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Epstein SE, Longbrake EE. Shifting our attention earlier in the multiple sclerosis disease course. Curr Opin Neurol 2024; 37:212-219. [PMID: 38546031 DOI: 10.1097/wco.0000000000001268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/30/2024]
Abstract
PURPOSE OF REVIEW Revisions of multiple sclerosis (MS) diagnostic criteria enable clinicians to diagnose patients earlier in the biologic disease course. Prompt initiation of therapy correlates with improved clinical outcomes. This has led to increased attention on the earliest stages of MS, including the MS prodrome and radiologically isolated syndrome (RIS). Here, we review current understanding and approach to patients with preclinical MS. RECENT FINDINGS MS disease biology often begins well before the onset of typical MS symptoms, and we are increasingly able to recognize preclinical and prodromal stages of MS. RIS represents the best characterized aspect of preclinical MS, and its diagnostic criteria were recently revised to better capture patients at highest risk of conversion to clinical MS. The first two randomized control trials evaluating disease modifying therapy use in RIS also found that treatment could delay or prevent onset of clinical disease. SUMMARY Despite progress in our understanding of the earliest stages of the MS disease course, additional research is needed to systematically identify patients with preclinical MS as well as capture those at risk for developing clinical disease. Recent data suggests that preventive immunomodulatory therapies may be beneficial for high-risk patients with RIS; though management remains controversial.
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Hinsinger G, Du Trieu De Terdonck L, Urbach S, Salvetat N, Rival M, Galoppin M, Ripoll C, Cezar R, Laurent-Chabalier S, Demattei C, Agherbi H, Castelnovo G, Lehmann S, Rigau V, Marin P, Thouvenot E. CD138 as a Specific CSF Biomarker of Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2024; 11:e200230. [PMID: 38669615 PMCID: PMC11057439 DOI: 10.1212/nxi.0000000000200230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/30/2024] [Indexed: 04/28/2024]
Abstract
BACKGROUND AND OBJECTIVES The aim of this study was to identify novel biomarkers for multiple sclerosis (MS) diagnosis and prognosis, addressing the critical need for specific and prognostically valuable markers in the field. METHODS We conducted an extensive proteomic investigation, combining analysis of (1) CSF proteome from symptomatic controls, fast and slow converters after clinically isolated syndromes, and patients with relapsing-remitting MS (n = 10 per group) using label-free quantitative proteomics and (2) oligodendrocyte secretome changes under proinflammatory or proapoptotic conditions using stable isotope labeling by amino acids in cell culture. Proteins exhibiting differential abundance in both proteomic analyses were combined with other putative MS biomarkers, yielding a comprehensive list of 87 proteins that underwent quantification through parallel reaction monitoring (PRM) in a novel cohort, comprising symptomatic controls, inflammatory neurologic disease controls, and patients with MS at various disease stages (n = 10 per group). The 11 proteins that passed this qualification step were subjected to a new PRM assay within an expanded cohort comprising 158 patients with either MS at different disease stages or other inflammatory or noninflammatory neurologic disease controls. RESULTS This study unveiled a promising biomarker signature for MS, including previously established candidates, such as chitinase 3-like protein 1, chitinase 3-like protein 2, chitotriosidase, immunoglobulin kappa chain region C, neutrophil gelatinase-associated lipocalin, and CD27. In addition, we identified novel markers, namely cat eye syndrome critical region protein 1 (adenosine deaminase 2, a therapeutic target in multiple sclerosis) and syndecan-1, a proteoglycan, also known as plasma cell surface marker CD138 and acting as chitinase 3-like protein 1 receptor implicated in inflammation and cancer signaling. CD138 exhibited good diagnostic accuracy in distinguishing MS from inflammatory neurologic disorders (area under the curve [AUC] = 0.85, CI 0.75-0.95). CD138 immunostaining was also observed in the brains of patients with MS and cultured oligodendrocyte precursor cells but was absent in astrocytes. DISCUSSION These findings identify CD138 as a specific CSF biomarker for MS and suggest the selective activation of the chitinase 3-like protein 1/CD138 pathway within the oligodendrocyte lineage in MS. They offer promising prospects for improving MS diagnosis and prognosis by providing much-needed specificity and clinical utility. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that CD138 distinguishes multiple sclerosis from other inflammatory neurologic disorders with an AUC of 0.85 (95% CI 0.75-0.95).
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Affiliation(s)
- Geoffrey Hinsinger
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Lucile Du Trieu De Terdonck
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Serge Urbach
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Nicolas Salvetat
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Manon Rival
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Manon Galoppin
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Chantal Ripoll
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Renaud Cezar
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Sabine Laurent-Chabalier
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Christophe Demattei
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Hanane Agherbi
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Giovanni Castelnovo
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Sylvain Lehmann
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Valérie Rigau
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Philippe Marin
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
| | - Eric Thouvenot
- From the IGF (G.H., L.D.T.D.T., S.U., M.R., M.G., C.R., P.M., E.T.), Université de Montpellier, CNRS, INSERM, Montpellier; Sys2Diag (N.S.), UMR 9005 CNRS / ALCEDIAG, Montpellier; Department of Neurology (M.R., H.A., G.C., E.T.), Nîmes University Hospital; IRMB (R.C.), Université de Montpellier, INSERM; Department of Immunology (R.C.), Nîmes University Hospital; Department of Biostatistics (S.L.-C., C.D.), Clinical Epidemiology, Public Health, and Innovation in Methodology, Nîmes University Hospital, Université de Montpellier; Biochemistry Department (S.L.), Hôpital Saint-Eloi; and Department of Pathology (V.R.), Montpellier University Hospital, France
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Yılmaz D, Teber S, Gültutan P, Yıldırım M, Bektaş Ö, Alikılıç D, Güngör M, Kara B, Öncel İ, Dilek TD, Saltık S, Kanmaz S, Yılmaz S, Tekgül H, Çavuşoğlu D, Karaoğlu P, Yılmaz Ü, Orak SA, Güngör O, Anlar B. A multicenter study of radiologically isolated syndrome in children and adolescents: Can we predict the course? Mult Scler Relat Disord 2023; 79:104948. [PMID: 37659352 DOI: 10.1016/j.msard.2023.104948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 06/29/2023] [Accepted: 08/20/2023] [Indexed: 09/04/2023]
Abstract
OBJECTIVES To evaluate clinical characteristics, imaging features and etiological profile of Radiologically Isolated Syndrome (RIS) along with clinical and radiological follow-up. METHODS Demographic, clinical and radiological data of patients younger than 18 years fulfilling the criteria for RIS were retrospectively analyzed. RIS was defined by the detection of lesions meeting the revised 2010 McDonald Criteria for dissemination in space on magnetic resonance imaging (MRI) in the absence of any symptoms of demyelinating disease or an alternative cause for the MRI findings. RESULTS There were total 69 patients (38 girls, 31 boys). The median age at index MRI was 15.7 years, and median follow-up time was 28 months. The most common reason for neuroimaging was headache (60.9%). A first clinical event occurred with median 11 months in 14/69 (20%) of cases. Those with oligoclonal bands (OCB) in cerebrospinal fluid (CSF) and follow-up longer than 3 years were more likely to experience a clinical event (p<0.05): 25% of those with OCB manifested clinical symptoms within the first year and 33.3% within the first two years compared to 6.3% and 9.4%, respectively in those without OCB. Radiological evolution was not associated with any variables: age, sex, reason for neuroimaging, serum 25-hydroxyvitamin D level, elevated IgG index, OCB positivity, total number and localization of lesions, presence of gadolinium enhancement, achievement of 2005 criteria for DIS and duration of follow-up. CONCLUSION Children and adolescents with RIS and CSF OCB should be followed-up for at least 3 years in order to detect any clinical symptoms suggestive of a demyelinating event. Because disease-modifying treatments are not approved in RIS and no consensus report justifies their use especially in pediatric RIS, close follow-up of OCB-positive patients is needed for early recognition of any clinical event and timely initiation of specific treatment.
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Affiliation(s)
- Deniz Yılmaz
- Department of Pediatrics, Division of Pediatric Neurology, Ankara City Hospital, Children's' Hospital, Ankara, Turkey.
