Improving Genetic Diagnosis for African Ancestry Populations

项目摘要 非洲血统的人在基因研究中的代表性严重不足，跨领域和 纪律。总体而言，这一点通过大型遗传数据库的构成最为明显，如在 只有14%的人有非洲血统。这些非洲血统中的绝大多数 个人是非裔美国人，最常见的是西非和欧洲血统的混合。 这意味着东非人口和生活在非洲大陆的其他非洲人甚至更远 到目前为止，在基因研究中的代表性不足。如果非洲血统的个人在基因上的代表性仍然不足 研究表明，他们将继续不太可能得到准确的基因诊断，也不太可能受益于 基因组医学研究进展。在这里，我们将使用gnomAD、NeuroDev和NeuroGAP-精神病的数据 解决这一代表性差距，并改善所有人的医学遗传和诊断管道 非洲血统类型(目标1)。管道改进将通过SEQR立即提供， 一个开放获取的分析平台，可在砧板上使用，供医学遗传学社区使用。我们会 对NeuroDev肯尼亚项目(NDK)的所有参与者进行基因特征分析，并使用这些数据测试和 改进这一渠道，为参与者确定基因诊断(目标2)。使用NDK的3小时数据 医学、认知和行为单元，我们将对稀有基因进行最大的表型表征 迄今东非个人的精神障碍(目标3)。正如NHGRI Atlas倡议所描述的那样，综合征 神经发育障碍在不同种族之间的表型表现往往不同。这个 相对常见的遗传性疾病(例如，DDX3X和22q11.2缺失综合征)的表现还没有 在非欧洲人群中表现得很好。在协作分析中，我们将比较表型 NDK病例概况和破译发育性疾病非洲研究的病例 在欧洲血统病例中观察到的遗传性疾病，如GeneReview和 G2MH网络。最后，这项工作产生的所有数据(例如，遗传数据、HPO术语)和算法将 公开提供，以便迅速改善非洲的医学遗传学研究和资源 社区(目标4)。

Project Summary People of African ancestry have been grossly underrepresented in genetic studies, across domains and disciplines. In aggregate, this is most visible through the constitution of large genetic databases like gnomAD, in which only 14% of individuals have some African ancestry. The great majority of those African-ancestry individuals are African American, and most commonly have a mixture of West African and European ancestry. This means that East African populations, and other Africans living on the African continent, are even further underrepresented in genetic studies to date. If African ancestry individuals remain underrepresented in genetic research, they will continue to be less likely to receive accurate genetic diagnoses and less likely to benefit from advances in genomic medicine. Here, we will use data from gnomAD, NeuroDev and NeuroGAP-Psychosis to address this representation gap and to improve medical genetic and diagnostic pipelines for individuals of all types of African ancestry (Aim 1). The pipeline improvements will be made immediately available through seqr, an open access analysis platform that is available on AnVIL for use by the medical genetics community. We will genetically characterize all participants from the NeuroDev Kenya project (NDK) and use this data to test and improve this pipeline and identify genetic diagnoses for participants (Aim 2). Using data from NDK’s 3 hour medical, cognitive and behavioral battery, we will conduct the largest phenotypic characterization of rare genetic disorders in East African individuals to date (Aim 3). As described by the NHGRI Atlas initiative, syndromic neurodevelopmental disorders often vary in their phenotypic presentation between ethnic groups. The presentations of relatively common genetic disorders (e.g. DDX3X and 22q11.2 deletion syndromes) have not been well characterized in non-European populations. In a collaborative analysis, we will compare the phenotypic profiles of NDK cases and cases from the Deciphering Developmental Disorders Africa study with common genetic disorders against those observed in European ancestry cases, as described in GeneReviews and the G2MH network. Lastly, all data (e.g. genetic data, HPO terms) and algorithms generated by this work will be made publicly available in order to rapidly improve medical genetics research and resources for African communities (Aim 4).