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

T he prevalence of type 2 diabetes is higher in populations of Native American ancestry, and in Hispanic American populations formed by admixture between Europeans and Native Americans, than in populations of European ancestry. One approach to distinguishing between environmental and genetic explanations for this difference is to study the relationship of type 2 diabetes risk to individual admixture proportions (the proportions of an individual’s genome that are of European and Native American ancestry). With only a few markers informative for ancestry, it is possible to estimate the average admixture proportions of any Hispanic American population. In such analyses, it has been possible to demonstrate that the prevalence of type 2 diabetes in Hispanic Americans in the south western United States varies with the average Native American admixture proportion of these populations. In the Native American population of Gila River, Arizona, USA, European admixture is associated with lower prevalence of type 2 diabetes. However, it has not been possible to demonstrate an association of type 2 diabetes with individual admixture proportions within an Hispanic American population. To estimate the admixture proportions of an individual accurately requires a larger panel of markers: at least 40 markers with average frequency differentials of 0.6 are required to estimate the admixture of an individual with a standard error of no more than 0.1. It is now possible to identify relatively large numbers of such ancestry informative markers from data accumulating in the public domain. For this study we typed a panel of 21 markers chosen to have large differences in frequency between European, Native American, and West African ancestry. 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. 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. 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. In this paper, we evaluated the association of type 2 diabetes, fasting insulin, and body mass index (BMI) with polymorphisms in five candidate genes in a sample from the Hispanic American population of San Luis Valley, Colorado, USA. The candidate genes are calpain 10 (CAPN10), guanine nucleotide binding protein, beta polypeptide 3 (GNB3), Key points