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Jakimovski D, Qureshi F, Ramanathan M, Gehman V, Keshavan A, Leyden K, Dwyer MG, Bergsland N, Weinstock-Guttman B, Zivadinov R. Proteomics and relationship with axonal pathology in multiple sclerosis: 5-year diffusion tensor imaging study. Brain Commun 2023; 5:fcad183. [PMID: 37361716 PMCID: PMC10288551 DOI: 10.1093/braincomms/fcad183] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 05/08/2023] [Accepted: 06/08/2023] [Indexed: 06/28/2023] Open
Abstract
Blood-based biomarkers can be economic and easily accessible tools for monitoring and predicting disease activity in multiple sclerosis. The objective of this study was to determine the predictive value of a multivariate proteomic assay for concurrent and future microstructural/axonal brain pathology in a longitudinal study of a heterogeneous group of people with multiple sclerosis. A proteomic analysis was obtained on serum samples from 202 people with multiple sclerosis (148 relapsing-remitting and 54 progressive) at baseline and 5-year follow-up. The concentration of 21 proteins related to multiple pathways of multiple sclerosis pathophysiology was derived using Proximity Extension Assay on the Olink platform. Patients were imaged on the same 3T MRI scanner at both timepoints. Тhe rate of whole brain, white matter and grey matter atrophy over the 5-year follow-up was determined using the multi-timepoint Structural Image Evaluation, using Normalisation, of Atrophy algorithms. Lesion burden measures were also assessed. The severity of microstructural axonal brain pathology was quantified using diffusion tensor imaging. Fractional anisotropy and mean diffusivity of normal-appearing brain tissue, normal-appearing white matter, grey matter, T2 and T1 lesions were calculated. Age, sex and body mass index-adjusted step-wise regression models were used. Glial fibrillary acidic protein was the most common and highest-ranked proteomic biomarker associated with greater concurrent microstructural central nervous system alterations (P < 0.001). The rate of whole brain atrophy was associated with baseline levels of glial fibrillary acidic protein, protogenin precursor, neurofilament light chain and myelin oligodendrocyte (P < 0.009), whereas grey matter atrophy was associated with higher baseline neurofilament light chain, higher osteopontin and lower protogenin precursor levels (P < 0.016). Higher baseline glial fibrillary acidic protein level was a significant predictor of future severity of the microstructural CNS alterations as measured by normal-appearing brain tissue fractional anisotropy and mean diffusivity (standardized β = -0.397/0.327, P < 0.001), normal-appearing white matter fractional anisotropy (standardized β = -0.466, P < 0.0012), grey matter mean diffusivity (standardized β = 0.346, P < 0.011) and T2 lesion mean diffusivity (standardized β = 0.416, P < 0.001) at the 5-year follow-up. Serum levels of myelin-oligodendrocyte glycoprotein, neurofilament light chain, contactin-2 and osteopontin proteins were additionally and independently associated with worse concomitant and future axonal pathology. Higher glial fibrillary acidic protein levels were associated with future disability progression (Exp(B) = 8.65, P = 0.004). Multiple proteomic biomarkers are independently associated with greater severity of axonal brain pathology as measured by diffusion tensor imaging in multiple sclerosis. Baseline serum glial fibrillary acidic protein levels can predict future disability progression.
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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 14203, USA
| | | | - Murali Ramanathan
- Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, NY 14214, 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 14203, 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 14203, USA
- IRCCS, Fondazione Don Carlo Gnocchi, Milan 20113, Italy
| | - 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 14203, USA
| | - Robert Zivadinov
- Correspondence to: Robert Zivadinov, MD, PhD Department of Neurology, Jacobs School of Medicine and Biomedical Sciences Buffalo Neuroimaging Analysis Center, Center for Biomedical Imaging at Clinical Translational Science Institute University at Buffalo, 100 High St., Buffalo, NY 14203, USA E-mail:
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2
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Jakimovski D, Wicks TR, Bergsland N, Dwyer MG, Weinstock-Guttman B, Zivadinov R. Neuroimaging Correlates of Patient-Reported Outcomes in Multiple Sclerosis. Degener Neurol Neuromuscul Dis 2023; 13:21-32. [PMID: 36756005 PMCID: PMC9900239 DOI: 10.2147/dnnd.s384038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 01/24/2023] [Indexed: 02/04/2023] Open
Abstract
Background Patient-reported outcomes (PROs) are increasingly associated with concurrent and future impairments in persons with multiple sclerosis (pwMS). The structural and pathological relationships with PROs in pwMS have not been elucidated. Methods One hundred and forty-two pwMS and 47 healthy controls (HCs) were scanned using 3T MRI and completed a PRO questionnaire named Lifeware® that outlines the physical and psychosocial abilities. Beck's Depression Inventory (BDI) assessed levels of depression. T1- and T2-lesion volume, volumes of the whole brain (WBV), gray matter (GMV), white matter (WMV) and lateral ventricle (LVV) were derived using JIM and SIENAX software. Additional deep GM (DGMV) and nuclei-specific volumes of the thalamus, caudate, globus pallidus, putamen, and hippocampus were calculated using FIRST. Ordinal regression models adjusted for age and depression and mediation analyses were used. Results When compared to HCs, pwMS reported significantly greater limitations in mobility domains, including standing up from low seat (p < 0.001), climbing flight of stairs (p < 0.001), lower limb limitation (p < 0.001), limitations in bladder continence (p = 0.001) and fatigability (p < 0.001). Patient-reported limitations related to lower extremity function were explained by age, BDI, and all DGM nuclei volumes (p < 0.029). No such relationships were seen in the HCs. Fatiguability and the extent of life satisfaction were only related to depression (BDI p < 0.001) and not associated with any MRI-based outcomes. Most relationships between structural pathology and PROs were mediated by BDI scores (p < 0.001). In the pwMS group, there were no significant differences in any MRI-based brain volumes between the levels of reported life satisfaction. Conclusion PRO measures of lower extremity limitations were associated with DGM structures and DGM-specific nuclei. These findings promote the relevance of measuring DGM structures as measures directly related to subjective well-being and walking limitations. Depression is a significant mediator of PROs and in particular of life satisfaction.
