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Miclea A, Zurawski J, Healy BC, Saxena S, Lokhande H, Quattrucci M, Chu R, Weiner HL, Bakshi R, Chitnis T. Novel serum biomarker associations with 7 Tesla MRI-defined cortical lesions, leptomeningeal enhancement, and deep gray matter volume in early multiple sclerosis. Sci Rep 2025; 15:12032. [PMID: 40200016 PMCID: PMC11978968 DOI: 10.1038/s41598-025-95229-x] [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: 10/27/2024] [Accepted: 03/19/2025] [Indexed: 04/10/2025] Open
Abstract
Gray matter demyelinating lesions, brain atrophy and meningeal inflammation are hypothesized to be relevant in multiple sclerosis (MS) disease pathogenesis, though their relationship to immune alterations in early MS is not well characterized. This study aims to investigate correlations between the concentrations of 112 serum proteins and 7 Tesla MRI-defined measures of disease severity in patients with early MS. In this analysis, patients with CIS or MS having a 7 Tesla brain MRI and blood sample both within five years of MS diagnosis were included (n = 57). Correlational analysis was adjusted for sex, age, and disease duration. Correlation between serum proteins and MRI-defined cortical and thalamic gray matter lesions, leptomeningeal enhancement (presence and foci number), deep gray matter (DGM) structure volumes, whole brain parenchymal volume and total T2 white matter lesion volume was assessed. In this study, cortical lesions were associated with higher IL-15, TNF-alpha, and BAFF levels, and lower levels of FcRL2. Leptomeningeal enhancement was associated with higher levels of PLXNB3 and lower levels of nCDase and CNTN5. Higher IL-1B levels correlated with lower DGM volume while higher levels of CDH6, SIGLEC9, and HAGH correlated with higher DGM volume. These novel associations between serum immune proteins and 7 T MRI outcomes may have relevance as disease biomarkers in early stages of MS.
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Affiliation(s)
- Andrei Miclea
- Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA
| | - Jonathan Zurawski
- Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, 02115, USA
| | - Brian C Healy
- Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, 02115, USA
- Biostatistics Center, Massachusetts General Hospital, 60 Fenwood Rd, Boston, MA, 02115, USA
| | - Shrishti Saxena
- Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA
| | - Hrishikesh Lokhande
- Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA
| | - Molly Quattrucci
- Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA
| | - Renxin Chu
- Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, 02115, USA
| | - Howard L Weiner
- Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, 02115, USA
| | - Rohit Bakshi
- Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, 02115, USA
- Department of Radiology, Harvard Medical School, Boston, MA, 02115, USA
| | - Tanuja Chitnis
- Brigham Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, 02115, USA.
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2
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Wood GK, Sargent BF, Ahmad ZUA, Tharmaratnam K, Dunai C, Egbe FN, Martin NH, Facer B, Pendered SL, Rogers HC, Hübel C, van Wamelen DJ, Bethlehem RAI, Giunchiglia V, Hellyer PJ, Trender W, Kalsi G, Needham E, Easton A, Jackson TA, Cunningham C, Upthegrove R, Pollak TA, Hotopf M, Solomon T, Pett SL, Shaw PJ, Wood N, Harrison NA, Miller KL, Jezzard P, Williams G, Duff EP, Williams S, Zelaya F, Smith SM, Keller S, Broome M, Kingston N, Husain M, Vincent A, Bradley J, Chinnery P, Menon DK, Aggleton JP, Nicholson TR, Taylor JP, David AS, Carson A, Bullmore E, Breen G, Hampshire A, Michael BD, Paddick SM, Leek EC. Posthospitalization COVID-19 cognitive deficits at 1 year are global and associated with elevated brain injury markers and gray matter volume reduction. Nat Med 2025; 31:245-257. [PMID: 39312956 PMCID: PMC11750706 DOI: 10.1038/s41591-024-03309-8] [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: 12/28/2023] [Accepted: 09/18/2024] [Indexed: 09/25/2024]
Abstract
The spectrum, pathophysiology and recovery trajectory of persistent post-COVID-19 cognitive deficits are unknown, limiting our ability to develop prevention and treatment strategies. We report the 1-year cognitive, serum biomarker and neuroimaging findings from a prospective, national study of cognition in 351 COVID-19 patients who required hospitalization, compared with 2,927 normative matched controls. Cognitive deficits were global, associated with elevated brain injury markers and reduced anterior cingulate cortex volume 1 year after COVID-19. Severity of the initial infective insult, postacute psychiatric symptoms and a history of encephalopathy were associated with the greatest deficits. There was strong concordance between subjective and objective cognitive deficits. Longitudinal follow-up in 106 patients demonstrated a trend toward recovery. Together, these findings support the hypothesis that brain injury in moderate to severe COVID-19 may be immune-mediated, and should guide the development of therapeutic strategies.
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Affiliation(s)
- Greta K Wood
- Department of Clinical Infection, Microbiology & Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
- Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - Brendan F Sargent
- Department of Clinical Infection, Microbiology & Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Zain-Ul-Abideen Ahmad
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Kukatharmini Tharmaratnam
- Department of Health Data Science, Institute of Population Health, University of Liverpool, Liverpool, UK
| | - Cordelia Dunai
- Department of Clinical Infection, Microbiology & Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
- NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Franklyn N Egbe
- Department of Clinical Infection, Microbiology & Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Naomi H Martin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Bethany Facer
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Sophie L Pendered
- Department of Clinical Infection, Microbiology & Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Henry C Rogers
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Christopher Hübel
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National Centre for Register-based Research, Aarhus Business and Social Sciences, Aarhus University, Aarhus, Denmark
- Department of Pediatric Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Daniel J van Wamelen
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Parkinson's Foundation Center of Excellence, King's College Hospital, London, UK
- Department of Neurology; Centre of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | | | | | - Peter J Hellyer
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - William Trender
- Department of Brain Sciences, Imperial College London, London, UK
| | - Gursharan Kalsi
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Edward Needham
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Ava Easton
- Department of Clinical Infection, Microbiology & Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
- Encephalitis International, Malton, UK
| | - Thomas A Jackson
- Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK
| | - Colm Cunningham
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Rachel Upthegrove
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
| | - Thomas A Pollak
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Matthew Hotopf
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Tom Solomon
- Department of Clinical Infection, Microbiology & Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
- NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
- The Pandemic Institute, University of Liverpool, Liverpool, UK
- Department of Neurology, Walton Centre Foundation Trust, Liverpool, UK
| | - Sarah L Pett
- MRC Clinical Trials Unit, UCL, London, UK
- Institute of Clinical Trials and Methodology, UCL, London, UK
- Institute for Global Health, UCL, London, UK
| | - Pamela J Shaw
- Division of Neuroscience, School of Medicine and Population Health, University of Sheffield, Sheffield, UK
- Sheffield Institute for Translational Neuroscience, NIHR Biomedical Research Centre, University of Sheffield, Sheffield, UK
| | - Nicholas Wood
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, UCL, London, UK
- UCL Genetics Institute, Division of Biosciences, UCL, London, UK
| | - Neil A Harrison
- Cardiff University Brain Research Imaging Centre, School of Medicine, Cardiff University, Cardiff, UK
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Peter Jezzard
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Guy Williams
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Eugene P Duff
- UK Dementia Research Institute, Department of Brain Sciences, Imperial College London, London, UK
| | - Steven Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust, London, UK
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Simon Keller
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Matthew Broome
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
- Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
| | - Nathalie Kingston
- NIHR Bioresource, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Department of Haematology, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Masud Husain
- Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Angela Vincent
- Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - John Bradley
- NIHR Bioresource, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Patrick Chinnery
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- MRC Mitochondrial Biology Unit, University of Cambridge, Cambridge, UK
| | - David K Menon
- Section of Perioperative, Acute, Critical Care and Emergency Medicine, Department of Medicine, University of Cambridge, Cambridge, UK
| | | | - Timothy R Nicholson
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
- Neuropsychiatry Research and Education Group, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - John-Paul Taylor
- Translational and Clinical Research Institute, Newcastle University, Newcastle, UK
- Old Age Psychiatry, Tyne and Wear NHS Trust, Newcastle, UK
| | - Anthony S David
- Department of Psychiatry, Institute of Mental Health, UCL, London, UK
| | - Alan Carson
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Ed Bullmore
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Department of Psychiatry, Institute of Behavioural and Clinical Neuroscience, University of Cambridge, Cambridge, UK
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust, London, UK
| | - Adam Hampshire
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Benedict D Michael
- Department of Clinical Infection, Microbiology & Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK.
- NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK.
