Article in Diabetes care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.
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.
Emily DrzymallaDivision of Blood Disorders and Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA.ORCID 0009-0007-7258-3777
Laura RaffieldDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Katherine KolorDivision of Blood Disorders and Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA.
Alain KoyamaDivision of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA.ORCID 0000-0002-1246-2937
Ramal MoonesingheDivision of Blood Disorders and Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA.
Meda E PavkovDivision of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA.
Cassandra N SpracklenDepartment of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA.
Muin J KhouryDivision of Blood Disorders and Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA.
Funding
Technology to Empower Changes in Health (TECH) Network Participant Technologies CenterU24OD023176 · OD · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2016 to 2022
$204.7M
Precision Medicine Initiative Cohort Program BiobankU24OD023121 · OD · MAYO CLINIC ROCHESTER · PI CEKANOVA, MARIA, CICEK, MINE · 2016 to 2024
$185.5M
Enhancing All of Us Data Resources for Nutrition Precision Health: the All of Us Data and Research CenterU2COD023196 · OD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GLAZER, DAVID, HARRIS, PAUL A. · 2016 to 2022
$143.7M
Adaptive Platform for Personalized EngagementU24OD023163 · OD · VIGNET, INC. · PI JAIN, PRADUMAN · 2017 to 2020
$102.6M
University of Arizona-Banner Health All of Us Research Program OT2OD026549 · OD · UNIVERSITY OF ARIZONA · PI MORENO, FRANCISCO A, REIMAN, ERIC MICHAEL · 2018 to 2023
$78.9M
California Precision Medicine Research Program ConsortiumOT2OD026552 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANTON-CULVER, HODA A, OHNO-MACHADO, LUCILA · 2018 to 2023
$73.4M
All of Us PennsylvaniaOT2OD026554 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E, VISWESWARAN, SHYAM · 2018 to 2023
$72.1M
New York City Consortium for Precision MedicineOT2OD026556 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BIER, LOUISE E, GHARAVI, ALI G · 2018 to 2023
$67.3M
SouthEast Enrollment Center (SEEC) OT2OD026551 · OD · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CARRASQUILLO, OLVEEN, COLON, VIVIAN · 2018 to 2023
$62.8M
Southern All of Us NetworkOT2OD026548 · OD · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI FOUAD, MONA N., KORF, BRUCE R · 2018 to 2023
$60.5M
Illinois Precision Medicine Consortium OT2OD026557 · OD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI AHSAN, HABIBUL, ARGOS, MARIA · 2018 to 2023
$60.5M
The New England Precision Medicine Consortium of the All of Us Research ProgramOT2OD026553 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI CLARK, CHERYL RENEE, KARLSON, ELIZABETH W · 2018 to 2023
objectiveThe goal of this study was to assess the additive value of considering type 2 diabetes (T2D) polygenic risk score (PRS) in addition to family history for T2D prediction. RESEARCH DESIGN AND
methodsData were obtained from the All of Us (AoU) research database. First-degree T2D family history was self-reported on the personal family history health questionnaire. A PRS was constructed from 1,289 variants identified from a large multiancestry genome-wide association study meta-analysis for T2D. Logistic regression models were run to generate odds ratios (ORs) and 95% CIs for T2D. All models were adjusted for age, sex, and BMI.
resultsA total of 109,958 AoU research participants were included in the analysis. The odds of T2D increased with 1 SD PRS (OR 1.75; 95% CI 1.71-1.79) and positive T2D family history (OR 2.32; 95% CI 2.20-2.43). In the joint model, both 1 SD PRS (OR 1.69; 95% CI 1.65-1.72) and family history (OR 2.06; 95% CI 1.98-2.15) were significantly associated with T2D, although the ORs were slightly attenuated. Predictive models that included both the PRS and family history (area under the curve [AUC] 0.794) performed better than models including only family history (AUC 0.763) or the PRS (AUC 0.785).
conclusionsIn predicting T2D, inclusion of a T2D PRS in addition to family history of T2D (first-degree relatives) added statistical value. Further study is needed to determine whether consideration of both family history and a PRS would be useful for clinical T2D prediction.
Indexed as
Diabetes Mellitus, Type 2Multifactorial InheritanceAdultAgedFemaleGenetic Predisposition to DiseaseGenetic Risk ScoreGenome-Wide Association StudyHumansMaleMiddle AgedRisk FactorsUnited States
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.
Additive Value of Polygenic Risk Score to Family History for Type 2 Diabetes Prediction: Results From the All of Us Research Database. · full record | OpenQuestion