Evidence map›Paper›PMID 32912333›Full record

ArticleGenome biology2020

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

Nicole R Gay, Michael Gloudemans, Margaret L Antonio, Nathan S Abell, Brunilda Balliu, YoSon Park, Alicia R Martin, Shaila Musharoff, Abhiram S Rao, François Aguet and 10 more

Abstract read
In one paragraph

Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

73 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. A Functional Variant ofJournal of asthma and allergy · 2026
    Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. [Multi-omics analysis of the relationship between oxidative stress-related gene and prostate cancer].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2025
    Article
  20. Article

13 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Nicole R GayDepartment of Genetics, Stanford University, Stanford, CA, USA.
Michael GloudemansBiomedical Informatics, Stanford University, Stanford, CA, USA.
Margaret L AntonioBiomedical Informatics, Stanford University, Stanford, CA, USA.
Nathan S AbellDepartment of Genetics, Stanford University, Stanford, CA, USA.
Brunilda BalliuDepartment of Biomathematics, University of California, Los Angeles, Los Angeles, CA, USA.
YoSon ParkDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Alicia R MartinAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
Shaila MusharoffDepartment of Genetics, Stanford University, Stanford, CA, USA.
Abhiram S RaoDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
François AguetThe Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Alvaro N BarbeiraSection of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.
Rodrigo BonazzolaSection of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.
Farhad HormozdiariThe Broad Institute of MIT and Harvard, Cambridge, MA, USA.
GTEx Consortium
Kristin G ArdlieThe Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Christopher D BrownDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Hae Kyung ImSection of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.
Tuuli LappalainenNew York Genome Center, New York, NY, USA.
Xiaoquan WenDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Stephen B MontgomeryDepartment of Genetics, Stanford University, Stanford, CA, USA. smontgom@stanford.edu.ORCID 0000-0002-5200-3903

Funding

INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2M
Pilot and Feasibility ProgramP30DK020595 · NIDDK · UNIVERSITY OF CHICAGO · PI GRAEME I BELL · 2013 to 2026
$20.9M
Optimizing imputation for diverse populations in a distributed frameworkU01HG009080 · NHGRI · STANFORD UNIVERSITY · PI KENNY, EIMEAR ELIZABETH · 2016 to 2020
$5.2M
Decoding the regulatory architecture of the human genome across cell types, individuals and diseaseU01HG009431 · NHGRI · STANFORD UNIVERSITY · PI PRITCHARD, JONATHAN K · 2017 to 2021
$3.5M
Network-based algorithms for target identification and drug repositioning from genetic associationsR01HG010067 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI GREENE, CASEY S · 2018 to 2022
$3.2M
Predicting causal non-coding variants in a founder populationR01HG008150 · NHGRI · STANFORD UNIVERSITY · PI MONTGOMERY, STEPHEN · 2015 to 2017
$1.4M
Integrative multi-omics in whole genome studies of HLBS disordersR01HL142015 · NHLBI · STANFORD UNIVERSITY · PI MONTGOMERY, STEPHEN · 2018 to 2019
$882k
Generalizing polygenic risk prediction methods across populations for insights into psychiatric diseaseR00MH117229 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI MARTIN, ALICIA · 2020 to 2022
$724k
Generalizing polygenic risk prediction methods across populations for insights into psychiatric diseaseK99MH117229 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI MARTIN, ALICIA · 2018 to 2019
$262k
NHGRI NIH HHS 5T32HG000044-22NHGRI NIH HHS R01 HG010067NHGRI NIH HHS R01HG010067NHGRI NIH HHS T32 HG000044NHGRI NIH HHS U01 HG009431NIDDK NIH HHS P30 DK020595NIH HHS R01HG008150NIH HHS R01HL142015NIH HHS U01HG009080NIH HHS U01HG009431NIMH NIH HHS K99 MH117229NIMH NIH HHS R00 MH117229
6 · The paper itself

Abstract

backgroundPopulation 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.

resultsHere, 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.

conclusionsWe 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.

Indexed as

Genome, HumanGenome-Wide Association StudyQuantitative Trait LociGene ExpressionGenotypeHumansRacial GroupsAdmixtureColocalizationeQTLGene expressionGTExLocal ancestryPopulation structure

Identifiers

PMID32912333
PMCPMC7488497

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.