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Gaspari M, Zini F, Stecchi S. Enhancing cognitive rehabilitation in multiple sclerosis with a disease-specific tool. Disabil Rehabil Assist Technol 2020; 18:313-326. [PMID: 33259243 DOI: 10.1080/17483107.2020.1849432] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
PURPOSE Computerised rehabilitation programs can be used to address cognitive deficits typically caused by multiple sclerosis (MS). However, there are still doubts on their effectiveness, due to mixed results obtained in clinical trials. The objective of this paper is to improve cognitive rehabilitation (CR) practices in MS, by presenting and assessing a MS-specific cognitive rehabilitation software. METHODS We conducted a detailed analysis of how CR is carried out in practice in MS rehabilitation centres. From the analysis, we elicited a reference CR process, and identified the essential features a software supporting the process should have. We designed and implemented MS-rehab, a novel MS-specific computerised rehabilitation system having the identified features. We experimented MS-rehab in a pilot study involving eight MS patients. To highlight the improvement with respect to the state of the art, we compared MS-rehab with available professional tools selected using well defined criteria. RESULTS This paper has three main contributions: (1) the identification of a set of essential features a computerised tool for CR in MS should provide; (2) MS-rehab, a novel CR system designed for MS therapists and patients, which embodies innovative MS specific features; (3) the assessment of MS-rehab efficacy in a pilot study with MS patients. CONCLUSIONS The availability of a MS-specific CR system like MS-rehab fosters the design of more rigorous clinical studies on the effectiveness of computerised rehabilitation in MS. MS-rehab demonstrated its potential and innovativeness as a tool for cognitive rehabilitation in MS.IMPLICATIONS FOR REHABILITATIONComputerized tools for cognitive rehabilitation (CR) in multiple sclerosis (MS) can be improved by a set of MS-specific features.The availability of advanced home-based cognitive rehabilitation mechanisms is fundamental for supporting standardized cognitive rehabilitation protocols in MS.A MS-specific CR system has given promising results in a pilot study involving MS patients.Hardly do state-of-the-art professional tools include all the required MS specific features.
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Affiliation(s)
- Mauro Gaspari
- Department of Computer Science and Engineering, University of Bologna, Bologna, Italy
| | - Floriano Zini
- Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy
| | - Sergio Stecchi
- Department of Computer Science and Engineering, University of Bologna, Bologna, Italy
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Altered phase and nonphase EEG activity expose impaired maintenance of a spatial-object attentional focus in multiple sclerosis patients. Sci Rep 2020; 10:20721. [PMID: 33244155 PMCID: PMC7691340 DOI: 10.1038/s41598-020-77690-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 11/04/2020] [Indexed: 11/09/2022] Open
Abstract
Some of the anatomical and functional basis of cognitive impairment in multiple sclerosis (MS) currently remains unknown. In particular, there is scarce knowledge about modulations in induced EEG (nonphase activity) for diverse frequency bands related to attentional deficits in this pathology. The present study analyzes phase and nonphase alpha and gamma modulations in 26 remitting-relapsing multiple sclerosis patients during their participation in the attention network test compared with twenty-six healthy controls (HCs) matched in sociodemographic variables. Behavioral results showed that the MS group exhibited general slowing, suggesting impairment in alerting and orienting networks, as has been previously described in other studies. Time–frequency analysis of EEG revealed that the gamma band was related to the spatial translation of the attentional focus, and the alpha band seemed to be related to the expectancy mechanisms and cognitive processing of the target. Moreover, phase and nonphase modulations differed in their psychophysiological roles and were affected differently in the MS and HC groups. In summary, nonphase modulations can unveil hidden cognitive mechanisms for phase analysis and complete our knowledge of the neural basis of cognitive impairment in multiple sclerosis pathology.
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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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Fritz NE, Edwards EM, Keller J, Eloyan A, Calabresi PA, Zackowski KM. Combining Magnetization Transfer Ratio MRI and Quantitative Measures of Walking Improves the Identification of Fallers in MS. Brain Sci 2020; 10:E822. [PMID: 33171942 PMCID: PMC7694635 DOI: 10.3390/brainsci10110822] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 10/27/2020] [Accepted: 11/04/2020] [Indexed: 12/22/2022] Open
Abstract
Multiple sclerosis (MS) impacts balance and walking function, resulting in accidental falls. History of falls and clinical assessment are commonly used for fall prediction, yet these measures have limited predictive validity. Falls are multifactorial; consideration of disease-specific pathology may be critical for improving fall prediction in MS. The objective of this study was to examine the predictive value of clinical measures (i.e., walking, strength, sensation) and corticospinal tract (CST) MRI measures, both discretely and combined, to fall status in MS. Twenty-nine individuals with relapsing-remitting MS (mean ± SD age: 48.7 ± 11.5 years; 17 females; Expanded Disability Status Scale (EDSS): 4.0 (range 1-6.5); symptom duration: 11.9 ± 8.7 years; 14 fallers) participated in a 3T brain MRI including diffusion tensor imaging and magnetization transfer ratio (MTR) and clinical tests of walking, strength, sensation and falls history. Clinical measures of walking were significantly associated with CST fractional anisotropy and MTR. A model including CST MTR, walk velocity and vibration sensation explained >31% of the variance in fall status (R2 = 0.3181) and accurately distinguished 73.8% fallers, which was superior to stand-alone models that included only MRI or clinical measures. This study advances the field by combining clinical and MRI measures to improve fall prediction accuracy in MS.
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Affiliation(s)
- Nora E. Fritz
- Center for Movement Studies, Kennedy Krieger Institute, Baltimore, MD 21205, USA; (J.K.); (K.M.Z.)
- Department of Physical Medicine and Rehabilitation, Johns Hopkins School of Medicine, Baltimore, MD 21224, USA
- Program in Physical Therapy and Department of Neurology, Wayne State University, Detroit, MI 48201, USA
- Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, USA;
| | - Erin M. Edwards
- Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, USA;
| | - Jennifer Keller
- Center for Movement Studies, Kennedy Krieger Institute, Baltimore, MD 21205, USA; (J.K.); (K.M.Z.)
| | - Ani Eloyan
- Department of Biostatistics, Brown University, Providence, RI 02912, USA;
| | - Peter A. Calabresi
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21224, USA;
| | - Kathleen M. Zackowski
- Center for Movement Studies, Kennedy Krieger Institute, Baltimore, MD 21205, USA; (J.K.); (K.M.Z.)
- Department of Physical Medicine and Rehabilitation, Johns Hopkins School of Medicine, Baltimore, MD 21224, USA
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21224, USA;
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Kolanko M, Win Z, Patel N, Malik O, Carswell C, Gontsarova A, Nicholas R, Perry R, Malhotra P. Using amyloid PET imaging to diagnose Alzheimer's disease in patients with multiple sclerosis. J Neurol 2020; 267:3268-3273. [PMID: 32556533 PMCID: PMC7578168 DOI: 10.1007/s00415-020-09969-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 04/23/2020] [Accepted: 06/01/2020] [Indexed: 12/02/2022]
Abstract
BACKGROUND Cognitive dysfunction affects 40-60% of individuals with multiple sclerosis (MS). The neuropsychological profile commonly consists of a subcortical pattern of deficits, although a proportion of patients have a severe progressive cortical dementia. However, patients with MS can be affected by other neurodegenerative diseases, such as Alzheimer's disease (AD). Little is known about the co-existence of these two conditions but distinguishing dementia due to MS alone from a coexisting neurodegenerative disease is challenging. Amyloid PET imaging has allowed improved AD diagnosis, especially in patients with atypical presentations or multiple possible causes of cognitive impairment. Amyloid PET demonstrates increased cortical signal in AD, whereas reductions in subcortical uptake are associated with demyelination. To the authors knowledge, there are no reports of clinical Amyloid PET use in MS patients with dementia. METHODS Here, three MS patients presenting to the Cognitive Neurology Clinic with progressive cognitive impairment are described. Due to lack of diagnostic clarity from standard investigations, they underwent Amyloid PET Imaging with 18F-florbetapir according to established appropriate use criteria and after review by a multidisciplinary team. RESULTS Two patients were diagnosed with AD based on positive Amyloid PET imaging and were subsequently started on cholinesterase inhibitor treatment. The other patient had a negative scan, leading to further investigations and identification of another potential cause of worsening cognitive impairment. CONCLUSIONS The experience from this case series suggests that Amyloid PET Imaging may be of diagnostic value in selected patients with MS and dementia. In these individuals, it may provide diagnostic clarity and assist with therapeutic decisions.
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Affiliation(s)
- Magdalena Kolanko
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W6 8RP, UK
- Department of Neurology, Imperial College Healthcare NHS Trust, London, UK
| | - Zarni Win
- Department of Nuclear Medicine, Imperial College Healthcare NHS Trust, London, UK
| | - Neva Patel
- Department of Nuclear Medicine, Imperial College Healthcare NHS Trust, London, UK
| | - Omar Malik
- Department of Neurology, Imperial College Healthcare NHS Trust, London, UK
| | | | | | - Richard Nicholas
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W6 8RP, UK
- Department of Neurology, Imperial College Healthcare NHS Trust, London, UK
| | - Richard Perry
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W6 8RP, UK
- Department of Neurology, Imperial College Healthcare NHS Trust, London, UK
| | - Paresh Malhotra
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W6 8RP, UK.
- Department of Neurology, Imperial College Healthcare NHS Trust, London, UK.
- UK Dementia Research Institute, Imperial College London, London, UK.
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Backward walking sensitively detects fallers in persons with multiple sclerosis. Mult Scler Relat Disord 2020; 45:102390. [DOI: 10.1016/j.msard.2020.102390] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 07/02/2020] [Accepted: 07/09/2020] [Indexed: 11/21/2022]
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Backward Walking and Dual-Task Assessment Improve Identification of Gait Impairments and Fall Risk in Individuals with MS. Mult Scler Int 2020; 2020:6707414. [PMID: 32963832 PMCID: PMC7495208 DOI: 10.1155/2020/6707414] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 08/25/2020] [Accepted: 08/28/2020] [Indexed: 11/30/2022] Open
Abstract
Background Individuals with multiple sclerosis (MS) experience deficits in motor and cognitive domains, resulting in impairment in dual-task walking ability. The goal of this study was to compare performance of forward walking and backward walking in single- and dual-task conditions in persons with MS to age- and sex-matched healthy controls. We also examined relationships between forward and backward walking to cognitive function, balance, and retrospective fall reports. Methods All measures were collected in a single session. A 2 × 2 × 2 mixed model ANOVA was used to compare differences in forward and backward walking in single- and dual-task conditions between MS and healthy controls. Spearman correlations were used to examine relationships between gait and cognitive function, falls, and balance. Results Eighteen individuals with relapsing-remitting MS and 14 age- and sex-matched healthy controls participated. Backward walking velocity revealed significant differences between groups for both single-task (p = 0.015) and dual-task (p = 0.014) conditions. Persons with MS demonstrated significant differences between single- and dual-task forward and backward walking velocities (p = 0.023; p = 0.004), whereas this difference was only apparent in the backward walking condition for healthy controls (p = 0.004). In persons with MS, there were significant differences in double support time between single- and dual-task conditions in both backward (p < 0.001) and forward (p = 0.001) directions. More falls at six months were significantly associated with shorter backward dual-task stride length (r = −0.490; p = 0.046) and slower velocity (r = −0.483; p = 0.050). Conclusion Differences in MS and age- and sex-matched healthy controls are more pronounced during backward compared to forward walking under single- and dual-task conditions. Future work with a larger sample size is needed to validate the clinical utility of backward walking and dual-task assessments and mitigate the limited sensitivity of the current dual-task assessments that primarily rely upon forward walking.
