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Banks SA, Willrich MAV, Eckel-Passow JE, Tobin WO. Cerebrospinal fluid kappa free light chains in patients with tumefactive demyelination. Clin Chem Lab Med 2024; 62:e189-e192. [PMID: 38295388 PMCID: PMC11195019 DOI: 10.1515/cclm-2023-1416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 01/22/2024] [Indexed: 02/02/2024]
Affiliation(s)
- Samantha A. Banks
- Department of Neurology, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Maria Alice V. Willrich
- Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, MN, USA
| | | | - W. Oliver Tobin
- Department of Neurology, Mayo Clinic College of Medicine, Rochester, MN, USA
- Mayo Clinic Center for Multiple Sclerosis and Autoimmune Neurology, Rochester, MN, USA
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2
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Hannich MJ, Konen FF, Gag K, Alkhayer A, Türker SN, Budde K, Nauck M, Wurster U, Dressel A, Skripuletz T, Süße M. Implications of monoclonal gammopathy and isoelectric focusing pattern 5 on the free light chain kappa diagnostics in cerebrospinal fluid. Clin Chem Lab Med 2024; 0:cclm-2023-1468. [PMID: 39039726 DOI: 10.1515/cclm-2023-1468] [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: 12/18/2023] [Accepted: 06/27/2024] [Indexed: 07/24/2024]
Abstract
OBJECTIVES Oligoclonal bands (OCB) analysis is the reference standard for detecting an intrathecal IgG synthesis. Alongside OCB, free light chains kappa (FLCκ) are considered an additional sensitive biomarker for determining patterns 2 or 3, indicating intrathecal Ig synthesis. However, kFLC IF is not suitable for detecting a monoclonal pattern 5. The primary aim of this study was to evaluate the impact of incorporating FLCκ analysis into routine cerebrospinal fluid (CSF) diagnostics instead of OCB testing on the rate of missed monoclonal IgG detection. METHODS A two-center retrospective biomarker study was conducted. OCB were identified using isoelectric focusing in polyacrylamide gels followed by silver staining or in agarose gels followed by immunofixation. FLCκ were quantified using nephelometry and FLCκ assay (Siemens). RESULTS Out of a combined total of 17,755 OCB analyses conducted between 2011 and 2021, a subset of 269 cases (1.5 %) exhibited pattern 5. 98 samples (36 %), which included 18 samples with intrathecal inflammation as determined by additional OCB pattern 2 were included in the FLCκ analysis. Of those, 16 (89 %) had intrathecal FLCκ synthesis. CONCLUSIONS While FLCκ offers a promising avenue for detecting an intrathecal inflammation, the pattern 5, though rare, remains a valuable additional finding of OCB analysis. A combined approach of FLCκ and OCB analysis is recommended for a comprehensive assessment of the humoral intrathecal immune response.
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Affiliation(s)
- Malte J Hannich
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- Department of Internal Medicine B, 221199 University Medicine Greifswald , Greifswald, Germany
| | - Franz F Konen
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Konrad Gag
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Aiham Alkhayer
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Seda N Türker
- Department of Psychiatry, Hannover Medical School, Hannover, Germany
| | - Kathrin Budde
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Ulrich Wurster
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | | | - Thomas Skripuletz
- Department of Internal Medicine B, 221199 University Medicine Greifswald , Greifswald, Germany
| | - Marie Süße
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- Department of Neurology, Hannover Medical School, Hannover, Germany
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3
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De Napoli G, Gastaldi M, Natali P, Bedin R, Simone AM, Santangelo M, Mariotto S, Vitetta F, Smolik K, Cardi M, Meletti S, Ferraro D. Kappa index in the diagnostic work-up of autoimmune encephalitis. J Neurol Sci 2024; 463:123146. [PMID: 39033735 DOI: 10.1016/j.jns.2024.123146] [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: 05/06/2024] [Revised: 07/03/2024] [Accepted: 07/16/2024] [Indexed: 07/23/2024]
Abstract
BACKGROUND The presence of inflammatory changes in the cerebrospinal fluid (CSF), including immunoglobulin intrathecal synthesis (IS), can support the diagnosis of autoimmune encephalitis (AE) and allow prompt treatment. The main aim of our study was to calculate the Kappa index as a marker of IS, in patients with AE. METHODS Charts of patients undergoing a diagnostic work-up for suspected AE between 2009 and 2023 were reviewed and the Graus criteria applied. CSF and serum kappa free light chains were determined using the Freelite assay (The Binding Site Group) and the turbidimetric Optilite analyzer. RESULTS We identified 34 patients with "definite" AE (9 anti-NMDAR AE and 25 limbic AE) and nine patients with "possible" AE. Five patients (15%) with definite AE had pleocytosis and twelve (34%) showed CSF-restricted oligoclonal bands (OCB) at isoelectric focusing. The Kappa index was >6 in 29.4% and > 3 in 50% of the definite AE patients. It was elevated (>3) in 36.4% of patients with definite AE who resulted negative to OCB testing and was the only altered parameter suggestive of an ongoing inflammatory process in the CNS in three definite AE patients with otherwise normal CSF findings (i.e. normal cell count and protein levels, no OCBs). In the possible AE group, one patient had a Kappa index >3 in the absence of OCB. CONCLUSIONS The Kappa index could be useful, as a more sensitive marker of IS and as a supportive marker of neuroinflammation, in the diagnostic work-up of suspected AE.
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Affiliation(s)
- Giulia De Napoli
- Department of Biomedical, Metabolic and Neurosciences, University of Modena and Reggio Emilia, Modena, Italy; Department of Neurosciences, Ospedale Civile di Baggiovara, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy
| | - Matteo Gastaldi
- Neuroimmunology Laboratory, IRCCS Mondino Foundation, Pavia, Italy
| | - Patrizia Natali
- Department of Laboratory Medicine, Azienda Ospedaliero-Universitaria and Azienda Unità Sanitaria Locale, Ospedale Civile di Baggiovara, Modena, Italy
| | - Roberta Bedin
- Department of Biomedical, Metabolic and Neurosciences, University of Modena and Reggio Emilia, Modena, Italy
| | | | | | - Sara Mariotto
- Neurology Unit, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Francesca Vitetta
- Department of Neurosciences, Ospedale Civile di Baggiovara, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy
| | - Krzysztof Smolik
- Department of Biomedical, Metabolic and Neurosciences, University of Modena and Reggio Emilia, Modena, Italy; Department of Neurosciences, Ospedale Civile di Baggiovara, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy
| | - Martina Cardi
- Department of Biomedical, Metabolic and Neurosciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Stefano Meletti
- Department of Biomedical, Metabolic and Neurosciences, University of Modena and Reggio Emilia, Modena, Italy; Department of Neurosciences, Ospedale Civile di Baggiovara, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy
| | - Diana Ferraro
- Department of Biomedical, Metabolic and Neurosciences, University of Modena and Reggio Emilia, Modena, Italy; Department of Neurosciences, Ospedale Civile di Baggiovara, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy.