| | - Serap Teber
- Department of Pediatrics, Division of Pediatric Neurology, Ankara University Faculty of Medicine, Ankara, Turkey
| | - Pembe Gültutan
- Department of Pediatrics, Division of Pediatric Neurology, Ankara City Hospital, Children's' Hospital, Ankara, Turkey
| | - Miraç Yıldırım
- Department of Pediatrics, Division of Pediatric Neurology, Ankara University Faculty of Medicine, Ankara, Turkey
| | - Ömer Bektaş
- Department of Pediatrics, Division of Pediatric Neurology, Ankara University Faculty of Medicine, Ankara, Turkey
| | - Defne Alikılıç
- Department of Pediatrics, Division of Pediatric Neurology, Kocaeli University Faculty of Medicine, Ankara, Turkey
| | - Mesut Güngör
- Department of Pediatrics, Division of Pediatric Neurology, Kocaeli University Faculty of Medicine, Ankara, Turkey
| | - Bülent Kara
- Department of Pediatrics, Division of Pediatric Neurology, Kocaeli University Faculty of Medicine, Ankara, Turkey
| | - İbrahim Öncel
- Department of Pediatrics, Division of Pediatric Neurology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Tuğçe Damla Dilek
- Department of Pediatrics, Division of Pediatric Neurology, İstanbul University Cerrahpaşa Faculty of Medicine, İstanbul, Turkey
| | - Sema Saltık
- Department of Pediatrics, Division of Pediatric Neurology, İstanbul University Cerrahpaşa Faculty of Medicine, İstanbul, Turkey
| | - Seda Kanmaz
- Department of Pediatrics, Division of Pediatric Neurology, Ege University Faculty of Medicine, İzmir, Turkey
| | - Sanem Yılmaz
- Department of Pediatrics, Division of Pediatric Neurology, Ege University Faculty of Medicine, İzmir, Turkey
| | - Hasan Tekgül
- Department of Pediatrics, Division of Pediatric Neurology, Ege University Faculty of Medicine, İzmir, Turkey
| | - Dilek Çavuşoğlu
- Department of Pediatrics, Division of Pediatric Neurology, Afyonkarahisar Health Science University Faculty of Medicine, Afyon, Turkey
| | - Pakize Karaoğlu
- Izmir Faculty of Medicine, Dr. Behçet Uz Children's Education and Research Hospital, Department of Pediatrics, Division of Pediatric Neurology, University of Health Sciences, Izmir, Turkey
| | - Ünsal Yılmaz
- Izmir Faculty of Medicine, Dr. Behçet Uz Children's Education and Research Hospital, Department of Pediatrics, Division of Pediatric Neurology, University of Health Sciences, Izmir, Turkey
| | - Sibğatullah Ali Orak
- Department of Pediatrics, Division of Pediatric Neurology, Celal Bayar University Faculty of Medicine, Manisa, Turkey
| | - Olcay Güngör
- Department of Pediatrics, Division of Pediatric Neurology, Pamukkale University Faculty of Medicine, Denizli, Turkey
| | - Banu Anlar
- Department of Pediatrics, Division of Pediatric Neurology, Hacettepe University Faculty of Medicine, Ankara, Turkey
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Levraut M, Gavoille A, Landes-Chateau C, Cohen M, Bresch S, Seitz-Polski B, Mondot L, Lebrun-Frenay C. Kappa Free Light Chain Index Predicts Disease Course in Clinically and Radiologically Isolated Syndromes. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2023; 10:e200156. [PMID: 37640543 PMCID: PMC10462056 DOI: 10.1212/nxi.0000000000200156] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 07/19/2023] [Indexed: 08/31/2023]
Abstract
BACKGROUND AND OBJECTIVES To evaluate whether the kappa free light chain index (K-index) can predict the occurrence of new T2-weighted MRI lesions (T2L) and clinical events in clinically isolated syndrome (CIS) and radiologically isolated syndrome (RIS). METHODS All consecutive patients presenting for the diagnostic workup, including CSF analysis, of clinical and/or MRI suspicion of multiple sclerosis (MS) since May 1, 2018, were evaluated. All patients diagnosed with CIS and RIS with at least 1-year follow-up were included. Clinical events and new T2L were collected during follow-up. The K-index performances in predicting new T2L and a clinical event were evaluated using time-dependent ROC analyses. The time to clinical event or new T2L was estimated using survival analysis according to the binarized K-index using an independent cutoff of 8.9, and the ability of each variable to predict outcomes was compared using the Harrell c-index. RESULTS One hundred and eighty two patients (146 CIS and 36 RIS, median age 39 [30; 48] y-o, 70% females) were included with a median follow-up of 21 [13, 33] months. One hundred five (58%) patients (85 CIS and 20 RIS) experienced new T2L, and 28 (15%; 21 CIS and 7 RIS) experienced a clinical event. The K-index could predict new T2L over time in CIS (area under the curve [AUC] ranging from 0.86 to 0.96) and in RIS (AUC ranging from 0.84 to 0.54) but also a clinical event in CIS (AUC ranging from 0.75 to 0.87). Compared with oligoclonal bands (OCBs), the K-index had a better sensitivity and a slight lower specificity in predicting new T2L and clinical events in both populations. In the predictive model, the K-index was the variable that best predict new T2L in both CIS and RIS but also clinical events in CIS (c-index ranging from 0.70 to 0.77), better than the other variables, including OCB. DISCUSSION This study provides evidence that the K-index predicts new T2L in CIS and RIS but also clinical attack in patients with CIS. We suggest adding the K-index in the further MS diagnosis criteria revisions as a dissemination-in-time biomarker.
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Affiliation(s)
- Michael Levraut
- From the URRIS (M.L., C.L.-C., M.C., L.M., C.L.-F.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Service de Médecine Interne (M.L.), Hôpital l'Archet 1, Centre Hospitalier Universitaire de Nice; Service de Biostatistique-Bioinformatique (A.G.), Hospices Civils de Lyon; Service de Neurologie (A.G.), Sclérose en Plaques, Pathologies de La Myéline et Neuro-inflammation, Hôpital Neurologique Pierre-Wertheimer, Hospices Civils de Lyon, Bron; Service de Neurologie (M.C., S.B., C.L.-F.), Centre de Ressource et Compétence - Sclérose En Plaques, Hôpital Pasteur 2; ImmunoPredict (B.S.-P.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Laboratoire d'Immunologie (B.S.-P.), Hôpital l'Archet 1; and Service de Radiologie (L.M.), Hôpital Pasteur 2, Centre Hospitalier Universitaire de Nice, France.
| | - Antoine Gavoille
- From the URRIS (M.L., C.L.-C., M.C., L.M., C.L.-F.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Service de Médecine Interne (M.L.), Hôpital l'Archet 1, Centre Hospitalier Universitaire de Nice; Service de Biostatistique-Bioinformatique (A.G.), Hospices Civils de Lyon; Service de Neurologie (A.G.), Sclérose en Plaques, Pathologies de La Myéline et Neuro-inflammation, Hôpital Neurologique Pierre-Wertheimer, Hospices Civils de Lyon, Bron; Service de Neurologie (M.C., S.B., C.L.-F.), Centre de Ressource et Compétence - Sclérose En Plaques, Hôpital Pasteur 2; ImmunoPredict (B.S.-P.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Laboratoire d'Immunologie (B.S.-P.), Hôpital l'Archet 1; and Service de Radiologie (L.M.), Hôpital Pasteur 2, Centre Hospitalier Universitaire de Nice, France
| | - Cassandre Landes-Chateau
- From the URRIS (M.L., C.L.-C., M.C., L.M., C.L.-F.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Service de Médecine Interne (M.L.), Hôpital l'Archet 1, Centre Hospitalier Universitaire de Nice; Service de Biostatistique-Bioinformatique (A.G.), Hospices Civils de Lyon; Service de Neurologie (A.G.), Sclérose en Plaques, Pathologies de La Myéline et Neuro-inflammation, Hôpital Neurologique Pierre-Wertheimer, Hospices Civils de Lyon, Bron; Service de Neurologie (M.C., S.B., C.L.-F.), Centre de Ressource et Compétence - Sclérose En Plaques, Hôpital Pasteur 2; ImmunoPredict (B.S.-P.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Laboratoire d'Immunologie (B.S.-P.), Hôpital l'Archet 1; and Service de Radiologie (L.M.), Hôpital Pasteur 2, Centre Hospitalier Universitaire de Nice, France
| | - Mikael Cohen
- From the URRIS (M.L., C.L.-C., M.C., L.M., C.L.-F.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Service de Médecine Interne (M.L.), Hôpital l'Archet 1, Centre Hospitalier Universitaire de Nice; Service de Biostatistique-Bioinformatique (A.G.), Hospices Civils de Lyon; Service de Neurologie (A.G.), Sclérose en Plaques, Pathologies de La Myéline et Neuro-inflammation, Hôpital Neurologique Pierre-Wertheimer, Hospices Civils de Lyon, Bron; Service de Neurologie (M.C., S.B., C.L.-F.), Centre de Ressource et Compétence - Sclérose En Plaques, Hôpital Pasteur 2; ImmunoPredict (B.S.-P.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Laboratoire d'Immunologie (B.S.-P.), Hôpital l'Archet 1; and Service de Radiologie (L.M.), Hôpital Pasteur 2, Centre Hospitalier Universitaire de Nice, France
| | - Saskia Bresch
- From the URRIS (M.L., C.L.-C., M.C., L.M., C.L.-F.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Service de Médecine Interne (M.L.), Hôpital l'Archet 1, Centre Hospitalier Universitaire de Nice; Service de Biostatistique-Bioinformatique (A.G.), Hospices Civils de Lyon; Service de Neurologie (A.G.), Sclérose en Plaques, Pathologies de La Myéline et Neuro-inflammation, Hôpital Neurologique Pierre-Wertheimer, Hospices Civils de Lyon, Bron; Service de Neurologie (M.C., S.B., C.L.-F.), Centre de Ressource et Compétence - Sclérose En Plaques, Hôpital Pasteur 2; ImmunoPredict (B.S.-P.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Laboratoire d'Immunologie (B.S.-P.), Hôpital l'Archet 1; and Service de Radiologie (L.M.), Hôpital Pasteur 2, Centre Hospitalier Universitaire de Nice, France
