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Wuerch EC, Mirzaei R, Yong VW. Niacin produces an inconsistent treatment response in the EAE model of multiple sclerosis. J Neuroimmunol 2024; 394:578421. [PMID: 39088907 DOI: 10.1016/j.jneuroim.2024.578421] [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: 04/30/2024] [Revised: 06/21/2024] [Accepted: 07/25/2024] [Indexed: 08/03/2024]
Abstract
Niacin was found in the lysolecithin model of multiple sclerosis (MS) to promote the phagocytic clearance of debris and enhance remyelination. Lysolecithin lesions have prominent microglia/macrophages but lack lymphocytes that populate plaques of MS or its experimental autoimmune encephalomyelitis (EAE) model. Thus, the current study assessed the efficacy of niacin in EAE. We found that niacin inconsistently affects EAE clinical score, and largely does not ameliorate neuropathology. In culture, niacin enhances phagocytosis by macrophages, but does not reduce T cell proliferation. We suggest that studies of niacin for potential remyelination in MS should include a therapeutic that targets adaptive immunity.
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Affiliation(s)
- Emily C Wuerch
- Hotchkiss Brain Institute and the Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Reza Mirzaei
- Hotchkiss Brain Institute and the Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, USA
| | - V Wee Yong
- Hotchkiss Brain Institute and the Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada.
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Marastoni D, Turano E, Tamanti A, Colato E, Pisani AI, Scartezzini A, Carotenuto S, Mazziotti V, Camera V, Anni D, Ziccardi S, Guandalini M, Pizzini FB, Virla F, Mariotti R, Magliozzi R, Bonetti B, Steinman L, Calabrese M. Association of Levels of CSF Osteopontin With Cortical Atrophy and Disability in Early Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2024; 11:e200265. [PMID: 38917380 PMCID: PMC11203401 DOI: 10.1212/nxi.0000000000200265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 04/29/2024] [Indexed: 06/27/2024]
Abstract
BACKGROUND AND OBJECTIVES To evaluate CSF inflammatory markers with accumulation of cortical damage as well as disease activity in patients with early relapsing-remitting MS (RRMS). METHODS CSF levels of osteopontin (OPN) and 66 inflammatory markers were assessed using an immune-assay multiplex technique in 107 patients with RRMS (82 F/25 M, mean age 35.7 ± 11.8 years). All patients underwent regular clinical assessment and yearly 3T MRI scans for 2 years while 39 patients had a 4-year follow-up. White matter lesion number and volume, cortical lesions (CLs) and volume, and global cortical thickness (CTh) were evaluated together with the 'no evidence of disease activity' (NEDA-3) status, defined by no relapses, no disability worsening, and no MRI activity, including CLs. RESULTS The random forest algorithm selected OPN, CXCL13, TWEAK, TNF, IL19, sCD30, sTNFR1, IL35, IL16, and sCD163 as significantly associated with changes in global CTh. OPN and CXCL13 were most related to accumulation of atrophy after 2 and 4 years. In a multivariate linear regression model on CSF markers, OPN (p < 0.001), CXCL13 (p = 0.001), and sTNFR1 (p = 0.024) were increased in those patients with accumulating atrophy (adjusted R-squared 0.615). The 10 markers were added in a model that included all clinical, demographic, and MRI variables: OPN (p = 0.002) and IL19 (p = 0.022) levels were confirmed to be significantly increased in patients developing more CTh change over the follow-up (adjusted R-squared 0.619). CXCL13 and OPN also revealed the best association with NEDA-3 after 2 years, with OPN significantly linked to disability accumulation (OR 2.468 [1.46-5.034], p = 0.004) at the multivariate logistic regression model. DISCUSSION These data confirm and expand our knowledge on the prognostic role of the CSF inflammatory profile in predicting changes in cortical pathology and disease activity in early MS. The data emphasize a crucial role of OPN.
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Affiliation(s)
- Damiano Marastoni
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Ermanna Turano
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Agnese Tamanti
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Elisa Colato
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Anna Isabella Pisani
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Arianna Scartezzini
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Silvia Carotenuto
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Valentina Mazziotti
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Valentina Camera
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Daniela Anni
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Stefano Ziccardi
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Maddalena Guandalini
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Francesca B Pizzini
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Federica Virla
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Raffaella Mariotti
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Roberta Magliozzi
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Bruno Bonetti
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Lawrence Steinman
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
| | - Massimiliano Calabrese
- From the Neurology B (D.M., E.T., A.T., E.C., A.I.P., A.S., S.C., V.M., V.C., D.A., S.Z., M.G., F.V., R. Magliozzi, M.C.); Anatomy and Histology section (E.T., F.V., R. Mariotti), Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Italy; Department of Anatomy and Neurosciences (E.C.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; Neuroradiology and Radiology Units (F.B.P.), Department of Engineering for Innovation Medicine, University of Verona, Italy; Department of Brain Sciences (R. Magliozzi), Faculty of Medicine, Imperial College London, United Kingdom; Neurology A (B.B.), Azienda Ospedaliera Universitaria Integrata di Verona, Italy; and Department of Neurology and Neurological Sciences Stanford University (L.S.), CA
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Agostini S, Mancuso R, Citterio LA, Caputo D, Oreni L, Nuzzi R, Pasanisi MB, Rovaris M, Clerici M. Serum miR-34a-5p, miR-103a-3p, and miR-376a-3p as possible biomarkers of conversion from relapsing-remitting to secondary progressive multiple sclerosis. Neurobiol Dis 2024; 200:106648. [PMID: 39181188 DOI: 10.1016/j.nbd.2024.106648] [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: 10/20/2023] [Revised: 08/21/2024] [Accepted: 08/21/2024] [Indexed: 08/27/2024] Open
Abstract
Relapsing-remitting (RR) Multiple Sclerosis (MS) is the most common form of the disease; RRMS patients can maintain their clinical phenotype throughout life or can develop a secondary progressive (SP) course over time. We investigated whether circulating miRNAs can predict RR-to-SPMS conversion. A serum miRNAs profile was initially analyzed in a cross-sectional study by qPCR in 16 patients (8 RRMS and 8 SPMS) (Discovery cohort). Three miRNAs, i.e. miR-34a-5p, miR-103a-3p and miR-376a-3p, were significantly up-regulated in SPMS compared to RRMS patients (p < 0.0 5). Serum concentration of the same miRNAs was subsequently analyzed in a retrospective study by ddPCR at baseline in 69 RRMS patients who did (N = 36 cSPMS) or did not (N = 33) convert into SPMS over a 10-year observation period (Study cohort). The results showed that these miRNAs were significantly increased at baseline only in those RRMS patients who converted to SPMS over time. miR-34a-5p and miR-376a-3p alone were significantly increased in cSPMS sera at the end of the 10-years period too. Serum concentration of miR-34a-5p, miR-103a-3p and miR-376a-3p is increased in RRMS patients several years before their conversion to SPMS. These miRNAs might be useful biomarkers to predict the conversion from RRMS to SPMS.
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Affiliation(s)
| | | | | | | | - Letizia Oreni
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | | | | | - Marco Rovaris
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Mario Clerici
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
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4
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La Rosa F, Dos Santos Silva J, Dereskewicz E, Invernizzi A, Cahan N, Galasso J, Garcia N, Graney R, Levy S, Verma G, Balchandani P, Reich DS, Horton M, Greenspan H, Sumowski J, Cuadra MB, Beck ES. BrainAgeNeXt: Advancing Brain Age Modeling for Individuals with Multiple Sclerosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.10.24311686. [PMID: 39148818 PMCID: PMC11326330 DOI: 10.1101/2024.08.10.24311686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Aging is associated with structural brain changes, cognitive decline, and neurodegenerative diseases. Brain age, an imaging biomarker sensitive to deviations from healthy aging, offers insights into structural aging variations and is a potential prognostic biomarker in neurodegenerative conditions. This study introduces BrainAgeNeXt, a novel convolutional neural network inspired by the MedNeXt framework, designed to predict brain age from T1-weighted magnetic resonance imaging (MRI) scans. BrainAgeNeXt was trained and validated on 11,574 MRI scans from 33 private and publicly available datasets of healthy volunteers, aged 5 to 95 years, imaged with 3T and 7T MRI. Performance was compared against three state-of-the-art brain age prediction methods. BrainAgeNeXt achieved a mean absolute error (MAE) of 2.78 ± 3.64 years, lower than the compared methods (MAE = 3.55, 3.59, and 4.16 years, respectively). We tested all methods also across different levels of image quality, and BrainAgeNeXt performed well even with motion artifacts and less common 7T MRI data. In three longitudinal multiple sclerosis (MS) cohorts (273 individuals), brain age was, on average, 4.21 ± 6.51 years greater than chronological age. Longitudinal analysis indicated that brain age increased by 1.15 years per chronological year in individuals with MS (95% CI = [1.05, 1.26]). Moreover, in early MS, individuals with worsening disability had a higher annual increase in brain age compared to those with stable clinical assessments (1.24 vs. 0.75, p < 0.01). These findings suggest that brain age is a promising prognostic biomarker for MS progression and potentially a valuable endpoint for clinical trials.
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Affiliation(s)
- Francesco La Rosa
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | | | - Emma Dereskewicz
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Azzurra Invernizzi
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Noa Cahan
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Julia Galasso
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Nadia Garcia
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Robin Graney
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Sarah Levy
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Gaurav Verma
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Priti Balchandani
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Megan Horton
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Hayit Greenspan
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - James Sumowski
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Merixtell Bach Cuadra
- CIBM Center for Biomedical Imaging, Switzerland
- Radiology Department, University of Lausanne and Lausanne University Hospital, Switzerland
| | - Erin S Beck
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
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5
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Traboulsee A, Li DKB. Routine MR Imaging Protocol and Standardization in Central Nervous System Demyelinating Diseases. Neuroimaging Clin N Am 2024; 34:317-334. [PMID: 38942519 DOI: 10.1016/j.nic.2024.03.002] [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: 06/30/2024]
Abstract
Standardized MR imaging protocols are important for the diagnosis and monitoring of patients with multiple sclerosis (MS) and the appropriate use of MR imaging in routine clinical practice. Advances in using MR imaging to establish an earlier diagnosis of MS, safety concerns regarding intravenous gadolinium-based contrast agents, and the value of spinal cord MR imaging for diagnostic, prognostic, and monitoring purposes suggest a changing role of MR imaging for the management and care of MS patients. The MR imaging protocol emphasizes 3 dimensional acquisitions for optimal comparison over time.
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Affiliation(s)
- Anthony Traboulsee
- Department of Medicine (Neurology), University of British Columbia, University of British Columbia Hospital, 2211 Wesbrook Mall, Room S113, Vancouver, British Columbia V6T 2B5, Canada.
| | - David K B Li
- Department of Radiology, University of British Columbia, University of British Columbia Hospital, 2211 Wesbrook Mall, Vancouver, British Columbia V6T 2B5, Canada
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6
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Cagol A, Tsagkas C, Granziera C. Advanced Brain Imaging in Central Nervous System Demyelinating Diseases. Neuroimaging Clin N Am 2024; 34:335-357. [PMID: 38942520 DOI: 10.1016/j.nic.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.
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Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland; Department of Health Sciences, University of Genova, Via A. Pastore, 1 16132 Genova, Italy. https://twitter.com/CagolAlessandr0
| | - Charidimos Tsagkas
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), 10 Center Drive, Bethesda, MD 20892, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland.
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7
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Scalfari A, Traboulsee A, Oh J, Airas L, Bittner S, Calabrese M, Garcia Dominguez JM, Granziera C, Greenberg B, Hellwig K, Illes Z, Lycke J, Popescu V, Bagnato F, Giovannoni G. Smouldering-Associated Worsening in Multiple Sclerosis: An International Consensus Statement on Definition, Biology, Clinical Implications, and Future Directions. Ann Neurol 2024. [PMID: 39051525 DOI: 10.1002/ana.27034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 07/03/2024] [Accepted: 07/05/2024] [Indexed: 07/27/2024]
Abstract
Despite therapeutic suppression of relapses, multiple sclerosis (MS) patients often experience subtle deterioration, which extends beyond the definition of "progression independent of relapsing activity." We propose the concept of smouldering-associated-worsening (SAW), encompassing physical and cognitive symptoms, resulting from smouldering pathological processes, which remain unmet therapeutic targets. We provide a consensus-based framework of possible pathological substrates and manifestations of smouldering MS, and we discuss clinical, radiological, and serum/cerebrospinal fluid biomarkers for potentially monitoring SAW. Finally, we share considerations for optimizing disease surveillance and implications for clinical trials to promote the integration of smouldering MS into routine practice and future research efforts. ANN NEUROL 2024.
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Affiliation(s)
- Antonio Scalfari
- Center of Neuroscience, Department of Medicine, Charing Cross Hospital, Imperial College, London, UK
| | | | - Jiwon Oh
- Division of Neurology, Department of Medicine, St Michael's Hospital, University of Toronto, Toronto, Canada
| | - Laura Airas
- University of Turku and Turku University Hospital, Turku, Finland
| | - Stefan Bittner
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (Rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | | | | | - Cristina Granziera
- Translational Imaging in Neurology (THiNK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University of Basel, Basel, Switzerland
- Department of Neurology and MS Center, University Hospital Basel Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), Basel, Switzerland
| | | | | | - Zsolt Illes
- Department of Neurology, Odense University Hospital, University of Southern Denmark, Odense, Denmark
| | - Jan Lycke
- Department of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Veronica Popescu
- University MS Centre Pelt-Hasselt, Noorderhart Hospital, Belgium Hasselt University, Pelt, Belgium
| | - Francesca Bagnato
- Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurology, VA Hospital, TN Valley Healthcare System, Nashville, TN, USA
| | - Gavin Giovannoni
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
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8
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Calabrese M, Preziosa P, Scalfari A, Colato E, Marastoni D, Absinta M, Battaglini M, De Stefano N, Di Filippo M, Hametner S, Howell OW, Inglese M, Lassmann H, Martin R, Nicholas R, Reynolds R, Rocca MA, Tamanti A, Vercellino M, Villar LM, Filippi M, Magliozzi R. Determinants and Biomarkers of Progression Independent of Relapses in Multiple Sclerosis. Ann Neurol 2024; 96:1-20. [PMID: 38568026 DOI: 10.1002/ana.26913] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/04/2024] [Accepted: 02/15/2024] [Indexed: 06/20/2024]
Abstract
Clinical, pathological, and imaging evidence in multiple sclerosis (MS) suggests that a smoldering inflammatory activity is present from the earliest stages of the disease and underlies the progression of disability, which proceeds relentlessly and independently of clinical and radiological relapses (PIRA). The complex system of pathological events driving "chronic" worsening is likely linked with the early accumulation of compartmentalized inflammation within the central nervous system as well as insufficient repair phenomena and mitochondrial failure. These mechanisms are partially lesion-independent and differ from those causing clinical relapses and the formation of new focal demyelinating lesions; they lead to neuroaxonal dysfunction and death, myelin loss, glia alterations, and finally, a neuronal network dysfunction outweighing central nervous system (CNS) compensatory mechanisms. This review aims to provide an overview of the state of the art of neuropathological, immunological, and imaging knowledge about the mechanisms underlying the smoldering disease activity, focusing on possible early biomarkers and their translation into clinical practice. ANN NEUROL 2024;96:1-20.