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Prathapan V, Eipert P, Wigger N, Kipp M, Appali R, Schmitt O. Modeling and simulation for prediction of multiple sclerosis progression. Comput Biol Med 2024; 175:108416. [PMID: 38657465 DOI: 10.1016/j.compbiomed.2024.108416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 03/28/2024] [Accepted: 04/03/2024] [Indexed: 04/26/2024]
Abstract
In light of extensive work that has created a wide range of techniques for predicting the course of multiple sclerosis (MS) disease, this paper attempts to provide an overview of these approaches and put forth an alternative way to predict the disease progression. For this purpose, the existing methods for estimating and predicting the course of the disease have been categorized into clinical, radiological, biological, and computational or artificial intelligence-based markers. Weighing the weaknesses and strengths of these prognostic groups is a profound method that is yet in need and works directly at the level of diseased connectivity. Therefore, we propose using the computational models in combination with established connectomes as a predictive tool for MS disease trajectories. The fundamental conduction-based Hodgkin-Huxley model emerged as promising from examining these studies. The advantage of the Hodgkin-Huxley model is that certain properties of connectomes, such as neuronal connection weights, spatial distances, and adjustments of signal transmission rates, can be taken into account. It is precisely these properties that are particularly altered in MS and that have strong implications for processing, transmission, and interactions of neuronal signaling patterns. The Hodgkin-Huxley (HH) equations as a point-neuron model are used for signal propagation inside a small network. The objective is to change the conduction parameter of the neuron model, replicate the changes in myelin properties in MS and observe the dynamics of the signal propagation across the network. The model is initially validated for different lengths, conduction values, and connection weights through three nodal connections. Later, these individual factors are incorporated into a small network and simulated to mimic the condition of MS. The signal propagation pattern is observed after inducing changes in conduction parameters at certain nodes in the network and compared against a control model pattern obtained before the changes are applied to the network. The signal propagation pattern varies as expected by adapting to the input conditions. Similarly, when the model is applied to a connectome, the pattern changes could give an insight into disease progression. This approach has opened up a new path to explore the progression of the disease in MS. The work is in its preliminary state, but with a future vision to apply this method in a connectome, providing a better clinical tool.
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Affiliation(s)
- Vishnu Prathapan
- Medical School Hamburg University of Applied Sciences and Medical University, Am Kaiserkai 1, 20457, Hamburg, Germany.
| | - Peter Eipert
- Medical School Hamburg University of Applied Sciences and Medical University, Am Kaiserkai 1, 20457, Hamburg, Germany.
| | - Nicole Wigger
- Department of Anatomy, University of Rostock Gertrudenstr 9, 18057, Rostock, Germany.
| | - Markus Kipp
- Department of Anatomy, University of Rostock Gertrudenstr 9, 18057, Rostock, Germany.
| | - Revathi Appali
- Institute of General Electrical Engineering, University of Rostock, Albert-Einstein-Straße 2, 18059, Rostock, Germany; Department of Aging of Individuals and Society, Interdisciplinary Faculty, University of Rostock, Universitätsplatz 1, 18055, Rostock, Germany.
| | - Oliver Schmitt
- Medical School Hamburg University of Applied Sciences and Medical University, Am Kaiserkai 1, 20457, Hamburg, Germany; Department of Anatomy, University of Rostock Gertrudenstr 9, 18057, Rostock, Germany.
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Maglio G, D’Agostino M, Caronte FP, Pezone L, Casamassimi A, Rienzo M, Di Zazzo E, Nappo C, Medici N, Molinari AM, Abbondanza C. Multiple Sclerosis: From the Application of Oligoclonal Bands to Novel Potential Biomarkers. Int J Mol Sci 2024; 25:5412. [PMID: 38791450 PMCID: PMC11121866 DOI: 10.3390/ijms25105412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 05/10/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024] Open
Abstract
Multiple sclerosis is a chronic immune-mediated disorder of the central nervous system with a high heterogeneity among patients. In the clinical setting, one of the main challenges is a proper and early diagnosis for the prediction of disease activity. Current diagnosis is based on the integration of clinical, imaging, and laboratory results, with the latter based on the presence of intrathecal IgG oligoclonal bands in the cerebrospinal fluid whose detection via isoelectric focusing followed by immunoblotting represents the gold standard. Intrathecal synthesis can also be evidenced by the measurement of kappa free light chains in the cerebrospinal fluid, which has reached similar diagnostic accuracy compared to that of oligoclonal bands in the identification of patients with multiple sclerosis; moreover, recent studies have also highlighted its value for early disease activity prediction. This strategy has significant advantages as compared to using oligoclonal band detection, even though some issues remain open. Here, we discuss the current methods applied for cerebrospinal fluid analysis to achieve the most accurate diagnosis and for follow-up and prognosis evaluation. In addition, we describe new promising biomarkers, currently under investigation, that could contribute both to a better diagnosis of multiple sclerosis and to its monitoring of the therapeutic treatment response.
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Affiliation(s)
- Grazia Maglio
- Unit of Clinical and Molecular Pathology, A.O.U. University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (G.M.); (M.D.); (F.P.C.); (L.P.); (C.N.); (N.M.); (A.M.M.)
| | - Marina D’Agostino
- Unit of Clinical and Molecular Pathology, A.O.U. University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (G.M.); (M.D.); (F.P.C.); (L.P.); (C.N.); (N.M.); (A.M.M.)
| | - Francesco Pio Caronte
- Unit of Clinical and Molecular Pathology, A.O.U. University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (G.M.); (M.D.); (F.P.C.); (L.P.); (C.N.); (N.M.); (A.M.M.)
| | - Luciano Pezone
- Unit of Clinical and Molecular Pathology, A.O.U. University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (G.M.); (M.D.); (F.P.C.); (L.P.); (C.N.); (N.M.); (A.M.M.)
| | - Amelia Casamassimi
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy
| | - Monica Rienzo
- Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, University of Campania “Luigi Vanvitelli”, 81100 Caserta, Italy;
| | - Erika Di Zazzo
- Department of Medicine and Health Sciences “V. Tiberio”, University of Molise, 86100 Campobasso, Italy;
| | - Carmela Nappo
- Unit of Clinical and Molecular Pathology, A.O.U. University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (G.M.); (M.D.); (F.P.C.); (L.P.); (C.N.); (N.M.); (A.M.M.)
| | - Nicola Medici
- Unit of Clinical and Molecular Pathology, A.O.U. University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (G.M.); (M.D.); (F.P.C.); (L.P.); (C.N.); (N.M.); (A.M.M.)
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy
| | - Anna Maria Molinari
- Unit of Clinical and Molecular Pathology, A.O.U. University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (G.M.); (M.D.); (F.P.C.); (L.P.); (C.N.); (N.M.); (A.M.M.)
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy
| | - Ciro Abbondanza
- Unit of Clinical and Molecular Pathology, A.O.U. University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (G.M.); (M.D.); (F.P.C.); (L.P.); (C.N.); (N.M.); (A.M.M.)