| | - Barbara Seitz-Polski
- From the URRIS (M.L., C.L.-C., M.C., L.M., C.L.-F.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Service de Médecine Interne (M.L.), Hôpital l'Archet 1, Centre Hospitalier Universitaire de Nice; Service de Biostatistique-Bioinformatique (A.G.), Hospices Civils de Lyon; Service de Neurologie (A.G.), Sclérose en Plaques, Pathologies de La Myéline et Neuro-inflammation, Hôpital Neurologique Pierre-Wertheimer, Hospices Civils de Lyon, Bron; Service de Neurologie (M.C., S.B., C.L.-F.), Centre de Ressource et Compétence - Sclérose En Plaques, Hôpital Pasteur 2; ImmunoPredict (B.S.-P.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Laboratoire d'Immunologie (B.S.-P.), Hôpital l'Archet 1; and Service de Radiologie (L.M.), Hôpital Pasteur 2, Centre Hospitalier Universitaire de Nice, France
| | - Lydiane Mondot
- From the URRIS (M.L., C.L.-C., M.C., L.M., C.L.-F.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Service de Médecine Interne (M.L.), Hôpital l'Archet 1, Centre Hospitalier Universitaire de Nice; Service de Biostatistique-Bioinformatique (A.G.), Hospices Civils de Lyon; Service de Neurologie (A.G.), Sclérose en Plaques, Pathologies de La Myéline et Neuro-inflammation, Hôpital Neurologique Pierre-Wertheimer, Hospices Civils de Lyon, Bron; Service de Neurologie (M.C., S.B., C.L.-F.), Centre de Ressource et Compétence - Sclérose En Plaques, Hôpital Pasteur 2; ImmunoPredict (B.S.-P.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Laboratoire d'Immunologie (B.S.-P.), Hôpital l'Archet 1; and Service de Radiologie (L.M.), Hôpital Pasteur 2, Centre Hospitalier Universitaire de Nice, France
| | - Christine Lebrun-Frenay
- From the URRIS (M.L., C.L.-C., M.C., L.M., C.L.-F.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Service de Médecine Interne (M.L.), Hôpital l'Archet 1, Centre Hospitalier Universitaire de Nice; Service de Biostatistique-Bioinformatique (A.G.), Hospices Civils de Lyon; Service de Neurologie (A.G.), Sclérose en Plaques, Pathologies de La Myéline et Neuro-inflammation, Hôpital Neurologique Pierre-Wertheimer, Hospices Civils de Lyon, Bron; Service de Neurologie (M.C., S.B., C.L.-F.), Centre de Ressource et Compétence - Sclérose En Plaques, Hôpital Pasteur 2; ImmunoPredict (B.S.-P.), Unité Mixte de Recherche Clinique Côte d'Azur (UMR2CA); Laboratoire d'Immunologie (B.S.-P.), Hôpital l'Archet 1; and Service de Radiologie (L.M.), Hôpital Pasteur 2, Centre Hospitalier Universitaire de Nice, France
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5
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Lebrun-Frenay C, Kantarci O, Siva A, Azevedo CJ, Makhani N, Pelletier D, Okuda DT. Radiologically isolated syndrome. Lancet Neurol 2023; 22:1075-1086. [PMID: 37839432 DOI: 10.1016/s1474-4422(23)00281-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 05/29/2023] [Accepted: 07/17/2023] [Indexed: 10/17/2023]
Abstract
Individuals can be deemed to have radiologically isolated syndrome (RIS) if they have incidental demyelinating-appearing lesions in their brain or spinal cord that are highly suggestive of multiple sclerosis but their clinical history does not include symptoms consistent with multiple sclerosis. Data from international longitudinal cohorts indicate that around half of people with RIS will develop relapsing or progressive symptoms of multiple sclerosis within 10 years, suggesting that in some individuals, RIS is a presymptomatic stage of multiple sclerosis. Risk factors for progression from RIS to clinical multiple sclerosis include younger age (ie, <35 years), male sex, CSF-restricted oligoclonal bands, spinal cord or infratentorial lesions, and gadolinium-enhancing lesions. Other imaging, biological, genetic, and digital biomarkers that might be of value in identifying individuals who are at the highest risk of developing multiple sclerosis need further investigation. Two 2-year randomised clinical trials showed the efficacy of approved multiple sclerosis immunomodulatory medications in preventing the clinical conversion to multiple sclerosis in some individuals with RIS. If substantiated in longer-term studies, these data have the potential to transform our approach to care for the people with RIS who are at the greatest risk of diagnosis with multiple sclerosis.
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Affiliation(s)
- Christine Lebrun-Frenay
- CRC-SEP Nice, Neurologie CHU Nice, Hôpital Pasteur 2, UMR2CA-URRIS, Université Côte d'Azur, Nice, France.
| | | | - Aksel Siva
- Department of Neurology, Cerrahpasa School of Medicine, Istanbul University, Turkiye
| | - Christina J Azevedo
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Naila Makhani
- Departments of Pediatrics and Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Daniel Pelletier
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Darin T Okuda
- Department of Neurology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
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6
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Wu Y, Geraldes R, Juryńczyk M, Palace J. Double-negative neuromyelitis optica spectrum disorder. Mult Scler 2023; 29:1353-1362. [PMID: 37740717 PMCID: PMC10580671 DOI: 10.1177/13524585231199819] [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: 05/24/2023] [Revised: 08/02/2023] [Accepted: 08/21/2023] [Indexed: 09/25/2023]
Abstract
Most patients with neuromyelitis optica spectrum disorders (NMOSD) test positive for aquaporin-4 antibody (AQP4-IgG) or myelin oligodendrocyte glycoprotein antibodies (MOG-IgG). Those who are negative are termed double-negative (DN) NMOSD and may constitute a diagnostic and therapeutic challenge. DN NMOSD is a syndrome rather than a single disease, ranging from a (postinfectious) monophasic illness to a more chronic syndrome that can be indistinguishable from AQP4-IgG+ NMOSD or develop into other mimics such as multiple sclerosis. Thus, underlying disease mechanisms are likely to be heterogeneous. This topical review aims to (1) reappraise antibody-negative NMOSD definition as it has changed over time with the development of the AQP4 and MOG-IgG assays; (2) outline clinical characteristics and the pathophysiological nature of this rare entity by contrasting its differences and similarities with antibody-positive NMOSD; (3) summarize laboratory characteristics and magnetic resonance imaging findings of DN NMOSD; and (4) discuss the current treatment for DN NMOSD.
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Affiliation(s)
- Yan Wu
- Neurology Department of First Affiliated Hospital of Kunming Medical University, Kunming, China/Nuffield Department of Clinical Neurosciences, Oxford University Hospitals, Oxford, UK
| | - Ruth Geraldes
- Nuffield Department of Clinical Neurosciences, Oxford University Hospitals, Oxford, UK/Neurology Department, Wexham Park hospital, Frimley Foundation Health Trust, Slough, UK
| | - Maciej Juryńczyk
- Department of Neurology, Stroke and Neurological Rehabilitation, Wolski Hospital, Warsaw, Poland
| | - Jacqueline Palace
- Nuffield Department of Clinical Neurosciences, Oxford University Hospitals, Oxford, UK
- J Palace Department Clinical Neurology, John Radcliffe Hospital, Oxford OX3 9DU, UK
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7
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Li F, Liu A, Zhao M, Luo L. Astrocytic Chitinase-3-like protein 1 in neurological diseases: Potential roles and future perspectives. J Neurochem 2023; 165:772-790. [PMID: 37026513 DOI: 10.1111/jnc.15824] [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: 12/09/2021] [Revised: 08/17/2022] [Accepted: 03/29/2023] [Indexed: 04/08/2023]
Abstract
Chitinase-3-like protein 1 (CHI3L1) is a secreted glycoprotein characterized by its ability to regulate multiple biological processes, such as the inflammatory response and gene transcriptional signaling activation. Abnormal CHI3L1 expression has been associated with multiple neurological disorders and serves as a biomarker for the early detection of several neurodegenerative diseases. Aberrant CHI3L1 expression is also reportedly associated with brain tumor migration and metastasis, as well as contributions to immune escape, playing important roles in brain tumor progression. CHI3L1 is synthesized and secreted mainly by reactive astrocytes in the central nervous system. Thus, targeting astrocytic CHI3L1 could be a promising approach for the treatment of neurological diseases, such as traumatic brain injury, ischemic stroke, Alzheimer's disease, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, and glioma. Based on current knowledge of CHI3L1, we assume that it acts as a molecule mediating several signaling pathways driving the initiation and progression of neurological disorders. This narrative review is the first to introduce the potential roles of astrocytic CHI3L1 in neurological disorders. We also equally explore astrocytic CHI3L1 mRNA expression under physiological and pathological conditions. Inhibiting CHI3L1 and disrupting its interaction with its receptors through multiple mechanisms of action are briefly discussed. These endeavors highlight the pivotal roles of astrocytic CHI3L1 in neurological disorders and could contribute to the development of effective inhibitors based on the strategy of structure-based drug discovery, which could be an attractive therapeutic approach for neurological disease treatment.
