Human Genetics

, Volume 119, Issue 6, pp 624–633 | Cite as

Racial admixture and its impact on BMI and blood pressure in African and Mexican Americans

  • Hua TangEmail author
  • Eric Jorgenson
  • Maya Gadde
  • Sharon L. R. Kardia
  • D. C. Rao
  • Xiaofeng Zhu
  • Nicholas J. Schork
  • Craig L. Hanis
  • Neil RischEmail author
Original Investigation


Admixed populations such as African Americans and Hispanic Americans present both challenges and opportunities in genetic epidemiologic research. Because of variation in admixture levels among individuals, case-control association studies may be subject to stratification bias. On the other hand, admixed populations also present special opportunities both for examining the role of genetic and environmental factors for observed racial/ethnic differences, and for possibly mapping alleles that contribute to such differences. Here we examined the distribution and relationship of individual admixture (IA) estimates with BMI and three measures of blood pressure in two admixed populations in the NHLBI Family Blood Pressure Program (FBPP): African Americans and Mexican Americans. For the African Americans, we observed modest but significant differences in average African IA among four recruitment sites. We observed a slight excess of African IA among hypertensives compared to normotensives, and a positive (non-significant) regression of African IA on blood pressure in untreated participants. Within Mexican Americans, we found no difference in average IA between hypertensives and normotensives, but a positive (marginally significant) regression of African IA on diastolic blood pressure. We also observed a significant positive regression of Caucasian IA (and negative regression of Native American IA) on BMI. Our results are suggestive of genetic differences between Africans and non-Africans that influence blood pressure, but such effects are likely to be modest compared to environmental ones. Excess obesity among Native Americans compared to whites is not consistent with a simple genetic explanation.


Mean Arterial Pressure Field Center African Ancestry Admix Population African American Participant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This investigation was based on data from the Family Blood Pressure Program (FBPP), which is supported by the National Heart, Lung, and Blood Institute. All authors are members of the FBPP. HT is supported by NIH R01GM073059.


