Evidence mapPaperPMID 36040739Full record

SynthesisJAMA network open2022

Association of Genetic Predisposition and Physical Activity With Risk of Gestational Diabetes in Nulliparous Women.

Kymberleigh A Pagel, Hoyin Chu, Rashika Ramola, Rafael F Guerrero, Judith H Chung, Samuel Parry, Uma M Reddy, Robert M Silver, Jonathan G Steller, Lynn M Yee and 5 more

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

9 citing papers in PubMed, 18 citations in OpenAlex.

  1. Observational
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Using Association Rules to Understand the Risk of Adverse Pregnancy Outcomes in a Diverse Population.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2023
    Article
  9. Review
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

15 authors at 13 institutions in 1 country.

Kymberleigh A PagelDepartment of Computer Science, Indiana University, Bloomington.
Hoyin ChuKhoury College of Computer Sciences, Northeastern University, Boston, Massachusetts.
Rashika RamolaKhoury College of Computer Sciences, Northeastern University, Boston, Massachusetts.
Rafael F GuerreroDepartment of Biological Sciences, North Carolina State University, Raleigh.
Judith H ChungDepartment of Obstetrics and Gynecology, University of California, Irvine.
Samuel ParryDepartment of Obstetrics and Gynecology, University of Pennsylvania School of Medicine, Philadelphia.
Uma M ReddyDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale School of Medicine, Yale University, New Haven, Connecticut.
Robert M SilverDepartment of Obstetrics and Gynecology, University of Utah School of Medicine, Salt Lake City.
Jonathan G StellerDepartment of Obstetrics and Gynecology, University of California, Irvine.
Lynn M YeeDepartment of Obstetrics and Gynecology, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Ronald J WapnerCollege of Physicians and Surgeons, Columbia University, New York, New York.
Matthew W HahnDepartment of Computer Science, Indiana University, Bloomington.
Sriraam NatarajanDepartment of Computer Science, The University of Texas at Dallas.
David M HaasDepartment of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis.
Predrag RadivojacKhoury College of Computer Sciences, Northeastern University, Boston, Massachusetts.
Northeastern University · USUniversity of California, Irvine · USColumbia University · USDana-Farber Cancer Institute · USIndiana University Bloomington · USIndiana University School of MedicineJohns Hopkins University · USNorth Carolina State University · USNorthwestern University · USThe University of Texas at Dallas · USUniversity of Pennsylvania · USUniversity of Utah · USYale University · US

Funding

Yale Clinical and Translational Science AwardUL1TR001863 · YALE UNIVERSITY · 2025 to 2025
$9.9M
NCATS NIH HHS UL1 TR001863NICHD NIH HHS R01 HD101246
6 · The paper itself

Abstract

Importance: Polygenic risk scores (PRS) for type 2 diabetes (T2D) can improve risk prediction for gestational diabetes (GD), yet the strength of the association between genetic and lifestyle risk factors has not been quantified. Objective: To assess the association of PRS and physical activity in existing GD risk models and identify patient subgroups who may receive the most benefits from a PRS or physical activity intervention. Design, Settings, and Participants: The Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be cohort was established to study individuals without previous pregnancy lasting at least 20 weeks (nulliparous) and to elucidate factors associated with adverse pregnancy outcomes. A subcohort of 3533 participants with European ancestry was used for risk assessment and performance evaluation. Participants were enrolled from October 5, 2010, to December 3, 2013, and underwent genotyping between February 19, 2019, and February 28, 2020. Data were analyzed from September 15, 2020, to November 10, 2021. Exposures: Self-reported total physical activity in early pregnancy was quantified as metabolic equivalents of task (METs). Polygenic risk scores were calculated for T2D using contributions of 84 single nucleotide variants, weighted by their association in the Diabetes Genetics Replication and Meta-analysis Consortium data. Main Outcomes and Measures: Estimation of the development of GD from clinical, genetic, and environmental variables collected in early pregnancy, assessed using measures of model discrimination. Odds ratios and positive likelihood ratios were used to evaluate the association of PRS and physical activity with GD risk. Results: A total of 3533 women were included in this analysis (mean [SD] age, 28.6 [4.9] years). In high-risk population subgroups (body mass index ≥25 or aged ≥35 years), individuals with high PRS (top 25th percentile) or low activity levels (METs <450) had increased odds of a GD diagnosis of 25% to 75%. Compared with the general population, participants with both high PRS and low activity levels had higher odds of a GD diagnosis (odds ratio, 3.4 [95% CI, 2.3-5.3]), whereas participants with low PRS and high METs had significantly reduced risk of a GD diagnosis (odds ratio, 0.5 [95% CI, 0.3-0.9]; P = .01). Conclusions and Relevance: In this cohort study, the addition of PRS was associated with the stratified risk of GD diagnosis among high-risk patient subgroups, suggesting the benefits of targeted PRS ascertainment to encourage early intervention.

Indexed as

Diabetes, GestationalDiabetes Mellitus, Type 2AdultCohort StudiesExerciseFemaleGenetic Predisposition to DiseaseHumansPregnancy

Identifiers

PMID36040739
PMCPMC9428742
OpenAlexW4293572026

What Socratic 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 Socratic graph.