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Affiliation(s)
- Massimiliano Calabrese
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Antonio Scalfari
- Centre of Neuroscience, Department of Medicine, Imperial College, London, UK
| | - Elisa Colato
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Damiano Marastoni
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Martina Absinta
- Translational Neuropathology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marco Battaglini
- Siena Imaging S.r.l., Siena, Italy
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Massimiliano Di Filippo
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Simon Hametner
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Owain W Howell
- Institute of Life Sciences, Swansea University Medical School, Swansea, UK
| | - Matilde Inglese
- Dipartimento di neuroscienze, riabilitazione, oftalmologia, genetica e scienze materno-infantili - DINOGMI, University of Genova, Genoa, Italy
| | - Hans Lassmann
- Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Roland Martin
- Institute of Experimental Immunology, University of Zurich, Zurich, Switzerland
- Therapeutic Design Unit, Center for Molecular Medicine, Department of Clinical Neurosciences, Karolinska Institutet, Stockholm, Sweden
- Cellerys AG, Schlieren, Switzerland
| | - Richard Nicholas
- Department of Brain Sciences, Faculty of Medicine, Burlington Danes, Imperial College London, London, UK
| | - Richard Reynolds
- Division of Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Agnese Tamanti
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
| | - Marco Vercellino
- Multiple Sclerosis Center & Neurologia I U, Department of Neuroscience, University Hospital AOU Città della Salute e della Scienza di Torino, Turin, Italy
| | - Luisa Maria Villar
- Department of Immunology, Ramon y Cajal University Hospital. IRYCIS. REI, Madrid, Spain
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Roberta Magliozzi
- Department of Neurosciences and Biomedicine and Movement, The Multiple Sclerosis Center of University Hospital of Verona, Verona, Italy
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Collorone S, Coll L, Lorenzi M, Lladó X, Sastre-Garriga J, Tintoré M, Montalban X, Rovira À, Pareto D, Tur C. Artificial intelligence applied to MRI data to tackle key challenges in multiple sclerosis. Mult Scler 2024; 30:767-784. [PMID: 38738527 DOI: 10.1177/13524585241249422] [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: 05/14/2024]
Abstract
Artificial intelligence (AI) is the branch of science aiming at creating algorithms able to carry out tasks that typically require human intelligence. In medicine, there has been a tremendous increase in AI applications thanks to increasingly powerful computers and the emergence of big data repositories. Multiple sclerosis (MS) is a chronic autoimmune condition affecting the central nervous system with a complex pathogenesis, a challenging diagnostic process strongly relying on magnetic resonance imaging (MRI) and a high and largely unexplained variability across patients. Therefore, AI applications in MS have the great potential of helping us better support the diagnosis, find markers for prognosis to eventually design more powerful randomised clinical trials and improve patient management in clinical practice and eventually understand the mechanisms of the disease. This topical review aims to summarise the recent advances in AI applied to MRI data in MS to illustrate its achievements, limitations and future directions.
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Affiliation(s)
- Sara Collorone
- NMR Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Llucia Coll
- Multiple Sclerosis Centre of Catalonia (Cemcat), Department of Neurology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Marco Lorenzi
- Epione Research Project, Inria Sophia Antipolis, Université Côte d'Azur, Nice, France
| | - Xavier Lladó
- Research Institute of Computer Vision and Robotics, University of Girona, Girona, Spain
| | - Jaume Sastre-Garriga
- Multiple Sclerosis Centre of Catalonia (Cemcat), Department of Neurology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Mar Tintoré
- Multiple Sclerosis Centre of Catalonia (Cemcat), Department of Neurology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Xavier Montalban
- Multiple Sclerosis Centre of Catalonia (Cemcat), Department of Neurology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology (IDI), Vall d'Hebron University Hospital, Barcelona, Spain
- Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology (IDI), Vall d'Hebron University Hospital, Barcelona, Spain
- Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Carmen Tur
- NMR Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, UK
- Multiple Sclerosis Centre of Catalonia (Cemcat), Department of Neurology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
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10
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Barakovic M, Weigel M, Cagol A, Schaedelin S, Galbusera R, Lu PJ, Chen X, Melie-Garcia L, Ocampo-Pineda M, Bahn E, Stadelmann C, Palombo M, Kappos L, Kuhle J, Magon S, Granziera C. A novel imaging marker of cortical "cellularity" in multiple sclerosis patients. Sci Rep 2024; 14:9848. [PMID: 38684744 PMCID: PMC11059177 DOI: 10.1038/s41598-024-60497-6] [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: 09/01/2023] [Accepted: 04/23/2024] [Indexed: 05/02/2024] Open
Abstract
Pathological data showed focal inflammation and regions of diffuse neuronal loss in the cortex of people with multiple sclerosis (MS). In this work, we applied a novel model ("soma and neurite density imaging (SANDI)") to multishell diffusion-weighted MRI data acquired in healthy subjects and people with multiple sclerosis (pwMS), in order to investigate inflammation and degeneration-related changes in the cortical tissue of pwMS. We aimed to (i) establish whether SANDI is applicable in vivo clinical data; (ii) investigate inflammatory and degenerative changes using SANDI soma fraction (fsoma)-a marker of cellularity-in both cortical lesions and in the normal-appearing-cortex and (iii) correlate SANDI fsoma with clinical and biological measures in pwMS. We applied a simplified version of SANDI to a clinical scanners. We then provided evidence that pwMS exhibited an overall decrease in cortical SANDI fsoma compared to healthy subjects, suggesting global degenerative processes compatible with neuronal loss. On the other hand, we have found that progressive pwMS showed a higher SANDI fsoma in the outer part of the cortex compared to relapsing-remitting pwMS, possibly supporting current pathological knowledge of increased innate inflammatory cells in these regions. A similar finding was obtained in subpial lesions in relapsing-remitting patients, reflecting existing pathological data in these lesion types. A significant correlation was found between SANDI fsoma and serum neurofilament light chain-a biomarker of inflammatory axonal damage-suggesting a relationship between SANDI soma fraction and inflammatory processes in pwMS again. Overall, our data show that SANDI fsoma is a promising biomarker to monitor changes in cellularity compatible with neurodegeneration and neuroinflammation in the cortex of MS patients.
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Affiliation(s)
- Muhamed Barakovic
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
- Pharmaceutical Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Matthias Weigel
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Alessandro Cagol
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Sabine Schaedelin
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Riccardo Galbusera
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Xinjie Chen
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Lester Melie-Garcia
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Mario Ocampo-Pineda
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Erik Bahn
- Institute of Neuropathology, University Medical Center, Göttingen, Germany
| | | | - Marco Palombo
- School of Psychology, Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
- School of Computer Science and Informatics, Cardiff University, Cardiff, UK
| | - Ludwig Kappos
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Stefano Magon
- Pharmaceutical Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland.
- Department of Neurology, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland.
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland.
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11
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Lomer NB, Asalemi KA, Saberi A, Sarlak K. Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies. PLoS One 2024; 19:e0300415. [PMID: 38626023 PMCID: PMC11020451 DOI: 10.1371/journal.pone.0300415] [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: 10/17/2023] [Accepted: 02/26/2024] [Indexed: 04/18/2024] Open
Abstract
INTRODUCTION Multiple Sclerosis (MS) is a chronic neurodegenerative disorder that affects the central nervous system (CNS) and results in progressive clinical disability and cognitive decline. Currently, there are no specific imaging parameters available for the prediction of longitudinal disability in MS patients. Magnetic resonance imaging (MRI) has linked imaging anomalies to clinical and cognitive deficits in MS. In this study, we aimed to evaluate the effectiveness of MRI in predicting disability, clinical progression, and cognitive decline in MS. METHODS In this study, according to PRISMA guidelines, we comprehensively searched the Web of Science, PubMed, and Embase databases to identify pertinent articles that employed conventional MRI in the context of Relapsing-Remitting and progressive forms of MS. Following a rigorous screening process, studies that met the predefined inclusion criteria were selected for data extraction and evaluated for potential sources of bias. RESULTS A total of 3028 records were retrieved from database searching. After a rigorous screening, 53 records met the criteria and were included in this study. Lesions and alterations in CNS structures like white matter, gray matter, corpus callosum, thalamus, and spinal cord, may be used to anticipate disability progression. Several prognostic factors associated with the progression of MS, including presence of cortical lesions, changes in gray matter volume, whole brain atrophy, the corpus callosum index, alterations in thalamic volume, and lesions or alterations in cross-sectional area of the spinal cord. For cognitive impairment in MS patients, reliable predictors include cortical gray matter volume, brain atrophy, lesion characteristics (T2-lesion load, temporal, frontal, and cerebellar lesions), white matter lesion volume, thalamic volume, and corpus callosum density. CONCLUSION This study indicates that MRI can be used to predict the cognitive decline, disability progression, and disease progression in MS patients over time.
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Affiliation(s)
| | | | - Alia Saberi
- Department of Neurology, Poursina Hospital, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
| | - Kasra Sarlak
- Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
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12
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Gross CC, Schulte-Mecklenbeck A, Steinberg OV, Wirth T, Lauks S, Bittner S, Schindler P, Baranzini SE, Groppa S, Bellmann-Strobl J, Bünger N, Chien C, Dawin E, Eveslage M, Fleischer V, Gonzalez-Escamilla G, Gisevius B, Haas J, Kerschensteiner M, Kirstein L, Korsukewitz C, Lohmann L, Lünemann JD, Luessi F, Meyer Zu Hörste G, Motte J, Ruck T, Ruprecht K, Schwab N, Steffen F, Meuth SG, Paul F, Wildemann B, Kümpfel T, Gold R, Hahn T, Zipp F, Klotz L, Wiendl H. Multiple sclerosis endophenotypes identified by high-dimensional blood signatures are associated with distinct disease trajectories. Sci Transl Med 2024; 16:eade8560. [PMID: 38536936 DOI: 10.1126/scitranslmed.ade8560] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 02/29/2024] [Indexed: 09/05/2024]
Abstract
One of the biggest challenges in managing multiple sclerosis is the heterogeneity of clinical manifestations and progression trajectories. It still remains to be elucidated whether this heterogeneity is reflected by discrete immune signatures in the blood as a surrogate of disease pathophysiology. Accordingly, individualized treatment selection based on immunobiological principles is still not feasible. Using two independent multicentric longitudinal cohorts of patients with early multiple sclerosis (n = 309 discovery and n = 232 validation), we were able to identify three distinct peripheral blood immunological endophenotypes by a combination of high-dimensional flow cytometry and serum proteomics, followed by unsupervised clustering. Longitudinal clinical and paraclinical follow-up data collected for the cohorts revealed that these endophenotypes were associated with disease trajectories of inflammation versus early structural damage. Investigating the capacity of immunotherapies to normalize endophenotype-specific immune signatures revealed discrete effect sizes as illustrated by the limited effect of interferon-β on endophenotype 3-related immune signatures. Accordingly, patients who fell into endophenotype 3 subsequently treated with interferon-β exhibited higher disease progression and MRI activity over a 4-year follow-up compared with treatment with other therapies. We therefore propose that ascertaining a patient's blood immune signature before immunomodulatory treatment initiation may facilitate prediction of clinical disease trajectories and enable personalized treatment decisions based on pathobiological principles.
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Affiliation(s)
- Catharina C Gross
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Andreas Schulte-Mecklenbeck
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Olga V Steinberg
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Timo Wirth
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Sarah Lauks
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Stefan Bittner
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Patrick Schindler
- Experimental and Clinical Research Center, a Cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Neuroscience Clinical Research Center, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, 10117 Berlin, Germany
- Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Sergio E Baranzini
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Judith Bellmann-Strobl
- Experimental and Clinical Research Center, a Cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Neuroscience Clinical Research Center, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, 10117 Berlin, Germany
| | - Nora Bünger
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Claudia Chien
- Experimental and Clinical Research Center, a Cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- NeuroCure Clinical Research Center, Charité - Univeritäsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Eva Dawin
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Maria Eveslage
- Institute of Biostatistics and Clinical Research, University of Münster, 48149 Münster, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Barbara Gisevius
- Department of Neurology, St. Josef-Hospital, Ruhr-University Bochum, 44791 Bochum, Germany
| | - Jürgen Haas
- Department of Neurology, University of Heidelberg, 69120 Heidelberg, Germany
| | - Martin Kerschensteiner
- Institute of Clinical Neuroimmunology, University Hospital and Biomedical Center (BMC), Faculty of Medicine, Ludwig Maximilians University of Munich, 81377 Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), 81377 Munich, Germany
| | - Lucienne Kirstein
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Catharina Korsukewitz
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Lisa Lohmann
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Jan D Lünemann
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Felix Luessi
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Gerd Meyer Zu Hörste
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Jeremias Motte
- Department of Neurology, St. Josef-Hospital, Ruhr-University Bochum, 44791 Bochum, Germany
| | - Tobias Ruck
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
- Department of Neurology, Medical Faculty, Heinrich-Heine-University Düsseldorf, 40225 Düsseldorf, Germany
| | - Klemens Ruprecht
- Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Nicholas Schwab
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Falk Steffen
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Sven G Meuth
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
- Department of Neurology, Medical Faculty, Heinrich-Heine-University Düsseldorf, 40225 Düsseldorf, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, a Cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
- Neuroscience Clinical Research Center, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, 10117 Berlin, Germany
- Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Brigitte Wildemann
- Department of Neurology, University of Heidelberg, 69120 Heidelberg, Germany
| | - Tania Kümpfel
- Institute of Clinical Neuroimmunology, University Hospital and Biomedical Center (BMC), Faculty of Medicine, Ludwig Maximilians University of Munich, 81377 Munich, Germany
| | - Ralf Gold
- Department of Neurology, St. Josef-Hospital, Ruhr-University Bochum, 44791 Bochum, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Frauke Zipp
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Luisa Klotz
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
| | - Heinz Wiendl
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, University of Münster, 48149 Münster, Germany
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13
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Hoffmann O, Gold R, Meuth SG, Linker RA, Skripuletz T, Wiendl H, Wattjes MP. Prognostic relevance of MRI in early relapsing multiple sclerosis: ready to guide treatment decision making? Ther Adv Neurol Disord 2024; 17:17562864241229325. [PMID: 38332854 PMCID: PMC10851744 DOI: 10.1177/17562864241229325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 01/12/2024] [Indexed: 02/10/2024] Open
Abstract
Magnetic resonance imaging (MRI) of the brain and spinal cord plays a crucial role in the diagnosis and monitoring of multiple sclerosis (MS). There is conclusive evidence that brain and spinal cord MRI findings in early disease stages also provide relevant insight into individual prognosis. This includes prediction of disease activity and disease progression, the accumulation of long-term disability and the conversion to secondary progressive MS. The extent to which these MRI findings should influence treatment decisions remains a subject of ongoing discussion. The aim of this review is to present and discuss the current knowledge and scientific evidence regarding the utility of MRI at early MS disease stages for prognostic classification of individual patients. In addition, we discuss the current evidence regarding the use of MRI in order to predict treatment response. Finally, we propose a potential approach as to how MRI data may be categorized and integrated into early clinical decision making.
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Affiliation(s)
- Olaf Hoffmann
- Department of Neurology, Alexianer St. Josefs-Krankenhaus Potsdam, Allee nach Sanssouci 7, 14471 Potsdam, Germany; Medizinische Hochschule Brandenburg Theodor Fontane, Neuruppin, Germany
| | - Ralf Gold
- Department of Neurology, St. Josef-Hospital, Ruhr-University Bochum, Bochum, Germany
| | - Sven G. Meuth
- Department of Neurology, Medical Faculty, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany
| | - Ralf A. Linker
- Department of Neurology, Regensburg University Hospital, Regensburg, Germany
| | | | - Heinz Wiendl
- Department of Neurology with Institute of Translational Neurology, University Hospital Münster, Münster, Germany
| | - Mike P. Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
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14
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Jakimovski D, Bittner S, Zivadinov R, Morrow SA, Benedict RH, Zipp F, Weinstock-Guttman B. Multiple sclerosis. Lancet 2024; 403:183-202. [PMID: 37949093 DOI: 10.1016/s0140-6736(23)01473-3] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 06/08/2023] [Accepted: 07/12/2023] [Indexed: 11/12/2023]
Abstract
Multiple sclerosis remains one of the most common causes of neurological disability in the young adult population (aged 18-40 years). Novel pathophysiological findings underline the importance of the interaction between genetics and environment. Improvements in diagnostic criteria, harmonised guidelines for MRI, and globalised treatment recommendations have led to more accurate diagnosis and an earlier start of effective immunomodulatory treatment than previously. Understanding and capturing the long prodromal multiple sclerosis period would further improve diagnostic abilities and thus treatment initiation, eventually improving long-term disease outcomes. The large portfolio of currently available medications paved the way for personalised therapeutic strategies that will balance safety and effectiveness. Incorporation of cognitive interventions, lifestyle recommendations, and management of non-neurological comorbidities could further improve quality of life and outcomes. Future challenges include the development of medications that successfully target the neurodegenerative aspect of the disease and creation of sensitive imaging and fluid biomarkers that can effectively predict and monitor disease changes.
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Affiliation(s)
- Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA; Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA
| | - Stefan Bittner
- Department of Neurology, Focus Program Translational Neuroscience and Immunotherapy, Rhine Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA; Center for Biomedical Imaging at the Clinical Translational Science Institute, State University of New York at Buffalo, Buffalo, NY, USA
| | - Sarah A Morrow
- Department of Clinical Neurological Sciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Ralph Hb Benedict
- Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA
| | - Frauke Zipp
- Department of Neurology, Focus Program Translational Neuroscience and Immunotherapy, Rhine Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
| | - Bianca Weinstock-Guttman
- Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY, USA.