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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,Correspondence: Dejan Jakimovski, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 100 High Street, Buffalo, NY, 14203, USA, Tel +1 716-859-7040, Fax +1 716-859-7066, Email
| | - Taylor R Wicks
- 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
| | - 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,IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy
| | - 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
| | - Bianca Weinstock-Guttman
- Department of Neurology, Jacobs Comprehensive MS Treatment and Research Center, 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 the Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA
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3
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Rehák Bučková B, Mareš J, Škoch A, Kopal J, Tintěra J, Dineen R, Řasová K, Hlinka J. Multimodal-neuroimaging machine-learning analysis of motor disability in multiple sclerosis. Brain Imaging Behav 2023; 17:18-34. [PMID: 36396890 DOI: 10.1007/s11682-022-00737-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/07/2022] [Indexed: 11/19/2022]
Abstract
Motor disability is a dominant and restricting symptom in multiple sclerosis, yet its neuroimaging correlates are not fully understood. We apply statistical and machine learning techniques on multimodal neuroimaging data to discriminate between multiple sclerosis patients and healthy controls and to predict motor disability scores in the patients. We examine the data of sixty-four multiple sclerosis patients and sixty-five controls, who underwent the MRI examination and the evaluation of motor disability scales. The modalities used comprised regional fractional anisotropy, regional grey matter volumes, and functional connectivity. For analysis, we employ two approaches: high-dimensional support vector machines run on features selected by Fisher Score (aiming for maximal classification accuracy), and low-dimensional logistic regression on the principal components of data (aiming for increased interpretability). We apply analogous regression methods to predict symptom severity. While fractional anisotropy provides the classification accuracy of 96.1% and 89.9% with both approaches respectively, including other modalities did not bring further improvement. Concerning the prediction of motor impairment, the low-dimensional approach performed more reliably. The first grey matter volume component was significantly correlated (R = 0.28-0.46, p < 0.05) with most clinical scales. In summary, we identified the relationship between both white and grey matter changes and motor impairment in multiple sclerosis. Furthermore, we were able to achieve the highest classification accuracy based on quantitative MRI measures of tissue integrity between patients and controls yet reported, while also providing a low-dimensional classification approach with comparable results, paving the way to interpretable machine learning models of brain changes in multiple sclerosis.
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Affiliation(s)
- Barbora Rehák Bučková
- The Czech Technical University in Prague, Karlovo namesti 13, 121 35, Prague, Czech Republic.,Institute of Computer Science of the Czech Academy of Sciences, Pod Vodarenskou vezi 2/271, 182 00, Prague, Czech Republic.,National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Jan Mareš
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic.,Institute for Clinical and Experimental Medicine, Videnska 1958, 140 21, Prague, Czech Republic
| | - Antonín Škoch
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic.,Institute for Clinical and Experimental Medicine, Videnska 1958, 140 21, Prague, Czech Republic
| | - Jakub Kopal
- Institute of Computer Science of the Czech Academy of Sciences, Pod Vodarenskou vezi 2/271, 182 00, Prague, Czech Republic
| | - Jaroslav Tintěra
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic.,Institute for Clinical and Experimental Medicine, Videnska 1958, 140 21, Prague, Czech Republic
| | - Robert Dineen
- University of Nottingham, Queen's Medical Centre, NG7 2UH, Nottingham, UK.,National Institute for Health Research, Nottingham Biomedical Research Centre, NG1 5DU, Nottingham, UK
| | - Kamila Řasová
- Charles University, Ruska 87, 100 00, Prague, Czech Republic
| | - Jaroslav Hlinka
- Institute of Computer Science of the Czech Academy of Sciences, Pod Vodarenskou vezi 2/271, 182 00, Prague, Czech Republic. .,National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic.
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Ganzetti M, Graves JS, Holm SP, Dondelinger F, Midaglia L, Gaetano L, Craveiro L, Lipsmeier F, Bernasconi C, Montalban X, Hauser SL, Lindemann M. Neural correlates of digital measures shown by structural MRI: a post-hoc analysis of a smartphone-based remote assessment feasibility study in multiple sclerosis. J Neurol 2023; 270:1624-1636. [PMID: 36469103 PMCID: PMC9970954 DOI: 10.1007/s00415-022-11494-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 11/15/2022] [Accepted: 11/17/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND A study was undertaken to evaluate remote monitoring via smartphone sensor-based tests in people with multiple sclerosis (PwMS). This analysis aimed to explore regional neural correlates of digital measures derived from these tests. METHODS In a 24-week, non-randomized, interventional, feasibility study (NCT02952911), sensor-based tests on the Floodlight Proof-of-Concept app were used to assess cognition (smartphone-based electronic Symbol Digit Modalities Test), upper extremity function (Draw a Shape Test, Pinching Test), and gait and balance (Static Balance Test, Two-Minute Walk Test, U-Turn Test). In this post-hoc analysis, digital measures and standard clinical measures (e.g., Nine-Hole Peg Test [9HPT]) were correlated against regional structural magnetic resonance imaging outcomes. Seventy-six PwMS aged 18-55 years with an Expanded Disability Status Scale score of 0.0-5.5 were enrolled from two different sites (USA and Spain). Sixty-two PwMS were included in this analysis. RESULTS Worse performance on digital and clinical measures was associated with smaller regional brain volumes and larger ventricular volumes. Whereas digital and clinical measures had many neural correlates in common (e.g., putamen, globus pallidus, caudate nucleus, lateral occipital cortex), some were observed only for digital measures. For example, Draw a Shape Test and Pinching Test measures, but not 9HPT score, correlated with volume of the hippocampus (r = 0.37 [drawing accuracy over time on the Draw a Shape Test]/ - 0.45 [touching asynchrony on the Pinching Test]), thalamus (r = 0.38/ - 0.41), and pons (r = 0.35/ - 0.35). CONCLUSIONS Multiple neural correlates were identified for the digital measures in a cohort of people with early MS. Digital measures showed associations with brain regions that clinical measures were unable to demonstrate, thus providing potential novel information on functional ability compared with standard clinical assessments.
