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Characterization of DupEx2 Duchenne Muscular Dystrophy

IRCCS San Raffaele · 2022
ClinicalTrials.gov · Datasets · License: Public Domain · 2022
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To characterize the clinical phenotype and possible predictive/prognostic factors of patients with Duchenne muscular dystrophy (DMD) due to duplication of exon 2 (Dup2). Specifically, we aim 1) to describe the progression of motor, respiratory and cardiac function; 2) to enquire if the phenotypic spectrum of Dup2 is milder than classic DMD, 3) to perform whole genome sequencing (WGS) to characterize DNA breakpoints to correlate with the phenotype; 4) to collect material for future proteomic/transcriptomic studies. Background/Rationale DMD is caused by mutations in the DMD gene and in 11% of cases is due to duplications. The most promising therapeutic approaches include mutation-specific therapies. Notably, there is increasing evidence that specific groups of mutations may underlie different disease trajectories compared to the "average" DMD population. It is thus mandatory to have more information on genotype-phenotype correlations and patterns of progression related to different genotypes. Dup2 is the most common DMD duplication and the only one for which a AAV-mediated exon skipping study is ongoing. Despite most case series and databases ascribe Dup2 to severe phenotype, our preliminary findings sustain that these patients have collectively a milder progression of the disease and in 1/3 of cases a significantly milder phenotype. Moreover, our attempts to reveal mechanism involved in attenuating the phenotype would confute the hypothesis of alternative spicing transcripts as previously described for DMD with deletion of exon 2. Research design and methods Clinical information regarding a cohort of 26 Italian Dup2 patients will be collected. Differences in time to loss of ambulation compared to a DMD control group will be achieved. Finally, we will retrieve DNA for correlative WGS studies. Anticipated output We expect that Dup2 patients present a milder DMD phenotype , which might be predicted by genomic studies.
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