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Affiliation(s)
- Fei Li
- Precision Pharmacy and Drug Development Center, Department of Pharmacy, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
- Department of Pharmacy, The Hospital of 92880 Troops, PLA Navy, Zhoushan, Zhejiang, China
| | - An Liu
- Precision Pharmacy and Drug Development Center, Department of Pharmacy, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Minggao Zhao
- Precision Pharmacy and Drug Development Center, Department of Pharmacy, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
- Institute of Medical Research, Northwestern Polytechnical University, Shaanxi, Xi'an, China
| | - Lanxin Luo
- Precision Pharmacy and Drug Development Center, Department of Pharmacy, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
- Institute of Medical Research, Northwestern Polytechnical University, Shaanxi, Xi'an, China
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8
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Rademacher TD, Meuth SG, Wiendl H, Johnen A, Landmeyer NC. Molecular biomarkers and cognitive impairment in multiple sclerosis: State of the field, limitations, and future direction - A systematic review and meta-analysis. Neurosci Biobehav Rev 2023; 146:105035. [PMID: 36608917 DOI: 10.1016/j.neubiorev.2023.105035] [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: 10/12/2022] [Revised: 12/20/2022] [Accepted: 01/02/2023] [Indexed: 01/05/2023]
Abstract
OBJECTIVE Multiple sclerosis (MS) is associated with cognitive impairment (CI) such as slowed information processing speed (IPS). Currently, no immunocellular or molecular markers have been established in cerebrospinal fluid and serum analysis as surrogate biomarkers with diagnostic or predictive value for the development of CI. This systematic review and meta-analysis aims to sum up the evidence regarding currently discussed markers for CI in MS. METHODS A literature search was conducted on molecular biomarkers of CI in MS, such as neurofilament light chain, chitinases, and vitamin D. RESULTS 5543 publications were screened, of which 77 entered the systematic review. 13 studies were included in the meta-analysis. Neurofilament light chain (CSF: rp = -0.294, p = 0.003; serum: rp = -0.137, p = 0.001) and serum levels of vitamin D (rp = 0.190, p = 0.014) were associated with IPS outcomes. CONCLUSIONS Neurofilament light chain and vitamin D are promising biomarkers to track impairments in IPS in MS. Further longitudinal research is needed to establish the use of molecular biomarkers to monitor cognitive decline.
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Affiliation(s)
| | - Sven G Meuth
- Department of Neurology, University Hospital Düsseldorf, Germany
| | - Heinz Wiendl
- Department of Neurology, University Hospital Münster, Germany
| | - Andreas Johnen
- Department of Neurology, University Hospital Münster, Germany
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9
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Rival M, Thouvenot E, Du Trieu de Terdonck L, Laurent-Chabalier S, Demattei C, Uygunoglu U, Castelnovo G, Cohen M, Okuda DT, Kantarci OH, Pelletier D, Azevedo C, Marin P, Lehmann S, Siva A, Mura T, Lebrun-Frenay C. Neurofilament Light Chain Levels Are Predictive of Clinical Conversion in Radiologically Isolated Syndrome. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2022; 10:10/1/e200044. [PMID: 36280258 PMCID: PMC9621336 DOI: 10.1212/nxi.0000000000200044] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 08/29/2022] [Indexed: 01/24/2023]
Abstract
BACKGROUND AND OBJECTIVES To evaluate the predictive value of serum neurofilament light chain (sNfL) and CSF NfL (cNfL) in patients with radiologically isolated syndrome (RIS) for evidence of disease activity (EDA) and clinical conversion (CC). METHODS sNfL and cNfL were measured at RIS diagnosis by single-molecule array (Simoa). The risk of EDA and CC according to sNfL and cNfL was evaluated using the Kaplan-Meier analysis and multivariate Cox regression models including age, spinal cord (SC) or infratentorial lesions, oligoclonal bands, CSF chitinase 3-like protein 1, and CSF white blood cells. RESULTS Sixty-one patients with RIS were included. At diagnosis, sNfL and cNfL were correlated (Spearman r = 0.78, p < 0.001). During follow-up, 47 patients with RIS showed EDA and 36 patients showed CC (median time 12.6 months, 1-86). When compared with low levels, medium and high cNfL (>260 pg/mL) and sNfL (>5.0 pg/mL) levels were predictive of EDA (log rank, p < 0.01 and p = 0.02, respectively). Medium-high cNfL levels were predictive of CC (log rank, p < 0.01). In Cox regression models, cNfL and sNfL were independent factors of EDA, while SC lesions, cNfL, and sNfL were independent factors of CC. DISCUSSION cNfL >260 pg/mL and sNfL >5.0 pg/mL at diagnosis are independent predictive factors of EDA and CC in RIS. Although cNfL predicts disease activity better, sNfL is more accessible than cNfL and can be considered when a lumbar puncture is not performed. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in people with radiologic isolated syndrome (RIS), initial serum and CSF NfL levels are associated with subsequent evidence of disease activity or clinical conversion.
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Affiliation(s)
- Manon Rival
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Eric Thouvenot
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France.
| | - Lucile Du Trieu de Terdonck
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Sabine Laurent-Chabalier
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Christophe Demattei
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Ugur Uygunoglu
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Giovanni Castelnovo
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Mikael Cohen
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Darin T Okuda
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Orhun H Kantarci
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Daniel Pelletier
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Christina Azevedo
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Philippe Marin
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Sylvain Lehmann
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Aksel Siva
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Thibault Mura
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
| | - Christine Lebrun-Frenay
- From the Department of Neurology (M.R., E.T., G.C.), Nîmes University Hospital Center, Univ. Montpellier; Functional Genomics Institute (M.R., E.T., L.D.T.T., P.M.), Univ. Montpellier, CNRS, INSERM; Department of Biostatistics (S.L.-C., C.D., T.M.), Clinical Epidemiology, Public Health and Innovation in Methdology (BESPIM), Nîmes University Hospital Center, Univ. Montpellier, France; Department of Neurology (U.U., A.S.), Cerrahpasa School of Medecine, University of Istanbul, Turkey; Centre de Ressources et Compétences Sclérose En Plaques (CRCSEP) (M.C., C.L.-F.), CHU de Nice, Hôpital Pasteur 2, Université Côte d'Azur, UR2CA-URRIS, France; UT Southwestern Medical Center (D.T.O.), Dallas, TX; Mayo Clinic (O.H.K.), Rochester, MN; University of South California (D.P., C.A.), Los Angeles; and LBPC-PPC (S.L.), Univ. Montpellier, CHU Montpellier, INM, INSERM, France
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10
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Floro S, Carandini T, Pietroboni AM, De Riz MA, Scarpini E, Galimberti D. Role of Chitinase 3-like 1 as a Biomarker in Multiple Sclerosis: A Systematic Review and Meta-analysis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2022; 9:9/4/e1164. [PMID: 35534236 PMCID: PMC9128043 DOI: 10.1212/nxi.0000000000001164] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/17/2022] [Indexed: 04/12/2023]
Abstract
BACKGROUND AND OBJECTIVES Multiple sclerosis (MS) is an autoimmune disease confined in the CNS, and its course is frequently subtle and variable. Therefore, predictive biomarkers are needed. In this scenario, we conducted a systematic review and meta-analysis to evaluate the reliability of chitinase 3-like 1 as a biomarker of MS. METHODS Research through the main scientific databases (PubMed, Scopus, Web of Science, and Cochrane Library) published from January 2010 to December 2020 was performed using the following keywords: "chitinase 3-like 1 and multiple sclerosis" and "YKL40 and multiple sclerosis." Articles were selected according to the 2020 updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines by 2 authors independently, and data were extracted; 20 of the 90 studies screened were included in the meta-analysis. The main efficacy measure was represented by the standardized mean difference of CSF and blood CHI3L1 levels; Review Manager version 5.4 and R software applications were used for analysis. RESULTS Higher levels of CHI3L1 were found in CSF of 673 patients with MS compared with 336 healthy controls (size-weighted mean difference [SMD] 50.88; 95% CI = 44.98-56.79; p < 0.00001) and in 461 patients with MS than 283 patients with clinically isolated syndrome (CIS) (SMD 28.18; 95% CI = 23.59-32.76; p < 0.00001). Mean CSF CHI3L1 levels were significantly higher in 561 converting than 445 nonconverting CIS (SMD 30.6; 95% CI = 28.31-32.93; p < 0.00001). CSF CHI3L1 levels were significantly higher in patients with primary progressive MS (PPMS) than in patients with relapsing-remitting MS (RRMS) (SMD 43.15; 95% CI = 24.41-61.90; p < 0.00001) and in patients with secondary progressive MS (SMD 41.86 with 95% CI = 32.39-51.33; p < 0.00001). CSF CHI3L1 levels in 407 patients with MS during remission phase of disease were significantly higher than those in 395 patients with MS with acute relapse (SMD 10.48; 95% CI = 08.51-12.44; p < 0.00001). The performances of CHI3L1 in blood for differentiating patients with MS from healthy controls were not significant (SMD 0.48; 95% CI = -1.18 to 2.14; p: 0.57). DISCUSSION CSF levels of CHI3L1 have a strong correlation with the MS pathologic course, in particular with the mechanism of progression of the disease; it helps to distinguish the PPMS from the RRMS. The potential role of CHI3L1 in serum needs to be further studied in the future.
