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Bjørklund G, Wallace DR, Hangan T, Butnariu M, Gurgas L, Peana M. Cerebral iron accumulation in multiple sclerosis: Pathophysiology and therapeutic implications. Autoimmun Rev 2025; 24:103741. [PMID: 39756528 DOI: 10.1016/j.autrev.2025.103741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2024] [Revised: 01/02/2025] [Accepted: 01/02/2025] [Indexed: 01/07/2025]
Abstract
Multiple sclerosis (MS) is a chronic autoimmune disorder of the central nervous system characterized by demyelination, neuroinflammation, and neurodegeneration. Recent studies highlight the role of cerebral iron (Fe) accumulation in exacerbating MS pathophysiology. Fe, essential for neural function, contributes to oxidative stress and inflammation when dysregulated, particularly in the brain's gray matter and demyelinated lesions. Advanced imaging techniques, including susceptibility-weighted and quantitative susceptibility mapping, have revealed abnormal Fe deposition patterns in MS patients, suggesting its involvement in disease progression. Iron's interaction with immune cells, such as microglia, releases pro-inflammatory cytokines, further amplifying neuroinflammation and neuronal damage. These findings implicate Fe dysregulation as a significant factor in MS progression, contributing to clinical manifestations like cognitive impairment. Therapeutic strategies targeting Fe metabolism, including Fe chelation therapies, show promise in reducing Fe-related damage, instilling optimism about the future of MS treatment. However, challenges such as crossing the blood-brain barrier and maintaining Fe homeostasis remain. Emerging approaches, such as Fe-targeted nanotherapeutics and biologics, offer new possibilities for personalized treatments. However, the journey is far from over. Continued research into the molecular mechanisms of Fe-induced neuroinflammation and oxidative damage is essential. Through this research, we can develop effective interventions that could slow MS progression and improve patient outcomes.
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Affiliation(s)
- Geir Bjørklund
- Council for Nutritional and Environmental Medicine (CONEM), Mo i Rana, Norway.
| | - David R Wallace
- Department of Pharmacology, Oklahoma State University Center for Health Sciences, Tulsa, OK, United States
| | - Tony Hangan
- Faculty of Medicine, Ovidius University of Constanta, Constanta, Romania
| | - Monica Butnariu
- University of Life Sciences "King Mihai I" from Timisoara, Timis, Romania; CONEM Romania Biotechnology and Environmental Sciences Group, University of Life Sciences "King Mihai I" from Timisoara, Timis, Romania
| | - Leonard Gurgas
- Faculty of Medicine, Ovidius University of Constanta, Constanta, Romania
| | - Massimiliano Peana
- Department of Chemical, Physical, Mathematical and Natural Sciences, University of Sassari, Italy
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Meijboom R, Foley P, MacDougall NJJ, Mina Y, York EN, Kampaite A, Mollison D, Kearns PKA, White N, Thrippleton MJ, Murray K, Valdés Hernández MDC, Reich DS, Connick P, Jacobson S, Nair G, Chandran S, Waldman AD. Fatigue in early multiple sclerosis: MRI metrics of neuroinflammation, relapse and neurodegeneration. Brain Commun 2024; 6:fcae278. [PMID: 39386090 PMCID: PMC11462441 DOI: 10.1093/braincomms/fcae278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 05/27/2024] [Accepted: 08/13/2024] [Indexed: 10/12/2024] Open
Abstract
Multiple sclerosis (MS) is a neuroinflammatory and neurodegenerative disease affecting the brain and spinal cord. Fatigue is a common disabling symptom from MS onset, however the mechanisms by which underlying disease processes cause fatigue remain unclear. Improved pathophysiological understanding offers potential for improved treatments for MS-related fatigue. MRI provides insights into in vivo neuroinflammatory activity and neurodegeneration, although existing evidence for imaging correlates of MS fatigue is mixed. We explore associations between fatigue and MRI measures in the brain and spinal cord to identify neuroinflammatory and regional neurodegenerative substrates of fatigue in early relapsing-remitting MS (RRMS). Recently diagnosed (<6 months), treatment-naive people with RRMS (n = 440) were recruited to a longitudinal multi-centre nationally representative cohort study. Participants underwent 3-Tesla brain MRI at baseline and one year. We calculated global and regional white and grey matter volumes, white matter lesion (WML) load and upper cervical spinal cord cross-sectional area levels C2-3, and assessed new/enlarging WMLs visually. Participants were classed as fatigued or non-fatigued