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Affiliation(s)
- Marco Ganzetti
- grid.417570.00000 0004 0374 1269F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Jennifer S. Graves
- grid.266100.30000 0001 2107 4242Department of Neurosciences, University of California San Diego, San Diego, CA USA
| | - Sven P. Holm
- grid.417570.00000 0004 0374 1269F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Frank Dondelinger
- grid.417570.00000 0004 0374 1269F. Hoffmann-La Roche Ltd, Basel, Switzerland ,grid.419481.10000 0001 1515 9979Present Address: Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Luciana Midaglia
- grid.411083.f0000 0001 0675 8654Department of Neurology-Neuroimmunology, Centre d’Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d’Hebron, Barcelona, Spain ,grid.7080.f0000 0001 2296 0625Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain
| | - Laura Gaetano
- grid.417570.00000 0004 0374 1269F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Licinio Craveiro
- grid.417570.00000 0004 0374 1269F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | | | - Corrado Bernasconi
- grid.417570.00000 0004 0374 1269F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Xavier Montalban
- grid.411083.f0000 0001 0675 8654Department of Neurology-Neuroimmunology, Centre d’Esclerosi Múltiple de Catalunya (Cemcat), Hospital Universitari Vall d’Hebron, Barcelona, Spain ,grid.7080.f0000 0001 2296 0625Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain
| | - Stephen L. Hauser
- grid.266102.10000 0001 2297 6811Department of Neurology, University of California San Francisco, San Francisco, CA USA
| | - Michael Lindemann
- grid.417570.00000 0004 0374 1269F. Hoffmann-La Roche Ltd, Basel, Switzerland
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5
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Cofré Lizama LE, Strik M, Van der Walt A, Kilpatrick TJ, Kolbe SC, Galea MP. Gait stability reflects motor tracts damage at early stages of multiple sclerosis. Mult Scler 2022; 28:1773-1782. [DOI: 10.1177/13524585221094464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: Gait in people with multiple sclerosis (PwMS) is affected even when no changes can be observed on clinical examination. A sensitive measure of gait deterioration is stability; however, its correlation with motor tract damage has not yet been established. Objective: To compare stability between PwMS and healthy controls (HCs) and determine associations between stability and diffusion magnetic resonance image (MRI) measures of axonal damage in selected sensorimotor tracts. Methods: Twenty-five PwMS (Expanded Disability Status Scale (EDSS) < 2.5) and 15 HCs walked on a treadmill. Stability from sacrum (LDESAC), shoulder (LDESHO) and cervical (LDECER) was calculated using the local divergence exponent (LDE). Participants underwent a 7T-MRI brain scan to obtain fibre-specific measures of axonal loss within the corticospinal tract (CST), interhemispheric sensorimotor tract (IHST) and cerebellothalamic tract (CTT). Correlation analyses between LDE and fibre density (FD) within tracts, fibre cross-section (FC) and FD modulated by FC (FDC) were conducted. Between-groups LDE differences were analysed using analysis of variance (ANOVA). Results: Correlations between all stability measures with CSTFD, between CSTFDC with LDESAC and LDECER, and LDECER with IHSTFD and IHSTFDC were significant yet moderate ( R < −0.4). Stability was significantly different between groups. Conclusions: Poorer gait stability is associated with corticospinal tract (CST) axonal loss in PwMS with no-to-low disability and is a sensitive indicator of neurodegeneration.
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Affiliation(s)
- L Eduardo Cofré Lizama
- School of Allied Health, Human Services and Sports, La Trobe University, Bundoora, VIC, Australia/Department of Medicine and Radiology, The University of Melbourne, Parkville, VIC, Australia
| | - Myrte Strik
- Melbourne Brain Centre Imaging Unit, Department of Radiology, The University of Melbourne, Parkville, VIC, Australia
| | - Anneke Van der Walt
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Trevor J Kilpatrick
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia/Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia/Department of Neurology, The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Scott C Kolbe
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Mary P Galea
- Galea Department of Medicine and Radiology, The University of Melbourne, Parkville, VIC, Australia
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Jakimovski D, Kavak KS, Zakalik K, Bromley L, Ozel O, Qutab N, Eckert SP, Kolb C, Weinstock-Guttman B. A prospective study to validate the expanded timed get-up-and-go in a population with multiple sclerosis. Mult Scler J Exp Transl Clin 2022; 8:20552173221099186. [PMID: 35571975 PMCID: PMC9102142 DOI: 10.1177/20552173221099186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 04/20/2022] [Indexed: 12/02/2022] Open
Abstract
Background Timed 25-foot walk (T25FW) test serves as gold standard in care of persons with multiple sclerosis (PwMS) and as walking measure of regulatory trials. Objective To validate and determine the clinical utility of Expanded Timed Get-Up and Go (ETGUG) as a disability measure in MS. Methods ETGUG intra-rater and inter-rater reproducibility was determined in 65 PwMS that were examined twice in two centres over 1-week. Values below the 5th and above the 95th percentile were considered minimally detectable change. A longitudinal cohort (32.4 months) of 145 PwMS from New York State MS Consortium (NYSMSC) was used for clinical validation as a predictor of disability worsening measured by Expanded Disability Status Scale (EDSS). Results ETGUG and T25FW had noteworthy intra-rater and inter-rater reproducibility (Cronbach coefficient>0.949). One-week ETGUG difference ranged from 15.07% to −14.84% (5th and 95th percentile). Over the NYSMSC follow-up, PwMS had significant slowing in walking as measured by ETGUG (20.8 to 25.9s, p = 0.009) but not by T25FW. 15% ETGUG worsening had similar ability to predict EDSS worsening when compared to 20% T25FW worsening (AUC 0.596 vs. 0.552). Conclusion Over 32-month follow-up, PwMS experience slowing in ETGUG walking time but not in T25FW. Although the scoring may be more challenging, ETGUG could be more sensitive to change and provide more comprehensive measure of lower extremity performance and ambulation 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, NY, USA
| | | | - Karen Zakalik
- Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences University at Buffalo, Buffalo, NY, USA
| | | | | | | | | | - Channa Kolb
- Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences University at Buffalo, Buffalo, NY, USA
| | - Bianca Weinstock-Guttman
- Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences University at Buffalo, Buffalo, NY, USA
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7
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Petracca M, Cutter G, Cocozza S, Freeman L, Kangarlu J, Margoni M, Moro M, Krieger S, El Mendili MM, Droby A, Wolinsky JS, Lublin F, Inglese M. Cerebellar pathology and disability worsening in relapsing-remitting multiple sclerosis: A retrospective analysis from the CombiRx trial. Eur J Neurol 2021; 29:515-521. [PMID: 34695274 DOI: 10.1111/ene.15157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 09/27/2021] [Accepted: 10/21/2021] [Indexed: 11/27/2022]
Abstract
BACKGROUND AND PURPOSE Cerebellar damage is a valuable predictor of disability, particularly in progressive multiple sclerosis. It is not clear if it could be an equally useful predictor of motor disability worsening in the relapsing-remitting phenotype. AIM We aimed to determine whether cerebellar damage is an equally useful predictor of motor disability worsening in the relapsing-remitting phenotype. METHODS Cerebellar lesion loads and volumes were estimated using baseline magnetic resonance imaging from the CombiRx trial (n = 838). The relationship between cerebellar damage and time to disability worsening (confirmed disability progression [CDP], timed 25-foot walk test [T25FWT] score worsening, nine-hole peg test [9HPT] score worsening) was tested in stagewise and stepwise Cox proportional hazards models, accounting for demographics and supratentorial damage. RESULTS Shorter time to 9HPT score worsening was associated with higher baseline Expanded Disability Status Scale (EDSS) score (hazard ratio [HR] 1.408, p = 0.0042) and higher volume of supratentorial and cerebellar T2 lesions (HR 1.005 p = 0.0196 and HR 2.211, p = 0.0002, respectively). Shorter time to T25FWT score worsening was associated with higher baseline EDSS (HR 1.232, p = 0.0006). Shorter time to CDP was associated with older age (HR 1.026, p = 0.0010), lower baseline EDSS score (HR 0.428, p < 0.0001) and higher volume of supratentorial T2 lesions (HR 1.024, p < 0.0001). CONCLUSION Among the explored outcomes, single time-point evaluation of cerebellar damage only allows the prediction of manual dexterity worsening. In clinical studies the selection of imaging biomarkers should be informed by the outcome of interest.