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Affiliation(s)
- Stefano Floro
- From the Fondazione IRCCS Ca' Granda (S.F., T.C., A.M.P., M.A.D.R., E.S., D.G.), Ospedale Policlinico; and University of Milan (S.F., E.S., D.G.), Milan, Italy
| | - Tiziana Carandini
- From the Fondazione IRCCS Ca' Granda (S.F., T.C., A.M.P., M.A.D.R., E.S., D.G.), Ospedale Policlinico; and University of Milan (S.F., E.S., D.G.), Milan, Italy
| | - Anna Margherita Pietroboni
- From the Fondazione IRCCS Ca' Granda (S.F., T.C., A.M.P., M.A.D.R., E.S., D.G.), Ospedale Policlinico; and University of Milan (S.F., E.S., D.G.), Milan, Italy
| | - Milena Alessandra De Riz
- From the Fondazione IRCCS Ca' Granda (S.F., T.C., A.M.P., M.A.D.R., E.S., D.G.), Ospedale Policlinico; and University of Milan (S.F., E.S., D.G.), Milan, Italy
| | - Elio Scarpini
- From the Fondazione IRCCS Ca' Granda (S.F., T.C., A.M.P., M.A.D.R., E.S., D.G.), Ospedale Policlinico; and University of Milan (S.F., E.S., D.G.), Milan, Italy
| | - Daniela Galimberti
- From the Fondazione IRCCS Ca' Granda (S.F., T.C., A.M.P., M.A.D.R., E.S., D.G.), Ospedale Policlinico; and University of Milan (S.F., E.S., D.G.), Milan, Italy
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11
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Update on Multiple Sclerosis Molecular Biomarkers to Monitor Treatment Effects. J Pers Med 2022; 12:jpm12040549. [PMID: 35455665 PMCID: PMC9024668 DOI: 10.3390/jpm12040549] [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: 02/25/2022] [Revised: 03/27/2022] [Accepted: 03/28/2022] [Indexed: 12/04/2022] Open
Abstract
Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease of the central nervous system characterized by broad inter- and intraindividual heterogeneity. The relapse rate, disability progression, and lesion load assessed through MRI are used to detect disease activity and response to treatment. Although it is possible to standardize these characteristics in larger patient groups, so far, this has been difficult to achieve in individual patients. Easily detectable molecular biomarkers can be powerful tools, permitting a tailored therapy approach for MS patients. However, only a few molecular biomarkers have been routinely used in clinical practice as the validation process, and their transfer into clinical practice takes a long time. This review describes the characteristics of an ideal MS biomarker, the challenges of establishing new biomarkers, and promising molecular biomarkers from blood or CSF samples used to monitor MS treatment effects in clinical practice.
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12
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Alifirova V, Kamenskikh E, Koroleva E, Kolokolova E, Petrakovich A. Prognostic markers of multiple sclerosis. Zh Nevrol Psikhiatr Im S S Korsakova 2022; 122:22-27. [DOI: 10.17116/jnevro202212202122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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13
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Barro C, Zetterberg H. The blood biomarkers puzzle - A review of protein biomarkers in neurodegenerative diseases. J Neurosci Methods 2021; 361:109281. [PMID: 34237384 DOI: 10.1016/j.jneumeth.2021.109281] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 06/07/2021] [Accepted: 07/04/2021] [Indexed: 02/04/2023]
Abstract
Neurodegenerative diseases are heterogeneous in their cause and clinical presentation making clinical assessment and disease monitoring challenging. Because of this, there is an urgent need for objective tools such as fluid biomarkers able to quantitate different aspects of the disease. In the last decade, technological improvements and awareness of the importance of biorepositories led to the discovery of an evolving number of fluid biomarkers covering the main characteristics of neurodegenerative diseases such as neurodegeneration, protein aggregates and inflammation. The ability to quantitate each aspect of the disease at a high definition enables a more precise stratification of the patients at inclusion in clinical trials, hence reducing the noise that may hamper the detection of therapeutical efficacy and allowing for smaller but likewise powered studies, which particularly improves the ability to start clinical trials for rare neurological diseases. Moreover, the use of fluid biomarkers has the potential to support a targeted therapeutical intervention, as it is now emerging for the treatment of amyloid-beta deposition in patients suffering from Alzheimer's disease. Here we review the knowledge that evolved from the measurement of fluid biomarker proteins in neurodegenerative conditions.
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Affiliation(s)
- Christian Barro
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA.
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL, London, UK; Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
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14
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Early multiple sclerosis: diagnostic challenges in clinically and radiologically isolated syndrome patients. Curr Opin Neurol 2021; 34:277-285. [PMID: 33661162 DOI: 10.1097/wco.0000000000000921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
PURPOSE OF REVIEW With the introduction of new diagnostic criteria, the sensibility for multiple sclerosis (MS) diagnosis increased and the number of cases with the clinically isolated syndrome (CIS) decreased. Nevertheless, a misdiagnosis might always be around the corner, and the exclusion of a 'better explanation' is mandatory.There is a pressing need to provide an update on the main prognostic factors that increase the risk of conversion from CIS or from radiologically isolated syndrome (RIS) to MS, and on the potential 'red flags' to consider during the diagnostic workup. RECENT FINDINGS We discuss diagnostic challenges when facing patients presenting with a first demyelinating attack or with a RIS, with a focus on recently revised diagnostic criteria, on other neuroinflammatory conditions to be considered in the differential diagnosis and on factors distinguishing patients at risk of developing MS.A correct definition of a 'typical' demyelinating attack, as well as a correct interpretation of MRI findings, remains crucial in the diagnostic process. The cerebrospinal fluid examination is warmly recommended to confirm the dissemination in time of the demyelinating process and to increase the diagnostic accuracy. SUMMARY An early and accurate diagnosis of MS requires careful consideration of all clinical, paraclinical and radiological data, as well the reliable exclusion of other mimicking pathological conditions. This is advocated to promptly initiate an appropriate disease-modifying therapy, which can impact positively on the long-term outcome of the disease.
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15
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Momtazmanesh S, Shobeiri P, Saghazadeh A, Teunissen CE, Burman J, Szalardy L, Klivenyi P, Bartos A, Fernandes A, Rezaei N. Neuronal and glial CSF biomarkers in multiple sclerosis: a systematic review and meta-analysis. Rev Neurosci 2021; 32:573-595. [PMID: 33594840 DOI: 10.1515/revneuro-2020-0145] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 01/15/2021] [Indexed: 12/29/2022]
Abstract
Multiple sclerosis (MS) is a neurodegenerative disease associated with inflammatory demyelination and astroglial activation, with neuronal and axonal damage as the leading factors of disability. We aimed to perform a meta-analysis to determine changes in CSF levels of neuronal and glial biomarkers, including neurofilament light chain (NFL), total tau (t-tau), chitinase-3-like protein 1 (CHI3L1), glial fibrillary acidic protein (GFAP), and S100B in various groups of MS (MS versus controls, clinically isolated syndrome (CIS) versus controls, CIS versus MS, relapsing-remitting MS (RRMS) versus progressive MS (PMS), and MS in relapse versus remission. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, we included 64 articles in the meta-analysis, including 4071 subjects. For investigation of sources of heterogeneity, subgroup analysis, meta-regression, and sensitivity analysis were conducted. Meta-analyses were performed for comparisons including at least three individual datasets. NFL, GFAP, t-tau, CHI3L1, and S100B were higher in MS and NFL, t-tau, and CHI3L1 were also elevated in CIS patients than controls. CHI3L1 was the only marker with higher levels in MS than CIS. GFAP levels were higher in PMS versus RRMS, and NFL, t-tau, and CHI3L1 did not differ between different subtypes. Only levels of NFL were higher in patients in relapse than remission. Meta-regression showed influence of sex and disease severity on NFL and t-tau levels, respectively and disease duration on both. Added to the role of these biomarkers in determining prognosis and treatment response, to conclude, they may serve in diagnosis of MS and distinguishing different subtypes.
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Affiliation(s)
- Sara Momtazmanesh
- School of Medicine, Tehran University of Medical Sciences (TUMS), Children's Medical Center Hospital, Dr. Qarib St., Keshavarz Blvd, Tehran14194, Iran.,Systematic Review and Meta-Analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran.,Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Parnian Shobeiri
- School of Medicine, Tehran University of Medical Sciences (TUMS), Children's Medical Center Hospital, Dr. Qarib St., Keshavarz Blvd, Tehran14194, Iran.,Systematic Review and Meta-Analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Amene Saghazadeh
- Systematic Review and Meta-Analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran.,Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Location VUmc, PK 2 BR 141, Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Joachim Burman
- Department of Neuroscience, Uppsala University Hospital, 75185Uppsala, Sweden
| | - Levente Szalardy
- Department of Neurology, Faculty of Medicine, Albert Szent-Györgyi Clinical Center, University of Szeged, Semmelweis u. 6, 6725Szeged, Hungary
| | - Peter Klivenyi
- Department of Neurology, Faculty of Medicine, Albert Szent-Györgyi Clinical Center, University of Szeged, Semmelweis u. 6, 6725Szeged, Hungary
| | - Ales Bartos
- Department of Neurology, Third Faculty of Medicine, Charles University, Ruska 87, 100 00Prague 10, Czech Republic
| | - Adelaide Fernandes
- Department of Pharmacological Sciences and Medicines, Faculty of Pharmacy, Universidade de Lisboa, Avenida Professor Gama Pinto, 1649-003Lisbon, Portugal
| | - Nima Rezaei
- Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran.,Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.,Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran
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16
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Radiologically isolated syndrome: from biological bases to practical management. Neurol Sci 2021; 42:1335-1344. [PMID: 33496891 DOI: 10.1007/s10072-021-05069-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 01/16/2021] [Indexed: 11/27/2022]
Abstract
BACKGROUND Technological advances and greater availability of magnetic resonance imaging have prompted an increment on incidental and unexpected findings within the central nervous system. The concept of radiologically isolated syndrome characterizes a group of subjects with images suggestive of demyelinating disease in the absence of a clinical episode compatible with multiple sclerosis. Since the description of this entity, many questions have arisen; some have received responses but others remain unanswered. A panel of experts met with the objective of performing a critical review of the currently available evidence. Definition, prevalence, biological bases, published evidence, and implications on patient management were reviewed. Thirty to 50% of subjects with radiologically isolated syndrome will progress to multiple sclerosis in 5 years. Male sex, age < 37 years old, and spinal lesions increase the risk. These subjects should be evaluated by a multiple sclerosis specialist, carefully excluding alternative diagnosis. An initial evaluation should include a brain and complete spine magnetic resonance, visual evoked potentials, and identification of oligoclonal bands in cerebrospinal fluid. Disease-modifying therapies could be considered when oligoclonal bands or radiological progression is present. CONCLUSION At present time, radiologically isolated syndrome cannot be considered a part of the multiple sclerosis spectrum. However, a proportion of patients may evolve to multiple sclerosis, meaning it represents much more than just a radiological finding.