at baseline according to the Fatigue Severity Scale (>/≤36). Disability and depression were assessed with the expanded-disability status scale and Patient Health Questionnaire, respectively. MRI measures were compared between fatigue groups, both cross-sectionally and longitudinally, using regression analyses. Higher disability and depression scores were observed for participants with fatigue, with a higher number of fatigued participants receiving disease-modifying treatments at follow-up. Structural MRI data for brain were available for n = 313 (45% fatigued) and for spinal cord for n = 324 (46% fatigued). Cervical spinal cord cross-sectional area 2-3, white and grey matter volumes decreased, and WML volume increased, over time for both groups (q < 0.05). However, no significant between-group differences in these measures were found either cross-sectionally or longitudinally (q > 0.05). The presence of new/enlarging WMLs (49% in fatigued; 51% in non-fatigued) at follow-up also did not differ between groups (q > 0.05). Our results suggest that fatigue is not driven by neuroinflammation or neurodegeneration measurable by current structural MRI in early RRMS. This novel negative finding in a large multi-centre cohort of people with recently diagnosed RRMS helps to resolve uncertainty in existing literature. Notably, we showed that fatigue is prevalent in patients without brain radiological relapse, who may be considered to have inactive disease. This suggests that symptom detection and treatment should remain a clinical priority regardless of neuroinflammatory disease activity. More sensitive objective biomarkers are needed to elucidate fatigue mechanisms in RRMS, and ultimately facilitate development of effective targeted treatments for this important 'hidden disability'.
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Affiliation(s)
- Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Peter Foley
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Niall J J MacDougall
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
- Department of Neurology, Institute of Neurological Sciences, Queen Elizabeth University Hospital, Glasgow G51 4TF, UK
| | - Yair Mina
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20824, USA
- Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv 69978, Israel
| | - Elizabeth N York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Daisy Mollison
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Patrick K A Kearns
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Nicole White
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Katy Murray
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
- Department of Neurology, Forth Valley Royal Hospital, Larbert FK5 4WR, UK
| | - Maria del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20824, USA
| | - Peter Connick
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Steven Jacobson
- Viral Immunology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20824, USA
| | - Govind Nair
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20824, USA
- Quantitative MRI Core Facility, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20824, USA
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh EH16 4SB, UK
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Harper JG, York EN, Meijboom R, Kampaite A, Thrippleton MJ, Kearns PKA, Valdés Hernández MDC, Chandran S, Waldman AD. Quantitative T 1 brain mapping in early relapsing-remitting multiple sclerosis: longitudinal changes, lesion heterogeneity and disability. Eur Radiol 2024; 34:3826-3839. [PMID: 37943312 PMCID: PMC11166797 DOI: 10.1007/s00330-023-10351-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 07/20/2023] [Accepted: 08/29/2023] [Indexed: 11/10/2023]
Abstract
OBJECTIVES To quantify brain microstructural changes in recently diagnosed relapsing-remitting multiple sclerosis (RRMS) using longitudinal T1 measures, and determine their associations with clinical disability. METHODS Seventy-nine people with recently diagnosed (< 6 months) RRMS were recruited from a single-centre cohort sub-study, and underwent baseline and 1-year brain MRI, including variable flip angle T1 mapping. Median T1 was measured in white matter lesions (WML), normal-appearing white matter (NAWM), cortical/deep grey matter (GM), thalami, basal ganglia and medial temporal regions. Prolonged T1 (≥ 2.00 s) and supramedian T1 (relative to cohort WML values) WML voxel counts were also measured. Longitudinal change was assessed with paired t-tests and compared with Bland-Altman limits of agreement from healthy control test-retest data. Regression analyses determined relationships with Expanded Disability Status Scale (EDSS) score and dichotomised EDSS outcomes (worsening or stable/improving). RESULTS Sixty-two people with RRMS (mean age 37.2 ± 10.9 [standard deviation], 48 female) and 11 healthy controls (age 44 ± 11, 7 female) contributed data. Prolonged and supramedian T1 WML components increased longitudinally (176 and 463 voxels, respectively; p < .001), and were associated with EDSS score at baseline (p < .05) and follow-up (supramedian: p < .01; prolonged: p < .05). No cohort-wide median T1 changes were found; however, increasing T1 in WML, NAWM, cortical/deep GM, basal ganglia and thalami was positively associated with EDSS worsening (p < .05). CONCLUSION T1 is sensitive to brain microstructure changes in early RRMS. Prolonged WML T1 components and subtle changes in NAWM and GM structures are associated with disability. CLINICAL RELEVANCE STATEMENT MRI T1 brain mapping quantifies disability-associated white matter lesion heterogeneity and subtle microstructural damage in normal-appearing brain parenchyma in recently diagnosed RRMS, and shows promise for early objective disease characterisation and stratification. KEY POINTS • Quantitative T1 mapping detects brain microstructural damage and lesion heterogeneity in recently diagnosed relapsing-remitting multiple sclerosis. • T1 increases in lesions and normal-appearing parenchyma, indicating microstructural damage, are associated with worsening disability. • Brain T1 measures are objective markers of disability-relevant pathology in early multiple sclerosis.
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Affiliation(s)
- James G Harper
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
| | - Elizabeth N York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK.
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK.
- Anne Rowling Regenerative Neurology Clinic, Edinburgh, UK.
| | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Patrick K A Kearns
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK.
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK.
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Meijboom R, York EN, Kampaite A, Harris MA, White N, Valdés Hernández MDC, Thrippleton MJ, MacDougall NJJ, Connick P, Hunt DPJ, Chandran S, Waldman AD. Patterns of brain atrophy in recently-diagnosed relapsing-remitting multiple sclerosis. PLoS One 2023; 18:e0288967. [PMID: 37506096 PMCID: PMC10381059 DOI: 10.1371/journal.pone.0288967] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 07/07/2023] [Indexed: 07/30/2023] Open
Abstract
Recurrent neuroinflammation in relapsing-remitting MS (RRMS) is thought to lead to neurodegeneration, resulting in progressive disability. Repeated magnetic resonance imaging (MRI) of the brain provides non-invasive measures of atrophy over time, a key marker of neurodegeneration. This study investigates regional neurodegeneration of the brain in recently-diagnosed RRMS using volumetry and voxel-based morphometry (VBM). RRMS patients (N = 354) underwent 3T structural MRI <6 months after diagnosis and 1-year follow-up, as part of the Scottish multicentre 'FutureMS' study. MRI data were processed using FreeSurfer to derive volumetrics, and FSL for VBM (grey matter (GM) only), to establish regional patterns of change in GM and normal-appearing white matter (NAWM) over time throughout the brain. Volumetric analyses showed a decrease over time (q<0.05) in bilateral cortical GM and NAWM, cerebellar GM, brainstem, amygdala, basal ganglia, hippocampus, accumbens, thalamus and ventral diencephalon. Additionally, NAWM and GM volume decreased respectively in the following cortical regions, frontal: 14 out of 26 regions and 16/26; temporal: 18/18 and 15/18; parietal: 14/14 and 11/14; occipital: 7/8 and 8/8. Left GM and NAWM asymmetry was observed in the frontal lobe. GM VBM analysis showed three major clusters of decrease over time: 1) temporal and subcortical areas, 2) cerebellum, 3) anterior cingulum and supplementary motor cortex; and four smaller clusters within the occipital lobe. Widespread GM and NAWM atrophy was observed in this large recently-diagnosed RRMS cohort, particularly in the brainstem, cerebellar GM, and subcortical and occipital-temporal regions; indicative of neurodegeneration across tissue types, and in accord with limited previous studies in early disease. Volumetric and VBM results emphasise different features of longitudinal lobar and loco-regional change, however identify consistent atrophy patterns across individuals. Atrophy measures targeted to specific brain regions may provide improved markers of neurodegeneration, and potential future imaging stratifiers and endpoints for clinical decision making and therapeutic trials.