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58
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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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Effect of a Combined Program of Strength and Dual Cognitive-Motor Tasks in Multiple Sclerosis Subjects. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17176397. [PMID: 32887411 PMCID: PMC7503584 DOI: 10.3390/ijerph17176397] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 08/26/2020] [Accepted: 09/01/2020] [Indexed: 12/29/2022]
Abstract
This study investigated the effects of a 24-week combined training program (CTP) based on strength exercises and cognitive–motor tasks performed concurrently in participants with multiple sclerosis. A randomized, controlled intervention study was carried out. In total, 31 subjects with a confirmed diagnosis of multiple sclerosis (14 men and 17 women) were stratified and randomized into an intervention group (17 subjects) and a control group (14 subjects). The intervention group completed three weekly training sessions for 24 weeks, while the control group pursued their normal daily activities. In this program, cognitive–motor tasks were completed at once (dual tasking). A 3D photogrammetry connected to a selective attention system designed for dual tasking while walking was used. Ground reaction forces were measured using two force plates, one for sit-to-stand testing, while the other was used for static force measurement. Postural equilibrium was examined using a stabilometric plate based for Romberg test assessment. The 24-week training program for multiple sclerosis patients improved their static peak force by 11% (p < 0 .05), their rate of force development by 36% (p < 0.05), and their balance (p < 0.05). Performance in daily activities such as walking or sitting-to-standing improved significantly in multiple sclerosis participants. CTP training was effective in reducing the dual-task costs of step length (48%) and walking velocity (54%), as compared to a matched control group.
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McComb M, Parambi R, Browne RW, Bodziak ML, Jakimovski D, Bergsland N, Maceski A, Weinstock-Guttman B, Kuhle J, Zivadinov R, Ramanathan M. Apolipoproteins AI and E are associated with neuroaxonal injury to gray matter in multiple sclerosis. Mult Scler Relat Disord 2020; 45:102389. [PMID: 32683305 DOI: 10.1016/j.msard.2020.102389] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 06/03/2020] [Accepted: 07/07/2020] [Indexed: 01/08/2023]
Abstract
Purpose To investigate the associations between longitudinal changes in lipid biomarkers and serum neurofilament (sNfL) levels in multiple sclerosis (MS) neurodegeneration and disease progression. Methods 5-year prospective, longitudinal study included 75 relapsing-remitting MS (RR-MS) and 37 progressive-MS (P-MS) patients. sNfL, plasma total cholesterol (TC), high-density (HDL-C) and low-density (LDL-C) lipoprotein cholesterol, apolipoproteins (Apo), ApoA-I, Apo-II, ApoB, ApoC-II and ApoE were measured at baseline and 5-years. Annual percent changes in whole brain volume (PBVC), gray matter volume (PGMVC) and cortical volume (PCVC) were obtained from MRI at baseline and 5-years. Results sNfL levels at 5-year follow-up were associated with ApoE at follow-up (p = 0.014), age at follow-up, body mass index (p < 0.001) and RR vs. P-MS status at follow-up. APOE4 allele was associated with greater sNfL levels at 5-years (p = 0.022) and pronounced in the P-MS group. PGMVC and PCVC were associated with percent changes in HDL-C (p = 0018 and p < 0.001, respectively) and ApoA-I (p = 0.0073 and p = 0.006). PGMVC and PCVC remained associated with percent change in HDL-C (p = 0.0024 and p < 0.001, respectively) after sNfL was included as a predictor. Conclusions HDL-C percent change is associated with decreased gray matter atrophy after adjusting for baseline sNfL.
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Affiliation(s)
- Mason McComb
- Department of Pharmaceutical Sciences, State University of New York, Buffalo, NY, USA
| | - Robert Parambi
- Department of Pharmaceutical Sciences, State University of New York, Buffalo, NY, USA
| | - Richard W Browne
- Department of Biotechnical and Clinical Laboratory Sciences, State University of New York, Buffalo, NY, USA
| | - Mary Lou Bodziak
- Department of Biotechnical and Clinical Laboratory Sciences, State University of New York, Buffalo, NY, USA
| | - Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, USA; IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy
| | - Aleksandra Maceski
- Neurologic Clinic and Policlinic, Departments of Medicine, Biomedicine and Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Bianca Weinstock-Guttman
- Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Jens Kuhle
- Neurologic Clinic and Policlinic, Departments of Medicine, Biomedicine and Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, USA; Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Murali Ramanathan
- Department of Pharmaceutical Sciences, State University of New York, Buffalo, NY, USA; Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, USA.
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Kiljan S, Prins M, Baselmans BM, Bol JGJM, Schenk GJ, van Dam AM. Enhanced GABAergic Immunoreactivity in Hippocampal Neurons and Astroglia of Multiple Sclerosis Patients. J Neuropathol Exp Neurol 2020; 78:480-491. [PMID: 31100147 PMCID: PMC6524632 DOI: 10.1093/jnen/nlz028] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Cognitive dysfunction occurs frequently in multiple sclerosis (MS). Research suggests that hippocampal lesions and GABAergic neurotransmitter changes contribute to cognitive dysfunction. In the present study, we aim to determine the cellular changes in GABAergic expression in MS hippocampus related to inflammation and demyelination. To this end, the presence and inflammatory activity of demyelinating lesions was determined by immunohistochemistry in human postmortem hippocampal tissue of 15 MS patients and 9 control subjects. Subsequently, GABAergic cells were visualized using parvalbumin (PV) and glutamate acid decarboxylase 67 (GAD67) markers. Fluorescent colabeling was performed of GAD67 with neuronal nuclei, PV, astrocytic glial fibrillary acidic protein, or vesicular GABA transporter. We observed increased GAD67-positive (GAD67+) neuron and synapse numbers in the CA1 of MS patients with active hippocampal lesions, not due to neurogenesis. The number and size of PV-positive neurons remained unchanged. GAD67+ astrocytes were more numerous in hippocampal white matter than grey matter lesions. Additionally, in MS patients with active hippocampal lesions GAD67+ astrocyte surface area was increased. Disturbed cognition was most prevalent in MS patients with active hippocampal lesions. Summarizing, increased GAD67 immunoreactivity occurs in neurons and astrocytes and relates to hippocampal inflammation and possibly disturbed cognition in MS.
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Affiliation(s)
- Svenja Kiljan
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Marloes Prins
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Bart M Baselmans
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.,Bart M. Baselmans, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - John G J M Bol
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Geert J Schenk
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Anne-Marie van Dam
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
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Artemiadis A, Bakirtzis C, Ifantopoulou P, Zis P, Bargiotas P, Grigoriadis N, Hadjigeorgiou G. The role of cognitive reserve in multiple sclerosis: A cross-sectional study in 526 patients. Mult Scler Relat Disord 2020; 41:102047. [DOI: 10.1016/j.msard.2020.102047] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2019] [Revised: 03/04/2020] [Accepted: 03/07/2020] [Indexed: 11/17/2022]
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Munari D, Fonte C, Varalta V, Battistuzzi E, Cassini S, Montagnoli AP, Gandolfi M, Modenese A, Filippetti M, Smania N, Picelli A. Effects of robot-assisted gait training combined with virtual reality on motor and cognitive functions in patients with multiple sclerosis: A pilot, single-blind, randomized controlled trial. Restor Neurol Neurosci 2020; 38:151-164. [DOI: 10.3233/rnn-190974] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Daniele Munari
- Neurorehabilitation Unit, University Hospital of Verona, Verona, Italy
| | - Cristina Fonte
- Neuromotor and Cognitive Rehabilitation Research Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Valentina Varalta
- Neuromotor and Cognitive Rehabilitation Research Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Elisa Battistuzzi
- Neuromotor and Cognitive Rehabilitation Research Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Silvia Cassini
- Neurorehabilitation Unit, University Hospital of Verona, Verona, Italy
| | - Anna Paola Montagnoli
- Neuromotor and Cognitive Rehabilitation Research Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Marialuisa Gandolfi
- Neurorehabilitation Unit, University Hospital of Verona, Verona, Italy
- Neuromotor and Cognitive Rehabilitation Research Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Angela Modenese
- Neuromotor and Cognitive Rehabilitation Research Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Mirko Filippetti
- Neuromotor and Cognitive Rehabilitation Research Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola Smania
- Neurorehabilitation Unit, University Hospital of Verona, Verona, Italy
- Neuromotor and Cognitive Rehabilitation Research Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Alessandro Picelli
- Neurorehabilitation Unit, University Hospital of Verona, Verona, Italy
- Neuromotor and Cognitive Rehabilitation Research Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
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Engel S, Graetz C, Salmen A, Muthuraman M, Toenges G, Ambrosius B, Bayas A, Berthele A, Heesen C, Klotz L, Kümpfel T, Linker RA, Meuth SG, Paul F, Stangel M, Tackenberg B, Then Bergh F, Tumani H, Weber F, Wildemann B, Zettl UK, Antony G, Bittner S, Groppa S, Hemmer B, Wiendl H, Gold R, Zipp F, Lill CM, Luessi F. Is APOE ε4 associated with cognitive performance in early MS? NEUROLOGY-NEUROIMMUNOLOGY & NEUROINFLAMMATION 2020; 7:7/4/e728. [PMID: 32358224 PMCID: PMC7217661 DOI: 10.1212/nxi.0000000000000728] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2019] [Accepted: 03/27/2020] [Indexed: 01/01/2023]
Abstract
Objective To assess the impact of APOE polymorphisms on cognitive performance in patients newly diagnosed with clinically isolated syndrome (CIS) or relapsing-remitting MS (RRMS). Methods This multicenter cohort study included 552 untreated patients recently diagnosed with CIS or RRMS according to the 2005 revised McDonald criteria. The single nucleotide polymorphisms rs429358 (ε4) and rs7412 (ε2) of the APOE haplotype were assessed by allelic discrimination assays. Cognitive performance was evaluated using the 3-second paced auditory serial addition test and the Multiple Sclerosis Inventory Cognition (MUSIC). Sum scores were calculated to approximate the overall cognitive performance and memory-centered cognitive functions. The impact of the APOE carrier status on cognitive performance was assessed using multiple linear regression models, also including demographic, clinical, MRI, and lifestyle factors. Results APOE ε4 homozygosity was associated with lower overall cognitive performance, whereas no relevant association was observed for APOE ε4 heterozygosity or APOE ε2 carrier status. Furthermore, higher disability levels, MRI lesion load, and depressive symptoms were associated with lower cognitive performance. Patients consuming alcohol had higher test scores than patients not consuming alcohol. Female sex, lower disability, and alcohol consumption were associated with better performance in the memory-centered subtests of MUSIC, whereas no relevant association was observed for APOE carrier status. Conclusion Along with parameters of a higher disease burden, APOE ε4 homozygosity was identified as a potential predictor of cognitive performance in this large cohort of patients with CIS and early RRMS.
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Affiliation(s)
- Sinah Engel
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Christiane Graetz
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Anke Salmen
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Muthuraman Muthuraman
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Gerrit Toenges
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Björn Ambrosius
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Antonios Bayas
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Achim Berthele
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Christoph Heesen
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Luisa Klotz
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Tania Kümpfel
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Ralf A Linker
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Sven G Meuth
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Friedemann Paul
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Martin Stangel
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Björn Tackenberg
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Florian Then Bergh
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Hayrettin Tumani
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Frank Weber
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Brigitte Wildemann
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Uwe K Zettl
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Gisela Antony
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Stefan Bittner
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Sergiu Groppa
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Bernhard Hemmer
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Heinz Wiendl
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Ralf Gold
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Frauke Zipp
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Christina M Lill
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Felix Luessi
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany.
