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

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 v8 release also includes up to 15% of...

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Autores principales: Gay, Nicole R., Gloudemans, Michael, Antonio, Margaret L., Abell, Nathan S., Balliu, Brunilda, Park, YoSon, Martin, Alicia R., Musharoff, Shaila, Rao, Abhiram S., Aguet, François, Barbeira, Alvaro N., Bonazzola, Rodrigo, Hormozdiari, Farhad, Ardlie, Kristin G., Brown, Christopher D., Im, Hae Kyung, Lappalainen, Tuuli, Wen, Xiaoquan, Montgomery, Stephen B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7488497/
https://www.ncbi.nlm.nih.gov/pubmed/32912333
http://dx.doi.org/10.1186/s13059-020-02113-0
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author Gay, Nicole R.
Gloudemans, Michael
Antonio, Margaret L.
Abell, Nathan S.
Balliu, Brunilda
Park, YoSon
Martin, Alicia R.
Musharoff, Shaila
Rao, Abhiram S.
Aguet, François
Barbeira, Alvaro N.
Bonazzola, Rodrigo
Hormozdiari, Farhad
Ardlie, Kristin G.
Brown, Christopher D.
Im, Hae Kyung
Lappalainen, Tuuli
Wen, Xiaoquan
Montgomery, Stephen B.
author_facet Gay, Nicole R.
Gloudemans, Michael
Antonio, Margaret L.
Abell, Nathan S.
Balliu, Brunilda
Park, YoSon
Martin, Alicia R.
Musharoff, Shaila
Rao, Abhiram S.
Aguet, François
Barbeira, Alvaro N.
Bonazzola, Rodrigo
Hormozdiari, Farhad
Ardlie, Kristin G.
Brown, Christopher D.
Im, Hae Kyung
Lappalainen, Tuuli
Wen, Xiaoquan
Montgomery, Stephen B.
author_sort Gay, Nicole R.
collection PubMed
description 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 v8 release also includes up to 15% of individuals of non-European ancestry. Assessing ancestry-based adjustments in GTEx improves portability of this research across populations and further characterizes 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 seven 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 31 loci (0.02%) where a significant colocalization is called only with one eQTL ancestry adjustment method. Notably, both adjustments produce similar numbers of significant colocalizations within each of two different colocalization methods, COLOC and FINEMAP. Finally, we identify a small subset of eQTL-associated variants highly correlated with local ancestry, providing a resource to enhance functional follow-up. CONCLUSIONS: We provide a local ancestry map for admixed individuals in the GTEx v8 release and describe the impact of ancestry and admixture on gene expression, eQTLs, and GWAS colocalization. While the majority of the results are concordant between local and global ancestry-based adjustments, we identify distinct advantages and disadvantages to each approach.
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spelling pubmed-74884972020-09-15 Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx Gay, Nicole R. Gloudemans, Michael Antonio, Margaret L. Abell, Nathan S. Balliu, Brunilda Park, YoSon Martin, Alicia R. Musharoff, Shaila Rao, Abhiram S. Aguet, François Barbeira, Alvaro N. Bonazzola, Rodrigo Hormozdiari, Farhad Ardlie, Kristin G. Brown, Christopher D. Im, Hae Kyung Lappalainen, Tuuli Wen, Xiaoquan Montgomery, Stephen B. Genome Biol Research 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 v8 release also includes up to 15% of individuals of non-European ancestry. Assessing ancestry-based adjustments in GTEx improves portability of this research across populations and further characterizes 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 seven 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 31 loci (0.02%) where a significant colocalization is called only with one eQTL ancestry adjustment method. Notably, both adjustments produce similar numbers of significant colocalizations within each of two different colocalization methods, COLOC and FINEMAP. Finally, we identify a small subset of eQTL-associated variants highly correlated with local ancestry, providing a resource to enhance functional follow-up. CONCLUSIONS: We provide a local ancestry map for admixed individuals in the GTEx v8 release and describe the impact of ancestry and admixture on gene expression, eQTLs, and GWAS colocalization. While the majority of the results are concordant between local and global ancestry-based adjustments, we identify distinct advantages and disadvantages to each approach. BioMed Central 2020-09-11 /pmc/articles/PMC7488497/ /pubmed/32912333 http://dx.doi.org/10.1186/s13059-020-02113-0 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Gay, Nicole R.
Gloudemans, Michael
Antonio, Margaret L.
Abell, Nathan S.
Balliu, Brunilda
Park, YoSon
Martin, Alicia R.
Musharoff, Shaila
Rao, Abhiram S.
Aguet, François
Barbeira, Alvaro N.
Bonazzola, Rodrigo
Hormozdiari, Farhad
Ardlie, Kristin G.
Brown, Christopher D.
Im, Hae Kyung
Lappalainen, Tuuli
Wen, Xiaoquan
Montgomery, Stephen B.
Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
title Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
title_full Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
title_fullStr Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
title_full_unstemmed Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
title_short Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
title_sort impact of admixture and ancestry on eqtl analysis and gwas colocalization in gtex
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7488497/
https://www.ncbi.nlm.nih.gov/pubmed/32912333
http://dx.doi.org/10.1186/s13059-020-02113-0
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