Abstract
Several disease-mapping methods have been proposed recently, which use the information generated by recent admixture of populations from historically distinct geographic origins. These methods include both classic likelihood and Bayesian approaches. In this study we directly maximize the likelihood function from the hidden Markov Model for admixture mapping using the EM algorithm, allowing for uncertainty in model parameters, such as the allele frequencies in the parental populations. We determined the robustness of the proposed method by examining the ancestral allele frequency estimate and individual marker-location specific ancestry when the data were generated by different population admixture models and no learning sample was used. The proposed method outperforms a widely used Bayesian MCMC strategy for data generated from various population admixture models. The multipoint information content for ancestry was derived based on the map provided by Smith et al. (2004) and the associated statistical power was calculated. We examined the distribution of admixture LD across the genome for both real and simulated data and established a threshold for genome wide significance applicable to admixture mapping studies. The software ADMIXPROGRAM for performing admixture mapping is available from authors.
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References
Altshuler D, Brooks LD, Chakravarti A, Collins FS, Daly MJ, Donnelly P, The International HapMap Consortium (2006) A haplotype map of the human genome. Nature. 437:1299–320
Carlson CS, Eberle MA, Rieder MJ, Yi Q, Kruglyak L, Nickerson DA (2004) Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. Am J Hum Genet 74:106–120
Chakraborty R, Weiss KM (1988) Admixture as a tool for finding linked genes and detecting that difference from allelic association between loci. Proc Natl Acad Sci USA 85:9119–9123
Cohen J, Pertsemlidis A, Kotowski IK, Graham R, Garcia CK, Hobbs HH (2005) Low LDL cholesterol in individuals of African descent resulting from frequent nonsense mutations in PCSK9. Nat Genet 37:161–165
Collins-Schramm HE, Phillips CM, Operario DJ, Lee JS, Weber JL, Hanson RL, Knowler WC, Cooper R, Li H, Seldin MF (2002) Ethnic-difference markers for use in mapping by admixture linkage disequilibrium. Am J Hum Genet 70:737–750
Cover TM, Thomas JA (1991) Elements of information theory. Wiley, New York
Devlin B, Roeder K (1999) Genomic control for association studies. Biometrics 55:997–1004
Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587
Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M, Lochner A, Faggart M, Liu-Cordero SN, Rotimi C, Adeyemo A, Cooper R, Ward R, Lander ES, Daly MJ, Altshuler D (2002) The structure of haplotype blocks in the human genome. Science 296:2225–2229
Halder I, Shriver MD (2003) Measuring and using admixture to study thegenetics of complex disease. Human Genomic 1:52–62
Hoggart CJ, Parra EJ, Shriver MD, Bonilla C, Kittles RA, Clayton DG, McKeigue PM (2003) Control of confounding of genetic associations in stratified populations. Am J Hum Genet 72:1492–1504
Hoggart CJ, Shriver MD, Kittles RA, Clayton DG, McKeigue PM (2004) Design and analysis of admixture mapping studies. Am J Hum Genet 74:965–978
Kaplan NL, Martin ER, Morris RW, Weir BS (1998) Marker selection for the transmission/disequilibrium test, in recently admixed populations. Am J Hum Genet 62:703–712
Kruglyak L, Lander ES (1995) Complete multipoint sib-pair analysis of qualitative and quantitative traits. Am J Hum Genet 57:439–454
Lander ES, Green P (1987) Construction of multilocus genetic linkage maps in humans. Proc Natl Acad Sci USA 84:2363–2367
Lautenberger JA, Stephens JC, O’Brien SJ, Smith MW (2000) Significant admixture linkage disequilibrium across 30 cM around the FY locus in African Americans. Am J Hum Genet 66:969–978
McKeigue PM (1997) Mapping genes underlying ethnic differences in disease risk by linkage disequilibrium in recently admixed populations. Am J Hum Genet 60:188–196
McKeigue PM (1998) Mapping genes that underlie ethnic differences in disease risk: methods for detecting linkage in admixed populations, by conditioning on parental admixture. Am J Hum Genet 63:241–251
McKeigue PM (2005) Prospects for admixture mapping of complex traits. Am J Hum Genet 76:1–7
McKeigue PM, Carpenter JR, Parra EJ, Shriver MD (2000) Estimation of admixture and detection of linkage in admixed populations by a Bayesian approach: application to African–American populations. Ann Hum Genet 64:171–186
McPeek MS, Sun L (2000) Statistical tests for detection of misspecified relationships by use of genome-screen data. Am J Hum Genet 66:1076–1094