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Cortese M, Munger KL, Martínez-Lapiscina EH, Barro C, Edan G, Freedman MS, Hartung HP, Montalbán X, Foley FW, Penner IK, Hemmer B, Fox EJ, Schippling S, Wicklein EM, Kappos L, Kuhle J, Ascherio A. Vitamin D, smoking, EBV, and long-term cognitive performance in MS: 11-year follow-up of BENEFIT. Neurology 2020; 94:e1950-e1960. [PMID: 32300060 DOI: 10.1212/wnl.0000000000009371] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Accepted: 12/02/2019] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVE To investigate whether vitamin D, smoking, and anti-Epstein-Barr virus (EBV) antibody concentrations predict long-term cognitive status and neuroaxonal injury in multiple sclerosis (MS). METHODS This study was conducted among 278 patients with clinically isolated syndrome who participated in the clinical trial BENEFIT (Betaferon/Betaseron in Newly Emerging Multiple Sclerosis for Initial Treatment) and completed the 11-year assessment (BENEFIT-11). We measured serum 25-hydroxyvitamin-D (25(OH)D), cotinine (smoking biomarker), and anti-Epstein-Barr virus nuclear antigen 1 (EBNA-1) immunoglobulin G (IgG) at baseline and at months 6, 12, and 24 and examined whether these biomarkers contributed to predict Paced Auditory Serial Addition Test (PASAT)-3 scores and serum neurofilament light chain (NfL) concentrations at 11 years. Linear and logistic regression models were adjusted for sex, baseline age, treatment allocation, steroid treatment, multifocal symptoms, T2 lesions, and body mass index. RESULTS Higher vitamin D predicted better, whereas smoking predicted worse cognitive performance. A 50-nmol/L higher mean 25(OH)D in the first 2 years was related to 65% lower odds of poorer PASAT performance at year 11 (95% confidence intervals [95% CIs]: 0.14-0.89). Standardized PASAT scores were lower in smokers and heavy smokers than nonsmokers (p trend = 0.026). Baseline anti-EBNA-1 IgG levels did not predict cognitive performance (p trend = 0.88). Associations with NfL concentrations at year 11 corroborated these findings-a 50-nmol/L higher mean 25(OH)D in the first 2 years was associated with 20% lower NfL (95% CI: -36% to 0%), whereas smokers had 20% higher NfL levels than nonsmokers (95% CI: 2%-40%). Anti-EBNA-1 antibodies were not associated with NfL. CONCLUSIONS Lower vitamin D and smoking after clinical onset predicted worse long-term cognitive function and neuronal integrity in patients with MS.
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Affiliation(s)
- Marianna Cortese
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
| | - Kassandra L Munger
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Elena H Martínez-Lapiscina
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Christian Barro
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Gilles Edan
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Mark S Freedman
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Hans-Peter Hartung
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Xavier Montalbán
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Frederick W Foley
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Iris Katharina Penner
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Bernhard Hemmer
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Edward J Fox
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Sven Schippling
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Eva-Maria Wicklein
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Ludwig Kappos
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Jens Kuhle
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Alberto Ascherio
- From the Department of Nutrition (M.C., K.L.M, A.A.), Harvard T.H. Chan School of Public Health, Boston, MA; Department of Global Public Health and Primary Care (M.C.), University of Bergen, Bergen, Norway; Department of Neurology (E.H.M.-L.), Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain; Departments of Medicine, Biomedicine and Clinical Research (C.B., L.K., J.K.), Neurologic Clinic and Policlinic, University Hospital Basel, University of Basel, Basel, Switzerland; CHU Hôpital Pontchaillou (G.E.), Rennes, France; University of Ottawa and Ottawa Hospital Research Institute (M.S.F.), Ottawa, Canada; Department of Neurology (H.-P.H.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf, Germany; St. Michael's Hospital (X.M.), University of Toronto, Canada and Multiple Sclerosis Center of Catalonia (Cemcat) (X.M.), Vall d'Hebron University Hospital, Barcelona, Spain; Ferkauf Graduate School of Psychology (F.W.F.), Yeshiva University, New York, NY; Department of Neurology (I.K.P.), Medical Faculty, Heinrich-Heine Universität, Düsseldorf and COGITO Center for Applied Neurocognition and Neuropsychological Research (I.K.P.), Düsseldorf, Germany; Technical University of Munich (B.H.), School of Medicine and Munich Cluster for Systems Neurology (SyNergy) (B.H.), Munich, Germany; Central Texas Neurology Consultants (E.J.F.), Round Rock, TX; Neuroimmunology and Multiple Sclerosis Research (S.S.), Department of Neurology, University Hospital Zurich, University of Zurich and Center for Neuroscience Zurich (S.S.), Federal Institute of Technology (ETH), Zurich, Switzerland; Bayer AG (E.-M.W.), Berlin, Germany; Department of Epidemiology (A.A.), Harvard T.H. Chan School of Public Health, Boston, MA and Channing Division of Network Medicine (A.A.); and Department of Medicine (A.A.), Brigham and Women's Hospital and Harvard Medical School, Boston, MA
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Mattioli F, Bellomi F, Stampatori C, Mariotto S, Ferrari S, Monaco S, Mancinelli C, Capra R. Longitudinal serum neurofilament light chain (sNfL) concentration relates to cognitive function in multiple sclerosis patients. J Neurol 2020; 267:2245-2251. [DOI: 10.1007/s00415-020-09832-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 04/08/2020] [Accepted: 04/08/2020] [Indexed: 11/28/2022]
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Remy C, Valet M, Stoquart G, El Sankari S, Van Pesch V, De Haan A, Lejeune T. Telecommunication and rehabilitation for patients with multiple sclerosis: access and willingness to use. A cross-sectional study. Eur J Phys Rehabil Med 2020; 56:403-411. [PMID: 32293811 DOI: 10.23736/s1973-9087.20.06061-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
BACKGROUND Telerehabilitation is a promising approach for patients with multiple sclerosis (MS), but uncertainties regarding patients' access and preferences remain. AIM To investigate the access to telecommunication technologies and rehabilitation services of patients with MS, and their willingness to use these technologies for rehabilitation. DESIGN Cross-sectional survey. SETTING Outpatient neurological facility. POPULATION Patients with MS. METHODS Patients with MS attending consultations in the Neurology department were asked to fill in a paper questionnaire. This anonymous z was designed to gain information about needs and access to rehabilitation and telecommunication technologies, as well as interests and perspectives of telerehabilitation among these patients. Descriptive statistics, Chi-squared tests and logistic regressions were used to describe the sample and survey answers. RESULTS Two hundred patients completed the questionnaire. Mean age was 44.41(±12.52) years. Seventy-one percent were women, and 49% were unemployed. Ninety-one percent of the patients regularly used internet and 73% used apps. Most patients were interested in using telecommunication technologies to receive a program of physical exercises (62%), for information and personalized advice about physical activity and MS (69%), and to communicate with caregivers (75%). Patients with EDSS>4 were less interested than patients with EDSS≤4 in communicating with the caregivers via apps (33% vs. 52%,Δ19%[CI-36%;-2%],P=0.04) but expressed greater interest in receiving information and personal advice about physical activity and MS via the internet (70% vs. 51%,Δ19%[CI+2%;+36%],P=0.03). One third of the patients was not interested in receiving telerehabilitation interventions (32%), notably patients with EDSS>4 and non-workers. CONCLUSIONS Patients with MS are mainly interested in using telecommunication technologies for rehabilitation services, and most of these patients have access to the required technology. Being mildly disabled and having a professional activity are associated with a greater interest in telerehabilitation. In contrary, patients with moderate-to-severe disability and non-workers have reportedly less access and ease in using the required technologies. CLINICAL REHABILITATION IMPACT Telerehabilitation is feasible and wished by patients with MS, specifically in patients with low EDSS scores and workers. Given the strong need for rehabilitation in more disabled patients, the barriers to its access, the lower access and ease of use of telecommunication technologies, a special effort is needed to facilitate their use in these patients.
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Affiliation(s)
- Caroline Remy
- Service of Physical Medicine and Rehabilitation, Clinic University of Saint-Luc, Brussels, Belgium
| | - Maxime Valet
- Service of Physical Medicine and Rehabilitation, Clinic University of Saint-Luc, Brussels, Belgium.,Neuromusculoskeletal lab (NMSK), Institut of Experimental Clinical Research, Department of Health Sciences, Catholic University of Louvain, Brussels, Belgium
| | - Gaëtan Stoquart
- Service of Physical Medicine and Rehabilitation, Clinic University of Saint-Luc, Brussels, Belgium.,Neuromusculoskeletal lab (NMSK), Institut of Experimental Clinical Research, Department of Health Sciences, Catholic University of Louvain, Brussels, Belgium
| | | | - Vincent Van Pesch
- Service of Neurology, Clinic University of Saint-Luc, Brussels, Belgium
| | - Alice De Haan
- Service of Neurology, Clinic University of Saint-Luc, Brussels, Belgium
| | - Thierry Lejeune
- Service of Physical Medicine and Rehabilitation, Clinic University of Saint-Luc, Brussels, Belgium - .,Neuromusculoskeletal lab (NMSK), Institut of Experimental Clinical Research, Department of Health Sciences, Catholic University of Louvain, Brussels, Belgium
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Jakimovski D, Ramanathan M, Weinstock-Guttman B, Bergsland N, Ramasamay DP, Carl E, Dwyer MG, Zivadinov R. Higher EBV response is associated with more severe gray matter and lesion pathology in relapsing multiple sclerosis patients: A case-controlled magnetization transfer ratio study. Mult Scler 2020; 26:322-332. [PMID: 30755085 PMCID: PMC6692251 DOI: 10.1177/1352458519828667] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Epstein-Barr virus (EBV) infection has been associated with higher clinical activity and risk of multiple sclerosis (MS). OBJECTIVE To evaluate associations between EBV-specific humoral response and magnetization transfer ratio (MTR)-derived measure in MS patients and healthy controls (HCs). METHODS The study included 101 MS patients (69 relapsing-remitting multiple sclerosis (RRMS) and 32 secondary-progressive multiple sclerosis (SPMS)) and 41 HCs who underwent clinical, serological, and magnetic resonance imaging (MRI) investigations. MTR values of T1 or T2 lesion volume (LV), normal-appearing (NA) brain tissue (NABT), gray matter (NAGM), and white matter (NAWM) were obtained. Enzyme-linked immunosorbent assay was used to quantify EBV antibody levels. Partial correlations corrected for MRI strength were used, and Benjamini-Hochberg-adjusted p-values < 0.05 were considered significant. RESULTS MS patients had significantly higher anti-EBV nuclear antigen-1 (EBNA-1) titer when compared to HCs (107.9 U/mL vs 27.8 U/mL, p < 0.001). Within the MS group, higher serum anti-EBNA-1 titer was significantly correlated with lower T1-LV MTR (r = -0.287, p = 0.035). Within the RRMS group, higher serum anti-EBNA-1 titer was associated with T1-LV MTR (r = -0.524, p = 0.001) and NAGM MTR (r = -0.308, p = 0.043). These associations were not present in HCs or SPMS patients. CONCLUSION Greater EBV humoral response is associated with lower GM MTR changes and focal destructive lesion pathology in RRMS patients.
