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Comparative Study
. 2003 Jun;72(6):1492-1504.
doi: 10.1086/375613.

Control of confounding of genetic associations in stratified populations

Clive J Hoggart  1 , Eteban J Parra, Mark D Shriver, Carolina Bonilla, Rick A Kittles, David G Clayton, Paul M McKeigue
Affiliations
Comparative Study

Control of confounding of genetic associations in stratified populations

Clive J Hoggart et al. Am J Hum Genet. 2003 Jun.

Abstract

To control for hidden population stratification in genetic-association studies, statistical methods that use marker genotype data to infer population structure have been proposed as a possible alternative to family-based designs. In principle, it is possible to infer population structure from associations between marker loci and from associations of markers with the trait, even when no information about the demographic background of the population is available. In a model in which the total population is formed by admixture between two or more subpopulations, confounding can be estimated and controlled. Current implementations of this approach have limitations, the most serious of which is that they do not allow for uncertainty in estimations of individual admixture proportions or for lack of identifiability of subpopulations in the model. We describe methods that overcome these limitations by a combination of Bayesian and classical approaches, and we demonstrate the methods by using data from three admixed populations--African American, African Caribbean, and Hispanic American--in which there is extreme confounding of trait-genotype associations because the trait under study (skin pigmentation) varies with admixture proportions. In these data sets, as many as one-third of marker loci show crude associations with the trait. Control for confounding by population stratification eliminates these associations, except at loci that are linked to candidate genes for the trait. With only 32 markers informative for ancestry, the efficiency of the analysis is 70%. These methods can deal with both confounding and selection bias in genetic-association studies, making family-based designs unnecessary.

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Figures

Figure 1
Figure 1
Directed graphical model for dependence-of-trait measurement and genotypes on admixture proportions and locus ancestry. Observed data (double-edged rectangles), stochastic nodes (ellipses), stochastic dependence (continuous arrows), and strata (single-edged rectangles) of individuals and loci, are shown.
Figure 2
Figure 2
Effect of adjustment for population stratification on P values for association with skin pigmentation in African American. Loci for which unadjusted associations are significant at P<.05 are shown as shaded squares.
Figure 3
Figure 3
Effect of adjustment for population stratification on P values for association with skin pigmentation in African Caribbeans. Loci for which unadjusted associations are significant at P<.05 are shown as shaded squares.
Figure 4
Figure 4
Effect of adjustment for population stratification on P values for association with skin reflectance in Hispanic Americans. Loci for which unadjusted associations are significant at P<.05 are shown as shaded squares.
See this image and copyright information in PMC

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References

Electronic-Database Information

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