefore provides an overview of recent network concepts that have enhanced our understanding of clinical progression in MS, especially focusing on cognition, as well as new concepts that will likely move the field forward in the near future.
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Affiliation(s)
- Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Tommy A A Broeders
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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14
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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: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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15
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Broeders TA, Douw L, Eijlers AJ, Dekker I, Uitdehaag BM, Barkhof F, Hulst HE, Vinkers CH, Geurts JJ, Schoonheim MM. A more unstable resting-state functional network in cognitively declining multiple sclerosis. Brain Commun 2022; 4:fcac095. [PMID: 35620116 PMCID: PMC9128379 DOI: 10.1093/braincomms/fcac095] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Revised: 02/14/2022] [Accepted: 04/11/2022] [Indexed: 11/24/2022] Open
Abstract
Cognitive impairment is common in people with multiple sclerosis and strongly
affects their daily functioning. Reports have linked disturbed cognitive
functioning in multiple sclerosis to changes in the organization of the
functional network. In a healthy brain, communication between brain regions and
which network a region belongs to is continuously and dynamically adapted to
enable adequate cognitive function. However, this dynamic network adaptation has
not been investigated in multiple sclerosis, and longitudinal network data
remain particularly rare. Therefore, the aim of this study was to longitudinally
identify patterns of dynamic network reconfigurations that are related to the
worsening of cognitive decline in multiple sclerosis. Resting-state functional
MRI and cognitive scores (expanded Brief Repeatable Battery of
Neuropsychological tests) were acquired in 230 patients with multiple sclerosis
and 59 matched healthy controls, at baseline (mean disease duration: 15 years)
and at 5-year follow-up. A sliding-window approach was used for functional MRI
analyses, where brain regions were dynamically assigned to one of seven
literature-based subnetworks. Dynamic reconfigurations of subnetworks were
characterized using measures of promiscuity (number of subnetworks switched to),
flexibility (number of switches), cohesion (mutual switches) and disjointedness
(independent switches). Cross-sectional differences between cognitive groups and
longitudinal changes were assessed, as well as relations with structural damage
and performance on specific cognitive domains. At baseline, 23% of
patients were cognitively impaired (≥2/7 domains
Z < −2) and 18% were mildly
impaired (≥2/7 domains
Z < −1.5). Longitudinally,
28% of patients declined over time (0.25 yearly change on ≥2/7
domains based on reliable change index). Cognitively impaired patients displayed
more dynamic network reconfigurations across the whole brain compared with
cognitively preserved patients and controls, i.e. showing higher promiscuity
(P = 0.047), flexibility
(P = 0.008) and cohesion
(P = 0.008). Over time, cognitively
declining patients showed a further increase in cohesion
(P = 0.004), which was not seen in stable
patients (P = 0.544). More cohesion was
related to more severe structural damage (average
r = 0.166,
P = 0.015) and worse verbal memory
(r = −0.156,
P = 0.022), information processing speed
(r = −0.202,
P = 0.003) and working memory
(r = −0.163,
P = 0.017). Cognitively impaired multiple
sclerosis patients exhibited a more unstable network reconfiguration compared to
preserved patients, i.e. brain regions switched between subnetworks more often,
which was related to structural damage. This shift to more unstable network
reconfigurations was also demonstrated longitudinally in patients that showed
cognitive decline only. These results indicate the potential relevance of a
progressive destabilization of network topology for understanding cognitive
decline in multiple sclerosis.
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Affiliation(s)
- Tommy A.A. Broeders
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Linda Douw
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anand J.C. Eijlers
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Iris Dekker
- Departments of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bernard M.J. Uitdehaag
- Departments of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Departments of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, UK
| | - Hanneke E. Hulst
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Christiaan H. Vinkers
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Departments of Psychiatry, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jeroen J.G. Geurts
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Menno M. Schoonheim
- Departments of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Landrigan J, Bessenyei K, Leitner D, Yakovenko I, Fisk JD, Prentice JL. A systematic review of the effects of cannabis on cognition in people with multiple sclerosis. Mult Scler Relat Disord 2022; 57:103338. [DOI: 10.1016/j.msard.2021.103338] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 10/05/2021] [Accepted: 10/15/2021] [Indexed: 02/07/2023]
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