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

Publication ,  Journal Article
Fang, H; Hui, Q; Lynch, J; Honerlaw, J; Assimes, TL; Huang, J; Vujkovic, M; Damrauer, SM; Pyarajan, S; Gaziano, JM; DuVall, SL; O'Donnell, CJ ...
Published in: Am J Hum Genet
October 3, 2019
Published version (DOI) Link to item

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.

Duke Scholars

Elizabeth Rebecca Hauser
Author Elizabeth Rebecca Hauser Biostatistics & Bioinformatics
Jean Crowell Beckham
Author Jean Crowell Beckham Psychiatry & Behavioral Sciences, Behavioral Medicine & Neur ...
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Published In

Am J Hum Genet

DOI

10.1016/j.ajhg.2019.08.012

EISSN

1537-6605

Publication Date

October 3, 2019

Volume

105

Issue

4

Start / End Page

763 / 772

Location

United States

Related Subject Headings

  • Support Vector Machine
  • Racial Groups
  • Machine Learning
  • Humans
  • Genome-Wide Association Study
  • Genetics & Heredity
  • Ethnicity
  • Algorithms
  • 42 Health sciences
  • 32 Biomedical and clinical sciences
 

Citation

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Fang, H., Hui, Q., Lynch, J., Honerlaw, J., Assimes, T. L., Huang, J., … Tang, H. (2019). Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies. Am J Hum Genet, 105(4), 763–772. https://doi.org/10.1016/j.ajhg.2019.08.012
Fang, Huaying, Qin Hui, Julie Lynch, Jacqueline Honerlaw, Themistocles L. Assimes, Jie Huang, Marijana Vujkovic, et al. “Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies.” Am J Hum Genet 105, no. 4 (October 3, 2019): 763–72. https://doi.org/10.1016/j.ajhg.2019.08.012.
Fang H, Hui Q, Lynch J, Honerlaw J, Assimes TL, Huang J, et al. Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies. Am J Hum Genet. 2019 Oct 3;105(4):763–72.
Fang, Huaying, et al. “Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies.” Am J Hum Genet, vol. 105, no. 4, Oct. 2019, pp. 763–72. Pubmed, doi:10.1016/j.ajhg.2019.08.012.
Fang H, Hui Q, Lynch J, Honerlaw J, Assimes TL, Huang J, Vujkovic M, Damrauer SM, Pyarajan S, Gaziano JM, DuVall SL, O’Donnell CJ, Cho K, Chang K-M, Wilson PWF, Tsao PS, VA Million Veteran Program, Sun YV, Tang H. Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies. Am J Hum Genet. 2019 Oct 3;105(4):763–772.
Journal cover image

Published In

Am J Hum Genet

DOI

10.1016/j.ajhg.2019.08.012

EISSN

1537-6605

Publication Date

October 3, 2019

Volume

105

Issue

4

Start / End Page

763 / 772

Location

United States

Related Subject Headings

  • Support Vector Machine
  • Racial Groups
  • Machine Learning
  • Humans
  • Genome-Wide Association Study
  • Genetics & Heredity
  • Ethnicity
  • Algorithms
  • 42 Health sciences
  • 32 Biomedical and clinical sciences