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Centonze D, Di Sapio A, Brescia Morra V, Colombo E, Inglese M, Paolicelli D, Salvetti M, Furlan R. Steps toward the implementation of neurofilaments in multiple sclerosis: patient profiles to be prioritized in clinical practice. Front Neurol 2025; 16:1571605. [PMID: 40224313 PMCID: PMC11987710 DOI: 10.3389/fneur.2025.1571605] [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: 02/05/2025] [Accepted: 03/11/2025] [Indexed: 04/15/2025] Open
Abstract
Multiple sclerosis (MS) is a chronic central nervous system disease characterized by neurodegeneration and inflammation. Neurofilament light chain (NfL), a protein released during axonal injury, has gained recognition as a potential biomarker for monitoring MS progression and treatment response. Evidence indicates that blood NfL (bNfL) offers a minimally invasive, cost-effective tool for tracking neuroaxonal damage. Regular bNfL assessments can identify subclinical disease activity, guide treatment intensification, and support individualized care. However, bNfL level evaluation is currently not optimized in Italian clinical practice. This work examines the utility of bNfL monitoring in clinical practice, focusing on optimizing its use within specific patient profiles, especially in resource-limited settings. bNfL testing, particularly in targeted MS patient profiles, including stable patients exhibiting subclinical signs of disease activity, such as fatigue, and patients off-treatment, represents a promising adjunct for personalized disease management. Its integration into clinical practice, alongside MRI and clinical assessments, can enhance decision-making and improve care efficiency, especially in settings with limited MRI resources. Further research is needed to standardize testing protocols and establish disease-specific cutoffs.
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Affiliation(s)
- Diego Centonze
- Department of Systems Medicine, Tor Vergata University, Rome, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | - Alessia Di Sapio
- Department of Neurology, Multiple Sclerosis Regional Referral Centre (CReSM), University Hospital San Luigi Gonzaga, Orbassano, Italy
| | - Vincenzo Brescia Morra
- Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences, Reproductive Sciences and Odontostomatology, Federico II University, Naples, Italy
| | - Elena Colombo
- Multiple Sclerosis Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Matilde Inglese
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Mother-Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Damiano Paolicelli
- Department of Translational Biomedicines and Neurosciences, University of Bari Aldo Moro, Bari, Italy
| | - Marco Salvetti
- IRCCS Neuromed, Pozzilli, Italy
- Department of Neurosciences, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Roberto Furlan
- Vita e Salute San Raffaele University, Milan, Italy
- Clinical Neuroimmunology Unit, Division of Neuroscience, Institute of Experimental Neurology, IRCCS San Raffaele Scientific Institute, Milan, Italy
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2
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De Angelis F, Ammoscato F, Parker RA, Plantone D, Doshi A, John NA, Williams T, Stutters J, MacManus D, Schmierer K, Barkhof F, Weir CJ, Giovannoni G, Chataway J, Gnanapavan S. Neurofilament heavy chain in secondary progressive multiple sclerosis. Mult Scler 2025; 31:303-313. [PMID: 39844621 PMCID: PMC11907725 DOI: 10.1177/13524585241311212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 11/27/2024] [Accepted: 12/11/2024] [Indexed: 01/24/2025]
Abstract
BACKGROUND Biomarkers are needed to track progression in MS trials. Neurofilament heavy chain (NfH) has been underutilized due to assay limitations. OBJECTIVE To investigate the added value of cerebrospinal fluid (CSF) NfH in secondary progressive multiple sclerosis (SPMS) using contemporary immunoassays. METHODS This exploratory study was part of the MS-SMART trial. Clinical assessments (including expanded disability status scale, upper and lower limb function, visual acuity and symbol digit modalities test (SDMT)), CSF and serum sampling were acquired at baseline (n = 54), 48 and 96 weeks. Brain magnetic resonance imagings (MRIs) were obtained at baseline and 96 weeks. The NfL and NfH were measured using single-molecule array assay. RESULTS Baseline CSF NfH and NfL correlated with information processing speed at 96 weeks, with CSF NfH showing stronger correlations (r = -0.49 for SDMT) than CSF NfL (r = -0.37 for SDMT). Baseline CSF NfL predicted poorer hand dexterity at baseline, 48 and 96 weeks. CSF NfH was the only predictor of cortical grey matter at baseline, while baseline CSF NfL was the only predictor of brain atrophy at 96 weeks. Serum neurofilaments showed limited associations. CONCLUSION CSF neurofilaments are better outcomes than serum neurofilaments in small SPMS studies. CSF NfH and NfL variably predict worsening hand function, information processing speed and brain volume loss, possibly reflecting complementary aspects of neurodegeneration.