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Affiliation(s)
- Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Murali Ramanathan
- Department of Pharmaceutical Sciences, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA
| | - Bianca Weinstock-Guttman
- Jacobs MS Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, NY, USA
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Deepa P. Ramasamay
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Ellen Carl
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Michael G. Dwyer
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
- Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA
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Renner A, Baetge SJ, Filser M, Ullrich S, Lassek C, Penner I. Characterizing cognitive deficits and potential predictors in multiple sclerosis: A large nationwide study applying Brief International Cognitive Assessment for Multiple Sclerosis in standard clinical care. J Neuropsychol 2020; 14:347-369. [DOI: 10.1111/jnp.12202] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 01/10/2020] [Indexed: 01/21/2023]
Affiliation(s)
- Alina Renner
- Cogito Center for Applied Neurocognition and Neuropsychological Research Düsseldorf Germany
| | - Sharon J. Baetge
- Cogito Center for Applied Neurocognition and Neuropsychological Research Düsseldorf Germany
| | - Melanie Filser
- Cogito Center for Applied Neurocognition and Neuropsychological Research Düsseldorf Germany
| | | | | | - Iris‐Katharina Penner
- Cogito Center for Applied Neurocognition and Neuropsychological Research Düsseldorf Germany
- Department of Neurology Medical Faculty Heinrich‐Heine University Düsseldorf Düsseldorf Germany
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Bogdanova MD, Mikadze YV, Bembeeva RT, Volkova EY. [Methodological issues of cognitive impairment studies in pediatric multiple sclerosis patients]. Zh Nevrol Psikhiatr Im S S Korsakova 2020; 119:105-111. [PMID: 31626226 DOI: 10.17116/jnevro2019119091105] [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] [Indexed: 11/17/2022]
Abstract
The article provides a review of the characteristics of cognitive impairment in multiple sclerosis (MS) and methods for its assessment in children. The features of the most frequently used neuropsychological batteries, with consideration of specifics of cognitive impairment in MS, and data on assessment of a state of cognitive functions obtained using neuropsychological tests are presented. The authors also discuss the issue of a long-term impact of the disease on a state of cognitive functions. Clinical factors, which can lead to cognitive impairment (type of multiple sclerosis, age at manifestation, number of relapses), are described.
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Affiliation(s)
- M D Bogdanova
- Lomonosov Moscow State University, Moscow, Russia; Sechenov First Moscow State Medical University, Moscow, Russia
| | - Yu V Mikadze
- Lomonosov Moscow State University, Moscow, Russia; Pirogov Russian National Research Medical University, Moscow, Russia
| | - R Ts Bembeeva
- Pirogov Russian National Research Medical University, Moscow, Russia
| | - E Yu Volkova
- Russian Pediatric Clinical Hospital, Pirogov Russian National Research Medical University, Moscow, Russia
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Gómez-Moreno SM, Cuadrado ML, Cruz-Orduña I, Martínez-Acebes EM, Gordo-Mañas R, Fernández-Pérez C, García-Ramos R. Validation of the Spanish-language version of the Montreal Cognitive Assessment as a screening test for cognitive impairment in multiple sclerosis. Neurologia 2020; 37:S0213-4853(19)30149-5. [PMID: 31983477 DOI: 10.1016/j.nrl.2019.11.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 11/04/2019] [Indexed: 11/28/2022] Open
Abstract
INTRODUCTION The neuropsychological batteries traditionally used for the assessment of cognitive impairment (CI) in patients with multiple sclerosis are complex tests requiring a long time to administer. Simpler tests are needed to detect cognitive impairment in daily clinical practice. OBJECTIVE We aimed to evaluate the diagnostic validity and reliability of the Montreal Cognitive Assessment (MoCA) test as a screening tool for CI in patients with multiple sclerosis, as compared against the Brief Neuropsychological Battery. MATERIAL AND METHODS We recruited 52 patients with multiple sclerosis (61.5% women; mean age [standard deviation]: 41.7 [11.5] years). We analysed the reliability (internal consistency, interobserver reliability, and test-retest reliability), construct validity (factor analysis, Pearson correlation coefficient, and coefficient of determination), and criterion validity (ROC curve, sensitivity, specificity, total agreement, positive and negative predictive values, positive and negative likelihood ratios, and Fagan nomogram) of the MoCA test in this population. RESULTS The prevalence of CI was 21.2% according to findings from the Brief Neuropsychological Battery, and 25% according to the MoCA test. The MoCA test showed good internal consistency (Cronbach alpha, 0.822) and interobserver and test-retest reliability (intraclass correlation coefficient 0.80 and 0.96, respectively). The correlation coefficient between total Brief Neuropsychological Battery and MoCA test scores was 0.82. The optimal cut-off point on the ROC curve was 25-26, yielding 91% sensitivity and 93% specificity. CONCLUSION The MoCA test is a valid and reliable tool for screening for CI in patients with multiple sclerosis.
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Affiliation(s)
- S M Gómez-Moreno
- Sección de Neurología, Hospital Universitario Infanta Leonor, Madrid, España.
| | - M L Cuadrado
- Servicio de Neurología, Hospital Clínico San Carlos, Madrid, España; Departamento de Medicina, Facultad de Medicina, Universidad Complutense de Madrid, Madrid, España
| | - I Cruz-Orduña
- Sección de Neurología, Hospital Universitario Infanta Leonor, Madrid, España
| | - E M Martínez-Acebes
- Sección de Neurología, Hospital Universitario Infanta Leonor, Madrid, España
| | - R Gordo-Mañas
- Sección de Neurología, Hospital Universitario Infanta Leonor, Madrid, España; La afiliación de R. Gordo-Mañas en el momento de la publicación de este artículo es: Servicio de Neurología, Hospital Universitario Príncipe de Asturias, Alcalá de Henares, Madrid, España
| | - C Fernández-Pérez
- Servicio de Medicina Preventiva, Hospital Clínico San Carlos, Madrid, España
| | - R García-Ramos
- Servicio de Neurología, Hospital Clínico San Carlos, Madrid, España; Departamento de Medicina, Facultad de Medicina, Universidad Complutense de Madrid, Madrid, España
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Cooray GK, Sundgren M, Brismar T. Mechanism of visual network dysfunction in relapsing-remitting multiple sclerosis and its relation to cognition. Clin Neurophysiol 2019; 131:361-367. [PMID: 31864125 DOI: 10.1016/j.clinph.2019.10.029] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 09/10/2019] [Accepted: 10/31/2019] [Indexed: 01/31/2023]
Abstract
OBJECTIVE To investigate if changes in brain network function and connectivity contribute to the abnormalities in visual event related potentials (ERP) in relapsing-remitting multiple sclerosis (RRMS), and explore their relation to a decrease in cognitive performance. METHODS We evaluated 72 patients with RRMS and 89 healthy control subjects in a cross-sectional study. Visual ERP were generated using illusory and non-illusory stimuli and recorded using 21 EEG scalp electrodes. The measured activity was modelled using Dynamic Causal Modelling. The model network consisted of 4 symmetric nodes including the primary visual cortex (V1/V2) and the Lateral Occipital Complex. Patients and controls were tested with a neuropsychological test battery consisting of 18 cognitive tests covering six cognitive domains. RESULTS We found reduced cortical connectivity in bottom-up and interhemispheric connections to the right lateral occipital complex in patients (p < 0.001). Furthermore, interhemispherical connections were related to cognitive dysfunction in several domains (attention, executive function, visual perception and organization, processing speed and global cognition) for patients (p < 0.05). No relation was seen between cortical network connectivity and cognitive function in the healthy control subjects. CONCLUSION Changes in the functional connectivity to higher cortical regions provide a neurobiological explanation for the changes of the visual ERP in RRMS. SIGNIFICANCE This study suggests that changes in connectivity to higher cortical regions partly explain visual network dysfunction in RRMS where a lower interhemispheric connectivity may contribute to impaired cognitive function.
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Affiliation(s)
- Gerald K Cooray
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden; Department of Clinical Neurophysiology, Karolinska University Hospital, Stockholm, Sweden.
| | - Mathias Sundgren
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden; Neuro Department, Karolinska University Hospital, Stockholm, Sweden
| | - Tom Brismar
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden; Department of Clinical Neurophysiology, Karolinska University Hospital, Stockholm, Sweden
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Abou Elmaaty AA, Flifel ME, Zarad CA. Correlation between brain magnetic resonance imaging, cognitive dysfunction and physical dysability in multiple sclerosis. THE EGYPTIAN JOURNAL OF NEUROLOGY, PSYCHIATRY AND NEUROSURGERY 2019. [DOI: 10.1186/s41983-019-0100-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Pitteri M, Ziccardi S, Dapor C, Guandalini M, Calabrese M. Lost in Classification: Lower Cognitive Functioning in Apparently Cognitive Normal Newly Diagnosed RRMS Patients. Brain Sci 2019; 9:E321. [PMID: 31766124 PMCID: PMC6895881 DOI: 10.3390/brainsci9110321] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 11/08/2019] [Accepted: 11/11/2019] [Indexed: 01/26/2023] Open
Abstract
Cognitive functioning in multiple sclerosis (MS) patients is usually related to the classic, dichotomic classification of impaired vs. unimpaired cognition. However, this approach is far from mirroring the real efficiency of cognitive functioning. Applying a different approach in which cognitive functioning is considered as a continuous variable, we aimed at showing that even newly diagnosed relapsing-remitting MS (RRMS) patients might suffer from reduced cognitive functioning with respect to a matched group of neurologically healthy controls (HCs), even if they were classified as having no cognitive impairment (CI). Fifty newly diagnosed RRMS patients and 36 HCs were tested with an extensive battery of neuropsychological tests. By using Z-scores applied to the whole group of RRMS and HCs together, a measure of cognitive functioning (Z-score index) was calculated. Among the 50 RRMS patients tested, 36 were classified as cognitively normal (CN). Even though classified as CN, RRMS patients performed worse than HCs at a global level (p = 0.004) and, more specifically, in the domains of memory (p = 0.005) and executive functioning (p = 0.006). These results highlight that reduced cognitive functioning can be present early in the disease course, even in patients without an evident CI. The current classification criteria of CI in MS should be considered with caution.
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Affiliation(s)
- Marco Pitteri
- Neurology section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (S.Z.); (C.D.); (M.G.)
| | | | | | | | - Massimiliano Calabrese
- Neurology section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (S.Z.); (C.D.); (M.G.)
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Amato MP, Prestipino E, Bellinvia A, Niccolai C, Razzolini L, Pastò L, Fratangelo R, Tudisco L, Fonderico M, Mattiolo PL, Goretti B, Zimatore GB, Losignore NA, Portaccio E, Lolli F. Cognitive impairment in multiple sclerosis: An exploratory analysis of environmental and lifestyle risk factors. PLoS One 2019; 14:e0222929. [PMID: 31634346 PMCID: PMC6802833 DOI: 10.1371/journal.pone.0222929] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 09/10/2019] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Many potentially modifiable risk factors for MS are investigated. It is not known, however, if these factors also apply to MS-related cognitive impairment (CI), a frequent consequence of MS. OBJECTIVE The aim of our study was to assess risk factors for CI in MS patients, focusing on environmental exposures, lifestyle and comorbidities. METHODS We included MS patients referring to MS Centers in Florence and Barletta between 2014 and 2017. Neuropsychological performance was assessed through the Rao's battery and Stroop test, cognitive reserve (premorbid intelligence quotient-IQ) was evaluated using the National Adult Reading Test (NART). Potential risk factors were investigated through a semi-structured questionnaire. RESULTS 150 patients were included. CI was detected in 45 (30%) subjects and was associated with older age (p<0.005), older age at MS onset (p = 0.016), higher EDSS score (p<0.005), progressive disease course (p = 0.048) and lower premorbid IQ score (p<0.005). As for risk factors, CI was related with lower physical activity in childhood-adolescence (p<0.005). In women, hormonal therapy resulted to be protective against CI (p = 0.041). However, in the multivariable analysis, the only significant predictors of CI were older age (p<0.05; OR 1.06, 95% CI 1.02-1.10) and lower premorbid IQ (p<0.05; OR 0.93, 95% CI: 0.88-0.98). Removing IQ from the model, CI was associated with higher EDSS (p = 0.030; OR 1.25, 95% CI 1.02-1.53) and, marginally, previous physical activity (p = 0.066; OR 0.49, 95% CI: 0.23-1.05). CONCLUSIONS Our findings suggest that physical activity in childhood-adolescence could be a contributor to cognitive reserve building, thus representing a potential protective factors for MS-related CI susceptible to preventive strategies.
