Link between MHC Fiber Type and Restoration of Dystrophin Expression and Key Components of the DAPC by Tricyclo-DNA-Mediated Exon Skipping

The administration of antisense oligonucleotide golodirsen reduces pathological regeneration in patients with Duchenne muscular dystrophy

During the last decade, multiple clinical trials for Duchenne muscular dystrophy (DMD) have focused on the induction of dystrophin expression using different strategies. Many of these trials have reported a clear increase in dystrophin protein following treatment. However, the low levels of the induced dystrophin protein have raised questions on its functionality. In our present study, using an unbiased, high-throughput digital image analysis platform, we assessed markers of regeneration and levels of dystrophin associated protein via immunofluorescent analysis of whole muscle sections in 25 DMD boys who received 48-weeks treatment with exon 53 skipping morpholino antisense oligonucleotide (PMO) golodirsen. We demonstrate that the de novo dystrophin induced by exon skipping with PMO golodirsen is capable of conferring a histological benefit in treated patients with an increase in dystrophin associated proteins at the dystrophin positive regions of the sarcolemma in post-treatment biopsies. Although 48 weeks treatment with golodirsen did not result in a significant change in the levels of fetal/developmental myosins for the entire cohort, there was a significant negative correlation between the amount of dystrophin and levels of regeneration observed in different biopsy samples. Our results provide, for the first time, evidence of functionality of induced dystrophin following successful therapeutic intervention in the human.

QuantiMus: A Machine Learning-Based Approach for High Precision Analysis of Skeletal Muscle Morphology

Skeletal muscle injury provokes a regenerative response, characterized by the de novo generation of myofibers that are distinguished by central nucleation and re-expression of developmentally restricted genes. In addition to these characteristics, myofiber cross-sectional area (CSA) is widely used to evaluate muscle hypertrophic and regenerative responses. Here, we introduce QuantiMus, a free software program that uses machine learning algorithms to quantify muscle morphology and molecular features with high precision and quick processing-time. The ability of QuantiMus to define and measure myofibers was compared to manual measurement or other automated software programs. QuantiMus rapidly and accurately defined total myofibers and measured CSA with comparable performance but quantified the CSA of centrally-nucleated fibers (CNFs) with greater precision compared to other software. It additionally quantified the fluorescence intensity of individual myofibers of human and mouse muscle, which was used to assess the distribution of myofiber type, based on the myosin heavy chain isoform that was expressed. Furthermore, analysis of entire quadriceps cross-sections of healthy and mdx mice showed that dystrophic muscle had an increased frequency of Evans blue dye+ injured myofibers. QuantiMus also revealed that the proportion of centrally nucleated, regenerating myofibers that express embryonic myosin heavy chain (eMyHC) or neural cell adhesion molecule (NCAM) were increased in dystrophic mice. Our findings reveal that QuantiMus has several advantages over existing software. The unique self-learning capacity of the machine learning algorithms provides superior accuracy and the ability to rapidly interrogate the complete muscle section. These qualities increase rigor and reproducibility by avoiding methods that rely on the sampling of representative areas of a section. This is of particular importance for the analysis of dystrophic muscle given the "patchy" distribution of muscle pathology. QuantiMus is an open source tool, allowing customization to meet investigator-specific needs and provides novel analytical approaches for quantifying muscle morphology.