Unlocking the genetic blueprint of duchenne muscular dystrophy: A personalized approach with MLPA and WES.

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Duchenne muscular dystrophy (DMD) is a progressive X-linked disorder causing muscle degeneration and multisystem involvement, requiring precise genetic diagnosis for timely intervention and treatment. To investigate the genetic landscape of DMD using a two-tiered diagnostic approach combining MLPA and WES, and to correlate genetic findings with clinical outcomes for improved management. A cross-sectional study of 80 male DMD patients was conducted using a sequential genetic approach, combining MLPA and WES, with bioinformatics and statistical analyses to explore genotype-phenotype correlations. Pathogenic variants were identified in 65 cases (81.2%), with deletions (67.5%) being the most common, followed by duplications (6.3%), splice-site (3.8%), and nonsense variants (3.8%). WES identified additional pathogenic variants in MLPA-negative cases, including novel mutations, expanding the known genetic spectrum of DMD. The combined MLPA-WES approach significantly improved diagnostic yield (χ² = 12.90, p<0.001). Functional analysis revealed disruptions in glycogen metabolism (46%), calcium transport (24%), and mitochondrial function (12%), with dystrophin-associated proteins (DAG1, SGCD) critically involved in muscle stability. Out-of-frame deletions were significantly associated with early disease onset (χ² = 49.03, p<0.001) and severe phenotypes (χ² = 47.04, p<0.001), supporting exon-skipping therapy. In-frame deletions correlated with milder progression, while nonsense variants posed a 2.5-fold increased risk of early cardiomyopathy (p=0.002), emphasizing the need for early intervention. Combining MLPA and WES enhances DMD diagnostic accuracy, enabling timely clinical interventions. Integrating functional analysis with genotype-phenotype correlations supports personalized therapeutic strategies, improving patient outcomes.