Comparison of three methods to estimate genetic ancestry and control for stratification in genetic association studies among admixed populations (original) (raw)

Abstract

Population stratification may confound the results of genetic association studies among unrelated individuals from admixed populations. Several methods have been proposed to estimate the ancestral information in admixed populations and used to adjust the population stratification in genetic association tests. We evaluate the performances of three different methods: maximum likelihood estimation, ADMIXMAP and Structure through various simulated data sets and real data from Latino subjects participating in a genetic study of asthma. All three methods provide similar information on the accuracy of ancestral estimates and control type I error rate at an approximately similar rate. The most important factor in determining accuracy of the ancestry estimate and in minimizing type I error rate is the number of markers used to estimate ancestry. We demonstrate that approximately 100 ancestry informative markers (AIMs) are required to obtain estimates of ancestry that correlate with correlation coefficients more than 0.9 with the true individual ancestral proportions. In addition, after accounting for the ancestry information in association tests, the excess of type I error rate is controlled at the 5% level when 100 markers are used to estimate ancestry. However, since the effect of admixture on the type I error rate worsens with sample size, the accuracy of ancestry estimates also needs to increase to make the appropriate correction. Using data from the Latino subjects, we also apply these methods to an association study between body mass index and 44 AIMs. These simulations are meant to provide some practical guidelines for investigators conducting association studies in admixed populations.

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Acknowledgements

Financial support was received from HL07185, GM61390, American Lung Association of California, RWJ Amos Medical Faculty Development Award, NCMHD Health Disparities Scholar, Extramural Clinical Research Loan Repayment Program for Individuals from Disadvantaged Backgrounds, 2001–2003, to Esteban González Burchard, K22CA109351, from the NIH, CRTG 02-0841-CCE from the American Cancer Society, and BCRP030551 from the Department of Defense to Elad Ziv, U19AG23122 from NIH to Steven Cummings, HL51823, HL074204, 3M01RR000083-38S30488, HL56443 and HL51831 to the Asthma Clinical Research Network, U01-CA86117, SFGH General Clinical Research Center M01RR00083-41, U01-HL 65899, UCSF-Children’s Hospital of Oakland Pediatric Clinical Research Center (M01 RR01271), Oakland, CA, Sandler Center for Basic Research in Asthma and the Sandler Family Supporting Foundation. The authors would like to acknowledge the families and the patients for their participation. The authors would also like to thank the numerous health care providers and community clinics for their support and participation in the GALA Study. In addition to the primary clinical centers of the investigators, participating community clinics and hospitals include: La Clinica de La Raza, Oakland, CA; UCSF-Children’s Hospital of Oakland Pediatric Clinical Research Center, Oakland, CA; General Clinical Research Center, SFGH, San Francisco, CA; Alliance Medical Center, Healdsburg, CA; Santa Clara Valley Medical Center, San José, CA; Fair Oaks Family Health Center, Redwood City, CA; Clinica de Salud del Valle de Salinas, Salinas, CA; Natividad Medical Center, Salinas, CA; Asthma Education and Management Program, Community Medical Centers, Fresno, CA., Diagnostic Health Centers of: Corozal, Naranjito, Catano, Orocovis, Barranquitas and San Antonio Hospital of Mayaguez. The authors would also like to acknowledge Monica Toscano, MariaElena Alioto, Ivan Gomez, Henry Matallana, Carmen Jimenez, Yannett Marcano, Pedro Yapor, Alma Ortiz, Lisandra Perez and Sheila Gonzalez for their assistance with recruitment and study organization. The authors would like to especially thank Dr. Jeffrey M. Drazen, Dr. Ed Silverman, Dr. Homer A. Boushey, Dr. Dean Shepaprd, Dr. Sylvette Nazario, Dr. Jesus Casal, Dr. Alfonso Torres, Dr. Jose Rodriguez-Santana, Dr. Rocio Chapella, Dr. Scott Weiss, and Dr. Jean G. Ford for all of their effort towards the creation of the GALA Study and to Dr. Mark D. Shriver for assistance in development of the AIMs and for providing ancestral DNA.

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Authors and Affiliations

1. Department of Medicine, University of California, Box 0833, San Francisco, CA, 94143-0833, USA
   Hui-Ju Tsai, Shweta Choudhry, Mariam Naqvi, Esteban González Burchard & Elad Ziv
2. Lung Biology Center, San Francisco General Hospital, San Francisco, CA, USA
   Hui-Ju Tsai, Shweta Choudhry, Mariam Naqvi & Esteban González Burchard
3. Center for Human Genetics, University of California, San Francisco, CA, USA
   Esteban González Burchard & Elad Ziv
4. San Juan VAMC, University of Puerto Rico School of Medicine, San Juan, PR, USA
   William Rodriguez-Cintron

Authors

1. Hui-Ju Tsai
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2. Shweta Choudhry
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3. Mariam Naqvi
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4. William Rodriguez-Cintron
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5. Esteban González Burchard
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6. Elad Ziv
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Correspondence toHui-Ju Tsai.

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Esteban González Burchard and Elad Ziv contributed equally to this manuscript.

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Tsai, HJ., Choudhry, S., Naqvi, M. et al. Comparison of three methods to estimate genetic ancestry and control for stratification in genetic association studies among admixed populations.Hum Genet 118, 424–433 (2005). https://doi.org/10.1007/s00439-005-0067-z

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• Received: 01 June 2005
• Accepted: 10 August 2005
• Published: 06 October 2005
• Issue Date: December 2005
• DOI: https://doi.org/10.1007/s00439-005-0067-z

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