Evidence map›Paper›PMID 35888152›Full record

ArticleLife (Basel, Switzerland)2022

Association between Usual Dietary Intake of Food Groups and DNA Methylation and Effect Modification by Metabotype in the KORA FF4 Cohort.

Fabian Hellbach, Sebastian-Edgar Baumeister, Rory Wilson, Nina Wawro, Chetana Dahal, Dennis Freuer, Hans Hauner, Annette Peters, Juliane Winkelmann, Lars Schwettmann and 6 more

Open access · goldAbstract read
In one paragraph

Article in Life (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 42% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
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

16 authors at 7 institutions in 2 countries.

Fabian HellbachInstitute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilian University of Munich, Marchioninistr. 15, 81377 Munich, Germany.
Sebastian-Edgar BaumeisterInstitute of Health Services Research in Dentistry, Medical Faculty, University of Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany.
Rory WilsonInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.
Nina WawroInstitute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilian University of Munich, Marchioninistr. 15, 81377 Munich, Germany.ORCID 0000-0001-8144-0291
Chetana DahalEpidemiology, Faculty of Medicine, University Hospital Augsburg, University of Augsburg, Stenglinstraße 2, 86156 Augsburg, Germany.
Dennis FreuerEpidemiology, Faculty of Medicine, University Hospital Augsburg, University of Augsburg, Stenglinstraße 2, 86156 Augsburg, Germany.ORCID 0000-0001-7188-9087
Hans HaunerElse Kröner-Fresenius-Center for Nutritional Medicine, TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany.ORCID 0000-0002-1682-5088
Annette PetersInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.ORCID 0000-0001-6645-0985
Juliane WinkelmannInstitute of Neurogenomic, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.
Lars SchwettmannInstitute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.ORCID 0000-0003-0935-6989
Wolfgang RathmannInstitute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225 Düsseldorf, Germany.
Florian KronenbergDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstr. 41, 6020 Innsbruck, Austria.
Wolfgang KoenigDZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Pettenkoferstr. 8A & 9, 80336 Munich, Germany.
Christa MeisingerEpidemiology, Faculty of Medicine, University Hospital Augsburg, University of Augsburg, Stenglinstraße 2, 86156 Augsburg, Germany.
Melanie WaldenbergerInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.ORCID 0000-0003-0583-5093
Jakob LinseisenInstitute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilian University of Munich, Marchioninistr. 15, 81377 Munich, Germany.
University of Augsburg · DEHelmholtz Zentrum München · DEDeutsches Diabetes-Zentrum e.V. · DEFresenius (Germany) · DEInnsbruck Medical University · ATUniversität Ulm · DEUniversity of Münster · DE

Funding

Biotechnology and Biological Sciences Research Council BB/S020845/1European HDHL Joint Programming Initiative 01EA1902B
6 · The paper itself

Abstract

Associations between diet and DNA methylation may vary among subjects with different metabolic states, which can be captured by clustering populations in metabolically homogenous subgroups, called metabotypes. Our aim was to examine the relationship between habitual consumption of various food groups and DNA methylation as well as to test for effect modification by metabotype. A cross-sectional analysis of participants (median age 58 years) of the population-based prospective KORA FF4 study, habitual dietary intake was modeled based on repeated 24-h diet recalls and a food frequency questionnaire. DNA methylation was measured using the Infinium MethylationEPIC BeadChip providing data on >850,000 sites in this epigenome-wide association study (EWAS). Three metabotype clusters were identified using four standard clinical parameters and BMI. Regression models were used to associate diet and DNA methylation, and to test for effect modification. Few significant signals were identified in the basic analysis while many significant signals were observed in models including food group-metabotype interaction terms. Most findings refer to interactions of food intake with metabotype 3, which is the metabotype with the most unfavorable metabolic profile. This research highlights the importance of the metabolic characteristics of subjects when identifying associations between diet and white blood cell DNA methylation in EWAS.

Indexed as

dietEPICepigenome-wide association studyEWAShumansinteractionmetabotype

Identifiers

PMID35888152
PMCPMC9318948
OpenAlexW4285733725

What OpenQuestion holds

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LicenceCC BY
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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.