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy
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Dekeyser C, De Kesel P, Cambron M, Vanopdenbosch L, Van Hijfte L, Vercammen M, Laureys G. Inter-assay diagnostic accuracy of cerebrospinal fluid kappa free light chains for the diagnosis of multiple sclerosis. Front Immunol 2024; 15:1385231. [PMID: 38745673 PMCID: PMC11091388 DOI: 10.3389/fimmu.2024.1385231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 04/12/2024] [Indexed: 05/16/2024] Open
Abstract
Background Cerebrospinal fluid (CSF) kappa free light chain (κFLC) measures gained increasing interest as diagnostic markers in multiple sclerosis (MS). However, the lack of studies comparing assay-dependent diagnostic cutoff values hinders their use in clinical practice. Additionally, the optimal κFLC parameter for identifying MS remains a subject of ongoing debate. Objectives The aim of this study was to compare same-sample diagnostic accuracies of the κFLC index, κIgG index, CSF κFLC/IgG ratio, and isolated CSF κFLC (iCSF-κFLC) between two reference centers using different methods. Methods Paired serum and CSF samples were analyzed for κFLC and albumin concentrations by Freelite®-Optilite (Sint-Jan Bruges hospital) and N Latex®-BNII (Ghent University hospital). Diagnostic performance to differentiate MS from controls was assessed using ROC curve analysis. Results A total of 263 participants were included (MS, n = 80). Optimal diagnostic cutoff values for the κFLC index (Freelite®-Optilite: 7.7; N Latex®-BNII: 4.71), κIgG index (Freelite®-Optilite: 14.15, N Latex®-BNII: 12.19), and CSF κFLC/IgG ratio (Freelite®-Optilite: 2.27; N Latex®-BNII: 1.44) differed between the two methods. Sensitivities related to optimal cutoff values were 89.9% (Freelite®-Optilite) versus 94.6% (N Latex®-BNII) for the κFLC index, 91% (Freelite®-Optilite) versus 92.2% (N Latex®-BNII) for the κIgG index, and 81.3% (Freelite®-Optilite) versus 91.4% (N Latex®-BNII) for the CSF κFLC/IgG ratio. However, for iCSF-κFLC, optimal diagnostic cutoff values (0.36 mg/L) and related specificities (81.8%) were identical with a related diagnostic sensitivity of 89.9% for Freelite®-Optilite and 90.5% for N Latex®-BNII. The diagnostic performance of the κFLC index [area under the curve (AUC) Freelite®-Optilite: 0.924; N Latex®-BNII: 0.962] and κIgG index (AUC Freelite®-Optilite: 0.929; N Latex®-BNII: 0.961) was superior compared to CSF oligoclonal bands (AUC: 0.898, sensitivity: 83.8%, specificity: 95.9%). Conclusions The κFLC index and the κIgG index seem to be excellent markers for identifying MS, irrespective of the method used for κFLC quantification. Based on the AUC, they appear to be the measures of choice. For all measures, optimal cutoff values differed between methods except for iCSF-κFLC. iCSF-κFLC might therefore serve as a method-independent, more cost-efficient, initial screening measure for MS. These findings are particularly relevant for clinical practice given the potential future implementation of intrathecal κFLC synthesis in MS diagnostic criteria and for future multicentre studies pooling data on κFLC measures.
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Affiliation(s)
| | - Pieter De Kesel
- Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Melissa Cambron
- Department of Neurology, AZ Sint-Jan Brugge, Bruges, Belgium
- Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | | | | | - Martine Vercammen
- Department of Laboratory Medicine, Algemeen Ziekenhuis (AZ) Sint-Jan Brugge, Bruges, Belgium
- Basic Biomedical Sciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Guy Laureys
- Department of Neurology, Ghent University Hospital, Ghent, Belgium
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Hagberg L, Rosenstein I, Lycke J, Zetterberg H, Yilmaz A, Edén A, Gisslén M. IgG and kappa free light chain CSF/serum indices: evaluating intrathecal immunoglobulin production in HIV infection in comparison with multiple sclerosis. Clin Chem Lab Med 2024; 0:cclm-2023-1018. [PMID: 38564810 DOI: 10.1515/cclm-2023-1018] [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: 09/12/2023] [Accepted: 03/08/2024] [Indexed: 04/04/2024]
Abstract
OBJECTIVES To study intrathecal kappa free light chain (KFLC) synthesis in people living with HIV (PLWH) in comparison with multiple sclerosis (MS). METHODS Cross-sectional analysis including 56 untreated and 150 well treated PLWH, and compared with 58 controls, and 223 MS patients. RESULTS Elevated serum/cerebrospinal fluid (CSF) IgG and KFLC indices were observed in untreated PLWH. Seventy percent of untreated PLWH had KFLC index above 6.1, a threshold associated with clinically isolated syndrome/MS diagnosis. No association was found between KFCL index and CSF markers of neuronal injury in either PLWH or MS patients. CONCLUSIONS HIV-related immune system dysfunction is often associated with an elevated KFLC index akin to those observed in MS. HIV infection should be considered as a differential diagnosis for patients presenting with neurological symptoms and increased intrathecal immunoglobulin synthesis.
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Affiliation(s)
- Lars Hagberg
- Department of Infectious Diseases, 70712 Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg , Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Igal Rosenstein
- Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Clinical Neuroscience, 70712 Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg , Gothenburg, Sweden
| | - Jan Lycke
- Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Clinical Neuroscience, 70712 Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg , Gothenburg, Sweden
| | - Henrik Zetterberg
- Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Aylin Yilmaz
- Department of Infectious Diseases, 70712 Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg , Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Arvid Edén
- Department of Infectious Diseases, 70712 Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg , Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Magnus Gisslén
- Department of Infectious Diseases, 70712 Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg , Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
- Public Health Agency of Sweden, Solna, Sweden
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Bauer A, Hegen H, Reindl M. Body fluid markers for multiple sclerosis and differential diagnosis from atypical demyelinating disorders. Expert Rev Mol Diagn 2024; 24:283-297. [PMID: 38533708 DOI: 10.1080/14737159.2024.2334849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 03/21/2024] [Indexed: 03/28/2024]
Abstract
INTRODUCTION Body fluid markers could be helpful to predict the conversion into clinically definite multiple sclerosis (MS) in people with a first demyelinating event of the central nervous system (CNS). Consequently, biomarkers such as oligoclonal bands, which are integrated in the current MS diagnostic criteria, could assist early MS diagnosis. AREAS COVERED This review examines existing knowledge on a broad spectrum of body fluid markers in people with a first CNS demyelinating event, explores their potential to predict conversion to MS, to assess MS disease activity, as well as their utility to differentiate MS from atypical demyelinating disorders such as neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein associated disease. EXPERT OPINION This field of research has shown a dramatic increase of evidence, especially in the last decade. Some biomarkers are already established in clinical routine (e.g. oligoclonal bands) while others are currently implemented (e.g. kappa free light chains) or considered as breakthroughs (e.g. neurofilament light). Determination of biomarkers poses challenges for continuous monitoring, especially if exclusively detectable in cerebrospinal fluid. A handful of biomarkers are measurable in blood which holds a significant potential.
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Affiliation(s)
- Angelika Bauer
- Clinical Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
- Institute of Hygiene and Medical Microbiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Harald Hegen
- Clinical Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Markus Reindl
- Clinical Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
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Domingues RB, Santos MVD, Salomão D, Senne C. Concordance rate between oligoclonal bands and the Kappa index in patients with suspected multiple sclerosis (MS). ARQUIVOS DE NEURO-PSIQUIATRIA 2024; 82:1-5. [PMID: 38485255 PMCID: PMC10940114 DOI: 10.1055/s-0044-1779690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 12/25/2023] [Indexed: 03/17/2024]
Abstract
BACKGROUND Oligoclonal bands (OCBs) and Kappa free light chains (FLCs) in the cerebrospinal fluid (CSF) are sensitive markers of intrathecal immunoglobulin (Ig)G synthesis in patients with multiple sclerosis. OBJECTIVE To evaluate the concordance rate between OCBCs and the Kappa index (KI) in patients with suspected multiple sclerosis (MS). METHODS Patients with suspected MS were referred to a specialized CSF laboratory as part of their diagnostic investigation. Paired CSF and serum samples were collected and submitted to detection of OCBs and determination of the KI. Positive and negative results were determined with both methods, and the percentage of agreement between them was established. RESULTS In total, 171 serum and CSF samples from 171 patients were included in the analysis. The mean age of the patients was of 40 ± 14.2 years; 18.9% of them were male, and 81.1% were female. The OCBs and KI presented concordant results in 161 (94.2%) samples: in 74 (43.3%), both were positive, and in 87 (50.9%), both were negative. In 10 cases, the results were discrepant: KI positive/OCB negative in 8 and OCB positive/KI negative in 2 cases. CONCLUSION The KI and OCBs presented high concordance level. Currently, the detection of OCBs in the CSF is the standard method for MS diagnosis, but it is time-consuming, and its visual interpretation can be difficult. The results suggest that the KI is a good alternative for the detection of intrathecal immunoproduction in cases of suspected MS.
