PROJECT SUMMARY Medical management of children with genetically determined neurodevelopmental syndromes represents a significant public health burden. While these syndromes are individually rare, they are collectively common. Notably, sleep disturbances are some of the most prevalent co-occurring conditions in these patients. Sleep quantity and quality is evidenced to be important to neurodevelopment and metabolism. Untreated sleep disturbances may have long-term negative impacts on neurological function, quality of life and productivity. While many factors contribute to sleep problems in children with neurodevelopmental syndromes, effective treatment of these issues reduces severity of numerous other symptoms. This suggests that sleep is a modifiable risk factor that, when effectively managed, may improve health outcomes and quality of life for these patients and their families. Understanding the causes and consequences of sleep problems is crucial to identifying effective approaches to treatment of sleep disturbances. This study proposes to focus on elucidating the causes and consequences of sleep disturbances in children with Prader-Willi syndrome (PWS), a classical genetic condition and known cause of early-onset morbid obesity. This will be one of the first studies to use data derived from electronic health records (EHRs) to evaluate real-world clinical information collected in children with rare genetic syndromes. We will develop an approach to integrate multiple types of EHR-derived data to 1) define the types of sleep problems observed in children with PWS, 2) define the relationship between sleep disordered breathing, symptom severity and expression of other important comorbidities—like obesity—in PWS, and 3) determine if differences in the molecular genetic classes of PWS are associated with differences in expression of sleep disturbances. The proposed project offers unprecedented opportunity to improve our understanding of the relationship between sleep, neurodevelopment, obesity, and genetics in children. An approach for extracting objective sleep measures from sleep study reports and genetic information from genetic testing results will be established providing an avenue for identification of novel treatments of sleep disturbances in children with rare genetic defects.