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Affiliation(s)
- Floriana De Angelis
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health and Care Research, University College London Hospitals Biomedical Research Centre, London, UK
| | | | - Richard A Parker
- Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Domenico Plantone
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Anisha Doshi
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Nevin A John
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Medicine, School of Clinical Sciences, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Monash Health, Melbourne, VIC, Australia
| | - Thomas Williams
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Jonathan Stutters
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Dave MacManus
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | | | - Frederik Barkhof
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health and Care Research, University College London Hospitals Biomedical Research Centre, London, UK
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - Christopher J Weir
- Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh, Edinburgh, UK
| | | | - Jeremy Chataway
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health and Care Research, University College London Hospitals Biomedical Research Centre, London, UK
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3
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De Paoli LF, Kirkcaldie MTK, King AE, Collins JM. Neurofilament heavy phosphorylated epitopes as biomarkers in ageing and neurodegenerative disease. J Neurochem 2025; 169:e16261. [PMID: 39556118 DOI: 10.1111/jnc.16261] [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: 06/17/2024] [Revised: 10/22/2024] [Accepted: 10/24/2024] [Indexed: 11/19/2024]
Abstract
From the day we are born, the nervous system is subject to insult, disease and degeneration. Aberrant phosphorylation states in neurofilaments, the major intermediate filaments of the neuronal cytoskeleton, accompany and mediate many pathological processes in degenerative disease. Neuronal damage, degeneration and death can release these internal components to the extracellular space and eventually the cerebrospinal fluid and blood. Sophisticated assay techniques are increasingly able to detect their presence and phosphorylation states at very low levels, increasing their utility as biomarkers and providing insights and differential diagnosis for the earliest stages of disease. Although a variety of studies focus on single or small clusters of neurofilament phosphorylated epitopes, this review offers a wider perspective of the phosphorylation landscape of the neurofilament heavy subunit, a major intermediate filament component in both ageing and disease.
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Affiliation(s)
- Laura F De Paoli
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Tasmania, Australia
| | - Matthew T K Kirkcaldie
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Tasmania, Australia
| | - Anna E King
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Tasmania, Australia
| | - Jessica M Collins
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Tasmania, Australia
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4
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Koch MW, Camara-Lemarroy C, Strijbis E, Mostert J, Leavitt VM, Repovic P, Bowen JD, Comtois J, Uitdehaag B, Cutter G. Selecting Informative Patients for Phase 2 Progressive Trials in MS: Design Considerations for Phase 2 Clinical Trials in Progressive MS. Mult Scler 2024; 30:41-47. [PMID: 39245930 PMCID: PMC11633076 DOI: 10.1177/13524585241274620] [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: 05/17/2024] [Revised: 07/08/2024] [Accepted: 07/18/2024] [Indexed: 09/10/2024]
Abstract
While relapsing-remitting multiple sclerosis (MS) has many therapeutic options, progressive forms of MS remain largely untreatable. Phase 2 clinical trials are our main tool to advance new treatments for progressive MS. Given the complexities of progressive MS, it will likely require many phase 2 trials to improve its treatment. To conduct informative and efficient phase 2 trials, it is important that such trials are designed in a way that they can identify a successful treatment as quickly and with as few participants as possible. In this topical review, we discuss cohort selection, outcome selection, cohort enrichment, and dosing selection as strategies to optimize the efficiency of phase 2 clinical trials in progressive MS.
