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

dc.contributor.authorGay, Nicole R.
dc.contributor.authorGloudemans, Michael
dc.contributor.authorAntonio, Margaret L.
dc.contributor.authorAbell, Nathan S.
dc.contributor.authorBalliu, Brunilda
dc.contributor.authorPark, YoSon
dc.contributor.authorMartin, Alicia R.
dc.contributor.authorMusharoff, Shaila
dc.contributor.authorRao, Abhiram S.
dc.contributor.authorAguet, François
dc.contributor.authorBarbeira, Alvaro N.
dc.contributor.authorBonazzola, Rodrigo
dc.contributor.authorHormozdiari, Farhad
dc.contributor.authorArdlie, Kristin G.
dc.contributor.authorBrown, Christopher D.
dc.contributor.authorIm, Hae K.
dc.contributor.authorLappalainen, Tuuli
dc.contributor.authorWen, Xiaoquan
dc.contributor.authorMontgomery, Stephen B.
dc.date.accessioned2022-08-10T18:36:03Z
dc.date.available2022-08-10T18:36:03Z
dc.date.issued2020-09-11
dc.identifier.citationGenome Biology. 2020 Sep 11;21(1):233
dc.identifier.urihttps://doi.org/10.1186/s13059-020-02113-0
dc.identifier.urihttps://hdl.handle.net/2027.42/173856en
dc.description.abstractAbstract 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.
dc.titleImpact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
dc.typeJournal Article
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/173856/1/13059_2020_Article_2113.pdf
dc.identifier.doihttps://dx.doi.org/10.7302/5587
dc.language.rfc3066en
dc.rights.holderThe Author(s)
dc.date.updated2022-08-10T18:36:02Z
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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