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15
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Abdelhak A, Antweiler K, Kowarik MC, Senel M, Havla J, Zettl UK, Kleiter I, Hoshi MM, Skripuletz T, Haarmann A, Stahmann A, Huss A, Gingele S, Krumbholz M, Selge C, Friede T, Ludolph AC, Overell J, Koendgen H, Clinch S, Wang Q, Ziemann U, Hauser SL, Kümpfel T, Green AJ, Tumani H. Patient-reported outcome parameters and disability worsening in progressive multiple sclerosis. Mult Scler Relat Disord 2024; 81:105139. [PMID: 38000130 PMCID: PMC10959125 DOI: 10.1016/j.msard.2023.105139] [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: 08/21/2023] [Revised: 11/03/2023] [Accepted: 11/14/2023] [Indexed: 11/26/2023]
Abstract
OBJECTIVES Detection and prediction of disability progression is a significant unmet need in people with progressive multiple sclerosis (PwPMS). Government and health agencies have deemed the use of patient-reported outcomes measurements (PROMs) in clinical practice and clinical trials a major strategic priority. Nevertheless, data documenting the clinical utility of PROMs in neurological diseases is scarce. This study evaluates if assessment of PROMs could track progression in PwPMS. METHODS Emerging blood Biomarkers in Progressive Multiple Sclerosis (EmBioProMS) investigated PROMs (Beck depression inventory-II (BDI-II), multiple sclerosis impact scale-29 (MSIS-29), fatigue scale for motor and cognition (FSMC)) in PwPMS (primary [PPMS] and secondary progressive MS [SPMS]). PROMs were evaluated longitudinally and compared between participants with disability progression (at baseline; retrospective evidence of disability progression (EDP), and during follow up (FU); prospective evidence of confirmed disability progression (CDP)) and those without progression. In an independent cohort of placebo participants of the phase III ORATORIO trial in PPMS, the diagnostic and prognostic value of another PROMs score (36-Item Short Form Survey [SF-36]) regarding CDP was evaluated. RESULTS EmBioProMS participants with EDP in the two years prior to inclusion (n = 136/227), or who suffered from CDP during FU (number of events= 88) had worse BDI-II, MSIS-29, and FSMC scores compared to PwPMS without progression. In addition, baseline MSIS29physical above 70th, 80th, and 90th percentiles predicted future CDP/ progression independent of relapse activity in EmBioProMS PPMS participants (HR of 3.7, 6.9, 6.7, p = 0.002, <0.001, and 0.001, respectively). In the placebo arm of ORATORIO (n = 137), the physical component score (PCS) of SF-36 worsened at week 120 compared to baseline, in cases who experienced progression over the preceding trial period (P = 0.018). Worse PCS at baseline was associated with higher hazard ratios of disability accumulation over the subsequent 120 weeks (HR: 2.01 [30th-], 2.11 [20th-], and 2.8 [10th percentile], P = 0.007, 0.012 and 0.005, respectively). CONCLUSIONS PROMs could provide additional, practical, cost-efficient, and remotely accessible insight about disability progression in PMS through standardized, structured, and quantifiable patient feedback.
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Affiliation(s)
- Ahmed Abdelhak
- Department of Neurology, University of California San Francisco (UCSF), San Francisco, USA; Department of Neurology, University Hospital of Ulm, Oberer Eselsberg 45, Ulm 89081, Germany
| | - Kai Antweiler
- Department of Medical Statistics, University Medical Centre Göttingen, Göttingen, Germany
| | - Markus C Kowarik
- Department of Neurology and Stroke, University Hospital of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Makbule Senel
- Department of Neurology, University Hospital of Ulm, Oberer Eselsberg 45, Ulm 89081, Germany
| | - Joachim Havla
- Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians University, Munich, Germany
| | - Uwe K Zettl
- Department of Neurology, Neuroimmunological Section, University of Rostock, Rostock, Germany
| | - Ingo Kleiter
- Marianne-Strauß-Klinik, Behandlungszentrum Kempfenhausen für Multiple Sklerose Kranke gGmbH, Berg, Germany
| | - Muna-Miriam Hoshi
- Marianne-Strauß-Klinik, Behandlungszentrum Kempfenhausen für Multiple Sklerose Kranke gGmbH, Berg, Germany
| | | | - Axel Haarmann
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Alexander Stahmann
- Forschungs- und Projektentwicklungs-gGmbH, MS-Registry by the German MS-Society, Hanover, Germany
| | - Andre Huss
- Department of Neurology, University Hospital of Ulm, Oberer Eselsberg 45, Ulm 89081, Germany
| | - Stefan Gingele
- Hannover Medical School, Department of Neurology, Hanover, Germany
| | - Markus Krumbholz
- Department of Neurology and Stroke, University Hospital of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany; Department of Neurology and Pain Treatment, Immanuel Klinik Rüdersdorf, University Hospital of the Brandenburg Medical School Theodor Fontane, Rüdersdorf bei Berlin, Germany; Faculty of Health Sciences Brandenburg, Brandenburg Medical School Theodor Fontane, Rüdersdorf bei Berlin, Germany
| | - Charlotte Selge
- Marianne-Strauß-Klinik, Behandlungszentrum Kempfenhausen für Multiple Sklerose Kranke gGmbH, Berg, Germany
| | - Tim Friede
- Department of Medical Statistics, University Medical Centre Göttingen, Göttingen, Germany
| | - Albert C Ludolph
- Department of Neurology, University Hospital of Ulm, Oberer Eselsberg 45, Ulm 89081, Germany
| | | | | | | | - Qing Wang
- F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Ulf Ziemann
- Department of Neurology and Stroke, University Hospital of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Stephen L Hauser
- Department of Neurology, University of California San Francisco (UCSF), San Francisco, USA
| | - Tania Kümpfel
- Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians University, Munich, Germany
| | - Ari J Green
- Department of Neurology, University of California San Francisco (UCSF), San Francisco, USA
| | - Hayrettin Tumani
- Department of Neurology, University Hospital of Ulm, Oberer Eselsberg 45, Ulm 89081, Germany.
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16
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Deleu D, Garcia Canibano B, Elalamy O, Sayed Abdelmoneim M, Boshra A. Practical Guidance on the Use of Cladribine Tablets in the Management or Relapsing Multiple Sclerosis: Expert Opinion from Qatar. Degener Neurol Neuromuscul Dis 2023; 13:81-88. [PMID: 38105885 PMCID: PMC10725680 DOI: 10.2147/dnnd.s433459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 11/02/2023] [Indexed: 12/19/2023] Open
Abstract
The increasing availability of high-efficacy disease-modifying therapies (DMT) for the management of relapsing multiple sclerosis (RMS) has increased the potential for individualised patient management but has added complexity to the design of treatment regimens. The long-term application of immune reconstitution therapy (IRT) is supported by an increasing database of real world studies that have added important information on the long-term safety and efficacy of this approach. Cladribine tablets (CladT) is an IRT given as two annual short courses of treatment, following which a majority of patients then demonstrate no significant MS disease activity over a period of years. Whether, and how, to treat patients beyond the first two years of treatment remains a matter for debate, as clinical evidence accumulates. We, a group of neurologists who manage people with RMS in Qatar, provide our expert consensus recommendations on the application and long-term management of CladT therapy based on our experience with treatment in the last 5 years. These include pragmatic recommendations for people with MS disease activity in years 3 and 4 (ie up to four years following first dose of CladT), and for people with or without MS disease activity in subsequent years. We believe our recommendations will help to ensure the optimal application of CladT-based IRT, with the potential benefit for the patient of achieving prolonged periods free of both MS disease symptoms and the burden of regular applications of immunosuppressive DMT.
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Affiliation(s)
- Dirk Deleu
- Department of Neurology (Neurosciences Institute), Hamad Medical Corporation, Doha, Qatar
| | | | - Osama Elalamy
- Department of Neurology (Neurosciences Institute), Hamad Medical Corporation, Doha, Qatar
| | | | - Amir Boshra
- Merck Serono Middle East FZ-Ltd., Dubai, UAE, an affiliate of Merck KGaA, Dubai, United Arab Emirates
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17
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Cacciaguerra L, Rocca MA, Filippi M. Understanding the Pathophysiology and Magnetic Resonance Imaging of Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders. Korean J Radiol 2023; 24:1260-1283. [PMID: 38016685 DOI: 10.3348/kjr.2023.0360] [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: 04/26/2023] [Revised: 08/09/2023] [Accepted: 08/21/2023] [Indexed: 11/30/2023] Open
Abstract
Magnetic resonance imaging (MRI) has been extensively applied in the study of multiple sclerosis (MS), substantially contributing to diagnosis, differential diagnosis, and disease monitoring. MRI studies have significantly contributed to the understanding of MS through the characterization of typical radiological features and their clinical or prognostic implications using conventional MRI pulse sequences and further with the application of advanced imaging techniques sensitive to microstructural damage. Interpretation of results has often been validated by MRI-pathology studies. However, the application of MRI techniques in the study of neuromyelitis optica spectrum disorders (NMOSD) remains an emerging field, and MRI studies have focused on radiological correlates of NMOSD and its pathophysiology to aid in diagnosis, improve monitoring, and identify relevant prognostic factors. In this review, we discuss the main contributions of MRI to the understanding of MS and NMOSD, focusing on the most novel discoveries to clarify differences in the pathophysiology of focal inflammation initiation and perpetuation, involvement of normal-appearing tissue, potential entry routes of pathogenic elements into the CNS, and existence of primary or secondary mechanisms of neurodegeneration.
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Affiliation(s)
- Laura Cacciaguerra
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milano, Italy.
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18
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Wang M, Liu C, Zou M, Niu Z, Zhu J, Jin T. Recent progress in epidemiology, clinical features, and therapy of multiple sclerosis in China. Ther Adv Neurol Disord 2023; 16:17562864231193816. [PMID: 37719665 PMCID: PMC10504852 DOI: 10.1177/17562864231193816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 07/24/2023] [Indexed: 09/19/2023] Open
Abstract
Multiple sclerosis (MS) is a demyelinating disease of the central nervous system characterized by inflammation, demyelination, and neurodegeneration. It mainly affects young adults, imposing a heavy burden on families and society. The epidemiology, clinical features, and management of MS are distinct among different countries. Although MS is a rare disease in China, there are 1.4 billion people in China, so the total number of MS patients is not small. Because of the lack of specific diagnostic biomarkers for MS, there is a high misdiagnosis rate in China, as in other regions. Due to different genetic backgrounds, the clinical manifestations of MS in Chinese are different from those in the West. Herein, this review aims to summarize the disease comprehensively, including clinical profile and the status of disease-modifying therapies in China based on published population-based observation and cohort studies, and also to compare with data from other countries and regions, thus providing help to develop diagnostic guideline and the novel therapeutic drugs. Meanwhile, we also discuss the problems and challenges we face, specifically for the diagnosis and treatment of MS in the middle- and low-income countries.
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Affiliation(s)
- Meng Wang
- Neuroscience Center, Department of Neurology, The First Hospital of Jilin University, Changchun, China
| | - Caiyun Liu
- Neuroscience Center, Department of Neurology, The First Hospital of Jilin University, Changchun, China
| | - Meijuan Zou
- Neuroscience Center, Department of Neurology, The First Hospital of Jilin University, Changchun, China
| | - Zixuan Niu
- Neuroscience Center, Department of Neurology, The First Hospital of Jilin University, Changchun, China
| | - Jie Zhu
- Neuroscience Center, Department of Neurology, The First Hospital of Jilin University, No. 1, Xinmin Street, Changchun 130021, China
- Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Karolinska University Hospital, Solna, Stockholm 171 64, Sweden
| | - Tao Jin
- Neuroscience Center, Department of Neurology, The First Hospital of Jilin University, No. 1, Xinmin Street, Changchun 130021, China
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19
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Carnero Contentti E, Okuda DT, Rojas JI, Chien C, Paul F, Alonso R. MRI to differentiate multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. J Neuroimaging 2023; 33:688-702. [PMID: 37322542 DOI: 10.1111/jon.13137] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 06/17/2023] Open
Abstract
Differentiating multiple sclerosis (MS) from other relapsing inflammatory autoimmune diseases of the central nervous system such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is crucial in clinical practice. The differential diagnosis may be challenging but making the correct ultimate diagnosis is critical, since prognosis and treatments differ, and inappropriate therapy may promote disability. In the last two decades, significant advances have been made in MS, NMOSD, and MOGAD including new diagnostic criteria with better characterization of typical clinical symptoms and suggestive imaging (magnetic resonance imaging [MRI]) lesions. MRI is invaluable in making the ultimate diagnosis. An increasing amount of new evidence with respect to the specificity of observed lesions as well as the associated dynamic changes in the acute and follow-up phase in each condition has been reported in distinct studies recently published. Additionally, differences in brain (including the optic nerve) and spinal cord lesion patterns between MS, aquaporin4-antibody-positive NMOSD, and MOGAD have been described. We therefore present a narrative review on the most relevant findings in brain, spinal cord, and optic nerve lesions on conventional MRI for distinguishing adult patients with MS from NMOSD and MOGAD in clinical practice. In this context, cortical and central vein sign lesions, brain and spinal cord lesions characteristic of MS, NMOSD, and MOGAD, optic nerve involvement, role of MRI at follow-up, and new proposed diagnostic criteria to differentiate MS from NMOSD and MOGAD were discussed.
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Affiliation(s)
| | - Darin T Okuda
- Department of Neurology, Neuroinnovation Program, Multiple Sclerosis & Neuroimmunology Imaging Program, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Juan I Rojas
- Centro de esclerosis múltiple de Buenos Aires, Buenos Aires, Argentina
| | - Claudia Chien
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Friedemman Paul
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ricardo Alonso
- Centro Universitario de Esclerosis Múltiple (CUEM), Hospital Ramos Mejía, Buenos Aires, Argentina
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20
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Statsenko Y, Smetanina D, Arora T, Östlundh L, Habuza T, Simiyu GL, Meribout S, Talako T, King FC, Makhnevych I, Gelovani JG, Das KM, Gorkom KNV, Almansoori TM, Al Zahmi F, Szólics M, Ismail F, Ljubisavljevic M. Multimodal diagnostics in multiple sclerosis: predicting disability and conversion from relapsing-remitting to secondary progressive disease course - protocol for systematic review and meta-analysis. BMJ Open 2023; 13:e068608. [PMID: 37451729 PMCID: PMC10351237 DOI: 10.1136/bmjopen-2022-068608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 05/03/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND The number of patients diagnosed with multiple sclerosis (MS) has increased significantly over the last decade. The challenge is to identify the transition from relapsing-remitting to secondary progressive MS. Since available methods to examine patients with MS are limited, both the diagnostics and prognostication of disease progression would benefit from the multimodal approach. The latter combines the evidence obtained from disparate radiologic modalities, neurophysiological evaluation, cognitive assessment and molecular diagnostics. In this systematic review we will analyse the advantages of multimodal studies in predicting the risk of conversion to secondary progressive MS. METHODS AND ANALYSIS We will use peer-reviewed publications available in Web of Science, Medline/PubMed, Scopus, Embase and CINAHL databases. In vivo studies reporting the predictive value of diagnostic methods will be considered. Selected publications will be processed through Covidence software for automatic deduplication and blind screening. Two reviewers will use a predefined template to extract the data from eligible studies. We will analyse the performance metrics (1) for the classification models reflecting the risk of secondary progression: sensitivity, specificity, accuracy, area under the receiver operating characteristic curve, positive and negative predictive values; (2) for the regression models forecasting disability scores: the ratio of mean absolute error to the range of values. Then, we will create ranking charts representing performance of the algorithms for calculating disability level and MS progression. Finally, we will compare the predictive power of radiological and radiomical correlates of clinical disability and cognitive impairment in patients with MS. ETHICS AND DISSEMINATION The study does not require ethical approval because we will analyse publicly available literature. The project results will be published in a peer-review journal and presented at scientific conferences. PROSPERO REGISTRATION NUMBER CRD42022354179.
