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Comi G, Dalla Costa G, Stankoff B, Hartung HP, Soelberg Sørensen P, Vermersch P, Leocani L. Assessing disease progression and treatment response in progressive multiple sclerosis. Nat Rev Neurol 2024; 20:573-586. [PMID: 39251843 DOI: 10.1038/s41582-024-01006-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/30/2024] [Indexed: 09/11/2024]
Abstract
Progressive multiple sclerosis poses a considerable challenge in the evaluation of disease progression and treatment response owing to its multifaceted pathophysiology. Traditional clinical measures such as the Expanded Disability Status Scale are limited in capturing the full scope of disease and treatment effects. Advanced imaging techniques, including MRI and PET scans, have emerged as valuable tools for the assessment of neurodegenerative processes, including the respective role of adaptive and innate immunity, detailed insights into brain and spinal cord atrophy, lesion dynamics and grey matter damage. The potential of cerebrospinal fluid and blood biomarkers is increasingly recognized, with neurofilament light chain levels being a notable indicator of neuro-axonal damage. Moreover, patient-reported outcomes are crucial for reflecting the subjective experience of disease progression and treatment efficacy, covering aspects such as fatigue, cognitive function and overall quality of life. The future incorporation of digital technologies and wearable devices in research and clinical practice promises to enhance our understanding of functional impairments and disease progression. This Review offers a comprehensive examination of these diverse evaluation tools, highlighting their combined use in accurately assessing disease progression and treatment efficacy in progressive multiple sclerosis, thereby guiding more effective therapeutic strategies.
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Affiliation(s)
- Giancarlo Comi
- Department of Neurorehabilitation Sciences, Casa di Cura Igea, Milan, Italy.
| | | | - Bruno Stankoff
- Sorbonne Université, Paris Brain Institute, Institut du Cerveau et de la Moelle Épinière, Centre National de la Recherche Scientifique, Inserm, Paris, France
| | - Hans-Peter Hartung
- Brain and Mind Center, University of Sydney, Sydney, Australia
- Department of Neurology, Palacky University Olomouc, Olomouc, Czech Republic
- Department of Neurology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Per Soelberg Sørensen
- Department of Neurology, Danish Multiple Sclerosis Center, University of Copenhagen, Rigshospitalet, Copenhagen, Denmark
| | - Patrick Vermersch
- University of Lille, Inserm U1172, Lille Neuroscience & Cognition, Centre Hospitalier Universitaire de Lille, Fédération Hospitalo-Universitaire Precision Medicine in Psychiatry, Lille, France
| | - Letizia Leocani
- Vita-Salute San Raffaele University, Milan, Italy
- Multiple Sclerosis Center, Casa di Cura Igea, Milan, Italy
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Zivadinov R, Schweser F, Jakimovski D, Bergsland N, Dwyer MG. Decoding Gray Matter Involvement in Multiple Sclerosis via Imaging. Neuroimaging Clin N Am 2024; 34:453-468. [PMID: 38942527 DOI: 10.1016/j.nic.2024.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
Multiple sclerosis (MS) is increasingly understood not only as a white matter disease but also involving both the deep and cortical gray matter (GM). GM pathology in people with MS (pwMS) includes the presence of lesions, leptomeningeal inflammation, atrophy, altered iron concentration, and microstructural changes. Studies using 7T and 3T MR imaging with optimized protocols established that GM damage is a principal driver of disease progression in pwMS. Future work is needed to incorporate the assessment of these GM imaging biomarkers into the clinical workup of pwMS and the assessment of treatment efficacy.
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Affiliation(s)
- Robert Zivadinov
- Department of Neurology, Buffalo Neuroimaging Analysis Center, 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.
| | - Ferdinand Schweser
- Department of Neurology, Buffalo Neuroimaging Analysis Center, 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
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Niels Bergsland
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Michael G Dwyer
- Department of Neurology, Buffalo Neuroimaging Analysis Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, 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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Calabrese M, Preziosa P, Scalfari A, Colato E, Marastoni D, Absinta M, Battaglini M, De Stefano N, Di Filippo M, Hametner S, Howell OW, Inglese M, Lassmann H, Martin R, Nicholas R, Reynolds R, Rocca MA, Tamanti A, Vercellino M, Villar LM, Filippi M, Magliozzi R. Determinants and Biomarkers of Progression Independent of Relapses in Multiple Sclerosis. Ann Neurol 2024; 96:1-20. [PMID: 38568026 DOI: 10.1002/ana.26913] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/04/2024] [Accepted: 02/15/2024] [Indexed: 06/20/2024]
Abstract
Clinical, pathological, and imaging evidence in multiple sclerosis (MS) suggests that a smoldering inflammatory activity is present from the earliest stages of the disease and underlies the progression of disability, which proceeds relentlessly and independently of clinical and radiological relapses (PIRA). The complex system of pathological events driving "chronic" worsening is likely linked with the early accumulation of compartmentalized inflammation within the central nervous system as well as insufficient repair phenomena and mitochondrial failure. These mechanisms are partially lesion-independent and differ from those causing clinical relapses and the formation of new focal demyelinating lesions; they lead to neuroaxonal dysfunction and death, myelin loss, glia alterations, and finally, a neuronal network dysfunction outweighing central nervous system (CNS) compensatory mechanisms. This review aims to provide an overview of the state of the art of neuropathological, immunological, and imaging knowledge about the mechanisms underlying the smoldering disease activity, focusing on possible early biomarkers and their translation into clinical practice. ANN NEUROL 2024;96:1-20.
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Affiliation(s)
- Massimiliano Calabrese
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Antonio Scalfari
- Centre of Neuroscience, Department of Medicine, Imperial College, London, UK
| | - Elisa Colato
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Damiano Marastoni
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Martina Absinta
- Translational Neuropathology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marco Battaglini
- Siena Imaging S.r.l., Siena, Italy
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Massimiliano Di Filippo
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Simon Hametner
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Owain W Howell
- Institute of Life Sciences, Swansea University Medical School, Swansea, UK
| | - Matilde Inglese
- Dipartimento di neuroscienze, riabilitazione, oftalmologia, genetica e scienze materno-infantili - DINOGMI, University of Genova, Genoa, Italy
| | - Hans Lassmann
- Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Roland Martin
- Institute of Experimental Immunology, University of Zurich, Zurich, Switzerland
- Therapeutic Design Unit, Center for Molecular Medicine, Department of Clinical Neurosciences, Karolinska Institutet, Stockholm, Sweden
- Cellerys AG, Schlieren, Switzerland
| | - Richard Nicholas
- Department of Brain Sciences, Faculty of Medicine, Burlington Danes, Imperial College London, London, UK
| | - Richard Reynolds
- Division of Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Agnese Tamanti
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Marco Vercellino
- Multiple Sclerosis Center & Neurologia I U, Department of Neuroscience, University Hospital AOU Città della Salute e della Scienza di Torino, Turin, Italy
| | - Luisa Maria Villar
- Department of Immunology, Ramon y Cajal University Hospital. IRYCIS. REI, Madrid, Spain
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Roberta Magliozzi
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
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Ananthavarathan P, Sahi N, Chard DT. An update on the role of magnetic resonance imaging in predicting and monitoring multiple sclerosis progression. Expert Rev Neurother 2024; 24:201-216. [PMID: 38235594 DOI: 10.1080/14737175.2024.2304116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/08/2024] [Indexed: 01/19/2024]
Abstract
INTRODUCTION While magnetic resonance imaging (MRI) is established in diagnosing and monitoring disease activity in multiple sclerosis (MS), its utility in predicting and monitoring disease progression is less clear. AREAS COVERED The authors consider changing concepts in the phenotypic classification of MS, including progression independent of relapses; pathological processes underpinning progression; advances in MRI measures to assess them; how well MRI features explain and predict clinical outcomes, including models that assess disease effects on neural networks, and the potential role for machine learning. EXPERT OPINION Relapsing-remitting and progressive MS have evolved from being viewed as mutually exclusive to having considerable overlap. Progression is likely the consequence of several pathological elements, each important in building more holistic prognostic models beyond conventional phenotypes. MRI is well placed to assess pathogenic processes underpinning progression, but we need to bridge the gap between MRI measures and clinical outcomes. Mapping pathological effects on specific neural networks may help and machine learning methods may be able to optimize predictive markers while identifying new, or previously overlooked, clinically relevant features. The ever-increasing ability to measure features on MRI raises the dilemma of what to measure and when, and the challenge of translating research methods into clinically useable tools.
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Affiliation(s)
- Piriyankan Ananthavarathan
- Department of Neuroinflammation, University College London Queen Square Multiple Sclerosis Centre, London, UK
| | - Nitin Sahi
- Department of Neuroinflammation, University College London Queen Square Multiple Sclerosis Centre, London, UK
| | - Declan T Chard
- Clinical Research Associate & Consultant Neurologist, Institute of Neurology - Queen Square Multiple Sclerosis Centre, London, UK
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Fleischer V, Gonzalez-Escamilla G, Pareto D, Rovira A, Sastre-Garriga J, Sowa P, Høgestøl EA, Harbo HF, Bellenberg B, Lukas C, Ruggieri S, Gasperini C, Uher T, Vaneckova M, Bittner S, Othman AE, Collorone S, Toosy AT, Meuth SG, Zipp F, Barkhof F, Ciccarelli O, Groppa S. Prognostic value of single-subject grey matter networks in early multiple sclerosis. Brain 2024; 147:135-146. [PMID: 37642541 PMCID: PMC10766234 DOI: 10.1093/brain/awad288] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/17/2023] [Accepted: 08/02/2023] [Indexed: 08/31/2023] Open
Abstract
The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural networks to predict 5-year Expanded Disability Status Scale (EDSS) progression in patients with relapsing-remitting MS (RRMS). We hypothesized that network measures, derived from MRI, outperform conventional MRI measurements at identifying patients at risk of developing disability progression. This longitudinal, multicentre study within the Magnetic Resonance Imaging in MS (MAGNIMS) network included 406 patients with RRMS (mean age = 35.7 ± 9.1 years) followed up for 5 years (mean follow-up = 5.0 ± 0.6 years). EDSS was determined to track disability accumulation. A group of 153 healthy subjects (mean age = 35.0 ± 10.1 years) with longitudinal MRI served as controls. All subjects underwent MRI at baseline and again 1 year after baseline. Grey matter atrophy over 1 year and white matter lesion load were determined. A single-subject brain network was reconstructed from T1-weighted scans based on grey matter atrophy measures derived from a statistical parameter mapping-based segmentation pipeline. Key topological measures, including network degree, global efficiency and transitivity, were calculated at single-subject level to quantify network properties related to EDSS progression. Areas under receiver operator characteristic (ROC) curves were constructed for grey matter atrophy and white matter lesion load, and the network measures and comparisons between ROC curves were conducted. The applied network analyses differentiated patients with RRMS who experience EDSS progression over 5 years through lower values for network degree [H(2) = 30.0, P < 0.001] and global efficiency [H(2) = 31.3, P < 0.001] from healthy controls but also from patients without progression. For transitivity, the comparisons showed no difference between the groups [H(2) = 1.5, P = 0.474]. Most notably, changes in network degree and global efficiency were detected independent of disease activity in the first year. The described network reorganization in patients experiencing EDSS progression was evident in the absence of grey matter atrophy. Network degree and global efficiency measurements demonstrated superiority of network measures in the ROC analyses over grey matter atrophy and white matter lesion load in predicting EDSS worsening (all P-values < 0.05). Our findings provide evidence that grey matter network reorganization over 1 year discloses relevant information about subsequent clinical worsening in RRMS. Early grey matter restructuring towards lower network efficiency predicts disability accumulation and outperforms conventional MRI predictors.
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Affiliation(s)
- Vinzenz Fleischer
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology (IDI), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
| | - Alex Rovira
- Section of Neuroradiology, Department of Radiology (IDI), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
| | - Jaume Sastre-Garriga
- Department of Neurology/Neuroimmunology, Multiple Sclerosis Centre of Catalonia, Hospital Universitari Vall d'Hebron, 08035 Barcelona, Spain
| | - Piotr Sowa
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, 0424 Oslo, Norway
| | - Einar A Høgestøl
- Institute of Clinical Medicine, University of Oslo, NO-0316 Oslo, Norway
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
| | - Hanne F Harbo
- Institute of Clinical Medicine, University of Oslo, NO-0316 Oslo, Norway
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
| | - Barbara Bellenberg
- Institute of Neuroradiology, St Josef Hospital, Ruhr-University Bochum, 44791 Bochum, Germany
| | - Carsten Lukas
- Institute of Neuroradiology, St Josef Hospital, Ruhr-University Bochum, 44791 Bochum, Germany
| | - Serena Ruggieri
- Department of Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Claudio Gasperini
- Department of Neurosciences, San Camillo-Forlanini Hospital, 00152 Rome, Italy
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, 121 08 Prague, Czech Republic
| | - Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, 121 08 Prague, Czech Republic
| | - Stefan Bittner
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Ahmed E Othman
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Sara Collorone
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
| | - Ahmed T Toosy
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
| | - Sven G Meuth
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225 Düsseldorf, Germany
| | - Frauke Zipp
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Frederik Barkhof
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, 1100 DD Amsterdam, Netherlands
| | - Olga Ciccarelli
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Science, University College of London, WC1E 6BT London, UK
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
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Colato E, Prados F, Stutters J, Bianchi A, Narayanan S, Arnold DL, Wheeler-Kingshott C, Barkhof F, Ciccarelli O, Chard DT, Eshaghi A. Networks of microstructural damage predict disability in multiple sclerosis. J Neurol Neurosurg Psychiatry 2023; 94:992-1003. [PMID: 37468305 DOI: 10.1136/jnnp-2022-330203] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 06/13/2023] [Indexed: 07/21/2023]
Abstract
BACKGROUND Network-based measures are emerging MRI markers in multiple sclerosis (MS). We aimed to identify networks of white (WM) and grey matter (GM) damage that predict disability progression and cognitive worsening using data-driven methods. METHODS We analysed data from 1836 participants with different MS phenotypes (843 in a discovery cohort and 842 in a replication cohort). We calculated standardised T1-weighted/T2-weighted (sT1w/T2w) ratio maps in brain GM and WM, and applied spatial independent component analysis to identify networks of covarying microstructural damage. Clinical outcomes were Expanded Disability Status Scale worsening confirmed at 24 weeks (24-week confirmed disability progression (CDP)) and time to cognitive worsening assessed by the Symbol Digit Modalities Test (SDMT). We used Cox proportional hazard models to calculate predictive value of network measures. RESULTS We identified 8 WM and 7 GM sT1w/T2w networks (of regional covariation in sT1w/T2w measures) in both cohorts. Network loading represents the degree of covariation in regional T1/T2 ratio within a given network. The loading factor in the anterior corona radiata and temporo-parieto-frontal components were associated with higher risks of developing CDP both in the discovery (HR=0.85, p<0.05 and HR=0.83, p<0.05, respectively) and replication cohorts (HR=0.84, p<0.05 and HR=0.80, p<0.005, respectively). The decreasing or increasing loading factor in the arcuate fasciculus, corpus callosum, deep GM, cortico-cerebellar patterns and lesion load were associated with a higher risk of developing SDMT worsening both in the discovery (HR=0.82, p<0.01; HR=0.87, p<0.05; HR=0.75, p<0.001; HR=0.86, p<0.05 and HR=1.27, p<0.0001) and replication cohorts (HR=0.82, p<0.005; HR=0.73, p<0.0001; HR=0.80, p<0.005; HR=0.85, p<0.01 and HR=1.26, p<0.0001). CONCLUSIONS GM and WM networks of microstructural changes predict disability and cognitive worsening in MS. Our approach may be used to identify patients at greater risk of disability worsening and stratify cohorts in treatment trials.
