Evidence map›Paper›PMID 36604111›Full record

ArticleBMJ open diabetes research & care2023

Rachel G Miller, Josyf C Mychaleckyj, Suna Onengut-Gumuscu, Trevor J Orchard, Tina Costacou

Open access · goldAbstract read
In one paragraph

Article in BMJ open diabetes research & care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
5.8field-weighted citation impact, top 3% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

  1. Pooled it
  2. Metformin Alone and in Combinations Alter the Methylation Patterns ofEndocrine, metabolic & immune disorders drug targets · 2026
    Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Integrated multiomic analyses: An approach to improve understanding of diabetic kidney disease.Diabetic medicine : a journal of the British Diabetic Association · 2025
    Review
  9. Review
  10. Update: the role of epigenetics in the metabolic memory of diabetic complications.American journal of physiology. Renal physiology · 2024
    Review
  11. Article
  12. Article
  13. Article
  14. 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

5 authors at 2 institutions in 1 country.

Rachel G MillerDepartment of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA MillerR@edc.pitt.edu.ORCID 0000-0003-1845-8477
Josyf C MychaleckyjCenter for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA.
Suna Onengut-GumuscuCenter for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA.
Trevor J OrchardDepartment of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Tina CostacouDepartment of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
University of Pittsburgh · USUniversity of Virginia · US

Funding

EPIDEMIOLOGY OF DIABETIC COMPLICATIONS--PHASE IIR01DK034818 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI COSTACOU, TINA · 1986 to 2019
$5.6M
NIDDK NIH HHS R01 DK034818
6 · The paper itself

Abstract

introductionDNA methylation (DNAme) has been cross-sectionally associated with type 2 diabetes and hemoglobin A1c (HbA1c) in the general population. However, longitudinal data and data in type 1 diabetes are currently very limited. Thus, we performed an epigenome-wide association study (EWAS) in an observational type 1 diabetes cohort to identify loci with DNAme associated with concurrent and future HbA1cs, as well as other clinical risk factors, over 28 years. RESEARCH DESIGN AND

methodsWhole blood DNAme in 683 597 CpGs was analyzed in the Pittsburgh Epidemiology of Diabetes Complications study of childhood onset (<17 years) type 1 diabetes (n=411). An EWAS of DNAme beta values and concurrent HbA1c was performed using linear models adjusted for diabetes duration, sex, pack years of smoking, estimated cell type composition variables, and technical/batch covariates. A longitudinal EWAS of subsequent repeated HbA1c measures was performed using mixed models. We further identified methylation quantitative trait loci (meQTLs) for significant CpGs and conducted a Mendelian randomization.

resultsDNAme at cg19693031 (Chr 1,

conclusionsOur results extend prior findings that

Indexed as

Diabetes ComplicationsDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2Carrier ProteinsDNA MethylationEpigenesis, GeneticGlycated HemoglobinGlycemic ControlHumansCarrier ProteinsGlycated HemoglobinTXNIP protein, humanCohort StudiesDiabetes Mellitus, Type 1EpidemiologyHbA1c

Identifiers

PMID36604111
PMCPMC9827189
OpenAlexW4313557900

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.