Evidence map›Paper›PMID 33664403›Full record

ArticleScientific reports2021

Quantifying genetic heterogeneity between continental populations for human height and body mass index.

Jing Guo, Andrew Bakshi, Ying Wang, Longda Jiang, Loic Yengo, Michael E Goddard, Peter M Visscher, Jian Yang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 5% of its field
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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Revisiting the Trans-Ancestry Genetic Correlation of Refractive Error.Investigative ophthalmology & visual science · 2025
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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

8 authors at 3 institutions in 2 countries.

Jing GuoInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Andrew BakshiMonash Partners Comprehensive Cancer Consortium, Monash Biomedicine Discovery Institute Cancer Program, Prostate Cancer Research Group, Department of Anatomy and Developmental Biology, Monash University, Clayton, VIC, 3800, Australia.
Ying WangInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Longda JiangInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Loic YengoInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Michael E GoddardFaculty of Veterinary and Agricultural Science, University of Melbourne, Parkville, VIC, Australia.
Peter M VisscherInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Jian YangInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia. jian.yang@westlake.edu.cn.
University of Queensland · AUUniversity of Melbourne · AUWellcome Sanger Institute · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWAS) in samples of European ancestry have identified thousands of genetic variants associated with complex traits in humans. However, it remains largely unclear whether these associations can be used in non-European populations. Here, we seek to quantify the proportion of genetic variation for a complex trait shared between continental populations. We estimated the between-population correlation of genetic effects at all SNPs ([Formula: see text]) or genome-wide significant SNPs ([Formula: see text]) for height and body mass index (BMI) in samples of European (EUR; [Formula: see text]) and African (AFR; [Formula: see text]) ancestry. The [Formula: see text] between EUR and AFR was 0.75 ([Formula: see text]) for height and 0.68 ([Formula: see text]) for BMI, and the corresponding [Formula: see text] was 0.82 ([Formula: see text]) for height and 0.87 ([Formula: see text]) for BMI, suggesting that a large proportion of GWAS findings discovered in Europeans are likely applicable to non-Europeans for height and BMI. There was no evidence that [Formula: see text] differs in SNP groups with different levels of between-population difference in allele frequency or linkage disequilibrium, which, however, can be due to the lack of power.

Indexed as

Body Mass IndexGenome-Wide Association StudyBlack PeopleBody HeightGene FrequencyGenetic HeterogeneityGenome, HumanHumansLinkage DisequilibriumModels, TheoreticalPolymorphism, Single NucleotideQuantitative Trait LociWhite People

Identifiers

PMID33664403
PMCPMC7933291
OpenAlexW3134871565

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.