- Department of Neurology, Walton Centre Foundation Trust, Liverpool, UK.
| | - Stella-Maria Paddick
- Translational and Clinical Research Institute, Newcastle University, Newcastle, UK
- Department of Old Age Psychiatry, Gateshead Health NHS Foundation Trust, Gateshead, UK
- Millenium Institute for Care Research (MICARE), Santiago, Chile
| | - E Charles Leek
- Department of Psychology, Institute of Population Health, Institute of Life and Human Sciences, University of Liverpool, Liverpool, UK
- School of Psychology, University of Southampton, Southampton, UK
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3
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Zhukovsky P, Tio ES, Coughlan G, Bennett DA, Wang Y, Hohman TJ, Pizzagalli DA, Mulsant BH, Voineskos AN, Felsky D. Genetic influences on brain and cognitive health and their interactions with cardiovascular conditions and depression. Nat Commun 2024; 15:5207. [PMID: 38890310 PMCID: PMC11189393 DOI: 10.1038/s41467-024-49430-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 06/04/2024] [Indexed: 06/20/2024] Open
Abstract
Approximately 40% of dementia cases could be prevented or delayed by modifiable risk factors related to lifestyle and environment. These risk factors, such as depression and vascular disease, do not affect all individuals in the same way, likely due to inter-individual differences in genetics. However, the precise nature of how genetic risk profiles interact with modifiable risk factors to affect brain health is poorly understood. Here we combine multiple data resources, including genotyping and postmortem gene expression, to map the genetic landscape of brain structure and identify 367 loci associated with cortical thickness and 13 loci associated with white matter hyperintensities (P < 5×10-8), with several loci also showing a significant association with cognitive function. We show that among 220 unique genetic loci associated with cortical thickness in our genome-wide association studies (GWAS), 95 also showed evidence of interaction with depression or cardiovascular conditions. Polygenic risk scores based on our GWAS of inferior frontal thickness also interacted with hypertension in predicting executive function in the Canadian Longitudinal Study on Aging. These findings advance our understanding of the genetic underpinning of brain structure and show that genetic risk for brain and cognitive health is in part moderated by treatable mid-life factors.
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Grants
- P30 AG072975 NIA NIH HHS
- U01 AG046152 NIA NIH HHS
- U01 AG061356 NIA NIH HHS
- R01 AG017917 NIA NIH HHS
- P30 AG010161 NIA NIH HHS
- R01 AG059716 NIA NIH HHS
- Wellcome Trust
- R01 AG015819 NIA NIH HHS
- Gouvernement du Canada | Instituts de Recherche en Santé du Canada | CIHR Skin Research Training Centre (Skin Research Training Centre)
- D.F. is supported by the generous contributions from the Michael and Sonja Koerner Foundation and the Krembil Family Foundation. D.F. is also supported in part by the Centre for Addiction and Mental Health (CAMH) Discovery Fund and CIHR.
- PZ was funded by the Canadian Institute of Health Research Postdoctoral Fellowship.
- Over the past 3 years, D.A.P has received consulting fees from Albright Stonebridge Group, Boehringer Ingelheim, Compass Pathways, Engrail Therapeutics, Neumora Therapeutics (formerly BlackThorn Therapeutics), Neurocrine Biosciences, Neuroscience Software, Otsuka, Sunovion, and Takeda; he has received honoraria from the Psychonomic Society and American Psychological Association (for editorial work) and from Alkermes; he has received research funding from the Brain and Behavior Research Foundation, the Dana Foundation, Millennium Pharmaceuticals, Wellcome Leap MCPsych, and NIMH; he has received stock options from Compass Pathways, Engrail Therapeutics, Neumora Therapeutics, and Neuroscience Software. No funding from these entities was used to support the current work, and all views expressed are solely those of the authors.
- U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
- A.N.V. currently receives funding from CIHR, the NIH, the National Sciences and Engineering Research Council (NSERC), the CAMH Foundation, and the University of Toronto. E.S.T. was funded by the Ontario Graduate Scholarship.
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Affiliation(s)
- Peter Zhukovsky
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, M5T 1R8, Canada
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Earvin S Tio
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Gillian Coughlan
- Department of Neurology, Massachusetts General Hospital, Boston, MA, 02129, USA
| | - David A Bennett
- Department of Neurological Sciences, RUSH Medical College, Chicago, IL, 60612, USA
| | - Yanling Wang
- Department of Neurological Sciences, RUSH Medical College, Chicago, IL, 60612, USA
| | - Timothy J Hohman
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Diego A Pizzagalli
- Department of Psychiatry, Harvard Medical School and Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, 02478, USA
| | - Benoit H Mulsant
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, M5T 1R8, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8, Canada.
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, M5T 1R8, Canada.
| | - Daniel Felsky
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, M5T 1R8, Canada.
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, M5S 1A8, Canada.
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, M5S 1A8, Canada.
- Rotman Research Institute, Baycrest Hospital, Toronto, ON, M6A 2E1, Canada.
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4
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Sun D, Wang R, Du Q, Zhang Y, Chen H, Shi Z, Wang X, Zhou H. Causal relationship between multiple sclerosis and cortical structure: a Mendelian randomization study. J Transl Med 2024; 22:83. [PMID: 38245759 PMCID: PMC10800041 DOI: 10.1186/s12967-024-04892-7] [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: 06/29/2023] [Accepted: 01/13/2024] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Observational studies have suggested an association between multiple sclerosis (MS) and cortical structure, but the results have been inconsistent. OBJECTIVE We used two-sample Mendelian randomization (MR) to assess the causal relationship between MS and cortical structure. METHODS MS data as the exposure trait, including 14,498 cases and 24,091 controls, were obtained from the International Multiple Sclerosis Genetics Consortium. Genome-wide association study (GWAS) data for cortical surface area (SAw/nw) and thickness (THw/nw) in 51,665 individuals of European ancestry were obtained from the ENIGMA Consortium. The inverse-variance weighted (IVW) method was used as the primary analysis for MR. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. Enrichment analysis was performed on MR analyses filtered by sensitivity analysis. RESULTS After IVW and sensitivity analysis filtering, only six surviving MR results provided suggestive evidence supporting a causal relationship between MS and cortical structure, including lingual SAw (p = .0342, beta (se) = 5.7127 (2.6969)), parahippocampal SAw (p = .0224, beta (se) = 1.5577 (0.6822)), rostral middle frontal SAw (p = .0154, beta (se) = - 9.0301 (3.7281)), cuneus THw (p = .0418, beta (se) = - 0.0020 (0.0010)), lateral orbitofrontal THw (p = .0281, beta (se) = 0.0025 (0.0010)), and lateral orbitofrontal THnw (p = .0417, beta (se) = 0.0029 (0.0014)). Enrichment analysis suggested that leukocyte cell-related pathways, JAK-STAT signaling pathway, NF-kappa B signaling pathway, cytokine-cytokine receptor interaction, and prolactin signaling pathway may be involved in the effect of MS on cortical morphology. CONCLUSION Our results provide evidence supporting a causal relationship between MS and cortical structure. Enrichment analysis suggests that the pathways mediating brain morphology abnormalities in MS patients are mainly related to immune and inflammation-driven pathways.
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Affiliation(s)
- Dongren Sun
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Rui Wang
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Qin Du
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Ying Zhang
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Hongxi Chen
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Ziyan Shi
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Xiaofei Wang
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China.
| | - Hongyu Zhou
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China.
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Jamali F, Aldughmi M, Atiani S, Al-Radaideh A, Dahbour S, Alhattab D, Khwaireh H, Arafat S, Jaghbeer JA, Rahmeh R, Abu Moshref K, Bawaneh H, Hassuneh MR, Hourani B, Ababneh O, Alghwiri A, Awidi A. Human Umbilical Cord-Derived Mesenchymal Stem Cells in the Treatment of Multiple Sclerosis Patients: Phase I/II Dose-Finding Clinical Study. Cell Transplant 2024; 33:9636897241233045. [PMID: 38450623 PMCID: PMC10921855 DOI: 10.1177/09636897241233045] [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: 09/12/2023] [Revised: 01/08/2024] [Accepted: 01/31/2024] [Indexed: 03/08/2024] Open
Abstract
Multiple sclerosis (MS) is a chronic neuro-inflammatory disease resulting in disabilities that negatively impact patients' life quality. While current treatment options do not reverse the course of the disease, treatment using mesenchymal stromal/stem cells (MSC) is promising. There has yet to be a consensus on the type and dose of MSC to be used in MS. This work aims to study the safety and efficacy of two treatment protocols of MSCs derived from the umbilical cord (UC-MSCs) and their secretome. The study included two groups of MS patients; Group A received two intrathecal doses of UC-MSCs, and Group B received a single dose. Both groups received UC-MSCs conditioned media 3 months post-treatment. Adverse events in the form of a clinical checklist and extensive laboratory tests were performed. Whole transcriptome analysis was performed on patients' cells at baseline and post-treatment. Results showed that all patients tolerated the cellular therapy without serious adverse events. The general disability scale improved significantly in both groups at 6 months post-treatment. Examining specific aspects of the disease revealed more parameters that improved in Group A compared to Group B patients, including a significant increase in the (CD3+CD4+) expressing lymphocytes at 12 months post-treatment. In addition, better outcomes were noted regarding lesion load, cortical thickness, manual dexterity, and information processing speed. Both protocols impacted the transcriptome of treated participants with genes, transcription factors, and microRNAs (miRNAs) differentially expressed compared to baseline. Inflammation-related and antigen-presenting (HLA-B) genes were downregulated in both groups. In contrast, TNF-alpha, TAP-1, and miR142 were downregulated only in Group A. The data presented indicate that both protocols are safe. Furthermore, it suggests that administering two doses of stem cells can be more beneficial to MS patients. Larger multisite studies should be initiated to further examine similar or higher doses of MSCs.