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17
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Muñoz-San Martín M, Torras S, Robles-Cedeño R, Buxó M, Gomez I, Matute-Blanch C, Comabella M, Villar LM, Perkal H, Quintana E, Ramió-Torrentà L. Radiologically isolated syndrome: targeting miRNAs as prognostic biomarkers. Epigenomics 2020; 12:2065-2076. [DOI: 10.2217/epi-2020-0172] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Aim: Some clinical and biological characteristics have been described as prognostic factors for clinical conversion into clinically definite multiple sclerosis in radiologically isolated syndrome (RIS) population. The aim of this study was to assess signatures of circulating miRNAs in those patients according to their conversion status after 5 years of follow-up. Patients & methods: OpenArray plates assessing 216 miRNA candidates were run in 15 RIS patients, and their relative abundances were analyzed. Results: A specific profile of deregulated circulating miRNAs (miR-144-3p, miR-448 and miR-653-3p in cerebrospinal fluid and miR-142-3p, miR-338-3p, miR-363-3p, miR-374b-5p, miR-424-5p, miR-483-3p in plasma) differentiated individuals who remained as RIS after 5 years of follow-up. Conclusion: Circulating miRNAs might be used as prognostic biomarkers for RIS patients.
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Affiliation(s)
- María Muñoz-San Martín
- Neurodegeneration & Neuroinflammation Group, Girona Biomedical Research Institute (IDIBGI), 17190 Salt, Spain
| | - Sandra Torras
- Neurodegeneration & Neuroinflammation Group, Girona Biomedical Research Institute (IDIBGI), 17190 Salt, Spain
| | - René Robles-Cedeño
- Department of Neurology, Girona Neuroimmunology & Multiple Sclerosis Unit, Dr. Josep Trueta University Hospital & Santa Caterina Hospital, Girona/Salt-Spain; Neurodegeneration & Neuroinflammation Group, Girona Biomedical Research Institute (IDIBGI), 17190 Salt, Spain
- REEM, Red Española de Esclerosis Múltiple
- Department of Medical Sciences, Faculty of Medicine, University of Girona, 17190 Girona, Spain
| | - Maria Buxó
- Girona Biomedical Research Institute (IDIBGI), 17190 Salt, Spain
| | - Imma Gomez
- Neurodegeneration & Neuroinflammation Group, Girona Biomedical Research Institute (IDIBGI), 17190 Salt, Spain
| | - Clara Matute-Blanch
- Servei de Neurologia-Neuroimmunologia, Centre d’Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d’Hebron (VHIR), Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
| | - Manuel Comabella
- REEM, Red Española de Esclerosis Múltiple
- Servei de Neurologia-Neuroimmunologia, Centre d’Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d’Hebron (VHIR), Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
| | - Luisa María Villar
- REEM, Red Española de Esclerosis Múltiple
- Department of Immunology, Hospital Ramón y Cajal, IRYCIS, 28034 Madrid, Spain
| | - Héctor Perkal
- Department of Neurology, Girona Neuroimmunology & Multiple Sclerosis Unit, Dr. Josep Trueta University Hospital & Santa Caterina Hospital, Girona/Salt-Spain; Neurodegeneration & Neuroinflammation Group, Girona Biomedical Research Institute (IDIBGI), 17190 Salt, Spain
| | - Ester Quintana
- Neurodegeneration & Neuroinflammation Group, Girona Biomedical Research Institute (IDIBGI), 17190 Salt, Spain
- REEM, Red Española de Esclerosis Múltiple
- Department of Medical Sciences, Faculty of Medicine, University of Girona, 17190 Girona, Spain
| | - Lluís Ramió-Torrentà
- Department of Neurology, Girona Neuroimmunology & Multiple Sclerosis Unit, Dr. Josep Trueta University Hospital & Santa Caterina Hospital, Girona/Salt-Spain; Neurodegeneration & Neuroinflammation Group, Girona Biomedical Research Institute (IDIBGI), 17190 Salt, Spain
- REEM, Red Española de Esclerosis Múltiple
- Department of Medical Sciences, Faculty of Medicine, University of Girona, 17190 Girona, Spain
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18
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Leguy S, Combès B, Bannier E, Kerbrat A. Prognostic value of spinal cord MRI in multiple sclerosis patients. Rev Neurol (Paris) 2020; 177:571-581. [PMID: 33069379 DOI: 10.1016/j.neurol.2020.08.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 08/04/2020] [Accepted: 08/05/2020] [Indexed: 11/19/2022]
Abstract
Multiple sclerosis [MS] is a common inflammatory, demyelinating and neurodegenerative disease of the central nervous system that affects both the brain and the spinal cord. In clinical practice, spinal cord MRI is performed far less frequently than brain MRI, mainly owing to technical limitations and time constraints. However, improvements of acquisition techniques, combined with a strong diagnosis and prognostic value, suggest an increasing use of spinal cord MRI in the near future. This review summarizes the current data from the literature on the prognostic value of spinal cord MRI in MS patients in the early and later stages of their disease. Both conventional and quantitative MRI techniques are discussed. The prognostic value of spinal cord lesions is clearly established at the onset of disease, underlining the interest of spinal cord conventional MRI at this stage. However, studies are currently lacking to affirm the prognostic role of spinal cord lesions later in the disease, and therefore the added value of regular follow-up with spinal cord MRI in addition to brain MRI. Besides, spinal cord atrophy, as measured by the loss of cervical spinal cord area, is also associated with disability progression, independently of other clinical and MRI factors including spinal cord lesions. Although potentially interesting, this measurement is not currently performed as a routine clinical procedure. Finally, other measures extracted from quantitative MRI have been established as valuable for a better understanding of the physiopathology of MS, but still remain a field of research.
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Affiliation(s)
- S Leguy
- CHU de Rennes, Neurology department, 2, Rue Henri-le-Guilloux, 35000 Rennes, France; University Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn U1228, Rennes, France
| | - B Combès
- University Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn U1228, Rennes, France
| | - E Bannier
- University Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn U1228, Rennes, France; CHU de Rennes, Radiology department, Rennes, France
| | - A Kerbrat
- CHU de Rennes, Neurology department, 2, Rue Henri-le-Guilloux, 35000 Rennes, France; University Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn U1228, Rennes, France.
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19
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Kabaeva AR, Boyko AN, Kulakova OG, Favorova OO. [Radiologically isolated syndrome: prognosis and predictors of conversion to multiple sclerosis]. Zh Nevrol Psikhiatr Im S S Korsakova 2020; 120:7-12. [PMID: 32844624 DOI: 10.17116/jnevro20201200727] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Increased sensitivity and availability of magnetic resonance imaging (MRI) in neurological routine practice led to the fact that more and more experts began to encounter changes typical for multiple sclerosis (MS) according to MRI in the absence of anamnestic and clinical indications of damage to the central nervous system (CNS). This nosological form has been defined as a radiologically isolated syndrome (RIS). More and more RIS cases convert to MS (up to 30% in the first 5 years after RIS diagnosis). At the moment, there are no biological markers that allow combining RIS and MS into one pathological process and early treatment with disease-modifying drugs (DMT). Prospective studies are actively being conducted to identify demographic, clinical, neuroimaging and biochemical conversion predictors. The identification of the molecular biological RIS features, combining these changes with MS, is an urgent scientific task and will allow timely initiation of therapy of the pathological process already at the subclinical stage.
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Affiliation(s)
- A R Kabaeva
- Pirogov Russian National Research Medical University, Moscow, Russia
| | - A N Boyko
- Pirogov Russian National Research Medical University, Moscow, Russia.,Federal Center of Cerebrovascular Pathology and Stroke, Moscow, Russia
| | - O G Kulakova
- Pirogov Russian National Research Medical University, Moscow, Russia.,Institute of Experimental Cardiology of National Medical Research Center of Cardiology, Moscow, Russia
| | - O O Favorova
- Pirogov Russian National Research Medical University, Moscow, Russia.,Institute of Experimental Cardiology of National Medical Research Center of Cardiology, Moscow, Russia
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20
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Hosseiny M, Newsome SD, Yousem DM. Radiologically Isolated Syndrome: A Review for Neuroradiologists. AJNR Am J Neuroradiol 2020; 41:1542-1549. [PMID: 32763896 DOI: 10.3174/ajnr.a6649] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 05/04/2020] [Indexed: 12/24/2022]
Abstract
Radiologically isolated syndrome refers to an entity in which white matter lesions fulfilling the criteria for multiple sclerosis occur in individuals without a history of a clinical demyelinating attack or alternative etiology. Since its introduction in 2009, the diagnostic criteria of radiologically isolated syndrome and its clinical relevance have been widely debated by neurologists and radiologists. The aim of the present study was to review the following: 1) historical evolution of radiologically isolated syndrome criteria, 2) clinical and imaging findings in adults and children with radiologically isolated syndrome, 3) imaging features of patients with radiologically isolated syndrome at high risk for conversion to MS, and 4) challenges and controversies for work-up, management, and therapeutic interventions of patients with radiologically isolated syndrome.
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Affiliation(s)
- M Hosseiny
- From the Department of Radiological Sciences (M.H.), David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, California
| | - S D Newsome
- Department of Neurology (S.D.N.), Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - D M Yousem
- Russell H. Morgan Department of Radiology and Radiological Sciences (D.M.Y.), Johns Hopkins Medical Institution, Baltimore, Maryland.
