Delays in diagnosis of Duchenne muscular dystrophy: An evaluation of genotypic and sociodemographic factors.

INTRODUCTION: In this study we investigate associations between genotypic and sociodemographic factors and the age of diagnosis of Duchenne muscular dystrophy (DMD). METHODS: Data were collected from the Duchenne Registry from 2007 to 2019, and then used to assess the impact genotype, race/ethnicity, neighborhood poverty levels, and other sociodemographics factors have on the age of diagnosis of DMD patients without a known family history, using univariate and multivariable linear regression. RESULTS: The mean age of diagnosis was 4.43 years. Non-Caucasian patients and patients from high-poverty neighborhoods were older at diagnosis (P < .01). Increased year of birth was associated with decreasing age of diagnosis (P < .001). Specific genetic mutation subtypes were associated with later ages of symptom onset and diagnosis (P = .005). DISCUSSION: After adjusting for genotype and year of birth, the average age of diagnosis was significantly later for traditionally at-risk patients.

Associations Between Self-Reported Behavioral and Learning Concerns and DMD Isoforms in Duchenne Muscular Dystrophy.

BACKGROUND: Duchenne muscular dystrophy (DMD) is an X-linked recessive neuromuscular disorder resulting from loss of dystrophin. In addition to its role in muscle, isoforms of dystrophin are expressed in different cell types of the brain, and DMD has been linked to language delays, behavioral abnormalities and learning disabilities. OBJECTIVE: To determine whether disruption of specific DMD isoforms, age, corticosteroid use, ambulation status, or country are associated with behavioral and/or learning concerns in DMD. METHODS: De-identified data were collected from the Duchenne Registry from 2007-2019. Females, patients with BMD, and those without genetic testing reports were excluded from the cohort. For the genetic analysis, patients were divided into four subgroups based on the location of their mutation and the predicted isoforms affected. Bivariate analysis was conducted using chi-square for categorical variables. Two multivariate logistic regressions were used to assess independent associations with behavioral and learning concerns, respectively, and to estimate the effect size of each variable. RESULTS: DMD mutations disrupting expression of Dp140 and Dp71 were associated with a higher likelihood of reported behavioral and learning concerns. Corticosteroid use, categorical age, and country were other factors associated with behavior and learning concerns. CONCLUSION: This data adds to our current understanding of DMD isoforms, their mutational consequence and impact on behavior and learning.