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Affiliation(s)
- Fatima Jamali
- Cell Therapy Center, The University of Jordan, Amman, Jordan
| | - Mayis Aldughmi
- Department of Physical Therapy, School of Rehabilitation Sciences, The University of Jordan, Amman, Jordan
| | - Serin Atiani
- Data Science Department, Princess Sumaya University for Technology, Amman, Jordan
| | - Ali Al-Radaideh
- Division of Neurology, Department of Internal Medicine, Faculty of Medicine, Jordan University Hospital, The University of Jordan, Amman, Jordan
- Laboratory of Nanomedicine, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Said Dahbour
- Department of Medical Imaging, Faculty of Applied Medical Sciences, The Hashemite University, Zarqa, Jordan
| | - Dana Alhattab
- Cell Therapy Center, The University of Jordan, Amman, Jordan
- Department of Medical Radiography, School of Health Sciences, University of Doha for Science and Technology, Doha, Qatar
| | - Hind Khwaireh
- Cell Therapy Center, The University of Jordan, Amman, Jordan
| | - Sally Arafat
- Cell Therapy Center, The University of Jordan, Amman, Jordan
| | - Joud Al Jaghbeer
- Department of Physical Therapy, School of Rehabilitation Sciences, The University of Jordan, Amman, Jordan
| | - Reem Rahmeh
- Cell Therapy Center, The University of Jordan, Amman, Jordan
| | | | - Hisham Bawaneh
- Hematology Department, Jordan University Hospital, Amman, Jordan
| | - Mona R. Hassuneh
- Department of Applied Biology, College of Sciences, University of Sharjah, Sharjah, United Arab Emirates
- Department of Biology, Faculty of Sciences, The University of Jordan, Amman, Jordan
| | - Bayan Hourani
- Cell Therapy Center, The University of Jordan, Amman, Jordan
| | - Osameh Ababneh
- Department of Ophthalmology, Jordan University Hospital, School of Medicine, The University of Jordan, Amman, Jordan
| | - Alia Alghwiri
- Department of Physical Therapy, School of Rehabilitation Sciences, The University of Jordan, Amman, Jordan
| | - Abdalla Awidi
- Cell Therapy Center, The University of Jordan, Amman, Jordan
- Hematology Department, Jordan University Hospital, Amman, Jordan
- Department of Internal Medicine, School of Medicine, The University of Jordan, Amman, Jordan
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6
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Ghezzi A, Neuteboom RF. Neurofilament Light Chain in Adult and Pediatric Multiple Sclerosis: A Promising Biomarker to Better Characterize Disease Activity and Personalize MS Treatment. Neurol Ther 2023; 12:1867-1881. [PMID: 37682513 PMCID: PMC10630260 DOI: 10.1007/s40120-023-00535-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 08/15/2023] [Indexed: 09/09/2023] Open
Abstract
Many biological markers have been explored in multiple sclerosis (MS) to better quantify disease burden and better evaluate response to treatments, beyond clinical and MRI data. Among these, neurofilament light chain (Nf-L), although non-specific for this disease and found to be increased in other neurological conditions, has been shown to be the most promising biomarker for assessing axonal damage in MS, with a definite role in predicting the development of MS in patients at the first neurological episode suggestive of MS, and also in a preclinical phase. There is strong evidence that Nf-L levels are increased more in relapsing versus stable MS patients, and that they predict future disease evolution (relapses, progression, MRI measures of activity/progression) in MS patients, providing information on response to therapy, helping to anticipate clinical decisions in patients with an apparently stable evolution, and identifying patient non-responders to disease-modifying treatments. Moreover, Nf-L can contribute to the better understanding of the mechanisms of demyelination and axonal damage in adult and pediatric MS. A fundamental requirement for its clinical use is the accurate standardization of normal values, corrected for confounding factors, in particular age, sex, body mass index, and presence of comorbidities. In this review, a guide is provided to update clinicians on the use of Nf-L in clinical activity.
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Affiliation(s)
- Angelo Ghezzi
- Dipartimento di Scienze della Salute, Università Piemonte Orientale A. Avogadro, Via Solaroli 17, 28100, Novara, Italy.
| | - R F Neuteboom
- Department of Neurology, ErasMS Center, Erasmus MC, PO Box 2040, 3000, Rotterdam, The Netherlands
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7
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Savitz J, Goeckner BD, Ford BN, Kent Teague T, Zheng H, Harezlak J, Mannix R, Tugan Muftuler L, Brett BL, McCrea MA, Meier TB. The effects of cytomegalovirus on brain structure following sport-related concussion. Brain 2023; 146:4262-4273. [PMID: 37070698 PMCID: PMC10545519 DOI: 10.1093/brain/awad126] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 03/06/2023] [Accepted: 03/27/2023] [Indexed: 04/19/2023] Open
Abstract
The neurotrophic herpes virus cytomegalovirus is a known cause of neuropathology in utero and in immunocompromised populations. Cytomegalovirus is reactivated by stress and inflammation, possibly explaining the emerging evidence linking it to subtle brain changes in the context of more minor disturbances of immune function. Even mild forms of traumatic brain injury, including sport-related concussion, are major physiological stressors that produce neuroinflammation. In theory, concussion could predispose to the reactivation of cytomegalovirus and amplify the effects of physical injury on brain structure. However, to our knowledge this hypothesis remains untested. This study evaluated the effect of cytomegalovirus serostatus on white and grey matter structure in a prospective study of athletes with concussion and matched contact-sport controls. Athletes who sustained concussion (n = 88) completed MRI at 1, 8, 15 and 45 days post-injury; matched uninjured athletes (n = 73) completed similar visits. Cytomegalovirus serostatus was determined by measuring serum IgG antibodies (n = 30 concussed athletes and n = 21 controls were seropositive). Inverse probability of treatment weighting was used to adjust for confounding factors between athletes with and without cytomegalovirus. White matter microstructure was assessed using diffusion kurtosis imaging metrics in regions previously shown to be sensitive to concussion. T1-weighted images were used to quantify mean cortical thickness and total surface area. Concussion-related symptoms, psychological distress, and serum concentration of C-reactive protein at 1 day post-injury were included as exploratory outcomes. Planned contrasts compared the effects of cytomegalovirus seropositivity in athletes with concussion and controls, separately. There was a significant effect of cytomegalovirus on axial and radial kurtosis in athletes with concussion but not controls. Cytomegalovirus positive athletes with concussion showed greater axial (P = 0.007, d = 0.44) and radial (P = 0.010, d = 0.41) kurtosis than cytomegalovirus negative athletes with concussion. Similarly, there was a significant association of cytomegalovirus with cortical thickness in athletes with concussion but not controls. Cytomegalovirus positive athletes with concussion had reduced mean cortical thickness of the right hemisphere (P = 0.009, d = 0.42) compared with cytomegalovirus negative athletes with concussion and showed a similar trend for the left hemisphere (P = 0.036, d = 0.33). There was no significant effect of cytomegalovirus on kurtosis fractional anisotropy, surface area, symptoms and C-reactive protein. The results raise the possibility that cytomegalovirus infection contributes to structural brain abnormalities in the aftermath of concussion perhaps via an amplification of concussion-associated neuroinflammation. More work is needed to identify the biological pathways underlying this process and to clarify the clinical relevance of this putative viral effect.
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Affiliation(s)
- Jonathan Savitz
- Laureate Institute for Brain Research, Tulsa, OK 74136, USA
- Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK 74119, USA
| | - Bryna D Goeckner
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Bart N Ford
- Department of Pharmacology and Physiology, Oklahoma State University Center for Health Sciences, Tulsa, OK 74107, USA
| | - T Kent Teague
- Department of Psychiatry, The University of Oklahoma School of Community Medicine, Tulsa, OK 74135, USA
- Department of Surgery, The University of Oklahoma School of Community Medicine, Tulsa, OK 74135, USA
- Department of Pharmaceutical Sciences, University of Oklahoma College of Pharmacy, Tulsa, OK 74135, USA
| | - Haixia Zheng
- Laureate Institute for Brain Research, Tulsa, OK 74136, USA
| | - Jaroslaw Harezlak
- Department of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Bloomington, IN 47405, USA
| | - Rebekah Mannix
- Division of Emergency Medicine, Boston Children’s Hospital, Boston, MA 02115, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - L Tugan Muftuler
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Benjamin L Brett
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Michael A McCrea
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Timothy B Meier
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
- Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA
- Department of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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8
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Sun J, Zhao W, Xie Y, Zhou F, Wu L, Li Y, Li H, Li Y, Zeng C, Han X, Liu Y, Zhang N. Personalized estimates of morphometric similarity in multiple sclerosis and neuromyelitis optica spectrum disorders. Neuroimage Clin 2023; 39:103454. [PMID: 37343344 PMCID: PMC10509529 DOI: 10.1016/j.nicl.2023.103454] [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: 03/10/2023] [Revised: 05/21/2023] [Accepted: 06/16/2023] [Indexed: 06/23/2023]
Abstract
Brain morphometric alterations involve multiple brain regions on progression of the disease in multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) and exhibit age-related degenerative changes during the pathological aging. Recent advance in brain morphometry as measured using MRI have leveraged Person-Based Similarity Index (PBSI) approach to assess the extent of within-diagnosis similarity or heterogeneity of brain neuroanatomical profiles between individuals of healthy populations and validate in neuropsychiatric disorders. Brain morphometric changes throughout the lifespan would be invaluable for understanding regional variability of age-related structural degeneration and the substrate of inflammatory demyelinating disease. Here, we aimed to quantify the neuroanatomical profiles with PBSI measures of cortical thickness (CT) and subcortical volumes (SV) in 263 MS, 207 NMOSD, and 338 healthy controls (HC) from six separate central datasets (aged 11-80). We explored the between-group comparisons of PBSI measures, as well as the advancing age and sex effects on PBSI measures. Compared to NMOSD, MS showed a lower extent of within-diagnosis similarity. Significant differences in regional contributions to PBSI score were observed in 29 brain regions between MS and NMOSD (P < 0.05/164, Bonferroni corrected), of which bilateral cerebellum in MS and bilateral parahippocampal gyrus in NMOSD represented the highest divergence between the two patient groups, with a high similarity effect within each group. The PBSI scores were generally lower with advancing age, but their associations showed different patterns depending on the age range. For MS, CT profiles were significantly negatively correlated with age until the early 30 s (ρ = -0.265, P = 0.030), while for NMOSD, SV profiles were significantly negatively correlated with age with 51 year-old and older (ρ = -0.365, P = 0.008). The current study suggests that PBSI approach could be used to quantify the variation in brain morphometric changes in CNS inflammatory demyelinating disease, and exhibited a greater neuroanatomical heterogeneity pattern in MS compared with NMOSD. Our results reveal that, as an MR marker, PBSI may be sensitive to distribute the disease-associated grey matter diversity and complexity. Disease-driven production of regionally selective and age stage-dependency changes in the neuroanatomical profile of MS and NMOSD should be considered to facilitate the prediction of clinical outcomes and assessment of treatment responses.
