Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies
Document Type
Journal Article
Publication Date
10-3-2019
Journal
American Journal of Human Genetics
Volume
105
Issue
4
DOI
10.1016/j.ajhg.2019.08.012
Keywords
biobank; ethnicity-specific trait loci; genetic ancestry; multi-ethnic cohort; self-reported race/ethnicity; stratified analysis; trans-ethnic GWAS
Abstract
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.
APA Citation
Fang, H., Hui, Q., Lynch, J., Honerlaw, J., Assimes, T., Huang, J., Vujkovic, M., Damrauer, S., Pyarajan, S., Gaziano, J., DuVall, S., O'Donnell, C., Cho, K., Chang, K., Wilson, P., Tsao, P., Ramoni, R., Breeling, J., Huang, G., Muralidhar, S., Moser, J., Whitbourne, S., Brewer, J., Concato, J., Warren, S., Argyres, D., Stephens, B., Brophy, M., Humphries, D., Do, N., Shayan, S., & Nguyen, X. (2019). Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies. American Journal of Human Genetics, 105 (4). http://dx.doi.org/10.1016/j.ajhg.2019.08.012