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Originally published as Genetics Published Articles Ahead of Print on April 2, 2006.

Genetics, Vol. 173, 1665-1678, July 2006, Copyright © 2006
doi:10.1534/genetics.105.055335

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A General Population-Genetic Model for the Production by Population Structure of Spurious Genotype–Phenotype Associations in Discrete, Admixed or Spatially Distributed Populations

Noah A. Rosenberg*,1 and Magnus Nordborg{dagger}

* Department of Human Genetics, Bioinformatics Program and the Life Sciences Institute, University of Michigan, Ann Arbor, Michigan 48109-2218 and {dagger} Department of Biological Sciences, University of Southern California, Los Angeles, California 90089-2910

1 Corresponding author: Department of Human Genetics, Bioinformatics Program and the Life Sciences Institute, University of Michigan, 2017 Palmer Commons, 100 Washtenaw Ave., Ann Arbor, MI 48109-2218.
E-mail: rnoah{at}umich.edu

In linkage disequilibrium mapping of genetic variants causally associated with phenotypes, spurious associations can potentially be generated by any of a variety of types of population structure. However, mathematical theory of the production of spurious associations has largely been restricted to population structure models that involve the sampling of individuals from a collection of discrete subpopulations. Here, we introduce a general model of spurious association in structured populations, appropriate whether the population structure involves discrete groups, admixture among such groups, or continuous variation across space. Under the assumptions of the model, we find that a single common principle—applicable to both the discrete and admixed settings as well as to spatial populations—gives a necessary and sufficient condition for the occurrence of spurious associations. Using a mathematical connection between the discrete and admixed cases, we show that in admixed populations, spurious associations are less severe than in corresponding mixtures of discrete subpopulations, especially when the variance of admixture across individuals is small. This observation, together with the results of simulations that examine the relative influences of various model parameters, has important implications for the design and analysis of genetic association studies in structured populations.




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