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Affiliation(s)
- Jie Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Wenjin Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yingying Xie
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Fuqing Zhou
- Department of Radiology, The First Afliated Hospital, Nanchang University, Nanchang 330006, Jiangxi Province, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi Province, China
| | - Lin Wu
- Department of Radiology, The First Afliated Hospital, Nanchang University, Nanchang 330006, Jiangxi Province, China
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi Province, China
| | - Yuxin Li
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Haiqing Li
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Yongmei Li
- Department of Radiology, The First Afliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Chun Zeng
- Department of Radiology, The First Afliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Xuemei Han
- Department of Neurology, China-Japan Union Hospital of Jilin University, Changchun 130031, Jilin Province, China
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119, The West Southern 4th Ring Road, Fengtai District, Beijing 100070, China
| | - Ningnannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
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9
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van Dam M, de Jong BA, Willemse EAJ, Nauta IM, Huiskamp M, Klein M, Moraal B, de Geus-Driessen S, Geurts JJG, Uitdehaag BMJ, Teunissen CE, Hulst HE. A multimodal marker for cognitive functioning in multiple sclerosis: the role of NfL, GFAP and conventional MRI in predicting cognitive functioning in a prospective clinical cohort. J Neurol 2023:10.1007/s00415-023-11676-4. [PMID: 37101095 DOI: 10.1007/s00415-023-11676-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 03/16/2023] [Accepted: 03/17/2023] [Indexed: 04/28/2023]
Abstract
BACKGROUND Cognitive impairment in people with MS (PwMS) has primarily been investigated using conventional imaging markers or fluid biomarkers of neurodegeneration separately. However, the single use of these markers do only partially explain the large heterogeneity found in PwMS. OBJECTIVE To investigate the use of multimodal (bio)markers: i.e., serum and cerebrospinal fluid (CSF) levels of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) and conventional imaging markers in predicting cognitive functioning in PwMS. METHODS Eighty-two PwMS (56 females, disease duration = 14 ± 9 years) underwent neuropsychological and neurological examination, structural magnetic resonance imaging, blood sampling and lumbar puncture. PwMS were classified as cognitively impaired (CI) if scoring ≥ 1.5SD below normative scores on ≥ 20% of test scores. Otherwise, PwMS were defined as cognitively preserved (CP). Association between fluid and imaging (bio)markers were investigated, as well as binary logistics regression to predict cognitive status. Finally, a multimodal marker was calculated using statistically important predictors of cognitive status. RESULTS Only higher NfL levels (in serum and CSF) correlated with worse processing speed (r = - 0.286, p = 0.012 and r = - 0.364, p = 0.007, respectively). sNfL added unique variance in the prediction of cognitive status on top of grey matter volume (NGMV), p = 0.002). A multimodal marker of NGMV and sNfL yielded most promising results in predicting cognitive status (sensitivity = 85%, specificity = 58%). CONCLUSION Fluid and imaging (bio)markers reflect different aspects of neurodegeneration and cannot be used interchangeably as markers for cognitive functioning in PwMS. The use of a multimodal marker, i.e., the combination of grey matter volume and sNfL, seems most promising for detecting cognitive deficits in MS.
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Affiliation(s)
- Maureen van Dam
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.
| | - Brigit A de Jong
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Eline A J Willemse
- Neurochemistry Lab, Department of Clinical Chemistry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
- Neurology Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Biomedicine and Clinical Research, Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Ilse M Nauta
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Marijn Huiskamp
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Martin Klein
- Department of Medical Psychology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Bastiaan Moraal
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Sanne de Geus-Driessen
- Department of Medical Psychology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Bernard M J Uitdehaag
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Lab, Department of Clinical Chemistry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Hanneke E Hulst
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Institute of Psychology, Health, Medical and Neuropsychology Unit, Leiden University, Wassenaarseweg 52, Leiden, The Netherlands
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10
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Pivovarova-Ramich O, Zimmermann HG, Paul F. Multiple sclerosis and circadian rhythms: Can diet act as a treatment? Acta Physiol (Oxf) 2023; 237:e13939. [PMID: 36700353 DOI: 10.1111/apha.13939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 12/15/2022] [Accepted: 01/24/2023] [Indexed: 01/27/2023]
Abstract
Multiple sclerosis (MS) is an autoimmune inflammatory and neurodegenerative disease of the central nervous system (CNS) with increasing incidence and prevalence. MS is associated with inflammatory and metabolic disturbances that, as preliminary human and animal data suggest, might be mediated by disruption of circadian rhythmicity. Nutrition habits can influence the risk for MS, and dietary interventions may be effective in modulating MS disease course. Chronotherapeutic approaches such as time-restricted eating (TRE) may benefit people with MS by stabilizing the circadian clock and restoring immunological and metabolic rhythms, thus potentially counteracting disease progression. This review provides a summary of selected studies on dietary intervention in MS, circadian rhythms, and their disruption in MS, including clock gene variations, circadian hormones, and retino-hypothalamic tract changes. Furthermore, we present studies that reported diurnal variations in MS, which might result from circadian disruption. And lastly, we suggest how chrononutritive approaches like TRE might counteract MS disease activity.
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Affiliation(s)
- Olga Pivovarova-Ramich
- Research Group Molecular Nutritional Medicine, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- Department of Endocrinology, Diabetes and Nutrition, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Hanna Gwendolyn Zimmermann
- Experimental and Clinical Research Center, Max-Delbrück Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max-Delbrück Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
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11
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Sen MK, Hossain MJ, Mahns DA, Brew BJ. Validity of serum neurofilament light chain as a prognostic biomarker of disease activity in multiple sclerosis. J Neurol 2023; 270:1908-1930. [PMID: 36520240 DOI: 10.1007/s00415-022-11507-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 11/24/2022] [Accepted: 11/25/2022] [Indexed: 12/23/2022]
Abstract
Multiple sclerosis (MS) is a chronic demyelinating and neuroinflammatory disease of the human central nervous system with complex pathoetiology, heterogeneous presentations and an unpredictable course of disease progression. There remains an urgent need to identify and validate a biomarker that can reliably predict the initiation and progression of MS as well as identify patient responses to disease-modifying treatments/therapies (DMTs). Studies exploring biomarkers in MS and other neurodegenerative diseases currently focus mainly on cerebrospinal fluid (CSF) analyses, which are invasive and impractical to perform on a repeated basis. Recent studies, replacing CSF with peripheral blood samples, have revealed that the elevation of serum neurofilament light chain (sNfL) in the clinical stages of MS is, potentially, an ideal prognostic biomarker for predicting disease progression and for possibly guiding treatment decisions. However, there are unresolved factors (the definition of abnormal values of sNfL concentration, the standardisation of measurement and the amount of change in sNfL concentration that is significant) that are preventing its use as a biomarker in routine clinical practice for MS. This updated review critiques these recent findings and highlights areas for focussed work to facilitate the use of sNfL as a prognostic biomarker in MS management.
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Affiliation(s)
- Monokesh K Sen
- School of Medicine, Western Sydney University, Penrith, NSW, Australia
- Peter Duncan Neuroscience Research Unit, St Vincent's Centre for Applied Medical Research, Darlinghurst, Sydney, 2010, Australia
- Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, 2006, Australia
| | - Md Jakir Hossain
- School of Biomedical Sciences, UNSW Sydney, Sydney, NSW, 2052, Australia
| | - David A Mahns
- School of Medicine, Western Sydney University, Penrith, NSW, Australia
| | - Bruce J Brew
- Peter Duncan Neuroscience Research Unit, St Vincent's Centre for Applied Medical Research, Darlinghurst, Sydney, 2010, Australia.