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Affiliation(s)
- Elisa Colato
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Ferran Prados
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Jonathan Stutters
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Alessia Bianchi
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Douglas L Arnold
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Claudia Wheeler-Kingshott
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Brain Connectivity Centre, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Frederik Barkhof
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, location Vrije Universiteit, Amsterdam, Netherlands
- Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre (BRC), London, UK
| | - Olga Ciccarelli
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre (BRC), London, UK
| | - Declan T Chard
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre (BRC), London, UK
| | - Arman Eshaghi
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
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Zhang K, Lincoln JA, Jiang X, Bernstam EV, Shams S. Predicting multiple sclerosis severity with multimodal deep neural networks. BMC Med Inform Decis Mak 2023; 23:255. [PMID: 37946182 PMCID: PMC10634041 DOI: 10.1186/s12911-023-02354-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Accepted: 10/25/2023] [Indexed: 11/12/2023] Open
Abstract
Multiple Sclerosis (MS) is a chronic disease developed in the human brain and spinal cord, which can cause permanent damage or deterioration of the nerves. The severity of MS disease is monitored by the Expanded Disability Status Scale, composed of several functional sub-scores. Early and accurate classification of MS disease severity is critical for slowing down or preventing disease progression via applying early therapeutic intervention strategies. Recent advances in deep learning and the wide use of Electronic Health Records (EHR) create opportunities to apply data-driven and predictive modeling tools for this goal. Previous studies focusing on using single-modal machine learning and deep learning algorithms were limited in terms of prediction accuracy due to data insufficiency or model simplicity. In this paper, we proposed the idea of using patients' multimodal longitudinal and longitudinal EHR data to predict multiple sclerosis disease severity in the future. Our contribution has two main facets. First, we describe a pioneering effort to integrate structured EHR data, neuroimaging data and clinical notes to build a multi-modal deep learning framework to predict patient's MS severity. The proposed pipeline demonstrates up to 19% increase in terms of the area under the Area Under the Receiver Operating Characteristic curve (AUROC) compared to models using single-modal data. Second, the study also provides valuable insights regarding the amount useful signal embedded in each data modality with respect to MS disease prediction, which may improve data collection processes.
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Affiliation(s)
- Kai Zhang
- Department of Health Data Science and Artificial Intelligence, McWilliams School of Biomedical Informatics, University of Texas Health Sciences Center at Houston, Houston, TX, USA
| | - John A Lincoln
- Department of Neurology, University of Texas Health Sciences Center, McGovern Medical School, Houston, TX, USA
| | - Xiaoqian Jiang
- Department of Health Data Science and Artificial Intelligence, McWilliams School of Biomedical Informatics, University of Texas Health Sciences Center at Houston, Houston, TX, USA
| | - Elmer V Bernstam
- Department of Health Data Science and Artificial Intelligence, McWilliams School of Biomedical Informatics, University of Texas Health Sciences Center at Houston, Houston, TX, USA
- Division of General Internal Medicine, Department of Internal Medicine, University of Texas Health Sciences Center, McGovern Medical School, Houston, TX, USA
| | - Shayan Shams
- Department of Health Data Science and Artificial Intelligence, McWilliams School of Biomedical Informatics, University of Texas Health Sciences Center at Houston, Houston, TX, USA.
- Department of Applied Data Science, San Jose State University, San Jose, CA, USA.
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8
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Patitucci E, Lipp I, Stickland RC, Wise RG, Tomassini V. Changes in brain perfusion with training-related visuomotor improvement in MS. Front Mol Neurosci 2023; 16:1270393. [PMID: 38025268 PMCID: PMC10665528 DOI: 10.3389/fnmol.2023.1270393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/26/2023] [Indexed: 12/01/2023] Open
Abstract
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system. A better understanding of the mechanisms supporting brain plasticity in MS would help to develop targeted interventions to promote recovery. A total of 29 MS patients and 19 healthy volunteers underwent clinical assessment and multi-modal MRI acquisition [fMRI during serial reaction time task (SRT), DWI, T1w structural scans and ASL of resting perfusion] at baseline and after 4-weeks of SRT training. Reduction of functional hyperactivation was observed in MS patients following the training, shown by the stronger reduction of the BOLD response during task execution compared to healthy volunteers. The functional reorganization was accompanied by a positive correlation between improvements in task accuracy and the change in resting perfusion after 4 weeks' training in right angular and supramarginal gyri in MS patients. No longitudinal changes in WM and GM measures and no correlation between task performance improvements and brain structure were observed in MS patients. Our results highlight a potential role for CBF as an early marker of plasticity, in terms of functional (cortical reorganization) and behavioral (performance improvement) changes in MS patients that may help to guide future interventions that exploit preserved plasticity mechanisms.
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Affiliation(s)
- Eleonora Patitucci
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, United Kingdom
| | - Ilona Lipp
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, United Kingdom
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Rachael Cecilia Stickland
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, United Kingdom
| | - Richard G. Wise
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, United Kingdom
- Institute for Advanced Biomedical Technologies, University of Chieti-Pescara “G. d’Annunzio,”Chieti, Italy
- Department of Neurosciences, Imaging and Clinical Sciences, University of Chieti-Pescara “G. d’Annunzio,”Chieti, Italy
| | - Valentina Tomassini
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff, United Kingdom
- Institute for Advanced Biomedical Technologies, University of Chieti-Pescara “G. d’Annunzio,”Chieti, Italy
- Department of Neurosciences, Imaging and Clinical Sciences, University of Chieti-Pescara “G. d’Annunzio,”Chieti, Italy
- Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, United Kingdom
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9
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Itoh N, Itoh Y, Stiles L, Voskuhl R. Sex differences in the neuronal transcriptome and synaptic mitochondrial function in the cerebral cortex of a multiple sclerosis model. Front Neurol 2023; 14:1268411. [PMID: 38020654 PMCID: PMC10654219 DOI: 10.3389/fneur.2023.1268411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 10/09/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction Multiple sclerosis (MS) affects the cerebral cortex, inducing cortical atrophy and neuronal and synaptic pathology. Despite the fact that women are more susceptible to getting MS, men with MS have worse disability progression. Here, sex differences in neurodegenerative mechanisms are determined in the cerebral cortex using the MS model, chronic experimental autoimmune encephalomyelitis (EAE). Methods Neurons from cerebral cortex tissues of chronic EAE, as well as age-matched healthy control, male and female mice underwent RNA sequencing and gene expression analyses using RiboTag technology. The morphology of mitochondria in neurons of cerebral cortex was assessed using Thy1-CFP-MitoS mice. Oxygen consumption rates were determined using mitochondrial respirometry assays from intact as well as permeabilized synaptosomes. Results RNA sequencing of neurons in cerebral cortex during chronic EAE in C57BL/6 mice showed robust differential gene expression in male EAE compared to male healthy controls. In contrast, there were few differences in female EAE compared to female healthy controls. The most enriched differential gene expression pathways in male mice during EAE were mitochondrial dysfunction and oxidative phosphorylation. Mitochondrial morphology in neurons showed significant abnormalities in the cerebral cortex of EAE males, but not EAE females. Regarding function, synaptosomes isolated from cerebral cortex of male, but not female, EAE mice demonstrated significantly decreased oxygen consumption rates during respirometry assays. Discussion Cortical neuronal transcriptomics, mitochondrial morphology, and functional respirometry assays in synaptosomes revealed worse neurodegeneration in male EAE mice. This is consistent with worse neurodegeneration in MS men and reveals a model and a target to develop treatments to prevent cortical neurodegeneration and mitigate disability progression in MS men.
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Affiliation(s)
- Noriko Itoh
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Yuichiro Itoh
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Linsey Stiles
- Department of Endocrinology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Rhonda Voskuhl
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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10
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Zhu Q, Yan Z, Shi Z, Luo D, Ding S, Chen X, Li Y. Increased cortical lesion load contributed to pathological changes beyond focal lesion in cortical gray matter of multiple sclerosis: a diffusion kurtosis imaging analysis. Cereb Cortex 2023; 33:10867-10876. [PMID: 37718158 DOI: 10.1093/cercor/bhad332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 08/20/2023] [Accepted: 08/22/2023] [Indexed: 09/19/2023] Open
Abstract
Biomarkers specific to cortical gray matter (cGM) pathological changes of multiple sclerosis (MS) are desperately needed to better understand the disease progression. The cGM damage occurs in cortical lesion (CL) and normal-appearing cGM (NAcGM) areas. While the association between CL load and cGM damage has been reported, little is known about how different CL types, i.e. intracortical lesion (ICL) and leukocortical lesion (LCL) would be associated with cGM damage. In our study, relapsing-remitting MS patients and healthy controls were divided into 4 groups according to CL load level. NAcGM diffusion kurtosis imaging (DKI)/diffusion tensor imaging (DTI) values and cGM volume (cGMV) were used to characterize the pathological changes in cGM. Univariate general linear model was used for group comparisons and stepwise regression analysis was used to assess the effects of ICL volume and LCL volume on NAcGM damage. We found peak values in DKI/DTI values, cGMV and neuropsychological scores in high CL load group. Kurtosis fractional anisotropy (KFA) was the most sensitive in characterizing NAcGM damage, and LCL volume related more to NAcGM damage. Our findings suggested KFA could become a surrogate biomarker to cGM damage, and LCL might be the main factor in whole brain NAcGM damage.
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Affiliation(s)
- Qiyuan Zhu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Zichun Yan
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Zhuowei Shi
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Dan Luo
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Shuang Ding
- Department of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing 400014, China
| | - Xiaoya Chen
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Yongmei Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
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11
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Hamwi M, Thebault S, Melkus G, Auriat AM, Pham A, Carrington A, Thornhill R, Walker LAS, Chakraborty S, Torres C, Zhang L, Atkins HL, Freedman MS, Aviv RI. MRI graph parameters are longitudinal markers of neuronal integrity in multiple sclerosis. Mult Scler Relat Disord 2023; 80:105066. [PMID: 39491411 DOI: 10.1016/j.msard.2023.105066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 10/06/2023] [Accepted: 10/10/2023] [Indexed: 11/05/2024]
Abstract
PURPOSE We sought to determine if structural network parameters add to traditional markers of MS treatment response following immunoablation and autologous haemopoietic stem cell transplantation (IAHSCT). The post-IAHSCT paradigm afforded us the opportunity to study MS patients after relapsing biology had been effectively suppressed, enabling us to study the cortical substrate of progressive MS in a less confounded manner. METHODS In this analysis of data from a phase 2 prospective study, associations between magnetic resonance graph parameters, N-acetylaspartate to creatine ratio (NAA/Cr), and serum neurofilament light chain (sNfL), amongst other markers, were assessed at 3 months pre-and 12 months post-IAHSCT. Correlations between graph parameter score changes and markers of brain health were calculated. Predictive factors of NAA/Cr or sNfL levels were calculated, adjusting for reference models. Model improvements were evaluated using the G2 likelihood-ratio test. RESULTS 24 patients (aged 18-38) were evaluated. Post-IAHSCT, high NAA/Cr and low sNfL (both measures of neuronal injury) were respectively associated with more favourable degree, density, clustering and path lengths, and degree, γ, and path length. Post-IAHSCT, absolute change in degree, path length and γ were associated with NAA/Cr and sNfL. Multivariate analysis demonstrated that the relative change in network parameters after IAHSCT accounted for 14% and 35% more variance in NAA/Cr and sNfL levels respectively than the reference model alone. CONCLUSIONS Cross-sectionally and longitudinally, network parameters demonstrate added utility as markers of disease severity in MS. These measures have the potential to capture cortical changes relevant to progressive non-relapsing biology in MS.
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Affiliation(s)
- Milad Hamwi
- Ottawa Hospital Research Institute; University of Ottawa, Department of Radiology, Radiation Oncology and Medical Physics
| | | | - Gerd Melkus
- Ottawa Hospital Research Institute; University of Ottawa, Department of Radiology, Radiation Oncology and Medical Physics; University of Ottawa, Brain and Mind Research Institute
| | - Angela M Auriat
- Ottawa Hospital Research Institute; University of Ottawa, Department of Radiology, Radiation Oncology and Medical Physics; University of Ottawa, Brain and Mind Research Institute; University of Ottawa, Faculty of Medicine.
| | - Alex Pham
- Ottawa Hospital Research Institute; University of Ottawa, Department of Radiology, Radiation Oncology and Medical Physics
| | - André Carrington
- Ottawa Hospital Research Institute; University of Ottawa, Department of Radiology, Radiation Oncology and Medical Physics; University of Waterloo, Department of Systems Design Engineering
| | - Rebecca Thornhill
- Ottawa Hospital Research Institute; University of Ottawa, Department of Radiology, Radiation Oncology and Medical Physics
| | - Lisa A S Walker
- Ottawa Hospital Research Institute; Ottawa Hospital, Department of Psychology; University of Ottawa, Brain and Mind Research Institute; University of Ottawa, Faculty of Medicine
| | - Santanu Chakraborty
- Ottawa Hospital, Department of Medical Imaging; University of Ottawa, Department of Radiology, Radiation Oncology and Medical Physics; University of Ottawa, Brain and Mind Research Institute
| | - Carlos Torres
- Ottawa Hospital Research Institute; Ottawa Hospital, Department of Medical Imaging; University of Ottawa, Department of Radiology, Radiation Oncology and Medical Physics; University of Ottawa, Brain and Mind Research Institute
| | - Liying Zhang
- Department of Medical Imaging Sunnybrook Health Sciences Centre
| | - Harold L Atkins
- Ottawa Hospital Research Institute; Ottawa Hospital Blood and Marrow Transplant Program; University of Ottawa, Faculty of Medicine
| | - Mark S Freedman
- Ottawa Hospital, Department of Neurology; University of Ottawa, Brain and Mind Research Institute
| | - Richard I Aviv
- Ottawa Hospital, Department of Medical Imaging; University of Ottawa, Department of Radiology, Radiation Oncology and Medical Physics; University of Ottawa, Brain and Mind Research Institute.
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12
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Wenger KJ, Hoelter MC, Yalachkov Y, Hendrik Schäfer J, Özkan D, Steffen F, Bittner S, Hattingen E, Foerch C, Schaller-Paule MA. Serum neurofilament light chain is more strongly associated with T2 lesion volume than with number of T2 lesions in patients with multiple sclerosis. Eur J Radiol 2023; 166:111019. [PMID: 37549559 DOI: 10.1016/j.ejrad.2023.111019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 03/24/2023] [Accepted: 07/28/2023] [Indexed: 08/09/2023]
Abstract
BACKGROUND AND PURPOSE MR imaging provides information on the number and extend of focal lesions in multiple sclerosis (MS) patients. This study explores whether total brain T2 lesion volume or lesion number shows a better correlation with serum and cerebrospinal fluid (CSF) biomarkers of disease activity. MATERIALS AND METHODS In total, 52 patients suffering from clinically isolated syndrome (CIS)/relapsing-remitting multiple sclerosis (RRMS) were assessed including MRI markers (total brain T2 lesion volume semi-automatically outlined on 3D DIR/FLAIR sequences, number of lesions), serum and CSF biomarkers at the time of neuroimaging (neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP)), and clinical parameters. After log-transformation and partial correlations adjusted for the covariates patients' age, BMI, EDSS-score and diagnosis, the Fisher's r-to-Z transformation was used to compare different correlation coefficients. RESULTS The correlation between lesion volume and serum NfL (r = 0.6, p < 0.001) was stronger compared to the association between the number of T2 lesions and serum NfL (r = 0.4, p < 0.01) (z = -2.0, p < 0.05). With regard to CSF NfL, there was a moderate, positive relationship for both number of T2 lesions and lesion volume (r = 0.5 respectively, p < 0.01). We found no significant association between MRI markers and GFAP levels. CONCLUSION Our findings suggest that there is a stronger association between serum NfL and T2 lesion volume, than there is between serum NfL and T2 lesion number. Improving robustness and accuracy of fully-automated lesion volume segmentation tools can expedite implementation into clinical routine and trials.
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Affiliation(s)
- Katharina J Wenger
- Goethe University Frankfurt, University Hospital, Institute of Neuroradiology, Germany.
| | - Maya C Hoelter
- Goethe University Frankfurt, University Hospital, Institute of Neuroradiology, Germany
| | - Yavor Yalachkov
- Goethe University Frankfurt, University Hospital, Department of Neurology, Germany
| | - Jan Hendrik Schäfer
- Goethe University Frankfurt, University Hospital, Department of Neurology, Germany
| | - Dilek Özkan
- Goethe University Frankfurt, University Hospital, Institute of Neuroradiology, Germany
| | - Falk Steffen
- Department of Neurology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Stefan Bittner
- Department of Neurology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Elke Hattingen
- Goethe University Frankfurt, University Hospital, Institute of Neuroradiology, Germany
| | - Christian Foerch
- Goethe University Frankfurt, University Hospital, Department of Neurology, Germany
| | - Martin A Schaller-Paule
- Goethe University Frankfurt, University Hospital, Department of Neurology, Germany; Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
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13
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Mistri D, Cacciaguerra L, Valsasina P, Pagani E, Filippi M, Rocca MA. Cognitive function in primary and secondary progressive multiple sclerosis: A multiparametric magnetic resonance imaging study. Eur J Neurol 2023; 30:2801-2810. [PMID: 37246467 DOI: 10.1111/ene.15900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 05/08/2023] [Accepted: 05/25/2023] [Indexed: 05/30/2023]
Abstract
BACKGROUND AND PURPOSE The differences in cognitive function between primary progressive and secondary progressive multiple sclerosis (MS) remain unclear. We compared cognitive performance between primary progressive multiple sclerosis (PPMS) and secondary progressive multiple sclerosis (SPMS), and explored the structural and functional magnetic resonance imaging (MRI) correlates of their cognitive functions. METHODS Seventy-five healthy controls and 183 MS patients (60 PPMS and 123 SPMS) underwent 3.0-T MRI. MS patients were administered the Brief Repeatable Battery of Neuropsychological Tests; cognitive domain z-scores were calculated and then averaged to obtain a measure of global cognition. Using hierarchical linear regression analysis, the contribution of lesion volumes, normalized brain volumes, white matter (WM) fractional anisotropy (FA) and mean diffusivity abnormalities, and resting state (RS) functional connectivity (FC) alterations to global cognition in PPMS and SPMS was investigated. RESULTS PPMS and SPMS had similar z-scores in all investigated cognitive domains. Poor global cognitive function was associated with decreased FA of the medial lemniscus (ΔR 2 = 0.11, p = 0.011) and lower normalized gray matter volume (ΔR 2 = 0.29, p < 0.001) in PPMS, and with decreased FA of the fornix (ΔR 2 = 0.35, p < 0.001) and lower normalized WM volume (ΔR 2 = 0.05; p = 0.034) in SPMS. CONCLUSIONS PPMS and SPMS had similar neuropsychological performance. Cognitive dysfunction in PPMS and SPMS was related to distinct patterns of structural MRI abnormalities and involvement of different WM tracts, whereas RS FC alterations did not contribute to explaining their global cognitive functioning.