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Affiliation(s)
- Maria Petracca
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Human Neurosciences, Sapienza University, Rome, Italy
| | - Gary Cutter
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Sirio Cocozza
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Leorah Freeman
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Houston, Texas, USA
| | - John Kangarlu
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Monica Margoni
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Padova Neuroscience Centre, University of Padua, Padua, Italy
| | - Matteo Moro
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genova, Genova, Italy
| | - Stephen Krieger
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mohamed Mounir El Mendili
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Aix Marseille Univ, CNRS, CRMBM, Marseille, France
| | - Amgad Droby
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Laboratory for Early Markers of Neurodegeneration (LEMON), Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Sagol School for Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Jerry S Wolinsky
- University of Texas Health Science Center at Houston (UTHealth), Houston, Texas, USA
| | - Fred Lublin
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Matilde Inglese
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal Child Health, University of Genoa, Genoa, Italy.,Ospedale Policlinico San Martino, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), Genoa, Italy
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8
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Jakimovski D, Zivadinov R, Vaughn CB, Ozel O, Weinstock-Guttman B. Clinical effects associated with five-year retinal nerve fiber layer thinning in multiple sclerosis. J Neurol Sci 2021; 427:117552. [PMID: 34175775 DOI: 10.1016/j.jns.2021.117552] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 06/18/2021] [Accepted: 06/19/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND Neurodegenerative changes in multiple sclerosis (MS) are associated with long-term disability progression (DP). Optical coherence tomography (OCT) measures may be used to monitor DP. OBJECTIVE To determine significant effects driving the changes in OCT-based peripapillary retinal nerve fiber layer (pRNFL) in heterogeneous group of MS patients. METHODS Total of 144 MS patients (109 relapsing-remitting MS and 35 progressive MS (PMS) with mean age at baseline of 47.6 and 56.5 years old, respectively) underwent clinical and OCT examination over 5-year follow-up. All OCT exams were reviewed using the OSCAR-IB criteria. The 5-year DP was determined based on Expanded Disability Status Scale (EDSS) changes and MS clinical trial criteria. Data regarding previous history of MS optic neuritis (MSON) and use of disease modifying treatment (DMT) was derived by in-person interview and review of electronic medical records. Mixed model-type of repeated measure analysis determined effects driving pRNFL change for analysis which utilized all eyes separately. RESULTS Over an average of 5.3-years follow-up, the MS population demonstrated significant pRNFL thinning (F = 16.108, p < 0.001). The pRNFL thinning was greater due to progressive MS subtype (F = 5.102, p = 0.025), greater age at baseline (F = 4.554, p = 0.034), occurrence of DP (F = 6.583, p = 0.011), and previous history of MSON (F = 7.053, p = 0.008). Use of any or highly potent DMT (natalizumab versus first-line injectable treatments versus no DMT) significantly reduced the pRNFL thinning (F = 8.367, p = 0.004) over the follow-up. Lastly, occurrence of DP in PMS patients older than 50 years old was associated with greater pRNFL thinning (F = 6.667, p = 0.013). CONCLUSION Longitudinal pRNFL changes are modified by age, disease subtype, disabiltiy progression, history of MSON, DMT use and their interactions.
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Affiliation(s)
- Dejan Jakimovski
- 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, USA; 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
- 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, USA; 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
| | - Caila B Vaughn
- 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, USA
| | - Osman Ozel
- 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, USA
| | - 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, USA
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9
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Fuchs TA, Dwyer MG, Jakimovski D, Bergsland N, Ramasamy DP, Weinstock-Guttman B, Hb Benedict R, Zivadinov R. Quantifying disease pathology and predicting disease progression in multiple sclerosis with only clinical routine T2-FLAIR MRI. NEUROIMAGE-CLINICAL 2021; 31:102705. [PMID: 34091352 PMCID: PMC8182301 DOI: 10.1016/j.nicl.2021.102705] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 05/12/2021] [Accepted: 05/19/2021] [Indexed: 12/17/2022]
Abstract
We explored five brain pathology measures from clinical-quality T2-FLAIR MRI in MS. These included LVV, thalamus volume, MOV, SCLV and network efficiency. T2-FLAIR measures predicted a majority of the variance in research-quality MRI. T2-FLAIR measures correlated with neurologic disability and cognitive function. T2-FLAIR measures predicted disability progression over five-years. T2-FLAIR measures can be used in legacy clinical datasets.
Background Although quantitative measures from research-quality MRI provide a means to study multiple sclerosis (MS) pathology in vivo, these metrics are often unavailable in legacy clinical datasets. Objective To determine how well an automatically-generated quantitative snapshot of brain pathology, measured only on clinical routine T2-FLAIR MRI, can substitute for more conventional measures on research MRI in terms of capturing multi-factorial disease pathology and providing similar clinical relevance. Methods MRI with both research-quality sequences and conventional clinical T2-FLAIR was acquired for 172 MS patients at baseline, and neurologic disability was assessed at baseline and five-years later. Five measures (thalamus volume, lateral ventricle volume, medulla oblongata volume, lesion volume, and network efficiency) for quantifying disparate aspects of neuropathology from low-resolution T2-FLAIR were applied to predict standard research-quality MRI measures. They were compared in regard to association with future neurologic disability and disease progression over five years. Results The combination of the five T2-FLAIR measures explained most of the variance in standard research-quality MRI. T2-FLAIR measures were associated with neurologic disability and cognitive function five-years later (R2 = 0.279, p < 0.001; R2 = 0.382, p < 0.001), similar to standard research-quality MRI (R2 = 0.279, p < 0.001; R2 = 0.366, p < 0.001). They also similarly predicted disability progression over five years (%-correctly-classified = 69.8, p = 0.034), compared to standard research-quality MRI (%-correctly-classified = 72.4%, p = 0.022) in relapsing-remitting MS. Conclusion A set of five T2-FLAIR-only measures can substitute for standard research-quality MRI, especially in relapsing-remitting MS. When only clinical T2-FLAIR is available, it can be used to obtain substantially more quantitative information about brain pathology and disability than is currently standard practice.
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Affiliation(s)
- 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; Jacobs Multiple Sclerosis Center, Department of Neurology, 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; Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - 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
| | - 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; IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Deepa P Ramasamy
- 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 Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, 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, 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; IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.