- School of Biomedical Sciences, UNSW Sydney, Sydney, NSW, 2052, Australia.
- Department of Neurology, St Vincent's Hospital, Darlinghurst, 2010, Australia.
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12
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Buchmann A, Pirpamer L, Pinter D, Voortman M, Helmlinger B, Pichler A, Maceski AM, Benkert P, Bachmaier G, Ropele S, Reindl M, Leppert D, Kuhle J, Enzinger C, Khalil M. High serum neurofilament light chain levels correlate with brain atrophy and physical disability in multiple sclerosis. Eur J Neurol 2023; 30:1389-1399. [PMID: 36779855 DOI: 10.1111/ene.15742] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/23/2022] [Accepted: 02/02/2023] [Indexed: 02/14/2023]
Abstract
BACKGROUND AND PURPOSE Serum neurofilament light chain (sNfL) is a promising biomarker of neuroaxonal damage in persons with multiple sclerosis (pwMS). In cross-sectional studies, sNfL has been associated with disease activity and brain magnetic resonance imaging (MRI) changes; however, it is still unclear to what extent in particular high sNfL levels impact on subsequent disease evolution. METHODS sNfL was quantified by an ultrasensitive single molecule array (Simoa) in 199 pwMS (median age = 34.2 years, 64.3% female) and 49 controls. All pwMS underwent 3-T MRI to assess global and compartmental normalized brain volumes, T2-lesion load, and cortical mean thickness. Follow-up data and serum samples were available in 144 pwMS (median follow-up time = 3.8 years). Linear and binary logistic models were used to estimate the independent contribution of sNfL for changes in MRI and Expanded Disability Status Scale (EDSS). Age-corrected sNfL z-scores from a normative database of healthy controls were used for sensitivity analyses. RESULTS High sNfL levels at baseline were associated with atrophy measures of the whole brain (standardized beta coefficient βj = -0.352, p < 0.001), white matter (βj = -0.229, p = 0.007), thalamus (βj = -0.372, p = 0.004), and putamen (βj = -1.687, p = 0.012). pwMS with high levels of sNfL at baseline and follow-up had a greater risk of EDSS worsening (p = 0.007). CONCLUSIONS Already single time point elevation of sNfL has a distinct effect on brain volume changes over a short-term period, and repeated high levels of sNfL indicate accumulating physical disability. Serial assessment of sNfL may provide added value in the clinical management of pwMS.
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Affiliation(s)
| | - Lukas Pirpamer
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Daniela Pinter
- Department of Neurology, Medical University of Graz, Graz, Austria
| | | | | | | | - Aleksandra Maleska Maceski
- Department of Neurology, University Hospital and University of Basel, Basel, Switzerland.,Multiple Sclerosis Center and Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB), Departments of Biomedicine and Clinical Research, University Hospital and University of Basel, Basel, Switzerland
| | - Pascal Benkert
- Department of Neurology, University Hospital and University of Basel, Basel, Switzerland.,Multiple Sclerosis Center and Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB), Departments of Biomedicine and Clinical Research, University Hospital and University of Basel, Basel, Switzerland
| | - Gerhard Bachmaier
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Markus Reindl
- Clinical Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - David Leppert
- Department of Neurology, University Hospital and University of Basel, Basel, Switzerland.,Multiple Sclerosis Center and Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB), Departments of Biomedicine and Clinical Research, University Hospital and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Department of Neurology, University Hospital and University of Basel, Basel, Switzerland.,Multiple Sclerosis Center and Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB), Departments of Biomedicine and Clinical Research, University Hospital and University of Basel, Basel, Switzerland
| | - Christian Enzinger
- Department of Neurology, Medical University of Graz, Graz, Austria.,Division of Neuroradiology, Vascular and Interventional Radiology, Medical University of Graz, Graz, Austria
| | - Michael Khalil
- Department of Neurology, Medical University of Graz, Graz, Austria
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13
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Schindler P, Aktas O, Ringelstein M, Wildemann B, Jarius S, Paul F, Ruprecht K. Glial fibrillary acidic protein as a biomarker in neuromyelitis optica spectrum disorder: a current review. Expert Rev Clin Immunol 2023; 19:71-91. [PMID: 36378751 DOI: 10.1080/1744666x.2023.2148657] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
INTRODUCTION Neuromyelitis optica spectrum disorder (NMOSD) is a relapsing, often debilitating neuroinflammatory disease, whose predominant clinical manifestations are longitudinally extensive transverse myelitis and optic neuritis. About 80% of the patients with an NMOSD phenotype have pathogenic autoantibodies against the astrocyte water channel aquaporin-4 (AQP4-IgG). While therapeutic options for NMOSD have greatly expanded in recent years, well-established biomarkers for prognosis or treatment response are still lacking. Glial fibrillary acidic protein (GFAP) is mainly expressed in astrocytes and can be detected in cerebrospinal fluid (CSF) and blood of patients with NMOSD. AREAS COVERED Here, we comprehensively review the current knowledge on GFAP as a biomarker in NMOSD. EXPERT OPINION In patients with AQP4-IgG+ NMOSD, GFAP levels are elevated in CSF and serum during acute attacks and correlate with disability, consistent with the pathophysiology of this antibody-mediated astrocytopathy. Serum GFAP levels tend to be higher in AQP4-IgG+ NMOSD than in its differential diagnoses, multiple sclerosis, and myelin oligodendrocyte antibody-associated disease. Importantly, serum GFAP levels in AQP4-IgG+ NMOSD during remission may be predictive of future disease activity. Serial serum GFAP measurements are emerging as a biomarker to monitor disease activity in AQP4-IgG+ NMOSD and could have the potential for application in clinical practice.
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Affiliation(s)
- Patrick Schindler
- Experimental and Clinical Research Center, A Cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and the Charité Universitätsmedizin Berlin, Berlin, Germany.,Department of Neurology, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Orhan Aktas
- Department of Neurology, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Marius Ringelstein
- Department of Neurology, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.,Department of Neurology, Center for Neurology and Neuropsychiatry, LVR-Klinikum, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Brigitte Wildemann
- Molecular Neuroimmunology Group, Department of Neurology, University of Heidelberg, Heidelberg, Germany
| | - Sven Jarius
- Molecular Neuroimmunology Group, Department of Neurology, University of Heidelberg, Heidelberg, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, A Cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and the Charité Universitätsmedizin Berlin, Berlin, Germany.,Department of Neurology, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Klemens Ruprecht
- Department of Neurology, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
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Dykukha I, Essner U, Schreiber H, Raithel LM, Penner IK. Effects of Sativex Ⓡ on cognitive function in patients with multiple sclerosis: A systematic review and meta-analysis. Mult Scler Relat Disord 2022; 68:104173. [PMID: 36174323 DOI: 10.1016/j.msard.2022.104173] [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: 01/05/2022] [Revised: 09/05/2022] [Accepted: 09/08/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Cognitive impairment is a common manifestation of multiple sclerosis (MS). OBJECTIVE To assess by systematic review and meta-analysis available evidence regarding the impact of nabiximols oromucosal spray on cognition in patients with MS. METHODS A systematic literature search of clinical studies (all types, any comparator) that measured cognitive function in patients with MS spasticity treated with nabiximols. Meta-analysis for cognitive endpoints was not possible due to heterogenous measurement instruments and outcomes. Meta-analysis was performed for adverse events (AEs) of special interest (cognition disorders) reported in randomized controlled trials (RCTs) of nabiximols versus placebo in patients with MS (with or without spasticity). Certainty of evidence and risk of bias were assessed. RESULTS Seven clinical studies (three RCTs) directly assessing cognitive function were included in the qualitative analysis. There was no consistent evidence to suggest that nabiximols causes cognitive impairment as assessed by a range of specific psychometric instruments across cognitive domains. Thirteen double-blind, placebo-controlled RCTs (nabiximols, n = 964; placebo, n = 904) were included in the meta-analysis of cognitive AEs. Most cognitive AEs (30 of 32 events, 93.8%) reported with nabiximols in MS patients occurred with not in-label use, i.e., dosage >12 sprays per day and/or not administered primarily for treatment of spasticity. CONCLUSIONS Within the limitations of the review, we can conclude that no detrimental effects of nabiximols on cognitive function were observed in patients with MS spasticity during up to 12 months follow-up and that cognitive AEs were rare and occurred only when nabiximols was not used according to its approved label.
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Affiliation(s)
- Igor Dykukha
- Medical Affairs, Almirall Hermal GmbH, Reinbek, Germany
| | - Ute Essner
- O. Meany Consultancy GmbH, Hamburg, Germany
| | - Herbert Schreiber
- Neurological Practice Center, Neuropoint Academy, NTD & Neurosys, Ulm, Germany
| | - Lina Marie Raithel
- COGITO Center for Applied Neurocognition and Neuropsychological Research, Düsseldorf, Germany
| | - Iris-Katharina Penner
- Department of Neurology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.
