Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies

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114 Scopus citations


Large-scale multi-ethnic cohorts offer unprecedented opportunities to elucidate the genetic factors influencing complex traits related to health and disease among minority populations. At the same time, the genetic diversity in these cohorts presents new challenges for analysis and interpretation. We consider the utility of race and/or ethnicity categories in genome-wide association studies (GWASs) of multi-ethnic cohorts. We demonstrate that race/ethnicity information enhances the ability to understand population-specific genetic architecture. To address the practical issue that self-identified racial/ethnic information may be incomplete, we propose a machine learning algorithm that produces a surrogate variable, termed HARE. We use height as a model trait to demonstrate the utility of HARE and ethnicity-specific GWASs.

Original languageEnglish (US)
Pages (from-to)763-772
Number of pages10
JournalAmerican Journal of Human Genetics
Issue number4
StatePublished - Oct 3 2019


  • biobank
  • ethnicity-specific trait loci
  • genetic ancestry
  • multi-ethnic cohort
  • self-reported race/ethnicity
  • stratified analysis
  • trans-ethnic GWAS

ASJC Scopus subject areas

  • Genetics(clinical)
  • Genetics


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