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Affiliation(s)
- Marcus W. Koch
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | | | - Eva Strijbis
- Department of Neurology, MS Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Jop Mostert
- Department of Neurology, Rijnstate Hospital, Arnhem, The Netherlands
| | - Victoria M. Leavitt
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Pavle Repovic
- Multiple Sclerosis Center, Swedish Neuroscience Institute, Seattle, WA, USA
| | - James D. Bowen
- Multiple Sclerosis Center, Swedish Neuroscience Institute, Seattle, WA, USA
| | - Jacynthe Comtois
- Department of Medicine, Neurology Service, Hôpital de la Cité-de-la-Santé, Laval, QC, Canada
| | - Bernard Uitdehaag
- Department of Neurology, MS Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Gary Cutter
- Department of Biostatistics, The University of Alabama at Birmingham, Birmingham, AL, USA
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5
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Chataway J, Williams T, Li V, Marrie RA, Ontaneda D, Fox RJ. Clinical trials for progressive multiple sclerosis: progress, new lessons learned, and remaining challenges. Lancet Neurol 2024; 23:277-301. [PMID: 38365380 DOI: 10.1016/s1474-4422(24)00027-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 10/04/2023] [Accepted: 01/12/2024] [Indexed: 02/18/2024]
Abstract
Despite the success of disease-modifying treatments in relapsing multiple sclerosis, for many individuals living with multiple sclerosis, progressive disability continues to accrue. How to interrupt the complex pathological processes underlying progression remains a daunting and ongoing challenge. Since 2014, several immunomodulatory approaches that have modest but clinically meaningful effects have been approved for the management of progressive multiple sclerosis, primarily for people who have active inflammatory disease. The approval of these drugs required large phase 3 trials that were sufficiently powered to detect meaningful effects on disability. New classes of drug, such as Bruton tyrosine-kinase inhibitors, are coming to the end of their trial stages, several candidate neuroprotective compounds have been successful in phase 2 trials, and innovative approaches to remyelination are now also being explored in clinical trials. Work continues to define intermediate outcomes that can provide results in phase 2 trials more quickly than disability measures, and more efficient trial designs, such as multi-arm multi-stage and futility approaches, are increasingly being used. Collaborations between patient organisations, pharmaceutical companies, and academic researchers will be crucial to ensure that future trials maintain this momentum and generate results that are relevant for people living with progressive multiple sclerosis.
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Affiliation(s)
- Jeremy Chataway
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK; Medical Research Council Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK; National Institute for Health Research, University College London Hospitals, Biomedical Research Centre, London, UK.
| | - Thomas Williams
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Vivien Li
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia; Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Ruth Ann Marrie
- Departments of Medicine and Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Robert J Fox
- Mellen Center for Multiple Sclerosis, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
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6
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Zhang H, Yang Y, Zhang J, Huang L, Niu Y, Chen H, Liu Q, Wang R. Oligodendrocytes Play a Critical Role in White Matter Damage of Vascular Dementia. Neuroscience 2024; 538:1-10. [PMID: 37913862 DOI: 10.1016/j.neuroscience.2023.10.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 10/17/2023] [Accepted: 10/21/2023] [Indexed: 11/03/2023]
Abstract
With the deepening of population aging, the treatment of cognitive impairment and dementia is facing increasing challenges. Vascular dementia (VaD) is a cognitive dysfunction caused by brain blood flow damage and one of the most common causes of dementia after Alzheimer's disease. White matter damage in patients with chronic ischemic dementia often occurs before cognitive impairment, and its pathological changes include leukoaraiosis, myelin destruction and oligodendrocyte death. The pathophysiology of vascular dementia is complex, involving a variety of neuronal and vascular lesions. The current proposed mechanisms include calcium overload, oxidative stress, nitrative stress and inflammatory damage, which can lead to hypoxia-ischemia and demyelination. Oligodendrocytes are the only myelinating cells in the central nervous system and closely associated with VaD. In this review article, we intend to further discuss the role of oligodendrocytes in white matter and myelin injury in VaD and the development of anti-myelin injury target drugs.
