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Nelke C, Schmid S, Kleefeld F, Schroeter CB, Goebel HH, Hoffmann S, Preuße C, Kölbel H, Meuth SG, Ruck T, Stenzel W. Complement and MHC patterns can provide the diagnostic framework for inflammatory neuromuscular diseases. Acta Neuropathol 2024; 147:15. [PMID: 38214778 PMCID: PMC10786976 DOI: 10.1007/s00401-023-02669-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 12/12/2023] [Accepted: 12/12/2023] [Indexed: 01/13/2024]
Abstract
Histopathological analysis stands as the gold standard for the identification and differentiation of inflammatory neuromuscular diseases. These disorders continue to constitute a diagnostic challenge due to their clinical heterogeneity, rarity and overlapping features. To establish standardized protocols for the diagnosis of inflammatory neuromuscular diseases, the development of cost-effective and widely applicable tools is crucial, especially in settings constrained by limited resources. The focus of this review is to emphasize the diagnostic value of major histocompatibility complex (MHC) and complement patterns in the immunohistochemical analysis of these diseases. We explore the immunological background of MHC and complement signatures that characterize inflammatory features, with a specific focus on idiopathic inflammatory myopathies. With this approach, we aim to provide a diagnostic algorithm that may improve and simplify the diagnostic workup based on a limited panel of stainings. Our approach acknowledges the current limitations in the field of inflammatory neuromuscular diseases, particularly the scarcity of large-scale, prospective studies that validate the diagnostic potential of these markers. Further efforts are needed to establish a consensus on the diagnostic protocol to effectively distinguish these diseases.
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Affiliation(s)
- Christopher Nelke
- Department of Neurology, Medical Faculty, Heinrich Heine University Duesseldorf, Moorenstr. 5, 40225, Duesseldorf, Germany
| | - Simone Schmid
- Department of Neuropathology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health (BIH), Charitéplatz 1, 10117, Berlin, Germany
| | - Felix Kleefeld
- Department of Neurology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health (BIH), Charitéplatz 1, 10117, Berlin, Germany
| | - Christina B Schroeter
- Department of Neurology, Medical Faculty, Heinrich Heine University Duesseldorf, Moorenstr. 5, 40225, Duesseldorf, Germany
| | - Hans-Hilmar Goebel
- Department of Neuropathology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health (BIH), Charitéplatz 1, 10117, Berlin, Germany
| | - Sarah Hoffmann
- Department of Neurology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health (BIH), Charitéplatz 1, 10117, Berlin, Germany
| | - Corinna Preuße
- Department of Neuropathology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health (BIH), Charitéplatz 1, 10117, Berlin, Germany
- Department of Neuropediatrics, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health (BIH), Augustenburger Platz 1, 13353, Berlin, Germany
| | - Heike Kölbel
- Department of Neuropaediatrics, Klinik für Kinderheilkunde I, Universitätsklinikum Essen, Essen, Germany
| | - Sven G Meuth
- Department of Neurology, Medical Faculty, Heinrich Heine University Duesseldorf, Moorenstr. 5, 40225, Duesseldorf, Germany
| | - Tobias Ruck
- Department of Neurology, Medical Faculty, Heinrich Heine University Duesseldorf, Moorenstr. 5, 40225, Duesseldorf, Germany
| | - Werner Stenzel
- Department of Neuropathology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health (BIH), Charitéplatz 1, 10117, Berlin, Germany.
- Leibniz Science Campus Chronic Inflammation, Berlin, Germany.
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Alawneh I, Stosic A, Gonorazky H. Muscle MRI patterns for limb girdle muscle dystrophies: systematic review. J Neurol 2023:10.1007/s00415-023-11722-1. [PMID: 37129643 DOI: 10.1007/s00415-023-11722-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 04/06/2023] [Accepted: 04/11/2023] [Indexed: 05/03/2023]
Abstract
Limb girdle muscle dystrophies (LGMDs) are a group of inherited neuromuscular disorders comprising more than 20 genes. There have been increasing efforts to characterize this group with Muscle MRI. However, due to the complexity and similarities, the interpretation of the MRI patterns is usually done by experts in the field. Here, we proposed a step-by-step image interpretation of Muscle MRI in LGDM by evaluating the variability of muscle pattern involvement reported in the literature. A systematic review with an open start date to November 2022 was conducted to describe all LGMDs' muscle MRI patterns. Eighty-eight studies were included in the final review. Data were found to describe muscle MRI patterns for 15 out of 17 LGMDs types. Although the diagnosis of LGMDs is challenging despite the advanced genetic testing and other diagnostic modalities, muscle MRI is shown to help in the diagnosis of LGMDs. To further increase the yield for muscle MRI in the neuromuscular field, larger cohorts of patients need to be conducted.
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Affiliation(s)
- Issa Alawneh
- Department of Neurology, The Hospital for Sick Children, Toronto, Canada
| | - Ana Stosic
- Genetics and Genome Biology Program, The Hospital for Sick Children Research Institute, Toronto, Canada
| | - Hernan Gonorazky
- Department of Neurology, The Hospital for Sick Children, Toronto, Canada.