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Affiliation(s)
- Yauhen Statsenko
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Medical Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
- Big Data Analytics Center, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE
| | - Darya Smetanina
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Medical Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
| | - Teresa Arora
- Psychology Department, College of Natural and Health Sciences, Zayed University, Abu Dhabi, Abu Dhabi Emirate, UAE
| | - Linda Östlundh
- National Medical Library, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE
- Library, Örebro University, Örebro, Sweden
| | - Tetiana Habuza
- Big Data Analytics Center, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE
- Department of Computer Science, College of Information Technology, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE
| | - Gillian Lylian Simiyu
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Medical Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
| | - Sarah Meribout
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Medical Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
- Internal Medicine Department, Maimonides Medical Center, New York, New York, USA
| | - Tatsiana Talako
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Department of Oncohematology, Minsk Scientific and Practical Center for Surgery, Transplantology and Hematology, Minsk, Belarus
| | - Fransina Christina King
- Physiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Neuroscience Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
| | - Iryna Makhnevych
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
| | - Juri George Gelovani
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Biomedical Engineering Department, Wayne State University, College of Engineering, Detroit, Michigan, USA
- Radiology Department, Siriraj Hospital, Faculty of Medicine, Mahidol University, Bangkok, Thailand
- Provost Office, United Arab Emirates University, Al Ain, Abu Dhabi Emirate, UAE
| | - Karuna M Das
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
| | - Klaus Neidl-Van Gorkom
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
| | - Taleb M Almansoori
- Radiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
| | - Fatmah Al Zahmi
- Neurology Department, Mediclinic Parkview Hospital, Dubai, Dubai Emirate, UAE
- Neurology Department, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, Dubai Emirate, UAE
| | - Miklós Szólics
- Internal Medicine Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Division of Neurology, Department of Medicine, Tawam Hospital, Al Ain, Abu Dhabi Emirate, UAE
| | - Fatima Ismail
- Pediatrics Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi, UAE
| | - Milos Ljubisavljevic
- Physiology Department, United Arab Emirates University, College of Medicine and Health Sciences, Al Ain, Abu Dhabi Emirate, UAE
- Neuroscience Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain, Abu Dhabi Emirate, UAE
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21
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de Caneda MAG, Rizzo MRL, Furlin G, Kupske A, Valentini BB, Ortiz RF, Silva CBDO, de Vecino MCA. Interrater reliability for the detection of cortical lesions on phase-sensitive inversion recovery magnetic resonance imaging in patients with multiple sclerosis. Radiol Bras 2023; 56:187-194. [PMID: 37829590 PMCID: PMC10567094 DOI: 10.1590/0100-3984.2022.0116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 02/15/2023] [Accepted: 05/09/2023] [Indexed: 10/14/2023] Open
Abstract
Objective To assess the reliability of phase-sensitive inversion recovery (PSIR) magnetic resonance imaging (MRI) and its accuracy for determining the topography of demyelinating cortical lesions in patients with multiple sclerosis (MS). Materials and Methods This was a cross-sectional study conducted at a tertiary referral center for MS and other demyelinating disorders. We assessed the agreement among three raters for the detection and topographic classification of cortical lesions on fluid-attenuated inversion recovery (FLAIR) and PSIR sequences in patients with MS. Results We recruited 71 patients with MS. The PSIR sequences detected 50% more lesions than did the FLAIR sequences. For detecting cortical lesions, the level of interrater agreement was satisfactory, with a mean free-response kappa (κFR) coefficient of 0.60, whereas the mean κFR for the topographic reclassification of the lesions was 0.57. On PSIR sequences, the raters reclassified 366 lesions (20% of the lesions detected on FLAIR sequences), with excellent interrater agreement. There was a significant correlation between the total number of lesions detected on PSIR sequences and the Expanded Disability Status Scale score (ρ = 0.35; p < 0.001). Conclusion It seems that PSIR sequences perform better than do FLAIR sequences, with clinically satisfactory interrater agreement, for the detection and topographic classification of cortical lesions. In our sample of patients with MS, the PSIR MRI findings were significantly associated with the disability status, which could influence decisions regarding the treatment of such patients.
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22
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Jacobs BM, Daruwalla C, McKeon MO, Al-Najjar R, Simcock-Davies A, Tuite-Dalton K, Brown JWL, Dobson R, Rodgers J, Middleton R. Early depressive symptoms and disability accrual in Multiple Sclerosis: a UK MS Register study. Sci Rep 2023; 13:8227. [PMID: 37225828 DOI: 10.1038/s41598-023-34545-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 05/03/2023] [Indexed: 05/26/2023] Open
Abstract
Understanding the associations and potential drivers of long-term disability in Multiple Sclerosis (MS) is of clinical and prognostic value. Previous data have suggested a link between depression and disability accrual in MS. We aimed to determine whether depression in early MS predicts subsequent accrual of disability. Using data from the UK MS Register, we identified individuals with and without symptoms of depression and anxiety close to disease onset. We used Cox proportional hazards regression to evaluate whether early depressive or anxiety symptoms predict subsequent physical disability worsening, measured using the Expanded Disability Status Scale (EDSS). We analysed data from 862 people with MS of whom 134 (15.5%) reached an EDSS of ≥ 6.0. Early depressive symptoms were associated with an increased risk of reaching an EDSS of 6.0 (HR 2.42, 95% CI 1.49-3.95, p < 0.001), however this effect dissipated when adjusting for baseline EDSS (HR 1.40, 95% CI 0.84-2.32, p = 0.2). These data suggest that early depressive symptoms in MS are associated with subsequent disability accrual, but are likely the result of disability rather than its cause.
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Affiliation(s)
- Benjamin M Jacobs
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
- Department of Neurology, Royal London Hospital, London, UK
| | - Cyrus Daruwalla
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Mollie O McKeon
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Raghda Al-Najjar
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | | | | | - J William L Brown
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Ruth Dobson
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
- Department of Neurology, Royal London Hospital, London, UK
| | - Jeff Rodgers
- Population Data Science, Swansea University Medical School, Swansea, UK
| | - Rod Middleton
- Population Data Science, Swansea University Medical School, Swansea, UK.
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23
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Zingaropoli MA, Pasculli P, Tartaglia M, Dominelli F, Ciccone F, Taglietti A, Perri V, Malimpensa L, Ferrazzano G, Iannetta M, Del Borgo C, Lichtner M, Mastroianni CM, Conte A, Ciardi MR. Evaluation of BAFF, APRIL and CD40L in Ocrelizumab-Treated pwMS and Infectious Risk. BIOLOGY 2023; 12:biology12040587. [PMID: 37106787 PMCID: PMC10135639 DOI: 10.3390/biology12040587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/04/2023] [Accepted: 04/11/2023] [Indexed: 04/29/2023]
Abstract
BACKGROUND The anti-CD20 monoclonal antibody ocrelizumab has been widely employed in the treatment of people with multiple sclerosis (pwMS). However, its B-cell-depleting effect may induce a higher risk of infectious events and alterations in the secretion of B-cell-activating factors, such as BAFF, APRIL and CD40L. METHODS The aim of this study was to investigate plasma BAFF, APRIL and CD40L levels and their relationship with infectious risk in ocrelizumab-treated pwMS at baseline (T0), at 6 months (T6) and at 12 months (T12) after starting the treatment. As a control group, healthy donors (HD) were enrolled too. RESULTS A total of 38 pwMS and 26 HD were enrolled. At baseline, pwMS showed higher plasma BAFF (p < 0.0001), APRIL (p = 0.0223) and CD40L (p < 0.0001) levels compared to HD. Compared to T0, plasma BAFF levels were significantly increased at both T6 and T12 (p < 0.0001 and p < 0.0001, respectively). Whereas plasma APRIL and CD40L levels were decreased at T12 (p = 0.0003 and p < 0.0001, respectively). When stratifying pwMS according to the development of an infectious event during the 12-month follow-up period in two groups-with (14) and without an infectious event (24)-higher plasma BAFF levels were observed at all time-points; significantly, in the group with an infectious event compared to the group without an infectious event (T0: p < 0.0001, T6: p = 0.0056 and T12: p = 0.0400). Conclusions: BAFF may have a role as a marker of immune dysfunction and of infectious risk.
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Affiliation(s)
| | - Patrizia Pasculli
- Department of Public Health and Infectious Diseases, Sapienza University of Rome, 00185 Rome, Italy
| | - Matteo Tartaglia
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Federica Dominelli
- Department of Public Health and Infectious Diseases, Sapienza University of Rome, 00185 Rome, Italy
| | - Federica Ciccone
- Department of Public Health and Infectious Diseases, Sapienza University of Rome, 00185 Rome, Italy
| | - Ambra Taglietti
- Department of Public Health and Infectious Diseases, Sapienza University of Rome, 00185 Rome, Italy
| | - Valentina Perri
- Department of Public Health and Infectious Diseases, Sapienza University of Rome, 00185 Rome, Italy
| | - Leonardo Malimpensa
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Gina Ferrazzano
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Marco Iannetta
- Infectious Disease Unit, Department of System Medicine, Tor Vergata University and Hospital, 00133 Rome, Italy
| | - Cosmo Del Borgo
- Infectious Diseases Unit, Santa Maria Goretti Hospital, Sapienza University of Rome, 04110 Latina, Italy
| | - Miriam Lichtner
- Infectious Diseases Unit, Santa Maria Goretti Hospital, Sapienza University of Rome, 04110 Latina, Italy
- Department of Neurosciences Mental Health and Sensory Organs, Sapienza University of Rome, 00185 Rome, Italy
| | | | - Antonella Conte
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
- IRCCS Neuromed, 86077 Pozzilli, Italy
| | - Maria Rosa Ciardi
- Department of Public Health and Infectious Diseases, Sapienza University of Rome, 00185 Rome, Italy
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24
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Zhou W, Graner M, Paucek P, Beseler C, Boisen M, Bubak A, Asturias F, George W, Graner A, Ormond D, Vollmer T, Alvarez E, Yu X. Multiple sclerosis plasma IgG aggregates induce complement-dependent neuronal apoptosis. Cell Death Dis 2023; 14:254. [PMID: 37031195 PMCID: PMC10082781 DOI: 10.1038/s41419-023-05783-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 03/23/2023] [Accepted: 03/27/2023] [Indexed: 04/10/2023]
Abstract
Grey matter pathology is central to the progression of multiple sclerosis (MS). We discovered that MS plasma immunoglobulin G (IgG) antibodies, mainly IgG1, form large aggregates (>100 nm) which are retained in the flow-through after binding to Protein A. Utilizing an annexin V live-cell apoptosis detection assay, we demonstrated six times higher levels of neuronal apoptosis induced by MS plasma IgG aggregates (n = 190, from two cohorts) compared to other neurological disorders (n = 116) and healthy donors (n = 44). MS IgG aggregate-mediated, complement-dependent neuronal apoptosis was evaluated in multiple model systems including primary human neurons, primary human astrocytes, neuroblastoma SH-SY5Y cells, and newborn mouse brain slices. Immunocytochemistry revealed the co-deposition of IgG, early and late complement activation products (C1q, C3b, and membrane attack complex C5b9), as well as active caspase 3 in treated neuronal cells. Furthermore, we found that MS plasma cytotoxic antibodies are not present in Protein G flow-through, nor in the paired plasma. The neuronal apoptosis can be inhibited by IgG depletion, disruption of IgG aggregates, pan-caspase inhibitor, and is completely abolished by digestion with IgG-cleaving enzyme IdeS. Transmission electron microscopy and nanoparticle tracking analysis revealed the sizes of MS IgG aggregates are greater than 100 nm. Our data support the pathological role of MS IgG antibodies and corroborate their connection to complement activation and axonal damage, suggesting that apoptosis may be a mechanism of neurodegeneration in MS.
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Affiliation(s)
- Wenbo Zhou
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA
| | - Michael Graner
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA
| | - Petr Paucek
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA
| | - Cheryl Beseler
- Department of Environmental, Agricultural and Occupational Health, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Matthew Boisen
- Zalgen Labs, LLC, 12635 E. Montview Blvd., Suite 131, Aurora, Colorado, 80045, USA
| | - Andrew Bubak
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA
| | - Francisco Asturias
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA
| | - Woro George
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA
| | - Arin Graner
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA
| | - David Ormond
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA
| | - Timothy Vollmer
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA
| | - Enrique Alvarez
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA
| | - Xiaoli Yu
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, 80045, USA.
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25
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Early Predictors of Disability and Cognition in Multiple Sclerosis Patients: A Long-Term Retrospective Analysis. J Clin Med 2023; 12:jcm12020685. [PMID: 36675614 PMCID: PMC9864935 DOI: 10.3390/jcm12020685] [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: 11/09/2022] [Revised: 12/27/2022] [Accepted: 01/13/2023] [Indexed: 01/18/2023] Open
Abstract
We conducted a retrospective analysis on multiple sclerosis (MS) patients with perceived cognitive decline and long disease duration to investigate early predictors of future cognitive impairment (CI) and motor disability. Sixty-five patients complaining of cognitive decline were assessed with an extensive neuropsychological battery at the last clinical follow-up and classified as mildly impaired, severely impaired, and cognitively spared based on the results. Motor disability was assessed with EDSS, MSSS, and ARMSS. Baseline demographic, clinical, and imaging parameters were retrospectively collected and inserted in separate multivariate regression models to investigate the predictive power of future impairment. Twenty-one patients (32.3%) showed no CI, seventeen (26.2%) showed mild CI, and twenty-seven (41.5%) showed severe CI. Older and less educated patients with higher EDSS, longer disease duration, and higher white matter lesion load (WMLL) at diagnosis (particularly with cerebellar involvement) were more likely to develop CI after a mean follow-up from diagnosis of 16.5 ± 6.9 years. DMT exposure was protective. The multivariate regression analyses confirmed WMLL, disease duration, and educational levels as the parameters with significant predictive value for future CI (R2 adjusted: 0.338 p: 0.001). Older patients with progressive phenotype both at diagnosis and T1 were more likely to be not fully ambulatory at T1 (R2 adjusted: 0.796 p: 0.0001). Our results further expand knowledge on early predictors of cognitive decline and evolution over time.
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26
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Attfield KE, Jensen LT, Kaufmann M, Friese MA, Fugger L. The immunology of multiple sclerosis. Nat Rev Immunol 2022; 22:734-750. [PMID: 35508809 DOI: 10.1038/s41577-022-00718-z] [Citation(s) in RCA: 110] [Impact Index Per Article: 55.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/30/2022] [Indexed: 12/11/2022]
Abstract
Our incomplete understanding of the causes and pathways involved in the onset and progression of multiple sclerosis (MS) limits our ability to effectively treat this complex neurological disease. Recent studies explore the role of immune cells at different stages of MS and how they interact with cells of the central nervous system (CNS). The findings presented here begin to question the exclusivity of an antigen-specific cause and highlight how seemingly distinct immune cell types can share common functions that drive disease. Innovative techniques further expose new disease-associated immune cell populations and reinforce how environmental context is critical to their phenotype and subsequent role in disease. Importantly, the differentiation of immune cells into a pathogenic state is potentially reversible through therapeutic manipulation. As such, understanding the mechanisms that provide plasticity to causal cell types is likely key to uncoupling these disease processes and may identify novel therapeutic targets that replace the need for cell ablation.
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Affiliation(s)
- Kathrine E Attfield
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, Oxford University Hospitals, University of Oxford, Oxford, UK
| | - Lise Torp Jensen
- Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Max Kaufmann
- Institut für Neuroimmunologie und Multiple Sklerose, Zentrum für Molekulare Neurobiologie Hamburg, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Manuel A Friese
- Institut für Neuroimmunologie und Multiple Sklerose, Zentrum für Molekulare Neurobiologie Hamburg, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Lars Fugger
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, Oxford University Hospitals, University of Oxford, Oxford, UK.
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK.
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27
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La Rosa F, Wynen M, Al-Louzi O, Beck ES, Huelnhagen T, Maggi P, Thiran JP, Kober T, Shinohara RT, Sati P, Reich DS, Granziera C, Absinta M, Bach Cuadra M. Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues. Neuroimage Clin 2022; 36:103205. [PMID: 36201950 PMCID: PMC9668629 DOI: 10.1016/j.nicl.2022.103205] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 09/09/2022] [Accepted: 09/16/2022] [Indexed: 12/14/2022]
Abstract
The current diagnostic criteria for multiple sclerosis (MS) lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progression. Recently, some MS lesional imaging biomarkers such as cortical lesions (CL), the central vein sign (CVS), and paramagnetic rim lesions (PRL), visible in specialized magnetic resonance imaging (MRI) sequences, have shown higher specificity in differential diagnosis. Moreover, studies have shown that CL and PRL are potential prognostic biomarkers, the former correlating with cognitive impairments and the latter with early disability progression. As machine learning-based methods have achieved extraordinary performance in the assessment of conventional imaging biomarkers, such as white matter lesion segmentation, several automated or semi-automated methods have been proposed as well for CL, PRL, and CVS. In the present review, we first introduce these MS biomarkers and their imaging methods. Subsequently, we describe the corresponding machine learning-based methods that were proposed to tackle these clinical questions, putting them into context with respect to the challenges they are facing, including non-standardized MRI protocols, limited datasets, and moderate inter-rater variability. We conclude by presenting the current limitations that prevent their broader deployment and suggesting future research directions.