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Affiliation(s)
- Hexin Zhang
- Key Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, School of Pharmacy, Ningxia Medical University, Yinchuan 750004, Ningxia, China
| | - Yanrong Yang
- Key Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, School of Pharmacy, Ningxia Medical University, Yinchuan 750004, Ningxia, China
| | - Jingjing Zhang
- Key Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, School of Pharmacy, Ningxia Medical University, Yinchuan 750004, Ningxia, China
| | - Li Huang
- Key Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, School of Pharmacy, Ningxia Medical University, Yinchuan 750004, Ningxia, China
| | - Yang Niu
- Key Laboratory of Modernization of Minority Medicine, Ministry of Education, Ningxia medical University, Yinchuan 750004, Ningxia, China
| | - Hua Chen
- Key Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, School of Pharmacy, Ningxia Medical University, Yinchuan 750004, Ningxia, China
| | - Qibing Liu
- Department of Pharmacy, The First Affiliated Hospital of Hainan Medical University, Haikou 570100, China
| | - Rui Wang
- Key Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, School of Pharmacy, Ningxia Medical University, Yinchuan 750004, Ningxia, China.
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7
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Carlson AK, Fox RJ. Pathophysiology, Diagnosis, Treatment and Emerging Neurotherapeutic Targets for Progressive Multiple Sclerosis: The Age of PIRA. Neurol Clin 2024; 42:39-54. [PMID: 37980122 DOI: 10.1016/j.ncl.2023.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2023]
Abstract
More than one million individuals are impacted by progressive forms of multiple sclerosis. The literature examining the management of MS has focused primarily on relapsing forms of disease, and effective therapies targeting progressive mechanisms in MS remains a significant unmet need. Despite this, there are several encouraging potential therapeutics on the horizon. Improved understanding of mechanisms underlying MS progression, identification and validation of biomarkers, identification of novel therapeutic targets, and improved trial design are needed to further propel progress in the management of individuals with progressive forms of MS.
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Affiliation(s)
- Alise K Carlson
- Cleveland Clinic Mellen Center, 9500 Euclid Avenue U10, Cleveland, OH 44195, USA
| | - Robert J Fox
- Cleveland Clinic Mellen Center, 9500 Euclid Avenue U10, Cleveland, OH 44195, USA.
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8
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Ladakis DC, Harrison KL, Smith MD, Solem K, Gadani S, Jank L, Hwang S, Farhadi F, Dewey BE, Fitzgerald KC, Sotirchos ES, Saidha S, Calabresi PA, Bhargava P. Bile acid metabolites predict multiple sclerosis progression and supplementation is safe in progressive disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.17.24301393. [PMID: 38293182 PMCID: PMC10827276 DOI: 10.1101/2024.01.17.24301393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Background Bile acid metabolism is altered in multiple sclerosis (MS) and tauroursodeoxycholic acid (TUDCA) supplementation ameliorated disease in mouse models of MS. Methods Global metabolomics was performed in an observational cohort of people with MS followed by pathway analysis to examine relationships between baseline metabolite levels and subsequent brain and retinal atrophy. A double-blind, placebo-controlled trial, was completed in people with progressive MS (PMS), randomized to receive either TUDCA (2g daily) or placebo for 16 weeks. Participants were followed with serial clinical and laboratory assessments. Primary outcomes were safety and tolerability of TUDCA, and exploratory outcomes included changes in clinical, laboratory and gut microbiome parameters. Results In the observational cohort, higher primary bile acid levels at baseline predicted slower whole brain, brain substructure and specific retinal layer atrophy. In the clinical trial, 47 participants were included in our analyses (21 in placebo arm, 26 in TUDCA arm). Adverse events did not significantly differ between arms (p=0.77). The TUDCA arm demonstrated increased serum levels of multiple bile acids. No significant differences were noted in clinical or fluid biomarker outcomes. Central memory CD4+ and Th1/17 cells decreased, while CD4+ naïve cells increased in the TUDCA arm compared to placebo. Changes in the composition and function of gut microbiota were also noted in the TUDCA arm compared to placebo. Conclusion Bile acid metabolism in MS is linked with brain and retinal atrophy. TUDCA supplementation in PMS is safe, tolerable and has measurable biological effects that warrant further evaluation in larger trials with a longer treatment duration.