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Affiliation(s)
- Damiano Mistri
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Laura Cacciaguerra
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
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14
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Krijnen EA, Russo AW, Salim Karam E, Lee H, Chiang FL, Schoonheim MM, Huang SY, Klawiter EC. Detection of grey matter microstructural substrates of neurodegeneration in multiple sclerosis. Brain Commun 2023; 5:fcad153. [PMID: 37274832 PMCID: PMC10233898 DOI: 10.1093/braincomms/fcad153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/16/2023] [Accepted: 05/22/2023] [Indexed: 06/07/2023] Open
Abstract
Multiple sclerosis features complex pathological changes in grey matter that begin early and eventually lead to diffuse atrophy. Novel approaches to image grey-matter microstructural alterations in vivo are highly sought after and would enable more sensitive monitoring of disease activity and progression. This cross-sectional study aimed to assess the sensitivity of high-gradient diffusion MRI for microstructural tissue damage in cortical and deep grey matter in people with multiple sclerosis and test the hypothesis that reduced cortical cell body density is associated with cortical and deep grey-matter volume loss. Forty-one people with multiple sclerosis (age 24-72, 14 females) and 37 age- and sex-matched healthy controls were scanned on a 3 T Connectom MRI scanner equipped with 300 mT/m gradients using a multi-shell diffusion MRI protocol. The soma and neurite density imaging model was fitted to high-gradient diffusion MRI data to obtain estimates of intra-neurite, intra-cellular and extra-cellular signal fractions and apparent soma radius. Cortical and deep grey-matter microstructural imaging metrics were compared between multiple sclerosis and healthy controls and correlated with grey-matter volume, clinical disability and cognitive outcomes. People with multiple sclerosis showed significant cortical and deep grey-matter volume loss compared with healthy controls. People with multiple sclerosis showed trends towards lower cortical intra-cellular signal fraction and significantly lower intra-cellular and higher extra-cellular signal fractions in deep grey matter, especially the thalamus and caudate, compared with healthy controls. Changes were most pronounced in progressive disease and correlated with the Expanded Disability Status Scale, but not the Symbol Digit Modalities Test. In multiple sclerosis, normalized thalamic volume was associated with thalamic microstructural imaging metrics. Whereas thalamic volume loss did not correlate with cortical volume loss, cortical microstructural imaging metrics were significantly associated with thalamic volume, and not with cortical volume. Compared with the short diffusion time (Δ = 19 ms) achievable on the Connectom scanner, at the longer diffusion time of Δ = 49 ms attainable on clinical scanners, multiple sclerosis-related changes in imaging metrics were generally less apparent with lower effect sizes in cortical and deep grey matter. Soma and neurite density imaging metrics obtained from high-gradient diffusion MRI data provide detailed grey-matter characterization beyond cortical and thalamic volumes and distinguish multiple sclerosis-related microstructural pathology from healthy controls. Cortical cell body density correlates with thalamic volume, appears sensitive to the microstructural substrate of neurodegeneration and reflects disability status in people with multiple sclerosis, becoming more pronounced as disability worsens.
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Affiliation(s)
- Eva A Krijnen
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
| | - Andrew W Russo
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Elsa Salim Karam
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Hansol Lee
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Florence L Chiang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Menno M Schoonheim
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC location VUmc, 1081 HV Amsterdam, The Netherlands
| | - Susie Y Huang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Eric C Klawiter
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
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15
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Margoni M, Pagani E, Preziosa P, Gueye M, Azzimonti M, Rocca MA, Filippi M. Unraveling the heterogeneous pathological substrates of relapse-onset multiple sclerosis: a multiparametric voxel-wise 3 T MRI study. J Neurol 2023:10.1007/s00415-023-11736-9. [PMID: 37093395 DOI: 10.1007/s00415-023-11736-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/17/2023] [Accepted: 04/17/2023] [Indexed: 04/25/2023]
Abstract
BACKGROUND In multiple sclerosis (MS), pathological processes affecting brain gray (GM) and white matter (WM) are heterogeneous. OBJECTIVE To apply a multimodal MRI approach to investigate the regional distribution of the different pathological processes occurring in the brain WM and GM of relapse-onset MS patients. METHODS Fifty-seven MS patients (forty-two relapsing remitting [RR], fifteen secondary progressive [SP]) and forty-seven age- and sex-matched healthy controls (HC) underwent a multimodal 3 T MRI acquisition. Between-group voxel-wise differences of brain WM and GM volumes, magnetization transfer ratio (MTR), T1-weighted(w)/T2w ratio, intracellular volume fraction (ICV_f), and quantitative susceptibility mapping (QSM) maps were investigated. RESULTS Compared to HC, RRMS showed significant WM, deep GM and cortical atrophy, significantly lower MTR and T1w/T2w ratio of periventricular and infratentorial WM, deep GM and several cortical areas, lower ICV_f in supratentorial and cerebellar WM and in some cortical areas, and lower QSM values in bilateral periventricular WM (p < 0.001). Compared to RRMS, SPMS patients showed significant deep GM and widespread cortical atrophy, significantly lower MTR of periventricular WM, deep GM and cerebellum, lower T1w/T2w ratio of fronto-temporal WM regions, lower ICV_f of some fronto-tempo-occipital WM and cortical areas. They also had increased QSM and T1w/T2w ratio in the pallidum, bilaterally (p < 0.001). CONCLUSION A periventricular pattern of demyelination and widespread GM and WM neuro-axonal loss are detectable in RRMS and are more severe in SPMS. Higher T1w/T2w ratio and QSM in the pallidum, possibly reflecting iron accumulation and neurodegeneration, may represent a relevant MRI marker to differentiate SPMS from RRMS.
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Affiliation(s)
- Monica Margoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Mor Gueye
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Matteo Azzimonti
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.
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16
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Mado H, Adamczyk-Sowa M, Sowa P. Role of Microglial Cells in the Pathophysiology of MS: Synergistic or Antagonistic? Int J Mol Sci 2023; 24:ijms24031861. [PMID: 36768183 PMCID: PMC9916250 DOI: 10.3390/ijms24031861] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 01/05/2023] [Accepted: 01/13/2023] [Indexed: 01/19/2023] Open
Abstract
Many studies indicate an important role of microglia and their cytokines in the pathophysiology of multiple sclerosis (MS). Microglia are the macrophages of the central nervous system (CNS). They have many functions, such as being "controllers" of the CNS homeostasis in pathological and healthy conditions, playing a key role in the active immune defense of the CNS. Macroglia exhibit a dual role, depending on the phenotype they adopt. First, they can exhibit neurotoxic effects, which are harmful in the case of MS. However, they also show neuroprotective and regenerative effects in this disease. Many of the effects of microglia are mediated through the cytokines they secrete, which have either positive or negative properties. Neurotoxic and pro-inflammatory effects can be mediated by microglia via lipopolysaccharide and gamma interferon. On the other hand, the mediators of anti-inflammatory and protective effects secreted by microglia can be, for example, interleukin-4 and -13. Further investigation into the role of microglia in MS pathophysiology may perhaps lead to the discovery of new therapies for MS, as recent research in this area has been very promising.
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Affiliation(s)
- Hubert Mado
- Department of Neurology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, 40-055 Katowice, Poland
- Correspondence: ; Tel.: +48-695948463; Fax: +48-323704597
| | - Monika Adamczyk-Sowa
- Department of Neurology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, 40-055 Katowice, Poland
| | - Paweł Sowa
- Department of Otorhinolaryngology and Oncological Laryngology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, 40-055 Katowice, Poland
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17
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Margoni M, Pagani E, Preziosa P, Palombo M, Gueye M, Azzimonti M, Filippi M, Rocca MA. In vivo quantification of brain soma and neurite density abnormalities in multiple sclerosis. J Neurol 2023; 270:433-445. [PMID: 36153468 DOI: 10.1007/s00415-022-11386-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 09/12/2022] [Accepted: 09/13/2022] [Indexed: 01/07/2023]
Abstract
BACKGROUND Soma and neurite density imaging (SANDI) is a new biophysical model that incorporates soma in addition to neurite density, thus possibly providing more specific information about the complex pathological processes of multiple sclerosis (MS). PURPOSE To discriminate the pathological abnormalities of MS white matter (WM) lesions, normal-appearing (NA) WM and cortex and to evaluate the associations among SANDI-derived measures, clinical disability, and conventional MRI variables. METHODS Twenty healthy controls (HC) and 23 MS underwent a 3 T brain MRI. Using SANDI on diffusion-weighted sequence, the fractions of neurite (fneurite) and soma (fsoma) were assessed in WM lesions, NAWM, and cortex. RESULTS Compared to HC WM, MS NAWM showed lower fneurite (false discovery rate [FDR]-p = 0.011). In MS patients, WM lesions showed lower fneurite and fsoma compared to both HC and MS NAWM (FDR-p < 0.001 for all). In the cortex, MS patients had lower fneurite and fsoma compared to HC (FDR-p ≤ 0.009). Compared to both HC and RRMS, PMS patients had lower fneurite in NAWM (vs HC: FDR-p < 0.001; vs RRMS: FDR-p = 0.003) and cortex (vs HC: FDR-p < 0.001; vs RRMS: p = 0.031, not surviving FDR correction), and lower cortical fsoma (vs HC: FDR-p < 0.001; vs RRMS: FDR-p = 0.009). Compared to HC, PMS also showed a higher fsoma in NAWM (FDR-p = 0.015). Fneurite and fsoma in the different brain compartments were correlated with age, phenotype, disease duration, disability, WM lesion volumes, normalized brain, cortical, and WM volumes (r from - 0.761 to 0.821, FDR-p ≤ 0.4). CONCLUSIONS SANDI may represent a clinically relevant model to discriminate different neurodegenerative phenomena that gradually accumulate through MS disease course.
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Affiliation(s)
- Monica Margoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marco Palombo
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
- School of Computer Science and Informatics, Cardiff University, Cardiff, UK
| | - Mor Gueye
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Matteo Azzimonti
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Maria Assunta Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
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18
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Vandiver MS, Roy B, Mahmud F, Lavretsky H, Kumar R. Functional comorbidities and brain tissue changes before and after lung transplant in adults. Front Cell Neurosci 2022; 16:1015568. [DOI: 10.3389/fncel.2022.1015568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 11/17/2022] [Indexed: 12/03/2022] Open
Abstract
BackgroundAdults undergoing lung transplant, as a lifesaving treatment for end stage lung disease, exhibit high levels of peri-operative neurocognitive dysfunction in multiple domains, including delirium, cognition, and autonomic deficits. These complications impact healthcare costs, quality of life, and patient outcomes. Post-operative symptoms likely result from loss of brain tissue integrity in sites mediating such regulatory functions. Our aim in this study was to examine peri-operative neurocognitive dysfunction and brain tissue changes after lung transplant in adults.MethodsWe retrospectively examined the UCLA lung transplant database to identify 114 lung transplant patients with pre-operative clinical and neurocognitive data. Of 114 patients, 9 lung transplant patients had pre- and post-transplant brain magnetic resonance imaging. Clinical and neurocognitive data were summarized for all subjects, and brain tissue volume changes, using T1-weighted images, before and after transplant were examined. T1-weighted images were partitioned into gray matter (GM)-tissue type, normalized to a common space, smoothed, and the smoothed GM-volume maps were compared between pre- and post-transplant (paired t-tests; covariate, age; SPM12, p < 0.005).ResultsIncreased comorbidities, including the diabetes mellitus (DM), hypertension, kidney disease, and sleep disordered breathing, as well as higher rates of neurocognitive dysfunction were observed in the lung transplant patients, with 41% experiencing post-operative delirium, 49% diagnosed with a mood disorder, and 25% of patients diagnosed with cognitive deficits, despite incomplete documentation. Similarly, high levels of delirium, cognitive dysfunction, and mood disorder were noted in a subset of patients used for brain MRI evaluation. Significantly decreased GM volumes emerged in multiple brain regions, including the frontal and prefrontal, parietal, temporal, bilateral anterior cingulate and insula, putamen, and cerebellar cortices.ConclusionAdults undergoing lung transplant often show significant pre-operative comorbidities, including diabetes mellitus, hypertension, and chronic kidney disease, as well as neurocognitive dysfunction. In addition, patients with lung transplant show significant brain tissue changes in regions that mediate cognition, autonomic, and mood functions. The findings indicate a brain structural basis for many enhanced post-operative symptoms and suggest a need for brain tissue protection in adults undergoing lung transplant to improve health outcomes.
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Marzi C, d'Ambrosio A, Diciotti S, Bisecco A, Altieri M, Filippi M, Rocca MA, Storelli L, Pantano P, Tommasin S, Cortese R, De Stefano N, Tedeschi G, Gallo A. Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set. Hum Brain Mapp 2022; 44:186-202. [PMID: 36255155 PMCID: PMC9783441 DOI: 10.1002/hbm.26106] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 06/02/2022] [Accepted: 09/24/2022] [Indexed: 02/05/2023] Open
Abstract
Many patients with multiple sclerosis (MS) experience information processing speed (IPS) deficits, and the Symbol Digit Modalities Test (SDMT) has been recommended as a valid screening test. Magnetic resonance imaging (MRI) has markedly improved the understanding of the mechanisms associated with cognitive deficits in MS. However, which structural MRI markers are the most closely related to cognitive performance is still unclear. We used the multicenter 3T-MRI data set of the Italian Neuroimaging Network Initiative to extract multimodal data (i.e., demographic, clinical, neuropsychological, and structural MRIs) of 540 MS patients. We aimed to assess, through machine learning techniques, the contribution of brain MRI structural volumes in the prediction of IPS deficits when combined with demographic and clinical features. We trained and tested the eXtreme Gradient Boosting (XGBoost) model following a rigorous validation scheme to obtain reliable generalization performance. We carried out a classification and a regression task based on SDMT scores feeding each model with different combinations of features. For the classification task, the model trained with thalamus, cortical gray matter, hippocampus, and lesions volumes achieved an area under the receiver operating characteristic curve of 0.74. For the regression task, the model trained with cortical gray matter and thalamus volumes, EDSS, nucleus accumbens, lesions, and putamen volumes, and age reached a mean absolute error of 0.95. In conclusion, our results confirmed that damage to cortical gray matter and relevant deep and archaic gray matter structures, such as the thalamus and hippocampus, is among the most relevant predictors of cognitive performance in MS.