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Mahamud Z, Burman J, Zelano J. Temporal trends of epilepsy in multiple sclerosis. Acta Neurol Scand 2022; 146:492-498. [PMID: 35852006 PMCID: PMC9795966 DOI: 10.1111/ane.13671] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 06/23/2022] [Accepted: 07/06/2022] [Indexed: 12/30/2022]
Abstract
OBJECTIVES Epilepsy is associated with advanced multiple sclerosis (MS). We aimed to investigate whether the incidence of epilepsy in MS has been affected by the introduction of disease-modifying treatments (DMT) for MS. MATERIALS AND METHODS This retrospective study included 14,557 patients from the Swedish MS register with MS onset between 1991 and 2018. Incident diagnoses of epilepsy or any seizure were identified through cross-linkage with the National Patient Register. Next, yearly prevalence of epilepsy as well as 5- and 10 years incidence of epilepsy or any seizure for consecutive years of MS onset were estimated, the latter with Kaplan-Meier analysis. Cox regression was used to adjust the association between the year of MS onset and incidence of epilepsy for baseline variables. RESULTS Prevalence of epilepsy in the MS cohort increased from 0.34% in 1991 to 2.54% in 2018 (yearly odds: 1.26 [1.22, 1.29]). The 5 years incidence rate of epilepsy, ranging from 0.4% (95% CI 0.008-0.79%) to 1.3% (95% CI 0.71-1.89%), and the 10 years incidence rate of epilepsy, ranging from 1.1% (95% CI 0.31-1.88%) to 2.6% (95% CI 1.22-3.97%) showed no significant trends (p = .147 and p = .418, respectively). Similarly, no significant trends were found for the incidences of any seizure. The incidence trends of epilepsy remained not significant after adjusting for sex, MS onset type (relapsing or progressive onset), or age at MS onset. CONCLUSIONS Our findings do not support the hypothesis that the introduction of novel DMT for MS has reduced the incidence of epilepsy among MS patients.
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Affiliation(s)
- Zamzam Mahamud
- Department of Clinical Neuroscience, Sahlgrenska AcademyUniversity of Gothenburg and Sahlgrenska University HospitalGothenburgSweden
| | - Joachim Burman
- Department of NeuroscienceUppsala UniversityUppsalaSweden
| | - Johan Zelano
- Department of Clinical Neuroscience, Sahlgrenska AcademyUniversity of Gothenburg and Sahlgrenska University HospitalGothenburgSweden,Wallenberg Centre for Molecular and Translational MedicineSahlgrenska academyGothenburg
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Tiu VE, Popescu BO, Enache II, Tiu C, Terecoasa E, Panea CA. Serum and CSF Biomarkers Predict Active Early Cognitive Decline Rather Than Established Cognitive Impairment at the Moment of RRMS Diagnosis. Diagnostics (Basel) 2022; 12:diagnostics12112571. [PMID: 36359416 PMCID: PMC9689215 DOI: 10.3390/diagnostics12112571] [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: 07/16/2022] [Revised: 10/19/2022] [Accepted: 10/20/2022] [Indexed: 11/16/2022] Open
Abstract
(1) Background: Cognitive impairment (CI) begins early in the evolution of multiple sclerosis (MS) but may only become obvious in the later stages of the disease. Little data is available regarding predictive biomarkers for early, active cognitive decline in relapse remitting MS (RRMS) patients. (2) Methods: 50 RRMS patients in the first 6 months following diagnosis were included. The minimum follow-up was one year. Biomarker samples were collected at baseline, 3-, 6- and 12-month follow-up. Cognitive performance was assessed at baseline and 12-month follow-up; (3) Results: Statistically significant differences were found for patients undergoing active cognitive decline for sNfL z-scores at baseline and 3 months, CSF NfL baseline values, CSF Aβ42 and the Bremso score as well. The logistic regression model based on these 5 variables was statistically significant, χ2(4) = 22.335, p < 0.0001, R2 = 0.671, with a sensitivity of 57.1%, specificity of 97.4%, a positive predictive value of 80% and a negative predictive value of 92.6%. (4) Conclusions: Our study shows that serum biomarkers (adjusted sNfL z-scores at baseline and 3 months) and CSF biomarkers (CSF NfL baseline values, CSF Aβ42), combined with a clinical score (BREMSO), can accurately predict an early cognitive decline for RRMS patients at the moment of diagnosis.
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Affiliation(s)
- Vlad Eugen Tiu
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, Elias University Emergency Hospital, 011461 Bucharest, Romania
| | - Bogdan Ovidiu Popescu
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, Colentina Clinical Hospital, 020125 Bucharest, Romania
- Correspondence:
| | - Iulian Ion Enache
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, University Emergency Hospital of Bucharest, 050098 Bucharest, Romania
| | - Cristina Tiu
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, University Emergency Hospital of Bucharest, 050098 Bucharest, Romania
| | - Elena Terecoasa
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, University Emergency Hospital of Bucharest, 050098 Bucharest, Romania
| | - Cristina Aura Panea
- Neurology Department, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Neurology Department, Elias University Emergency Hospital, 011461 Bucharest, Romania
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17
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Barile B, Ashtari P, Stamile C, Marzullo A, Maes F, Durand-Dubief F, Van Huffel S, Sappey-Marinier D. Classification of multiple sclerosis clinical profiles using machine learning and grey matter connectome. Front Robot AI 2022; 9:926255. [PMID: 36313252 PMCID: PMC9608344 DOI: 10.3389/frobt.2022.926255] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 08/18/2022] [Indexed: 11/24/2022] Open
Abstract
Purpose: The main goal of this study is to investigate the discrimination power of Grey Matter (GM) thickness connectome data between Multiple Sclerosis (MS) clinical profiles using statistical and Machine Learning (ML) methods. Materials and Methods: A dataset composed of 90 MS patients acquired at the MS clinic of Lyon Neurological Hospital was used for the analysis. Four MS profiles were considered, corresponding to Clinical Isolated Syndrome (CIS), Relapsing-Remitting MS (RRMS), Secondary Progressive MS (SPMS), and Primary Progressive MS (PPMS). Each patient was classified in one of these profiles by our neurologist and underwent longitudinal MRI examinations including T1-weighted image acquisition at each examination, from which the GM tissue was segmented and the cortical GM thickness measured. Following the GM parcellation using two different atlases (FSAverage and Glasser 2016), the morphological connectome was built and six global metrics (Betweenness Centrality (BC), Assortativity (r), Transitivity (T), Efficiency (E g ), Modularity (Q) and Density (D)) were extracted. Based on their connectivity metrics, MS profiles were first statistically compared and second, classified using four different learning machines (Logistic Regression, Random Forest, Support Vector Machine and AdaBoost), combined in a higher level ensemble model by majority voting. Finally, the impact of the GM spatial resolution on the MS clinical profiles classification was analyzed. Results: Using binary comparisons between the four MS clinical profiles, statistical differences and classification performances higher than 0.7 were observed. Good performances were obtained when comparing the two early clinical forms, RRMS and PPMS (F1 score of 0.86), and the two neurodegenerative profiles, PPMS and SPMS (F1 score of 0.72). When comparing the two atlases, slightly better performances were obtained with the Glasser 2016 atlas, especially between RRMS with PPMS (F1 score of 0.83), compared to the FSAverage atlas (F1 score of 0.69). Also, the thresholding value for graph binarization was investigated suggesting more informative graph properties in the percentile range between 0.6 and 0.8. Conclusion: An automated pipeline was proposed for the classification of MS clinical profiles using six global graph metrics extracted from the GM morphological connectome of MS patients. This work demonstrated that GM morphological connectivity data could provide good classification performances by combining four simple ML models, without the cost of long and complex MR techniques, such as MR diffusion, and/or deep learning architectures.