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Affiliation(s)
- Maria Pia Amato
- Department NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Elio Prestipino
- Department NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
| | - Angelo Bellinvia
- Department NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
| | - Claudia Niccolai
- Department NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
| | - Lorenzo Razzolini
- Department NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
| | - Luisa Pastò
- SOD Neurological Rehabilitation, Careggi University Hospital, Florence, Italy
| | - Roberto Fratangelo
- Department NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
| | - Laura Tudisco
- Department NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
| | - Mattia Fonderico
- Department NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
| | - Paolo Luca Mattiolo
- Department NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
| | - Benedetta Goretti
- Department NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
| | | | | | | | - Francesco Lolli
- Department NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
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Jakimovski D, Zivadinov R, Ramanthan M, Hagemeier J, Weinstock-Guttman B, Tomic D, Kropshofer H, Fuchs TA, Barro C, Leppert D, Yaldizli Ö, Kuhle J, Benedict RHB. Serum neurofilament light chain level associations with clinical and cognitive performance in multiple sclerosis: A longitudinal retrospective 5-year study. Mult Scler 2019; 26:1670-1681. [DOI: 10.1177/1352458519881428] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Background: A limited number of studies investigated associations between serum neurofilament light chain (sNfL) and cognition in persons with multiple sclerosis (PwMS). Objective: To assess cross-sectional and longitudinal associations between sNfL levels, clinical, and cognitive performance in PwMS and age-matched healthy controls (HCs). Materials: One hundred twenty-seven PwMS (85 relapsing–remitting MS/42 progressive MS), 20 clinically isolated syndrome patients, and 52 HCs were followed for 5 years. sNfL levels were measured using the single-molecule array (Simoa) assay and quantified in picograms per milliliter. Expanded Disability Status Scale (EDSS), walking, and manual dexterity tests were obtained. At follow-up, Brief International Cognitive Assessment for MS (BICAMS) was utilized. Cognitively impaired (CI) status was derived using HC-based z-scores. Age-, sex-, and education-adjusted analysis of covariance (ANCOVA) and regression models were used. Multiple comparison–adjusted values of q < 0.05 were considered significant. Results: In PwMS, sNfL levels were cross-sectionally associated with walking speed ( r = 0.235, q = 0.036), manual dexterity ( r = 0.337, q = 0.002), and cognitive processing speed (CPS; r =−0.265, q = 0.012). Baseline sNfL levels predicted 5-year EDSS scores ( r = 0.25, q = 0.012), dexterity ( r = 0.224, q = 0.033), and CPS ( r =−0.205, q = 0.049). CI patients had higher sNfL levels (27.2 vs. 20.6, p = 0.016) and greater absolute longitudinal sNfL increase when compared with non-CI patients (4.8 vs. 0.7, p = 0.04). Conclusion: Higher sNfL levels are associated with poorer current and future clinical and cognitive performance.
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Affiliation(s)
- Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA/Jacobs MS Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Robert Zivadinov
- Jacobs MS Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA/Center for Biomedical Imaging at Clinical Translational Science Institute, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Murali Ramanthan
- Department of Pharmaceutical Sciences, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Jesper Hagemeier
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Bianca Weinstock-Guttman
- Jacobs MS Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | | | | | - Tom A Fuchs
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Christian Barro
- Neurologic Clinic and Policlinic, Departments of Medicine, Biomedicine, and Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | | | - Özgür Yaldizli
- Neurologic Clinic and Policlinic, Departments of Medicine, Biomedicine, and Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurologic Clinic and Policlinic, Departments of Medicine, Biomedicine, and Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Ralph HB Benedict
- Jacobs MS Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
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Social-cognitive theory variables as correlates of sedentary behavior in multiple sclerosis: Preliminary evidence. Disabil Health J 2019; 12:622-627. [DOI: 10.1016/j.dhjo.2019.05.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 04/30/2019] [Accepted: 05/07/2019] [Indexed: 12/29/2022]
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Ifantopoulou P, Artemiadis AK, Bakirtzis C, Zekiou K, Papadopoulos TS, Diakogiannis I, Hadjigeorgiou G, Grigoriadis N, Orologas A. Cognitive and brain reserve in multiple sclerosis––A cross-sectional study. Mult Scler Relat Disord 2019; 35:128-134. [DOI: 10.1016/j.msard.2019.07.027] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 06/29/2019] [Accepted: 07/27/2019] [Indexed: 10/26/2022]
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Eijlers AJ, Dekker I, Steenwijk MD, Meijer KA, Hulst HE, Pouwels PJ, Uitdehaag BM, Barkhof F, Vrenken H, Schoonheim MM, Geurts JJ. Cortical atrophy accelerates as cognitive decline worsens in multiple sclerosis. Neurology 2019; 93:e1348-e1359. [DOI: 10.1212/wnl.0000000000008198] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 05/02/2019] [Indexed: 01/15/2023] Open
Abstract
ObjectiveTo determine which pathologic process could be responsible for the acceleration of cognitive decline during the course of multiple sclerosis (MS), using longitudinal structural MRI, which was related to cognitive decline in relapsing-remitting MS (RRMS) and progressive MS (PMS).MethodsA prospective cohort of 230 patients with MS (179 RRMS and 51 PMS) and 59 healthy controls was evaluated twice with 5-year (mean 4.9, SD 0.94) interval during which 22 patients with RRMS converted to PMS. Annual rates of cortical and deep gray matter atrophy as well as lesion volume increase were computed on longitudinal (3T) MRI data and correlated to the annual rate of cognitive decline as measured using an extensive cognitive evaluation at both time points.ResultsThe deep gray matter atrophy rate did not differ between PMS and RRMS (−0.82%/year vs −0.71%/year, p = 0.11), while faster cortical atrophy was observed in PMS (−0.87%/year vs −0.48%/year, p < 0.01). Similarly, faster cognitive decline was observed in PMS compared to RRMS (p < 0.01). Annual cognitive decline was related to the rate of annual lesion volume increase in stable RRMS (r = −0.17, p = 0.03) to the rate of annual deep gray matter atrophy in converting RRMS (r = 0.50, p = 0.02) and annual cortical atrophy in PMS (r = 0.35, p = 0.01).ConclusionsThese results indicate that cortical atrophy and cognitive decline accelerate together during the course of MS. Substrates of cognitive decline shifted from worsening lesional pathology in stable RRMS to deep gray matter atrophy in converting RRMS and to accelerated cortical atrophy in PMS only.
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Baird JF, Cederberg KL, Sikes EM, Jeng B, Sasaki JE, Sandroff BM, Motl RW. Changes in Cognitive Performance With Age in Adults With Multiple Sclerosis. Cogn Behav Neurol 2019; 32:201-207. [PMID: 31517704 PMCID: PMC6750025 DOI: 10.1097/wnn.0000000000000200] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
BACKGROUND Cognitive impairment is one of the most common consequences of multiple sclerosis (MS), yet there is a shortage of data regarding how cognition changes during the life span of individuals with MS. This information is of increasing importance given the growing proportion of older adults with MS. OBJECTIVE To study possible changes in cognitive function in correlation with increasing age in individuals with MS. METHODS Participants (N=129) were recruited and a priori allocated into one of three age groups (young, middle-aged, and older). All participants completed the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) during a single laboratory testing session. The BICAMS measures cognitive processing speed as well as verbal and visuospatial learning and memory. RESULTS A multivariate analysis of variance indicated that cognitive function significantly differed by age group, and these differences were not explained by amount of physical activity, years of education, years since diagnosis, or race. Older adults displayed significantly worse cognitive processing speed than young and middle-aged adults. The older and middle-aged adults also demonstrated significantly worse visuospatial learning and memory than the younger adults. Effect sizes indicated that cognitive processing speed and verbal learning and memory were more affected in late adulthood than early adulthood, whereas visuospatial learning and memory was affected similarly in early and late adulthood. CONCLUSIONS Older adults with MS demonstrated significant impairments in cognitive function compared to young and middle-aged adults with MS. Future studies should determine the predictors of cognitive decline in this age cohort.
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Affiliation(s)
- Jessica F. Baird
- Department of Physical Therapy, University of Alabama at Birmingham
- University of Alabama at Birmingham Center for Exercise Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | | | - E. Morghen Sikes
- Department of Physical Therapy, University of Alabama at Birmingham
| | - Brenda Jeng
- Department of Physical Therapy, University of Alabama at Birmingham
| | - Jeffer E. Sasaki
- Graduate Program in Physical Education, Federal University of Triangulo Mineiro, Uberaba, Minas Gerais, Brazil
| | - Brian M. Sandroff
- Department of Physical Therapy, University of Alabama at Birmingham
- University of Alabama at Birmingham Center for Exercise Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Robert W. Motl
- Department of Physical Therapy, University of Alabama at Birmingham
- University of Alabama at Birmingham Center for Exercise Medicine, University of Alabama at Birmingham, Birmingham, Alabama
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Sadeghi Bahmani D, Razazian N, Motl RW, Farnia V, Alikhani M, Pühse U, Gerber M, Brand S. Physical activity interventions can improve emotion regulation and dimensions of empathy in persons with multiple sclerosis: An exploratory study. Mult Scler Relat Disord 2019; 37:101380. [PMID: 32173007 DOI: 10.1016/j.msard.2019.101380] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 08/28/2019] [Accepted: 08/30/2019] [Indexed: 12/27/2022]
Abstract
BACKGROUND Persons with multiple sclerosis (PwMS) report difficulties with emotion regulation and empathy. Regular physical activity (RPA) improves dimensions of psychological well-being in PwMS, but it remains unclear if regular physical activity has effects on emotion regulation and empathy. The present study investigated the effect of regular physical activity on emotion regulation and empathy, and explored, if endurance training or coordinative training are better than an active control condition. METHODS 92 female PwMS (mean age: 37.4 years; age range: 20-57 years; mean EDSS: 2.43) took part in this study. Participants were randomly assigned into endurance training, coordinative training, or active control conditions that all lasted 8 weeks and were yoked on frequency, duration, and social contact. Participants completed questionnaires on emotion regulation, empathy, depression and fatigue before and after the 8-week conditions. RESULTS Regulation and control of emotions and empathy improved over time, but more so in the exercising groups, compared to the active control group. No changes over time and between groups were observed for perception and acknowledgement of emotions, emotional expressivity, and empathy, as measured with Reading in the Eyes test. These changes were not influenced by control for depression and fatigue as covariates. CONCLUSIONS Both endurance and coordinative exercise training had favorable effects on some aspects of emotion regulation and social cognition such as empathy in PwMS. Such initial results support for examination of exercise training for the treatment of issues of emotion regulation and social interactions in PwMS.
