Evidence map›Paper›PMID 38625702›Full record

ArticleJAMA network open2024

Genetic Researchers' Use of and Interest in Research With Diverse Ancestral Groups.

Kaitlyn Jaffe, Amanda K Greene, Luyun Chen, Kerry A Ryan, Chris Krenz, J Scott Roberts, Brian J Zikmund-Fisher, Amy L McGuire, J Denard Thomas, Erica E Marsh and 1 more

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
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.

Kaitlyn JaffeDepartment of Health Promotion and Policy, University of Massachusetts, Amherst.
Amanda K GreeneCenter for Bioethics and Social Sciences in Medicine, University of Michigan Medical School, Ann Arbor.
Luyun ChenDepartment of Obstetrics and Gynecology, University of Michigan Medical School, Ann Arbor.
Kerry A RyanCenter for Bioethics and Social Sciences in Medicine, University of Michigan Medical School, Ann Arbor.
Chris KrenzCenter for Bioethics and Social Sciences in Medicine, University of Michigan Medical School, Ann Arbor.
J Scott RobertsCenter for Bioethics and Social Sciences in Medicine, University of Michigan Medical School, Ann Arbor.
Brian J Zikmund-FisherCenter for Bioethics and Social Sciences in Medicine, University of Michigan Medical School, Ann Arbor.
Amy L McGuireCenter for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, Texas.
J Denard ThomasCenter for Bioethics and Social Sciences in Medicine, University of Michigan Medical School, Ann Arbor.
Erica E MarshDepartment of Obstetrics and Gynecology, University of Michigan Medical School, Ann Arbor.
Kayte Spector-BagdadyCenter for Bioethics and Social Sciences in Medicine, University of Michigan Medical School, Ann Arbor.

Funding

Michigan Institute for Clinical and Health Research (MICHR)UM1TR004404 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Julie C Lumeng · 2023 to 2026
$39.8M
The Sulston Project: making the knowledge commons for interpreting cancer genomic variants more effectiveR01CA237118 · NCI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI COOK-DEEGAN, ROBERT MULLAN, MCGUIRE, AMY L · 2019 to 2022
$2.4M
Hospitals Sharing Patient Data and Biospecimens with Commercial Entities: Evidence-Based Translation to Improved PracticeR01TR004244 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SPECTOR-BAGDADY, KAYTE KELLEHER · 2022 to 2025
$1.9M
BRAINShare: Sharing Data in BRAIN Initiative StudiesR01MH126937 · NIMH · BAYLOR COLLEGE OF MEDICINE · PI MCGUIRE, AMY L, SHETH, SAMEER ANIL · 2021 to 2024
$1.8M
Genetic data partnerships: Enabling equitable access within academic/private data sharing agreementsK01HG010496 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SPECTOR-BAGDADY, KAYTE KELLEHER · 2019 to 2023
$875k
NCATS NIH HHS R01 TR004244NCATS NIH HHS UM1 TR004404NCI NIH HHS R01 CA237118NHGRI NIH HHS K01 HG010496NIMH NIH HHS R01 MH126937
6 · The paper itself

Abstract

Importance: Genetic researchers must have access to databases populated with data from diverse ancestral groups to ensure research is generalizable or targeted for historically excluded communities. Objective: To determine genetic researchers' interest in doing research with diverse ancestral populations, which database stewards offer adequate samples, and additional facilitators for use of diverse ancestral data. Design, Setting, and Participants: This survey study was conducted from June to December 2022 and was part of an exploratory sequential mixed-methods project in which previous qualitative results informed survey design. Eligible participants included genetic researchers who held US academic affiliations and conducted research using human genetic databases. Exposure: Internet-administered survey to genetic research professionals. Main Outcomes and Measures: The survey assessed respondents' experience and interest in research with diverse ancestral data, perceptions of adequacy of diverse data across database stewards (ie, private, government, or consortia), and identified facilitators for encouraging use of diverse ancestral data. Descriptive statistics, χ2 tests, and z tests were used to describe respondents' perspectives and experiences. Results: A total of 294 researchers (171 men [58.5%]; 121 women [41.2%]) were included in the study, resulting in a response rate of 20.4%. Across seniority level, 109 respondents (37.1%) were senior researchers, 85 (28.9%) were mid-level researchers, 71 (24.1%) were junior researchers, and 27 (9.2%) were trainees. Significantly more respondents worked with data from European ancestral populations (261 respondents [88.8%]) compared with any other ancestral population. Respondents who had not done research with Indigenous ancestral groups (210 respondents [71.4%]) were significantly more likely to report interest in doing so than not (121 respondents [41.2%] vs 89 respondents [30.3%]; P < .001). Respondents reported discrepancies in the adequacy of ancestral populations with significantly more reporting European samples as adequate across consortium (203 respondents [90.6%]), government (200 respondents [89.7%]), and private (42 respondents [80.8%]) databases, compared with any other ancestral population. There were no significant differences in reported adequacy of ancestral populations across database stewards. A majority of respondents without access to adequate diverse samples reported that increasing the ancestral diversity of existing databases (201 respondents [68.4%]) and increasing access to databases that are already diverse (166 respondents [56.5%]) would increase the likelihood of them using a more diverse sample. Conclusions and Relevance: In this survey study of US genetic researchers, respondents reported existing databases only provide adequate ancestral samples for European populations, despite their interest in other ancestral populations. These findings suggest there are specific gaps in access to and composition of genetic databases, highlighting the urgent need to boost diversity in research samples to improve inclusivity in genetic research practices.

Indexed as

GovernmentIndigenous PeoplesDatabases, FactualFemaleHumansInternetMaleProbability

Identifiers

PMID38625702
PMCPMC11022111

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.