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10
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Baird JF, Motl RW. Cognitive Function and Whole-Brain MRI Metrics Are Not Associated with Mobility in Older Adults with Multiple Sclerosis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18084232. [PMID: 33923592 PMCID: PMC8073870 DOI: 10.3390/ijerph18084232] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 04/08/2021] [Accepted: 04/14/2021] [Indexed: 11/16/2022]
Abstract
Due to advances in disease-modifying medications and earlier management of comorbidities, adults with multiple sclerosis (MS) are living longer, and this coincides with the aging of the general population. One major problem among older adults with and without MS is limited mobility, a consequence of aging that often negatively affects quality of life. Identifying factors that contribute to mobility disability is needed to develop targeted rehabilitation approaches. This study examined cognitive processing speed and global brain atrophy as factors that may contribute to mobility disability in older adults with and without MS. Older adults (≥55 years) with MS (n = 31) and age- and sex-matched controls (n = 22) completed measures of mobility (Short Physical Performance Battery) and cognitive processing speed (Symbol Digit Modalities Test) and underwent an MRI to obtain whole-brain metrics (gray matter volume, white matter volume, ventricular volume) as markers of atrophy. Mobility was significantly worse in the MS group than in the control group (p = 0.004). Spearman correlations indicated that neither cognitive processing speed (MS: rs = 0.26; Control: rs = 0.08) nor markers of global brain atrophy (MS: rs range = −0.30 to −0.06; Control: rs range = −0.40 to 0.16) were significantly associated with mobility in either group. Other factors such as subcortical gray matter structures, functional connectivity, exercise/physical activity, and cardiovascular fitness should be examined as factors that may influence mobility in aging adults with and without MS.
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Affiliation(s)
- Jessica F. Baird
- Correspondence: (J.F.B.); (R.W.M.); Tel.: +1-205-934-5905 (R.W.M.)
| | - Robert W. Motl
- Correspondence: (J.F.B.); (R.W.M.); Tel.: +1-205-934-5905 (R.W.M.)
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11
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Strik M, Cofré Lizama LE, Shanahan CJ, van der Walt A, Boonstra FMC, Glarin R, Kilpatrick TJ, Geurts JJG, Cleary JO, Schoonheim MM, Galea MP, Kolbe SC. Axonal loss in major sensorimotor tracts is associated with impaired motor performance in minimally disabled multiple sclerosis patients. Brain Commun 2021; 3:fcab032. [PMID: 34222866 PMCID: PMC8244644 DOI: 10.1093/braincomms/fcab032] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/15/2020] [Accepted: 01/11/2021] [Indexed: 12/13/2022] Open
Abstract
Multiple sclerosis is a neuroinflammatory disease of the CNS that is associated with significant irreversible neuro-axonal loss, leading to permanent disability. There is thus an urgent need for in vivo markers of axonal loss for use in patient monitoring or as end-points for trials of neuroprotective agents. Advanced diffusion MRI can provide markers of diffuse loss of axonal fibre density or atrophy within specific white matter pathways. These markers can be interrogated in specific white matter tracts that underpin important functional domains such as sensorimotor function. This study aimed to evaluate advanced diffusion MRI markers of axonal loss within the major sensorimotor tracts of the brain, and to correlate the degree of axonal loss in these tracts to precise kinematic measures of hand and foot motor control and gait in minimally disabled people with multiple sclerosis. Twenty-eight patients (Expanded Disability Status Scale < 4, and Kurtzke Functional System Scores for pyramidal and cerebellar function ≤ 2) and 18 healthy subjects underwent ultra-high field 7 Tesla diffusion MRI for calculation of fibre-specific measures of axonal loss (fibre density, reflecting diffuse axonal loss and fibre cross-section reflecting tract atrophy) within three tracts: cortico-spinal tract, interhemispheric sensorimotor tract and cerebello-thalamic tracts. A visually guided force-matching task involving either the hand or foot was used to assess visuomotor control, and three-dimensional marker-based video tracking was used to assess gait. Fibre-specific axonal markers for each tract were compared between groups and correlated with visuomotor task performance (force error and lag) and gait parameters (stance, stride length, step width, single and double support) in patients. Patients displayed significant regional loss of fibre cross-section with minimal loss of fibre density in all tracts of interest compared to healthy subjects (family-wise error corrected p-value < 0.05), despite relatively few focal lesions within these tracts. In patients, reduced axonal fibre density and cross-section within the corticospinal tracts and interhemispheric sensorimotor tracts were associated with larger force tracking error and gait impairments (shorter stance, smaller step width and longer double support) (family-wise error corrected p-value < 0.05). In conclusion, significant gait and motor control impairments can be detected in minimally disabled people with multiple sclerosis that correlated with axonal loss in major sensorimotor pathways of the brain. Given that axonal loss is irreversible, the combined use of advanced imaging and kinematic markers could be used to identify patients at risk of more severe motor impairments as they emerge for more aggressive therapeutic interventions.