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Affiliation(s)
- Chiara Marzi
- MS Center and 3T‐MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS)University of Campania “Luigi Vanvitelli”NapoliItaly,Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi” – DEIAlma Mater Studiorum – University of BolognaBolognaItaly
| | - Alessandro d'Ambrosio
- MS Center and 3T‐MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS)University of Campania “Luigi Vanvitelli”NapoliItaly
| | - Stefano Diciotti
- Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi” – DEIAlma Mater Studiorum – University of BolognaBolognaItaly,Alma Mater Research Institute for Human‐Centered Artificial IntelligenceUniversity of BolognaBolognaItaly
| | - Alvino Bisecco
- MS Center and 3T‐MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS)University of Campania “Luigi Vanvitelli”NapoliItaly
| | - Manuela Altieri
- MS Center and 3T‐MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS)University of Campania “Luigi Vanvitelli”NapoliItaly,Department of PsychologyUniversity of Campania “Luigi Vanvitelli”NapoliItaly
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of NeuroscienceVita‐Salute San Raffaele University, IRCCS San Raffaele Scientific InstituteMilanItaly,Neurology and Neurophysiology UnitVita‐Salute San Raffaele University, IRCCS San Raffaele Scientific InstituteMilanItaly
| | - Maria Assunta Rocca
- Neuroimaging Research Unit, Division of NeuroscienceVita‐Salute San Raffaele University, IRCCS San Raffaele Scientific InstituteMilanItaly,Neurology and Neurophysiology UnitVita‐Salute San Raffaele University, IRCCS San Raffaele Scientific InstituteMilanItaly
| | - Loredana Storelli
- Neuroimaging Research Unit, Division of NeuroscienceVita‐Salute San Raffaele University, IRCCS San Raffaele Scientific InstituteMilanItaly
| | - Patrizia Pantano
- Department of Human NeurosciencesSapienza University of RomeRomeItaly,IRCCS NeuromedPozzilliItaly
| | - Silvia Tommasin
- Department of Human NeurosciencesSapienza University of RomeRomeItaly
| | - Rosa Cortese
- Department of Medicine, Surgery and NeuroscienceUniversity of SienaSienaItaly
| | - Nicola De Stefano
- Department of Medicine, Surgery and NeuroscienceUniversity of SienaSienaItaly
| | - Gioacchino Tedeschi
- MS Center and 3T‐MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS)University of Campania “Luigi Vanvitelli”NapoliItaly
| | - Antonio Gallo
- MS Center and 3T‐MRI Research Unit, Department of Advanced Medical and Surgical Sciences (DAMSS)University of Campania “Luigi Vanvitelli”NapoliItaly
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20
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Zejlon C, Nakhostin D, Winklhofer S, Pangalu A, Kulcsar Z, Lewandowski S, Finnsson J, Piehl F, Ingre C, Granberg T, Ineichen BV. Structural magnetic resonance imaging findings and histopathological correlations in motor neuron diseases—A systematic review and meta-analysis. Front Neurol 2022; 13:947347. [PMID: 36110394 PMCID: PMC9468579 DOI: 10.3389/fneur.2022.947347] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 07/08/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectivesThe lack of systematic evidence on neuroimaging findings in motor neuron diseases (MND) hampers the diagnostic utility of magnetic resonance imaging (MRI). Thus, we aimed at performing a systematic review and meta-analysis of MRI features in MND including their histopathological correlation.MethodsIn a comprehensive literature search, out of 5941 unique publications, 223 records assessing brain and spinal cord MRI findings in MND were eligible for a qualitative synthesis. 21 records were included in a random effect model meta-analysis.ResultsOur meta-analysis shows that both T2-hyperintensities along the corticospinal tracts (CST) and motor cortex T2*-hypointensitites, also called “motor band sign”, are more prevalent in ALS patients compared to controls [OR 2.21 (95%-CI: 1.40–3.49) and 10.85 (95%-CI: 3.74–31.44), respectively]. These two imaging findings correlate to focal axonal degeneration/myelin pallor or glial iron deposition on histopathology, respectively. Additionally, certain clinical MND phenotypes such as amyotrophic lateral sclerosis (ALS) seem to present with distinct CNS atrophy patterns.ConclusionsAlthough CST T2-hyperintensities and the “motor band sign” are non-specific imaging features, they can be leveraged for diagnostic workup of suspected MND cases, together with certain brain atrophy patterns. Collectively, this study provides high-grade evidence for the usefulness of MRI in the diagnostic workup of suspected MND cases.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42020182682.
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Affiliation(s)
- Charlotte Zejlon
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Dominik Nakhostin
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Sebastian Winklhofer
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Athina Pangalu
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | | | - Johannes Finnsson
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Fredrik Piehl
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center of Neurology, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Caroline Ingre
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Tobias Granberg
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Benjamin Victor Ineichen
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
- *Correspondence: Benjamin Victor Ineichen
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21
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Misin O, Matilainen M, Nylund M, Honkonen E, Rissanen E, Sucksdorff M, Airas L. Innate Immune Cell–Related Pathology in the Thalamus Signals a Risk for Disability Progression in Multiple Sclerosis. NEUROLOGY - NEUROIMMUNOLOGY NEUROINFLAMMATION 2022; 9:9/4/e1182. [PMID: 35581004 PMCID: PMC9128041 DOI: 10.1212/nxi.0000000000001182] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 03/17/2022] [Indexed: 11/16/2022]
Abstract
Background and Objectives Our aim was to investigate whether 18-kDa translocator protein (TSPO) radioligand binding in gray matter (GM) predicts later disability progression in multiple sclerosis (MS). Methods In this prospective imaging study, innate immune cells were investigated in the MS patient brain using PET imaging. The distribution volume ratio (DVR) of the TSPO-binding radioligand [11C]PK11195 was determined in 5 GM regions: thalamus, caudate, putamen, pallidum, and cortical GM. Volumetric brain MRI parameters were obtained for comparison. The Expanded Disability Status Scale (EDSS) score was assessed at baseline and after follow-up of 3.0 ± 0.3 (mean ± SD) years. Disability progression was defined as an EDSS score increase of 1.0 point or 0.5 point if the baseline EDSS score was ≥6.0. A forward-type stepwise logistic regression model was constructed to compare multiple imaging and clinical variables in their ability to predict later disability progression. Results The cohort consisted of 66 patients with MS and 18 healthy controls. Patients with later disability progression (n = 17) had more advanced atrophy in the thalamus, caudate, and putamen at baseline compared with patients with no subsequent worsening. TSPO binding was significantly higher in the thalamus among the patients with later worsening. The thalamic DVR was the only measured imaging variable that remained a significant predictor of disability progression in the regression model. The final model predicted disability progression with 52.9% sensitivity and 93.9% specificity with an area under the curve value of 0.82 (receiver operating characteristic curve). Discussion Increased TSPO radioligand binding in the thalamus has potential in predicting short-term disability progression in MS and seems to be more sensitive for this than GM atrophy measures.
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22
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Maarouf A, Audoin B, Gherib S, El Mendili MM, Viout P, Pariollaud F, Boutière C, Rico A, Guye M, Ranjeva JP, Zaaraoui W, Pelletier J. Grey-matter sodium concentration as an individual marker of multiple sclerosis severity. Mult Scler 2022; 28:1903-1912. [PMID: 35723278 DOI: 10.1177/13524585221102587] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
OBJECTIVE Quantification of brain injury in patients with variable disability despite similar disease duration may be relevant to identify the mechanisms underlying disability in multiple sclerosis (MS). We aimed to compare grey-matter sodium abnormalities (GMSAs), a parameter reflecting neuronal and astrocyte dysfunction, in MS patients with benign multiple sclerosis (BMS) and non-benign multiple sclerosis (NBMS). METHODS We identified never-treated BMS patients in our local MS database of 1352 patients. A group with NBMS was identified with same disease duration. All participants underwent 23Na magnetic resonance imaging (MRI). The existence of GMSA was detected by statistical analysis. RESULTS In total, 102 individuals were included (21 BMS, 25 NBMS and 56 controls). GMSA was detected in 10 BMS and 19 NBMS (11/16 relapsing-remitting multiple sclerosis (RRMS) and 8/9 secondary progressive multiple sclerosis (SPMS) patients) (p = 0.05). On logistic regression including the presence or absence of GMSA, thalamic volume, cortical grey-matter volume and T2-weighted lesion load, thalamic volume was independently associated with BMS status (odds ratio (OR) = 0.64 for each unit). Nonetheless, the absence of GMSA was independently associated when excluding patients with significant cognitive alteration (n = 7) from the BMS group (OR = 4.6). CONCLUSION Detection of GMSA in individuals and thalamic volume are promising to differentiate BMS from NBMS as compared with cortical or whole grey-matter atrophy and T2-weighted lesions.
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Affiliation(s)
- Adil Maarouf
- Aix-Marseille Université, CNRS, CRMBM, Marseille, France/APHM, Hôpital de la Timone, Pôle de Neurosciences Cliniques, Service de Neurologie, Marseille, France
| | - Bertrand Audoin
- Aix-Marseille Université, CNRS, CRMBM, Marseille, France/APHM, Hôpital de la Timone, Pôle de Neurosciences Cliniques, Service de Neurologie, Marseille, France
| | - Soraya Gherib
- Aix-Marseille Université, CNRS, CRMBM, Marseille, France
| | | | - Patrick Viout
- Aix-Marseille Université, CNRS, CRMBM, Marseille, France
| | | | - Clémence Boutière
- APHM, Hôpital de la Timone, Pôle de Neurosciences Cliniques, Service de Neurologie, Marseille, France
| | - Audrey Rico
- Aix-Marseille Université, CNRS, CRMBM, Marseille, France/APHM, Hôpital de la Timone, Pôle de Neurosciences Cliniques, Service de Neurologie, Marseille, France
| | - Maxime Guye
- Aix-Marseille Université, CNRS, CRMBM, Marseille, France/APHM, Hôpital de la Timone, CEMEREM, Marseille, France
| | | | - Wafaa Zaaraoui
- Aix-Marseille Université, CNRS, CRMBM, Marseille, France
| | - Jean Pelletier
- Aix-Marseille Université, CNRS, CRMBM, Marseille, France/APHM, Hôpital de la Timone, Pôle de Neurosciences Cliniques, Service de Neurologie, Marseille, France
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23
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Bells S, Longoni G, Berenbaum T, de Medeiros CB, Narayanan S, Banwell BL, Arnold DL, Mabbott DJ, Ann Yeh E. Patterns of white and gray structural abnormality associated with paediatric demyelinating disorders. Neuroimage Clin 2022; 34:103001. [PMID: 35381508 PMCID: PMC8980471 DOI: 10.1016/j.nicl.2022.103001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/21/2022] [Accepted: 03/30/2022] [Indexed: 11/26/2022]
Abstract
A multi-modal approach was used to evaluate the visual pathway from anterior (retina) to posterior (visual cortex) in both paediatric MOGAD and MS patients. MS patients exhibited more widespread white matter abnormalities; MOGAD patients exhibited white matter changes primarily within the optic radiation. The pattern of cortical thinning differed in MS and MOGAD patients. Reduced RNFLT was associated with lower axonal density in MOGAD and tortuosity in MS.
The impact of multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein (MOG) - associated disorders (MOGAD) on brain structure in youth remains poorly understood. Reductions in cortical mantle thickness on structural MRI and abnormal diffusion-based white matter metrics (e.g., diffusion tensor parameters) have been well documented in MS but not in MOGAD. Characterizing structural abnormalities found in children with these disorders can help clarify the differences and similarities in their impact on neuroanatomy. Importantly, while MS and MOGAD affect the entire CNS, the visual pathway is of particular interest in both groups, as most patients have evidence for clinical or subclinical involvement of the anterior visual pathway. Thus, the visual pathway is of key interest in analyses of structural abnormalities in these disorders and may distinguish MOGAD from MS patients. In this study we collected MRI data on 18 MS patients, 14 MOGAD patients and 26 age- and sex-matched typically developing children (TDC). Full-brain group differences in fixel diffusion measures (fibre-bundle populations) and cortical thickness measures were tested using age and sex as covariates. Visual pathway analysis was performed by extracting mean diffusion measures within lesion free optic radiations, cortical thickness within the visual cortex, and retinal nerve fibre layer (RNFL) and ganglion cell layer thickness measures from optical coherence tomography (OCT). Fixel based analysis (FBA) revealed MS patients have widespread abnormal white matter within the corticospinal tract, inferior longitudinal fasciculus, and optic radiations, while within MOGAD patients, non-lesional impact on white matter was found primarily in the right optic radiation. Cortical thickness measures were reduced predominately in the temporal and parietal lobes in MS patients and in frontal, cingulate and visual cortices in MOGAD patients. Additionally, our findings of associations between reduced RNFLT and axonal density in MOGAD and TORT in MS patients in the optic radiations imply widespread axonal and myelin damage in the visual pathway, respectively. Overall, our approach of combining FBA, cortical thickness and OCT measures has helped evaluate similarities and differences in brain structure in MS and MOGAD patients in comparison to TDC.
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Affiliation(s)
- Sonya Bells
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Pediatric Neurology, Spectrum Health Helen Devos Children's Hospital, Grand Rapids, USA; Department of Pediatrics and Human Development, Michigan State University, East Lansing, USA
| | - Giulia Longoni
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Department of Neurology, Hospital for Sick Children, Toronto, Canada; Department of Paediatrics, University of Toronto, Toronto, Canada
| | - Tara Berenbaum
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada
| | - Cynthia B de Medeiros
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada
| | - Sridar Narayanan
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Brenda L Banwell
- Division of Child Neurology, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, USA
| | - Douglas L Arnold
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Donald J Mabbott
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Department of Psychology, University of Toronto, Toronto, Canada
| | - E Ann Yeh
- Neurosciences and Mental Health Program, Research Institute, Hospital for Sick Children, Toronto, Canada; Department of Neurology, Hospital for Sick Children, Toronto, Canada; Department of Paediatrics, University of Toronto, Toronto, Canada.
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24
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Li J, Liu B, Banaschewski T, Bokde ALW, Quinlan EB, Desrivières S, Flor H, Frouin V, Garavan H, Gowland P, Heinz A, Ittermann B, Martinot JL, Artiges E, Nees F, Papadopoulos Orfanos D, Paus T, Poustka L, Hohmann S, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Jiang T. Orbitofrontal cortex volume links polygenic risk for smoking with tobacco use in healthy adolescents. Psychol Med 2022; 52:1175-1182. [PMID: 32878661 DOI: 10.1017/s0033291720002962] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Tobacco smoking remains one of the leading causes of preventable illness and death and is heritable with complex underpinnings. Converging evidence suggests a contribution of the polygenic risk for smoking to the use of tobacco and other substances. Yet, the underlying brain mechanisms between the genetic risk and tobacco smoking remain poorly understood. METHODS Genomic, neuroimaging, and self-report data were acquired from a large cohort of adolescents from the IMAGEN study (a European multicenter study). Polygenic risk scores (PGRS) for smoking were calculated based on a genome-wide association study meta-analysis conducted by the Tobacco and Genetics Consortium. We examined the interrelationships among the genetic risk for smoking initiation, brain structure, and the number of occasions of tobacco use. RESULTS A higher smoking PGRS was significantly associated with both an increased number of occasions of tobacco use and smaller cortical volume of the right orbitofrontal cortex (OFC). Furthermore, reduced cortical volume within this cluster correlated with greater tobacco use. A subsequent path analysis suggested that the cortical volume within this cluster partially mediated the association between the genetic risk for smoking and the number of occasions of tobacco use. CONCLUSIONS Our data provide the first evidence for the involvement of the OFC in the relationship between smoking PGRS and tobacco use. Future studies of the molecular mechanisms underlying tobacco smoking should consider the mediation effect of the related neural structure.
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Affiliation(s)
- Jin Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
| | - Bing Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- University of Chinese Academy of Sciences, 19 Yuquan Road, Beijing, 100049, China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Erin Burke Quinlan
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany
| | - Vincent Frouin
- NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, Vermont, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 'Neuroimaging & Psychiatry', University Paris-Saclay, University Paris Descartes - Sorbonne Paris Cité; and Maison de Solenn, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 'Neuroimaging & Psychiatry', University Paris-Saclay, University Paris Descartes - Sorbonne Paris Cité; and Psychiatry Department 91G16, Orsay Hospital, Orsay, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | | | - Tomáš Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, M6A 2E1, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
- PONS Research Group, Department of Psychiatry and Psychotherapy, Campus Charite Mitte, Humboldt University, Berlin, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, P.R. China
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- University of Chinese Academy of Sciences, 19 Yuquan Road, Beijing, 100049, China
- The Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
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25
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Williams TE, Holdsworth KP, Nicholas JM, Eshaghi A, Katsanouli T, Wellington H, Heslegrave A, Zetterberg H, Frost C, Chataway J. Assessing Neurofilaments as Biomarkers of Neuroprotection in Progressive Multiple Sclerosis: From the MS-STAT Randomized Controlled Trial. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2022; 9:9/2/e1130. [PMID: 35031587 PMCID: PMC8759719 DOI: 10.1212/nxi.0000000000001130] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 11/23/2021] [Indexed: 01/10/2023]
Abstract
Background and Objectives Improved biomarkers of neuroprotective treatment are needed in progressive multiple sclerosis (PMS) to facilitate more efficient phase 2 trial design. The MS-STAT randomized controlled trial supported the neuroprotective potential of high-dose simvastatin in secondary progressive MS (SPMS). Here, we analyze serum from the MS-STAT trial to assess the extent to which neurofilament light (NfL) and neurofilament heavy (NfH), both promising biomarkers of neuroaxonal injury, may act as biomarkers of simvastatin treatment in SPMS. Methods The MS-STAT trial randomized patients to 80 mg simvastatin or placebo. Serum was analyzed for NfL and NfH using Simoa technology. We used linear mixed models to investigate the treatment effects of simvastatin compared with placebo on NfL and NfH. Additional models examined the relationships between neurofilaments and MRI and clinical measures of disease severity. Results A total of 140 patients with SPMS were included. There was no evidence for a simvastatin treatment effect on NfL or NfH: compared with placebo, NfL was 1.2% lower (95% CI 10.6% lower to 9.2% higher; p = 0.820) and NfH was 0.4% lower (95% CI 18.4% lower to 21.6% higher; p = 0.969) in the simvastatin treatment group. Secondary analyses suggested that higher NfL was associated with greater subsequent whole brain atrophy, higher T2 lesion volume, and more new/enlarging T2 lesions in the previous 12 months, as well as greater physical disability. There were no significant associations between NfH and MRI or clinical variables. Discussion We found no evidence of a simvastatin treatment effect on serum neurofilaments. While confirmation of the neuroprotective benefits of simvastatin is awaited from the ongoing phase 3 study (NCT03387670), our results suggest that treatments capable of slowing the rate of whole brain atrophy in SPMS, such as simvastatin, may act via mechanisms largely independent of neuroaxonal injury, as quantified by NfL. This has important implications for the design of future phase 2 clinical trials in PMS. Trial Registration Information MS-STAT: NCT00647348. Classification of Evidence This study provides class I evidence that simvastatin treatment does not have a large impact on either serum NfL or NfH, as quantified in this study, in SPMS.
