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Calvi A, Mendelsohn Z, Hamed W, Chard D, Tur C, Stutters J, MacManus D, Kanber B, Wheeler-Kingshott CAMG, Barkhof F, Prados F. Treatment reduces the incidence of newly appearing multiple sclerosis lesions evolving into chronic active, slowly expanding lesions: A retrospective analysis. Eur J Neurol 2024; 31:e16092. [PMID: 37823722 DOI: 10.1111/ene.16092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 09/05/2023] [Accepted: 09/21/2023] [Indexed: 10/13/2023]
Abstract
BACKGROUND AND PURPOSE Newly appearing lesions in multiple sclerosis (MS) may evolve into chronically active, slowly expanding lesions (SELs), leading to sustained disability progression. The aim of this study was to evaluate the incidence of newly appearing lesions developing into SELs, and their correlation to clinical evolution and treatment. METHODS A retrospective analysis of a fingolimod trial in primary progressive MS (PPMS; INFORMS, NCT00731692) was undertaken. Data were available from 324 patients with magnetic resonance imaging scans up to 3 years after screening. New lesions at year 1 were identified with convolutional neural networks, and SELs obtained through a deformation-based method. Clinical disability was assessed annually by Expanded Disability Status Scale (EDSS), Nine-Hole Peg Test, Timed 25-Foot Walk, and Paced Auditory Serial Addition Test. Linear, logistic, and mixed-effect models were used to assess the relationship between the Jacobian expansion in new lesions and SELs, disability scores, and treatment status. RESULTS One hundred seventy patients had ≥1 new lesions at year 1 and had a higher lesion count at screening compared to patients with no new lesions (median = 27 vs. 22, p = 0.007). Among the new lesions (median = 2 per patient), 37% evolved into definite or possible SELs. Higher SEL volume and count were associated with EDSS worsening and confirmed disability progression. Treated patients had lower volume and count of definite SELs (β = -0.04, 95% confidence interval [CI] = -0.07 to -0.01, p = 0.015; β = -0.36, 95% CI = -0.67 to -0.06, p = 0.019, respectively). CONCLUSIONS Incident chronic active lesions are common in PPMS, and fingolimod treatment can reduce their number.
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Affiliation(s)
- Alberto Calvi
- NMR Research Unit, Institute of Neurology, University College London, London, UK
- Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Fundació Clinic per a la Recerca Biomèdica, Barcelona, Spain
| | - Zoe Mendelsohn
- NMR Research Unit, Institute of Neurology, University College London, London, UK
- Department of Radiology, Charité School of Medicine and University Hospital Berlin, Berlin, Germany
| | - Weaam Hamed
- NMR Research Unit, Institute of Neurology, University College London, London, UK
- Department of Radiology, Mansoura University Hospital, Mansoura, Egypt
| | - Declan Chard
- NMR Research Unit, Institute of Neurology, University College London, London, UK
- National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, UK
| | - Carmen Tur
- NMR Research Unit, Institute of Neurology, University College London, London, UK
- Neurology-Neuroimmunology Department, Multiple Sclerosis Centre of Catalonia, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Jon Stutters
- NMR Research Unit, Institute of Neurology, University College London, London, UK
| | - David MacManus
- NMR Research Unit, Institute of Neurology, University College London, London, UK
| | - Baris Kanber
- National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, UK
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing, University College London, London, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Institute of Neurology, University College London, London, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Frederik Barkhof
- NMR Research Unit, Institute of Neurology, University College London, London, UK
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing, University College London, London, UK
- Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC), Vrije Universiteit, Amsterdam, the Netherlands
| | - Ferran Prados
- NMR Research Unit, Institute of Neurology, University College London, London, UK
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing, University College London, London, UK
- e-Health Centre, Universitat Oberta de Catalunya, Barcelona, Spain
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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: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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Solanky BS, John NA, DeAngelis F, Stutters J, Prados F, Schneider T, Parker RA, Weir CJ, Monteverdi A, Plantone D, Doshi A, MacManus D, Marshall I, Barkhof F, Gandini Wheeler-Kingshott CAM, Chataway J. NAA is a Marker of Disability in Secondary-Progressive MS: A Proton MR Spectroscopic Imaging Study. AJNR Am J Neuroradiol 2020; 41:2209-2218. [PMID: 33154071 DOI: 10.3174/ajnr.a6809] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 07/24/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND AND PURPOSE The secondary progressive phase of multiple sclerosis is characterised by disability progression due to processes that lead to neurodegeneration. Surrogate markers such as those derived from MRI are beneficial in understanding the pathophysiology that drives disease