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Affiliation(s)
- Myrte Strik
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, the Netherlands
| | - L Eduardo Cofré Lizama
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
- School of Allied Health, Human Services and Sports, La Trobe University, Victoria 3086, Australia
| | - Camille J Shanahan
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
| | - Anneke van der Walt
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne 3004, Australia
| | - Frederique M C Boonstra
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne 3004, Australia
| | - Rebecca Glarin
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
| | - Trevor J Kilpatrick
- Florey Institute of Neuroscience and Mental Health, Parkville 3052, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Parkville 3052, Australia
- Department of Neurology, Royal Melbourne Hospital, Parkville 3050, Australia
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, the Netherlands
| | - Jon O Cleary
- Department of Radiology, Guy’s and St. Thomas’ NHS Foundation Trust, London SE1 7EH, UK
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, the Netherlands
| | - Mary P Galea
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
| | - Scott C Kolbe
- Department of Medicine and Radiology, University of Melbourne, Parkville 3010, Australia
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne 3004, Australia
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12
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Bergsland N, Benedict RHB, Dwyer MG, Fuchs TA, Jakimovski D, Schweser F, Tavazzi E, Weinstock-Guttman B, Zivadinov R. Thalamic Nuclei Volumes and Their Relationships to Neuroperformance in Multiple Sclerosis: A Cross-Sectional Structural MRI Study. J Magn Reson Imaging 2021; 53:731-739. [PMID: 33044013 DOI: 10.1002/jmri.27389] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 09/25/2020] [Accepted: 09/25/2020] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Although reduced thalamic volume is associated with multiple sclerosis (MS)-related clinical impairment, the role of individual thalamic nuclei remains poorly understood. PURPOSE/HYPOTHESIS To test whether individual thalamic nuclei volumes are more strongly associated with clinical disability than the whole thalamic volume. STUDY TYPE Retrospective analysis of a prospective dataset. SUBJECTS A total of 108 MS patients and 48 age- and sex-matched healthy controls (HCs) FIELD STRENGTH: 3T. SEQUENCES 3D T1 -weighted inversion recovery spoiled gradient echo; 2D T2 -weighted fluid-attenuated inversion recovery spin echo; 2D dual-echo proton density-weighted/T2 -weighted spin echo. ASSESSMENTS Clinical assessments included the Expanded Disability Status Scale (EDSS), Nine-Hole Peg Test (9HPT), Timed 25-Foot Walk (T25FW), Symbol Digit Modalities Test (SDMT), Brief Visuospatial Memory Test-Revised (BVMTR), and the California Verbal Learning Test (CVLT2). FreeSurfer provided anterior, intralaminar, lateral, medial, ventral, posterior, and total volumes. STATISTICAL TESTS False discovery rate-corrected partial correlations (controlling for age, sex, and education) to assess the relationships between volumes and neuroperformance. RESULTS Compared to HCs, MS patients presented with lower thalamic nuclei volumes (P < 0.05) except for the intralaminar nucleus (P = 0.279) and scored worse on all neuroperformance scales (P ≤ 0.05) except for CVLT2 (P = 0.151). All nuclei except intralaminar were associated with EDSS (correlation coefficient range: -0.233 to -0.395), SDMT (range: 0.247-0.423), and 9HPT (range: -0.232 to -0.303) (all P < 0.05). BVMTR was associated with anterior (r = 0.319), lateral (r = 0.31), and medial (r = 0.304) volumes (all P < 0.05). T25FW correlated with ventral (r = -0.392) and total (r = -0.309) volumes (both P < 0.05), with the latter being significantly greater (P < 0.05). DATA CONCLUSION Assessing individual nuclei volume can aid in unraveling the relationship between thalamic pathology and disparate aspects of MS-related disability. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- 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, New York, USA
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Ralph H B Benedict
- Jacobs Comprehensive MS Treatment and Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, USA
| | - Michael G Dwyer
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, USA
| | - Tom A Fuchs
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, USA
| | - 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, New York, USA
| | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, USA
- Center for Biomedical Imaging at Clinical Translational Science Institute, The State University of New York, Buffalo, New York, USA
| | - Eleonora Tavazzi
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, USA
| | - Bianca Weinstock-Guttman
- Jacobs Comprehensive MS Treatment and Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, 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, New York, USA
- Center for Biomedical Imaging at Clinical Translational Science Institute, The State University of New York, Buffalo, New York, USA
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13
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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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14
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Jakimovski D, Zivadinov R, Bergsland N, Ramasamy DP, Hagemeier J, Weinstock-Guttman B, Kolb C, Hojnacki D, Dwyer MG. Sex-Specific Differences in Life Span Brain Volumes in Multiple Sclerosis. J Neuroimaging 2020; 30:342-350. [PMID: 32392376 DOI: 10.1111/jon.12709] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 03/22/2020] [Accepted: 03/23/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND AND PURPOSE Numerous sex-specific differences in multiple sclerosis (MS) susceptibility, disease manifestation, disability progression, inflammation, and neurodegeneration have been previously reported. Previous magnetic resonance imaging (MRI) studies have shown structural differences between female and male MS brain volumes. To determine sex-specific global and tissue-specific brain volume throughout the MS life span in a real-world large MRI database. METHODS A total of 2,199 MS patients (female/male ratio of 1,651/548) underwent structural MRI imaging on either a 1.5-T or 3-T scanner. Global and tissue-specific volumes of whole brain (WBV), white matter, and gray matter (GMV) were determined by utilizing Structural Image Evaluation using Normalisation of Atrophy Cross-sectional (SIENAX). Lateral ventricular volume (LVV) was determined with the Neurological Software Tool for REliable Atrophy Measurement (NeuroSTREAM). General linear models investigated sex and age interactions, and post hoc comparative sex analyses were performed. RESULTS Despite being age-matched with female MS patents, a greater proportion of male MS patients were diagnosed with progressive MS and had lower normalized WBV (P < .001), GMV (P < .001), and greater LVV (P < .001). In addition to significant stand-alone main effects, an interaction between sex and age had an additional effect on the LVV (F-statistics = 4.53, P = .033) and GMV (F-statistics = 4.59, P = .032). The sex and age interaction was retained in both models of LVV (F-statistics = 3.31, P = .069) and GMV (F-statistics = 6.1, P = .003) when disease subtype and disease-modifying treatment (DMT) were also included. Although male MS patients presented with significantly greater LVV and lower GMV during the early and midlife period when compared to their female counterparts (P < .001 for LVV and P < .019 for GMV), these differences were nullified in 60+ years old patients. Similar findings were seen within a subanalysis of MS patients that were not on any DMT at the time of enrollment. CONCLUSION There are sex-specific differences in the LVV and GMV over the MS life span.
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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
| | - 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.,Translational Imaging Center at Clinical Translational Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY
| | - 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.,IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Deepa P Ramasamy
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY
| | - 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
| | - Bianca Weinstock-Guttman
- Jacobs MS Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York, Buffalo, NY
| | - Channa Kolb
- Jacobs MS Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York, Buffalo, NY
| | - David Hojnacki
- Jacobs MS Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York, Buffalo, NY
| | - 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
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15
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Jakimovski D, Bergsland N, Dwyer MG, Hagemeier J, Ramasamy DP, Szigeti K, Guttuso T, Lichter D, Hojnacki D, Weinstock-Guttman B, Benedict RHB, Zivadinov R. Long-standing multiple sclerosis neurodegeneration: volumetric magnetic resonance imaging comparison to Parkinson's disease, mild cognitive impairment, Alzheimer's disease, and elderly healthy controls. Neurobiol Aging 2020; 90:84-92. [PMID: 32147244 DOI: 10.1016/j.neurobiolaging.2020.02.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 01/30/2020] [Accepted: 02/03/2020] [Indexed: 12/16/2022]
Abstract
Multiple sclerosis (MS) exhibits neurodegeneration driven disability progression. We compared the extent of neurodegeneration among 112 long-standing MS patients, 37 Parkinson's disease (PD) patients, 34 amnestic mild cognitive impairment (aMCI) patients, 37 Alzheimer's disease (AD) patients, and 184 healthy controls. 3T MRI volumes of whole brain (WBV), white matter (WMV), gray matter (GMV), cortical (CV), deep gray matter (DGM), and nuclei-specific volumes of thalamus, caudate, putamen, globus pallidus, and hippocampus were derived with SIENAX and FIRST software. Аge and sex-adjusted analysis of covariance was used. WBV was not significantly different between diseases. MS had significantly lower WMV compared to other disease groups (p < 0.021). Only AD had smaller GMV and CV when compared to MS (both p < 0.001). MS had smaller DGM volume than PD and aMCI (p < 0.001 and p = 0.026, respectively) and lower thalamic volume when compared to all other neurodegenerative diseases (p < 0.008). Long-standing MS exhibits comparable global atrophy with lower WMV and thalamic volume when compared to other classical neurodegenerative diseases.