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Affiliation(s)
- Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Elizabeth N. York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, United Kingdom
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Mathew A. Harris
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Nicole White
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Maria del C. Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - N. J. J. MacDougall
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, United Kingdom
| | - Peter Connick
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, United Kingdom
| | - David P. J. Hunt
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, United Kingdom
| | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
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York EN, Meijboom R, Thrippleton MJ, Bastin ME, Kampaite A, White N, Chandran S, Waldman AD. Longitudinal microstructural MRI markers of demyelination and neurodegeneration in early relapsing-remitting multiple sclerosis: Magnetisation transfer, water diffusion and g-ratio. Neuroimage Clin 2022; 36:103228. [PMID: 36265199 PMCID: PMC9668599 DOI: 10.1016/j.nicl.2022.103228] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 10/07/2022] [Accepted: 10/08/2022] [Indexed: 11/11/2022]
Abstract
INTRODUCTION Quantitative microstructural MRI, such as myelin-sensitive magnetisation transfer ratio (MTR) or saturation (MTsat), axon-sensitive water diffusion Neurite Orientation Dispersion and Density Imaging (NODDI), and the aggregate g-ratio, may provide more specific markers of white matter integrity than conventional MRI for early patient stratification in relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to determine the sensitivity of such markers to longitudinal pathological change within cerebral white matter lesions (WML) and normal-appearing white matter (NAWM) in recently diagnosed RRMS. METHODS Seventy-nine people with recently diagnosed RRMS, from the FutureMS longitudinal cohort, were recruited to an extended MRI protocol at baseline and one year later. Twelve healthy volunteers received the same MRI protocol, repeated within two weeks. Ethics approval and written informed consent were obtained. 3T MRI included magnetisation transfer, and multi-shell diffusion-weighted imaging. NAWM and whole brain were segmented from 3D T1-weighted MPRAGE, and WML from T2-weighted FLAIR. MTR, MTsat, NODDI isotropic (ISOVF) and intracellular (ICVF) volume fractions, and g-ratio (calculated from MTsat and NODDI data) were measured within WML and NAWM. Brain parenchymal fraction (BPF) was also calculated. Longitudinal change in BPF and microstructural metrics was assessed with paired t-tests (α = 0.05) and linear mixed models, adjusted for confounding factors with False Discovery Rate (FDR) correction for multiple comparisons. Longitudinal changes were compared with test-retest Bland-Altman limits of agreement from healthy control white matter. The influence of longitudinal change on g-ratio was explored through post-hoc analysis in silico by computing g-ratio with realistic simulated MTsat and NODDI values. RESULTS In NAWM, g-ratio and ICVF increased, and MTsat decreased over one year (adjusted mean difference = 0.007, 0.005, and -0.057 respectively, all FDR-corrected p < 0.05). There was no significant change in MTR, ISOVF, or BPF. In WML, MTsat, NODDI ICVF and ISOVF increased over time (adjusted mean difference = 0.083, 0.024 and 0.016, respectively, all FDR-corrected p < 0.05). Group-level longitudinal changes exceeded test-retest limits of agreement for NODDI ISOVF and ICVF in WML only. In silico analysis showed g-ratio may increase due to a decrease in MTsat or ISOVF, or an increase in ICVF. DISCUSSION G-ratio and MTsat changes in NAWM over one year may indicate subtle myelin loss in early RRMS, which were not apparent with BPF or NAWM MTR. Increases in NAWM and WML NODDI ICVF were not anticipated, and raise the possibility of axonal swelling or morphological change. Increases in WML MTsat may reflect myelin repair. Changes in NODDI ISOVF are more likely to reflect alterations in water content. Competing MTsat and ICVF changes may account for the absence of g-ratio change in WML. Longitudinal changes in microstructural measures are significant at a group level, however detection in individual patients in early RRMS is limited by technique reproducibility. CONCLUSION MTsat and g-ratio are more sensitive than MTR to early pathological changes in RRMS, but complex dependence of g-ratio on NODDI parameters limit the interpretation of aggregate measures in isolation. Improvements in technique reproducibility and validation of MRI biophysical models across a range of pathological tissue states are needed.