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Mavoungou LO, Neuenschwander S, Pham U, Iyer PS, Mermod N. Characterization of mesoangioblast cell fate and improved promyogenic potential of a satellite cell-like subpopulation upon transplantation in dystrophic murine muscles. Stem Cell Res 2019; 41:101619. [PMID: 31683098 DOI: 10.1016/j.scr.2019.101619] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 09/20/2019] [Accepted: 10/11/2019] [Indexed: 12/13/2022] Open
Abstract
Duchenne muscular dystrophy (DMD) is a lethal muscle-wasting disease caused by the lack of dystrophin in muscle fibers that is currently without curative treatment. Mesoangioblasts (MABs) are multipotent progenitor cells that can differentiate to a myogenic lineage and that can be used to express Dystrophin upon transplantation into muscles, in autologous gene therapy approaches. However, their fate in the muscle environment remains poorly characterized. Here, we investigated the differentiation fate of MABs following their transplantation in DMD murine muscles using a mass cytometry strategy. This allowed the identification and isolation of a fraction of MAB-derived cells presenting common properties with satellite muscle stem cells. This analysis also indicated that most cells did not undergo a myogenic differentiation path once in the muscle environment, limiting their capacity to restore dystrophin expression in transplanted muscles. We therefore assessed whether MAB treatment with cytokines and growth factors prior to engraftment may improve their myogenic fate. We identified a combination of such signals that ameliorates MABs capacity to undergo myogenic differentiation in vivo and to restore dystrophin expression upon engraftment in myopathic murine muscles.
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Affiliation(s)
- Lionel O Mavoungou
- Institute of Biotechnology and Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | | | - Uyen Pham
- Grand Valley State University, MI, USA
| | - Pavithra S Iyer
- Institute of Biotechnology and Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland; Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zürich, Switzerland
| | - Nicolas Mermod
- Institute of Biotechnology and Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland.
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Leporq B, Le Troter A, Le Fur Y, Salort-Campana E, Guye M, Beuf O, Attarian S, Bendahan D. Combined quantification of fatty infiltration, T 1-relaxation times and T 2*-relaxation times in normal-appearing skeletal muscle of controls and dystrophic patients. MAGMA 2017; 30:407-415. [PMID: 28332039 DOI: 10.1007/s10334-017-0616-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2016] [Revised: 03/06/2017] [Accepted: 03/15/2017] [Indexed: 12/13/2022]
Abstract
OBJECTIVES To evaluate the combination of a fat-water separation method with an automated segmentation algorithm to quantify the intermuscular fatty-infiltrated fraction, the relaxation times, and the microscopic fatty infiltration in the normal-appearing muscle. MATERIALS AND METHODS MR acquisitions were performed at 1.5T in seven patients with facio-scapulo-humeral dystrophy and eight controls. Disease severity was assessed using commonly used scales for the upper and lower limbs. The fat-water separation method provided proton density fat fraction (PDFF) and relaxation times maps (T 2* and T 1). The segmentation algorithm distinguished adipose tissue and normal-appearing muscle from the T 2* map and combined active contours, a clustering analysis, and a morphological closing process to calculate the index of fatty infiltration (IFI) in the muscle compartment defined as the relative amount of pixels with the ratio between the number of pixels within IMAT and the total number of pixels (IMAT + normal appearing muscle). RESULTS In patients, relaxation times were longer and a larger fatty infiltration has been quantified in the normal-appearing muscle. T 2* and PDFF distributions were broader. The relaxation times were correlated to the Vignos scale whereas the microscopic fatty infiltration was linked to the Medwin-Gardner-Walton scale. The IFI was linked to a composite clinical severity scale gathering the whole set of scales. CONCLUSION The MRI indices quantified within the normal-appearing muscle could be considered as potential biomarkers of dystrophies and quantitatively illustrate tissue alterations such as inflammation and fatty infiltration.
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Affiliation(s)
- Benjamin Leporq
- Laboratoire CREATIS CNRS UMR 5220; Inserm U1206; INSA-Lyon; UCBL Lyon 1, 7, Avenue Jean Capelle, 69621, Villeurbanne Cedex, France.
| | - Arnaud Le Troter
- Aix-Marseille University, CRMBM, CNRS UMR, 6612, Marseille, France
| | - Yann Le Fur
- Aix-Marseille University, CRMBM, CNRS UMR, 6612, Marseille, France
| | | | - Maxime Guye
- Aix-Marseille University, CRMBM, CNRS UMR, 6612, Marseille, France
| | - Olivier Beuf
- Laboratoire CREATIS CNRS UMR 5220; Inserm U1206; INSA-Lyon; UCBL Lyon 1, 7, Avenue Jean Capelle, 69621, Villeurbanne Cedex, France
| | - Shahram Attarian
- Reference Center for Neuromuscular Disorders, Timone Hospital, Marseille, France
| | - David Bendahan
- Aix-Marseille University, CRMBM, CNRS UMR, 6612, Marseille, France
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