Relation of type 2 diabetes to individual admixture and candidate gene polymorphisms in the Hispanic American population of San Luis Valley, Colorado

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Abstract
The possible relationship of type 2 diabetes risk to individual admixture proportions within Hispanic American populations complicates the interpretation of associations of type 2 diabetes with candidate gene polymorphisms within these populations. If admixture proportions vary between individuals (hidden population stratification) and the risk of type 2 diabetes varies with individual admixture proportions, this will confound allelic associations with type 2 diabetes at any loci where allele frequencies differ between Europeans and Native Americans. We have shown that in recently admixed populations associations are often observed between unlinked genetic markers.7–9 Thus, when carrying out association studies in admixed populations, it is necessary to control for possible confounding by population stratification. The classic approach to this has been to type parents as controls, but for a late onset disease such as type 2 diabetes parents of cases are not usually available for study. By typing ancestry informative markers, we can estimate individual admixture and control for it as a confounder. The most satisfactory approach to this is to fit a statistical model of population admixture, individual admixture, and the relationship of disease risk to individual admixture. Tests for allelic association with the disease can then be adjusted for the confounder. Although the statistical model is based on a straightforward application of the laws of mendelian genetics, to fit such a model in practice requires bayesian computationally intensive methods. We have developed a general purpose program (ADMIXMAP) for modelling admixture based on this approach, and have demonstrated the ability to distinguish associations of a trait with alleles at loci that are linked to a trait locus from associations with unlinked loci that are generated by population stratification.9,10 Where two or more loci in the same gene have been typed, the program can also model the unobserved haplotypes, given phase-unknown genotype data.

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