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Affiliation(s)
- Dimitrios C. Ladakis
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Kimystian L. Harrison
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Matthew D. Smith
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Krista Solem
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Sachin Gadani
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Larissa Jank
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Soonmyung Hwang
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Farzaneh Farhadi
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Blake E. Dewey
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Kathryn C. Fitzgerald
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Elias S. Sotirchos
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Shiv Saidha
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Peter A. Calabresi
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
| | - Pavan Bhargava
- Johns Hopkins University School of Medicine, Department of Neurology, Baltimore, United States
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Williams T, John N, Calvi A, Bianchi A, De Angelis F, Doshi A, Wright S, Shatila M, Yiannakas MC, Chowdhury F, Stutters J, Ricciardi A, Prados F, MacManus D, Braisher M, Blackstone J, Ciccarelli O, Gandini Wheeler-Kingshott CAM, Barkhof F, Chataway J. Cardiovascular risk factors in secondary progressive multiple sclerosis: A cross-sectional analysis from the MS-STAT2 randomized controlled trial. Eur J Neurol 2023; 30:2769-2780. [PMID: 37318885 DOI: 10.1111/ene.15924] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND AND PURPOSE There is increasing evidence that cardiovascular risk (CVR) contributes to disability progression in multiple sclerosis (MS). CVR is particularly prevalent in secondary progressive MS (SPMS) and can be quantified through validated composite CVR scores. The aim was to examine the cross-sectional relationships between excess modifiable CVR, whole and regional brain atrophy on magnetic resonance imaging, and disability in patients with SPMS. METHODS Participants had SPMS, and data were collected at enrolment into the MS-STAT2 trial. Composite CVR scores were calculated using the QRISK3 software. Prematurely achieved CVR due to modifiable risk factors was expressed as QRISK3 premature CVR, derived through reference to the normative QRISK3 dataset and expressed in years. Associations were determined with multiple linear regressions. RESULTS For the 218 participants, mean age was 54 years and median Expanded Disability Status Scale was 6.0. Each additional year of prematurely achieved CVR was associated with a 2.7 mL (beta coefficient; 95% confidence interval 0.8-4.7; p = 0.006) smaller normalized whole brain volume. The strongest relationship was seen for the cortical grey matter (beta coefficient 1.6 mL per year; 95% confidence interval 0.5-2.7; p = 0.003), and associations were also found with poorer verbal working memory performance. Body mass index demonstrated the strongest relationships with normalized brain volumes, whilst serum lipid ratios demonstrated strong relationships with verbal and visuospatial working memory performance. CONCLUSIONS Prematurely achieved CVR is associated with lower normalized brain volumes in SPMS. Future longitudinal analyses of this clinical trial dataset will be important to determine whether CVR predicts future disease worsening.
