Evidence map›Paper›PMID 42716946›Full record

ArticleNature communications2026

Large-scale admixture mapping in the All of Us Research Program improves the characterization of cross-population phenotypic differences.

Ravi Mandla, Zhuozheng Shi, Kangcheng Hou, Ying Wang, Georgia Mies, Alan J Aw, Sinead Cullina, Penn Medicine BioBank, Eimear Kenny, Iain Mathieson and 3 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Admixture mapping identifies complex trait associations with local ancestry in themedRxiv : the preprint server for health sciences · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Ravi Mandla *Graduate Program in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA. ravi.mandla@pennmedicine.upenn.edu.ORCID http://orcid.org/0000-0002-0782-0138
Zhuozheng Shi *Graduate Program in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA.
Kangcheng HouDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Ying WangAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.ORCID http://orcid.org/0000-0001-7808-6279
Georgia MiesGraduate Program in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0009-0003-2905-693X
Alan J AwDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0001-9455-7878
Sinead CullinaInstitute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Penn Medicine BioBank
Eimear KennyInstitute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID http://orcid.org/0000-0001-9198-759X
Iain MathiesonDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0002-4256-3982
Elizabeth G AtkinsonDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.ORCID http://orcid.org/0000-0002-6308-776X
Alicia R MartinAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.ORCID http://orcid.org/0000-0003-0241-3522
Bogdan PasaniucDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. bogdan.pasaniuc@pennmedicine.upenn.edu.ORCID http://orcid.org/0000-0002-0227-2056

Funding

Phenotypic Diversity in COVID-19UL1TR001878 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI FITZGERALD, GARRET A · 2016 to 2025
$102.4M
NCATS NIH HHS UL1 TR001878
6 · The paper itself

Abstract

Admixed individuals have been understudied in medical research largely due to their complex genetic ancestries. However, the consideration of admixture can identify ancestry-enriched genetic associations, delineating genetic underpinnings of cross-population phenotypic variation. Here, we performed admixture mapping in individuals with inferred admixture from African and European populations (N = 48,921). Across 22 traits, we identified 71 ancestry-trait associations, including loci where ancestral haplotypes explained phenotypic variation yet were missed by single-variant association testing due to their stricter multiple testing burden. One such locus where inferred local AFR ancestries are associated with increased hemoglobin A1c (HbA1c) was 12q14.3, highlighting its potential role in explaining differences between populations. Together, our results expand upon the phenotypic differences between populations and characterize loci where genetic ancestries play a critical role in the architecture of disease.

Indexed as

Genetics, PopulationAfrican PeopleBlack PeopleChromosome MappingEuropean PeopleGenome-Wide Association StudyHaplotypesHumansPhenotypePolymorphism, Single NucleotideQuantitative Trait LociWhite People

Identifiers

PMID42716946
PMCPMC13558699

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Registered trials

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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.