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Key Words
- ms, multiple sclerosis
- mri, magnetic resonance imaging
- dl, deep learning
- ml, machine learning
- cl, cortical lesions
- prl, paramagnetic rim lesions
- cvs, central vein sign
- wml, white matter lesions
- flair, fluid-attenuated inversion recovery
- mprage, magnetization prepared rapid gradient-echo
- gm, gray matter
- wm, white matter
- psir, phase-sensitive inversion recovery
- dir, double inversion recovery
- mp2rage, magnetization-prepared 2 rapid gradient echoes
- sels, slowly evolving/expanding lesions
- cnn, convolutional neural network
- xai, explainable ai
- pv, partial volume
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Affiliation(s)
- Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Maxence Wynen
- CIBM Center for Biomedical Imaging, Switzerland; ICTeam, UCLouvain, Louvain-la-Neuve, Belgium; Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Omar Al-Louzi
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Erin S Beck
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Till Huelnhagen
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Pietro Maggi
- Louvain Inflammation Imaging Lab (NIL), Institute of Neuroscience (IoNS), UCLouvain, Brussels, Belgium; Department of Neurology, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium; Department of Neurology, CHUV, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
| | - Tobias Kober
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Russell T Shinohara
- Center for Biomedical Image Computing and Analysis (CBICA), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA; Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Switzerland; Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Martina Absinta
- IRCCS San Raffaele Hospital and Vita-Salute San Raffaele University, Milan, Italy; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Lausanne University and University Hospital, Switzerland
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Response to the letter synthetic double inversion recovery (DIR) and phase-sensitive inversion recovery (PSIR) images showed better delineation of multiple sclerosis plaques. Neuroradiology 2022; 64:1915-1916. [PMID: 36066632 DOI: 10.1007/s00234-022-03040-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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Abstract
PURPOSE OF REVIEW This article provides an update on progressive forms of multiple sclerosis (MS) commonly referred to as primary progressive MS and secondary progressive MS. It discusses the importance of diagnosing and detecting progression early, the similarities between progressive forms, challenges in detecting progression, factors that could augment progression, and the importance of disease-modifying therapies in patients with evidence of active progressive MS. It also discusses the overall care of progressive MS. RECENT FINDINGS The pathogenesis of primary progressive MS and secondary progressive MS is overlapping, and in both presentations, patients with relapses or focal MRI activity are classified as having active, progressive MS. All currently approved disease-modifying therapies are indicated for active secondary progressive MS. The therapeutic opportunity of anti-inflammatory drugs for the treatment of progressive MS is enhanced in those who are younger and have a shorter disease duration. Vascular comorbidities may contribute to progression in MS. SUMMARY Several challenges remain in the diagnosis, follow-up, and treatment of progressive MS. Early identification of active progressive MS is needed to maximize treatment benefit. The advantages of optimal comorbidity management (eg, hypertension, hyperlipidemia) in delaying progression are uncertain. Clinical care guidelines for advanced, severe MS are lacking.
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The Possible Role of Neural Cell Apoptosis in Multiple Sclerosis. Int J Mol Sci 2022; 23:ijms23147584. [PMID: 35886931 PMCID: PMC9316123 DOI: 10.3390/ijms23147584] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/04/2022] [Accepted: 07/05/2022] [Indexed: 11/17/2022] Open
Abstract
The etiology of multiple sclerosis (MS), a demyelinating disease affecting the central nervous system (CNS), remains obscure. Although apoptosis of oligodendrocytes and neurons has been observed in MS lesions, the contribution of this cell death process to disease pathogenesis remains controversial. It is usually considered that MS-associated demyelination and axonal degeneration result from neuroinflammation and an autoimmune process targeting myelin proteins. However, experimental data indicate that oligodendrocyte and/or neuronal cell death may indeed precede the development of inflammation and autoimmunity. These findings raise the question as to whether neural cell apoptosis is the key event initiating and/or driving the pathological cascade, leading to clinical functional deficits in MS. Similarly, regarding axonal damage, a key pathological feature of MS lesions, the roles of inflammation-independent and cell autonomous neuronal processes need to be further explored. While oligodendrocyte and neuronal loss in MS may not necessarily be mutually exclusive, particular attention should be given to the role of neuronal apoptosis in the development of axonal loss. If proven, MS could be viewed primarily as a neurodegenerative disease accompanied by a secondary neuroinflammatory and autoimmune process.
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Kaufmann M, Schaupp AL, Sun R, Coscia F, Dendrou CA, Cortes A, Kaur G, Evans HG, Mollbrink A, Navarro JF, Sonner JK, Mayer C, DeLuca GC, Lundeberg J, Matthews PM, Attfield KE, Friese MA, Mann M, Fugger L. Identification of early neurodegenerative pathways in progressive multiple sclerosis. Nat Neurosci 2022; 25:944-955. [PMID: 35726057 DOI: 10.1038/s41593-022-01097-3] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 05/16/2022] [Indexed: 11/08/2022]
Abstract
Progressive multiple sclerosis (MS) is characterized by unrelenting neurodegeneration, which causes cumulative disability and is refractory to current treatments. Drug development to prevent disease progression is an urgent clinical need yet is constrained by an incomplete understanding of its complex pathogenesis. Using spatial transcriptomics and proteomics on fresh-frozen human MS brain tissue, we identified multicellular mechanisms of progressive MS pathogenesis and traced their origin in relation to spatially distributed stages of neurodegeneration. By resolving ligand-receptor interactions in local microenvironments, we discovered defunct trophic and anti-inflammatory intercellular communications within areas of early neuronal decline. Proteins associated with neuronal damage in patient samples showed mechanistic concordance with published in vivo knockdown and central nervous system (CNS) disease models, supporting their causal role and value as potential therapeutic targets in progressive MS. Our findings provide a new framework for drug development strategies, rooted in an understanding of the complex cellular and signaling dynamics in human diseased tissue that facilitate this debilitating disease.
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Affiliation(s)
- Max Kaufmann
- Institut für Neuroimmunologie und Multiple Sklerose, Zentrum für Molekulare Neurobiologie Hamburg, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Anna-Lena Schaupp
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Rosa Sun
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Neurosurgery, Queen Elizabeth Hospital, Birmingham, UK
| | - Fabian Coscia
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Spatial Proteomics Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Calliope A Dendrou
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Adrian Cortes
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Gurman Kaur
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hayley G Evans
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Annelie Mollbrink
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Solna, Sweden
| | - José Fernández Navarro
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Solna, Sweden
| | - Jana K Sonner
- Institut für Neuroimmunologie und Multiple Sklerose, Zentrum für Molekulare Neurobiologie Hamburg, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Christina Mayer
- Institut für Neuroimmunologie und Multiple Sklerose, Zentrum für Molekulare Neurobiologie Hamburg, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Gabriele C DeLuca
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, UK
| | - Joakim Lundeberg
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Solna, Sweden
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, London, UK
- UK Dementia Research Institute, Imperial College London, London, UK
| | - Kathrine E Attfield
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Manuel A Friese
- Institut für Neuroimmunologie und Multiple Sklerose, Zentrum für Molekulare Neurobiologie Hamburg, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Matthias Mann
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Lars Fugger
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, UK.
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Marastoni D, Crescenzo F, Pisani AI, Zuco C, Schiavi G, Benedetti G, Ricciardi GK, Montemezzi S, Pizzini FB, Tamanti A, Calabrese M. Two years' effect of dimethyl fumarate on focal and diffuse gray matter pathology in multiple sclerosis. Mult Scler 2022; 28:2090-2098. [PMID: 35765211 DOI: 10.1177/13524585221104014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Data on the effect of dimethyl fumarate (DMF) on focal and diffuse gray matter (GM) damage, a relevant pathological substrate of multiple sclerosis (MS)-related disability are lacking. OBJECTIVE To evaluate the DMF effect on cortical lesions (CLs) accumulation and global and regional GM atrophy in subjects with relapsing-remitting MS. METHODS A total of 148 patients (mean age 38.1 ± 9.7 years) treated with DMF ended a 2-year longitudinal study. All underwent regular Expanded Disability Status Scale (EDSS assessment), and at least two 3T-magnetic resonance imaging (MRI) at 3 and 24 months after DMF initiation. CLs and changes in global and regional atrophy of several brain regions were compared with 47 untreated age and sex-matched patients. RESULTS DMF-treated patients showed lower CLs accumulation (median 0[0-3] vs 2[0-7], p < 0.001) with respect to controls. Global cortical thickness (p < 0.001) and regional thickness and volume were lower in treated group (cerebellum, hippocampus, caudate, and putamen: p < 0.001; thalamus p = 0.03). Lower relapse rate (14% vs 40%, p < 0.001), EDSS change (0.2 ± 0.4 vs 0.4 ± 0.9, p < 0.001), and new WM lesions (median 0[0-5] vs 2[0-6], p < 0.001) were reported. No severe adverse drug reactions occurred. CONCLUSIONS Beyond the well-known effect on disease activity, these results provide evidence of the effect of DMF through reduced progression of focal and diffuse GM damage.
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Affiliation(s)
- Damiano Marastoni
- Regional Multiple Sclerosis Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | | | - Anna I Pisani
- Regional Multiple Sclerosis Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Carmela Zuco
- Neurology Unit, "Carlo Poma" Hospital, ASST Mantua, Mantua, Italy
| | - Gianmarco Schiavi
- Regional Multiple Sclerosis Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Giulia Benedetti
- Regional Multiple Sclerosis Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Giuseppe K Ricciardi
- Neuroradiology & Radiology Units, Department of Diagnostic and Pathology, Integrated University Hospital of Verona, Verona, Italy
| | - Stefania Montemezzi
- Neuroradiology & Radiology Units, Department of Diagnostic and Pathology, Integrated University Hospital of Verona, Verona, Italy
| | - Francesca B Pizzini
- Radiology Unit, Department of Diagnostic and Public Health, University of Verona, Verona, Italy
| | - Agnese Tamanti
- Regional Multiple Sclerosis Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Massimiliano Calabrese
- Regional Multiple Sclerosis Center, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
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33
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Marastoni D, Pisani AI, Schiavi G, Mazziotti V, Castellaro M, Tamanti A, Bosello F, Crescenzo F, Ricciardi GK, Montemezzi S, Pizzini FB, Calabrese M. CSF TNF and osteopontin levels correlate with the response to dimethyl fumarate in early multiple sclerosis. Ther Adv Neurol Disord 2022; 15:17562864221092124. [PMID: 35755969 PMCID: PMC9218430 DOI: 10.1177/17562864221092124] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 03/18/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Disease activity in the first years after a diagnosis of relapsing-remitting multiple sclerosis (RRMS) is a negative prognostic factor for long-term disability. Markers of both clinical and radiological responses to disease-modifying therapies (DMTs) are advocated. Objective: The objective of this study is to estimate the value of cerebrospinal fluid (CSF) inflammatory markers at the time of diagnosis in predicting the disease activity in treatment-naïve multiple sclerosis (MS) patients exposed to dimethyl fumarate (DMF). Methods: In total, 48 RRMS patients (31 females/17 males) treated with DMF after the diagnosis were included in this 2-year longitudinal study. All patients underwent a CSF examination, regular clinical and 3T magnetic resonance imaging (MRI) scans that included the assessment of white matter (WM) lesions, cortical lesions (CLs) and global cortical thickness. CSF levels of 10 pro-inflammatory markers – CXCL13 [chemokine (C-X-C motif) ligand 13 or B lymphocyte chemoattractant], CXCL12 (stromal cell-derived factor or C-X-C motif chemokine 12), tumour necrosis factor (TNF), APRIL (a proliferation-inducing ligand, or tumour necrosis factor ligand superfamily member 13), LIGHT (tumour necrosis factor ligand superfamily member 14 or tumour necrosis factor superfamily member 14), interferon (IFN) gamma, interleukin 12 (IL-12), osteopontin, sCD163 [soluble-CD163 (cluster of differentiation 163)] and Chitinase3-like1 – were assessed using immune-assay multiplex techniques. The combined three-domain status of ‘no evidence of disease activity’ (NEDA-3) was defined by no relapses, no disability worsening and no MRI activity, including CLs. Results: Twenty patients (42%) reached the NEDA-3 status; patients with disease activity showed higher CSF TNF (p = 0.009), osteopontin (p = 0.005), CXCL12 (p = 0.037), CXCL13 (p = 0.040) and IFN gamma levels (p = 0.019) compared with NEDA-3 patients. After applying a random forest approach, TNF and osteopontin revealed the most important variables associated with the NEDA-3 status. Six molecules that emerged at the random forest approach were added in a multivariate regression model with demographic, clinical and MRI measures of WM and grey matter damage as independent variables. TNF levels confirmed to be associated with the absence of disease activity: odds ratio (OR) = 0.25, CI% = 0.04–0.77. Conclusion: CSF inflammatory markers may provide prognostic information in predicting disease activity in the first years after DMF initiation. CSF TNF levels are a possible candidate in predicting treatment response, in addition to clinical, demographic and MRI variables.
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Affiliation(s)
- Damiano Marastoni
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Anna I Pisani
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Gianmarco Schiavi
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Valentina Mazziotti
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Marco Castellaro
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Agnese Tamanti
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Francesca Bosello
- Department of Neurosciences, Biomedicine and Movement Sciences, Eye Clinic, Ocular Immunology and Neuroophthalmology Service, AOUI-University of Verona, Verona, Italy
| | - Francesco Crescenzo
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Giuseppe K Ricciardi
- Neuroradiology & Radiology Units, Integrated University Hospital of Verona, Verona, Italy
| | - Stefania Montemezzi
- Neuroradiology & Radiology Units, Integrated University Hospital of Verona, Verona, Italy
| | - Francesca B Pizzini
- Radiology, Department of Diagnostic and Public Health, Integrated University Hospital of Verona, Verona, Italy
| | - Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Policlinico 'G.B. Rossi' Borgo Roma, Piazzale L. A. Scuro, 10, 37134 Verona, Italy
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Madsen MAJ, Wiggermann V, Marques MFM, Lundell H, Cerri S, Puonti O, Blinkenberg M, Christensen JR, Sellebjerg F, Siebner HR. Linking lesions in sensorimotor cortex to contralateral hand function in multiple sclerosis: a 7 T MRI study. Brain 2022; 145:3522-3535. [PMID: 35653498 PMCID: PMC9586550 DOI: 10.1093/brain/awac203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/17/2022] [Accepted: 05/20/2022] [Indexed: 11/14/2022] Open
Abstract
Abstract
Cortical lesions constitute a key manifestation of multiple sclerosis and contribute to clinical disability and cognitive impairment. Yet it is unknown whether local cortical lesions and cortical lesion subtypes contribute to domain-specific impairments attributable to the function of the lesioned cortex.
In this cross-sectional study, we assessed how cortical lesions in the primary sensorimotor hand area (SM1-HAND) relate to corticomotor physiology and sensorimotor function of the contralateral hand. 50 relapse-free patients with relapsing-remitting or secondary-progressive multiple sclerosis and 28 healthy age- and sex-matched participants underwent whole-brain 7 T MRI to map cortical lesions. Brain scans were also used to estimate normalized brain volume, pericentral cortical thickness, white matter lesion fraction of the corticospinal tract, infratentorial lesion volume and the cross-sectional area of the upper cervical spinal cord. We tested sensorimotor hand function and calculated a motor and sensory composite score for each hand. In 37 patients and 20 healthy controls, we measured maximal motor evoked potential (MEP) amplitude, resting motor threshold and corticomotor conduction time with transcranial magnetic stimulation (TMS) and the N20 latency from somatosensory evoked potentials (SSEPs).
Patients showed at least one cortical lesion in the SM1-HAND in 47 of 100 hemispheres. The presence of a lesion was associated with worse contralateral sensory (P = 0.014) and motor (P = 0.009) composite scores. TMS of a lesion-positive SM1-HAND revealed a decreased maximal MEP amplitude (P < 0.001) and delayed corticomotor conduction (P = 0.002) relative to a lesion-negative SM1-HAND. Stepwise mixed linear regressions showed that the presence of an SM1-HAND lesion, higher white-matter lesion fraction of the corticospinal tract, reduced spinal cord cross-sectional area and higher infratentorial lesion volume were associated with reduced contralateral motor hand function. Cortical lesions in SM1-HAND, spinal cord cross-sectional area and normalized brain volume were also associated with smaller maximal MEP amplitude and longer corticomotor conduction times. The effect of cortical lesions on sensory function was no longer significant when controlling for MRI-based covariates. Lastly, we found that intracortical and subpial lesions had the largest effect on reduced motor hand function, intracortical lesions on reduced MEP amplitude and leukocortical lesions on delayed corticomotor conduction.
