Improving Genetic Diagnosis for African Ancestry Populations

NIH Pandemic-Era Grants

Pandemic Era Grants

2024

Document text

Principal Investigator: Anne  O'Donnell-Luria
Organization: BROAD INSTITUTE, INC.
Fiscal Year: 2024
Award: $651,581
Funding agency: National Human Genome Research Institute

People in the United States (US) who are of African ancestry face medical genetic health disparities. They are less likely to receive accurate genetic diagnoses and face longer diagnostic odysseys, particularly for neurodevelopmental disorders such as Rubinstein-Taybi syndrome and epileptic encephalopathies. These disparities reflect the composition of large genetic databases like gnomAD, in which only 14% of individuals have some African ancestry. Should this remain the case, scientific understanding of population structure, evolution, selection signatures, and genetic discovery endeavors, will be less likely to succeed. Here, we will use data from gnomAD, NeuroDev and NeuroGAP-Psychosis to address this scientific gap and to improve medical genetic and diagnostic pipelines in US African ancestry populations (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 medical characterization of rare genetic disorders in East African individuals to date (Aim 3). In a collaborative analysis, we will compare the phenotypic profiles of NDK cases and cases from the Deciphering Developmental Disorders in 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 in the US and internationally (Aim 4).

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