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Affiliation(s)
- Thomas E Williams
- From the Queen Square Multiple Sclerosis Centre (T.E.W., A.E., J.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London; National Hospital of Neurology and Neurosurgery (T.E.W., J.C.), London; London School of Hygiene and Tropical Medicine (K.P.H., J.M.N., T.K., C.F.); and UK Dementia Research Institute at UCL (H.W., A.H., H.Z.), United Kingdom.
| | - Katherine P Holdsworth
- From the Queen Square Multiple Sclerosis Centre (T.E.W., A.E., J.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London; National Hospital of Neurology and Neurosurgery (T.E.W., J.C.), London; London School of Hygiene and Tropical Medicine (K.P.H., J.M.N., T.K., C.F.); and UK Dementia Research Institute at UCL (H.W., A.H., H.Z.), United Kingdom
| | - Jennifer M Nicholas
- From the Queen Square Multiple Sclerosis Centre (T.E.W., A.E., J.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London; National Hospital of Neurology and Neurosurgery (T.E.W., J.C.), London; London School of Hygiene and Tropical Medicine (K.P.H., J.M.N., T.K., C.F.); and UK Dementia Research Institute at UCL (H.W., A.H., H.Z.), United Kingdom
| | - Arman Eshaghi
- From the Queen Square Multiple Sclerosis Centre (T.E.W., A.E., J.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London; National Hospital of Neurology and Neurosurgery (T.E.W., J.C.), London; London School of Hygiene and Tropical Medicine (K.P.H., J.M.N., T.K., C.F.); and UK Dementia Research Institute at UCL (H.W., A.H., H.Z.), United Kingdom
| | - Theodora Katsanouli
- From the Queen Square Multiple Sclerosis Centre (T.E.W., A.E., J.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London; National Hospital of Neurology and Neurosurgery (T.E.W., J.C.), London; London School of Hygiene and Tropical Medicine (K.P.H., J.M.N., T.K., C.F.); and UK Dementia Research Institute at UCL (H.W., A.H., H.Z.), United Kingdom
| | - Henrietta Wellington
- From the Queen Square Multiple Sclerosis Centre (T.E.W., A.E., J.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London; National Hospital of Neurology and Neurosurgery (T.E.W., J.C.), London; London School of Hygiene and Tropical Medicine (K.P.H., J.M.N., T.K., C.F.); and UK Dementia Research Institute at UCL (H.W., A.H., H.Z.), United Kingdom
| | - Amanda Heslegrave
- From the Queen Square Multiple Sclerosis Centre (T.E.W., A.E., J.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London; National Hospital of Neurology and Neurosurgery (T.E.W., J.C.), London; London School of Hygiene and Tropical Medicine (K.P.H., J.M.N., T.K., C.F.); and UK Dementia Research Institute at UCL (H.W., A.H., H.Z.), United Kingdom
| | - Henrik Zetterberg
- From the Queen Square Multiple Sclerosis Centre (T.E.W., A.E., J.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London; National Hospital of Neurology and Neurosurgery (T.E.W., J.C.), London; London School of Hygiene and Tropical Medicine (K.P.H., J.M.N., T.K., C.F.); and UK Dementia Research Institute at UCL (H.W., A.H., H.Z.), United Kingdom
| | - Chris Frost
- From the Queen Square Multiple Sclerosis Centre (T.E.W., A.E., J.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London; National Hospital of Neurology and Neurosurgery (T.E.W., J.C.), London; London School of Hygiene and Tropical Medicine (K.P.H., J.M.N., T.K., C.F.); and UK Dementia Research Institute at UCL (H.W., A.H., H.Z.), United Kingdom
| | - Jeremy Chataway
- From the Queen Square Multiple Sclerosis Centre (T.E.W., A.E., J.C.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London; National Hospital of Neurology and Neurosurgery (T.E.W., J.C.), London; London School of Hygiene and Tropical Medicine (K.P.H., J.M.N., T.K., C.F.); and UK Dementia Research Institute at UCL (H.W., A.H., H.Z.), United Kingdom
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26
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Lie IA, Weeda MM, Mattiesing RM, Mol MAE, Pouwels PJW, Barkhof F, Torkildsen Ø, Bø L, Myhr KM, Vrenken H. Relationship Between White Matter Lesions and Gray Matter Atrophy in Multiple Sclerosis: A Systematic Review. Neurology 2022; 98:e1562-e1573. [PMID: 35173016 PMCID: PMC9038199 DOI: 10.1212/wnl.0000000000200006] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 01/03/2022] [Indexed: 11/20/2022] Open
Abstract
Background and Objectives There is currently no consensus about the extent of gray matter (GM) atrophy that can be attributed to secondary changes after white matter (WM) lesions or the temporal and spatial relationships between the 2 phenomena. Elucidating this interplay will broaden the understanding of the combined inflammatory and neurodegenerative pathophysiology of multiple sclerosis (MS), and separating atrophic changes due to primary and secondary neurodegenerative mechanisms will then be pivotal to properly evaluate treatment effects, especially if these treatments target the different processes individually. To untangle these complex pathologic mechanisms, this systematic review provides an essential first step: an objective and comprehensive overview of the existing in vivo knowledge of the relationship between brain WM lesions and GM atrophy in patients diagnosed with MS. The overall aim was to clarify the extent to which WM lesions are associated with both global and regional GM atrophy and how this may differ in the different disease subtypes. Methods We searched MEDLINE (through PubMed) and Embase for reports containing direct associations between brain GM and WM lesion measures obtained by conventional MRI sequences in patients with clinically isolated syndrome and MS. No restriction was applied for publication date. The quality and risk of bias in included studies were evaluated with the Quality Assessment Tool for observational cohort and cross-sectional studies (NIH, Bethesda, MA). Qualitative and descriptive analyses were performed. Results A total of 90 articles were included. WM lesion volumes were related mostly to global, cortical and deep GM volumes, and those significant associations were almost without exception negative, indicating that higher WM lesion volumes were associated with lower GM volumes or lower cortical thicknesses. The most consistent relationship between WM lesions and GM atrophy was seen in early (relapsing) disease and less so in progressive MS. Discussion The findings suggest that GM neurodegeneration is mostly secondary to damage in the WM during early disease stages while becoming more detached and dominated by other, possibly primary neurodegenerative disease mechanisms in progressive MS.
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Affiliation(s)
- Ingrid Anne Lie
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Merlin M Weeda
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Rozemarijn M Mattiesing
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Marijke A E Mol
- Medical Library, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Petra J W Pouwels
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, UCL London, London, UK
| | - Øivind Torkildsen
- Department of Clinical Medicine, University of Bergen, Bergen, Norway.,Neuro-SysMed, Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Lars Bø
- Department of Clinical Medicine, University of Bergen, Bergen, Norway.,Norwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Kjell-Morten Myhr
- Department of Clinical Medicine, University of Bergen, Bergen, Norway.,Neuro-SysMed, Department of Neurology, Haukeland University Hospital, Bergen, Norway
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
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27
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The effect of gadolinium-based contrast-agents on automated brain atrophy measurements by FreeSurfer in patients with multiple sclerosis. Eur Radiol 2022; 32:3576-3587. [PMID: 34978580 PMCID: PMC9038813 DOI: 10.1007/s00330-021-08405-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 09/07/2021] [Accepted: 10/12/2021] [Indexed: 12/12/2022]
Abstract
OBJECTIVE To determine whether reliable brain atrophy measures can be obtained from post-contrast 3D T1-weighted images in patients with multiple sclerosis (MS) using FreeSurfer. METHODS Twenty-two patients with MS were included, in which 3D T1-weighted MR images were obtained during the same scanner visit, with the same acquisition protocol, before and after administration of gadolinium-based contrast agents (GBCAs). Two FreeSurfer versions (v.6.0.1 and v.7.1.1.) were applied to calculate grey matter (GM) and white matter (WM) volumes and global and regional cortical thickness. The consistency between measures obtained in pre- and post-contrast images was assessed by intra-class correlation coefficient (ICC), the difference was investigated by paired t-tests, and the mean percentage increase or decrease was calculated for total WM and GM matter volume, total deep GM and thalamus volume, and mean cortical thickness. RESULTS Good to excellent reliability was found between all investigated measures, with ICC ranging from 0.926 to 0.996, all p values < 0.001. GM volumes and cortical thickness measurements were significantly higher in post-contrast images by 3.1 to 17.4%, while total WM volume decreased significantly by 1.7% (all p values < 0.001). CONCLUSION The consistency between values obtained from pre- and post-contrast images was excellent, suggesting it may be possible to extract reliable brain atrophy measurements from T1-weighted images acquired after administration of GBCAs, using FreeSurfer. However, absolute values were systematically different between pre- and post-contrast images, meaning that such images should not be compared directly. Potential systematic effects, possibly dependent on GBCA dose or the delay time after contrast injection, should be investigated. TRIAL REGISTRATION Clinical trials.gov. identifier: NCT00360906. KEY POINTS • The influence of gadolinium-based contrast agents (GBCAs) on atrophy measurements is still largely unknown and challenges the use of a considerable source of historical and prospective real-world data. • In 22 patients with multiple sclerosis, the consistency between brain atrophy measurements obtained from pre- and post-contrast images was excellent, suggesting it may be possible to extract reliable atrophy measurements in T1-weighted images acquired after administration of GBCAs, using FreeSurfer. • Absolute values were systematically different between pre- and post-contrast images, meaning that such images should not be compared directly, and measurements extracted from certain regions (e.g., the temporal pole) should be interpreted with caution.
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28
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Age-related changes in multiple sclerosis and experimental autoimmune encephalomyelitis. Semin Immunol 2022; 59:101631. [PMID: 35752572 DOI: 10.1016/j.smim.2022.101631] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 06/03/2022] [Accepted: 06/13/2022] [Indexed: 01/15/2023]
Abstract
A better understanding of the pathological mechanisms that drive neurodegeneration in people living with multiple sclerosis (MS) is needed to design effective therapies to treat and/or prevent disease progression. We propose that CNS-intrinsic inflammation and re-modelling of the sub-arachnoid space of the leptomeninges sets the stage for neurodegeneration from the earliest stages of MS. While neurodegenerative processes are clinically silent early in disease, ageing results in neurodegenerative changes that become clinically manifest as progressive disability. Here we review pathological correlates of MS disease progression, highlight emerging mouse models that mimic key progressive changes in MS, and provide new perspectives on therapeutic approaches to protect against MS-associated neurodegeneration.
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29
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Complement-associated loss of CA2 inhibitory synapses in the demyelinated hippocampus impairs memory. Acta Neuropathol 2021; 142:643-667. [PMID: 34170374 PMCID: PMC8423657 DOI: 10.1007/s00401-021-02338-8] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 06/03/2021] [Accepted: 06/14/2021] [Indexed: 12/27/2022]
Abstract
The complement system is implicated in synapse loss in the MS hippocampus, but the functional consequences of synapse loss remain poorly understood. Here, in post-mortem MS hippocampi with demyelination we find that deposits of the complement component C1q are enriched in the CA2 subfield, are linked to loss of inhibitory synapses and are significantly higher in MS patients with cognitive impairments compared to those with preserved cognitive functions. Using the cuprizone mouse model of demyelination, we corroborated that C1q deposits are highest within the demyelinated dorsal hippocampal CA2 pyramidal layer and co-localized with inhibitory synapses engulfed by microglia/macrophages. In agreement with the loss of inhibitory perisomatic synapses, we found that Schaffer collateral feedforward inhibition but not excitation was impaired in CA2 pyramidal neurons and accompanied by intrinsic changes and a reduced spike output. Finally, consistent with excitability deficits, we show that cuprizone-treated mice exhibit impaired encoding of social memories. Together, our findings identify CA2 as a critical circuit in demyelinated intrahippocampal lesions and memory dysfunctions in MS.
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30
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Bussas M, Grahl S, Pongratz V, Berthele A, Gasperi C, Andlauer T, Gaser C, Kirschke JS, Wiestler B, Zimmer C, Hemmer B, Mühlau M. Gray matter atrophy in relapsing-remitting multiple sclerosis is associated with white matter lesions in connecting fibers. Mult Scler 2021; 28:900-909. [PMID: 34591698 PMCID: PMC9024016 DOI: 10.1177/13524585211044957] [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] [Indexed: 11/16/2022]
Abstract
Background: Lesions of brain white matter (WM) and atrophy of brain gray matter (GM) are well-established surrogate parameters in multiple sclerosis (MS), but it is unclear how closely these parameters relate to each other. Objective: To assess across the whole cerebrum whether GM atrophy can be explained by lesions in connecting WM tracts. Methods: GM images of 600 patients with relapsing-remitting MS (women = 68%; median age = 33.0 years, median expanded disability status scale score = 1.5) were converted to atrophy maps by data from a healthy control cohort. An atlas of WM tracts from the Human Connectome Project and individual lesion maps were merged to identify potentially disconnected GM regions, leading to individual disconnectome maps. Across the whole cerebrum, GM atrophy and potentially disconnected GM were tested for association both cross-sectionally and longitudinally. Results: We found highly significant correlations between disconnection and atrophy across most of the cerebrum. Longitudinal analysis demonstrated a close temporal relation of WM lesion formation and GM atrophy in connecting fibers. Conclusion: GM atrophy is associated with WM lesions in connecting fibers. Caution is warranted when interpreting group differences in GM atrophy exclusively as differences in early neurodegeneration independent of WM lesion formation.
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Affiliation(s)
- Matthias Bussas
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Sophia Grahl
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Viola Pongratz
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Achim Berthele
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christiane Gasperi
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Till Andlauer
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Gaser
- Department of Psychiatry and Department of Neurology, Jena University Hospital, Jena, Germany
| | - Jan S Kirschke
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Bernhard Hemmer
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Mark Mühlau
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany/TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
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31
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Tsouki F, Williams A. Multifaceted involvement of microglia in gray matter pathology in multiple sclerosis. Stem Cells 2021; 39:993-1007. [PMID: 33754376 DOI: 10.1002/stem.3374] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 03/01/2021] [Indexed: 06/12/2023]
Abstract
In the inflammatory demyelinating neurodegenerative disease multiple sclerosis (MS), there is increasing interest in gray matter pathology, as neuronal loss and cortical atrophy correlate with disability and disease progression, and MS therapeutics fail to significantly slow or stop neurodegeneration. Microglia, the central nervous system (CNS)-resident macrophages, are extensively involved in white matter MS pathology, but are also implicated in gray matter pathology, similar to other neurodegenerative diseases, for which there is synaptic, axonal, and neuronal degeneration. Microglia display regional heterogeneity within the CNS, which reflects their highly plastic nature and their ability to deliver context-dependent responses tailored to the demands of their microenvironment. Therefore, microglial roles in the MS gray matter in part reflect and in part diverge from those in the white matter. The present review summarizes current knowledge of microglial involvement in gray matter changes in MS, in demyelination, synaptic damage, and neurodegeneration, with evidence implicating microglia in pathology, neuroprotection, and repair. As our understanding of microglial physiology and pathophysiology increases, we describe how we are moving toward potential therapeutic applications in MS, harnessing microglia to protect and regenerate the CNS.
