Genome sequencing of 35,024 predominantly African ancestry persons addresses gaps in genomics and healthcare
Avery, C.; Babanejad, M.; Baker, J.; Bledsoe, X.; Blostein, F.; Corty, R. W.; Ellis, K.; Hung, A. M.; Lake, A.; Shelley, J.; Sheng, Q.; Vanderbilt University Medical Center and Alliance for Genomic Discovery Investigators, ; Aldrich, M.; Basford, M.; Bastarache, L.; Below, J.; Bick, A. G.; Embi, P.; Feng, Q.; Gamazon, E.; Han, L.; HIRBO, J.; Marginean, K.; Mosley, J.; Pulley, J.; Roden, D. M.; Ruderfer, D. M.; Shuey, M.; Shyr, Y.; Stein, C. M.; Walsh, C.; Wilkins, C.
Show abstract
Genetic variation is crucial in human development, disease susceptibility, and drug response. Despite populations of African descent having the highest degree of genetic variation, genetic research has predominantly focused on populations of European descent, limiting potential for discovery. Recent studies of individuals with African ancestry have driven key medical advances benefiting all populations. Large scale, electronic health record (EHR) linked biobanks have provided opportunities to expand genetic research to larger and more diverse populations. We present initial results from the Alliance for Genomic Discovery (n = 35,024), in which 80% of participants have majority African ancestry, with genome sequencing and extensive phenotyping (median [~]10 years of EHR data). We demonstrate that genetic variants known to disproportionately cause disease in patients of African descent are under-documented in the medical record, including treatable genetic conditions such as transthyretin amyloidosis. Our findings confirm that many disease-associated genetic variants have consistent effects between groups with majority African and European ancestry, including common variation, structural variation, and clonal hematopoiesis of indeterminate potential. We discover novel variants associated with drug adverse events and diagnostic codes, powered by the increased frequency of these variants in individuals with majority African ancestry. Furthermore, we report independent effects of genetic risk and social factors on glycemic control in individuals with type 2 diabetes. Overall, this work highlights the value of integrating genome sequencing and deep phenotyping in genetically diverse populations to broaden our understanding of human health and disease.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Widespread recessive effects on common diseases in a cohort of 44,000 British Pakistanis and Bangladeshis with high autozygosity 97%
- Characterization of exome variants and their metabolic impact in 6,716 American Indians from Southwest US 96%
- Genetic association studies using disease liabilities from deep neural networks 96%
Similar papers in this journal
- A combined polygenic score of 21,293 rare and 22 common variants significantly improves diabetes diagnosis based on hemoglobin A1C levels 97%
- Genome-wide analysis in 756,646 individuals provides first genetic evidence that ACE2 expression influences COVID-19 risk and yields genetic risk scores predictive of severe disease 97%
- Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes 96%
Similar papers in this journal
- The impact of non-additive genetic associations on age-related complex diseases. 97%
- Common genetic variation associated with Mendelian disease severity revealed through cryptic phenotype analysis 96%
- Diagnostic Utility of Genome-wide DNA Methylation Analysis in Genetically Unsolved Developmental and Epileptic Encephalopathies and Refinement of a CHD2 Episignature 96%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.