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Miklušová M, Fürst T, Zimek D, Mareš J. Prognostic value of cerebrospinal fluid biomarkers in multiple sclerosis: The key role of kappa free light chains and a multivariate predictor for disease progression. Mult Scler Relat Disord 2024; 82:105402. [PMID: 38160638 DOI: 10.1016/j.msard.2023.105402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 12/14/2023] [Accepted: 12/21/2023] [Indexed: 01/03/2024]
Abstract
OBJECTIVE Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating disease of the central nervous system with varying progression rates among individuals. The ability to predict disease progression is crucial for treatment decisions with disease-modifying therapies (DMTs). A few cerebrospinal fluid (CSF) biomarkers have been investigated in relation to disease progression, but few have been effectively translated into clinical practice. The aim of this study was to evaluate the diagnostic and prognostic value of known CSF markers, to compare their sensitivity and specificity, and to develop a prognostic model using a combination of markers to predict disease progression. METHODS This retrospective cohort study included 82 patients with a first episode of inflammatory demyelinating symptoms suggestive of MS between January 2018 and January 2021. Patients underwent diagnostic lumbar puncture and other investigations according to the multiple sclerosis (MS) protocol. They were divided into three groups according to MRI findings, relapse rate and EDSS score. CSF marker concentrations were determined by laser nephelometry and electrochemiluminescence immunoassay. RESULTS The results showed that the number of oligoclonal bands could discriminate the progression-free group from the other groups, but had a lower discriminatory power compared to CSF marker concentrations. Among CSF markers, FLC kappa showed the best discriminatory performance. By combining FLC kappa with gender and lesion localization information, a simple predictor of progression-free group membership was proposed. This predictor showed good sensitivity (91 %) and specificity (65 %). CONCLUSION In conclusion, CSF FLC kappa concentration, together with gender and lesion localization, may be a valuable predictor of disease progression in MS patients. This study highlights the potential of using CSF biomarkers for prognostic purposes and offers a simple approach to predicting disease progression.
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Affiliation(s)
- Martina Miklušová
- Faculty of Medicine and Dentistry, Palacky University Olomouc, Czech Republic; University Hospital Olomouc Department of Neurology, Olomouc, Czechia.
| | - Tomáš Fürst
- Department of Mathematical Analysis and Applications of Mathematics, Faculty of Science, Palacky University Olomouc, Czech Republic
| | - Dalibor Zimek
- Faculty of Medicine and Dentistry, Palacky University Olomouc, Czech Republic; University Hospital Olomouc Department of Neurology, Olomouc, Czechia
| | - Jan Mareš
- Faculty of Medicine and Dentistry, Palacky University Olomouc, Czech Republic; University Hospital Olomouc Department of Neurology, Olomouc, Czechia
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11
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Luigetti M, Primiano G, Basile V, Vitali F, Pignalosa S, Romano A, Sabino A, Marino M, Di Santo R, Ciasca G, Basile U. Serum Neurofilament and Free Light Chain Levels in Patients Undergoing Treatment for Chronic Inflammatory Demyelinating Polyneuropathy. Int J Mol Sci 2024; 25:1254. [PMID: 38279256 PMCID: PMC10816730 DOI: 10.3390/ijms25021254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 01/10/2024] [Accepted: 01/12/2024] [Indexed: 01/28/2024] Open
Abstract
Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is an immune-mediated disorder affecting the peripheral nervous system. Despite the established diagnostic criteria, monitoring disease activity and treatment remains challenging. To address this limitation, we investigated serum neurofilament light chain (sNfL) and serum free light chains (sFLCs) as potential biomarkers. A total of 32 CIDP patients undergoing immunoglobulin therapy and 32 healthy controls enrolled in the present study, and agreed to have their blood plasma sNfL and sFLCs analyzed, while CIDP severity was assessed through the modified Rankin Scale (mRS) and the Overall Neuropathy Limitations Scale (ONLS). In line with the immunoglobulin treatment aimed at limiting neuronal damage administered to the majority of patients, sNfL levels did not exhibit significant differences between the two groups. However, CIDP patients showed significantly elevated sFLC and sFLC ratios, while the marker levels did not correlate with the clinical scores. The study confirms the potential of sFLCs as a sensitive biomarker of inflammatory processes in CIDP. Additionally, the present study results regarding neurofilaments strengthen the role of sNfL in monitoring CIDP treatments, confirming the effectiveness of immunoglobulin therapy. Overall, our results demonstrate how combining these markers can lead to better patient characterization for improved treatment.
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Affiliation(s)
- Marco Luigetti
- Dipartimento di Neuroscienze, Organi di Senso e Torace, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy; (M.L.); (A.R.)
- Dipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; (F.V.); (A.S.)
| | - Guido Primiano
- Dipartimento di Neuroscienze, Organi di Senso e Torace, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy; (M.L.); (A.R.)
- Dipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; (F.V.); (A.S.)
- Fondazione UILDM Lazio Onlus, 00167 Rome, Italy
| | - Valerio Basile
- Clinical Pathology Unit and Cancer Biobank, Department of Research and Advanced Technologies, I.R.C.C.S. Regina Elena National Cancer Institute, 00144 Rome, Italy;
| | - Francesca Vitali
- Dipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; (F.V.); (A.S.)
| | - Stefano Pignalosa
- Dipartimento di Patologia Clinica, Ospedale Santa Maria Goretti, A.U.S.L. Latina, 04100 Latina, Italy; (S.P.); (U.B.)
| | - Angela Romano
- Dipartimento di Neuroscienze, Organi di Senso e Torace, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy; (M.L.); (A.R.)
| | - Andrea Sabino
- Dipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; (F.V.); (A.S.)
| | - Mariapaola Marino
- Sezione di Patologia Generale, Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, 00168 Rome, Italy;
- Fondazione Policlinico Universitario “A. Gemelli” I.R.C.C.S., 00168 Rome, Italy; (R.D.S.); (G.C.)
| | - Riccardo Di Santo
- Fondazione Policlinico Universitario “A. Gemelli” I.R.C.C.S., 00168 Rome, Italy; (R.D.S.); (G.C.)
- Sezione di Fisica, Dipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Gabriele Ciasca
- Fondazione Policlinico Universitario “A. Gemelli” I.R.C.C.S., 00168 Rome, Italy; (R.D.S.); (G.C.)
- Sezione di Fisica, Dipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Umberto Basile
- Dipartimento di Patologia Clinica, Ospedale Santa Maria Goretti, A.U.S.L. Latina, 04100 Latina, Italy; (S.P.); (U.B.)
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12
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Hegen H, Berek K, Cavalla P, Christiansen M, Emeršič A, Di Filippo M, Gaetani L, Hassler M, Leurs C, Milosavljevic D, van Pesch V, Petersen T, Presslauer S, Rosenstein I, Rot U, Schnabl C, Teunissen C, Vecchio D, Vercellino M, Deisenhammer F. Diagnostic value of kappa free light chain index in patients with primary progressive multiple sclerosis - a multicentre study. Front Immunol 2023; 14:1327947. [PMID: 38169789 PMCID: PMC10758426 DOI: 10.3389/fimmu.2023.1327947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024] Open
Abstract
Background Kappa free light chains (κ-FLC) in the cerebrospinal fluid (CSF) are an emerging biomarker in multiple sclerosis (MS). Objective To investigate whether κ-FLC index has similar diagnostic value in patients with primary progressive multiple sclerosis (PPMS) compared to oligoclonal bands (OCB). Methods Patients with PPMS were recruited through 11 MS centres across 7 countries. κ-FLC were measured by immunonephelometry/-turbidimetry. OCB were determined by isoelectric focusing and immunofixation. Results A total of 174 patients (mean age of 52±11 years, 51% males) were included. κ-FLC index using a cut-off of 6.1 was positive in 161 (93%) and OCB in 153 (88%) patients. Conclusion κ-FLC index shows similar diagnostic sensitivity than OCB in PPMS.