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Affiliation(s)
- Foteini Tsouki
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, The University of Edinburgh, Edinburgh BioQuarter, Edinburgh, UK
| | - Anna Williams
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, The University of Edinburgh, Edinburgh BioQuarter, Edinburgh, UK
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32
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van Olst L, Rodriguez-Mogeda C, Picon C, Kiljan S, James RE, Kamermans A, van der Pol SMA, Knoop L, Michailidou I, Drost E, Franssen M, Schenk GJ, Geurts JJG, Amor S, Mazarakis ND, van Horssen J, de Vries HE, Reynolds R, Witte ME. Meningeal inflammation in multiple sclerosis induces phenotypic changes in cortical microglia that differentially associate with neurodegeneration. Acta Neuropathol 2021; 141:881-899. [PMID: 33779783 PMCID: PMC8113309 DOI: 10.1007/s00401-021-02293-4] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 02/15/2021] [Accepted: 03/03/2021] [Indexed: 12/21/2022]
Abstract
Meningeal inflammation strongly associates with demyelination and neuronal loss in the underlying cortex of progressive MS patients, thereby contributing significantly to clinical disability. However, the pathological mechanisms of meningeal inflammation-induced cortical pathology are still largely elusive. By extensive analysis of cortical microglia in post-mortem progressive MS tissue, we identified cortical areas with two MS-specific microglial populations, termed MS1 and MS2 cortex. The microglial population in MS1 cortex was characterized by a higher density and increased expression of the activation markers HLA class II and CD68, whereas microglia in MS2 cortex showed increased morphological complexity and loss of P2Y12 and TMEM119 expression. Interestingly, both populations associated with inflammation of the overlying meninges and were time-dependently replicated in an in vivo rat model for progressive MS-like chronic meningeal inflammation. In this recently developed animal model, cortical microglia at 1-month post-induction of experimental meningeal inflammation resembled microglia in MS1 cortex, and microglia at 2 months post-induction acquired a MS2-like phenotype. Furthermore, we observed that MS1 microglia in both MS cortex and the animal model were found closely apposing neuronal cell bodies and to mediate pre-synaptic displacement and phagocytosis, which coincided with a relative sparing of neurons. In contrast, microglia in MS2 cortex were not involved in these synaptic alterations, but instead associated with substantial neuronal loss. Taken together, our results show that in response to meningeal inflammation, microglia acquire two distinct phenotypes that differentially associate with neurodegeneration in the progressive MS cortex. Furthermore, our in vivo data suggests that microglia initially protect neurons from meningeal inflammation-induced cell death by removing pre-synapses from the neuronal soma, but eventually lose these protective properties contributing to neuronal loss.
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Affiliation(s)
- Lynn van Olst
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Carla Rodriguez-Mogeda
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Carmen Picon
- Division of Neuroscience, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK
| | - Svenja Kiljan
- Department of Anatomy and Neurosciences, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Rachel E James
- Division of Neuroscience, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK
| | - Alwin Kamermans
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Susanne M A van der Pol
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Lydian Knoop
- Department of Pathology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Iliana Michailidou
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Evelien Drost
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Marc Franssen
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Geert J Schenk
- Department of Anatomy and Neurosciences, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Sandra Amor
- Department of Pathology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Nicholas D Mazarakis
- Division of Neuroscience, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK
| | - Jack van Horssen
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Helga E de Vries
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
- Department of Medical Biochemistry, Amsterdam UMC, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
| | - Richard Reynolds
- Division of Neuroscience, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK.
- Centre for Molecular Neuropathology, LKC School of Medicine, Nanyang Technological University, Singapore, Singapore.
| | - Maarten E Witte
- Department of Molecular Cell Biology and Immunology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands.
- Department of Pathology, Amsterdam UMC, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands.
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Ferreira-Atuesta C, Reyes S, Giovanonni G, Gnanapavan S. The Evolution of Neurofilament Light Chain in Multiple Sclerosis. Front Neurosci 2021; 15:642384. [PMID: 33889068 PMCID: PMC8055958 DOI: 10.3389/fnins.2021.642384] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 03/17/2021] [Indexed: 12/18/2022] Open
Abstract
Multiple sclerosis (MS) is an autoimmune, inflammatory neurodegenerative disease of the central nervous system characterized by demyelination and axonal damage. Diagnosis and prognosis are mainly assessed through clinical examination and neuroimaging. However, more sensitive biomarkers are needed to measure disease activity and guide treatment decisions in MS. Prompt and individualized management can reduce inflammatory activity and delay disease progression. Neurofilament Light chain (NfL), a neuron-specific cytoskeletal protein that is released into the extracellular fluid following axonal injury, has been identified as a biomarker of disease activity in MS. Measurement of NfL levels can capture the extent of neuroaxonal damage, especially in early stages of the disease. A growing body of evidence has shown that NfL in cerebrospinal fluid (CSF) and serum can be used as reliable indicators of prognosis and treatment response. More recently, NfL has been shown to facilitate individualized treatment decisions for individuals with MS. In this review, we discuss the characteristics that make NfL a highly informative biomarker and depict the available technologies used for its measurement. We further discuss the growing role of serum and CSF NfL in MS research and clinical settings. Finally, we address some of the current topics of debate regarding the use of NfL in clinical practice and examine the possible directions that this biomarker may take in the future.
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Affiliation(s)
- Carolina Ferreira-Atuesta
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.,Department of Neurology, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - Saúl Reyes
- Department of Neurology, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia.,The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Gavin Giovanonni
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.,Department of Neurology, The Royal London Hospital, Barts Health NHS Trust, London, United Kingdom
| | - Sharmilee Gnanapavan
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.,Department of Neurology, The Royal London Hospital, Barts Health NHS Trust, London, United Kingdom
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Haider L, Chung K, Birch G, Eshaghi A, Mangesius S, Prados F, Tur C, Ciccarelli O, Barkhof F, Chard D. Linear brain atrophy measures in multiple sclerosis and clinically isolated syndromes: a 30-year follow-up. J Neurol Neurosurg Psychiatry 2021; 92:jnnp-2020-325421. [PMID: 33785581 DOI: 10.1136/jnnp-2020-325421] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2020] [Revised: 01/25/2021] [Accepted: 03/02/2021] [Indexed: 01/07/2023]
Abstract
OBJECTIVE To determine 30-year brain atrophy rates following clinically isolated syndromes and the relationship of atrophy in the first 5 years and clinical outcomes 25 years later. METHODS A cohort of 132 people who presented with a clinically isolated syndrome suggestive of multiple sclerosis (MS) were recruited between 1984-1987. Clinical and MRI data were collected prospectively over 30 years. Widths of the third ventricle and the medulla oblongata were used as linear atrophy measures. RESULTS At 30 years, 27 participants remained classified as having had a clinically isolated syndrome, 34 converted to relapsing remitting MS, 26 to secondary progressive MS and 16 had died due to MS. The mean age at baseline was 31.7 years (SD 7.5) and the mean disease duration was 30.8 years (SD 0.9). Change in medullary and third ventricular width within the first 5 years, allowing for white matter lesion accrual and Expanded Disability Status Scale increases over the same period, predicted clinical outcome measures at 30 years. 1 mm of medullary atrophy within the first 5 years increased the risk for secondary progressive MS or MS related death by 30 years by 583% (OR 5.83, 95% CI 1.74 to 19.61, p<0.005), using logistic regression. CONCLUSIONS Our findings show that brain regional atrophy within 5 years of a clinically isolated syndrome predicts progressive MS or a related death, and disability 25 years later.
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Affiliation(s)
- Lukas Haider
- UCL Queen Square Institute of Neurology, UCL, London, UK
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Wien, Wien, Austria
| | - Karen Chung
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London, London, London, UK
| | - Giselle Birch
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London, London, London, UK
| | - Arman Eshaghi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London, London, London, UK
- Department of Medical Physics and Biomedical Engineering, University College London, London, London, UK
| | - Stephanie Mangesius
- Department of Neuroradiology, Medizinische Universitat Innsbruck, Innsbruck, Austria
- Neuroimaging Core Facility, Medizinische Universitat Innsbruck, Innsbruck, Tirol, Austria
| | - Ferran Prados
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, London, UK
- Universitat Oberta de Catalunya, Barcelona, Catalunya, Spain
| | - Carmen Tur
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London, London, London, UK
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London, London, London, UK
- University College London Hospitals (UCLH) Biomedical Research Centre, National Institute for Health Research, London, London, UK
| | - Frederik Barkhof
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London, London, London, UK
- Department of Radiology and Nuclear Medicine, VU University Medical Centre Amsterdam, Amsterdam, Noord-Holland, Netherlands
| | - Declan Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London, London, London, UK
- University College London Hospitals (UCLH) Biomedical Research Centre, National Institute for Health Research, London, London, UK
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Bouman PM, Steenwijk MD, Pouwels PJW, Schoonheim MM, Barkhof F, Jonkman LE, Geurts JJG. Histopathology-validated recommendations for cortical lesion imaging in multiple sclerosis. Brain 2021; 143:2988-2997. [PMID: 32889535 PMCID: PMC7586087 DOI: 10.1093/brain/awaa233] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 04/10/2020] [Accepted: 06/01/2020] [Indexed: 11/30/2022] Open
Abstract
Cortical demyelinating lesions are clinically important in multiple sclerosis, but notoriously difficult to visualize with MRI. At clinical field strengths, double inversion recovery MRI is most sensitive, but still only detects 18% of all histopathologically validated cortical lesions. More recently, phase-sensitive inversion recovery was suggested to have a higher sensitivity than double inversion recovery, although this claim was not histopathologically validated. Therefore, this retrospective study aimed to provide clarity on this matter by identifying which MRI sequence best detects histopathologically-validated cortical lesions at clinical field strength, by comparing sensitivity and specificity of the thus far most commonly used MRI sequences, which are T2, fluid-attenuated inversion recovery (FLAIR), double inversion recovery and phase-sensitive inversion recovery. Post-mortem MRI was performed on non-fixed coronal hemispheric brain slices of 23 patients with progressive multiple sclerosis directly after autopsy, at 3 T, using T1 and proton-density/T2-weighted, as well as FLAIR, double inversion recovery and phase-sensitive inversion recovery sequences. A total of 93 cortical tissue blocks were sampled from these slices. Blinded to histopathology, all MRI sequences were consensus scored for cortical lesions. Subsequently, tissue samples were stained for proteolipid protein (myelin) and scored for cortical lesion types I–IV (mixed grey matter/white matter, intracortical, subpial and cortex-spanning lesions, respectively). MRI scores were compared to histopathological scores to calculate sensitivity and specificity per sequence. Next, a retrospective (unblinded) scoring was performed to explore maximum scoring potential per sequence. Histopathologically, 224 cortical lesions were detected, of which the majority were subpial. In a mixed model, sensitivity of T1, proton-density/T2, FLAIR, double inversion recovery and phase-sensitive inversion recovery was 8.9%, 5.4%, 5.4%, 22.8% and 23.7%, respectively (20, 12, 12, 51 and 53 cortical lesions). Specificity of the prospective scoring was 80.0%, 75.0%, 80.0%, 91.1% and 88.3%. Sensitivity and specificity did not significantly differ between double inversion recovery and phase-sensitive inversion recovery, while phase-sensitive inversion recovery identified more lesions than double inversion recovery upon retrospective analysis (126 versus 95; P < 0.001). We conclude that, at 3 T, double inversion recovery and phase-sensitive inversion recovery sequences outperform conventional sequences T1, proton-density/T2 and FLAIR. While their overall sensitivity does not exceed 25%, double inversion recovery and phase-sensitive inversion recovery are highly pathologically specific when using existing scoring criteria and their use is recommended for optimal cortical lesion assessment in multiple sclerosis.
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Affiliation(s)
- Piet M Bouman
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Petra J W Pouwels
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.,UCL Institutes of Neurology and Healthcare Engineering, UCL, London, UK
| | - Laura E Jonkman
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
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Treaba CA, Herranz E, Barletta VT, Mehndiratta A, Ouellette R, Sloane JA, Klawiter EC, Kinkel RP, Mainero C. The relevance of multiple sclerosis cortical lesions on cortical thinning and their clinical impact as assessed by 7.0-T MRI. J Neurol 2021; 268:2473-2481. [PMID: 33523256 DOI: 10.1007/s00415-021-10400-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 01/04/2021] [Accepted: 01/05/2021] [Indexed: 10/22/2022]
Abstract
OBJECTIVE This study aimed to investigate at 7.0-T MRI a) the role of multiple sclerosis (MS) cortical lesions in cortical tissue loss b) their relation to neurological disability. METHODS In 76 relapsing remitting and 26 secondary progressive MS patients (N = 102) and 56 healthy subjects 7.0-T T2*-weighted images were acquired for lesion segmentation; 3.0-T T1-weighted structural scans for cortical surface reconstruction/cortical thickness estimation. Patients were dichotomized based on the median cortical lesion volume in low and high cortical lesion load groups that differed by age, MS phenotype and degree of neurological disability. Group differences in cortical thickness were tested on reconstructed cortical surface. Patients were evaluated clinically by means of the Expanded Disability Status Scale (EDSS). RESULTS Cortical lesions were detected in 96% of patients. White matter lesion load was greater in the high than in the low cortical lesion load MS group (p = 0.01). Both MS groups disclosed clusters (prevalently parietal) of cortical thinning relative to healthy subjects, though these regions did not show the highest cortical lesion density, which predominantly involved frontal regions. Cortical thickness decreased on average by 0.37 mm, (p = 0.002) in MS patients for each unit standard deviation change in white matter lesion volume. The odds of having a higher EDSS were associated with cortical lesion volume (1.78, p = 0.01) and disease duration (1.15, p < 0.001). CONCLUSION Cortical thinning in MS is not directly related to cortical lesion load but rather with white matter lesion volume. Neurological disability in MS is better explained by cortical lesion volume assessment.
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Affiliation(s)
- Constantina A Treaba
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Elena Herranz
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Valeria T Barletta
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Ambica Mehndiratta
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Russell Ouellette
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Jacob A Sloane
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Eric C Klawiter
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Caterina Mainero
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA. .,Harvard Medical School, Boston, MA, USA.
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37
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Rothstein TL. Gray Matter Matters: A Longitudinal Magnetic Resonance Voxel-Based Morphometry Study of Primary Progressive Multiple Sclerosis. Front Neurol 2020; 11:581537. [PMID: 33281717 PMCID: PMC7689315 DOI: 10.3389/fneur.2020.581537] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 10/14/2020] [Indexed: 12/31/2022] Open
Abstract
Background: Multiple Sclerosis (MS) lesions in white matter (WM) are easily detected with conventional MRI which induce inflammation thereby generating contrast. WM lesions do not consistently explain the extent of clinical disability, cognitive impairment, or the source of an exacerbation. Gray matter (GM) structures including the cerebral cortex and various deep nuclei are known to be affected early in Primary Progressive Multiple Sclerosis (PPMS) and drive disease progression, disability, fatigue, and cognitive dysfunction. However, little is known about how rapidly GM lesions develop and accumulate over time. Objective: The purpose of this study is to analyze the degree and rate of progression in 25 patients with PPMS using voxel-based automated volumetric quantitation. Methods: This is a retrospective single-center study which includes a cohort of 25 patients with PPMS scanned utilizing NeuroQuant® 3 dimensional voxel-based morphometry (3D VBM) automated analysis and database and restudied after a period of ~1 year (11–14 months). Comparisons with normative data were acquired for whole brain, forebrain parenchyma, cortical GM, hippocampus, thalamus, superior and inferior lateral ventricles. GM volume changes were correlated with their clinical motor and cognitive scores using Extended Disability Status Scales (EDSS) and Montreal Cognitive Assessments (MoCA). Results: Steep reductions occurred in cerebral cortical GM and deep GM nuclei volumes which correlated with each patient's clinical and cognitive impairment. The median observed percentile volume losses were statistically significant compared with the 50th percentile for each GM component. Longitudinal assessments of an unselected sample of one dozen patients involved in the PPMS study showed prominent losses occurring mainly in cortical GM and hippocampus which were reflected in their EDSS and MoCA. The longitudinal results were compared with a similar sample of patients having Relapsing MS (RMS) whose GM values were largely in normal range, annualized volume GM changes were much less, while WM hyperintensities were in abnormal range in half the unselected cases. Conclusions: Knowledge of the degree and rapidity with which cortical atrophy and deep GM volume loss develops clarifies the source of progressive cognitive and clinical decline in PPMS.