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Affiliation(s)
- Berardino Barile
- CREATIS (UMR 5220 CNRS & U1294 INSERM), Université Claude Bernard Lyon1, INSA-Lyon, Université de Lyon, Lyon, France
- Department of Electrical Engineering, KU Leuven, Leuven, Belgium
| | - Pooya Ashtari
- Department of Electrical Engineering, KU Leuven, Leuven, Belgium
| | | | - Aldo Marzullo
- Department of Mathematics and Computer Science, University of Calabria, Rende, Italy
| | - Frederik Maes
- Department of Electrical Engineering, KU Leuven, Leuven, Belgium
| | - Françoise Durand-Dubief
- CREATIS (UMR 5220 CNRS & U1294 INSERM), Université Claude Bernard Lyon1, INSA-Lyon, Université de Lyon, Lyon, France
- Hôpital Neurologique, Service de Neurologie, Hospices Civils de Lyon, Bron, France
| | | | - Dominique Sappey-Marinier
- CREATIS (UMR 5220 CNRS & U1294 INSERM), Université Claude Bernard Lyon1, INSA-Lyon, Université de Lyon, Lyon, France
- CERMEP–Imagerie du Vivant, Université de Lyon, Lyon, France
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Williams T, Tur C, Eshaghi A, Doshi A, Chan D, Binks S, Wellington H, Heslegrave A, Zetterberg H, Chataway J. Serum neurofilament light and MRI predictors of cognitive decline in patients with secondary progressive multiple sclerosis: Analysis from the MS-STAT randomised controlled trial. Mult Scler 2022; 28:1913-1926. [PMID: 35946107 PMCID: PMC9493411 DOI: 10.1177/13524585221114441] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 06/28/2022] [Accepted: 07/01/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Cognitive impairment affects 50%-75% of people with secondary progressive multiple sclerosis (PwSPMS). Improving our ability to predict cognitive decline may facilitate earlier intervention. OBJECTIVE The main aim of this study was to assess the relationship between longitudinal changes in cognition and baseline serum neurofilament light chain (sNfL) in PwSPMS. In a multi-modal analysis, MRI variables were additionally included to determine if sNfL has predictive utility beyond that already established through MRI. METHODS Participants from the MS-STAT trial underwent a detailed neuropsychological test battery at baseline, 12 and 24 months. Linear mixed models were used to assess the relationships between cognition, sNfL, T2 lesion volume (T2LV) and normalised regional brain volumes. RESULTS Median age and Expanded Disability Status Score (EDSS) were 51 and 6.0. Each doubling of baseline sNfL was associated with a 0.010 [0.003-0.017] point per month faster decline in WASI Full Scale IQ Z-score (p = 0.008), independent of T2LV and normalised regional volumes. In contrast, lower baseline volume of the transverse temporal gyrus was associated with poorer current cognitive performance (0.362 [0.026-0.698] point reduction per mL, p = 0.035), but not change in cognition. The results were supported by secondary analyses on individual cognitive components. CONCLUSION Elevated sNfL is associated with faster cognitive decline, independent of T2LV and regional normalised volumes.
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Affiliation(s)
- Thomas Williams
- Queen Square Multiple Sclerosis Centre,
Department of Neuroinflammation, UCL Queen Square Institute of Neurology,
University College London, Russell Square House, 10-12 Russell Square,
London WC1B 5EH, UK
- Queen Square Multiple Sclerosis Centre,
Department of Neuroinflammation, UCL Queen Square Institute of Neurology,
University College London, London, UK
| | - Carmen Tur
- Queen Square Multiple Sclerosis Centre,
Department of Neuroinflammation, UCL Queen Square Institute of Neurology,
University College London, London, UK/Multiple Sclerosis Centre of Catalonia
(Cemcat), Vall d’Hebron Institute of Research, Vall d’Hebron Barcelona
Hospital Campus, Barcelona, Spain
| | - Arman Eshaghi
- Queen Square Multiple Sclerosis Centre,
Department of Neuroinflammation, UCL Queen Square Institute of Neurology,
University College London, London, UK
| | - Anisha Doshi
- Queen Square Multiple Sclerosis Centre,
Department of Neuroinflammation, UCL Queen Square Institute of Neurology,
University College London, London, UK
| | - Dennis Chan
- UCL Institute of Cognitive Neuroscience,
University College London, London, UK
| | - Sophie Binks
- Department of Neurology, Nuffield Department of
Clinical Neurosciences, Oxford, UK
| | - Henny Wellington
- UK Dementia Research Institute, University
College London, London, UK
| | - Amanda Heslegrave
- UK Dementia Research Institute, University
College London, London, UK
| | - Henrik Zetterberg
- UK Dementia Research Institute, University
College London, London, UK/ Department of Psychiatry and Neurochemistry,
Institute of Neuroscience and Physiology, The Sahlgrenska Academy,
University of Gothenburg, Mölndal, Sweden/Clinical Neurochemistry
Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden/Department of
Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London,
UK/Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong
Kong, China
| | - Jeremy Chataway
- Queen Square Multiple Sclerosis Centre,
Department of Neuroinflammation, UCL Queen Square Institute of Neurology,
University College London, London, UK/National Institute for Health
Research, University College London Hospitals, Biomedical Research Centre,
London, UK/Medical Research Council Clinical Trials Unit, Institute of
Clinical Trials and Methodology, University College London, London, UK
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19
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Ning L, Wang B. Neurofilament light chain in blood as a diagnostic and predictive biomarker for multiple sclerosis: A systematic review and meta-analysis. PLoS One 2022; 17:e0274565. [PMID: 36103562 PMCID: PMC9473405 DOI: 10.1371/journal.pone.0274565] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 08/30/2022] [Indexed: 11/18/2022] Open
Abstract
Background
Neurofilament light chain (NfL) in cerebrospinal fluid (CSF) is a biomarker of multiple sclerosis (MS). However, CSF sampling is invasive and has limited the clinical application. With the development of highly sensitive single-molecule assay, the accurate quantification of the very low NfL levels in blood become feasible. As evidence being accumulated, we performed a meta-analysis to evaluate the diagnostic and predictive value of blood NfL in MS patients.
Methods
We performed literature search on PubMed, EMBASE, Web of Science and Cochrane Library from inception to May 31, 2022. The blood NfL differences between MS vs. controls, MS vs. clinically isolated syndrome (CIS), progressive MS (PMS) vs. relapsing-remitting MS (RRMS), and MS in relapse vs. MS in remission were estimated by standard mean difference (SMD) and corresponding 95% confidence interval (CI). Pooled hazard ratio (HR) and 95%CI were calculated to predict time to reach Expanded Disability Status Scale (EDSS) score≥4.0 and to relapse.
Results
A total of 28 studies comprising 6545 MS patients and 2477 controls were eligible for meta-analysis of diagnosis value, and 5 studies with 4444 patients were synthesized in analysis of predictive value. Blood NfL levels were significantly higher in MS patients vs. age-matched controls (SMD = 0.64, 95%CI 0.44–0.85, P<0.001), vs. non-matched controls (SMD = 0.76, 95%CI 0.56–0.96, P<0.001) and vs. CIS patients (SMD = 0.30, 95%CI 0.18–0.42, P<0.001), in PMS vs. RRMS (SMD = 0.56, 95%CI 0.27–0.85, P<0.001), and in relapsed patients vs. remitted patients (SMD = 0.54, 95%CI 0.16–0.92, P = 0.005). Patients with high blood NfL levels had shorter time to reach EDSS score≥4.0 (HR = 2.36, 95%CI 1.32–4.21, P = 0.004) but similar time to relapse (HR = 1.32, 95%CI 0.90–1.93, P = 0.155) compared to those with low NfL levels.
Conclusion
As far as we know, this is the first meta-analysis evaluating the diagnosis and predictive value of blood NfL in MS. The present study indicates blood NfL may be a useful biomarker in diagnosing MS, distinguishing MS subtypes and predicting disease worsening in the future.
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Affiliation(s)
- Liangxia Ning
- Department of Neurology, Yuncheng Central Hospital, The Eighth Shanxi Medical University, Yuncheng, China
| | - Bin Wang
- Department of Neurology, Yuncheng Central Hospital, The Eighth Shanxi Medical University, Yuncheng, China
- * E-mail:
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20
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Yalachkov Y, Anschütz V, Jakob J, Schaller-Paule MA, Schäfer JH, Reiländer A, Friedauer L, Behrens M, Steffen F, Bittner S, Foerch C. Brain-derived neurotrophic factor and neurofilament light chain in cerebrospinal fluid are inversely correlated with cognition in Multiple Sclerosis at the time of diagnosis. Mult Scler Relat Disord 2022; 63:103822. [DOI: 10.1016/j.msard.2022.103822] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 04/03/2022] [Accepted: 04/21/2022] [Indexed: 12/21/2022]
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21
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Raimo S, Trojano L, Gaita M, d'Onofrio F, Spitaleri D, Santangelo G. Relationship between apathy and cognitive dysfunctions in Multiple Sclerosis: a 4-year prospective longitudinal study. Mult Scler Relat Disord 2022; 63:103929. [DOI: 10.1016/j.msard.2022.103929] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/10/2022] [Accepted: 05/27/2022] [Indexed: 12/01/2022]
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22
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Biernacki T, Kokas Z, Sandi D, Füvesi J, Fricska-Nagy Z, Faragó P, Kincses TZ, Klivényi P, Bencsik K, Vécsei L. Emerging Biomarkers of Multiple Sclerosis in the Blood and the CSF: A Focus on Neurofilaments and Therapeutic Considerations. Int J Mol Sci 2022; 23:ijms23063383. [PMID: 35328802 PMCID: PMC8951485 DOI: 10.3390/ijms23063383] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 03/12/2022] [Accepted: 03/17/2022] [Indexed: 12/12/2022] Open
Abstract
INTRODUCTION Multiple Sclerosis (MS) is the most common immune-mediated chronic neurodegenerative disease of the central nervous system (CNS) affecting young people. This is due to the permanent disability, cognitive impairment, and the enormous detrimental impact MS can exert on a patient's health-related quality of life. It is of great importance to recognise it in time and commence adequate treatment at an early stage. The currently used disease-modifying therapies (DMT) aim to reduce disease activity and thus halt disability development, which in current clinical practice are monitored by clinical and imaging parameters but not by biomarkers found in blood and/or the cerebrospinal fluid (CSF). Both clinical and radiological measures routinely used to monitor disease activity lack information on the fundamental pathophysiological features and mechanisms of MS. Furthermore, they lag behind the disease process itself. By the time a clinical relapse becomes evident or a new lesion appears on the MRI scan, potentially irreversible damage has already occurred in the CNS. In recent years, several biomarkers that previously have been linked to other neurological and immunological diseases have received increased attention in MS. Additionally, other novel, potential biomarkers with prognostic and diagnostic properties have been detected in the CSF and blood of MS patients. AREAS COVERED In this review, we summarise the most up-to-date knowledge and research conducted on the already known and most promising new biomarker candidates found in the CSF and blood of MS patients. DISCUSSION the current diagnostic criteria of MS relies on three pillars: MRI imaging, clinical events, and the presence of oligoclonal bands in the CSF (which was reinstated into the diagnostic criteria by the most recent revision). Even though the most recent McDonald criteria made the diagnosis of MS faster than the prior iteration, it is still not an infallible diagnostic toolset, especially at the very early stage of the clinically isolated syndrome. Together with the gold standard MRI and clinical measures, ancillary blood and CSF biomarkers may not just improve diagnostic accuracy and speed but very well may become agents to monitor therapeutic efficacy and make even more personalised treatment in MS a reality in the near future. The major disadvantage of these biomarkers in the past has been the need to obtain CSF to measure them. However, the recent advances in extremely sensitive immunoassays made their measurement possible from peripheral blood even when present only in minuscule concentrations. This should mark the beginning of a new biomarker research and utilisation era in MS.
