Measuring and using admixture to study the genetics of complex diseases.

Indrani Halder, Mark D. Shriver

Research output: Contribution to journalArticlepeer-review

74 Scopus citations


Admixture is an important evolutionary force that can and should be used in efforts to apply genomic data and technology to the study of complex disease genetics. Admixture linkage disequilibrium (ALD) is created by the process of admixture and, in recently admixed populations, extends for substantial distances (of the order of 10 to 20 cM). The amount of ALD generated depends on the level of admixture, ancestry information content of markers and the admixture dynamics of the population, and thus influences admixture mapping (AM). The authors discuss different models of admixture and how these can have an impact on the success of AM studies. Selection of markers is important, since markers informative for parental population ancestry are required and these are uncommon. Rarely does the process of admixture result in a population that is uniform for individual admixture levels, but instead there is substantial population stratification. This stratification can be understood as variation in individual admixtures and can be both a source of statistical power for ancestry--phenotype correlation studies as well as a confounder in causing false-positives in gene association studies. Methods to detect and control for stratification in case/control and AM studies are reviewed, along with recent studies showing individual ancestry--phenotype correlations. Using skin pigmentation as a model phenotype, implications of AM in complex disease gene mapping studies are discussed. Finally, the article discusses some limitations of this approach that should be considered when designing an effective AM study.

Original languageEnglish (US)
Pages (from-to)52-62
Number of pages11
JournalHuman genomics
Issue number1
StatePublished - Nov 2003

All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Molecular Biology
  • Genetics
  • Drug Discovery


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