  1. Almasy L, Blangero J (1998) Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet 62:1198–1211PubMedCrossRefGoogle Scholar
  2. Boerwinkle E, Brown CA, Carrejo M, Ferrell R, Hanis C, Hutchinson R et al (2002) Multi-center genetic study of hypertension—the family blood pressure program (FBPP). Hypertension 39:3–9CrossRefGoogle Scholar
  3. Burchard EG, Borrell LN, Choudhry S, Naqvi M, Tsai HJ, Rodriguez-Santana JR, Chapela R, Rogers SD, Mei R, Rodriguez-Cintron W, Arena JF, Kittles R, Perez-Stable EJ, Ziv E, Risch N (2005) Latino populations: a unique opportunity for the study of race, genetics, and social environment in epidemiological research. Am J Public Health 95:2161–2168CrossRefGoogle Scholar
  4. Burke GL, Bild DE, Hilner JE, Folsom AR, Wagenknecht LE, Sidney S (1996) Differences in weight gain in relation to race, gender, age and education in young adults: the CARDIA study. Coronary artery risk development in young adults. Ethn Health 1:327–335PubMedCrossRefGoogle Scholar
  5. Clarke CA, Wyn Edwards J, Haddock DRW, Howel-Evans AW, McConnell RB, Sheppard PM (1956) ABO blood groups and secretor character in duodenal ulcer. Br Med J 2:725–731PubMedCrossRefGoogle Scholar
  6. Falk CT, Rubinstein P (1987) Haplotype relative risks: an easy reliable way to construct a proper control sample for risk calculations. Ann Hum Genet 51:227–233PubMedCrossRefGoogle Scholar
  7. Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587PubMedGoogle Scholar
  8. Fernandez JR, Shriver MD, Beasley TM, Rafla-Demetrious N, Parra E, Albu J, Nicklas B, Ryan AS, McKeigue PM, Hoggart CL, Weinsier RL, Allison DB (2003) Association of African genetic admixture with resting metabolic rate and obesity among women. Obes Res 11:904–911PubMedCrossRefGoogle Scholar
  9. Freedman ML, Reich D, Penney KL, McDonald GJ, Mignault AA, Patterson N, Gabriel SB, Topol EJ, Smoller JW, Pato CN, Pato MT, Petryshen TL, Kolonel LN, Lander ES, Sklar P, Henderson B, Hirschhorn JN, Altshuler D (2004) Assessing the impact of population stratification on genetic association studies. Nat Genet 36:388–393PubMedCrossRefGoogle Scholar
  10. Hoggart CJ, Shriver MD, Kittles RA, Clayton DG, McKeigue PM (2004) Design and analysis of admixture mapping studies. Am J Hum Genet 74:965–978PubMedCrossRefGoogle Scholar
  11. Lander ES, Schork NJ (1994) Genetic dissection of complex traits. Science 265:2037–2048PubMedCrossRefGoogle Scholar
  12. McKeigue P (1997) Mapping genes underlying ethnic differences in disease risk by linkage disequilibrium in recently admixed populations. Am J Hum Genet 60:188–196PubMedGoogle Scholar
  13. Montana G, Pritchard JK (2004) Statistical tests for admixture mapping with case-control and cases-only data. Am J Hum Genet 75:771–789PubMedCrossRefGoogle Scholar
  14. Pankow JS, Province MA, Hunt SC, Arnett DK (2002) Regarding “Testing for population subdivision and association in four case-control studies”. Am J Hum Genet 71:1478–1480PubMedCrossRefGoogle Scholar
  15. Parra EJ, Marcini A, Akey J, Martinson J, Batzer MA, Cooper R, Forrester T, Allison DB, Deka R, Ferrell RE, Shriver MD (1998) Estimating African American admixture proportions by use of population-specific alleles. Am J Hum Genet 63:1839–1851PubMedCrossRefGoogle Scholar
  16. 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 74:979–1000PubMedCrossRefGoogle Scholar
  17. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedGoogle Scholar
  18. Reich D, Patterson N, De Jager PL, McDonald GJ, Waliszewska A, Tandon A, Lincoln RR, DeLoa C, Fruhan SA, Cabre P, Bera O, Semana G, Kelly MA, Francis DA, Ardlie K, Khan O, Cree BA, Hauser SL, Oksenberg JR, Hafler DA (2005) A whole-genome admixture scan finds a candidate locus for multiple sclerosis susceptibility. Nat Genet 37:1113–1118PubMedCrossRefGoogle Scholar
  19. Risch N (1992) Mapping genes for complex diseases using association studies with recently admixed populations. Am J Hum Genet Suppl 51:A13Google Scholar
  20. Risch N, Merikangas K (1996) The future of genetic studies of complex human diseaes. Science 273:1516–1517PubMedCrossRefGoogle Scholar
  21. Risch N, Teng J (1998) The relative power of family-based and case-control designs for linkage disequilibrium studies of complex human diseases. I. DNA pooling. Genome Res 8:1273–1288PubMedGoogle Scholar
  22. Rosenberg NA, Pritchard JK, Weber JL, Cann HM, Kidd KK, Zhivotovsky LA, Feldman MW (2002) Genetic structure of human populations. Science 298:2381–2385PubMedCrossRefGoogle Scholar
  23. Sachidanandam R, Weissman D, Schmidt SC, Kakol JM, Stein LD, Marth G et al (2001) A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms. Nature 409:928–933PubMedCrossRefGoogle Scholar
  24. Schaid DJ, Rowland C (1998) Use of parents, sibs, and unrelated controls for detection of associations between genetic markers and disease. Am J Hum Genet 63:1492–1506PubMedCrossRefGoogle Scholar
  25. 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 74:1001–1013PubMedCrossRefGoogle Scholar
  26. Sorel JE, Ragland DR, Syme SL (1991) Blood pressure in Mexican Americans, whites, and blacks. The second national health and nutrition examination survey and the hispanic health and nutrition examination survey. Am J Epidemiol 134:370–378PubMedGoogle Scholar
  27. Spielman RS, McGinnis RE, Ewens WJ (1993) Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am J Hum Genet 52:506–516PubMedGoogle Scholar
  28. Stephens JC, Briscoe D, O’Brien SJ (1994) Mapping by admixture linkage disequilibrium in human populations: limits and guidelines. Am J Hum Genet 55:809–824PubMedGoogle Scholar
  29. Tang H, Quertermous T, Rodriguez B, Kardia SL, Zhu X, Brown A, Pankow JS, Province MA, Hunt SC, Boerwinkle E, Schork NJ, Risch NJ (2005a) Genetic structure, self-identified race/ethnicity, and confounding in case-control association studies. Am J Hum Genet 76:268–275CrossRefGoogle Scholar
  30. Tang H, Peng J, Wang P, Risch NJ (2005b) Estimation of individual admixture: analytical and study design considerations. Genet Epidemiol 28:289–301CrossRefGoogle Scholar
  31. Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG et al (2001) The sequence of the human genome. Science 291:1304–1351PubMedCrossRefGoogle Scholar
  32. Williams RC, Long JC, Hanson RL, Sievers ML, Knowler WC (2000) Individual estimates of European genetic admixture associated with lower body-mass index, plasma glucose, and prevalence of type 2 diabetes in Pima Indians. Am J Hum Genet 66:527–538PubMedCrossRefGoogle Scholar
  33. Zhu X, Cooper RS, Elston RC (2004) Linkage analysis of a complex disease through use of admixed populations. Am J Hum Genet 74:1136–1153PubMedCrossRefGoogle Scholar
  34. 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 37:177–181PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Hua Tang
    • 1
    Email author
  • Eric Jorgenson
    • 2
  • Maya Gadde
    • 3
    • 10
  • Sharon L. R. Kardia
    • 4
  • D. C. Rao
    • 5
  • Xiaofeng Zhu
    • 6
  • Nicholas J. Schork
    • 7
  • Craig L. Hanis
    • 8
  • Neil Risch
    • 2
    • 9
    Email author
  1. 1.Division of Public Health SciencesFred Hutchinson Cancer Research CenterSeattleUSA
  2. 2.Institute for Human GeneticsUniversity of CaliforniaSan FranciscoUSA
  3. 3.Department of GeneticsStanford UniversityStanfordUSA
  4. 4.Department of EpidemiologyUniversity of Michigan School of Public HealthAnn ArborUSA
  5. 5.Division of BiostatisticsWashington UniversitySt. LouisUSA
  6. 6.Department of Preventive Medicine and EpidemiologyLoyola University Medical CenterMaywoodUSA
  7. 7.Department of PsychiatryUniversity of CaliforniaSan DiegoUSA
  8. 8.Department of GeneticsUniversity of TexasHoustonUSA
  9. 9.Division of ResearchKaiser PermanenteOaklandUSA
  10. 10.Netblue Inc.Mountain ViewUSA

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