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The clinical imperative for inclusivity: Race, ethnicity, and ancestry (REA) in genomics.

Alice B PopejoyDeborah I RitterKristy CrooksErin CurreyStephanie M FullertonLucia A HindorffBarbara KoenigErin M RamosElena P SorokinHannah WandMathew W WrightJames ZouChristopher R GignouxVence L BonhamSharon E PlonCarlos D Bustamantenull null
Published in: Human mutation (2019)
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 ascertained from annotations 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 clinically relevant variants 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 through partnerships and collaborations and adopted across clinical genomics.
Keyphrases
  • single cell
  • emergency department
  • public health
  • systematic review
  • big data
  • electronic health record
  • genome wide
  • rna seq
  • health information
  • clinical practice
  • global health
  • genetic diversity