Evidence map›Paper›PMID 42465418›Full record

ArticlebioRxiv : the preprint server for biology2026

Recommendations for the ethical and accurate use of population descriptors: a trainee-led survey of early-career researchers.

Jayati Sharma, Betzaida Maldonado, Rachel Ungar, Alvina Adimoelja, J P Flores, Tamara Gjorgjieva, Krystin Jones, Alyna Khan, Diane Xue, Roshni Patel and 1 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. 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
–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

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

11 authors.

Jayati SharmaDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, MD, 21205.ORCID 0000-0002-4084-8319
Betzaida MaldonadoUniversity of Colorado Anschutz, Department of Biomedical Informatics, Aurora, CO 80045.
Rachel UngarStanford Center for Biomedical Ethics, Stanford School of Medicine, Stanford University, Stanford, CA, 94305.ORCID 0000-0002-2214-959X
Alvina AdimoeljaDepartment of Genetics, Stanford School of Medicine, Stanford CA 94305.ORCID 0000-0003-2340-6663
J P FloresCurriculum in Bioinformatics & Computational Biology, Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599.ORCID 0000-0001-5619-8990
Tamara GjorgjievaDepartment of Genetics, Stanford School of Medicine, Stanford CA 94305.
Krystin JonesDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, MD, 21205.
Alyna KhanSchool of Engineering, Design, and Innovation, Pennsylvania State University, University Park, PA, 16802.
Diane XueDepartment of Genetics, University of Pennsylvania, Philadelphia, PA 19104.
Roshni PatelDepartment of Data Science, University of Oregon, Eugene, OR 97403.ORCID 0000-0002-8574-031X
Christa CaggianoInstitute for Genomic Health, Icahn School of Medicine at Mt. Sinai, New York, NY, 10029.ORCID 0000-0001-5755-1274

Funding

Evaluation of Polygenic Risk Scores as a Valid Instrument to Conduct Mendelian Randomization in Diverse Ancestry PopulationsF31HG013440 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI SHARMA, JAYATI · 2024 to 2024
$49k
NHGRI NIH HHS F31 HG013440NHGRI NIH HHS F32 HG014400
6 · The paper itself

Abstract

Despite the importance of population descriptors in human genomics research, many scientists struggle to translate evolving ethical guidelines into their computational workflows. To characterize this gap between recommendations and implementation, we conducted a mixed-methods survey of early-career researchers to assess how they understand and implement the landmark 2023 NASEM report on the use of population descriptors in human genetics research. We show that while exposure to the report fosters ethical awareness, fundamental misconceptions about race and ancestry persist across academic disciplines, and trainees face structural bottlenecks, including legacy data constraints and a lack of technical confidence. To address this gap, we offer actionable, stakeholder-specific recommendations across the research lifecycle ranging from decision-support tools to "bring-your-own-data" workshops to leadership from academic journals, scientific societies, and trainee mentors. Ultimately, we argue that to promote scientific rigor and reduce bias in genetic discoveries, the scientific ecosystem must invest in the infrastructure necessary to empower the next generation of researchers.

Identifiers

PMID42465418
PMCPMC13371038

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.