Improving Genetic Diagnosis for African Ancestry Populations

Broad Institute, Inc., Cambridge MA

Investigators

Abstract

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).