Human MutationGenomicsPeer-reviewed journal article
The Clinical Imperative for Inclusivity: Race, Ethnicity, and Ancestry (REA) in Genomics
Alice B. PopejoyiD, Deborah RitteriD, Kristy CrooksiD, Erin CurreyiD, Stephanie Malia FullertoniD, Lucia A. HindorffiD, Barbara Ann KoenigiD, Erin M. RamosiD, Elena P. SorokiniD, Hannah WandiD, Matt W. WrightiD, James ZouiD, Christopher R. GignouxiD, Vence L. BonhamiD, Sharon E. PloniD, Carlos D. BustamanteiD
Abstract
The Clinical Genome Resource (ClinGen) Ancestry and Diversity Working Group highlights the need to develop guidance on race, ethnicity, and ancestry (REA) data collection and use in clinical genomics. We present quantitative and qualitative evidence to characterize: 1) acquisition of REA data via clinical laboratory requisition forms, and 2) information disparity across populations in the Genome Aggregation Database (gnomAD) at clinically relevant sites as determined by variants in ClinVar. Our requisition form analysis showed substantial heterogeneity in clinical laboratory ascertainment of REA, as well as marked incongruity among terms used to define REA categories. There was also striking disparity across REA populations in the amount of information available about variants at clinically relevant sites in gnomAD. European ancestral populations constituted the majority of observations (55.8%), allele counts (59.7%), and private alleles (56.1%) in gnomAD at 550 loci with \"pathogenic\" and \"likely pathogenic\" expert-reviewed variants in ClinVar. Our findings highlight the importance of implementing and supporting programs to increase diversity in genome sequencing and clinical genomics, as well as measuring uncertainty around population-level datasets that are used in variant interpretation. Finally, we suggest the need for a standardized REA data collection framework to be developed and adopted across clinical genomics.
- organism: human
- assay: whole-genome sequencing
- research focus: benchmarking
- approach: statistical model
- Citations
- 172
- FWCI
- 9.05
- Field percentile
- top 1%
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