Together, this comprehensive multi-level assessment of sensorimotor brain damage shows that the presence of a cortical lesion in SM1-HAND is associated with impaired corticomotor function of the hand, after accounting for damage at the subcortical level. The results also provide preliminary evidence that cortical lesion types may affect the various facets of corticomotor function differentially.
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Affiliation(s)
- Mads A. J. Madsen
- Copenhagen University Hospital - Amager & Hvidovre Danish Research Centre for Magnetic Resonance, , 2650 Hvidovre, Denmark
| | - Vanessa Wiggermann
- Copenhagen University Hospital - Amager & Hvidovre Danish Research Centre for Magnetic Resonance, , 2650 Hvidovre, Denmark
| | - Marta F. M. Marques
- Copenhagen University Hospital - Amager & Hvidovre Danish Research Centre for Magnetic Resonance, , 2650 Hvidovre, Denmark
| | - Henrik Lundell
- Copenhagen University Hospital - Amager & Hvidovre Danish Research Centre for Magnetic Resonance, , 2650 Hvidovre, Denmark
| | - Stefano Cerri
- Copenhagen University Hospital - Amager & Hvidovre Danish Research Centre for Magnetic Resonance, , 2650 Hvidovre, Denmark
- Technical University of Denmark Department of Health Technology, , 2800 Kgs. Lyngby, Denmark
| | - Oula Puonti
- Copenhagen University Hospital - Amager & Hvidovre Danish Research Centre for Magnetic Resonance, , 2650 Hvidovre, Denmark
| | - Morten Blinkenberg
- Copenhagen University Hospital – Rigshospitalet Danish Multiple Sclerosis Center, Department of Neurology, , 2600 Glostrup, Denmark
| | - Jeppe Romme Christensen
- Copenhagen University Hospital – Rigshospitalet Danish Multiple Sclerosis Center, Department of Neurology, , 2600 Glostrup, Denmark
| | - Finn Sellebjerg
- Copenhagen University Hospital – Rigshospitalet Danish Multiple Sclerosis Center, Department of Neurology, , 2600 Glostrup, Denmark
- University of Copenhagen Department of Clinical Medicine, , 2200 Copenhagen, Denmark
| | - Hartwig R. Siebner
- Copenhagen University Hospital - Amager & Hvidovre Danish Research Centre for Magnetic Resonance, , 2650 Hvidovre, Denmark
- Copenhagen University Hospital - Bispebjerg & Frederiksberg Department of Neurology, , 2400 Copenhagen, Denmark
- University of Copenhagen Department of Clinical Medicine, , 2200 Copenhagen, Denmark
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Preziosa P, Pagani E, Bonacchi R, Cacciaguerra L, Falini A, Rocca MA, Filippi M. In vivo detection of damage in multiple sclerosis cortex and cortical lesions using NODDI. J Neurol Neurosurg Psychiatry 2022; 93:628-636. [PMID: 34799405 DOI: 10.1136/jnnp-2021-327803] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 10/28/2021] [Indexed: 11/03/2022]
Abstract
OBJECTIVE To characterise in vivo the microstructural abnormalities of multiple sclerosis (MS) normal-appearing (NA) cortex and cortical lesions (CLs) and their relations with clinical phenotypes and disability using neurite orientation dispersion and density imaging (NODDI). METHODS One hundred and seventy-two patients with MS (101 relapsing-remitting multiple sclerosis (RRMS), 71 progressive multiple sclerosis (PMS)) and 62 healthy controls (HCs) underwent a brain 3T MRI. Brain cortex and CLs were segmented from three-dimensional T1-weighted and double inversion recovery sequences. Using NODDI on diffusion-weighted sequence, intracellular volume fraction (ICV_f) and Orientation Dispersion Index (ODI) were assessed in NA cortex and CLs with default or optimised parallel diffusivity for the cortex (D//=1.7 or 1.2 µm2/ms, respectively). RESULTS The NA cortex of patients with MS had significantly lower ICV_f versus HCs' cortex with both D// values (false discovery rate (FDR)-p <0.001). CLs showed significantly decreased ICV_f and ODI versus NA cortex of both HCs and patients with MS with both D// values (FDR-p ≤0.008). Patients with PMS versus RRMS had significantly decreased NA cortex ICV_f and ODI (FDR-p=0.050 and FDR-p=0.032) with only D//=1.7 µm2/ms. No CL microstructural differences were found between MS clinical phenotypes. MS NA cortex ICV_f and ODI were significantly correlated with disease duration, clinical disability, lesion burden and global and regional brain atrophy (r from -0.51 to 0.71, FDR-p from <0.001 to 0.045). CONCLUSIONS A significant neurite loss occurs in MS NA cortex. CLs show a further neurite density reduction and a reduced ODI suggesting a simplification of neurite complexity. NODDI is relevant to investigate in vivo the heterogeneous pathology affecting the MS cortex.
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Affiliation(s)
- Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Raffaello Bonacchi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Laura Cacciaguerra
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Vita-Salute San Raffaele University, Milano, Italy
| | - Andrea Falini
- Vita-Salute San Raffaele University, Milano, Italy.,Department of Neuroradiology, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Vita-Salute San Raffaele University, Milano, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy .,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Vita-Salute San Raffaele University, Milano, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milano, Italy
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Cagol A, Schaedelin S, Barakovic M, Benkert P, Todea RA, Rahmanzadeh R, Galbusera R, Lu PJ, Weigel M, Melie-Garcia L, Ruberte E, Siebenborn N, Battaglini M, Radue EW, Yaldizli Ö, Oechtering J, Sinnecker T, Lorscheider J, Fischer-Barnicol B, Müller S, Achtnichts L, Vehoff J, Disanto G, Findling O, Chan A, Salmen A, Pot C, Bridel C, Zecca C, Derfuss T, Lieb JM, Remonda L, Wagner F, Vargas MI, Du Pasquier R, Lalive PH, Pravatà E, Weber J, Cattin PC, Gobbi C, Leppert D, Kappos L, Kuhle J, Granziera C. Association of Brain Atrophy With Disease Progression Independent of Relapse Activity in Patients With Relapsing Multiple Sclerosis. JAMA Neurol 2022; 79:682-692. [PMID: 35575778 DOI: 10.1001/jamaneurol.2022.1025] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Importance The mechanisms driving neurodegeneration and brain atrophy in relapsing multiple sclerosis (RMS) are not completely understood. Objective To determine whether disability progression independent of relapse activity (PIRA) in patients with RMS is associated with accelerated brain tissue loss. Design, Setting, and Participants In this observational, longitudinal cohort study with median (IQR) follow-up of 3.2 years (2.0-4.9), data were acquired from January 2012 to September 2019 in a consortium of tertiary university and nonuniversity referral hospitals. Patients were included if they had regular clinical follow-up and at least 2 brain magnetic resonance imaging (MRI) scans suitable for volumetric analysis. Data were analyzed between January 2020 and March 2021. Exposures According to the clinical evolution during the entire observation, patients were classified as those presenting (1) relapse activity only, (2) PIRA episodes only, (3) mixed activity, or (4) clinical stability. Main Outcomes and Measures Mean difference in annual percentage change (MD-APC) in brain volume/cortical thickness between groups, calculated after propensity score matching. Brain atrophy rates, and their association with the variables of interest, were explored with linear mixed-effect models. Results Included were 1904 brain MRI scans from 516 patients with RMS (67.4% female; mean [SD] age, 41.4 [11.1] years; median [IQR] Expanded Disability Status Scale score, 2.0 [1.5-3.0]). Scans with insufficient quality were excluded (n = 19). Radiological inflammatory activity was associated with increased atrophy rates in several brain compartments, while an increased annualized relapse rate was linked to accelerated deep gray matter (GM) volume loss. When compared with clinically stable patients, patients with PIRA had an increased rate of brain volume loss (MD-APC, -0.36; 95% CI, -0.60 to -0.12; P = .02), mainly driven by GM loss in the cerebral cortex. Patients who were relapsing presented increased whole brain atrophy (MD-APC, -0.18; 95% CI, -0.34 to -0.02; P = .04) with respect to clinically stable patients, with accelerated GM loss in both cerebral cortex and deep GM. No differences in brain atrophy rates were measured between patients with PIRA and those presenting relapse activity. Conclusions and Relevance Our study shows that patients with RMS and PIRA exhibit accelerated brain atrophy, especially in the cerebral cortex. These results point to the need to recognize the insidious manifestations of PIRA in clinical practice and to further evaluate treatment strategies for patients with PIRA in clinical trials.
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Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Sabine Schaedelin
- Clinical Trial Unit, Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Pascal Benkert
- Clinical Trial Unit, Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Ramona-Alexandra Todea
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland.,Division of Diagnostic and Interventional Neuroradiology, Clinic for Radiology and Nuclear Medicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Reza Rahmanzadeh
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Riccardo Galbusera
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland.,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Lester Melie-Garcia
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Esther Ruberte
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland.,Medical Image Analysis Center (MIAC) and Quantitative Biomedical Imaging Group, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Nina Siebenborn
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Ernst-Wilhelm Radue
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Özgür Yaldizli
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Johanna Oechtering
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Tim Sinnecker
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland.,Medical Image Analysis Center (MIAC) and Quantitative Biomedical Imaging Group, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Johannes Lorscheider
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Bettina Fischer-Barnicol
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Stefanie Müller
- Department of Neurology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Lutz Achtnichts
- Department of Neurology, Cantonal Hospital Aarau, Aarau, Switzerland
| | - Jochen Vehoff
- Department of Neurology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Giulio Disanto
- Neurology Department, Neurocenter of Southern Switzerland, Lugano, Switzerland
| | - Oliver Findling
- Department of Neurology, Cantonal Hospital Aarau, Aarau, Switzerland
| | - Andrew Chan
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Anke Salmen
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Caroline Pot
- Division of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - Claire Bridel
- Division of Neurology, Department of Clinical Neurosciences, Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Chiara Zecca
- Neurology Department, Neurocenter of Southern Switzerland, Lugano, Switzerland.,Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
| | - Tobias Derfuss
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Johanna M Lieb
- Division of Diagnostic and Interventional Neuroradiology, Clinic for Radiology and Nuclear Medicine, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Luca Remonda
- Department of Radiology, Cantonal Hospital Aarau, Aarau, Switzerland
| | - Franca Wagner
- Department of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Maria I Vargas
- Department of Radiology, Faculty of Medicine, Geneva University Hospital, Geneva, Switzerland
| | - Renaud Du Pasquier
- Division of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland.,Division of Radiology, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - Patrice H Lalive
- Division of Neurology, Department of Clinical Neurosciences, Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Emanuele Pravatà
- Neurology Department, Neurocenter of Southern Switzerland, Lugano, Switzerland.,Department of Neuroradiology, Neurocenter of Southern Switzerland, Lugano, Switzerland
| | - Johannes Weber
- Department of Radiology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Philippe C Cattin
- Center for Medical Image, Analysis, and Navigation, Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Claudio Gobbi
- Neurology Department, Neurocenter of Southern Switzerland, Lugano, Switzerland.,Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
| | - David Leppert
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINK) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.,Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
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37
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Arnold DL, Piani-Meier D, Bar-Or A, Benedict RH, Cree BA, Giovannoni G, Gold R, Vermersch P, Arnould S, Dahlke F, Hach T, Ritter S, Karlsson G, Kappos L, Fox RJ. Effect of siponimod on magnetic resonance imaging measures of neurodegeneration and myelination in secondary progressive multiple sclerosis: Gray matter atrophy and magnetization transfer ratio analyses from the EXPAND phase 3 trial. Mult Scler 2022; 28:1526-1540. [PMID: 35261318 PMCID: PMC9315182 DOI: 10.1177/13524585221076717] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) measurements of gray matter (GM) atrophy and magnetization transfer ratio (MTR; correlate of myelination) may provide better insights than conventional MRI regarding brain tissue integrity/myelination in multiple sclerosis (MS). OBJECTIVE To examine the effect of siponimod in the EXPAND trial on whole-brain and GM atrophy, newly formed normalized magnetization transfer ratio (nMTR) lesions, and nMTR-assessed integrity of normal-appearing brain tissue (NABT), cortical GM (cGM), and normal-appearing white matter (NAWM). METHODS Patients with secondary progressive multiple sclerosis (SPMS) received siponimod (2 mg/day; n =1037) or placebo (n = 523). Endpoints included percentage change from baseline to months 12/24 in whole-brain, cGM, and thalamic volumes; change in nMTR from baseline to months 12/24 in NABT, cGM, and NAWM; MTR recovery in newly formed lesions. RESULTS Compared with placebo, siponimod significantly reduced progression of whole-brain and GM atrophy over 12/24 months, and was associated with improvements in brain tissue integrity/myelination within newly formed nMTR lesions and across NABT, cGM, and NAWM over 24 months. Effects were consistent across age, disease duration, inflammatory activity subgroups, and disease severity. CONCLUSION Siponimod reduced brain tissue damage in patients with SPMS as evidenced by objective measures of brain tissue integrity/myelination. This is consistent with central nervous system (CNS) effects observed in preclinical models. ClinicalTrials.gov number: NCT01665144.
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Affiliation(s)
- Douglas L Arnold
- NeuroRx, Montreal, QC, Canada/Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | | | - Amit Bar-Or
- Center for Neuroinflammation and Experimental Therapeutics and Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Bruce Ac Cree
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Gavin Giovannoni
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Ralf Gold
- Department of Neurology, St Josef-Hospital/Ruhr-University Bochum, Bochum, Germany
| | - Patrick Vermersch
- Univ. Lille, Inserm U1172 LilNCog, CHU Lille, FHU Precise, Lille, France
| | - Sophie Arnould
- Novartis Pharma AG, Basel, Switzerland; *at the time of writing
| | - Frank Dahlke
- Novartis Pharma AG, Basel, Switzerland; *at the time of writing
| | - Thomas Hach
- Novartis Pharma AG, Basel, Switzerland; *at the time of writing
| | - Shannon Ritter
- Novartis Pharma AG, Basel, Switzerland; *at the time of writing
| | - Göril Karlsson
- Novartis Pharma AG, Basel, Switzerland; *at the time of writing
| | - Ludwig Kappos
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) and MS Center, Departments of Head, Spine and Neuromedicine, Clinical Research, Biomedicine and Biomedical Engineering, University Hospital, University of Basel, Basel, Switzerland
| | - Robert J Fox
- Mellen Center for Multiple Sclerosis Treatment and Research, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
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38
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Dal-Bianco A, Schranzer R, Grabner G, Lanzinger M, Kolbrink S, Pusswald G, Altmann P, Ponleitner M, Weber M, Kornek B, Zebenholzer K, Schmied C, Berger T, Lassmann H, Trattnig S, Hametner S, Leutmezer F, Rommer P. Iron Rims in Patients With Multiple Sclerosis as Neurodegenerative Marker? A 7-Tesla Magnetic Resonance Study. Front Neurol 2022; 12:632749. [PMID: 34992573 PMCID: PMC8724313 DOI: 10.3389/fneur.2021.632749] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 11/12/2021] [Indexed: 11/13/2022] Open
Abstract
Introduction: Multiple sclerosis (MS) is a demyelinating and neurodegenerative disease of the central nervous system, characterized by inflammatory-driven demyelination. Symptoms in MS manifest as both physical and neuropsychological deficits. With time, inflammation is accompanied by neurodegeneration, indicated by brain volume loss on an MRI. Here, we combined clinical, imaging, and serum biomarkers in patients with iron rim lesions (IRLs), which lead to severe tissue destruction and thus contribute to the accumulation of clinical disability. Objectives: Subcortical atrophy and ventricular enlargement using an automatic segmentation pipeline for 7 Tesla (T) MRI, serum neurofilament light chain (sNfL) levels, and neuropsychological performance in patients with MS with IRLs and non-IRLs were assessed. Methods: In total 29 patients with MS [15 women, 24 relapsing-remitting multiple sclerosis (RRMS), and five secondary-progressive multiple sclerosis (SPMS)] aged 38 (22–69) years with an Expanded Disability Status Score of 2 (0–8) and a disease duration of 11 (5–40) years underwent neurological and neuropsychological examinations. Volumes of lesions, subcortical structures, and lateral ventricles on 7-T MRI (SWI, FLAIR, and MP2RAGE, 3D Segmentation Software) and sNfL concentrations using the Simoa SR-X Analyzer in IRL and non-IRL patients were assessed. Results: (1) Iron rim lesions patients had a higher FLAIR lesion count (p = 0.047). Patients with higher MP2Rage lesion volume exhibited more IRLs (p <0.014) and showed poorer performance in the information processing speed tested within 1 year using the Symbol Digit Modalities Test (SDMT) (p <0.047). (2) Within 3 years, patients showed atrophy of the thalamus (p = 0.021) and putamen (p = 0.043) and enlargement of the lateral ventricles (p = 0.012). At baseline and after 3 years, thalamic volumes were lower in IRLs than in non-IRL patients (p = 0.045). (3) At baseline, IRL patients had higher sNfL concentrations (p = 0.028). Higher sNfL concentrations were associated with poorer SDMT (p = 0.004), regardless of IRL presence. (4) IRL and non-IRL patients showed no significant difference in the neuropsychological performance within 1 year. Conclusions: Compared with non-IRL patients, IRL patients had higher FLAIR lesion counts, smaller thalamic volumes, and higher sNfL concentrations. Our pilot study combines IRL and sNfL, two biomarkers considered indicative for neurodegenerative processes. Our preliminary data underscore the reported destructive nature of IRLs.
