DMD/BMD - GENETICS: EP.116 Establishing clinical and genetic characteristics in young, glucocorticoid-naïve boys with Duchenne muscular dystrophy: the FOR DMD study

Abstract

We describe the clinical characteristics and genetic profile of a large sample of young glucocorticoid-naïve boys with Duchenne muscular dystrophy (DMD). Screening and baseline data were collected for participants in the FOR-DMD study, an international, multi-centre, randomized, double-blind clinical trial comparing 3 commonly prescribed glucocorticoid regimens in untreated DMD boys with a confirmed genetic diagnosis of DMD between 4 and < 8 years of age. One hundred ninety-six boys were recruited in the study. The mean age at randomization was 5.9 (standard deviation, SD 1 year). The most frequent mutation type was out of frame deletions (130/193, 67.3%) of which 68.5% (89/130) were amenable to exon skipping. Mutations amenable to exon 51 skipping were the most frequent (n=25). Stop codon mutations were reported in 19/193 boys (10%). The mean age of parental concern was 29.8 months (SD 18.7); the mean age of genetic diagnosis was 50.3 months (SD 23.8). The mean ages at independent walking and talking in sentences were 17.1 (SD 4.2) and 29.0 (SD 10.7) months, respectively. Pre-steroid median height and weight were below the 50th percentiles regardless of age group. Boys with exon 8 skippable deletions performed better in time to walk/run 10 meters compared to boys carrying other out of frame deletions not amenable to skipping (4.8±0.7 vs 6.3±4 seconds, p 0.001). Boys with exon 53 skippable deletions showed a lower baseline performance in the 6-minute walk test compared to boys with other out of frame deletions not amenable to skipping (308.9±61 vs 342±46 metres, p 0.003). In conclusion, this study describes clinical, genetic, and anthropometric characteristics of a sample of young glucocorticoid-naïve boys with DMD. Some genotype-phenotype associations were identified. These findings characterise a baseline pre-steroid cohort and, with the longitudinal data to follow, will help to inform eligibility criteria and outcome measures for future clinical trials in DMD.