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Affiliation(s)
- Dena Sadeghi Bahmani
- University of Basel, Psychiatric Clinics (UPK), Center of Affective, Stress and Sleep Disorders (ZASS), Basel, Switzerland; Kermanshah University of Medical Sciences (KUMS), Department of Psychiatry, Substance Abuse Prevention Research Center, Health Institute, Kermanshah, Iran; Kermanshah University of Medical Sciences (KUMS), Department of Psychiatry, Sleep Disorders Research Center, Kermanshah, Iran; Isfahan Neurosciences Research Center, Alzahra Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran; Tehran University of Medical Sciences, School of Medicine, Tehran, Iran.
| | - Nazanin Razazian
- Kermanshah University of Medical Sciences, Neurology Department, Kermanshah, Iran
| | - Robert W Motl
- Departments of Physical Therapy, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Vahid Farnia
- Kermanshah University of Medical Sciences (KUMS), Department of Psychiatry, Substance Abuse Prevention Research Center, Health Institute, Kermanshah, Iran
| | - Mostafa Alikhani
- Kermanshah University of Medical Sciences (KUMS), Department of Psychiatry, Substance Abuse Prevention Research Center, Health Institute, Kermanshah, Iran
| | - Uwe Pühse
- University of Basel, Department of Sport, Exercise, and Health, Division of Sport Science and Psychosocial Health, Basel, Switzerland
| | - Markus Gerber
- University of Basel, Department of Sport, Exercise, and Health, Division of Sport Science and Psychosocial Health, Basel, Switzerland
| | - Serge Brand
- University of Basel, Psychiatric Clinics (UPK), Center of Affective, Stress and Sleep Disorders (ZASS), Basel, Switzerland; Kermanshah University of Medical Sciences (KUMS), Department of Psychiatry, Substance Abuse Prevention Research Center, Health Institute, Kermanshah, Iran; Kermanshah University of Medical Sciences (KUMS), Department of Psychiatry, Sleep Disorders Research Center, Kermanshah, Iran; University of Basel, Department of Sport, Exercise, and Health, Division of Sport Science and Psychosocial Health, Basel, Switzerland; Tehran University of Medical Sciences, School of Medicine, Tehran, Iran
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83
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Fuchs TA, Benedict RHB, Bartnik A, Choudhery S, Li X, Mallory M, Oship D, Yasin F, Ashton K, Jakimovski D, Bergsland N, Ramasamy DP, Weinstock-Guttman B, Zivadinov R, Dwyer MG. Preserved network functional connectivity underlies cognitive reserve in multiple sclerosis. Hum Brain Mapp 2019; 40:5231-5241. [PMID: 31444887 PMCID: PMC6864900 DOI: 10.1002/hbm.24768] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 07/26/2019] [Accepted: 08/08/2019] [Indexed: 12/27/2022] Open
Abstract
Cognitive reserve is one's mental resilience or resistance to the effects of structural brain damage. Reserve effects are well established in people with multiple sclerosis (PwMS) and Alzheimer's disease, but the neural basis of this phenomenon is unclear. We aimed to investigate whether preservation of functional connectivity explains cognitive reserve. Seventy‐four PwMS and 29 HCs underwent neuropsychological assessment and 3 T MRI. Structural damage measures included gray matter (GM) atrophy and network white matter (WM) tract disruption between pairs of GM regions. Resting‐state functional connectivity was also assessed. PwMS exhibited significantly impaired cognitive processing speed (t = 2.14, p = .037) and visual/spatial memory (t = 2.72, p = .008), and had significantly greater variance in functional connectivity relative to HCs within relevant networks (p < .001, p < .001, p = .016). Higher premorbid verbal intelligence, a proxy for cognitive reserve, predicted relative preservation of functional connectivity despite accumulation of GM atrophy (standardized‐β = .301, p = .021). Furthermore, preservation of functional connectivity attenuated the impact of structural network WM tract disruption on cognition (β = −.513, p = .001, for cognitive processing speed; β = −.209, p = .066, for visual/spatial memory). The data suggests that preserved functional connectivity explains cognitive reserve in PwMS, helping to maintain cognitive capacity despite structural damage.
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Affiliation(s)
- Tom A Fuchs
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Ralph H B Benedict
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Alexander Bartnik
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Sanjeevani Choudhery
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Xian Li
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Matthew Mallory
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Devon Oship
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Faizan Yasin
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Kira Ashton
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Dejan Jakimovski
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Niels Bergsland
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Deepa P Ramasamy
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Bianca Weinstock-Guttman
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Robert Zivadinov
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Center for Biomedical Imaging, Clinical Translational Science Institute, University at Buffalo, State University of New York (SUNY), Buffalo, New York
| | - Michael G Dwyer
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York.,Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York (SUNY), Buffalo, New York
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84
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Jakimovski D, Kuhle J, Ramanathan M, Barro C, Tomic D, Hagemeier J, Kropshofer H, Bergsland N, Leppert D, Dwyer MG, Michalak Z, Benedict RHB, Weinstock-Guttman B, Zivadinov R. Serum neurofilament light chain levels associations with gray matter pathology: a 5-year longitudinal study. Ann Clin Transl Neurol 2019; 6:1757-1770. [PMID: 31437387 PMCID: PMC6764487 DOI: 10.1002/acn3.50872] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 07/05/2019] [Accepted: 07/29/2019] [Indexed: 01/16/2023] Open
Abstract
Background Gray matter (GM) pathology is closely associated with physical and cognitive impairment in persons with multiple sclerosis (PwMS). Similarly, serum neurofilament light chain (sNfL) levels are related to MS disease activity and progression. Objectives To assess the cross–sectional and longitudinal associations between sNfL and MRI–derived lesion and brain volume outcomes in PwMS and age–matched healthy controls (HCs). Materials and Methods Forty‐seven HCs and 120 PwMS were followed over 5 years. All subjects underwent baseline and follow–up 3T MRI and sNfL examinations. Lesion volumes (LV) and global, tissue–specific and regional brain volumes were assessed. sNfL levels were analyzed using single molecule array (Simoa) assay and quantified in pg/mL. The associations between sNfL levels and MRI outcomes were investigated using regression analyses adjusted for age, sex, baseline disease modifying treatment (DMT) use and change in DMT over the follow‐up. False discovery rate (FDR)–adjusted q‐values <0.05 were considered significant. Results In PwMS, baseline sNfL was associated with baseline T1‐, T2‐ and gadolinium‐LV (q = 0.002, q = 0.001 and q < 0.001, respectively), but not with their longitudinal changes. Higher baseline sNfL levels were associated with lower baseline deep GM (β = −0.257, q = 0.017), thalamus (β = −0.216, q = 0.0017), caudate (β = −0.263, q = 0.014) and hippocampus (β = −0.267, q = 0.015) volumes. Baseline sNfL was associated with longitudinal decline of deep GM (β = −0.386, q < 0.001), putamen (β = −0.395, q < 0.001), whole brain (β = −0.356, q = 0.002), thalamus (β = −0.272, q = 0.049), globus pallidus (β = −0.284, q = 0.017), and GM (β = −0.264, q = 0.042) volumes. No associations between sNfL and MRI–derived measures were seen in the HCs. Conclusion Higher sNfL levels were associated with baseline LVs and greater development of GM atrophy in PwMS.
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Affiliation(s)
- Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York
| | - Jens Kuhle
- Neurologic Clinic and Policlinic, Departments of Medicine, Biomedicine and Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Murali Ramanathan
- Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, New York
| | - Christian Barro
- Neurologic Clinic and Policlinic, Departments of Medicine, Biomedicine and Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | | | - Jesper Hagemeier
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York
| | | | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York
| | | | - Michael G Dwyer
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York.,Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, New York
| | - Zuzanna Michalak
- Neurologic Clinic and Policlinic, Departments of Medicine, Biomedicine and Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Ralph H B Benedict
- Jacobs MS Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York
| | - Bianca Weinstock-Guttman
- Jacobs MS Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York.,Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, New York
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85
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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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86
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Zivadinov R, Dwyer MG. Network Dynamics and Cognitive Impairment in Multiple Sclerosis: Functional MRI-based Decoupling of Complex Relationships. Radiology 2019; 292:458-459. [PMID: 31237815 DOI: 10.1148/radiol.2019191125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Robert Zivadinov
- From the Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 100 High St, Buffalo, NY 14203; and Center for Biomedical Imaging at the Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY
| | - Michael G Dwyer
- From the Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 100 High St, Buffalo, NY 14203; and Center for Biomedical Imaging at the Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY
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87
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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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88
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Jakimovski D, Topolski M, Kimura K, Pandya V, Weinstock-Guttman B, Zivadinov R. Decrease in Secondary Neck Vessels in Multiple Sclerosis: A 5-year Longitudinal Magnetic Resonance Angiography Study. Curr Neurovasc Res 2019; 16:215-223. [PMID: 31195944 DOI: 10.2174/1567202616666190612111127] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 05/02/2019] [Accepted: 05/03/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Studies have previously shown greater arterial and venous extracranial vascular changes in persons with multiple sclerosis (PwMS) when compared to healthy controls (HCs). OBJECTIVES To determine the change in the number and size of secondary neck vessels in PwMS and HCs over a 5-year follow-up period. METHODS Both at baseline and follow-up, 83 PwMS and 25 HCs underwent magnetic resonance angiography (MRA) imaging and analysis. The number and cross-sectional area (CSA) of all secondary neck vessels (excluding the common/internal carotid, vertebral artery, and internal jugular vein) measured at levels from C2-T1 were determined by semi-automated edge detection/ contouring software. The longitudinal change in the number and CSA of the secondary neck vessels from the PwMS and HCs were analyzed by non-parametric Wilcoxon repeated measure. Benjamini-Hochberg procedure adjusted for false discovery rate (FDR). RESULTS For over 5 years, PwMS demonstrated a consistent longitudinal decrease in both the number of secondary neck vessels (Z-change between -3.3 and -5.4, q=0.001) and their CSA (Zchange between -2.9 and -5.2, q=0.004). On the contrary, the HCs did not demonstrate a significant longitudinal change in secondary neck vessels over the follow-up period. Due to the longitudinal decrease, the PwMS showed a lower number of secondary neck vessels when compared to HCs measured at follow-up (p<0.029, except for C4 with trending p=0.071). The PwMS changes were also corroborated within each MS phenotype. CONCLUSION PwMS demonstrate a significant mid-term decrease in the number and the size of the secondary neck vessels. The clinical relevance of these findings and the effect on intracranial blood flow are currently unknown.
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Affiliation(s)
- Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center (BNAC), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States
| | - Matthew Topolski
- Buffalo Neuroimaging Analysis Center (BNAC), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States
| | - Kana Kimura
- Buffalo Neuroimaging Analysis Center (BNAC), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States
| | - Virja Pandya
- Buffalo Neuroimaging Analysis Center (BNAC), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States
| | - Bianca Weinstock-Guttman
- Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center (BNAC), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States.,enter for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, United States
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Oreja-Guevara C, Ayuso Blanco T, Brieva Ruiz L, Hernández Pérez MÁ, Meca-Lallana V, Ramió-Torrentà L. Cognitive Dysfunctions and Assessments in Multiple Sclerosis. Front Neurol 2019; 10:581. [PMID: 31214113 PMCID: PMC6558141 DOI: 10.3389/fneur.2019.00581] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 05/16/2019] [Indexed: 12/22/2022] Open
Abstract
Cognitive impairment has been reported at all phases and all subtypes of multiple sclerosis. It remains a major cause of neurological disability in young and middle-aged adults suffering from the disease. The severity and type of cognitive impairment varies considerably among individuals and can be observed both in early and in later stages. The areas which have commonly shown more deficits are: information processing speed, complex attention, memory, and executive function. Even though an alteration in both the white matter and in the gray matter has been found in patients with multiple sclerosis and cognitive impairment, the underlying process still remains unknown. Standardized neurological examinations fail to detect emerging cognitive deficits and self-reported cognitive complaints by the patients can be confounded by other subjective symptoms. This review is a comprehensive and short update of the literature on cognitive dysfunctions, the possible confounders and the impact of quality of life in patients with multiple sclerosis.