Montana G, Pritchard JK (2004) Statistical tests for admixture mapping with case-control and cases-only data. Am J Hum Genet 75:771–789
Patterson N, Hattangadi N, Lane B, Lohmueller KE, Hafler DA, Oksenberg JR, Hauser SL, Smith MW, O’Brien SJ, Altshuler D, Daly MJ, Reich D (2004) Methods for high-density admixture mapping of disease genes. Am J Hum Genet 74:979–1000
Pfaff CL, Parra EJ, Bonilla C, Hiester K, McKeigue PM, Kamboh MI, Hutchinson RG, Ferrell RE, Boerwinkle E, Shriver MD (2001) Population structure in admixed populations: effect of admixture dynamics on the pattern of linkage disequilibrium. Am J Hum Genet 68:198–207
Rife DC (1954) Populations of hybrid origin as source material for the detection of linkage. Am J Hum Genet 6:26–33
Risch N (1992) Mapping genes for complex disease using association studies with recently admixed populations. Am J Hum Genet 51(suppl):13
Risch NJ (2000) Searching for genetic determinants in the new millennium. Nature 405:847–856
Risch NJ, Merikangas K (1996) The future of genetic studies of complex human diseases. Science 273:1516–1517
Rosenberg NA, Li LM, Ward R, Pritchard JK (2003) Informativeness of genetic markers for inference of ancestry. Am J Hum Genet 73:1402–1422
Shriver MD, Parra EJ, Dios S, Bonilla C, Norton H, Jovel C, Pfaff C, Jones C, Massac A, Cameron N, Baron A, Jackson T, Argyropoulos G, Jin L, Hoggart CJ, McKeigue PM, Kittles RA (2003) Skin pigmentation, biogeographical ancestry and admixture mapping. Hum Genet 112:387–399
Smith MW, Lautenberger JA, Shin HD, Chretien JP, Shrestha S, Gilbert DA, O’Brien SJ (2001) Markers for mapping by admixture linkage disequilibrium in African American and Hispanic populations. Am J Hum Genet 69:1080–1094
Smith MW, Patterson N, Lautenberger JA, Truelove AL, McDonald GJ, Waliszewska A, Kessing BD, Malasky MJ, Scafe C, Le E, De Jager PL, Mignault AA, Yi Z, De The G, Essex M, Sankale JL, Moore JH, Poku K, Phair JP, Goedert JJ, Vlahov D, Williams SM, Tishkoff SA, Winkler CA, De La Vega FM, Woodage T, Sninsky JJ, Hafler DA, Altshuler D, Gilbert DA, O’Brien SJ, Reich D (2004) A high-density admixture map for disease gene discovery in african americans. Am J Hum Genet 74:1001–1013
Stephens JC, Briscoe D, O’Brien SJ (1994) Mapping by admixture linkage disequilibrium in human populations: limits and guidelines. Am J Hum Genet 55:809–824
Tang H, Peng J, Wang P, Risch NJ (2005) Estimation of individual admixture: Analytical and study design considerations. Genet Epidemiol 28:289–301
Tang H, Coram M, Wang P, Zhu X, Risch N (2006) Reconstructing genetic ancestry blocks in admixed individuals. Am J Hum Genet 79:1–12
Thomson G (1995) Mapping disease genes: family-based association studies. Am J Hum Genet 57:487–498
Victor RG, Haley RW, Willett DL, Peshock RM, Vaeth PC, Leonard D, Basit M, Cooper RS, Iannacchione VG, Visscher WA, Staab JM, Hobbs HH (2004) The Dallas Heart Study: a population-based probability sample for the multidisciplinary study of ethnic differences in cardiovascular health. Am J Cardiol 93:1473–1480
Zhang C, Chen K, Seldin MF, Li H (2004) A hidden Markov modeling approach for admixture mapping based on case-control data. Genet Epidemiol 27:225–239
Zhang SL, Sha Q, Zhu X (2006) Analytical correction for multiple testing in admixture mapping, including genome-scan. (submitted)
Zheng C, Elston RC (1999) Multipoint linkage disequilibrium mapping with particular reference to the African–American population. Genet Epidemiol 17:79–101
Zhu X, Cooper RS, Elston RC (2004) Linkage analysis of a complex disease through use of admixed populations. Am J Hum Genet 74:1136–1153
Zhu X, Luke A, Cooper RS, Quertermous T, Hanis C, Mosley T, Gu CC, Tang H, Rao DC, Risch N, Weder A (2005) Admixture mapping for hypertension loci with genome-scan markers. Nat Genet 37:177–181
Acknowledgments
This work was supported by grant from National Human Genome Research Institute (R01 HG003054, R03 HG 003613), Institute of General Medical Sciences (R01 GM069940, R01 GM073059), and the Donald W. Reynolds Clinical Cardiovascular Center at UT Southwestern, Dallas, TX. We thank the investigators of the Dallas Heart study and Jonathan Cohen for providing the data on the admixture panel.
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Zhu, X., Zhang, S., Tang, H. et al. A classical likelihood based approach for admixture mapping using EM algorithm. Hum Genet 120, 431–445 (2006). https://doi.org/10.1007/s00439-006-0224-z
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DOI: https://doi.org/10.1007/s00439-006-0224-z