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Affiliation(s)
| | - R Schranzer
- Department of Neurology, Vienna, Austria.,Department of Medical Engineering, Carinthia University of Applied Sciences, Klagenfurt, Austria
| | - G Grabner
- Department of Neurology, Vienna, Austria.,Department of Medical Engineering, Carinthia University of Applied Sciences, Klagenfurt, Austria
| | | | - S Kolbrink
- Department of Neurology, Vienna, Austria
| | - G Pusswald
- Department of Neurology, Vienna, Austria
| | - P Altmann
- Department of Neurology, Vienna, Austria
| | | | - M Weber
- Department of Biomedical Imaging and Image-Guided Therapy, High Field Magnetic Resonance Centre, Vienna, Austria
| | - B Kornek
- Department of Neurology, Vienna, Austria
| | | | - C Schmied
- Department of Neurology, Vienna, Austria
| | - T Berger
- Department of Neurology, Vienna, Austria
| | - H Lassmann
- Department of Neuroimmunology, Center for Brain Research, Vienna, Austria
| | - S Trattnig
- Department of Biomedical Imaging and Image-Guided Therapy, High Field Magnetic Resonance Centre, Vienna, Austria
| | - S Hametner
- Department of Neurology, Vienna, Austria.,Institute of Neurology, Medical University of Vienna, Vienna, Austria
| | | | - P Rommer
- Department of Neurology, Vienna, Austria
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39
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Cortese R, Giorgio A, Severa G, De Stefano N. MRI Prognostic Factors in Multiple Sclerosis, Neuromyelitis Optica Spectrum Disorder, and Myelin Oligodendrocyte Antibody Disease. Front Neurol 2021; 12:679881. [PMID: 34867701 PMCID: PMC8636325 DOI: 10.3389/fneur.2021.679881] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 10/08/2021] [Indexed: 11/25/2022] Open
Abstract
Several MRI measures have been developed in the last couple of decades, providing a number of imaging biomarkers that can capture the complexity of the pathological processes occurring in multiple sclerosis (MS) brains. Such measures have provided more specific information on the heterogeneous pathologic substrate of MS-related tissue damage, being able to detect, and quantify the evolution of structural changes both within and outside focal lesions. In clinical practise, MRI is increasingly used in the MS field to help to assess patients during follow-up, guide treatment decisions and, importantly, predict the disease course. Moreover, the process of identifying new effective therapies for MS patients has been supported by the use of serial MRI examinations in order to sensitively detect the sub-clinical effects of disease-modifying treatments at an earlier stage than is possible using measures based on clinical disease activity. However, despite this has been largely demonstrated in the relapsing forms of MS, a poor understanding of the underlying pathologic mechanisms leading to either progression or tissue repair in MS as well as the lack of sensitive outcome measures for the progressive phases of the disease and repair therapies makes the development of effective treatments a big challenge. Finally, the role of MRI biomarkers in the monitoring of disease activity and the assessment of treatment response in other inflammatory demyelinating diseases of the central nervous system, such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte antibody disease (MOGAD) is still marginal, and advanced MRI studies have shown conflicting results. Against this background, this review focused on recently developed MRI measures, which were sensitive to pathological changes, and that could best contribute in the future to provide prognostic information and monitor patients with MS and other inflammatory demyelinating diseases, in particular, NMOSD and MOGAD.
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Affiliation(s)
- Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Antonio Giorgio
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Gianmarco Severa
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
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40
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Thompson AJ, Carroll W, Ciccarelli O, Comi G, Cross A, Donnelly A, Feinstein A, Fox RJ, Helme A, Hohlfeld R, Hyde R, Kanellis P, Landsman D, Lubetzki C, Marrie RA, Morahan J, Montalban X, Musch B, Rawlings S, Salvetti M, Sellebjerg F, Sincock C, Smith KE, Strum J, Zaratin P, Coetzee T. Charting a global research strategy for progressive MS-An international progressive MS Alliance proposal. Mult Scler 2021; 28:16-28. [PMID: 34850641 PMCID: PMC8688983 DOI: 10.1177/13524585211059766] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Progressive forms of multiple sclerosis (MS) affect more than 1 million individuals globally. Recent approvals of ocrelizumab for primary progressive MS and siponimod for active secondary progressive MS have opened the therapeutic door, though results from early trials of neuroprotective agents have been mixed. The recent introduction of the term 'active' secondary progressive MS into the therapeutic lexicon has introduced potential confusion to disease description and thereby clinical management. OBJECTIVE This paper reviews recent progress, highlights continued knowledge and proposes, on behalf of the International Progressive MS Alliance, a global research strategy for progressive MS. METHODS Literature searches of PubMed between 2015 and May, 2021 were conducted using the search terms "progressive multiple sclerosis", "primary progressive multiple sclerosis", "secondary progressive MS". Proposed strategies were developed through a series of in-person and virtual meetings of the International Progressive MS Alliance Scientific Steering Committee. RESULTS Sustaining and accelerating progress will require greater understanding of underlying mechanisms, identification of potential therapeutic targets, biomarker discovery and validation, and conduct of clinical trials with improved trial design. Encouraging developments in symptomatic and rehabilitative interventions are starting to address ongoing challenges experienced by people with progressive MS. CONCLUSION We need to manage these challenges and realise the opportunities in the context of a global research strategy, which will improve quality of life for people with progressive MS.
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Affiliation(s)
| | | | | | | | - Anne Cross
- Washington University in St. Louis, St. Louis, MO, USA
| | | | | | | | | | - Reinhard Hohlfeld
- Munich Cluster for Systems Neurology, Ludwig Maximilian University of Munich, Munich, Germany
| | | | | | | | | | | | | | - Xavier Montalban
- Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | | | - Marco Salvetti
- Department of Neurosciences, Mental Health and Sensory Organs, Centre for Experimental Neurological Therapies (CENTERS), Sapienza University of Rome, Rome, Italy/Istituto Neurologico Mediterraneo (INM) Neuromed, Pozzilli, Italy
| | - Finn Sellebjerg
- Copenhagen University Hospital-Rigshospitalet, Glostrup, Denmark
| | | | | | - Jon Strum
- International Progressive MS Alliance, Los Angeles, CA, USA
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41
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Madsen MAJ, Wiggermann V, Bramow S, Christensen JR, Sellebjerg F, Siebner HR. Imaging cortical multiple sclerosis lesions with ultra-high field MRI. Neuroimage Clin 2021; 32:102847. [PMID: 34653837 PMCID: PMC8517925 DOI: 10.1016/j.nicl.2021.102847] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 08/19/2021] [Accepted: 08/25/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Cortical lesions are abundant in multiple sclerosis (MS), yet difficult to visualize in vivo. Ultra-high field (UHF) MRI at 7 T and above provides technological advances suited to optimize the detection of cortical lesions in MS. PURPOSE To provide a narrative and quantitative systematic review of the literature on UHF MRI of cortical lesions in MS. METHODS A systematic search of all literature on UHF MRI of cortical lesions in MS published before September 2020. Quantitative outcome measures included cortical lesion numbers reported using 3 T and 7 T MRI and between 7 T MRI sequences, along with sensitivity of UHF MRI towards cortical lesions verified by histopathology. RESULTS 7 T MRI detected on average 52 ± 26% (mean ± 95% confidence interval) more cortical lesions than the best performing image contrast at 3 T, with the largest increase in type II-IV intracortical lesion detection. Across all studies, the mean cortical lesion number was 17 ± 6 per patient. In progressive MS cohorts, approximately four times more cortical lesions were reported than in CIS/early RRMS, and RRMS. Yet, there was no difference in lesion type ratio between these MS subtypes. Furthermore, superiority of one MRI sequence over another could not be established from available data. Post-mortem lesion detection with UHF MRI agreed only modestly with pathological examinations. Mean pro- and retrospective sensitivity was 33 ± 6% and 71 ± 10%, respectively, with the highest sensitivity towards type I and type IV lesions. CONCLUSION UHF MRI improves cortical lesion detection in MS considerably compared to 3 T MRI, particularly for type II-IV lesions. Despite modest sensitivity, 7 T MRI is still capable of visualizing all aspects of cortical lesion pathology and could potentially aid clinicians in diagnosing and monitoring MS, and progressive MS in particular. However, standardization of acquisition and segmentation protocols is needed.
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Affiliation(s)
- Mads A J Madsen
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark.
| | - Vanessa Wiggermann
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark
| | - Stephan Bramow
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark
| | - Jeppe Romme Christensen
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark
| | - Finn Sellebjerg
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 1-23, 2600 Glostrup, Denmark; Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3b, 2200 Copenhagen, Denmark
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager & Hvidovre, Kettegard Allé 30, 2650 Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital - Bispebjerg, Bispebjerg Bakke 23, 2400 Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3b, 2200 Copenhagen, Denmark
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42
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Rose DR, Amin M, Ontaneda D. Prediction in treatment outcomes in multiple sclerosis: challenges and recent advances. Expert Rev Clin Immunol 2021; 17:1187-1198. [PMID: 34570656 DOI: 10.1080/1744666x.2021.1986005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
INTRODUCTION Multiple Sclerosis (MS) is a chronic autoimmune and neurodegenerative disease of the central nervous system with a course dependent on early treatment response. Increasing evidence also suggests that despite eliminating disease activity (relapses and lesions), many patients continue to accrue disability, highlighting the need for a more comprehensive definition of treatment success. Optimizing disability outcome measures, as well as continuously improving our understanding of neuroinflammatory and neurodegenerative biomarkers is required. AREAS COVERED This review describes the challenges inherent in classifying and monitoring disease phenotype in MS. The review also provides an assessment of clinical, radiological, and blood biomarker tools for current and future practice. EXPERT OPINION Emerging MRI techniques and standardized patient outcome assessments will increase the accuracy of initial diagnosis and understanding of disease progression.
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Affiliation(s)
- Deja R Rose
- Cleveland Clinic, Mellen Center for Multiple Sclerosis, Cleveland Ohio, United States
| | - Moein Amin
- Cleveland Clinic, Mellen Center for Multiple Sclerosis, Cleveland Ohio, United States.,Department of Neurology, Cleveland Clinic, Cleveland Ohio, United States
| | - Daniel Ontaneda
- Cleveland Clinic, Mellen Center for Multiple Sclerosis, Cleveland Ohio, United States.,Department of Neurology, Cleveland Clinic, Cleveland Ohio, United States
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43
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Pitteri M, Magliozzi R, Nicholas R, Ziccardi S, Pisani AI, Pezzini F, Marastoni D, Calabrese M. Cerebrospinal fluid inflammatory profile of cognitive impairment in newly diagnosed multiple sclerosis patients. Mult Scler 2021; 28:768-777. [PMID: 34328817 DOI: 10.1177/13524585211032510] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND The cerebrospinal fluid (CSF) molecular milieu is a marker of diffuse intrathecal inflammation in the meninges that, in turn, targets the grey matter (GM) in multiple sclerosis (MS). Cognitive impairment (CI) is associated with brain damage in MS and is often present early in people with MS (pwMS). OBJECTIVE To investigate whether a specific CSF inflammatory profile is associated with different degrees of CI in newly diagnosed pwMS. METHODS Sixty-nine pwMS and 43 healthy controls (HCs) underwent neuropsychological testing. The presence and levels of 57 inflammatory mediators in the CSF were assessed. RESULTS Apparently cognitively normal (ACN) pwMS had impaired executive functioning compared to HCs but performed better than pwMS with mild and severe CI (mCI and sCI) in all tests. CSF mediators involving innate immunity and immune activation and recruitment, differentiate ACN from pwMS with mCI, while CSF mediators related to B- and T-cell immunity and chemotaxis differentiate both ACN and mCI from those with sCI. CXCL13 was the only molecule that differentiated sCI from mCI pwMS. CONCLUSION Specific CSF molecular patterns, reflecting the involvement of both innate and adaptive immune responses, are associated with the severity of CI in newly diagnosed pwMS.
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Affiliation(s)
- Marco Pitteri
- Neurology Section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Roberta Magliozzi
- Neurology Section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy/Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Richard Nicholas
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Stefano Ziccardi
- Neurology Section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Anna Isabella Pisani
- Neurology Section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Francesco Pezzini
- Neurology Section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Damiano Marastoni
- Neurology Section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Massimiliano Calabrese
- Neurology Section, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
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Liu J, Beck ES, Filippini S, van Gelderen P, de Zwart JA, Norato G, Sati P, Al-Louzi O, Kolb H, Donadieu M, Morrison M, Duyn JH, Reich DS. Navigator-Guided Motion and B0 Correction of T2*-Weighted Magnetic Resonance Imaging Improves Multiple Sclerosis Cortical Lesion Detection. Invest Radiol 2021; 56:409-416. [PMID: 34086012 PMCID: PMC8269363 DOI: 10.1097/rli.0000000000000754] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Cortical lesions are common in multiple sclerosis (MS). T2*-weighted (T2*w) imaging at 7 T is relatively sensitive for cortical lesions, but quality is often compromised by motion and main magnetic field (B0) fluctuations. PURPOSE The aim of this study was to determine whether motion and B0 correction with a navigator-guided gradient-recalled echo sequence can improve cortical lesion detection in T2*w magnetic resonance imaging. MATERIALS AND METHODS In this prospective study, a gradient-recalled echo sequence incorporating a navigator allowing for motion and B0 field correction was applied to collect T2*w images at 7 T from adults with MS between August 2019 and March 2020. T2*-weighted images were acquired in 1 to 3 partially overlapping scans per individual and were reconstructed using global average B0 correction ("uncorrected") or motion correction and spatially linear B0 correction ("corrected"). Image quality rating and manual segmentation of cortical lesions were performed on uncorrected and corrected images. Lesions seen on a single scan were retrospectively evaluated on the complementary scan. The association of cortical lesions with clinical disability was assessed. Mixed models were used to determine the effect of correction on lesion detection as well as on the relationship between disability and lesion count. RESULTS A total of 22 T2*w scans were performed on 11 adults with MS (mean [SD] age, 49 [11] years; 8 women). Quality improved for 20 of 22 scans (91%) after correction. A total of 69 cortical lesions were identified on uncorrected images (median per scan, 2; range, 0-11) versus 148 on corrected images (median per scan, 4.5; range, 0-25; rate ratio [RR], 2.1; P < 0.0001). For low-quality uncorrected scans with moderate to severe motion artifact (18/22, 82%), there was an improvement in cortical lesion detection with correction (RR, 2.5; P < 0.0001), whereas there was no significant change in cortical lesion detection for high-quality scans (RR, 1.3; P = 0.43). CONCLUSIONS Navigator-guided motion and B0 correction substantially improves the overall image quality of T2*w magnetic resonance imaging at 7 T and increases its sensitivity for cortical lesions.