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Affiliation(s)
- Harald Hegen
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Klaus Berek
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Paola Cavalla
- Multiple Sclerosis Center and Neurologia I U, Department of Neuroscience and Mental Health, AOU Città della Salute e della Scienza di Torino, Torino, Italy
| | - Mikael Christiansen
- Department of Clinical Biochemistry, Regional Hospital in Horsens, Horsens, Denmark
| | - Andreja Emeršič
- Department of Neurology, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Massimiliano Di Filippo
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Lorenzo Gaetani
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | | | - Cyra Leurs
- Department of Neurology and Neurophysiology, Amsterdam Neuroscience, Amsterdam UMC, Location VUMC, Amsterdam, Netherlands
| | | | | | - Thor Petersen
- Sygehus Sønderjylland, Department of Regional Health Research, University Hospital of Southern Denmark, Hadersleben, Denmark
| | | | - Igal Rosenstein
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Uroš Rot
- Department of Neurology, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | | | - Charlotte Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam UMC, Location Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Domizia Vecchio
- Neurology Unit Department of Translational Medicine, Maggiore della Carità University Hospital, Novara, Italy
| | - Marco Vercellino
- Multiple Sclerosis Center and Neurologia I U, Department of Neuroscience and Mental Health, AOU Città della Salute e della Scienza di Torino, Torino, Italy
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13
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Toscano S, Chisari CG, Lo Fermo S, Gulino G, Zappia M, Patti F. A dynamic interpretation of κFLC index for the diagnosis of multiple sclerosis: a change of perspective. J Neurol 2023; 270:6010-6020. [PMID: 37639016 PMCID: PMC10632300 DOI: 10.1007/s00415-023-11952-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 08/16/2023] [Accepted: 08/17/2023] [Indexed: 08/29/2023]
Abstract
BACKGROUND Previous studies attempted to define the best threshold for κ free light chains (κFLC) index, confirming higher sensitivity (Se) but less specificity (Sp) compared with IgG oligoclonal bands (OCB) for the diagnosis of MS. OBJECTIVE To evaluate the diagnostic accuracy of different κFLC index intervals in a miscellaneous cohort of neurological patients, proposing a procedural flowchart for MS diagnosis. METHODS We analyzed data from 607 patients diagnosed with MS (179), CIS (116), other inflammatory (94) or non-inflammatory neurological diseases (218). Measures of diagnostic accuracy were reported for different potential thresholds of κFLC index, and for IgG OCB and IgG index. Binary logistic regression was to used to calculate the odds of being diagnosed with MS based on each increase of κFLC index. RESULTS CSF IgG OCB showed 72.2% Se (CI 95% 68.4-75.7) and 95.2% Sp (CI 95% 93.1-96.7) in discriminating between MS/CIS and controls, with an AUC of 0.84 (CI 95% 0.80-0.87). The highest diagnostic accuracy was reported for κFLC index cut-off of 5.0 (Se = 85.4%, Sp = 90.4%, AUC = 0.88), while a threshold of 11.0 exhibited higher Sp (95.5%, 95% CI 93.1-97.1) than IgG OCB. AUCs for all thresholds between 4.25 and 6.6 were not significantly different from each other, but were significantly higher than the AUC of IgG OCB (p < 0.05). The odds of being diagnosed with MS/CIS increased by 17.1% for each unit increase of κFLC index (OR = 1.17; 95% CI 1.12-1.23; p < 0.001). CONCLUSION κFLC index performed better than CSF IgG OCB in supporting the diagnosis of MS/CIS, with the advantage of being a cost-effective and quantitative analysis.
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Affiliation(s)
- Simona Toscano
- Department of Biomedical and Biotechnological Sciences, University of Catania, Via Santa Sofia 97, 95123, Catania, Italy
- Multiple Sclerosis Unit, University-Hospital G. Rodolico-San Marco, Via Santa Sofia 78, 95123, Catania, Italy
| | - Clara Grazia Chisari
- Multiple Sclerosis Unit, University-Hospital G. Rodolico-San Marco, Via Santa Sofia 78, 95123, Catania, Italy
- Department "GF Ingrassia", Section Neuroscience, University of Catania, Via Santa Sofia 87, 95123, Catania, Italy
| | - Salvatore Lo Fermo
- Multiple Sclerosis Unit, University-Hospital G. Rodolico-San Marco, Via Santa Sofia 78, 95123, Catania, Italy
- Department "GF Ingrassia", Section Neuroscience, University of Catania, Via Santa Sofia 87, 95123, Catania, Italy
| | - Giuseppa Gulino
- Central Laboratory, A.O.U. Policlinico-San Marco, Via Santa Sofia 78, 95123, Catania, Italy
| | - Mario Zappia
- Department "GF Ingrassia", Section Neuroscience, University of Catania, Via Santa Sofia 87, 95123, Catania, Italy
| | - Francesco Patti
- Multiple Sclerosis Unit, University-Hospital G. Rodolico-San Marco, Via Santa Sofia 78, 95123, Catania, Italy.
- Department "GF Ingrassia", Section Neuroscience, University of Catania, Via Santa Sofia 87, 95123, Catania, Italy.
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14
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Židó M, Kačer D, Valeš K, Zimová D, Štětkářová I. Metabolomics of Cerebrospinal Fluid Amino and Fatty Acids in Early Stages of Multiple Sclerosis. Int J Mol Sci 2023; 24:16271. [PMID: 38003464 PMCID: PMC10671192 DOI: 10.3390/ijms242216271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 11/07/2023] [Accepted: 11/08/2023] [Indexed: 11/26/2023] Open
Abstract
Multiple sclerosis (MS) is a demyelinating and neurodegenerative autoimmune disease of the central nervous system (CNS) damaging myelin and axons. Diagnosis is based on the combination of clinical findings, magnetic resonance imaging (MRI) and analysis of cerebrospinal fluid (CSF). Metabolomics is a systematic study that allows us to track amounts of different metabolites in a chosen medium. The aim of this study was to establish metabolomic differences between the cerebrospinal fluid of patients in the early stages of multiple sclerosis and healthy controls, which could potentially serve as markers for predicting disease activity. We collected CSF from 40 patients after the first attack of clinical symptoms who fulfilled revised McDonald criteria of MS, and the CSF of 33 controls. Analyses of CSF samples were performed by using the high-performance liquid chromatography system coupled with a mass spectrometer with a high-resolution detector. Significant changes in concentrations of arginine, histidine, spermidine, glutamate, choline, tyrosine, serine, oleic acid, stearic acid and linoleic acid were observed. More prominently, Expanded Disability Status Scale values significantly correlated with lower concentrations of histidine. We conclude that these metabolites could potentially play a role as a biomarker of disease activity and predict presumable inflammatory changes.
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Affiliation(s)
- Michal Židó
- Department of Neurology, Third Faculty of Medicine, Charles University, 100 00 Prague, Czech Republic;
- Department of Neurology, Faculty Hospital Královské Vinohrady, 100 34 Prague, Czech Republic;
| | - David Kačer
- National Institute of Mental Health, 250 67 Klecany, Czech Republic; (D.K.); (K.V.)
| | - Karel Valeš
- National Institute of Mental Health, 250 67 Klecany, Czech Republic; (D.K.); (K.V.)
