BMC Genomics (Jun 2021)

Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study

  • Yao Hu,
  • Stephanie A. Bien,
  • Katherine K. Nishimura,
  • Jeffrey Haessler,
  • Chani J. Hodonsky,
  • Antoine R. Baldassari,
  • Heather M. Highland,
  • Zhe Wang,
  • Michael Preuss,
  • Colleen M. Sitlani,
  • Genevieve L. Wojcik,
  • Ran Tao,
  • Mariaelisa Graff,
  • Laura M. Huckins,
  • Quan Sun,
  • Ming-Huei Chen,
  • Abdou Mousas,
  • Paul L. Auer,
  • Guillaume Lettre,
  • the Blood Cell Consortium,
  • Charles Kooperberg

Journal volume & issue
Vol. 22, no. 1
pp. 1 – 11


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Abstract Background Circulating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented. Results We performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance (P < 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance (P < 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations. Conclusions Our results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.