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Recent advances in molecular therapies for Duchenne muscular dystrophy (DMD) require precise genetic diagnosis because most therapeutic strategies are mutation-specific. To understand more about the genotype-phenotype correlations of the DMD gene we performed a comprehensive analysis of the DMD mutational spectrum in a large series of families. Here we provide the clinical, pathological and genetic features of 576 dystrophinopathy patients. DMD gene analysis was performed using the MLPA technique and whole gene sequencing in blood DNA and muscle cDNA. The impact of the DNA variants on mRNA splicing and protein functionality was evaluated by in silico analysis using computational algorithms. DMD mutations were detected in 576 unrelated dystrophinopathy families by combining the analysis of exonic copies and the analysis of small mutations. We found that 471 of these mutations were large intragenic rearrangements. Of these, 406 (70.5%) were exonic deletions, 64 (11.1%) were exonic duplications, and one was a deletion/duplication complex rearrangement (0.2%). Small mutations were identified in 105 cases (18.2%), most being nonsense/frameshift types (75.2%). Mutations in splice sites, however, were relatively frequent (20%). In total, 276 mutations were identified, 85 of which have not been previously described. The diagnostic algorithm used proved to be accurate for the molecular diagnosis of dystrophinopathies. The reading frame rule was fulfilled in 90.4% of DMD patients and in 82.4% of Becker muscular dystrophy patients (BMD), with significant differences between the mutation types. We found that 58% of DMD patients would be included in single exon-exon skipping trials, 63% from strategies directed against multiexon-skipping exons 45 to 55, and 14% from PTC therapy. A detailed analysis of missense mutations provided valuable information about their impact on the protein structure. [ABSTRACT FROM AUTHOR]

DMD nonsense and frameshift mutations lead to severe Duchenne muscular dystrophy while in-frame mutations lead to milder Becker muscular dystrophy. Exceptions are found in 10% of cases and the production of alternatively spliced transcripts is considered a key modifier of disease severity. Several exonic mutations have been shown to induce exon-skipping, while splice site mutations result in exon-skipping or activation of cryptic splice sites. However, factors determining the splicing pathway are still unclear. Point mutations provide valuable information regarding the regulation of pre-mRNA splicing and elements defining exon identity in the DMD gene. Here we provide a comprehensive analysis of 98 point mutations related to clinical phenotype and their effect on muscle mRNA and dystrophin expression. Aberrant splicing was found in 27 mutations due to alteration of splice sites or splicing regulatory elements. Bioinformatics analysis was performed to test the ability of the available algorithms to predict consequences on mRNA and to investigate the major factors that determine the splicing pathway in mutations affecting splicing signals. Our findings suggest that the splicing pathway is highly dependent on the interplay between splice site strength and density of regulatory elements. [ABSTRACT FROM AUTHOR]

DMD nonsense and frameshift mutations lead to severe Duchenne muscular dystrophy while in-frame mutations lead to milder Becker muscular dystrophy. Exceptions are found in 10% of cases and the production of alternatively spliced transcripts is considered a key modifier of disease severity. Several exonic mutations have been shown to induce exon-skipping, while splice site mutations result in exon-skipping or activation of cryptic splice sites. However, factors determining the splicing pathway are still unclear. Point mutations provide valuable information regarding the regulation of pre-mRNA splicing and elements defining exon identity in the DMD gene. Here we provide a comprehensive analysis of 98 point mutations related to clinical phenotype and their effect on muscle mRNA and dystrophin expression. Aberrant splicing was found in 27 mutations due to alteration of splice sites or splicing regulatory elements. Bioinformatics analysis was performed to test the ability of the available algorithms to predict consequences on mRNA and to investigate the major factors that determine the splicing pathway in mutations affecting splicing signals. Our findings suggest that the splicing pathway is highly dependent on the interplay between splice site strength and density of regulatory elements.