- Department of Psychiatry and Medical Psychology, Third Faculty of Medicine, Charles University, 100 00 Prague, Czech Republic
| | - Denisa Zimová
- Department of Neurology, Faculty Hospital Královské Vinohrady, 100 34 Prague, Czech Republic;
| | - Ivana Štětkářová
- Department of Neurology, Third Faculty of Medicine, Charles University, 100 00 Prague, Czech Republic;
- Department of Neurology, Faculty Hospital Královské Vinohrady, 100 34 Prague, Czech Republic;
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15
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Tortosa-Carreres J, Quiroga-Varela A, Castillo-Villalba J, Piqueras-Rodríguez M, Ramió-Torrenta L, Cubas-Núñez L, Gasqué-Rubio R, Quintanilla-Bordas C, Huertas-Pons JM, Miguela A, Casanova B, Laiz-Marro B, Pérez-Miralles FC. Improving the efficiency of free kappa light chains as diagnostic biomarker of Multiple Sclerosis by using a novel algorithm. Mult Scler Relat Disord 2023; 79:104997. [PMID: 37714099 DOI: 10.1016/j.msard.2023.104997] [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: 08/01/2023] [Revised: 08/21/2023] [Accepted: 09/04/2023] [Indexed: 09/17/2023]
Abstract
BACKGROUND Intrathecal immunoglobulin synthesis (ITS) plays a crucial role in the diagnosis of multiple sclerosis (MS). Traditionally, the gold standard method for detecting ITS has been through the analysis of oligoclonal bands (OCB). However, the paradigm has shifted with the introduction of the free kappa light chains (FKLC) method. In fact, a recent consensus recommends evaluating FKLC index (FKLCi) as the primary approach and reserving oligoclonal bands with borderline results. The objective of our study is to investigate the diagnostic efficiency of combining FKLC with other methods to predict ITS while minimizing the reliance on OCB. METHODS A total of 192 patients were included in the study, consisting of 145 individuals diagnosed with multiple sclerosis (pwMS) and 46 with other neurological diseases (controls). Among the MS cases, 100 patients were assigned to the Training Cohort (TC), while an external Validation Cohort (VC) comprised of 45 MS patients was established. Diagnostic efficiency was assessed for FKLCi, OCB, Link index, and the Reiber formula for IgG and FKLC. Optimal cutoff values for Link index and FKLCi were also determined. The last procedure was developed for diverse algorithms using the parameters mentioned above, which included the optimal cutoffs previously obtained. The calculations were conducted independently for both the TC and the VC, as well as for a composite cohort formed by combining data from all patients (OC) RESULTS: One algorithm, named KRO, was developed based on the determination of FKLCi and Reiber Formula as the primary diagnostic parameters. For cases where the FKLCi result was mildly increased, OCB was utilized as a supplementary test. The KRO algorithm demonstrated superior diagnostic accuracy in the OC (89%), resulting in a reduction of OCB consumption by 91%. DISCUSSION The KRO algorithm demonstrated superior sensitivity and accuracy although lower specificity and NPV compared to the use of FKLCi and OCB alone. The present research aligns with the new consensus recommendations regarding the diagnostic approach. Our findings indicate that employing a combined marker approach via KRO could prove to be a proficient screening tool for multiple sclerosis. This approach also holds the potential to address inherent limitations associated with each individual marker. However, to further validate and solidify the efficacy of our algorithm, additional studies involving larger cohorts are warranted.
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Affiliation(s)
- Jordi Tortosa-Carreres
- Laboratory Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain; Medicine Department, University of Valencia, Valencia 46010, Spain.
| | - Anna Quiroga-Varela
- Neurodegeneration and Neuroinflammation Research Group, Girona Biomedical Research Institute (IDIBGI), Girona, Spain
| | - Jessica Castillo-Villalba
- Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España; Medicine Department, University of Valencia, Valencia 46010, Spain
| | - Mónica Piqueras-Rodríguez
- Laboratory Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain; Medicine Department, University of Valencia, Valencia 46010, Spain
| | - Lluís Ramió-Torrenta
- Girona Neuroimmumology and Multiple Sclerosis Unit, Neurology Department, Dr. Josep Trueta University Hospital and Santa Caterina Hospital, Girona, Spain; Neurodegeneration and Neuroinflammation Research Group, Girona Biomedical Research Institute (IDIBGI), Girona, Spain; Medical Sciences Department, University of Girona, Girona, Spain
| | - Laura Cubas-Núñez
- Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España
| | - Raquel Gasqué-Rubio
- Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España; Medicine Department, University of Valencia, Valencia 46010, Spain
| | - Carlos Quintanilla-Bordas
- Neurology Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain; Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España
| | - Joana María Huertas-Pons
- Neurodegeneration and Neuroinflammation Research Group, Girona Biomedical Research Institute (IDIBGI), Girona, Spain
| | - Albert Miguela
- Neurodegeneration and Neuroinflammation Research Group, Girona Biomedical Research Institute (IDIBGI), Girona, Spain
| | - Bonaventura Casanova
- Neurology Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain; Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España
| | - Begoña Laiz-Marro
- Laboratory Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain
| | - Francisco Carlos Pérez-Miralles
- Neurology Department, La Fe University and Polytechnic Hospital, Valencia 46026, Spain; Grupo de investigación en Neuroinmunología, Instituto de Investigación Sanitaria La Fe (IISLAFE), Valencia, España
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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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17
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Arroyo-Pereiro P, García-Serrano L, Morandeira F, Urban B, Mas V, Framil M, León I, Muñoz-Vendrell A, Matas E, Romero-Pinel L, Martínez-Yélamos A, Martínez-Yélamos S, Bau L. Kappa free light chains index in multiple sclerosis very long-term prognosis. Front Immunol 2023; 14:1223514. [PMID: 37885887 PMCID: PMC10598843 DOI: 10.3389/fimmu.2023.1223514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 09/11/2023] [Indexed: 10/28/2023] Open
Abstract
Introduction The role of the kappa-free light chain (kFLC) in the diagnosis of multiple sclerosis (MS) and, to a lesser extent, its role as a medium-term prognostic marker have been extensively studied. This study aimed to explore its potential as a long-term prognostic marker for MS. Methods We performed an exploratory retrospective observational study by selecting patients systemically followed up in our MS unit with available cerebrospinal fluid and serum samples at the time of initial evaluation. Two groups were defined: benign MS (bMS), defined as patients with Expanded Disability Status Scale (EDSS) ≤ 3 at 10 years of follow-up, and aggressive MS (aMS), defined as patients with EDSS ≥ 6 at 15 years of follow-up. Clinical variables were collected, and the immunoglobulin G (IgG) index, kFLC index, and oligoclonal bands (OCB) were determined for all patients and compared between the groups. Results Twenty bMS and 15 aMS patients were included in this study. Sixty percent (21/35) were female, and the mean age at the time of the first symptom was 31.5 ± 9.45 years, with no statistical differences between groups. Median follow-up time was 19.8 years (Interquartile range, IQR 15.9-24.6). The median EDSS scores at the last follow-up were 1.5 and 7.5 in the bMS and the aMS group, respectively. No statistically significant differences were found in the kFLC index between the two groups (136.6 vs. 140.27, p=0.59). The IgG index was positive in 62.9% of patients (55% bMS vs. 73.3% aMS, p>0.05), and OCB was positive in 88.6% (90% bMS vs. 86.7% aMS, p>0.05). A significant positive correlation was found between IgG and kFLC indices (rs = 0.85, p<0.001). Conclusion Given the absence of differences between the two groups with opposite disease courses, it is unlikely that the kFLC index is a reliable and powerful marker of long-term prognosis in MS.
