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

2019; Elsevier BV; Volume: 105; Issue: 4 Linguagem: Inglês

10.1016/j.ajhg.2019.08.012

1537-6605

Huaying Fang, Qin Hui, Julie A. Lynch, Jacqueline Honerlaw, Themistocles L. Assimes, Jie Huang, Marijana Vujković, Scott M. Damrauer, Saiju Pyarajan, J. Michael Gaziano, Scott L. DuVall, Christopher J. O’Donnell, Kelly Cho, Kyong–Mi Chang, Peter W.F. Wilson, Philip S. Tsao, Yan V. Sun, Hua Tang, J. Michael Gaziano, Rachel Ramoni, Jim Breeling, Kyong–Mi Chang, Grant D. Huang, Sumitra Muralidhar, Christopher J. O’Donnell, Philip S. Tsao, Sumitra Muralidhar, Jennifer Moser, Stacey B. Whitbourne, Jessica V. Brewer, John Concato, Stuart Warren, Dean P. Argyres, Brady Stephens, Mary T. Brophy, Donald E. Humphries, Nhan Do, Shahpoor Shayan, Xuan‐Mai T. Nguyen, Saiju Pyarajan, Kelly Cho, Elizabeth R. Hauser, Yan V. Sun, Hongyu Zhao, Peter W.F. Wilson, Rachel McArdle, Louis J. Dell’Italia, John B. Harley, Jeff Whittle, Jean C. Beckham, John A. Wells, Salvador Gutierrez, Gretchen Gibson, Laurence S. Kaminsky, Gerardo Villareal, Scott Kinlay, Junzhe Xu, Mark B. Hamner, Kathlyn Sue Haddock, Sujata Bhushan, Pran Iruvanti, Michael Godschalk, Zuhair K. Ballas, Malcolm Buford, Stephen Mastorides, Jon Klein, Nora Ratcliffe, Hermes Flórez, Alan C. Swann, Maureen Murdoch, Peruvemba Sriram, Shing Shing Yeh, Ronald G. Washburn, Darshana Jhala, Samuel M. Aguayo, David Cohen, Satish Sharma, John Callaghan, Kris Ann Oursler, Mary A. Whooley, Sunil K. Ahuja, Amparo Gutierrez, Ronald Schifman, Jennifer Greco, Michael Rauchman, Richard J. Servatius, Mary E. Oehlert, Agnes Wallbom, Ronald Fernando, Timothy R. Morgan, Todd Stapley, Scott E. Sherman, Gwenevere Anderson, Elif Sonel, Edward J. Boyko, Laurence Meyer, Samir Gupta, Joseph Fayad, Adriana M. Hung, Jack Lichy, Robin A. Hurley, R. Brooks Robey, Rob Striker,

Genetic Mapping and Diversity in Plants and Animals

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. 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.