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Affiliation(s)
- Elizabeth N York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom; Anne Rowling Regenerative Neurology Clinic, Edinburgh, United Kingdom.
| | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Nicole White
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Anne Rowling Regenerative Neurology Clinic, Edinburgh, United Kingdom; UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom.
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Chen Y, Larraz J, Wong M, Kearns P, Brown F, Martin SJ, Connick P, MacDougall N, Weaver C, Dhillon B, Chandran S. Longitudinal retinal imaging study of newly diagnosed relapsing-remitting multiple sclerosis in Scottish population: baseline and 12 months follow-up profile of FutureMS retinal imaging cohort. BMJ Open Ophthalmol 2022; 7:e001024. [PMID: 36161838 PMCID: PMC9315911 DOI: 10.1136/bmjophth-2022-001024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 06/03/2022] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVE Multiple sclerosis (MS) is an inflammatory degenerative condition of central nervous system. The disease course and presentation of MS is highly heterogeneous. Advanced retinal imaging techniques such as optic coherence tomography (OCT) can capture abnormalities of anterior visual pathway with high resolution, which may contribute greater insights into the pathophysiology of MS. METHODS People with newly diagnosed relapsing-remitting MS were recruited for FutureMS retinal imaging study from two study centres in Scotland. The baseline visit was completed within 6 months of diagnosis with initial follow-up 12 months after the baseline visit. The assessments included in FutureMS retinal imaging study were visual acuity test, self-reported eye questionnaire and OCT scan. RESULTS A total of 196 FutureMS participants completed the retinal imaging study of FutureMS with 185 participants at M0 and 155 at M12. A total of 144 participants completed both M0 and M12 visits. At the whole cohort level, the distribution of retinal measures is generally consistent between baseline and follow-up. CONCLUSION The FutureMS retinal imaging study aims to demonstrate that patient with MS present with different extent of retinal abnormalities that can be captured by retinal imaging modalities such as OCT soon after diagnosis. These changes may sensitively mirror the brain atrophy or serve as predictors for disease activity. By developing sensitive, quantifiable and objective retinal biomarkers, FutureMS retinal imaging study will provide an opportunity to stratify patient with MS at an early stage and support future therapeutic strategies for a better outcome.