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Affiliation(s)
- Pablo Arroyo-Pereiro
- Multiple Sclerosis Unit, Department of Neurology, Hospital Universitari de Bellvitge- Institut d’Investigació Biomèdica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
| | - Lydia García-Serrano
- Department of Immunology, Hospital Universitari de Bellvitge – Institut d’Investigació Biomédica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
| | - Francisco Morandeira
- Department of Immunology, Hospital Universitari de Bellvitge – Institut d’Investigació Biomédica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
| | - Blanca Urban
- Department of Immunology, Hospital Universitari de Bellvitge – Institut d’Investigació Biomédica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
| | - Virginia Mas
- Department of Immunology, Hospital Universitari de Bellvitge – Institut d’Investigació Biomédica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
| | - Mario Framil
- Department of Immunology, Hospital Universitari de Bellvitge – Institut d’Investigació Biomédica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
| | - Isabel León
- Multiple Sclerosis Unit, Department of Neurology, Hospital Universitari de Bellvitge- Institut d’Investigació Biomèdica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
| | - Albert Muñoz-Vendrell
- Multiple Sclerosis Unit, Department of Neurology, Hospital Universitari de Bellvitge- Institut d’Investigació Biomèdica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
| | - Elisabet Matas
- Multiple Sclerosis Unit, Department of Neurology, Hospital Universitari de Bellvitge- Institut d’Investigació Biomèdica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
| | - Lucía Romero-Pinel
- Multiple Sclerosis Unit, Department of Neurology, Hospital Universitari de Bellvitge- Institut d’Investigació Biomèdica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
| | - Antonio Martínez-Yélamos
- Multiple Sclerosis Unit, Department of Neurology, Hospital Universitari de Bellvitge- Institut d’Investigació Biomèdica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
- Departament of Clinical Sciences, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona (UB), Barcelona, Spain
| | - Sergio Martínez-Yélamos
- Multiple Sclerosis Unit, Department of Neurology, Hospital Universitari de Bellvitge- Institut d’Investigació Biomèdica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
- Departament of Clinical Sciences, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona (UB), Barcelona, Spain
| | - Laura Bau
- Multiple Sclerosis Unit, Department of Neurology, Hospital Universitari de Bellvitge- Institut d’Investigació Biomèdica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Spain
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18
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Deschamps R, Shor N, Papeix C, Boudot de la Motte M, Bensa C, Marignier R, Lecler A, Vignal-Clermont C, Ghillani P, Gazzano M, Maillart E, Sterlin D. Relevance of kappa free light chains index in patients with aquaporin-4 or myelin-oligodendrocyte-glycoprotein antibodies. Eur J Neurol 2023; 30:2865-2869. [PMID: 37243935 DOI: 10.1111/ene.15897] [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: 03/16/2023] [Revised: 05/23/2023] [Accepted: 05/24/2023] [Indexed: 05/29/2023]
Abstract
BACKGROUND The kappa free light chains index (κ-index) is increasing in importance as a fast, easy, cost-effective, and quantitative biomarker in multiple sclerosis (MS), which can replace cerebrospinal fluid (CSF)-restricted oligoclonal bands (OCB) detection. In previous studies, controls often included mixed patients with several inflammatory central nervous system disorders. The aim of the present study was to assess the κ-index in patients with serum aquaporin-4 (AQP4)-IgG or myelin-oligodendrocyte-glycoprotein (MOG)-IgG. METHODS We analyzed CSF/serum samples of patients with AQP4-IgG or MOG-Ig and evaluated distinct κ-index cut-offs. We described clinical and magnetic resonance imaging (MRI) features of patients with the highest κ-index values. RESULTS In 11 patients with AQP4-IgG, median κ-index was 16.8 (range 0.2; 63) and 6/11 (54.5%) had κ-index >12. Among 42 patients with MOG-IgG, 2 had low positive MOG-IgG titers, were ultimately diagnosed with MS, and had a markedly increased κ-index (54.1 and 102.5 respectively). For the remaining 40 MOG-IgG-positive patients the median κ-index was 0.3 (range 0.1; 15.5). Some 6/40 (15%) and 1/40 (2.5%) patients had a κ-index >6 and >12, respectively. None fulfilled MRI dissemination in space and dissemination in time (DIS/DIT) criteria and the final diagnosis was MOG-IgG-associated disease (MOGAD) for these 40 patients. Four of the 40 (10%) MOG-IgG-positive patients had OCB. CONCLUSION While a marked increase in κ-index could discriminate MS from MOGAD, a low κ-index threshold could lead to confusion between MS and MOGAD or AQP4 antibody-positive neuromyelitis optica spectrum disorder.
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Affiliation(s)
- Romain Deschamps
- Department of Neurology, Hôpital Fondation Adolphe de Rothschild, Paris, France
| | - Natalia Shor
- Department of Neuroradiology, Assistance Publique Hôpitaux de Paris, Hôpitaux Universitaires La Pitié Salpêtrière - Sorbonne Université, Paris, France
- Department of Neuroradiology, Centre Hospitalier National d'Ophtalmologie des Quinze-Vingts, Paris, France
| | - Caroline Papeix
- Department of Neurology, Hôpital Fondation Adolphe de Rothschild, Paris, France
| | | | - Caroline Bensa
- Department of Neurology, Hôpital Fondation Adolphe de Rothschild, Paris, France
| | - Romain Marignier
- Centre de Référence des Maladies Inflammatoires Rares du Cerveau et de la Moelle, Hôpital Neurologique Pierre Wertheimer, Hospices Civils de Lyon, Lyon, France
- Department of Neurology, Sclérose en Plaques, Pathologies de la Myéline et Neuro-inflammation, Lyon, France
| | - Augustin Lecler
- Department of Radiology, Hôpital Fondation Adolphe de Rothschild, Paris, France
| | | | - Pascale Ghillani
- Department of Immunology, Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Pitié-Salpêtrière, Paris, France
| | - Marianne Gazzano
- Department of Immunology, Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Pitié-Salpêtrière, Paris, France
| | - Elisabeth Maillart
- Department of Neurology, Centre de référence des maladies inflammatoires rares du cerveau et de la moelle (MIRCEM). Assistance Publique Hôpitaux de Paris, Hôpitaux Universitaires La Pitié Salpêtrière- Sorbonne Université, Paris, France
| | - Delphine Sterlin
- Department of Immunology, Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Pitié-Salpêtrière, Paris, France
- Centre d'Immunologie et des Maladies Infectieuses (CIMI-Paris), Sorbonne Université, Inserm, Paris, France
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19
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Solomon AJ, Arrambide G, Brownlee WJ, Flanagan EP, Amato MP, Amezcua L, Banwell BL, Barkhof F, Corboy JR, Correale J, Fujihara K, Graves J, Harnegie MP, Hemmer B, Lechner-Scott J, Marrie RA, Newsome SD, Rocca MA, Royal W, Waubant EL, Yamout B, Cohen JA. Differential diagnosis of suspected multiple sclerosis: an updated consensus approach. Lancet Neurol 2023; 22:750-768. [PMID: 37479377 DOI: 10.1016/s1474-4422(23)00148-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 03/14/2023] [Accepted: 03/31/2023] [Indexed: 07/23/2023]
Abstract
Accurate diagnosis of multiple sclerosis requires careful attention to its differential diagnosis-many disorders can mimic the clinical manifestations and paraclinical findings of this disease. A collaborative effort, organised by The International Advisory Committee on Clinical Trials in Multiple Sclerosis in 2008, provided diagnostic approaches to multiple sclerosis and identified clinical and paraclinical findings (so-called red flags) suggestive of alternative diagnoses. Since then, knowledge of disorders in the differential diagnosis of multiple sclerosis has expanded substantially. For example, CNS inflammatory disorders that present with syndromes overlapping with multiple sclerosis can increasingly be distinguished from multiple sclerosis with the aid of specific clinical, MRI, and laboratory findings; studies of people misdiagnosed with multiple sclerosis have also provided insights into clinical presentations for which extra caution is warranted. Considering these data, an update to the recommended diagnostic approaches to common clinical presentations and key clinical and paraclinical red flags is warranted to inform the contemporary clinical evaluation of patients with suspected multiple sclerosis.
