High-Throughput Digital Image Analysis Reveals Distinct Patterns of Dystrophin Expression in Dystrophinopathy Patients - Sorbonne Université Access content directly
Journal Articles Journal of Neuropathology and Experimental Neurology Year : 2021

High-Throughput Digital Image Analysis Reveals Distinct Patterns of Dystrophin Expression in Dystrophinopathy Patients

Abstract

Duchenne muscular dystrophy (DMD) is an incurable disease caused by out-of-frame DMD gene deletions while in frame deletions lead to the milder Becker muscular dystrophy (BMD). In the last decade several antisense oligonucleotides drugs have been developed to induce a partially functional internally deleted dystrophin, similar to that produced in BMD, and expected to ameliorate the disease course. The pattern of dystrophin expression and functionality in dystrophinopathy patients is variable due to multiple factors, such as molecular functionality of the dystrophin and its distribution. To benchmark the success of therapeutic intervention, a clear understanding of dystrophin expression patterns in dystrophinopathy patients is vital. Recently, several groups have used innovative techniques to quantify dystrophin in muscle biopsies of children but not in patients with milder BMD. This study reports on dystrophin expression using both Western blotting and an automated, high-throughput, image analysis platform in DMD, BMD, and intermediate DMD/BMD skeletal muscle biopsies. Our results found a significant correlation between Western blot and immunofluorescent quantification indicating consistency between the different methodologies. However, we identified significant inter-and intradisease heterogeneity of patterns of dystrophin expression in patients irrespective of the amount detected on blot, due to variability in both fluorescence intensity and dystrophin sarcolemmal circumference coverage. Our data highlight the heterogeneity of the pattern of dystrophin expression in BMD, which will assist the assessment of dystrophin restoration therapies.
Fichier principal
Vignette du fichier
nlab088.pdf (792.03 Ko) Télécharger le fichier
Origin : Publication funded by an institution

Dates and versions

hal-03454233 , version 1 (29-11-2021)

Identifiers

Cite

Silvia Torelli, Domenic Scaglioni, Valentina Sardone, Matthew J Ellis, Joana Domingos, et al.. High-Throughput Digital Image Analysis Reveals Distinct Patterns of Dystrophin Expression in Dystrophinopathy Patients. Journal of Neuropathology and Experimental Neurology, 2021, 80 (10), pp.955 - 965. ⟨10.1093/jnen/nlab088⟩. ⟨hal-03454233⟩
55 View
41 Download

Altmetric

Share

Gmail Facebook X LinkedIn More