Abstract

Myotonic dystrophy type 1 (DM1) is a severe autosomal dominant neuromuscular disease in which the musculoskeletal system contributes substantially to overall mortality and morbidity. DM1 stems from a noncoding CTG trinucleotide repeat expansion in the DMPK gene. The human skeletal actin long repeat (HSALR) mouse model reproduces several aspects of the disease, but the muscle-wasting phenotype of this model has never been characterized in vivo. Herein, we used quantitative MRI to measure the fat and muscle volumes in the leg compartment (LC) of mice. These acquired data were processed to extract relevant parameters such as fat fraction and fat infiltration (fat LC/LC) in HSALR and control (FBV) muscles. These results showed increased fat volume (fat LC) and fat infiltration within the muscle tissue of the leg compartment (muscle LC), in agreement with necropsies, in which fatty clumps were observed, and consistent with previous findings in DM1 patients. Model mice did not reproduce the characteristic impaired fat fraction, widespread fat replacement through the muscles, or reduced muscle volume reported in patients. Taken together, the observed abnormal replacement of skeletal muscle by fat in the HSALR mice indicates that these mice partially reproduced the muscle phenotype observed in humans.

Details

Title
Quantitative magnetic resonance imaging assessment of muscle composition in myotonic dystrophy mice
Author
Bargiela, Ariadna 1 ; Ten-Esteve, Amadeo 2 ; Martí-Bonmatí, Luis 2 ; Sevilla, Teresa 3 ; Perez Alonso, Manuel 4 ; Artero, Ruben 4 

 La Fe Health Research Institute (IISLAFE), Neuromuscular Research Unit, Neurology Department, Valencia, Spain 
 Singular Scientific and Technical Infrastructures (ICTS), Biomedical Imaging Research Group (GIBI230) and “La Fe” Imaging Node of the Distributed Biomedical Imaging Network (ReDIB), Valencia, Spain; La Fe University and Polytechnic Hospital, Medical Imaging Department, Valencia, Spain 
 La Fe Health Research Institute (IISLAFE), Neuromuscular Research Unit, Neurology Department, Valencia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Valencia, Spain (GRID:grid.452372.5) (ISNI:0000 0004 1791 1185); Universitat de València, Department of Medicine, Valencia, Spain (GRID:grid.5338.d) (ISNI:0000 0001 2173 938X) 
 University of Valencia, University Research Institute for Biotechnology and Biomedicine (BIOTECMED), Valencia, Spain (GRID:grid.5338.d) (ISNI:0000 0001 2173 938X); INCLIVA Biomedical Research Institute, Translational Genomics Group, Valencia, Spain (GRID:grid.429003.c) (ISNI:0000 0004 7413 8491) 
Pages
503
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2763171365
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.