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21
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Jons D, Zetterberg H, Malmeström C, Bergström T, Axelsson M, Blennow K, Thulin M, Sundström P, Andersen O. Intrathecal immunoreactivity in people with or without previous infectious mononucleosis. Acta Neurol Scand 2020; 142:161-168. [PMID: 32415852 DOI: 10.1111/ane.13280] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 05/07/2020] [Accepted: 05/12/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVES The risk of developing multiple sclerosis (MS) increases (OR: 3.1) after infectious mononucleosis (IM). However, the nature of this link is obscure. We tested the hypothesis that IM might incur long-term sequelae, including low-key inflammatory activity, with characteristics of an MS endophenotype (or presymptomatic trait) and that assays of MS-relevant cyto-/chemokines in the cerebrospinal fluid (CSF) post-IM may show a trend in this direction. MATERIALS AND METHODS We selected seven CSF cytokines (IL-1b, IL-6, YKL-40, TNF-alpha) or chemokines (IL-8, CCL2, IP-10), representing pro-inflammatory factors previously associated with MS. We assayed the CSF levels of these seven cyto-/chemokines in healthy individuals with a median follow-up time of 10 years after serologically confirmed IM (post-IM group, n = 22), and in healthy controls without a history of IM (n = 19). A group of MS patients (n = 23) were included as reference. RESULTS The CSF levels of IP-10, YKL-40, and CCL-2 were higher in the post-IM group than in our IM unexposed controls (P = .021, .049, .028). Seven of seven cyto-/chemokine assays showed a trend in the predicted direction (P of binomial ratio = .008). However, this trend was non-significant in a multivariate test (P = .22). A power analysis indicated that similar studies including a larger cohort would be numerically realistic. CONCLUSIONS These results do not reject the hypothesis that the established epidemiological association between IM and MS results from a stepwise inflammatory propagation from IM sequelae to an MS endophenotype (or presymptomatic trait) in a proportion of IM patients, pending confirmation with adequate power.
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Affiliation(s)
- Daniel Jons
- Department of Clinical Neuroscience Institute of Neuroscience and Physiology The Sahlgrenska Academy University of Gothenburg Gothenburg Sweden
- Department of Neurology Sahlgrenska University Hospital Gothenburg Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry Institute of Neuroscience and Physiology The Sahlgrenska Academy University of Gothenburg Mölndal Sweden
- Clinical Neurochemistry Laboratory Sahlgrenska University Hospital Mölndal Sweden
- UK Dementia Research Institute at UCL London UK
- Department of Neurodegenerative Diseases UCL Institute of Neurology London UK
| | - Clas Malmeström
- Department of Clinical Neuroscience Institute of Neuroscience and Physiology The Sahlgrenska Academy University of Gothenburg Gothenburg Sweden
- Department of Neurology Sahlgrenska University Hospital Gothenburg Sweden
| | - Tomas Bergström
- Department of Clinical Microbiology Sahlgrenska University HospitalVästra Götaland Region Gothenburg Sweden
| | - Markus Axelsson
- Department of Clinical Neuroscience Institute of Neuroscience and Physiology The Sahlgrenska Academy University of Gothenburg Gothenburg Sweden
- Department of Neurology Sahlgrenska University Hospital Gothenburg Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry Institute of Neuroscience and Physiology The Sahlgrenska Academy University of Gothenburg Mölndal Sweden
- Clinical Neurochemistry Laboratory Sahlgrenska University Hospital Mölndal Sweden
| | - Måns Thulin
- Department of Statistics Uppsala University Uppsala Sweden
- School of Mathematics and Maxwell Institute for Mathematical Sciences University of Edinburgh Edinburgh UK
| | - Peter Sundström
- Department of Clinical Science, Neurosciences Umeå University Umeå Sweden
| | - Oluf Andersen
- Department of Clinical Neuroscience Institute of Neuroscience and Physiology The Sahlgrenska Academy University of Gothenburg Gothenburg Sweden
- Department of Neurology Sahlgrenska University Hospital Gothenburg Sweden
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22
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Lebrun-Frenay C, Kantarci O, Siva A, Sormani MP, Pelletier D, Okuda DT. Radiologically Isolated Syndrome: 10-Year Risk Estimate of a Clinical Event. Ann Neurol 2020; 88:407-417. [PMID: 32500558 DOI: 10.1002/ana.25799] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 05/21/2020] [Accepted: 05/26/2020] [Indexed: 02/04/2023]
Abstract
OBJECTIVE We have previously identified male sex, younger age, and the presence of spinal cord lesions as independent factors that increase the 5-year risk for evolution from radiologically isolated syndrome (RIS) to multiple sclerosis. Here, we investigate risk factors for the development of a clinical event using a 10-year, multinational, retrospectively identified RIS dataset. METHODS RIS subjects were identified according to 2009 RIS criteria and followed longitudinally as part of a worldwide cohort study. We analyzed data from 21 individual databases from 5 different countries. Associations between clinical and magnetic resonance imaging (MRI) characteristics and the risk of developing a first clinical event were determined using multivariate Cox regression models. RESULTS Additional follow-up data were available in 277 of 451 RIS subjects (86% female). The mean age at RIS diagnosis was 37.2 years (range, 11-74 years), with a median clinical follow-up of 6.7 years. The cumulative probability of a first clinical event at 10 years was 51.2%. Age, positive cerebrospinal fluid for oligoclonal bands, infratentorial lesions on MRI, and spinal cord lesions, were baseline independent predictors associated with a subsequent clinical event. The presence of gadolinium-enhanced lesions during follow-up was also associated with the risk of a seminal event. The reason for MRI and gadolinium-enhancing lesions at baseline did not influence the risk of a subsequent clinical event. INTERPRETATION Approximately half of all individuals with RIS experience a first clinical event within 10 years of the index MRI. The identification of independent predictors of risk for symptom onset may guide education and clinical management of individuals with RIS. ANN NEUROL 2020;88:407-417.
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Affiliation(s)
| | | | - Aksel Siva
- Department of Neurology, Istanbul University Cerrahpasa School of Medicine, Istanbul, Turkey
| | - Maria P Sormani
- Statistic Unit, University of Genoa, Genoa, Italy.,IRCCS Ospedale Policlinico San Martino, IRCCS, Genoa, Italy
| | | | - Darin T Okuda
- University of Texas Southwestern Medical Center, Dallas, TX, USA
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23
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Ziemssen T, Akgün K, Brück W. Molecular biomarkers in multiple sclerosis. J Neuroinflammation 2019; 16:272. [PMID: 31870389 PMCID: PMC6929340 DOI: 10.1186/s12974-019-1674-2] [Citation(s) in RCA: 130] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Accepted: 12/16/2019] [Indexed: 11/30/2022] Open
Abstract
Multiple sclerosis (MS) is an inflammatory-neurodegenerative disease of the central nervous system presenting with significant inter- and intraindividual heterogeneity. However, the application of clinical and imaging biomarkers is currently not able to allow individual characterization and prediction. Complementary, molecular biomarkers which are easily quantifiable come from the areas of immunology and neurobiology due to the causal pathomechanisms and can excellently complement other disease characteristics. Only a few molecular biomarkers have so far been routinely used in clinical practice as their validation and transfer take a long time. This review describes the characteristics that an ideal MS biomarker should have and the challenges of establishing new biomarkers. In addition, clinically relevant and promising biomarkers from the blood and cerebrospinal fluid are presented which are useful for MS diagnosis and prognosis as well as for the assessment of therapy response and side effects.
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Affiliation(s)
- Tjalf Ziemssen
- MS center, Center of Clinical Neuroscience, University Clinic Carl-Gustav Carus, Dresden University of Technology, Dresden, Germany.
| | - Katja Akgün
- MS center, Center of Clinical Neuroscience, University Clinic Carl-Gustav Carus, Dresden University of Technology, Dresden, Germany
| | - Wolfgang Brück
- Institute of Neuropathology, University Medical Center, Göttingen, Germany
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24
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Bisulca J, De Lury A, Coyle PK, Syritsyna O, Peyster R, Bangiyev L, Duong TQ. MRI features associated with high likelihood of conversion of radiologically isolated syndrome to multiple sclerosis. Mult Scler Relat Disord 2019; 36:101381. [PMID: 31518773 DOI: 10.1016/j.msard.2019.101381] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 08/30/2019] [Accepted: 08/31/2019] [Indexed: 10/26/2022]
Abstract
Radiologically isolated syndrome (RIS) is the asymptomatic precursor to clinically isolated syndrome, relapsing-remitting multiple sclerosis (MS) or primary progressive MS. RIS is frequently diagnosed when an individual gets an MRI for an unrelated medical issue, such as headache or trauma. Treating RIS patients is controversial, but physicians may be inclined to offer prophylactic treatment for high-risk RIS patients. Identifying imaging and clinical features associated with high likelihood of early clinical conversion may prove helpful to identify a high-risk subset for potential MS therapy. The goal of this paper is to review current literatures to identify imaging and clinical features that predict early (within 5 years) conversion from RIS to MS.
