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Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx

View ORCID ProfileNicole R. Gay, Michael Gloudemans, Margaret L. Antonio, Brunilda Balliu, YoSon Park, Alicia R. Martin, Shaila Musharoff, Abhiram Rao, François Aguet, Alvaro Barbeira, Rodrigo Bonazzola, Farhad Hormozdiari, GTEx Consortium, Kristin G. Ardlie, Christopher D. Brown, Hae Kyung Im, Tuuli Lappalainen, Xiaoquan Wen, Stephen B. Montgomery
doi: https://doi.org/10.1101/836825
Nicole R. Gay
1Department of Genetics, Stanford University, Stanford, California, USA
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Michael Gloudemans
2Biomedical Informatics, Stanford University, Stanford, California, USA
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Margaret L. Antonio
2Biomedical Informatics, Stanford University, Stanford, California, USA
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Brunilda Balliu
3Department of Biomathematics, University of California, Los Angeles, Los Angeles, CA, USA
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YoSon Park
4Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
5Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
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Alicia R. Martin
6Analytic and Translational Genetics Unit, Massachusetts General Hospital, MA, USA
7Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA
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Shaila Musharoff
1Department of Genetics, Stanford University, Stanford, California, USA
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Abhiram Rao
8Department of Bioengineering, Stanford University, Stanford, California, USA
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François Aguet
9The Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Alvaro Barbeira
10Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
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Rodrigo Bonazzola
10Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
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Farhad Hormozdiari
11Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
9The Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Kristin G. Ardlie
9The Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Christopher D. Brown
4Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
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Hae Kyung Im
10Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
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Tuuli Lappalainen
9The Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Xiaoquan Wen
12Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
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Stephen B. Montgomery
13Department of Pathology, Stanford University, Stanford, California, USA
1Department of Genetics, Stanford University, Stanford, California, USA
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  • For correspondence: smontgom@stanford.edu
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Abstract

Background Population structure among study subjects may confound genetic association studies, and lack of proper correction can lead to spurious findings. The Genotype-Tissue Expression (GTEx) project largely contains individuals of European ancestry, but the final release (v8) also includes up to 15% of individuals of non-European ancestry. Assessing ancestry-based adjustments in GTEx provides an opportunity to improve portability of this research across populations and to further measure the impact of population structure on GWAS colocalization.

Results Here, we identify a subset of 117 individuals in GTEx (v8) with a high degree of population admixture and estimate genome-wide local ancestry. We perform genome-wide cis-eQTL mapping using admixed samples in six tissues, adjusted by either global or local ancestry. Consistent with previous work, we observe improved power with local ancestry adjustment. At loci where the two adjustments produce different lead variants, we observe only 0.8% of tests with GWAS colocalization posterior probabilities that change by 10% or more. Notably, both adjustments produce similar numbers of significant colocalizations. Finally, we identify a small subset of GTEx v8 eQTL-associated variants highly correlated with local ancestry (R2 > 0.7), providing a resource to enhance functional follow-up.

Conclusions We provide a local ancestry map for admixed individuals in the final GTEx release and describe the impact of ancestry and admixture on gene expression, eQTLs, and GWAS colocalization. While the majority of results are concordant between local and global ancestry-based adjustments, we identify distinct advantages and disadvantages to each approach.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted November 09, 2019.
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Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
Nicole R. Gay, Michael Gloudemans, Margaret L. Antonio, Brunilda Balliu, YoSon Park, Alicia R. Martin, Shaila Musharoff, Abhiram Rao, François Aguet, Alvaro Barbeira, Rodrigo Bonazzola, Farhad Hormozdiari, GTEx Consortium, Kristin G. Ardlie, Christopher D. Brown, Hae Kyung Im, Tuuli Lappalainen, Xiaoquan Wen, Stephen B. Montgomery
bioRxiv 836825; doi: https://doi.org/10.1101/836825
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Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
Nicole R. Gay, Michael Gloudemans, Margaret L. Antonio, Brunilda Balliu, YoSon Park, Alicia R. Martin, Shaila Musharoff, Abhiram Rao, François Aguet, Alvaro Barbeira, Rodrigo Bonazzola, Farhad Hormozdiari, GTEx Consortium, Kristin G. Ardlie, Christopher D. Brown, Hae Kyung Im, Tuuli Lappalainen, Xiaoquan Wen, Stephen B. Montgomery
bioRxiv 836825; doi: https://doi.org/10.1101/836825

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