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Admixture-matched case-control study: a practical approach for genetic association studies in admixed populations
Authors:Hui-Ju Tsai  Jennifer Y. Kho  Nishat Shaikh  Shweta Choudhry  Mariam Naqvi  Daniel Navarro  Henry Matallana  Richard Castro  Craig M. Lilly  H. George Watson  Kelley Meade  Michael LeNoir  Shannon Thyne  Elad Ziv  Esteban González Burchard
Affiliation:(1) Department of Medicine, Study of African American, Asthma, Genes and Environments (SAGE), University of California, 0833, San Francisco, CA 94143-0833, USA;(2) Lung Biology Center, Study of African American, Asthma, Genes and Environments (SAGE), San Francisco General Hospital, San Francisco, CA, USA;(3) Center for Human Genetics, Study of African American, Asthma, Genes and Environments (SAGE), University of California, San Francisco, CA, USA;(4) Brigham and Women’s Hospital, Boston, MA, USA;(5) The James A. Watson Wellness Center, Oakland, CA, USA;(6) Children’s Hospital and Research Institute, Oakland, CA, USA;(7) Bay Area Pediatrics, Oakland, CA, USA
Abstract:Case-control genetic association studies in admixed populations are known to be susceptible to genetic confounding due to population stratification. The transmission/disequilibrium test (TDT) approach can avoid this problem. However, the TDT is expensive and impractical for late-onset diseases. Case-control study designs, in which, cases and controls are matched by admixture, can be an appealing and a suitable alternative for genetic association studies in admixed populations. In this study, we applied this matching strategy when recruiting our African American participants in the Study of African American, Asthma, Genes and Environments. Group admixture in this cohort consists of 83% African ancestry and 17% European ancestry, which was consistent with reports from other studies. By carrying out several complementary analyses, our results show that there is a substructure in the cohort, but that the admixture distributions are almost identical in cases and controls, and also in cases only. We performed association tests for asthma-related traits with ancestry, and only found that FEV(1), a measure for baseline pulmonary function, was associated with ancestry after adjusting for socio-economic and environmental risk factors (P=0.01). We did not observe an excess of type I error rate in our association tests for ancestry informative markers and asthma-related phenotypes when ancestry was not adjusted in the analyses. Furthermore, using the association tests between genetic variants in a known asthma candidate gene, beta(2) adrenergic receptor (beta(2)AR) and DeltaFEF(25-75), an asthma-related phenotype, as an example, we demonstrated population stratification was not a confounder in our genetic association. Our present work demonstrates that admixture-matched case-control strategies can efficiently control population stratification confounding in admixed populations.
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