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Affiliation(s)
- Yingdi Chen
- The Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh, EdinburghUK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Juan Larraz
- The Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh, EdinburghUK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Michael Wong
- The Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh, EdinburghUK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Patrick Kearns
- The Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh, EdinburghUK
- MRC Human Genetics Unit, Chromatin Lab, Genome Regulation Section, University of Edinburgh, Edinburgh, UK
| | - Fraser Brown
- The Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh, EdinburghUK
| | - Sarah-Jane Martin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Department of Neurology, Institute of Neurological Sciences,Queen Elizabeth University Hospital-, University of Glasgow, Glasgow, UK
| | - Peter Connick
- The Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh, EdinburghUK
- Department of Clinical Neurosciences, Edinburgh Royal Infirmary, NHS Lothian, EdinburghUK
| | - Niall MacDougall
- Department of Neurology, Institute of Neurological Sciences,Queen Elizabeth University Hospital-, University of Glasgow, Glasgow, UK
- Department of Neurology, University Hospital Hairmyres, East Kilbride, UK
| | - Christine Weaver
- The Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh, EdinburghUK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Baljean Dhillon
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Princess Alexandra Eye Pavilion, NHS Lothian, EdinburghUK
| | - Siddharthan Chandran
- The Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh, EdinburghUK
- Department of Clinical Neurosciences, Edinburgh Royal Infirmary, NHS Lothian, EdinburghUK
- UK Dementia Research Institue, The University of Edinburgh, Edinburgh, UK
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7
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Kearns PKA, Martin SJ, Chang J, Meijboom R, York EN, Chen Y, Weaver C, Stenson A, Hafezi K, Thomson S, Freyer E, Murphy L, Harroud A, Foley P, Hunt D, McLeod M, O'Riordan J, Carod-Artal FJ, MacDougall NJJ, Baranzini SE, Waldman AD, Connick P, Chandran S. FutureMS cohort profile: a Scottish multicentre inception cohort study of relapsing-remitting multiple sclerosis. BMJ Open 2022; 12:e058506. [PMID: 35768080 PMCID: PMC9244691 DOI: 10.1136/bmjopen-2021-058506] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 06/14/2022] [Indexed: 01/02/2023] Open
Abstract
PURPOSE Multiple sclerosis (MS) is an immune-mediated, neuroinflammatory disease of the central nervous system and in industrialised countries is the most common cause of progressive neurological disability in working age persons. While treatable, there is substantial interindividual heterogeneity in disease activity and response to treatment. Currently, the ability to predict at diagnosis who will have a benign, intermediate or aggressive disease course is very limited. There is, therefore, a need for integrated predictive tools to inform individualised treatment decision making. PARTICIPANTS Established with the aim of addressing this need for individualised predictive tools, FutureMS is a nationally representative, prospective observational cohort study of 440 adults with a new diagnosis of relapsing-remitting MS living in Scotland at the time of diagnosis between May 2016 and March 2019. FINDINGS TO DATE The study aims to explore the pathobiology and determinants of disease heterogeneity in MS and combines detailed clinical phenotyping with imaging, genetic and biomarker metrics of disease activity and progression. Recruitment, baseline assessment and follow-up at year 1 is complete. Here, we describe the cohort design and present a profile of the participants at baseline and 1 year of follow-up. FUTURE PLANS A third follow-up wave for the cohort has recently begun at 5 years after first visit and a further wave of follow-up is funded for year 10. Longer-term follow-up is anticipated thereafter.
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Affiliation(s)
- Patrick K A Kearns
- Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- Chromatin Lab, Genome Regulation Section, The University of Edinburgh MRC Human Genetics Unit, Edinburgh, UK
- Department of Clinical Neurosciences, Royal Infirmary of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- Department of Neurology, Institute of Clinical Neurosciences, NHS Greater Glasgow and Clyde, Glasgow, UK
- Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Sarah J Martin
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- Department of Neurology, Institute of Clinical Neurosciences, NHS Greater Glasgow and Clyde, Glasgow, UK
| | - Jessie Chang
- Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Elizabeth N York
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Yingdi Chen
- Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
| | - Christine Weaver
- Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Amy Stenson
- Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | | | - Stacey Thomson
- Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Elizabeth Freyer
- Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Lee Murphy
- Wellcome Trust Clinical Research Facility, Edinburgh, UK
| | - Adil Harroud
- Department of Neurology, Weill Institute of Clinical Neuroscience, San Francisco, California, USA
| | - Peter Foley
- Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - David Hunt
- Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Margaret McLeod
- Department of Neurology, Aberdeen Royal Infirmary, Aberdeen, UK
| | - Jonathon O'Riordan
- Tayside Centre for Clinical Neurosciences, University of Dundee Division of Neuroscience, Dundee, UK
| | | | - Niall J J MacDougall
- Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- Department of Neurology, Wishaw General Hospital, Wishaw, UK
| | - Sergio E Baranzini
- Department of Neurology, Weill Institute of Clinical Neuroscience, San Francisco, California, USA
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Peter Connick
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Siddharthan Chandran
- Anne Rowling Regenerative Neurology Clinic, The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
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