Evidence map›Paper›PMID 41555923›Full record

ArticleFrontiers in genetics2025

Monitoring diversity in genome-wide association studies requires measuring and reporting on immigration-related factors.

Yao Tu, Lindsay Fernandez-Rhodes

Abstract read
In one paragraph

Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Yao TuDepartment of Biobehavioral Health, College of Health and Human Development, Pennsylvania State University, University Park, PA, United States.
Lindsay Fernandez-RhodesDepartment of Biobehavioral Health, College of Health and Human Development, Pennsylvania State University, University Park, PA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have made remarkable progress to date in deciphering the genetic foundations of complex traits, yet persistent gaps remain in how sample heterogeneity is measured and reported. Current practices typically emphasize diversity by broad ancestry categories or stratification by country of recruitment, but these dimensions alone fail to capture the immigration-related factors that contribute to the genetic or environmental origins of heterogeneity. We argue that incorporating variables, such as country of origin, in descriptions and analyses provides essential context for interpreting genetic associations, particularly in increasingly multi-population and trans-national GWAS samples. We highlight how neglected these variables are in the literature using the GWAS Catalog. We provide suggestions for reporting on these data in future studies. By advocating for a more comprehensive view of diversity in GWAS, we aim to address the under-representation of immigrants in GWAS and thereby strengthen the validity and interpretability of future genomic studies.

Indexed as

Country of birthcountry of recruitmentdiversity and inclusionenvironmentgene-environment (G-E) interactiongenome-wide association studiesimmigration

Identifiers

PMID41555923
PMCPMC12812395

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.