Deep phenotyping of the central nervous system in Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is an X-linked, life-limiting muscle-wasting disorder caused by a loss of the protein dystrophin. Approximately half of DMD patients have cognitive and neurobehavioural symptoms, which can be related to mutation site. A mouse model of DMD (mdx) displays a central nervous system (CNS) phenotype, including increased fear responses. Abnormal neurodevelopment has been implicated in DMD pathogenesis, with white matter microstructural abnormalities and reduced grey matter volume on magnetic resonance imaging (MRI). Absence of dystrophin also causes functional abnormalities in the hippocampus, amygdala, and prefrontal cortex due to dysfunction in inhibitory GABA-ergic synapses; areas implicated in neurodevelopmental disorders, memory, emotional reactivity, and fear. Abnormal synaptic dysfunction and fear responses are reversed with dystrophin-restoration in mdx mice, thus raising the prospect of future trials for therapeutic interventions for which sensitive CNS outcome measures would be needed. In this doctoral thesis I have addressed two broad themes: 1) a deeper exploration of the DMD CNS phenotype and genotype-phenotype associations; 2) an evaluation of existing and novel CNS outcome measures. 1) I determined estimates of neurobehavioural co-morbidities in dystrophinopathies (DMD and Becker muscular dystrophy) in a systematic review and meta-analysis. I analysed neurobehavioural data from 140 DMD patients to further evaluate phenotype-genotype associations. I explored anxiety symptoms directly with DMD boys and their parents in a qualitative study and evaluated anxiety assessment instruments. 2) As fear, or startle, responses have not previously been studied in DMD, I developed a novel task to investigate physiological startle responses in a cohort of DMD and control boys, finding that they were indeed increased in DMD, and that the startle response could be a useful biomarker of dystrophin deficiency. Finally, I conducted an imaging study using advanced MRI techniques, and identified a diffusion imaging metric that could also be a useful CNS biomarker