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Affiliation(s)
- Joseph Bisulca
- Departments of Radiology and Neurology, Stony Brook Medicine, 101 Nicolls Rd, Stony Brook, NY 11794, USA
| | - Amy De Lury
- Departments of Radiology and Neurology, Stony Brook Medicine, 101 Nicolls Rd, Stony Brook, NY 11794, USA
| | - Patricia K Coyle
- Departments of Radiology and Neurology, Stony Brook Medicine, 101 Nicolls Rd, Stony Brook, NY 11794, USA
| | - Olga Syritsyna
- Departments of Radiology and Neurology, Stony Brook Medicine, 101 Nicolls Rd, Stony Brook, NY 11794, USA
| | - Robert Peyster
- Departments of Radiology and Neurology, Stony Brook Medicine, 101 Nicolls Rd, Stony Brook, NY 11794, USA
| | - Lev Bangiyev
- Departments of Radiology and Neurology, Stony Brook Medicine, 101 Nicolls Rd, Stony Brook, NY 11794, USA
| | - Tim Q Duong
- Departments of Radiology and Neurology, Stony Brook Medicine, 101 Nicolls Rd, Stony Brook, NY 11794, USA.
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25
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Engel S, Friedrich M, Muthuraman M, Steffen F, Poplawski A, Groppa S, Bittner S, Zipp F, Luessi F. Intrathecal B-cell accumulation and axonal damage distinguish MRI-based benign from aggressive onset in MS. NEUROLOGY-NEUROIMMUNOLOGY & NEUROINFLAMMATION 2019; 6:6/5/e595. [PMID: 31454774 PMCID: PMC6705631 DOI: 10.1212/nxi.0000000000000595] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Accepted: 05/28/2019] [Indexed: 01/24/2023]
Abstract
Objective We explored the incremental value of adding multiple disease activity biomarkers in CSF and serum for distinguishing MRI-based benign from aggressive MS in early disease course. Methods Ninety-three patients diagnosed with clinically isolated syndrome (CIS) or early MS were divided into 3 nonoverlapping severity groups defined by objective MRI criteria. Ninety-seven patients with noninflammatory neurologic disorders and 48 patients with other inflammatory neurologic diseases served as controls. Leukocyte subsets in the CSF were analyzed by flow cytometry. CSF neurofilament light chain (NfL) and chitinase-3-like protein 1 (CHI3L1) levels were measured by ELISA. Serum NfL levels were examined using single molecule array technology. Results CSF CD20+/CD14+ ratios and NfL levels in CSF and serum were significantly different between high and low MRI severity groups, whereas no difference was found for CSF CHI3L1 levels. NfL levels in CSF and serum highly correlated. Receiver operating characteristic analysis demonstrated that the cumulative sums combining CSF CD20+/CD14+ ratios and NfL levels in serum or CSF considerably improved diagnostic accuracy. A composite score built from these 2 cumulative sums best distinguished MRI severity. These findings were validated by support vector machine analysis, which confirmed that the accuracy of the cumulative sums and composite score outperforms single biomarkers. Conclusion Patients with extreme manifestations of CIS or early MS defined by strict MRI parameters can be best distinguished by combining markers of intrathecal B-cell accumulation and axonal damage. This could stratify individual treatment decisions toward a more personalized immunotherapy.
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Affiliation(s)
- Sinah Engel
- From the Department of Neurology (S.E., M.F., M.M., F.S., S.G., S.B., F.Z., F.L.), Focus Program Translational Neuroscience (FTN), and Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn), University Medical Center of the Johannes Gutenberg University, Mainz; and Institute of Medical Biostatistics (A.P.), Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Michaela Friedrich
- From the Department of Neurology (S.E., M.F., M.M., F.S., S.G., S.B., F.Z., F.L.), Focus Program Translational Neuroscience (FTN), and Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn), University Medical Center of the Johannes Gutenberg University, Mainz; and Institute of Medical Biostatistics (A.P.), Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Muthuraman Muthuraman
- From the Department of Neurology (S.E., M.F., M.M., F.S., S.G., S.B., F.Z., F.L.), Focus Program Translational Neuroscience (FTN), and Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn), University Medical Center of the Johannes Gutenberg University, Mainz; and Institute of Medical Biostatistics (A.P.), Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Falk Steffen
- From the Department of Neurology (S.E., M.F., M.M., F.S., S.G., S.B., F.Z., F.L.), Focus Program Translational Neuroscience (FTN), and Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn), University Medical Center of the Johannes Gutenberg University, Mainz; and Institute of Medical Biostatistics (A.P.), Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Alicia Poplawski
- From the Department of Neurology (S.E., M.F., M.M., F.S., S.G., S.B., F.Z., F.L.), Focus Program Translational Neuroscience (FTN), and Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn), University Medical Center of the Johannes Gutenberg University, Mainz; and Institute of Medical Biostatistics (A.P.), Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Sergiu Groppa
- From the Department of Neurology (S.E., M.F., M.M., F.S., S.G., S.B., F.Z., F.L.), Focus Program Translational Neuroscience (FTN), and Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn), University Medical Center of the Johannes Gutenberg University, Mainz; and Institute of Medical Biostatistics (A.P.), Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Stefan Bittner
- From the Department of Neurology (S.E., M.F., M.M., F.S., S.G., S.B., F.Z., F.L.), Focus Program Translational Neuroscience (FTN), and Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn), University Medical Center of the Johannes Gutenberg University, Mainz; and Institute of Medical Biostatistics (A.P.), Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Frauke Zipp
- From the Department of Neurology (S.E., M.F., M.M., F.S., S.G., S.B., F.Z., F.L.), Focus Program Translational Neuroscience (FTN), and Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn), University Medical Center of the Johannes Gutenberg University, Mainz; and Institute of Medical Biostatistics (A.P.), Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Felix Luessi
- From the Department of Neurology (S.E., M.F., M.M., F.S., S.G., S.B., F.Z., F.L.), Focus Program Translational Neuroscience (FTN), and Immunotherapy (FZI), Rhine-Main Neuroscience Network (rmn), University Medical Center of the Johannes Gutenberg University, Mainz; and Institute of Medical Biostatistics (A.P.), Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany.
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26
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Pawlitzki M, Sweeney-Reed CM, Bittner D, Lux A, Vielhaber S, Schreiber S, Paul F, Neumann J. CSF-Progranulin and Neurofilament Light Chain Levels in Patients With Radiologically Isolated Syndrome-Sign of Inflammation. Front Neurol 2018; 9:1075. [PMID: 30619038 PMCID: PMC6305325 DOI: 10.3389/fneur.2018.01075] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 11/26/2018] [Indexed: 12/13/2022] Open
Abstract
Background: Cerebrospinal fluid (CSF) markers of disease in patients with radiologically isolated syndrome (RIS) are the subject of intense investigation, because they have the potential to enhance our understanding of the natural disease course and provide insights into similarities and differences between RIS and other multiple sclerosis (MS) disease identities. Methods: Here we compared neurofilament light chain (NFL) and progranulin (PGRN) levels in the CSF in RIS patients with levels in patients with different subtypes of MS and healthy controls (HC) using Kruskal–Wallis one-way analysis of variance. Results: Median CSF NFL concentrations in RIS patients did not differ to those in HC and clinically isolated syndrome (CIS) patients, but were significantly lower than in relapsing remitting (RRMS) and primary progressive (PPMS) MS patients. In contrast, RIS patients exhibited higher median CSF PGRN levels than HC and showed no significant differences compared with CIS, RRMS, and PPMS cases. Conclusion: We postulate that elevated PGRN values in the CSF of RIS patients might indicate inflammatory and repair activity prior to axonal disintegration.
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Affiliation(s)
- Marc Pawlitzki
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany.,Department of Neurology with Institute of Translational Neurology, University Hospital of Muenster, Münster, Germany
| | | | - Daniel Bittner
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Anke Lux
- Department for Biometrics and Medical Informatics, Otto-von-Guericke-University, Magdeburg, Germany
| | - Stefan Vielhaber
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Stefanie Schreiber
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Friedemann Paul
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, NeuroCure Clinical Research Center, Berlin, Germany.,Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Jens Neumann
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
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27
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Thouvenot E. Multiple sclerosis biomarkers: Helping the diagnosis? Rev Neurol (Paris) 2018; 174:364-371. [PMID: 29784249 DOI: 10.1016/j.neurol.2018.04.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2018] [Accepted: 04/04/2018] [Indexed: 11/29/2022]
Abstract
Multiple sclerosis (MS) is a complex heterogeneous disease. Diagnostic criteria are based on symptoms, biomarkers, MRI data and exclusion of differential diagnoses. Over the past few years, the usefulness of biomarkers has progressively decreased with the development of new MRI criteria, yet dozens of new biomarkers, especially in cerebrospinal fluid, for MS diagnosis and prognosis have been described. Large-scale studies validating some of these new biomarkers have also provided confirmation of a restricted set of biomarkers (presented here in this review) as having potential value for different stages of the disease, including as early as clinically isolated syndrome and radiologically isolated syndrome. However, differentiating progressive forms of MS from relapsing-remitting MS remains a genuine challenge, and could help to predict future conversion to secondary-progressive MS. In addition, new approaches combining multiple biomarkers might allow us to unravel the complexity of the disease and determine disease stages more precisely. Moreover, recent technological developments allowing analysis of biomarkers in plasma have also provided less invasive analysis of MS, and should serve to predict MS evolution and therapeutic responses during follow-up.
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Affiliation(s)
- E Thouvenot
- Department of neurology, centre hospitalier universitaire Carémeau, 9, place du Pr. Robert Debré, 30029 Nîmes cedex 9, France; Équipe neuroprotéomique et signalisation des maladies neurologiques et psychiatriques, UMR5203, institut de génomique fonctionnelle, université de Montpellier, 141, rue de la Cardonille, 34094 Montpellier c edex 5, France.
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