Evidence map›Paper›PMID 35169870›Full record

SynthesisDiabetologia2022

Epigenome-wide association study of incident type 2 diabetes: a meta-analysis of five prospective European cohorts.

Eliza Fraszczyk, Annemieke M W Spijkerman, Yan Zhang, Stefan Brandmaier, Felix R Day, Li Zhou, Paul Wackers, Martijn E T Dollé, Vincent W Bloks, Xīn Gào and 16 more

Open access · greenAbstract readMeta-Analysis
In one paragraph

Synthesis in Diabetologia, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 2 pooled it
2.9field-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

47 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Observational
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Metformin Alone and in Combinations Alter the Methylation Patterns ofEndocrine, metabolic & immune disorders drug targets · 2026
    Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Estimating population structure using epigenome-wide methylation data.medRxiv : the preprint server for health sciences · 2025
    Article
  19. Review
  20. 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

26 authors at 14 institutions in 4 countries.

Eliza FraszczykDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Annemieke M W SpijkermanCentre for Nutrition, Prevention and Health services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
Yan ZhangDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany.
Stefan BrandmaierResearch Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.
Felix R DayMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
Li ZhouLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Paul WackersCentre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
Martijn E T DolléCentre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
Vincent W BloksDepartment of Pediatrics, Section of Molecular Metabolism and Nutrition, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Xīn GàoDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany.
Christian GiegerResearch Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.
Jaspal KoonerDepartment of Cardiology, Ealing Hospital, Ealing, UK.
Jennifer KriebelResearch Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.
H Susan J PicavetCentre for Nutrition, Prevention and Health services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
Wolfgang RathmannGerman Center for Diabetes Research (DZD), Neuherberg, Germany.
Ben SchöttkerDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany.
Marie LohLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
W M Monique VerschurenCentre for Nutrition, Prevention and Health services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
Jana V van Vliet-OstaptchoukGenomics Coordination Center, Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Nicholas J WarehamMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
John C ChambersLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Ken K OngMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
Harald GrallertResearch Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.
Hermann BrennerDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany.
Mirjam LuijtenCentre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands. mirjam.luijten@rivm.nl.
Harold SniederDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands. h.snieder@umcg.nl.
National Institute for Public Health and the Environment · NLDeutsches Diabetes-Zentrum e.V. · DEGerman Cancer Research Center · DEHeidelberg University · DENanyang Technological University · SGUniversity of Cambridge · GBUniversity of Groningen · NLEaling Hospital · GBGerman Center for Diabetes Research · DEHeinrich Heine University Düsseldorf · DEHelmholtz Zentrum München · DEImperial College London · GBMRC Epidemiology Unit · GBUniversity Medical Center Utrecht · NL

Funding

HBN-1 Regulated Hypothermia Formulation and Evaluation of ToxicityZIATR000028 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI ALIMARDANOV, ASAF · 2015 to 2019
$3.8M
Cancer Research UK 14136Cancer Research UK C864/A8257Department of Health 16/136/68Medical Research Council G0401527Medical Research Council G1000143Medical Research Council G9502233Medical Research Council MC_UU_00006/1Medical Research Council MC_UU_00006/2Medical Research Council MC_UU_12015/1Medical Research Council MC_UU_12015/2Medical Research Council MR/L00002/1Medical Research Council MR/N003284/1Medical Research Council MR/S019669/1Wellcome Trust 212945/Z/18/Z
6 · The paper itself

Abstract

aims/hypothesisType 2 diabetes is a complex metabolic disease with increasing prevalence worldwide. Improving the prediction of incident type 2 diabetes using epigenetic markers could help tailor prevention efforts to those at the highest risk. The aim of this study was to identify predictive methylation markers for incident type 2 diabetes by combining epigenome-wide association study (EWAS) results from five prospective European cohorts.

methodsWe conducted a meta-analysis of EWASs in blood collected 7-10 years prior to type 2 diabetes diagnosis. DNA methylation was measured with Illumina Infinium Methylation arrays. A total of 1250 cases and 1950 controls from five longitudinal cohorts were included: Doetinchem, ESTHER, KORA1, KORA2 and EPIC-Norfolk. Associations between DNA methylation and incident type 2 diabetes were examined using robust linear regression with adjustment for potential confounders. Inverse-variance fixed-effects meta-analysis of cohort-level individual CpG EWAS estimates was performed using METAL. The methylGSA R package was used for gene set enrichment analysis. Confirmation of genome-wide significant CpG sites was performed in a cohort of Indian Asians (LOLIPOP, UK).

resultsThe meta-analysis identified 76 CpG sites that were differentially methylated in individuals with incident type 2 diabetes compared with control individuals (p values <1.1 × 10 CONCLUSIONS/

interpretationBy combining results from five European cohorts, and thus significantly increasing study sample size, we identified 76 CpG sites associated with incident type 2 diabetes. Replication of 64 CpGs in an independent cohort of Indian Asians suggests that the association between DNA methylation levels and incident type 2 diabetes is robust and independent of ethnicity. Our data also indicate that BMI partly explains the association between DNA methylation and incident type 2 diabetes. Further studies are required to elucidate the underlying biological mechanisms and to determine potential causal roles of the differentially methylated CpG sites in type 2 diabetes development.

Indexed as

Diabetes Mellitus, Type 2EpigenomeCpG IslandsDNA MethylationEpigenesis, GeneticGenome-Wide Association StudyHumansProspective StudiesBiomarkersDNA methylationEpigeneticsEpigenome-wide association studiesMeta-analysisPredictionProspective studiesType 2 diabetes

Identifiers

PMID35169870
PMCPMC8960572
OpenAlexW4212983816

What OpenQuestion holds

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Registered trials

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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.