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Affiliation(s)
- Andrew J Solomon
- Department of Neurological Sciences, Larner College of Medicine at the University of Vermont, University Health Center, Burlington, VT, USA.
| | - Georgina Arrambide
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Wallace J Brownlee
- National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - Eoin P Flanagan
- Departments of Neurology and Laboratory Medicine and Pathology and the Center for Multiple Sclerosis and Autoimmune Neurology, Mayo Clinic, Rochester, MN, USA
| | - Maria Pia Amato
- Department NEUROFARBA, University of Florence, Florence, Italy; IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Lilyana Amezcua
- Department of Neurology, University of Southern California, Keck School of Medicine, Los Angeles, CA, USA
| | - Brenda L Banwell
- Department of Neurology, University of Pennsylvania, Division of Child Neurology, Philadelphia, PA, USA; Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - John R Corboy
- Department of Neurology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Jorge Correale
- Department of Neurology, Fleni Institute of Biological Chemistry and Physical Chemistry (IQUIFIB), Buenos Aires, Argentina; National Council for Scientific and Technical Research/University of Buenos Aires, Buenos Aires, Argentina
| | - Kazuo Fujihara
- Department of Multiple Sclerosis Therapeutics, Fukushima Medical University School of Medicine, Koriyama, Japan; Multiple Sclerosis and Neuromyelitis Optica Center, Southern TOHOKU Research Institute for Neuroscience, Koriyama, Japan
| | - Jennifer Graves
- Department of Neurosciences, University of California, San Diego, CA, USA
| | | | - Bernhard Hemmer
- Department of Neurology, Klinikum rechts der Isar, Medical Faculty, Technische Universität München, Munich, Germany; Munich Cluster for Systems Neurology, Munich, Germany
| | - Jeannette Lechner-Scott
- Department of Neurology, John Hunter Hospital, Newcastle, NSW Australia; Hunter Medical Research Institute Neurology, University of Newcastle, Newcastle, NSW, Australia
| | - Ruth Ann Marrie
- Departments of Internal Medicine and Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Scott D Newsome
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, Neurology Unit, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Walter Royal
- Department of Neurobiology and Neuroscience Institute, Morehouse School of Medicine, Atlanta, GA, USA
| | - Emmanuelle L Waubant
- Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - Bassem Yamout
- Neurology Institute, Harley Street Medical Center, Abu Dhabi, United Arab Emirates
| | - Jeffrey A Cohen
- Mellen Center for MS Treatment and Research, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
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20
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Hegen H, Berek K, Bsteh G, Auer M, Altmann P, Di Pauli F, Grams A, Milosavljevic D, Ponleitner M, Poskaite P, Schnabl C, Wurth S, Zinganell A, Berger T, Walde J, Deisenhammer F. Kappa free light chain and neurofilament light independently predict early multiple sclerosis disease activity-a cohort study. EBioMedicine 2023; 91:104573. [PMID: 37086651 PMCID: PMC10148088 DOI: 10.1016/j.ebiom.2023.104573] [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: 01/05/2023] [Revised: 03/08/2023] [Accepted: 03/31/2023] [Indexed: 04/24/2023] Open
Abstract
BACKGROUND Inter-individual courses of multiple sclerosis (MS) are extremely variable. The objective of this study was to investigate whether κ-free light chain (κ-FLC) index and serum neurofilament light (sNfL) have an additive predictive value for MS disease activity. METHODS Patients with early MS who had cerebrospinal fluid (CSF) and serum sampling at disease onset were followed for four years. At baseline, age, sex, disease duration, number of T2-hyperintense (T2L), and contrast-enhancing T1 lesions (CEL) on MRI were determined. During follow-up, the occurrence of a second clinical attack and start of disease-modifying treatment (DMT) were registered. κ-FLC was measured by nephelometry, and κ-FLC index calculated as [CSF κ-FLC/serum κ-FLC]/albumin quotient. sNfL was determined by single-molecule array, and age- and body-mass-index adjusted Z scores were calculated. FINDINGS A total of 86 patients at a mean age of 33 ± 10 years and with a female predominance of 67% were included; 36 (42%) patients experienced a second clinical attack during follow-up. Cox regression analysis adjusted for age, sex, T2L, CEL, disease and follow-up duration, and DMT use during follow-up revealed that both κ-FLC index as well as sNfL Z score independently predict time to second clinical attack. The chance for freedom of relapse within 12 months was 2% in patients with high levels of κ-FLC index (>100) and high sNfL Z score (>3), 30% in patients with high κ-FLC index (>100) and lower sNfL Z score (≤3), 70% in patients with lower κ-FLC index (≤100) but high sNfL Z score (>3), and 90% in patients with lower levels of κ-FLC index (≤100) and sNfL Z score (≤3). INTERPRETATION κ-FLC index and sNfL Z score have an additive predictive value for early MS disease activity that is independent of known predictors. FUNDING This study was funded by a grant of the charitable foundation of the Austrian Multiple Sclerosis Society.
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Affiliation(s)
- Harald Hegen
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.
| | - Klaus Berek
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Gabriel Bsteh
- Department of Neurology, Medical University of Vienna, Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Michael Auer
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Patrick Altmann
- Department of Neurology, Medical University of Vienna, Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Franziska Di Pauli
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Astrid Grams
- Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Markus Ponleitner
- Department of Neurology, Medical University of Vienna, Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Paulina Poskaite
- Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Sebastian Wurth
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Anne Zinganell
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Thomas Berger
- Department of Neurology, Medical University of Vienna, Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Janette Walde
- Department of Statistics, Faculty of Economics and Statistics, University of Innsbruck, Innsbruck, Austria.
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21
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Rosenstein I, Axelsson M, Novakova L, Rasch S, Blennow K, Zetterberg H, Lycke J. High levels of kappa free light chain synthesis predict cognitive decline in relapsing-remitting multiple sclerosis. Front Immunol 2023; 14:1106028. [PMID: 36742305 PMCID: PMC9896185 DOI: 10.3389/fimmu.2023.1106028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 01/04/2023] [Indexed: 01/21/2023] Open
Abstract
Background Evolving evidence suggests that measurement of cerebrospinal fluid (CSF) kappa free light chain (KFLC) synthesis has high diagnostic sensitivity and specificity for multiple sclerosis (MS), but its prognostic ability is less investigated. The usefulness of KFLC in predicting cognitive impairment (CI) is still unknown. Methods In a monocentric longitudinal retrospecitve cohort study, KFLC-index ([CSF KFLC/serum KFLC]/[CSF albumin/serum albumin]) measured by latex-enhanced immunonephelometry was prospectively determined as part of the diagnostic workup in patients with early relapsing-remitting MS (RRMS, n=77). The ability of KFLC-index to predict information processing speed (IPS) worsening as assessed with the symbol digit modalities test (SDMT) was investigated in univariable and multivariable models. Results In patients with KFLC-index>100 (n=31), 11 subjects (35.5%) showed reduced SDMT scores by ≥8 points at follow-up (mean follow-up time 7.3 ± 2.6 years), compared with their baseline scores (p=0.01). Baseline KFLC-index>100 was strongly associated with a higher hazard of SDMT score reduction at follow-up (adjusted hazard ratio 10.5, 95% confidence interval 2.2-50.8, p=0.003; median time to SDMT reduction 7 years). Conclusion Intrathecal KFLC synthesis has become an attractive diagnostic tool for MS. We show for the first time that in a real-world setting of early RRMS, KFLC-index predicted cognitive decline. Whether this predictive ability of KFLC-index also concerns other cognitive domains than IPS, warrants further investigations.
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Affiliation(s)
- Igal Rosenstein
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden,*Correspondence: Igal Rosenstein,
| | - Markus Axelsson
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Lenka Novakova
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sofia Rasch
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden,United Kingdom (UK) Dementia Research Institute at University College London (UCL), London, United Kingdom,Department of Neurodegenerative Disease, University College London (UCL) Queen Square Institute of Neurology, London, United Kingdom,Hong Kong Centre for Neurodegenerative Diseases, Hong Kong SAR, China,Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Jan Lycke
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
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