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Affiliation(s)
- Thomas Williams
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Nevin John
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Medicine, School of Clinical Sciences, Monash University, Clayton, Victoria, Australia
| | - Alberto Calvi
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Alessia Bianchi
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Floriana De Angelis
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, UK
| | - Anisha Doshi
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Sarah Wright
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Madiha Shatila
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Marios C Yiannakas
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Fatima Chowdhury
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Jon Stutters
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Antonio Ricciardi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Ferran Prados
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- Universitat Oberta de Catalunya, Barcelona, Spain
| | - David MacManus
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Marie Braisher
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - James Blackstone
- Comprehensive Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK
| | - Olga Ciccarelli
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Frederik Barkhof
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, UK
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- Department of Radiology & Nuclear Medicine, VU University Medical Centre, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jeremy Chataway
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, UK
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10
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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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11
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Camara-Lemarroy C, Silva C, Gohill J, Yong VW, Koch M. Serum neurofilament-light and glial fibrillary acidic protein levels in hydroxychloroquine-treated primary progressive multiple sclerosis. Eur J Neurol 2023; 30:187-194. [PMID: 36214614 DOI: 10.1111/ene.15588] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 08/02/2022] [Accepted: 09/29/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND In a recent trial, hydroxychloroquine (HCQ) treatment reduced the expected rate of disability worsening at 18 months in primary progressive multiple sclerosis (PPMS). Neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) are emerging biomarkers in multiple sclerosis. METHODS We measured NfL and GFAP levels in serum samples from 39 patients with inactive PPMS included in a phase II clinical trial of HCQ treatment in PPMS at multiple time points over 18 months, and investigated the association of these biomarkers with clinical disability at screening and during follow-up. Screening and 12-month retinal nerve fiber layer (RNFL) thickness was also recorded and analyzed. RESULTS NfL and GFAP levels increased over time, but only significantly from screening to month 6. NfL and GFAP levels did not significantly increase from month 6 up to month 18. At screening, NfL and GFAP levels did not correlate with the Expanded Disability Status Scale (EDSS), and GFAP but not NfL modestly correlated with Timed 25-Foot Walk test (T25FW). Screening NfL and GFAP levels did not predict disability worsening (≥20% worsening on the T25FW) at month 18. RNFL thickness decreased significantly from screening to month 12 and independently predicted disability worsening. CONCLUSIONS In this cohort of people with inactive PPMS, HCQ treatment attenuated the increase of NfL and GFAP after 6 months of treatment and up to 18 months of follow-up, suggesting a treatment effect of HCQ over these biomarkers. RNFL thickness, a marker of neuroaxonal atrophy, was associated with disability worsening, and should be explored further as a prognostic marker in this population.
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Affiliation(s)
- Carlos Camara-Lemarroy
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,UANL School of Medicine, Monterrey, Mexico
| | - Claudia Silva
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Jit Gohill
- Section of Ophthalmology, Department of Surgery, University of Calgary, Calgary, Alberta, Canada
| | - V Wee Yong
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Marcus Koch
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
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12
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Kosa P, Barbour C, Varosanec M, Wichman A, Sandford M, Greenwood M, Bielekova B. Molecular models of multiple sclerosis severity identify heterogeneity of pathogenic mechanisms. Nat Commun 2022; 13:7670. [PMID: 36509784 PMCID: PMC9744737 DOI: 10.1038/s41467-022-35357-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 11/29/2022] [Indexed: 12/14/2022] Open
Abstract
While autopsy studies identify many abnormalities in the central nervous system (CNS) of subjects dying with neurological diseases, without their quantification in living subjects across the lifespan, pathogenic processes cannot be differentiated from epiphenomena. Using machine learning (ML), we searched for likely pathogenic mechanisms of multiple sclerosis (MS). We aggregated cerebrospinal fluid (CSF) biomarkers from 1305 proteins, measured blindly in the training dataset of untreated MS patients (N = 129), into models that predict past and future speed of disability accumulation across all MS phenotypes. Healthy volunteers (N = 24) data differentiated natural aging and sex effects from MS-related mechanisms. Resulting models, validated (Rho 0.40-0.51, p < 0.0001) in an independent longitudinal cohort (N = 98), uncovered intra-individual molecular heterogeneity. While candidate pathogenic processes must be validated in successful clinical trials, measuring them in living people will enable screening drugs for desired pharmacodynamic effects. This will facilitate drug development making, it hopefully more efficient and successful.