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Affiliation(s)
- Celia Oreja-Guevara
- Servicio de Neurología, Hospital Clínico San Carlos, IdISSC, Departamento de Medicina, Universidad Complutense, Madrid, Spain
| | | | | | - Miguel Ángel Hernández Pérez
- Servicio de Neurología, Hospital Universitario Nuestra Señora de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Virginia Meca-Lallana
- Unidad de Esclerosis Múltiple, Servicio de Neurología, Fundación de Investigación Biomédica, Hospital Universitario de la Princesa, Madrid, Spain
| | - Lluís Ramió-Torrentà
- Unidad de Esclerosis Múltiple y Neuroinmunología de Girona, Servicio de Neurología, IDIBGI, Hospital Universitario Dr. Josep Trueta, Girona, Spain
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Mayo CD, Miksche K, Attwell-Pope K, Gawryluk JR. The relationship between physical activity and symptoms of fatigue, mood, and perceived cognitive impairment in adults with multiple sclerosis. J Clin Exp Neuropsychol 2019; 41:715-722. [PMID: 31096850 DOI: 10.1080/13803395.2019.1614535] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Introduction: Multiple Sclerosis (MS) is achronic neurological condition that requires costly treatment for aconstellation of motor and sensory symptoms, as well as fatigue, depression, and cognitive problems. Given that this pharmacological treatment often results in side effects, there is acrucial need for low-costbehavioral treatments that are effective in further reducing MS symptoms. It has been hypothesized that physical activity may slow the neurodegenerative progression of MS. The aim of the current study was to investigate the relationship between physical activity and commonly reported MS symptoms, including fatigue, depression, and perceived cognitive impairment. Method: 86 individuals with MS responded to amail-outquestionnaire. Physical activity, fatigue, mood, and perceived cognitive impairment were assessed using the following measures: Godin Leisure-TimeExercise Questionnaire (GLTEQ), Modified Fatigue Impact Scale (MFIS), Patient Health Questionnaire (PHQ-9), and Patient Deficit Questionnaire (PDQ). Descriptive and correlational statistics were calculated to investigate the relationship between scores on the GLTEQ and scores on the MFIS, PHQ-9, and PDQ. Results: Overall, there was asignificant negative relationship between physical activity (GLTEQ) and fatigue (MFIS; r= -.34, p= .002) and depression (PHQ-9; r= -.23, p= .034) in individuals with MS. There was not asignificant relationship between physical activity and overall perceived cognitive dysfunction (PDQ; r= -.19, p= .08), but when the PDQ subscales were examined, there was asignificant relationship with perceived retrospective (r = 0.24, p= .03) and prospective memory abilities (r = -.22, p= .04). When the RRMS and progressive subtypes were examined separately, we observed asimilar pattern of results for the RRMS group, but the progressive MS group did not reach significance. Conclusions: Individuals with MS who reported more strenuous and/or frequent physical activity, reported fewer problems with fatigue, depression, and perceived memory abilities.
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Affiliation(s)
- Chantel D Mayo
- a Department of Psychology , University of Victoria , Victoria , Canada
| | - Kelly Miksche
- a Department of Psychology , University of Victoria , Victoria , Canada
| | | | - Jodie R Gawryluk
- a Department of Psychology , University of Victoria , Victoria , Canada
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91
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Jakimovski D, Topolski M, Genovese AV, Weinstock-Guttman B, Zivadinov R. Vascular aspects of multiple sclerosis: emphasis on perfusion and cardiovascular comorbidities. Expert Rev Neurother 2019; 19:445-458. [PMID: 31003583 DOI: 10.1080/14737175.2019.1610394] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
INTRODUCTION Multiple sclerosis (MS) is a chronic inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. Over the last two decades, more favorable MS long-term outcomes have contributed toward increase in prevalence of the aged MS population. Emergence of age-associated pathology, such as cardiovascular diseases, may interact with the MS pathophysiology and further contribute to disease progression. Areas covered: This review summarizes the cardiovascular involvement in MS pathology, its disease activity, and progression. The cardiovascular health, the presence of various cardiovascular diseases, and their effect on MS cognitive performance are further explored. In similar fashion, the emerging evidence of a higher incidence of extracranial arterial pathology and its association with brain MS pathology are discussed. Finally, the authors outline the methodologies behind specific perfusion magnetic resonance imaging (MRI) and ultrasound Doppler techniques, which allow measurement of disease-specific and age-specific vascular changes in the aging population and MS patients. Expert opinion: Cardiovascular pathology significantly contributes to worse clinical and MRI-derived disease outcomes in MS. Global and regional cerebral hypoperfusion may be associated with poorer physical and cognitive performance. Prevention, improved detection, and treatment of the cardiovascular-based pathology may improve the overall long-term health of MS patients.
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Affiliation(s)
- Dejan Jakimovski
- a Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences , University at Buffalo, State University of New York , Buffalo , NY , USA.,b Jacobs Multiple Sclerosis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences , University at Buffalo, The State University of New York , Buffalo , NY , USA
| | - Matthew Topolski
- a Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences , University at Buffalo, State University of New York , Buffalo , NY , USA
| | - Antonia Valentina Genovese
- a Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences , University at Buffalo, State University of New York , Buffalo , NY , USA.,c Institute of Radiology, Department of Clinical Surgical Diagnostic and Pediatric Sciences , University of Pavia , Pavia , Italy
| | - Bianca Weinstock-Guttman
- b Jacobs Multiple Sclerosis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences , University at Buffalo, The State University of New York , Buffalo , NY , USA
| | - Robert Zivadinov
- a Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences , University at Buffalo, State University of New York , Buffalo , NY , USA.,b Jacobs Multiple Sclerosis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences , University at Buffalo, The State University of New York , Buffalo , NY , USA.,d Center for Biomedical Imaging at Clinical Translational Science Institute , University at Buffalo, State University of New York , Buffalo , NY , USA
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92
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Wajda DA, Wood TA, Sosnoff JJ. The attentional cost of movement in multiple sclerosis. J Neural Transm (Vienna) 2019; 126:577-583. [PMID: 30906960 DOI: 10.1007/s00702-019-01990-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Accepted: 03/05/2019] [Indexed: 11/26/2022]
Abstract
Individuals living with multiple sclerosis frequently have impairments in mobility. These impairments are more pronounced when they engage in a cognitively demanding mobility tasks (i.e., walking and talking, obstacle clearance, etc). Based in part on the attentional capacity model of movement, these impairments are suggested to result from greater attentional demands. Yet, this model has not been directly tested in neurological populations. The objective of the study was to determine whether individuals with multiple sclerosis have greater attentional cost of movement across a range of tasks. This study tested probe reaction times of 20 individuals with multiple sclerosis and 26 healthy controls in five different movement tasks. The tasks were specifically chosen to challenge the perceptual-motor system based on variations in static and dynamic balance requirements. Participants were asked to verbally respond as quickly as possible to randomly presented audio probes during motor performance. Task order was randomized, and average probe reaction time was calculated for each task. The results showed tasks requiring dynamic stability had greater probe reaction times in both healthy controls and individuals with multiple sclerosis. Furthermore, individuals with multiple sclerosis had longer probe reaction times across all tasks compared to healthy controls. Yet, there was no relationship between probe reaction times and performance during a complex walking scenario. The results indicate the attentional capacity model may be inadequate to explain cognitive-motor interaction in people with multiple sclerosis. Future studies should address the theoretical framework of cognitive-motor interaction, which may influence the design of interventions aimed at improving performance in individuals with MS.
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Affiliation(s)
- Douglas A Wajda
- Department of Health and Human Performance, Cleveland State University, Cleveland, OH, USA
| | - Tyler A Wood
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Jacob J Sosnoff
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
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93
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Aguirre N, Cruz-Gómez ÁJ, Miró-Padilla A, Bueichekú E, Broseta Torres R, Ávila C, Sanchis-Segura C, Forn C. Repeated Working Memory Training Improves Task Performance and Neural Efficiency in Multiple Sclerosis Patients and Healthy Controls. Mult Scler Int 2019; 2019:2657902. [PMID: 31139470 PMCID: PMC6500632 DOI: 10.1155/2019/2657902] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 03/06/2019] [Accepted: 04/04/2019] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND/OBJECTIVE To explore the effectiveness of a specific working memory (WM) training program in MS patients and healthy controls (HC). METHOD 29 MS patients and 29 matched HC were enrolled in the study. MS and HC were randomly split into two groups: nontraining groups (15HC/14 MS) and training groups (14 HC/15 MS). Training groups underwent adaptive n-back training (60 min/day; 4 days). Functional magnetic resonance imaging (fMRI) was used to monitor brain activity during n-back performance (conditions: 0-back, 2-back, and 3-back) at 3 time points: (1) baseline, (2) post-training (+7days), and (3) follow-up (+35days). RESULTS In post-training and follow-up fMRI sessions, trained groups (HC and MS patients) exhibited significant reaction time (RT) reductions and increases in Correct Responses (CRs) during 2-back and 3-back performance. This improvement of task performance was accompanied by a decrease in brain activation in the WM frontoparietal network. The two effects were significantly correlated. CONCLUSIONS After WM training, both cognitively preserved MS patients and HC participants showed task performance improvement made possible by neuroplastic processes that enhanced neural efficiency.
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Affiliation(s)
- Naiara Aguirre
- Universitat Jaume I. Departament de Psicología Bàsica, Clínica i Psicobiología, Castelló de la Plana 12006, Spain
| | - Álvaro Javier Cruz-Gómez
- Universitat Jaume I. Departament de Psicología Bàsica, Clínica i Psicobiología, Castelló de la Plana 12006, Spain
| | - Anna Miró-Padilla
- Universitat Jaume I. Departament de Psicología Bàsica, Clínica i Psicobiología, Castelló de la Plana 12006, Spain
| | - Elisenda Bueichekú
- Universitat Jaume I. Departament de Psicología Bàsica, Clínica i Psicobiología, Castelló de la Plana 12006, Spain
| | | | - César Ávila
- Universitat Jaume I. Departament de Psicología Bàsica, Clínica i Psicobiología, Castelló de la Plana 12006, Spain
| | - Carla Sanchis-Segura
- Universitat Jaume I. Departament de Psicología Bàsica, Clínica i Psicobiología, Castelló de la Plana 12006, Spain
| | - Cristina Forn
- Universitat Jaume I. Departament de Psicología Bàsica, Clínica i Psicobiología, Castelló de la Plana 12006, Spain
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94
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Pitteri M, Genova H, Lengenfelder J, DeLuca J, Ziccardi S, Rossi V, Calabrese M. Social cognition deficits and the role of amygdala in relapsing remitting multiple sclerosis patients without cognitive impairment. Mult Scler Relat Disord 2019; 29:118-123. [DOI: 10.1016/j.msard.2019.01.030] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 11/20/2018] [Accepted: 01/18/2019] [Indexed: 12/19/2022]
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95
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Huang SY, Fan Q, Machado N, Eloyan A, Bireley JD, Russo AW, Tobyne SM, Patel KR, Brewer K, Rapaport SF, Nummenmaa A, Witzel T, Sherman JC, Wald LL, Klawiter EC. Corpus callosum axon diameter relates to cognitive impairment in multiple sclerosis. Ann Clin Transl Neurol 2019; 6:882-892. [PMID: 31139686 PMCID: PMC6529828 DOI: 10.1002/acn3.760] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 02/16/2019] [Accepted: 02/27/2019] [Indexed: 11/24/2022] Open
Abstract
Objective To evaluate alterations in apparent axon diameter and axon density obtained by high‐gradient diffusion MRI in the corpus callosum of MS patients and the relationship of these advanced diffusion MRI metrics to neurologic disability and cognitive impairment in MS. Methods Thirty people with MS (23 relapsing‐remitting MS [RRMS], 7 progressive MS [PMS]) and 23 healthy controls were scanned on a human 3‐tesla (3T) MRI scanner equipped with 300 mT/m maximum gradient strength using a comprehensive multishell diffusion MRI protocol. Data were fitted to a three‐compartment geometric model of white matter to estimate apparent axon diameter and axon density in the midline corpus callosum. Neurologic disability and cognitive function were measured using the Expanded Disability Status Scale (EDSS), Multiple Sclerosis Functional Composite (MSFC), and Minimal Assessment of Cognitive Function in MS battery. Results Apparent axon diameter was significantly larger and axon density reduced in the normal‐appearing corpus callosum (NACC) of MS patients compared to healthy controls, with similar trends seen in PMS compared to RRMS. Larger apparent axon diameter in the NACC of MS patients correlated with greater disability as measured by the EDSS (r = 0.555, P = 0.007) and poorer performance on the Symbol Digits Modalities Test (r = ‐0.593, P = 0.008) and Brief Visuospatial Memory Test–Revised (r = −0.632, P < 0.01), tests of interhemispheric processing speed and new learning and memory, respectively. Interpretation Apparent axon diameter in the corpus callosum obtained from high‐gradient diffusion MRI is a potential imaging biomarker that may be used to understand the development and progression of cognitive impairment in MS.
