Evidence map›Paper›PMID 34257098›Full record

ArticleDiabetes care2021

Genetic Risk Score for Type 2 Diabetes and Traits Related to Glucose-Insulin Homeostasis in Youth: The Exploring Perinatal Outcomes Among Children (EPOCH) Study.

Maggie A Stanislawski, Elizabeth Litkowski, Sridharan Raghavan, Kylie K Harrall, Jessica Shaw, Deborah H Glueck, Ethan M Lange, Dana Dabelea, Leslie A Lange

Open access · bronzeAbstract read
In one paragraph

Article in Diabetes care, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
3.0field-weighted citation impact, top 9% 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
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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

9 authors at 3 institutions in 1 country.

Maggie A StanislawskiDivision of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO maggie.stanislawski@cuanschutz.edu.ORCID 0000-0001-7768-8868
Elizabeth LitkowskiDivision of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO.
Sridharan RaghavanDivision of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO.ORCID 0000-0003-0643-4873
Kylie K HarrallDepartment of Epidemiology, University of Colorado School of Public Health, Aurora, CO.
Jessica ShawDepartment of Epidemiology, University of Colorado School of Public Health, Aurora, CO.
Deborah H GlueckDepartment of Epidemiology, University of Colorado School of Public Health, Aurora, CO.
Ethan M LangeDivision of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO.
Dana DabeleaDepartment of Epidemiology, University of Colorado School of Public Health, Aurora, CO.ORCID 0000-0001-9514-8929
Leslie A LangeDivision of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO.
Colorado School of Public Health · USUniversity of Colorado Denver · USUniversity of Colorado Hospital · US

Funding

PILOT STUDY--SUBSTRATE METABOLISM IN EXTREMELY LOW BIRTH WEIGHT INFANTSP30DK048520 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI Edward L Melanson · 1995 to 2026
$32.6M
University of Colorado Anschutz Medical Campus DRCP30DK116073 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI PETER J DEMPSEY · 2020 to 2026
$10.8M
Exploring the Fetal Origins Hypothesis in Diverse YouthR01DK068001 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI DABELEA, DANA · 2005 to 2015
$4.5M
The Contribution of Omic Profiles to Weight Loss and ObesityK01HL157658 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI Maggie A Stanislawski · 2022 to 2026
$794k
CSRD VA IK2 CX001907NHLBI NIH HHS K01 HL157658NIDDK NIH HHS P30 DK048520NIDDK NIH HHS P30 DK116073NIDDK NIH HHS R01 DK068001
6 · The paper itself

Abstract

objectiveThe metabolic phenotype of youth-onset type 2 diabetes (T2D) differs from that of adult-onset T2D, but little is known about genetic contributions. We aimed to evaluate the association between a T2D genetic risk score (GRS) and traits related to glucose-insulin homeostasis among healthy youth. RESEARCH DESIGN AND

methodsWe used data from 356 youth (mean age 16.7 years; 50% female) in the Exploring Perinatal Outcomes Among Children (EPOCH) cohort to calculate a standardized weighted GRS based on 271 single nucleotide polymorphisms associated with T2D in adults. We used linear regression to assess associations of the GRS with log-transformed fasting glucose, 2-h glucose, HOMA of insulin resistance (HOMA-IR), oral disposition index, and insulinogenic index adjusted for age, sex, BMI

resultsHigher weighted GRS was associated with lower oral disposition index (β = -0.11; 95% CI -0.19, -0.02) and insulinogenic index (β = -0.08; 95% CI -0.17, -0.001), but not with fasting glucose (β = 0.01; 95% CI -0.01, 0.02), 2-h glucose (β = 0.03; 95% CI -0.0004, 0.06), or HOMA-IR (β = 0.02; 95% CI -0.04, 0.07). BMI

conclusionsOur results suggest that T2D genetic risk factors established in adults are relevant to glucose-insulin homeostasis in youth and that maintaining a healthy weight may be particularly important for youth with high genetic risk of T2D.

Indexed as

Diabetes Mellitus, Type 2Insulin ResistanceAdolescentBlood GlucoseChildFemaleGlucoseHomeostasisHumansInsulinMalePhenotypePregnancyRisk FactorsBlood GlucoseGlucoseInsulin

Identifiers

PMID34257098
PMCPMC8740919
OpenAlexW3180369932

What OpenQuestion holds

Textmetadata
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.