Investigating the Genetic Landscape of Cerebral Palsy

项目总结/摘要 脑性瘫痪（CP）是最常见的儿童期发作的运动障碍，影响764，000人 仅在美国。一个患有CP的个体的终身医疗费用估计为140万美元， 这代表了实质性的医疗保健和经济影响。多种风险因素导致CP， 包括早产、宫内感染和缺氧缺血性脑病。约20%的 例，没有明确的围产期危险因素（“隐源性CP”）。越来越多的证据表明 家族性病例和越来越多的孤立病例表明，隐源性CP可能部分由 单基因疾病，包括超过50种可治疗的先天性代谢缺陷。然而，这些研究 涉及少量参与者，患者人群使用管理数据进行表征， 对精确临床表征的关注有限。CP的遗传景观的全部宽度是 未知 我们假设，相当一部分隐源性CP患者将有致病性或 一个可能的致病性变异的单一基因提供了解释他们的症状。我们严格建议 表型分析一个大型的隐源性和非隐源性CP患者前瞻性队列， 通过机构基因组学试点研究进行外显子组测序，然后分析外显子组 测序数据，以确定每个亚组中单基因疾病的存在。 为了实现这些目标，我们将患者分类为隐源性CP或非隐源性CP。我们将 系统、严格和纵向表征神经、运动、通信和 神经影像学表型使用的研究措施验证CP。接下来，我们将使用 一个机构的管道，为不同的解释。最后，我们将建立一个统计模型， 存在遗传性疾病与表型措施，以帮助预测哪些个人与CP是 最有可能患有单基因疾病。 如果应用于整个人群，这项工作可能会导致单个基因的识别， 成千上万的CP患者的疾病，包括分子诊断可以治疗的疾病， 积极地改变孩子的发展轨迹。确定病因是了解 CP的生物学基质需要为这种高度流行的疾病开发合理的治疗方法。

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.