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Affiliation(s)
- Ted L Rothstein
- Department of Neurology, Multiple Sclerosis Clinical Care and Research Center, George Washington University School of Medicine, Washington, DC, United States
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Beutel T, Dzimiera J, Kapell H, Engelhardt M, Gass A, Schirmer L. Cortical projection neurons as a therapeutic target in multiple sclerosis. Expert Opin Ther Targets 2020; 24:1211-1224. [PMID: 33103501 DOI: 10.1080/14728222.2020.1842358] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
INTRODUCTION Multiple sclerosis (MS) is a chronic inflammatory-demyelinating disease of the central nervous system associated with lesions of the cortical gray matter and subcortical white matter. Recently, cortical lesions have become a major focus of research because cortical pathology and neuronal damage are critical determinants of irreversible clinical progression. Recent transcriptomic studies point toward cell type-specific changes in cortical neurons in MS with a selective vulnerability of excitatory projection neuron subtypes. AREAS COVERED We discuss the cortical mapping and the molecular properties of excitatory projection neurons and their role in MS lesion pathology while placing an emphasis on their subtype-specific transcriptomic changes and levels of vulnerability. We also examine the latest magnetic resonance imaging techniques to study cortical MS pathology as a key tool for monitoring disease progression and treatment efficacy. Finally, we consider possible therapeutic avenues and novel strategies to protect excitatory cortical projection neurons. Literature search methodology: PubMed articles from 2000-2020. EXPERT OPINION Excitatory cortical projection neurons are an emerging therapeutic target in the treatment of progressive MS. Understanding neuron subtype-specific molecular pathologies and their exact spatial mapping will help establish starting points for the development of novel cell type-specific therapies and biomarkers in MS.
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Affiliation(s)
- Tatjana Beutel
- Department of Neurology, Medical Faculty Mannheim, MCTN, Heidelberg University , Mannheim, Germany
| | - Julia Dzimiera
- Department of Neurology, Medical Faculty Mannheim, MCTN, Heidelberg University , Mannheim, Germany
| | - Hannah Kapell
- Department of Neurology, Medical Faculty Mannheim, MCTN, Heidelberg University , Mannheim, Germany
| | - Maren Engelhardt
- Institute of Neuroanatomy, Medical Faculty Mannheim, MCTN, Heidelberg University , Mannheim, Germany.,Interdisciplinary Center for Neurosciences, Heidelberg University , Heidelberg, Germany
| | - Achim Gass
- Department of Neurology, Medical Faculty Mannheim, MCTN, Heidelberg University , Mannheim, Germany
| | - Lucas Schirmer
- Department of Neurology, Medical Faculty Mannheim, MCTN, Heidelberg University , Mannheim, Germany.,Interdisciplinary Center for Neurosciences, Heidelberg University , Heidelberg, Germany
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Sugijono SE, Mulyadi R, Firdausia S, Prihartono J, Estiasari R. Corpus callosum index correlates with brain volumetry and disability in multiple sclerosis patients. NEUROSCIENCES (RIYADH, SAUDI ARABIA) 2020; 25:193-199. [PMID: 32683399 PMCID: PMC8015480 DOI: 10.17712/nsj.2020.3.20190093] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Accepted: 04/15/2020] [Indexed: 11/20/2022]
Abstract
OBJECTIVE To analyze the correlation between corpus callosum index (CCI), brain volumetry, and disability in multiple sclerosis (MS) patients. The brain volumetry consists of the corpus callosum, cortical gray matter, subcortical gray matter, and white matter volumes. METHODS This was a retrospective cross-sectional study from October 2018 to February 2019 of 30 patients with MS aged 20 to 61 years old. Brain volumetry was performed using FreeSurfer software. The CCI were measured manually using conventional best mid-sagittal T1W brain MRI. The anterior, posterior, and medium segments were measured and divided to its greatest anteroposterior diameter. Higher CCI values indicated greater corpus callosum volumes. Clinical evaluation was comprised of MS subtype, age of onset, relapse frequency and Expanded Disability Status Scale (EDSS). RESULTS Thirty MS patients with median of age 22 years were included. Relapsing-remitting (RRMS) subtype were 73.3%. Very significant correlations were shown between the CCI and corpus callosum volume (CCV) (r=0.79; p<0.0001) and cerebral white matter volume (r=0.81; p<0.0001). Significant correlations were shown between the CCI and cortical gray matter volume (r=0.64; p<0.0001) and subcortical gray matter volume (r=0.69; p<0.0001). The CCI was positively correlated with age of onset and inversely with EDSS. The CCV and CCI were smaller in secondary progressive MS (SPMS). CONCLUSION The CCI is easy and fast to obtain in conventional MRI and significantly correlated with brain volumetry, age of onset and disability in MS patients.
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Affiliation(s)
- Stefanus E. Sugijono
- From the Department of Radiology (Sugijono), Division of Neuroradiology (Mulyadi), Department of Radiology, Department of Neurology (Firdausia, Estiasari), Department of Community Medicine (Prihartono), Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia.
| | - Rahmad Mulyadi
- From the Department of Radiology (Sugijono), Division of Neuroradiology (Mulyadi), Department of Radiology, Department of Neurology (Firdausia, Estiasari), Department of Community Medicine (Prihartono), Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia.
| | - Salsabila Firdausia
- From the Department of Radiology (Sugijono), Division of Neuroradiology (Mulyadi), Department of Radiology, Department of Neurology (Firdausia, Estiasari), Department of Community Medicine (Prihartono), Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia.
| | - Joedo Prihartono
- From the Department of Radiology (Sugijono), Division of Neuroradiology (Mulyadi), Department of Radiology, Department of Neurology (Firdausia, Estiasari), Department of Community Medicine (Prihartono), Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia.
| | - Riwanti Estiasari
- From the Department of Radiology (Sugijono), Division of Neuroradiology (Mulyadi), Department of Radiology, Department of Neurology (Firdausia, Estiasari), Department of Community Medicine (Prihartono), Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia.
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40
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Preziosa P, Kiljan S, Steenwijk MD, Meani A, van de Berg WDJ, Schenk GJ, Rocca MA, Filippi M, Geurts JJG, Jonkman LE. Axonal degeneration as substrate of fractional anisotropy abnormalities in multiple sclerosis cortex. Brain 2020; 142:1921-1937. [PMID: 31168614 DOI: 10.1093/brain/awz143] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 03/14/2019] [Accepted: 04/09/2019] [Indexed: 12/11/2022] Open
Abstract
Cortical microstructural abnormalities are associated with clinical and cognitive deterioration in multiple sclerosis. Using diffusion tensor MRI, a higher fractional anisotropy has been found in cortical lesions versus normal-appearing cortex in multiple sclerosis. The pathological substrates of this finding have yet to be definitively elucidated. By performing a combined post-mortem diffusion tensor MRI and histopathology study, we aimed to define the histopathological substrates of diffusivity abnormalities in multiple sclerosis cortex. Sixteen subjects with multiple sclerosis and 10 age- and sex-matched non-neurological control donors underwent post-mortem in situ at 3 T MRI, followed by brain dissection. One hundred and ten paraffin-embedded tissue blocks (54 from multiple sclerosis patients, 56 from non-neurological controls) were matched to the diffusion tensor sequence to obtain regional diffusivity measures. Using immunohistochemistry and silver staining, cortical density of myelin, microglia, astrocytes and axons, and density and volume of neurons and glial cells were evaluated. Correlates of diffusivity abnormalities with histological markers were assessed through linear mixed-effects models. Cortical lesions (77% subpial) were found in 27/54 (50%) multiple sclerosis cortical regions. Multiple sclerosis normal-appearing cortex had a significantly lower fractional anisotropy compared to cortex from non-neurological controls (P = 0.047), whereas fractional anisotropy in demyelinated cortex was significantly higher than in multiple sclerosis normal-appearing cortex (P = 0.012) but not different from non-neurological control cortex (P = 0.420). Compared to non-neurological control cortex, both multiple sclerosis normal-appearing and demyelinated cortices showed a lower density of axons perpendicular to the cortical surface (P = 0.012 for both) and of total axons (parallel and perpendicular to cortical surface) (P = 0.028 and 0.012). In multiple sclerosis, demyelinated cortex had a lower density of myelin (P = 0.004), parallel (P = 0.018) and total axons (P = 0.029) versus normal-appearing cortex. Regarding the pathological substrate, in non-neurological controls, cortical fractional anisotropy was positively associated with density of perpendicular, parallel, and total axons (P = 0.031 for all). In multiple sclerosis, normal-appearing cortex fractional anisotropy was positively associated with perpendicular and total axon density (P = 0.031 for both), while associations with myelin, glial and total cells and parallel axons did not survive multiple comparison correction. Demyelinated cortex fractional anisotropy was positively associated with density of neurons, and total cells and negatively with microglia density, without surviving multiple comparison correction. Our results suggest that a reduction of perpendicular axons in normal-appearing cortex and of both perpendicular and parallel axons in demyelinated cortex may underlie the substrate influencing cortical microstructural coherence and being responsible for the different patterns of fractional anisotropy changes occurring in multiple sclerosis cortex.
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Affiliation(s)
- Paolo Preziosa
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Svenja Kiljan
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Alessandro Meani
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Wilma D J van de Berg
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Geert J Schenk
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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41
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Kiljan S, Preziosa P, Jonkman LE, van de Berg WD, Twisk J, Pouwels PJ, Schenk GJ, Rocca MA, Filippi M, Geurts JJ, Steenwijk MD. Cortical axonal loss is associated with both gray matter demyelination and white matter tract pathology in progressive multiple sclerosis: Evidence from a combined MRI-histopathology study. Mult Scler 2020; 27:380-390. [PMID: 32390507 PMCID: PMC7897796 DOI: 10.1177/1352458520918978] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Background: Neuroaxonal degeneration is one of the hallmarks of clinical deterioration in progressive multiple sclerosis (PMS). Objective: To elucidate the association between neuroaxonal degeneration and both local cortical and connected white matter (WM) tract pathology in PMS. Methods: Post-mortem in situ 3T magnetic resonance imaging (MRI) and cortical tissue blocks were collected from 16 PMS donors and 10 controls. Cortical neuroaxonal, myelin, and microglia densities were quantified histopathologically. From diffusion tensor MRI, fractional anisotropy, axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) were quantified in normal-appearing white matter (NAWM) and white matter lesions (WML) of WM tracts connected to dissected cortical regions. Between-group differences and within-group associations were investigated through linear mixed models. Results: The PMS donors displayed significant axonal loss in both demyelinated and normal-appearing (NA) cortices (p < 0.001 and p = 0.02) compared with controls. In PMS, cortical axonal density was associated with WML MD and AD (p = 0.003; p = 0.02, respectively), and NAWM MD and AD (p = 0.04; p = 0.049, respectively). NAWM AD and WML AD explained 12.6% and 22.6%, respectively, of axonal density variance in NA cortex. Additional axonal loss in demyelinated cortex was associated with cortical demyelination severity (p = 0.002), explaining 34.4% of axonal loss variance. Conclusion: Reduced integrity of connected WM tracts and cortical demyelination both contribute to cortical axonal loss in PMS.
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Affiliation(s)
- Svenja Kiljan
- Department of Anatomy & Neurosciences, Amsterdam UMC, locatie VU University Medical Center, Amsterdam, The Netherlands/Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands
| | - Paolo Preziosa
- Department of Anatomy & Neurosciences, Amsterdam UMC, locatie VU University Medical Center, Amsterdam, The Netherlands/Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands/Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Laura E Jonkman
- Department of Anatomy & Neurosciences, Amsterdam UMC, locatie VU University Medical Center, Amsterdam, The Netherlands
| | - Wilma Dj van de Berg
- Department of Anatomy & Neurosciences, Amsterdam UMC, locatie VU University Medical Center, Amsterdam, The Netherlands
| | - Jos Twisk
- Department of Epidemiology and Biostatistics, Amsterdam UMC, locatie VU University Medical Center, Amsterdam, The Netherlands
| | - Petra Jw Pouwels
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam UMC, locatie VU University Medical Center, Amsterdam, The Netherlands
| | - Geert J Schenk
- Department of Anatomy & Neurosciences, Amsterdam UMC, locatie VU University Medical Center, Amsterdam, The Netherlands/Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Neurology Unit, Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy/Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen Jg Geurts
- Department of Anatomy & Neurosciences, Amsterdam UMC, locatie VU University Medical Center, Amsterdam, The Netherlands/Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy & Neurosciences, Amsterdam UMC, locatie VU University Medical Center, Amsterdam, The Netherlands/Amsterdam Neuroscience, MS Center Amsterdam, Amsterdam, The Netherlands
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42
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Tsagkas C, Chakravarty MM, Gaetano L, Naegelin Y, Amann M, Parmar K, Papadopoulou A, Wuerfel J, Kappos L, Sprenger T, Magon S. Longitudinal patterns of cortical thinning in multiple sclerosis. Hum Brain Mapp 2020; 41:2198-2215. [PMID: 32067281 PMCID: PMC7268070 DOI: 10.1002/hbm.24940] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 12/21/2019] [Accepted: 01/13/2020] [Indexed: 01/19/2023] Open
Abstract
In multiple sclerosis (MS), cortical atrophy is correlated with clinical and neuropsychological measures. We aimed to examine the differences in the temporospatial evolution of cortical thickness (CTh) between MS‐subtypes and to study the association of CTh with T2‐weighted white matter lesions (T2LV) and clinical progression. Two hundred and forty‐three MS patients (180 relapsing–remitting [RRMS], 51 secondary‐progressive [SPMS], and 12 primary‐progressive [PPMS]) underwent annual clinical (incl. expanded disability status scale [EDSS]) and MRI‐examinations over 6 years. T2LV and CTh were measured. CTh did not differ between MS‐subgroups. Higher total T2LV was associated with extended bilateral CTh‐reduction on average, but did not correlate with CTh‐changes over time. In RRMS, CTh‐ and EDSS‐changes over time were negatively correlated in large bilateral prefrontal, frontal, parietal, temporal, and occipital areas. In SPMS, CTh was not associated with the EDSS. In PPMS, CTh‐ and EDSS‐changes over time were correlated in small clusters predominantly in left parietal areas. Increase of brain lesion load does not lead to an immediate CTh‐reduction. Although CTh did not differ between MS‐subtypes, a dissociation in the correlation between CTh‐ and EDSS‐changes over time between RRMS and progressive‐MS was shown, possibly underlining the contribution of subcortical pathology to clinical progression in progressive‐MS.
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Affiliation(s)
- Charidimos Tsagkas
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Medical Image Analysis Center AG, Basel, Switzerland
| | - M Mallar Chakravarty
- Cerebral Imaging Centre - Douglas Mental Health University Institute, Verdun, QC, Canada.,Department of Biomedical Engineering, McGill University, Montreal, QC, Canada.,Department of Psychiatry, McGill University, Montreal, QC, Canada
| | | | - Yvonne Naegelin
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Switzerland
| | - Michael Amann
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Switzerland.,Medical Image Analysis Center AG, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Katrin Parmar
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Athina Papadopoulou
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,NeuroCure Clinical Research Center, Charite - Universitatsmedizin Berlin, corporate member of Freie Universitat Berlin, Humboldt-Universitat zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Jens Wuerfel
- Medical Image Analysis Center AG, Basel, Switzerland.,Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Till Sprenger
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Switzerland.,Department of Neurology, DKD HELIOS Klinik Wiesbaden, Wiesbaden, Germany
| | - Stefano Magon
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Switzerland.,Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
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43
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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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44
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Radetz A, Koirala N, Krämer J, Johnen A, Fleischer V, Gonzalez-Escamilla G, Cerina M, Muthuraman M, Meuth SG, Groppa S. Gray matter integrity predicts white matter network reorganization in multiple sclerosis. Hum Brain Mapp 2019; 41:917-927. [PMID: 32026599 PMCID: PMC7268008 DOI: 10.1002/hbm.24849] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Revised: 10/16/2019] [Accepted: 10/17/2019] [Indexed: 01/19/2023] Open
Abstract
Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease leading to gray matter atrophy and brain network reconfiguration as a response to increasing tissue damage. We evaluated whether white matter network reconfiguration appears subsequently to gray matter damage, or whether the gray matter degenerates following alterations in white matter networks. MRI data from 83 patients with clinically isolated syndrome and early relapsing-remitting MS were acquired at two time points with a follow-up after 1 year. White matter network integrity was assessed based on probabilistic tractography performed on diffusion-weighted data using graph theoretical analyses. We evaluated gray matter integrity by computing cortical thickness and deep gray matter volume in 94 regions at both time points. The thickness of middle temporal cortex and the volume of deep gray matter regions including thalamus, caudate, putamen, and brain stem showed significant atrophy between baseline and follow-up. White matter network dynamics, as defined by modularity and distance measure changes over time, were predicted by deep gray matter volume of the atrophying anatomical structures. Initial white matter network properties, on the other hand, did not predict atrophy. Furthermore, gray matter integrity at baseline significantly predicted physical disability at 1-year follow-up. In a sub-analysis, deep gray matter volume was significantly related to cognitive performance at baseline. Hence, we postulate that atrophy of deep gray matter structures drives the adaptation of white matter networks. Moreover, deep gray matter volumes are highly predictive for disability progression and cognitive performance.