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Affiliation(s)
- Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown Massachusetts
| | - Qiuyun Fan
- Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown Massachusetts
| | - Natalya Machado
- Department of Neurology Massachusetts General Hospital Boston Massachusetts
| | - Ani Eloyan
- Department of Biostatistics School of Public Health Brown University Providence Rhode Island
| | - John D Bireley
- Department of Neurology Massachusetts General Hospital Boston Massachusetts
| | - Andrew W Russo
- Department of Neurology Massachusetts General Hospital Boston Massachusetts
| | - Sean M Tobyne
- Department of Neurology Massachusetts General Hospital Boston Massachusetts
| | - Kevin R Patel
- Department of Neurology Massachusetts General Hospital Boston Massachusetts
| | - Kristina Brewer
- Department of Neurology Massachusetts General Hospital Boston Massachusetts
| | - Sarah F Rapaport
- Department of Neurology Massachusetts General Hospital Boston Massachusetts
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown Massachusetts
| | - Thomas Witzel
- Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown Massachusetts
| | - Janet C Sherman
- Psychology Assessment Center Department of Neurology Massachusetts General Hospital Boston Massachusetts
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown Massachusetts
| | - Eric C Klawiter
- Department of Neurology Massachusetts General Hospital Boston Massachusetts
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96
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Amato MP, Prestipino E, Bellinvia A. Identifying risk factors for cognitive issues in multiple sclerosis. Expert Rev Neurother 2019; 19:333-347. [PMID: 30829076 DOI: 10.1080/14737175.2019.1590199] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
INTRODUCTION Cognitive impairment (CI) in Multiple Sclerosis (MS) has progressively regained clinical and research interest and is currently recognized as a debilitating and burdensome problem for these patients. Studying risk and protecting factors that may influence the development and course of CI is currently an area of increasing interest, due to the potential for preventive strategies. Areas covered: In this narrative review the authors briefly addressed the physiopathologic basis, assessment and management of CI in MS and then focused on identifying modifiable and not modifiable risk factors for CI in MS, providing an overview of the current knowledge in the field and indicating avenues for future research. Expert opinion: Improving our understanding of potentially modifiable environmental and lifestyle risk factors or protective factors for CI is important in order to prompt preventive strategies and orient patient counselling and clinical management. To this aim, we need to enhance the current level of evidence linking lifestyle factors to cognition and evaluate some factors that were only preliminary addressed in research. Moreover, we need to explore the role of each factor into the subject cognitive outcome, next to the possible interactions between different environmental factors as well as between environmental and genetic factors.
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Affiliation(s)
- Maria Pia Amato
- a NEUROFARBA Department, Neuroscience section , University of Florence , Florence , Italy.,b IRCSS Fondazione Don Carlo Gnocchi , Florence , Italy
| | - Elio Prestipino
- a NEUROFARBA Department, Neuroscience section , University of Florence , Florence , Italy
| | - Angelo Bellinvia
- a NEUROFARBA Department, Neuroscience section , University of Florence , Florence , Italy
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97
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Lazo-Gomez R, Velázquez GDLLG, Mireles-Jacobo D, Sotomayor-Sobrino MA. Mechanisms of neurobehavioral abnormalities in multiple sclerosis: Contributions from neural and immune components. Clin Neurophysiol Pract 2019; 4:39-46. [PMID: 30911699 PMCID: PMC6416523 DOI: 10.1016/j.cnp.2019.01.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2018] [Revised: 12/21/2018] [Accepted: 01/10/2019] [Indexed: 12/14/2022] Open
Abstract
Multiple sclerosis-related neurobehavioral abnormalities are one of the main components of disability in this disease. The same pathological processes that explain demyelination periods and neurodegeneration also allow the comprehension of neurobehavioral abnormalities. Inflammation in the central nervous system caused by cells of the immune system, especially lymphocytes, and by resident cells, such as astrocytes and microglia, directly modulate neurotransmission and synaptic physiology, resulting in behavioral changes (such as sickness behavior) and amplifying the degenerative mechanisms that occur in multiple sclerosis. In addition, neuronal death caused by glutamate-mediated excitotoxicity, alterations in GABAergic, serotonergic, and dopaminergic neurotransmission, and the mechanisms of axon damage are of foremost importance to explain the reduction in brain volume and the associated cognitive decline. Neuroinflammation and neurodegeneration are not isolated phenomena and various instances of interaction between them have been described. This presents attractive targets for the development of therapeutic strategies for this neglected component of multiple sclerosis related disability.
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Affiliation(s)
- Rafael Lazo-Gomez
- Neuroscience franchise, Novartis Pharma México, Calzada de Tlalpan 1779, San Diego Churubusco, 04120 Coyoacán, CDMX, Mexico
| | | | - Diego Mireles-Jacobo
- Neuroscience franchise, Novartis Pharma México, Calzada de Tlalpan 1779, San Diego Churubusco, 04120 Coyoacán, CDMX, Mexico
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98
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Cognitive Functioning in Patients with Pediatric-Onset Multiple Sclerosis, an Updated Review and Future Focus. CHILDREN-BASEL 2019; 6:children6020021. [PMID: 30720736 PMCID: PMC6406784 DOI: 10.3390/children6020021] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Revised: 01/28/2019] [Accepted: 01/31/2019] [Indexed: 12/11/2022]
Abstract
Pediatric-onset multiple sclerosis (POMS) is relatively rare, but as technology and neuroimaging advance, an increasing number of cases are identified, and our understanding of how multiple sclerosis (MS) impacts the developing brain improves. There are consistent findings in the literature highlighting the impact of MS and other demyelinating diseases on cognitive functioning and cognitive development. We also have a better understanding of how POMS impacts psychosocial functioning and functional outcomes in daily living. This paper hopes to review findings associated with cognitive and psychosocial functioning in patients with POMS, as well as explore more recent advances in the field and how they relate to cognitive and psychosocial outcomes. We also discuss the ongoing need for future studies with a focus on better understanding deficits and disease correlates, but also preventative measures and potential rehabilitation.
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99
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Jakimovski D, Benedict RH, Marr K, Gandhi S, Bergsland N, Weinstock-Guttman B, Zivadinov R. Lower total cerebral arterial flow contributes to cognitive performance in multiple sclerosis patients. Mult Scler 2019; 26:201-209. [PMID: 30625030 DOI: 10.1177/1352458518819608] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND The cognitive performance in multiple sclerosis (MS) patients declines with aging, longer disease duration, and possibly cardiovascular comorbidities. OBJECTIVES We investigated whether lower total cerebral arterial blood flow (CABF) measured at the level of the carotid and vertebral arteries may contribute to worse cognitive performance in 132 MS patients and 47 healthy controls. METHODS Total CABF was evaluated with extracranial Doppler, whereas structural T2-lesion volume (LV) and gray matter volume (GMV) were measured on 3T MRI. The cognitive performance was assessed by Symbol Digit Modalities Test (SDMT), Brief Visuospatial Memory Test-Revised (BVMT-R), and California Verbal Learning Test-Second Edition (CVLT-II). Analysis of covariance, partial correlation, and regression models were used to test the differences between study groups and cognition/CABF correlations. False discovery rate (FDR)-corrected (Benjamini-Hochberg) p-values (i.e. q-values) less than 0.05 were considered significant. RESULTS Association between lower total CABF and the lower cognitive performance was observed only in MS patients (r = 0.318, q < 0.001 and r = 0.244, q = 0.012 for SDMT and BVMT-R, respectively). Lower GMV, higher T2-LV, and CABF were significantly associated with poorer performance on the processing speed measure of SDMT (adjusted R2 = 0.295, t-statistics = 2.538, standardized β = 0.203, and q = 0.020), but not with memory tests. Cognitively impaired MS patients had lower total CABF compared to cognitively preserved (884.5 vs 1020.2 mL/min, q = 0.008). CONCLUSION Cognitively impaired MS patients presented with lower total CABF. Altered CABF may be a result of reduced metabolic rate and might contribute to abnormal cognitive aging in MS.
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Affiliation(s)
- Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Ralph Hb Benedict
- Jacobs Multiple Sclerosis Center for Treatment and Research, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Karen Marr
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Sirin Gandhi
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Bianca Weinstock-Guttman
- Jacobs Multiple Sclerosis Center for Treatment and Research, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA/Center for Biomedical Imaging, Clinical Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, USA
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100
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Fuchs TA, Wojcik C, Wilding GE, Pol J, Dwyer MG, Weinstock-Guttman B, Zivadinov R, Benedict RH. Trait Conscientiousness predicts rate of longitudinal SDMT decline in multiple sclerosis. Mult Scler 2019; 26:245-252. [PMID: 30615562 DOI: 10.1177/1352458518820272] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
BACKGROUND Many people with multiple sclerosis (MS) exhibit cognitive decline over several years. Baseline differences may put people at greater risk for such decline. OBJECTIVE To characterize rates of longitudinal cognitive decline and investigate baseline clinical predictors. METHODS We report a retrospective analysis of 531 MS patients whose data were gleaned from a multi-study database, aggregated over 16 years. Linear mixed effects modeling was applied to estimate the average rate of decline on Symbol Digit Modalities Test (SDMT) performance and to predict rates of decline using baseline clinical variables. RESULTS Participants exhibited an average estimated decline of 0.22 SDMT raw-score points/year (95% confidence interval (CI) (-0.32, -0.12)). We observed a significant main effect of time from baseline (t = -2.78, p = 0.006), test form (t = 2.13, p = 0.034), disease course (t = 2.91, p = 0.004), age (t = -2.76, p = 0.006), sex (t = -2.71, p = 0.007), subjective cognitive impairment (t = -2.00, p = 0.046), premorbid verbal intelligence (t = 5.14, p < 0.001), and trait Conscientiousness (t = 2.69, p = 0.008). A significant interaction emerged for Conscientiousness and time from baseline (t = 2.57, p = 0.011). CONCLUSION Higher baseline trait Conscientiousness predicts slower rates of longitudinal cognitive decline in MS. This relationship, the average rate of decline, and practice effects can inform future research and clinical treatment decisions.
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Affiliation(s)
- Tom A Fuchs
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA/Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Curtis Wojcik
- Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Gregory E Wilding
- Department of Biostatistics, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Jeta Pol
- Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Michael G Dwyer
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA/Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Bianca Weinstock-Guttman
- Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Robert Zivadinov
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA/Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA/Center for Biomedical Imaging, Clinical Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Ralph Hb Benedict
- Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
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