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Affiliation(s)
- Peter Kosa
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - Christopher Barbour
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - Mihael Varosanec
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - Alison Wichman
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - Mary Sandford
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - Mark Greenwood
- grid.41891.350000 0001 2156 6108Department of Mathematical Sciences, Montana State University, Bozeman, MT USA
| | - Bibiana Bielekova
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
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13
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Kolson DL. Developments in Neuroprotection for HIV-Associated Neurocognitive Disorders (HAND). Curr HIV/AIDS Rep 2022; 19:344-357. [PMID: 35867211 PMCID: PMC9305687 DOI: 10.1007/s11904-022-00612-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/02/2022] [Indexed: 01/18/2023]
Abstract
PURPOSE OF REVIEW Reducing the risk of HIV-associated neurocognitive disorders (HAND) is an elusive treatment goal for people living with HIV. Combination antiretroviral therapy (cART) has reduced the prevalence of HIV-associated dementia, but milder, disabling HAND is an unmet challenge. As newer cART regimens that more consistently suppress central nervous system (CNS) HIV replication are developed, the testing of adjunctive neuroprotective therapies must accelerate. RECENT FINDINGS Successes in modifying cART regimens for CNS efficacy (penetrance, chemokine receptor targeting) and delivery (nanoformulations) in pilot studies suggest that improving cART neuroprotection and reducing HAND risk is achievable. Additionally, drugs currently used in neuroinflammatory, neuropsychiatric, and metabolic disorders show promise as adjuncts to cART, likely by broadly targeting neuroinflammation, oxidative stress, aerobic metabolism, and/or neurotransmitter metabolism. Adjunctive cognitive brain therapy and aerobic exercise may provide additional efficacy. Adjunctive neuroprotective therapies, including available FDA-approved drugs, cognitive therapy, and aerobic exercise combined with improved cART offer plausible strategies for optimizing the prevention and treatment of HAND.
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Affiliation(s)
- Dennis L Kolson
- Department of Neurology, University of Pennsylvania, Room 280C Clinical Research Building, 415 Curie Boulevard, Philadelphia, PA, 19104, USA.
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14
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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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15
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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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16
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Sotirchos ES, Vasileiou ES, Filippatou AG, Fitzgerald KC, Smith MD, Lord HN, Kalaitzidis G, Lambe J, Duval A, Prince JL, Mowry EM, Saidha S, Calabresi PA. Association of Serum Neurofilament Light Chain With Inner Retinal Layer Thinning in Multiple Sclerosis. Neurology 2022; 99:e688-e697. [PMID: 35618438 PMCID: PMC9484608 DOI: 10.1212/wnl.0000000000200778] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 04/11/2022] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Serum neurofilament light chain (sNfL) and optical coherence tomography (OCT)-derived retinal measures (including peripapillary retinal nerve fiber layer [pRNFL] and macular ganglion cell layer/inner plexiform layer [GCIPL] thickness) have been proposed as biomarkers of neurodegeneration in multiple sclerosis (MS). However, studies evaluating the associations between sNfL and OCT-derived retinal measures in MS are limited. METHODS In this retrospective analysis of a longitudinal, observational, single-center cohort study, sNfL levels were measured in people with MS and healthy controls (HCs) using single molecule array. Participants with MS were followed with serial OCT for a median follow-up of 4.5 years. Eyes with optic neuritis (ON) within 6 months of baseline OCT or ON during follow-up were excluded. Age-normative cutoffs of sNfL were derived using the HC data, and MS participants with sNfL greater than the 97.5th percentile for age were classified as having elevated sNfL (sNfL-E). Analyses were performed with mixed-effects linear regression models and adjusted for age, sex, race, and history of ON. RESULTS A total of 130 HCs (age: 42.4 ± 14.2 years; 62% female) and 403 people with MS (age: 43.1 ± 12.0 years; 78% female) were included. Elevated sNfL levels were present at baseline in 80 participants with MS (19.9%). At baseline, sNfL-E participants had modestly lower pRNFL (-3.03 ± 1.50 μm; p = 0.044) and GCIPL thickness (-2.74 ± 1.02 μm; p = 0.007). As compared with those with sNfL within the reference range, eyes from NfL-E participants exhibited faster longitudinal thinning of the pRNFL (45% faster; -0.74 vs -0.51 μm/y; p = 0.015) and GCIPL (25% faster; -0.35 vs -0.28 μm/y; p = 0.021). Significant differences in rates of pRNFL and GCIPL thinning between sNfL groups were found only in those with relapsing-remitting MS but not progressive MS. DISCUSSION Elevated baseline sNfL is associated with accelerated rates of retinal neuroaxonal loss in relapsing-remitting MS, independent of overt ON, but may be less reflective of retinal neurodegeneration in progressive MS.
