Joint ancestry and association testing in admixed individuals.

For samples of admixed individuals, it is possible to test for both ancestry effects via admixture mapping and genotype effects via association mapping. Here, we describe a joint test called BMIX that combines admixture and association statistics at single markers. We first perform high-density admi...

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Main Authors: Daniel Shriner, Adebowale Adeyemo, Charles N Rotimi
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-12-01
Series:PLoS Computational Biology
Online Access:https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1002325&type=printable
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author Daniel Shriner
Adebowale Adeyemo
Charles N Rotimi
author_facet Daniel Shriner
Adebowale Adeyemo
Charles N Rotimi
author_sort Daniel Shriner
collection DOAJ
description For samples of admixed individuals, it is possible to test for both ancestry effects via admixture mapping and genotype effects via association mapping. Here, we describe a joint test called BMIX that combines admixture and association statistics at single markers. We first perform high-density admixture mapping using local ancestry. We then perform association mapping using stratified regression, wherein for each marker genotypes are stratified by local ancestry. In both stages, we use generalized linear models, providing the advantage that the joint test can be used with any phenotype distribution with an appropriate link function. To define the alternative densities for admixture mapping and association mapping, we describe a method based on autocorrelation to empirically estimate the testing burdens of admixture mapping and association mapping. We then describe a joint test that uses the posterior probabilities from admixture mapping as prior probabilities for association mapping, capitalizing on the reduced testing burden of admixture mapping relative to association mapping. By simulation, we show that BMIX is potentially orders-of-magnitude more powerful than the MIX score, which is currently the most powerful frequentist joint test. We illustrate the gain in power through analysis of fasting plasma glucose among 922 unrelated, non-diabetic, admixed African Americans from the Howard University Family Study. We detected loci at 1q24 and 6q26 as genome-wide significant via admixture mapping; both loci have been independently reported from linkage analysis. Using the association data, we resolved the 1q24 signal into two regions. One region, upstream of the gene FAM78B, contains three binding sites for the transcription factor PPARG and two binding sites for HNF1A, both previously implicated in the pathology of type 2 diabetes. The fact that both loci showed ancestry effects may provide novel insight into the genetic architecture of fasting plasma glucose in individuals of African ancestry.
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spelling doaj-art-88d7c791fcf04cf9aa8500c0a2e2838f2025-08-20T03:46:42ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582011-12-01712e100232510.1371/journal.pcbi.1002325Joint ancestry and association testing in admixed individuals.Daniel ShrinerAdebowale AdeyemoCharles N RotimiFor samples of admixed individuals, it is possible to test for both ancestry effects via admixture mapping and genotype effects via association mapping. Here, we describe a joint test called BMIX that combines admixture and association statistics at single markers. We first perform high-density admixture mapping using local ancestry. We then perform association mapping using stratified regression, wherein for each marker genotypes are stratified by local ancestry. In both stages, we use generalized linear models, providing the advantage that the joint test can be used with any phenotype distribution with an appropriate link function. To define the alternative densities for admixture mapping and association mapping, we describe a method based on autocorrelation to empirically estimate the testing burdens of admixture mapping and association mapping. We then describe a joint test that uses the posterior probabilities from admixture mapping as prior probabilities for association mapping, capitalizing on the reduced testing burden of admixture mapping relative to association mapping. By simulation, we show that BMIX is potentially orders-of-magnitude more powerful than the MIX score, which is currently the most powerful frequentist joint test. We illustrate the gain in power through analysis of fasting plasma glucose among 922 unrelated, non-diabetic, admixed African Americans from the Howard University Family Study. We detected loci at 1q24 and 6q26 as genome-wide significant via admixture mapping; both loci have been independently reported from linkage analysis. Using the association data, we resolved the 1q24 signal into two regions. One region, upstream of the gene FAM78B, contains three binding sites for the transcription factor PPARG and two binding sites for HNF1A, both previously implicated in the pathology of type 2 diabetes. The fact that both loci showed ancestry effects may provide novel insight into the genetic architecture of fasting plasma glucose in individuals of African ancestry.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1002325&type=printable
spellingShingle Daniel Shriner
Adebowale Adeyemo
Charles N Rotimi
Joint ancestry and association testing in admixed individuals.
PLoS Computational Biology
title Joint ancestry and association testing in admixed individuals.
title_full Joint ancestry and association testing in admixed individuals.
title_fullStr Joint ancestry and association testing in admixed individuals.
title_full_unstemmed Joint ancestry and association testing in admixed individuals.
title_short Joint ancestry and association testing in admixed individuals.
title_sort joint ancestry and association testing in admixed individuals
url https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1002325&type=printable
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AT adebowaleadeyemo jointancestryandassociationtestinginadmixedindividuals
AT charlesnrotimi jointancestryandassociationtestinginadmixedindividuals