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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
| | - 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; IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy
| | - 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
| | - 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
| | - Deepa P Ramasamy
- 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
| | - Kinga Szigeti
- 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
| | - Thomas Guttuso
- 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
| | - David Lichter
- 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
| | - David Hojnacki
- 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; 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, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA; Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Ralph H B Benedict
- 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; 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, State University of New York, Buffalo, NY, USA; 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; 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 at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA.
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Jakimovski D, Weinstock-Guttman B, Ramanathan M, Dwyer MG, Zivadinov R. Infections, Vaccines and Autoimmunity: A Multiple Sclerosis Perspective. Vaccines (Basel) 2020; 8:vaccines8010050. [PMID: 32012815 PMCID: PMC7157658 DOI: 10.3390/vaccines8010050] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Revised: 01/21/2020] [Accepted: 01/24/2020] [Indexed: 12/13/2022] Open
Abstract
Background: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease that is associated with multiple environmental factors. Among suspected susceptibility events, studies have questioned the potential role of overt viral and bacterial infections, including the Epstein Bar virus (EBV) and human endogenous retroviruses (HERV). Furthermore, the fast development of immunomodulatory therapies further questions the efficacy of the standard immunization policies in MS patients. Topics reviewed: This narrative review will discuss the potential interplay between viral and bacterial infections and their treatment on MS susceptibility and disease progression. In addition, the review specifically discusses the interactions between MS pathophysiology and vaccination for hepatitis B, influenza, human papillomavirus, diphtheria, pertussis, and tetanus (DTP), and Bacillus Calmette-Guerin (BCG). Data regarding potential interaction between MS disease modifying treatment (DMT) and vaccine effectiveness is also reviewed. Moreover, HERV-targeted therapies such as GNbAC1 (temelimab), EBV-based vaccines for treatment of MS, and the current state regarding the development of T-cell and DNA vaccination are discussed. Lastly, a reviewing commentary on the recent 2019 American Academy of Neurology (AAN) practice recommendations regarding immunization and vaccine-preventable infections in the settings of MS is provided. Conclusion: There is currently no sufficient evidence to support associations between standard vaccination policies and increased risk of MS. MS patients treated with immunomodulatory therapies may have a lower benefit from viral and bacterial vaccination. Despite their historical underperformance, new efforts in creating MS-based vaccines are currently ongoing. MS vaccination programs follow the set back and slow recovery which is widely seen in other fields of medicine.
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Affiliation(s)
- Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY 14203, USA
- Correspondence:
| | - Bianca Weinstock-Guttman
- Jacobs MS Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY 14203, USA
| | - Murali Ramanathan
- School of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, NY 14214, USA
| | - Michael G. Dwyer
- Buffalo Neuroimaging Analysis Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY 14203, USA
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY 14203, USA
- Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY 14203, USA
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Baldassari LE, Nakamura K, Moss BP, Macaron G, Li H, Weber M, Jones SE, Rao SM, Miller D, Conway DS, Bermel RA, Cohen JA, Ontaneda D, McGinley MP. Technology-enabled comprehensive characterization of multiple sclerosis in clinical practice. Mult Scler Relat Disord 2019; 38:101525. [PMID: 31759186 DOI: 10.1016/j.msard.2019.101525] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 10/08/2019] [Accepted: 11/13/2019] [Indexed: 12/20/2022]
Abstract
BACKGROUND Objective and longitudinal measurements of disability in patients with multiple sclerosis (MS) are desired in order to monitor disease status and response to disease-modifying and symptomatic therapies. Technology-enabled comprehensive assessment of MS patients, including neuroperformance tests (NPTs), patient-reported outcome measures (PROMs), and MRI, is incorporated into clinical care at our center. The relationships of each NPT with PROMs and MRI measures in a real-world setting are incompletely studied, particularly in larger datasets. OBJECTIVES To demonstrate the utility of comprehensive neurological assessment and determine the association between NPTs, PROMs, and quantitative MRI measures in a large MS clinical cohort. METHODS NPTs (processing speed [PST], contrast sensitivity [CST], manual dexterity [MDT], and walking speed [WST]) and physical disability-related PROMs (Quality of Life in Neurological Disorders [Neuro-QoL], Patient Determined Disease Steps [PDDS], and Patient-Reported Outcomes Measurement Information System Global-10 [PROMIS-10] physical) were collected as part of routine clinical care. Fully-automated MRI analysis calculated T2-lesion volume (T2LV), whole brain fraction (WBF), thalamic volume (TV), and cervical spinal cord cross-sectional area (CA) for brain MRIs completed within 3 months of a clinic visit during which NPTs and PROMs were assessed. Spearman's rank correlation coefficients evaluated the cross-sectional associations of NPTs with PROMs and MRI measures. Linear regression was utilized to determine which combination of clinical characteristics, patient demographics, MRI measures, and PROMs best cross-sectionally explained each NPT result. RESULTS 997 unique patients (age 47.7 ± 11.4 years, 71.8% female) who underwent assessments over a 2-year period were included. Correlations among NPTs and PROMs were moderate. PST correlations were strongest for Neuro-QoL upper extremity (NQ-UE) (Spearman's rho = 0.43) and lower extremity (NQ-LE) (0.47). CST correlations were strongest for NQ-UE (0.33), NQ-LE (0.36), and PDDS (-0.31). MDT correlations were strongest for NQ-UE (-0.53), NQ-LE (-0.54), and PDDS (0.53). WST correlations were strongest for PDDS (0.64) and NQ-LE (-0.65). NPTs also had moderate correlations with MRI metrics, the strongest of which were observed with PST (with T2LV (-0.44) and WBF (0.49)). Spearman's rho for other NPT-MRI correlations ranged from 0.23 to 0.36. Linear regression identified age, disease duration, PROMIS-10 physical, NQ-UE, NQ-LE, T2LV and WBF as significant cross-sectional explanatory variables for PST (adjusted R2=0.46). For CST, significant variables included age and NQ-LE (adjusted R2 = 0.30). For MDT, significant variables included PDDS, PROMIS-10 physical, NQ-UE, NQ-LE, T2LV, and WBF (adjusted R2=0.37). For WST, significant variables included sex, PDDS, NQ-LE, T2LV, and CA (adjusted R2=0.39). CONCLUSIONS Impaired performance on NPTs correlated with worse physical disability-related PROMs and MRI disease severity, but the strongest cross-sectional explanatory variables for each NPT component varied. This study supports the use of comprehensive, objective quantification of MS status in clinical and research settings. Future longitudinal analyses can determine predictors of treatment response and disability worsening.
