Abstract
As genome-wide association studies expand beyond populations of European ancestry, the role of admixture will become increasingly important in the continued discovery and fine-mapping of variation influencing complex traits. Although admixture is commonly viewed as a confounding influence in association studies, approaches such as admixture mapping have demonstrated its ability to highlight disease susceptibility regions of the genome. In this study, we illustrate a powerful two-stage testing strategy designed to uncover trait-associated single nucleotide polymorphisms in the presence of ancestral allele frequency differentiation. In the first stage, we conduct an association scan by using predicted genotypic values based on regional admixture estimates. We then select a subset of promising markers for inclusion in a second-stage analysis, where association is tested between the observed genotype and the phenotype conditional on the predicted genotype. We prove that, under the null hypothesis, the test statistics used in each stage are orthogonal and asymptotically independent. Using simulated data designed to mimic African-American populations in the case of a quantitative trait, we show that our two-stage procedure maintains appropriate control of the family wise error rate and has higher power under realistic effect sizes than the one-stage testing procedure in which all markers are tested for association simultaneously with control of admixture. We apply the proposed procedure to a study of height in 201 African-Americans genotyped at 108 ancestry informative markers. The two-stage procedure identified two statistically significant markers rs1985080 (PTHB1/BBS9) and rs952718 (ABCA12). PTHB1/BBS9 is downregulated by parathyroid hormone in osteoblastic cells and is thought to be involved in parathyroid hormone action in bones and may play a role in height. ABCA12 is a member of the superfamily of ATP binding cassette transporters and its potential involvement in height is unclear.
Highlights
One of the major focuses of current genomics research is the expansion of association studies beyond populations of European and Asian descent, including African populations and admixed populations such as African-Americans and Hispanics
Using simulated data designed to mimic African-American populations in the case of a quantitative trait, we show that our two-stage procedure maintains appropriate control of the family wise error rate and has higher power under realistic effect sizes than the one-stage testing procedure in which all markers are tested for association simultaneously with control of admixture
family wise type I error rate (FWER) evaluation We estimated the FWER as the proportion of replicates in which at least one non-disease-associated single nucleotide polymorphisms (SNPs) was found to be significantly associated with the disease, under two situations: (1) under the null hypothesis that there is no SNP associated with the trait with and without confounding association by admixture and (2) under the non-complete null hypothesis, in which some ancestry SNPs are associated with the trait and the associations are confounded by admixture between these ancestry SNPs and the trait
Summary
One of the major focuses of current genomics research is the expansion of association studies beyond populations of European and Asian descent, including African populations and admixed populations such as African-Americans and Hispanics. These investigations carry several potential pitfalls such as greater haplotype diversity and lower levels of linkage disequilibrium (LD), one of the most well-known issues is the potential confounding influence of population stratification and admixture (Marchini et al, 2004; Smith et al, 2004; Teo et al, 2010). With the rapid cost decrease for platforms assaying potentially millions of single nucleotide polymorphisms (SNPs), the initial appeal of www.frontiersin.org
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