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Affiliation(s)
- Tamás Biernacki
- Albert Szent-Györgyi Clinical Centre, Department of Neurology, Faculty of General Medicine, University of Szeged, 6725 Szeged, Hungary; (T.B.); (Z.K.); (D.S.); (J.F.); (Z.F.-N.); (P.F.); (T.Z.K.); (P.K.); (K.B.)
| | - Zsófia Kokas
- Albert Szent-Györgyi Clinical Centre, Department of Neurology, Faculty of General Medicine, University of Szeged, 6725 Szeged, Hungary; (T.B.); (Z.K.); (D.S.); (J.F.); (Z.F.-N.); (P.F.); (T.Z.K.); (P.K.); (K.B.)
| | - Dániel Sandi
- Albert Szent-Györgyi Clinical Centre, Department of Neurology, Faculty of General Medicine, University of Szeged, 6725 Szeged, Hungary; (T.B.); (Z.K.); (D.S.); (J.F.); (Z.F.-N.); (P.F.); (T.Z.K.); (P.K.); (K.B.)
| | - Judit Füvesi
- Albert Szent-Györgyi Clinical Centre, Department of Neurology, Faculty of General Medicine, University of Szeged, 6725 Szeged, Hungary; (T.B.); (Z.K.); (D.S.); (J.F.); (Z.F.-N.); (P.F.); (T.Z.K.); (P.K.); (K.B.)
| | - Zsanett Fricska-Nagy
- Albert Szent-Györgyi Clinical Centre, Department of Neurology, Faculty of General Medicine, University of Szeged, 6725 Szeged, Hungary; (T.B.); (Z.K.); (D.S.); (J.F.); (Z.F.-N.); (P.F.); (T.Z.K.); (P.K.); (K.B.)
| | - Péter Faragó
- Albert Szent-Györgyi Clinical Centre, Department of Neurology, Faculty of General Medicine, University of Szeged, 6725 Szeged, Hungary; (T.B.); (Z.K.); (D.S.); (J.F.); (Z.F.-N.); (P.F.); (T.Z.K.); (P.K.); (K.B.)
| | - Tamás Zsigmond Kincses
- Albert Szent-Györgyi Clinical Centre, Department of Neurology, Faculty of General Medicine, University of Szeged, 6725 Szeged, Hungary; (T.B.); (Z.K.); (D.S.); (J.F.); (Z.F.-N.); (P.F.); (T.Z.K.); (P.K.); (K.B.)
- Albert Szent-Györgyi Clinical Centre, Department of Radiology, Albert Szent-Györgyi Faculty of Medicine, University of Szeged, 6725 Szeged, Hungary
| | - Péter Klivényi
- Albert Szent-Györgyi Clinical Centre, Department of Neurology, Faculty of General Medicine, University of Szeged, 6725 Szeged, Hungary; (T.B.); (Z.K.); (D.S.); (J.F.); (Z.F.-N.); (P.F.); (T.Z.K.); (P.K.); (K.B.)
| | - Krisztina Bencsik
- Albert Szent-Györgyi Clinical Centre, Department of Neurology, Faculty of General Medicine, University of Szeged, 6725 Szeged, Hungary; (T.B.); (Z.K.); (D.S.); (J.F.); (Z.F.-N.); (P.F.); (T.Z.K.); (P.K.); (K.B.)
| | - László Vécsei
- Albert Szent-Györgyi Clinical Centre, Department of Neurology, Faculty of General Medicine, University of Szeged, 6725 Szeged, Hungary; (T.B.); (Z.K.); (D.S.); (J.F.); (Z.F.-N.); (P.F.); (T.Z.K.); (P.K.); (K.B.)
- MTA-SZTE Neuroscience Research Group, University of Szeged, 6725 Szeged, Hungary
- Correspondence: ; Tel.: +36-62-545-356; Fax: +36-62-545-597
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23
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Virgilio E, Vecchio D, Crespi I, Puricelli C, Barbero P, Galli G, Cantello R, Dianzani U, Comi C. Cerebrospinal fluid biomarkers and cognitive functions at multiple sclerosis diagnosis. J Neurol 2022; 269:3249-3257. [PMID: 35088141 DOI: 10.1007/s00415-021-10945-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 12/21/2021] [Accepted: 12/22/2021] [Indexed: 02/06/2023]
Abstract
Cognitive impairment (CI) is a frequent and disabling symptom in Multiple Sclerosis (MS). Axonal damage may contribute to CI development from early stages. Nevertheless, no biomarkers are at the moment available to track CI in MS patients. We aimed to explore the correlation of cerebrospinal fluid (CSF) axonal biomarkers, in particular: light-chain neurofilaments (NFL), Tau, and Beta-amyloid protein (Abeta) in MS patients with CI at the diagnosis. 62 newly diagnosed MS patients were enrolled, and cognition was evaluated using the Brief International Cognitive Assessment for MS (BICAMS) battery. CSF NFL, Abeta, and Tau levels were determined with commercial ELISA. Patients with CI (45.1%) did not differ for demographic, clinical, and MRI characteristics (except for lower educational level), but they displayed greater neurodegeneration, exhibiting higher mean CSF Tau protein (162.1 ± 52.96 pg/ml versus 132.2 ± 63.86 pg/ml p:0.03). No differences were observed for Abeta and NFL. The number of impaired tests and Tau were significantly correlated (r:0.32 p:0.01). Tau was higher in particular in patients with slowed information processing speed (IPS) (p:0.006) and a linear regression analysis accounting for EDSS, MRI, and MS subtype confirmed Tau as a weak predictor of IPS and cognitive impairment. In conclusion, CI has an important burden on the quality of life of MS patients and should be looked for even at diagnosis. Axonal damage biomarkers, and in particular Tau, seem to reflect cognition impairment in the early stages.
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Affiliation(s)
- Eleonora Virgilio
- Department of Translational Medicine, Neurology Unit, Maggiore Della Carità Hospital, University of Piemonte Orientale, Corso Mazzini 18, 28100, Novara, Italy. .,Phd Program in Medical Sciences and Biotechnologies, Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy. .,Department of Translational Medicine, Neurology Unit, S. Andrea Hospital, University of Piemonte Orientale, Vercelli, Italy.
| | - Domizia Vecchio
- Department of Translational Medicine, Neurology Unit, Maggiore Della Carità Hospital, University of Piemonte Orientale, Corso Mazzini 18, 28100, Novara, Italy.,Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases (IRCAD), University of Piemonte Orientale, Novara, Italy
| | - Ilaria Crespi
- Department of Health Sciences, Clinical Biochemistry, University of Piemonte Orientale, Novara, Italy
| | - Chiara Puricelli
- Department of Health Sciences, Clinical Biochemistry, University of Piemonte Orientale, Novara, Italy
| | - Paolo Barbero
- Department of Translational Medicine, Neurology Unit, Maggiore Della Carità Hospital, University of Piemonte Orientale, Corso Mazzini 18, 28100, Novara, Italy
| | - Giulia Galli
- Department of Translational Medicine, Neurology Unit, Maggiore Della Carità Hospital, University of Piemonte Orientale, Corso Mazzini 18, 28100, Novara, Italy
| | - Roberto Cantello
- Department of Translational Medicine, Neurology Unit, Maggiore Della Carità Hospital, University of Piemonte Orientale, Corso Mazzini 18, 28100, Novara, Italy
| | - Umberto Dianzani
- Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases (IRCAD), University of Piemonte Orientale, Novara, Italy.,Department of Health Sciences, Clinical Biochemistry, University of Piemonte Orientale, Novara, Italy
| | - Cristoforo Comi
- Department of Translational Medicine, Neurology Unit, S. Andrea Hospital, University of Piemonte Orientale, Vercelli, Italy.,Department of Health Sciences, Interdisciplinary Research Center of Autoimmune Diseases (IRCAD), University of Piemonte Orientale, Novara, Italy
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