The primary determinant of disease severity in patients with severe Duchenne muscular dystrophy (DMD) or milder Becker muscular dystrophy (BMD) is whether their dystrophin gene (DMD) mutation disrupts the mRNA reading frame or permits the expression of a partially functional protein. However, even in the complete absence of dystrophin, variability in disease severity is observed, with candidate gene studies implicating several genes as potential DMD modifiers. This study undertakes a comprehensive genome-wide search for modifier loci influencing disease severity in DMD patients. The availability of subjects for such studies remains limited, resulting in modest sample sizes that challenge the GWAS design. To address this, we have implemented measures to minimize heterogeneity within the dataset at the dystrophin (DMD) gene itself, adopting a conservative approach to DMD mutation classification to limit the possibility of residual dystrophin expression. Additionally, the study employed statistical methods that are well-suited to smaller sample sizes, including the use of a novel linear regression-like residual for time to ambulatory loss and the application of evidential statistics, specifically the Posterior Probability of Linkage Disequilibrium (PPLD), to assess trait-SNP associations in the GWAS framework. With a sample size of 419 patients, this study has identified multiple candidate genetic modifier loci. The molecular data available in dbGaP includes 2,562,265 directly genotyped variants in 419 people using the Illumina Infinium Omni2.5Exome-8 Beadchip assay, achieving a genotyping rate of 0.998. The phenotypic data comprises age at ambulatory loss, steroid status, DMD gene mutation, and the PPLD value from the time-to-event (TE) phenotype.

Genetic Modifiers of Duchenne Muscular Dystrophy

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