Expression profiling of disease progression in canine model of Duchenne muscular dystrophy
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abstract
Duchenne muscular dystrophy (DMD) causes progressive disability in 1 of every 5,000 boys due to the lack of functional dystrophin protein. Despite much advancement in knowledge about DMD disease presentation and progression-attributable in part to studies using mouse and canine models of the disease-current DMD treatments are not equally effective in all patients. There remains, therefore, a need for translational animal models in which novel treatment targets can be identified and evaluated. Golden Retriever muscular dystrophy (GRMD) is a phenotypically and genetically homologous animal model of DMD. As with DMD, speed of disease progression in GRMD varies substantially. However, unlike DMD, all GRMD dogs possess the same causal mutation; therefore genetic modifiers of phenotypic variation are relatively easier to identify. Furthermore, the GRMD dogs used in this study reside within the same colony, reducing the confounding effects of environment on phenotypic variation. To detect modifiers of disease progression, we developed gene expression profiles using RNA sequencing for 9 dogs: 6 GRMD dogs (3 with faster-progressing and 3 with slower-progressing disease, based on quantitative, objective biomarkers) and 3 control dogs from the same colony. All dogs were evaluated at 2 time points: early disease onset (3 months of age) and the point at which GRMD stabilizes (6 months of age) using quantitative, objective biomarkers identified as robust against the effects of relatedness/inbreeding. Across all comparisons, the most differentially expressed genes fell into 3 categories: myogenesis/muscle regeneration, metabolism, and inflammation. Our findings are largely in concordance with DMD and mouse model studies, reinforcing the utility of GRMD as a translational model. Novel findings include the strong up-regulation of chitinase 3-like 1 (CHI3L1) in faster-progressing GRMD dogs, suggesting previously unexplored mechanisms underlie progression speed in GRMD and DMD. In summary, our findings support the utility of RNA sequencing for evaluating potential biomarkers of GRMD progression speed, and are valuable for identifying new avenues of exploration in DMD research.