progression and its relationship to clinical disability. We undertook a 1H-MRS imaging study in a large secondary progressive MS (SPMS) cohort, to examine whether metabolic markers of brain injury are associated with measures of disability, both physical and cognitive. MATERIALS AND METHODS A cross-sectional analysis of individuals with secondary-progressive MS was performed in 119 participants. They underwent 1H-MR spectroscopy to obtain estimated concentrations and ratios to total Cr for total NAA, mIns, Glx, and total Cho in normal-appearing WM and GM. Clinical outcome measures chosen were the following: Paced Auditory Serial Addition Test, Symbol Digit Modalities Test, Nine-Hole Peg Test, Timed 25-foot Walk Test, and the Expanded Disability Status Scale. The relationship between these neurometabolites and clinical disability measures was initially examined using Spearman rank correlations. Significant associations were then further analyzed in multiple regression models adjusting for age, sex, disease duration, T2 lesion load, normalized brain volume, and occurrence of relapses in 2 years preceding study entry. RESULTS Significant associations, which were then confirmed by multiple linear regression, were found in normal-appearing WM for total NAA (tNAA)/total Cr (tCr) and the Nine-Hole Peg Test (ρ = 0.23; 95% CI, 0.06-0.40); tNAA and tNAA/tCr and the Paced Auditory Serial Addition Test (ρ = 0.21; 95% CI, 0.03-0.38) (ρ = 0.19; 95% CI, 0.01-0.36); mIns/tCr and the Paced Auditory Serial Addition Test, (ρ = -0.23; 95% CI, -0.39 to -0.05); and in GM for tCho and the Paced Auditory Serial Addition Test (ρ = -0.24; 95% CI, -0.40 to -0.06). No other GM or normal-appearing WM relationships were found with any metabolite, with associations found during initial correlation testing losing significance after multiple linear regression analysis. CONCLUSIONS This study suggests that metabolic markers of neuroaxonal integrity and astrogliosis in normal-appearing WM and membrane turnover in GM may act as markers of disability in secondary-progressive MS.
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Affiliation(s)
- B S Solanky
- From the Department of Neuroinflammation (B.S.S., N.A.J., F.D., J.S., F.P., D.P., A.D., D.M., C.A.M.G.W.-K., J.C.), Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology
| | - N A John
- From the Department of Neuroinflammation (B.S.S., N.A.J., F.D., J.S., F.P., D.P., A.D., D.M., C.A.M.G.W.-K., J.C.), Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology
| | - F DeAngelis
- From the Department of Neuroinflammation (B.S.S., N.A.J., F.D., J.S., F.P., D.P., A.D., D.M., C.A.M.G.W.-K., J.C.), Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology
| | - J Stutters
- From the Department of Neuroinflammation (B.S.S., N.A.J., F.D., J.S., F.P., D.P., A.D., D.M., C.A.M.G.W.-K., J.C.), Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology
| | - F Prados
- From the Department of Neuroinflammation (B.S.S., N.A.J., F.D., J.S., F.P., D.P., A.D., D.M., C.A.M.G.W.-K., J.C.), Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology
- Centre for Medical Image Computing (F.P., F.B.), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- Universitat Oberta de Catalunya (F.P.), Barcelona, Spain
| | | | - R A Parker
- Edinburgh Clinical Trials Unit (R.A.P., C.J.W.), Usher Institute
| | - C J Weir
- Edinburgh Clinical Trials Unit (R.A.P., C.J.W.), Usher Institute
| | - A Monteverdi
- Department of Brain and Behavioural Sciences (A.M., C.A.M.G.W.-K.), University of Pavia, Pavia, Italy
| | - D Plantone
- From the Department of Neuroinflammation (B.S.S., N.A.J., F.D., J.S., F.P., D.P., A.D., D.M., C.A.M.G.W.-K., J.C.), Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology
| | - A Doshi
- From the Department of Neuroinflammation (B.S.S., N.A.J., F.D., J.S., F.P., D.P., A.D., D.M., C.A.M.G.W.-K., J.C.), Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology
| | - D MacManus
- From the Department of Neuroinflammation (B.S.S., N.A.J., F.D., J.S., F.P., D.P., A.D., D.M., C.A.M.G.W.-K., J.C.), Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology
| | - I Marshall
- Centre for Clinical Brain Sciences (I.M.), University of Edinburgh, Edinburgh, UK
| | - F Barkhof
- Centre for Medical Image Computing (F.P., F.B.), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- National Institute for Health Research (F.B.), University College London Hospitals Biomedical Research Centre, London, UK
- Department of Radiology and Nuclear Medicine (F.B., J.C.), MS Center Amsterdam, Amsterdam, the Netherlands
| | - C A M Gandini Wheeler-Kingshott
- From the Department of Neuroinflammation (B.S.S., N.A.J., F.D., J.S., F.P., D.P., A.D., D.M., C.A.M.G.W.-K., J.C.), Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology
- Brain MRI 3T Research Center (C.A.M.G.W.-K.), Scientific Institute for Research, Hospitalization and Healthcare Mondino National Neurological Institute Foundation, Pavia, Italy
- Department of Brain and Behavioural Sciences (A.M., C.A.M.G.W.-K.), University of Pavia, Pavia, Italy
| | - J Chataway
- From the Department of Neuroinflammation (B.S.S., N.A.J., F.D., J.S., F.P., D.P., A.D., D.M., C.A.M.G.W.-K., J.C.), Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology
- Department of Radiology and Nuclear Medicine (F.B., J.C.), MS Center Amsterdam, Amsterdam, the Netherlands
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