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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.
Afiliação
  • Gay NR; Department of Genetics, Stanford University, Stanford, CA, USA.
  • Gloudemans M; Biomedical Informatics, Stanford University, Stanford, CA, USA.
  • Antonio ML; Biomedical Informatics, Stanford University, Stanford, CA, USA.
  • Abell NS; Department of Genetics, Stanford University, Stanford, CA, USA.
  • Balliu B; Department of Biomathematics, University of California, Los Angeles, Los Angeles, CA, USA.
  • Park Y; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Martin AR; Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Musharoff S; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Rao AS; Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA.
  • Aguet F; Department of Genetics, Stanford University, Stanford, CA, USA.
  • Barbeira AN; Department of Bioengineering, Stanford University, Stanford, CA, USA.
  • Bonazzola R; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Hormozdiari F; Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.
  • Ardlie KG; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Brown CD; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Lappalainen T; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Wen X; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Montgomery SB; Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.
Genome Biol ; 21(1): 233, 2020 09 11.
Article em En | MEDLINE | ID: mdl-32912333
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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genoma Humano / Locos de Características Quantitativas / Grupos Raciais / Estudo de Associação Genômica Ampla Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article
Texto completo
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genoma Humano / Locos de Características Quantitativas / Grupos Raciais / Estudo de Associação Genômica Ampla Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article