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Affiliation(s)
- Laura E Baldassari
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, United States
| | - Kunio Nakamura
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Brandon P Moss
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, United States
| | - Gabrielle Macaron
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, United States
| | - Hong Li
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, United States
| | - Malory Weber
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, United States
| | - Stephen E Jones
- Imaging Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Stephen M Rao
- Lou Ruvo Center for Brain Health, Cleveland Clinic, Cleveland, OH, United States
| | - Deborah Miller
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, United States
| | - Devon S Conway
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, United States
| | - Robert A Bermel
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, United States
| | - Jeffrey A Cohen
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, United States
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, United States
| | - Marisa P McGinley
- Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, United States.
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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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19
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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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20
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Browne RW, Jakimovski D, Ziliotto N, Kuhle J, Bernardi F, Weinstock-Guttman B, Zivadinov R, Ramanathan M. High-density lipoprotein cholesterol is associated with multiple sclerosis fatigue: A fatigue-metabolism nexus? J Clin Lipidol 2019; 13:654-663.e1. [PMID: 31307953 DOI: 10.1016/j.jacl.2019.06.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 05/31/2019] [Accepted: 06/04/2019] [Indexed: 12/11/2022]
Abstract
BACKGROUND Fatigue is a frequent symptom in multiple sclerosis (MS). The role of cholesterol and lipids in MS fatigue has not been investigated. OBJECTIVE To investigate the associations of cholesterol biomarkers and serum neurofilament light chain (sNfL) with fatigue in relapsing-remitting MS. METHODS This cross-sectional study included 75 relapsing-remitting MS patients (69% female, mean age ± SD: 49.6 ± 11 years and median Expanded Disability Status Scale score: 2.0). Fatigue, disability, and depression were assessed with Fatigue Severity Scale (FSS), Expanded Disability Status Scale, and the Beck Depression Index-Fast Screen, respectively. sNfL was measured using single-molecule array technology. Plasma total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and an apolipoprotein panel data were obtained. Soluble intercellular adhesion molecule-1 (sICAM-1), soluble vascular adhesion molecule-1 (sVCAM-1), chemokine (C-C motif) ligand 5 (CCL5 or RANTES), and CCL18 levels were measured to assess inflammation. RESULTS The mean FSS was 4.27 ± 1.73, and 57% had severe fatigue status (SFS, FSS ≥ 4.0). In regression analyses adjusted for age, sex, disability, and depression, lower FSS and SFS were associated with greater HDL-C (P = .006 for FSS, and P = .016 for SFS) and lower TC to HDL-C ratio (P = .011 for FSS, and P = .009 for SFS). Apolipoprotein A-II was also associated with FSS (P = .022). sNfL, CCL5, CCL18, sICAM-1, and sVCAM-1 levels were not associated with fatigue after adjusting for disability and depression. CONCLUSIONS TC to HDL-C ratio is associated with MS fatigue. Our results implicate a potential role for the HDL-C pathway in MS fatigue and could provide possible targets for the treatment of MS fatigue.
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Affiliation(s)
- Richard W Browne
- Department of Biotechnical and Clinical Laboratory Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
| | - 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
| | - Nicole Ziliotto
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Jens Kuhle
- Neurologic Clinic and Policlinic, Departments of Medicine, Biomedicine and Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Francesco Bernardi
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | | | - 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; Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Murali Ramanathan
- Department of Biotechnical and Clinical Laboratory Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
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21
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Jakimovski D, Weinstock-Guttman B, Roy S, Jaworski M, Hancock L, Nizinski A, Srinivasan P, Fuchs TA, Szigeti K, Zivadinov R, Benedict RHB. Cognitive Profiles of Aging in Multiple Sclerosis. Front Aging Neurosci 2019; 11:105. [PMID: 31133845 PMCID: PMC6524468 DOI: 10.3389/fnagi.2019.00105] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 04/18/2019] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Increasingly favorable mortality prognosis in multiple sclerosis (MS) raises questions regarding MS-specific cognitive aging and the presence of comorbidities such as Alzheimer's disease (AD). OBJECTIVE To assess elderly with MS (EwMS) and age-matched healthy controls (HCs) using both MS- and AD-specific psychometrics. METHODS EwMS (n = 104) and 56 HCs were assessed on a broad spectrum of language, visual-spatial processing, memory, processing speed, and executive function tests. Using logistic regression analysis, we examined cognitive performance differences between the EwMS and HC groups. Cognitive impairment (CI) was defined using a -1.5 SD threshold relative to age and education years-matched HCs, in two cognitive domains. RESULTS CI was observed in 47.1% of EwMS with differences most often seen on tests emphasizing cognitive processing speed as measured by Symbol Digit Modalities Test (SDMT) (d = 0.9, p < 0.001) and verbal fluency (both category-based d = 0.87, p < 0.001; letter-based d = 0.67, p < 0.001). After adjusting for age, sex and years of education, MS/HC diagnosis was best predicted (R 2 = 0.27) by differences in category-based verbal fluency (Wald = 9.935, p = 0.002) and SDMT (Wald = 13.937, p < 0.001). CONCLUSION This study confirms the common hallmark of slowed cognitive processing speed in MS among elderly patients. Defective verbal fluency, less often observed in younger cohorts, may represent emerging cognitive pathology due to other etiologies.
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Affiliation(s)
- Dejan Jakimovski
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo – The State University of New York, Buffalo, NY, United States
- 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, United States
| | - Bianca Weinstock-Guttman
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo – The State University of New York, Buffalo, NY, United States
| | - Shumita Roy
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo – The State University of New York, Buffalo, NY, United States
| | - Michael Jaworski
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo – The State University of New York, Buffalo, NY, United States
| | - Laura Hancock
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States
| | - Alissa Nizinski
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo – The State University of New York, Buffalo, NY, United States
| | - Pavitra Srinivasan
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo – The State University of New York, Buffalo, NY, United States
| | - Tom A. Fuchs
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo – The State University of New York, Buffalo, NY, United States
- 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, United States
| | - Kinga Szigeti
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo – The State University of New York, Buffalo, NY, United States
| | - Robert Zivadinov
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo – The State University of New York, Buffalo, NY, United States
- 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, United States
- Clinical Translational Science Institute, Center for Biomedical Imaging, University at Buffalo – The State University of New York, Buffalo, NY, United States
| | - Ralph H. B. Benedict
- Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo – The State University of New York, Buffalo, NY, United States
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22
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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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