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Affiliation(s)
- Elias S Sotirchos
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD.
| | - Eleni S Vasileiou
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
| | - Angeliki G Filippatou
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
| | - Kathryn C Fitzgerald
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
| | - Matthew D Smith
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
| | - Hannah-Noelle Lord
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
| | - Grigorios Kalaitzidis
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
| | - Jeffrey Lambe
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
| | - Anna Duval
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
| | - Jerry L Prince
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
| | - Ellen M Mowry
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
| | - Shiv Saidha
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
| | - Peter A Calabresi
- From the Departments of Neurology (E.S.S., E.S.V., A.G.F., K.C.F., M.D.S., H.-N.L., G.K., J.L., A.D., E.M.M., S.S., P.A.C.), and Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, MD
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17
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Li V, Leurent B, Barkhof F, Braisher M, Cafferty F, Ciccarelli O, Eshaghi A, Gray E, Nicholas JM, Parmar M, Peryer G, Robertson J, Stallard N, Wason J, Chataway J. Designing Multi-arm Multistage Adaptive Trials for Neuroprotection in Progressive Multiple Sclerosis. Neurology 2022; 98:754-764. [PMID: 35321926 PMCID: PMC9109150 DOI: 10.1212/wnl.0000000000200604] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 03/10/2022] [Indexed: 11/24/2022] Open
Abstract
There are few treatments shown to slow disability progression in progressive multiple sclerosis (PMS). One challenge has been efficiently testing the pipeline of candidate therapies from preclinical studies in clinical trials. Multi-arm multistage (MAMS) platform trials may accelerate evaluation of new therapies compared to traditional sequential clinical trials. We describe a MAMS design in PMS focusing on selection of interim and final outcome measures, sample size, and statistical considerations. The UK MS Society Expert Consortium for Progression in MS Clinical Trials reviewed recent phase II and III PMS trials to inform interim and final outcome selection and design measures. Simulations were performed to evaluate trial operating characteristics under different treatment effect, recruitment rate, and sample size assumptions. People with MS formed a patient and public involvement group and contributed to the trial design, ensuring it would meet the needs of the MS community. The proposed design evaluates 3 experimental arms compared to a common standard of care arm in 2 stages. Stage 1 (interim) outcome will be whole brain atrophy on MRI at 18 months, assessed for 123 participants per arm. Treatments with sufficient evidence for slowing brain atrophy will continue to the second stage. The stage 2 (final) outcome will be time to 6-month confirmed disability progression, based on a composite clinical score comprising the Expanded Disability Status Scale, Timed 25-Foot Walk test, and 9-Hole Peg Test. To detect a hazard ratio of 0.75 for this primary final outcome with 90% power, 600 participants per arm are required. Assuming one treatment progresses to stage 2, the trial will recruit ≈1,900 participants and last ≈6 years. This is approximately two-thirds the size and half the time of separate 2-arm phase II and III trials. The proposed MAMS trial design will substantially reduce duration and sample size compared to traditional clinical trials, accelerating discovery of effective treatments for PMS. The design was well-received by people with multiple sclerosis. The practical and statistical principles of MAMS trial design may be applicable to other neurodegenerative conditions to facilitate efficient testing of new therapies.
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Affiliation(s)
- Vivien Li
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Baptiste Leurent
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Frederik Barkhof
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Marie Braisher
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Fay Cafferty
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Olga Ciccarelli
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Arman Eshaghi
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Emma Gray
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Jennifer M Nicholas
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Mahesh Parmar
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Guy Peryer
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Jenny Robertson
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Nigel Stallard
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - James Wason
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Jeremy Chataway
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
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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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