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Affiliation(s)
- Angela Radetz
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Nabin Koirala
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Julia Krämer
- Department of Neurology, University of Münster, Münster, Germany
| | - Andreas Johnen
- Department of Neurology, University of Münster, Münster, Germany
| | - Vinzenz Fleischer
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Manuela Cerina
- Department of Neurology, University of Münster, Münster, Germany
| | - Muthuraman Muthuraman
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sven G Meuth
- Department of Neurology, University of Münster, Münster, Germany
| | - Sergiu Groppa
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
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45
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Silva BA, Ferrari CC. Cortical and meningeal pathology in progressive multiple sclerosis: a new therapeutic target? Rev Neurosci 2019; 30:221-232. [PMID: 30048237 DOI: 10.1515/revneuro-2018-0017] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 05/04/2018] [Indexed: 12/31/2022]
Abstract
Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease that involves an intricate interaction between the central nervous system and the immune system. Nevertheless, its etiology is still unknown. MS exhibits different clinical courses: recurrent episodes with remission periods ('relapsing-remitting') that can evolve to a 'secondary progressive' form or persistent progression from the onset of the disease ('primary progressive'). The discovery of an effective treatment and cure has been hampered due to the pathological and clinical heterogeneity of the disease. Historically, MS has been considered as a disease exclusively of white matter. However, patients with progressive forms of MS present with cortical lesions associated with meningeal inflammation along with physical and cognitive disabilities. The pathogenesis of the cortical lesions has not yet been fully described. Animal models that represent both the cortical and meningeal pathologies will be critical in addressing MS pathogenesis as well as the design of specific treatments. In this review, we will address the state-of-the-art diagnostic and therapeutic alternatives and the development of strategies to discover new therapeutic approaches, especially for the progressive forms.
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Affiliation(s)
- Berenice Anabel Silva
- Institute of Basic Science and Experimental Medicine (ICBME), University Institute, Italian Hospital, Potosi 4240 (C1199ABB), CABA, Buenos Aires, Argentina.,Leloir Institute Foundation, Institute for Biochemical Investigations of Buenos Aires, (IIBBA, CONICET), Patricias Argentinas 435 (C1405BWE), Buenos Aires, Argentina, e-mail:
| | - Carina Cintia Ferrari
- Institute of Basic Science and Experimental Medicine (ICBME), University Institute, Italian Hospital, Potosi 4240 (C1199ABB), CABA, Buenos Aires, Argentina.,Leloir Institute Foundation, Institute for Biochemical Investigations of Buenos Aires, (IIBBA, CONICET), Patricias Argentinas 435 (C1405BWE), Buenos Aires, Argentina
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46
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Imaging in mice and men: Pathophysiological insights into multiple sclerosis from conventional and advanced MRI techniques. Prog Neurobiol 2019; 182:101663. [PMID: 31374243 DOI: 10.1016/j.pneurobio.2019.101663] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 06/17/2019] [Accepted: 07/17/2019] [Indexed: 01/16/2023]
Abstract
Magnetic resonance imaging (MRI) is the most important tool for diagnosing multiple sclerosis (MS). However, MRI is still unable to precisely quantify the specific pathophysiological processes that underlie imaging findings in MS. Because autopsy and biopsy samples of MS patients are rare and biased towards a chronic burnt-out end or fulminant acute early stage, the only available methods to identify human disease pathology are to apply MRI techniques in combination with subsequent histopathological examination to small animal models of MS and to transfer these insights to MS patients. This review summarizes the existing combined imaging and histopathological studies performed in MS mouse models and humans with MS (in vivo and ex vivo), to promote a better understanding of the pathophysiology that underlies conventional MRI, diffusion tensor and magnetization transfer imaging findings in MS patients. Moreover, it provides a critical view on imaging capabilities and results in MS patients and mouse models and for future studies recommends how to combine those particular MR sequences and parameters whose underlying pathophysiological basis could be partly clarified. Further combined longitudinal in vivo imaging and histopathological studies on rationally selected, appropriate mouse models are required.
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47
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Eijlers AJC, van Geest Q, Dekker I, Steenwijk MD, Meijer KA, Hulst HE, Barkhof F, Uitdehaag BMJ, Schoonheim MM, Geurts JJG. Predicting cognitive decline in multiple sclerosis: a 5-year follow-up study. Brain 2019; 141:2605-2618. [PMID: 30169585 DOI: 10.1093/brain/awy202] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Accepted: 06/15/2018] [Indexed: 11/14/2022] Open
Abstract
Cognitive decline is common in multiple sclerosis and strongly affects overall quality of life. Despite the identification of cross-sectional MRI correlates of cognitive impairment, predictors of future cognitive decline remain unclear. The objective of this study was to identify which MRI measures of structural damage, demographic and/or clinical measures at baseline best predict cognitive decline, during a 5-year follow-up period. A total of 234 patients with clinically definite multiple sclerosis and 60 healthy control subjects were examined twice, with a 5-year interval (mean = 4.9 years, standard deviation = 0.9). An extensive neuropsychological evaluation was performed at both time points and the reliable change index was computed to evaluate cognitive decline. Both whole-brain and regional MRI (3 T) measures were assessed at baseline, including white matter lesion volume, diffusion-based white matter integrity, cortical and deep grey matter volume. Logistic regression analyses were performed to determine which baseline measures best predicted cognitive decline in the entire sample as well as in early relapsing-remitting (symptom duration <10 years), late relapsing-remitting (symptom duration ≥10 years) and progressive phenotypes. At baseline, patients with multiple sclerosis had a mean disease duration of 14.8 (standard deviation = 8.4) years and 96/234 patients (41%) were classified as cognitively impaired. A total of 66/234 patients (28%) demonstrated cognitive decline during follow-up, with higher frequencies in progressive compared to relapsing-remitting patients: 18/33 secondary progressive patients (55%), 10/19 primary progressive patients (53%) and 38/182 relapsing-remitting patients (21%). A prediction model that included only whole-brain MRI measures (Nagelkerke R2 = 0.22, P < 0.001) showed cortical grey matter volume as the only significant MRI predictor of cognitive decline, while a prediction model that assessed regional MRI measures (Nagelkerke R2 = 0.35, P < 0.001) indicated integrity loss of the anterior thalamic radiation, lesions in the superior longitudinal fasciculus and temporal atrophy as significant MRI predictors for cognitive decline. Disease stage specific regressions showed that cognitive decline in early relapsing-remitting multiple sclerosis was predicted by white matter integrity damage, while cognitive decline in late relapsing-remitting and progressive multiple sclerosis was predicted by cortical atrophy. These results indicate that patients with more severe structural damage at baseline, and especially cortical atrophy, are more prone to suffer from cognitive decline. New studies now need to further elucidate the underlying mechanisms leading to cortical atrophy, evaluate the value of including cortical atrophy as a possible outcome marker in clinical trials as well as study its potential use in individual patient management.
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Affiliation(s)
- Anand J C Eijlers
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Quinten van Geest
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Iris Dekker
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Department of Neurology, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Kim A Meijer
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Hanneke E Hulst
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, UCL, London, UK
| | - Bernard M J Uitdehaag
- Department of Neurology, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, MS Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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48
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Wang C, Barnett MH, Yiannikas C, Barton J, Parratt J, You Y, Graham SL, Klistorner A. Lesion activity and chronic demyelination are the major determinants of brain atrophy in MS. NEUROLOGY-NEUROIMMUNOLOGY & NEUROINFLAMMATION 2019; 6:6/5/e593. [PMID: 31454773 PMCID: PMC6705629 DOI: 10.1212/nxi.0000000000000593] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Accepted: 05/07/2019] [Indexed: 01/26/2023]
Abstract
Objective To evaluate the combined effect of lesion activity and pathologic processes occurring in both chronically demyelinated lesions and normal-appearing white matter (NAWM) on brain atrophy in MS. Methods Pre- and post-gadolinium T1, fluid attenuation inversion recovery, and diffusion tensor imaging images were acquired from 50 consecutive patients with relapsing-remitting MS (all, but one, on disease-modifying therapy) at baseline and 5 years. Brain atrophy was measured using structural image evaluation, using normalization of atrophy percent brain volume change (PBVC) analysis. Results During follow-up, brain volume diminished by 2.0% ± 1.1%. PBVC was not associated with patient age, disease duration, sex, or type of treatment. PBVC moderately correlated with baseline lesion load (r = −0.38, p = 0.016), but demonstrated strong association with new lesion activity (r = −0.63, p < 0.001). Brain atrophy was also strongly linked to the increase of water diffusion within chronic MS lesions (r = −0.62, p < 0.001). In normal-appearing white matter (NAWM), PBVC demonstrated a significant correlation with both baseline and longitudinal increase of demyelination as measured by radial diffusivity (RD, r = −0.44, p = 0.005 and r = −0.35, p = 0.026, respectively). Linear regression analysis explained 62% of the variance in PBVC. It confirmed the major role of new lesion activity (p = 0.002, standardized beta-coefficient −0.42), whereas change in diffusivity inside chronic lesions and NAWM RD at baseline also contributed significantly (p = 0.04 and 0.02, standardized beta-coefficient −0.31 and −0.29, respectively), increasing predictive power of the model by 55%. Conclusion In addition to new lesion activity, progressive loss of demyelinated axons in chronic lesions and the degree of demyelination in NAWM significantly contribute to accelerated loss of brain tissue in patients with MS receiving immunomodulatory therapy.
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Affiliation(s)
- Chenyu Wang
- From the Brain and Mind Centre (C.W., M.H.B., J.B.), Sydney Medical School, University of Sydney; Sydney Neuroimaging Analysis Centre (C.W., M.H.B.); Royal North Shore Hospital (C.Y., J.P.); Save Sight Institute (Y.Y., A.K.), Sydney Medical School, University of Sydney; and Faculty of Medicine and Health Sciences (S.L.G., A.K.), Macquarie University, Sydney, NSW, Australia
| | - Michael H Barnett
- From the Brain and Mind Centre (C.W., M.H.B., J.B.), Sydney Medical School, University of Sydney; Sydney Neuroimaging Analysis Centre (C.W., M.H.B.); Royal North Shore Hospital (C.Y., J.P.); Save Sight Institute (Y.Y., A.K.), Sydney Medical School, University of Sydney; and Faculty of Medicine and Health Sciences (S.L.G., A.K.), Macquarie University, Sydney, NSW, Australia
| | - Con Yiannikas
- From the Brain and Mind Centre (C.W., M.H.B., J.B.), Sydney Medical School, University of Sydney; Sydney Neuroimaging Analysis Centre (C.W., M.H.B.); Royal North Shore Hospital (C.Y., J.P.); Save Sight Institute (Y.Y., A.K.), Sydney Medical School, University of Sydney; and Faculty of Medicine and Health Sciences (S.L.G., A.K.), Macquarie University, Sydney, NSW, Australia
| | - Joshua Barton
- From the Brain and Mind Centre (C.W., M.H.B., J.B.), Sydney Medical School, University of Sydney; Sydney Neuroimaging Analysis Centre (C.W., M.H.B.); Royal North Shore Hospital (C.Y., J.P.); Save Sight Institute (Y.Y., A.K.), Sydney Medical School, University of Sydney; and Faculty of Medicine and Health Sciences (S.L.G., A.K.), Macquarie University, Sydney, NSW, Australia
| | - John Parratt
- From the Brain and Mind Centre (C.W., M.H.B., J.B.), Sydney Medical School, University of Sydney; Sydney Neuroimaging Analysis Centre (C.W., M.H.B.); Royal North Shore Hospital (C.Y., J.P.); Save Sight Institute (Y.Y., A.K.), Sydney Medical School, University of Sydney; and Faculty of Medicine and Health Sciences (S.L.G., A.K.), Macquarie University, Sydney, NSW, Australia
| | - Yuyi You
- From the Brain and Mind Centre (C.W., M.H.B., J.B.), Sydney Medical School, University of Sydney; Sydney Neuroimaging Analysis Centre (C.W., M.H.B.); Royal North Shore Hospital (C.Y., J.P.); Save Sight Institute (Y.Y., A.K.), Sydney Medical School, University of Sydney; and Faculty of Medicine and Health Sciences (S.L.G., A.K.), Macquarie University, Sydney, NSW, Australia
| | - Stuart L Graham
- From the Brain and Mind Centre (C.W., M.H.B., J.B.), Sydney Medical School, University of Sydney; Sydney Neuroimaging Analysis Centre (C.W., M.H.B.); Royal North Shore Hospital (C.Y., J.P.); Save Sight Institute (Y.Y., A.K.), Sydney Medical School, University of Sydney; and Faculty of Medicine and Health Sciences (S.L.G., A.K.), Macquarie University, Sydney, NSW, Australia
| | - Alexander Klistorner
- From the Brain and Mind Centre (C.W., M.H.B., J.B.), Sydney Medical School, University of Sydney; Sydney Neuroimaging Analysis Centre (C.W., M.H.B.); Royal North Shore Hospital (C.Y., J.P.); Save Sight Institute (Y.Y., A.K.), Sydney Medical School, University of Sydney; and Faculty of Medicine and Health Sciences (S.L.G., A.K.), Macquarie University, Sydney, NSW, Australia.
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Filippi M, Brück W, Chard D, Fazekas F, Geurts JJG, Enzinger C, Hametner S, Kuhlmann T, Preziosa P, Rovira À, Schmierer K, Stadelmann C, Rocca MA. Association between pathological and MRI findings in multiple sclerosis. Lancet Neurol 2019; 18:198-210. [DOI: 10.1016/s1474-4422(18)30451-4] [Citation(s) in RCA: 87] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 10/22/2018] [Accepted: 11/12/2018] [Indexed: 12/12/2022]
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50
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Bevan RJ, Evans R, Griffiths L, Watkins LM, Rees MI, Magliozzi R, Allen I, McDonnell G, Kee R, Naughton M, Fitzgerald DC, Reynolds R, Neal JW, Howell OW. Meningeal inflammation and cortical demyelination in acute multiple sclerosis. Ann Neurol 2018; 84:829-842. [DOI: 10.1002/ana.25365] [Citation(s) in RCA: 76] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Revised: 10/18/2018] [Accepted: 10/19/2018] [Indexed: 12/25/2022]
Affiliation(s)
- Ryan J. Bevan
- Institute of Life Sciences; Swansea University Medical School; Swansea United Kingdom
| | - Rhian Evans
- Institute of Life Sciences; Swansea University Medical School; Swansea United Kingdom
| | - Lauren Griffiths
- Institute of Life Sciences; Swansea University Medical School; Swansea United Kingdom
| | - Lewis M. Watkins
- Institute of Life Sciences; Swansea University Medical School; Swansea United Kingdom
| | - Mark I. Rees
- Institute of Life Sciences; Swansea University Medical School; Swansea United Kingdom
| | - Roberta Magliozzi
- Neurology Unit, University of Verona; Verona Italy
- Division of Brain Sciences, Faculty of Medicine; Imperial College London; London United Kingdom
| | - Ingrid Allen
- Wellcome-Wolfson Institute for Experimental Medicine; School of Medicine, Dentistry, and Biomedical Science, Queen's University Belfast; Belfast United Kingdom
| | - Gavin McDonnell
- Belfast Health and Social Care Trust; Belfast United Kingdom
| | - Rachel Kee
- Belfast Health and Social Care Trust; Belfast United Kingdom
| | - Michelle Naughton
- Wellcome-Wolfson Institute for Experimental Medicine; School of Medicine, Dentistry, and Biomedical Science, Queen's University Belfast; Belfast United Kingdom
| | - Denise C. Fitzgerald
- Wellcome-Wolfson Institute for Experimental Medicine; School of Medicine, Dentistry, and Biomedical Science, Queen's University Belfast; Belfast United Kingdom
| | - Richard Reynolds
- Division of Brain Sciences, Faculty of Medicine; Imperial College London; London United Kingdom
| | - James W. Neal
- Institute of Life Sciences; Swansea University Medical School; Swansea United Kingdom
| | - Owain W. Howell
- Institute of Life Sciences; Swansea University Medical School; Swansea United Kingdom
- Division of Brain Sciences, Faculty of Medicine; Imperial College London; London United Kingdom
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