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Affiliation(s)
- Jiaen Liu
- Advanced MRI Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Erin S Beck
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
| | - Stefano Filippini
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
- Department of Neurosciences, Drug, and Child Health, University of Florence, Florence, Italy
| | - Peter van Gelderen
- Advanced MRI Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Jacco A de Zwart
- Advanced MRI Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Gina Norato
- Clinical Trials Unit, NINDS, NIH, Bethesda, MD, USA
| | - Pascal Sati
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Omar Al-Louzi
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
| | - Hadar Kolb
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
| | - Maxime Donadieu
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
| | - Mark Morrison
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
| | - Jeff H Duyn
- Advanced MRI Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
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45
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Barzegar M, Najdaghi S, Afshari-Safavi A, Nehzat N, Mirmosayyeb O, Shaygannejad V. Early predictors of conversion to secondary progressive multiple sclerosis. Mult Scler Relat Disord 2021; 54:103115. [PMID: 34216997 DOI: 10.1016/j.msard.2021.103115] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 06/10/2021] [Accepted: 06/22/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND We conducted this study to estimated the time of conversion from relapsing-remitting MS (RRMS) to SPMS and its early predictor factors. METHODS In this retrospective study, demographic, clinical, and imaging data from MS patients at diagnosis were extracted. Cox proportional hazards model was used to assess the association between various baseline characteristics and conversion to SPMS. We also assessed the association brtween escalation and early intensive therapy approaches with transition to progressive phase. RESULTS Out of 1903 patients with RRMS at baseline, 293 (15.4%) patients progressed to SPMS during follow-up. The estimated number of patients converted to SPMS was 10% at 10-years, 50% at 20-years, and 93% at 30-years. On multivariate Cox regression analysis older age at onset (HR: 1.067, 95%CI: 1.048-1.085, p < 0.001), smoking (HR: 2.120, 95%CI: 1.203-3.736, p = 0.009), higher EDSS at onset (HR: 1.199, 95%CI: 1.109-1.295, p < 0.001), motor dysfunction (HR: 2.470, 95%CI: 1.605-3.800, p < 0.001), cerebellar dysfunction (HR: 3.096, 95%CI: 1.840-5.211, p < 0.001), and presence of lesions in spinal cord (HR: 0.573, 95%CI: 0.297-0.989, p = 0.042) increased the risk of conversion from RRMS to SPMS. No significant difference between escalation and EIT groups in the risk of transition to progressive phase (weighted HR = 1.438; 95% CI: 0.963, 2.147; p = 0.076) was found. CONCLUSION Our data support previous observations that smoking is a modifiable risk factor for secondary progressive MS and confirms that spinal cord involvement, age, and more severe disease at onset are prognostic factors for converting to secondary progressive MS.
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Affiliation(s)
- Mahdi Barzegar
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Department of neurology, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Soroush Najdaghi
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Department of neurology, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Alireza Afshari-Safavi
- Department of neurology, Isfahan University of Medical Sciences, Isfahan, Iran; Department of Biostatistics and Epidemiology, Faculty of Health, North Khorasan University of Medical Sciences, Bojnurd, Iran
| | - Nasim Nehzat
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Universal Council of Epidemiology (UCE), Universal Scientific Education and Research Network (USERN), Tehran University of Medical Sciences, Tehran, Iran
| | - Omid Mirmosayyeb
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Department of neurology, Isfahan University of Medical Sciences, Isfahan, Iran; Universal Council of Epidemiology (UCE), Universal Scientific Education and Research Network (USERN), Tehran University of Medical Sciences, Tehran, Iran
| | - Vahid Shaygannejad
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Department of neurology, Isfahan University of Medical Sciences, Isfahan, Iran.
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46
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Wang Y, Fellah S, Fields ME, Guilliams KP, Binkley MM, Eldeniz C, Shimony JS, Reis M, Vo KD, Chen Y, Lee JM, An H, Ford AL. Cerebral Oxygen Metabolic Stress, Microstructural Injury, and Infarction in Adults With Sickle Cell Disease. Neurology 2021; 97:e902-e912. [PMID: 34172536 PMCID: PMC8408504 DOI: 10.1212/wnl.0000000000012404] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 05/26/2021] [Indexed: 12/18/2022] Open
Abstract
OBJECTIVE To determine the patient- and tissue-based relationships between cerebral hemodynamic and oxygen metabolic stress, microstructural injury, and infarct location in adults with sickle cell disease (SCD). METHODS Control and SCD participants underwent brain MRI to quantify cerebral blood flow (CBF), oxygen extraction fraction (OEF), mean diffusivity (MD), and fractional anisotropy (FA) within normal-appearing white matter (NAWM), and infarcts on FLAIR. Multivariable linear regression examined the patient- and voxel-based associations between hemodynamic and metabolic stress (defined as elevated CBF and OEF, respectively), white matter microstructure, and infarct location. RESULTS Of 83 control and SCD participants, adults with SCD demonstrated increased CBF (50.9 vs 38.8 mL/min/100g, p<0.001), increased OEF (0.35 vs 0.25, p<0.001), increased MD (0.76 vs 0.72 x 10-3mm2 s-1, p=0.005), and decreased FA (0.40 vs 0.42, p=0.021) within NAWM compared to controls. In multivariable analysis, increased OEF (β=0.19, p=0.035), but not CBF (β=0.00, p=0.340), independently predicted increased MD in the SCD cohort, while neither were predictors in controls. On voxel-wise regression, the SCD cohort demonstrated widespread OEF elevation, encompassing deep white matter regions of elevated MD and reduced FA, which spatially extended beyond high density infarct locations from the SCD cohort. CONCLUSION Elevated OEF, a putative index of cerebral oxygen metabolic stress, may provide a metric of ischemic vulnerability which could enable individualization of therapeutic strategies in SCD. The patient- and tissue-based relationships between elevated OEF, elevated MD, and cerebral infarcts suggest that oxygen metabolic stress may underlie microstructural injury prior to the development of cerebral infarcts in SCD.
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Affiliation(s)
- Yan Wang
- Department of Neurology, Washington University School of Medicine, St. Louis, MO
| | - Slim Fellah
- Department of Neurology, Washington University School of Medicine, St. Louis, MO
| | - Melanie E Fields
- Division of Pediatric Hematology/Oncology, Washington University School of Medicine, St. Louis, MO
| | - Kristin P Guilliams
- Division of Pediatric Neurology, Washington University School of Medicine, St. Louis, MO
| | - Michael M Binkley
- Department of Neurology, Washington University School of Medicine, St. Louis, MO
| | - Cihat Eldeniz
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Martin Reis
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Katie D Vo
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Yasheng Chen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Jin-Moo Lee
- Department of Neurology, Washington University School of Medicine, St. Louis, MO.,Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Hongyu An
- Department of Neurology, Washington University School of Medicine, St. Louis, MO.,Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Andria L Ford
- Department of Neurology, Washington University School of Medicine, St. Louis, MO; .,Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO
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47
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Pisani AI, Scalfari A, Crescenzo F, Romualdi C, Calabrese M. A novel prognostic score to assess the risk of progression in relapsing-remitting multiple sclerosis patients. Eur J Neurol 2021; 28:2503-2512. [PMID: 33835665 PMCID: PMC8360167 DOI: 10.1111/ene.14859] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 04/03/2021] [Indexed: 01/10/2023]
Abstract
BACKGROUND At the patient level, the prognostic value of several features that are known to be associated with an increased risk of converting from relapsing-remitting (RR) to secondary phase (SP) multiple sclerosis (MS) remains limited. METHODS Among 262 RRMS patients followed up for 10 years, we assessed the probability of developing the SP course based on clinical and conventional and non-conventional magnetic resonance imaging (MRI) parameters at diagnosis and after 2 years. We used a machine learning method, the random survival forests, to identify, according to their minimal depth (MD), the most predictive factors associated with the risk of SP conversion, which were then combined to compute the secondary progressive risk score (SP-RiSc). RESULTS During the observation period, 69 (26%) patients converted to SPMS. The number of cortical lesions (MD = 2.47) and age (MD = 3.30) at diagnosis, the global cortical thinning (MD = 1.65), the cerebellar cortical volume loss (MD = 2.15) and the cortical lesion load increase (MD = 3.15) over the first 2 years exerted the greatest predictive effect. Three patients' risk groups were identified; in the high-risk group, 85% (46/55) of patients entered the SP phase in 7 median years. The SP-RiSc optimal cut-off estimated was 17.7 showing specificity and sensitivity of 87% and 92%, respectively, and overall accuracy of 88%. CONCLUSIONS The SP-RiSc yielded a high performance in identifying MS patients with high probability to develop SPMS, which can help improve management strategies. These findings are the premise of further larger prospective studies to assess its use in clinical settings.
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Affiliation(s)
- Anna Isabella Pisani
- Department of Neurological and Movement Sciences, University of Verona, Verona, Italy
| | | | - Francesco Crescenzo
- Department of Neurological and Movement Sciences, University of Verona, Verona, Italy
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48
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Abstract
PURPOSE OF REVIEW Ultra-high field 7 T MRI has multiple applications for the in vivo characterization of the heterogeneous aspects underlying multiple sclerosis including the identification of cortical lesions, characterization of the different types of white matter plaques, evaluation of structures difficult to assess with conventional MRI (thalamus, cerebellum, spinal cord, meninges). RECENT FINDINGS The sensitivity of cortical lesion detection at 7 T is twice than at lower field MRI, especially for subpial lesions, the most common cortical lesion type in multiple sclerosis. Cortical lesion load accrual is independent of that in the white matter and predicts disability progression.Seven Tesla MRI provides details on tissue microstructure that can be used to improve white matter lesion characterization. These include the presence of a central vein, whose identification can be used to improve multiple sclerosis diagnosis, or the appearance of an iron-rich paramagnetic rim on susceptibility-weighted images, which corresponds to iron-rich microglia at the periphery of slow expanding lesions. Improvements in cerebellar and spinal cord tissue delineation and lesion characterization have also been demonstrated. SUMMARY Imaging at 7 T allows assessing more comprehensively the complementary pathophysiological aspects of multiple sclerosis, opening up novel perspectives for clinical and therapeutics evaluation.
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49
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Penner IK, Gass A, Schreiber H, Wattjes MP. [Neuropsychological and MRI diagnostics in secondary progressive multiple sclerosis]. DER NERVENARZT 2021; 92:1293-1301. [PMID: 33891150 PMCID: PMC8648628 DOI: 10.1007/s00115-021-01118-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 03/02/2021] [Indexed: 11/24/2022]
Abstract
Hintergrund Die Multiple Sklerose ist im longitudinalen Verlauf oft ein Krankheitskontinuum mit initial schubförmig-remittierender Phase (RRMS) und späterer sekundärer Progredienz (SPMS). Die meisten bisher zugelassenen Therapien sind bei SPMS nicht ausreichend wirksam. Die frühe Erkennung der SPMS-Konversion ist daher entscheidend für die Therapiewahl. Wichtige Entscheidungshilfen können dabei die Testung kognitiver Teilleistungen und die Magnetresonanztomographie (MRT) sein. Ziel der Arbeit Darstellung der Bedeutung kognitiver Testungen und von MRT-Untersuchungen für Prädiktion und Erfassung der SPMS-Konversion. Ausarbeitung von Strategien der Verlaufsbeobachtung und Therapiesteuerung in der Praxis, insbesondere in der ambulanten Versorgung. Material und Methoden Übersichtsarbeit auf Basis einer unsystematischen Literaturrecherche. Ergebnisse Standardisierte kognitive Testung kann für die frühe SPMS-Diagnose hilfreich sein und die Verlaufsbewertung erleichtern. Eine jährliche Anwendung sensitiver Screeningtests wie Symbol Digit Modalities Test (SDMT) und Brief Visual Memory Test-Revised (BVMT‑R) oder der Brief International Cognitive Assessment for MS (BICAMS)-Testbatterie ist empfehlenswert. Persistierende inflammatorische Aktivität im MRT in den ersten drei Jahren der Erkrankung sowie das Vorhandensein kortikaler Läsionen sind prädiktiv für eine SPMS-Konversion. Ein standardisiertes MRT-Monitoring auf Merkmale einer progressiven MS kann den klinisch und neurokognitiv begründeten SPMS-Verdacht stützen. Diskussion Die interdisziplinäre Versorgung von MS-Patienten durch klinisch versierte Neurologen, unterstützt durch neuropsychologische Testung und MRT, hat einen hohen Stellenwert für die SPMS-Prädiktion und Diagnose. Letztere erlaubt eine frühe Umstellung auf geeignete Therapien, da bei SPMS andere Interventionen als für die RRMS notwendig sind. Nach erfolgter medikamentöser Umstellung erlaubt die klinische, neuropsychologische und bildgebende Vigilanz ein stringentes Monitoring auf neuroinflammatorische und -degenerative Aktivität sowie Therapiekomplikationen.
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Affiliation(s)
- I-K Penner
- Klinik für Neurologie, Medizinische Fakultät, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Deutschland. .,COGITO Zentrum für angewandte Neurokognition und neuropsychologische Forschung, Merowingerplatz 1, 40225, Düsseldorf, Deutschland.
| | - A Gass
- Neurologische Klinik, Universitätsmedizin Mannheim, Mannheim, Deutschland
| | - H Schreiber
- Nervenärztliche Gemeinschaftspraxis, Neuropoint Akademie und NTD, Ulm, Deutschland
| | - M P Wattjes
- Institut für diagnostische und interventionelle Neuroradiologie, Medizinische Hochschule Hannover, Hannover, Deutschland
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50
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Haider L, Prados F, Chung K, Goodkin O, Kanber B, Sudre C, Yiannakas M, Samson RS, Mangesius S, Thompson AJ, Gandini Wheeler-Kingshott CAM, Ciccarelli O, Chard DT, Barkhof F. Cortical involvement determines impairment 30 years after a clinically isolated syndrome. Brain 2021; 144:1384-1395. [PMID: 33880511 PMCID: PMC8219364 DOI: 10.1093/brain/awab033] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 11/24/2020] [Accepted: 12/03/2020] [Indexed: 01/01/2023] Open
Abstract
Many studies report an overlap of MRI and clinical findings between patients with relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS), which in part is reflective of inclusion of subjects with variable disease duration and short periods of follow-up. To overcome these limitations, we examined the differences between RRMS and SPMS and the relationship between MRI measures and clinical outcomes 30 years after first presentation with clinically isolated syndrome suggestive of multiple sclerosis. Sixty-three patients were studied 30 years after their initial presentation with a clinically isolated syndrome; only 14% received a disease modifying treatment at any time point. Twenty-seven patients developed RRMS, 15 SPMS and 21 experienced no further neurological events; these groups were comparable in terms of age and disease duration. Clinical assessment included the Expanded Disability Status Scale, 9-Hole Peg Test and Timed 25-Foot Walk and the Brief International Cognitive Assessment For Multiple Sclerosis. All subjects underwent a comprehensive MRI protocol at 3 T measuring brain white and grey matter (lesions, volumes and magnetization transfer ratio) and cervical cord involvement. Linear regression models were used to estimate age- and gender-adjusted group differences between clinical phenotypes after 30 years, and stepwise selection to determine associations between a large sets of MRI predictor variables and physical and cognitive outcome measures. At the 30-year follow-up, the greatest differences in MRI measures between SPMS and RRMS were the number of cortical lesions, which were higher in SPMS (the presence of cortical lesions had 100% sensitivity and 88% specificity), and grey matter volume, which was lower in SPMS. Across all subjects, cortical lesions, grey matter volume and cervical cord volume explained 60% of the variance of the Expanded Disability Status Scale; cortical lesions alone explained 43%. Grey matter volume, cortical lesions and gender explained 43% of the variance of Timed 25-Foot Walk. Reduced cortical magnetization transfer ratios emerged as the only significant explanatory variable for the symbol digit modality test and explained 52% of its variance. Cortical involvement, both in terms of lesions and atrophy, appears to be the main correlate of progressive disease and disability in a cohort of individuals with very long follow-up and homogeneous disease duration, indicating that this should be the target of therapeutic interventions.
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Affiliation(s)
- Lukas Haider
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,Department of Biomedical Imaging and Image Guided Therapy, Medical University Vienna, Austria
| | - Ferran Prados
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,Universitat Oberta de Catalunya, Barcelona, Spain
| | - Karen Chung
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Olivia Goodkin
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Baris Kanber
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK
| | - Carole Sudre
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Marios Yiannakas
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Rebecca S Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Stephanie Mangesius
- Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria.,Neuroimaging Core Facility, Medical University of Innsbruck, Innsbruck, Austria
| | - Alan J Thompson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy.,Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK
| | - Declan T Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK
| | - Frederik Barkhof
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Queen Square Institute of Neurology, University College London, London, UK.,Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK.,Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
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