Investigating the Genetic Landscape of Cerebral Palsy

PROJECT SUMMARY/ABSTRACT Cerebral palsy (CP) is the most common childhood-onset motor disability, affecting 764,000 individuals in the United States alone. The lifetime medical costs for a single individual with CP are estimated at $1.4M, which represents a substantial healthcare and economic impact. A diverse set of risk factors contributes to CP, including prematurity, intrauterine infection, and hypoxic ischemic encephalopathy. In approximately 20% of cases, there are no clear perinatal risk factors (“cryptogenic CP”). There is accumulating evidence from rare familial cases and a growing number of isolated cases suggesting that cryptogenic CP may result in part from single gene disorders, including over 50 treatable inborn errors of metabolism. However, these studies have involved small numbers of participants, with patient populations characterized using administrative data with limited attention to precise clinical characterization. The full breadth of the genetic landscape of CP is unknown. We hypothesize that a substantial portion of individuals with cryptogenic CP will have a pathogenic or likely pathogenic variant in a single gene providing an explanation for their symptoms. We propose rigorously phenotyping a large prospective cohort of individuals with both cryptogenic and non-cryptogenic CP who have undergone exome sequencing through an institutional genomics pilot study, and then analyzing exome sequencing data to determine the presence of single gene disorders in each subgroup. To accomplish these goals, we will classify patients as cryptogenic CP or non-cryptogenic CP. We will systematically, rigorously, and longitudinally characterize neurological, motor, communication, and neuroimaging phenotypes using research measures validated for CP. Next, we will analyze exome data using an institutional pipeline for variant interpretation. Finally, we will build a statistical model that correlates the presence of a genetic disorder with phenotypic measures in order to help predict which individuals with CP are most likely to have a single gene disorder. If applied to the population at large, the proposed work could lead to identification of single gene disorders in thousands of individuals with CP, including treatable conditions where a molecular diagnosis may positively alter a child's developmental trajectory. Determining etiology represents a first step in understanding the biological substrates of CP needed for developing rational therapeutics for this highly prevalent condition.