Evidence map›Paper›PMID 29278407›Full record

ArticleInternational journal of obesity (2005)2018

Novel associations between blood DNA methylation and body mass index in middle-aged and older adults.

Y M Geurts, P-A Dugué, J E Joo, E Makalic, C-H Jung, W Guan, S Nguyen, M L Grove, E M Wong, A M Hodge and 15 more

Abstract read
PubMed Publisher
In one paragraph

Article in International journal of obesity (2005), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 5 pooled it
5.6field-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

40 citing papers in PubMed, 5 syntheses or guidelines pooled it, 93 citations in OpenAlex.

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  11. Association of Epigenetic Markers of Aging With Prevalent and Incident Type 2 Diabetes.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
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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

25 authors at 7 institutions in 4 countries.

Y M GeurtsCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
P-A DuguéCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
J E JooGenetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, VIC, Australia.
E MakalicCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.
C-H JungMelbourne Bioinformatics, University of Melbourne, Parkville, VIC, Australia.
W GuanDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
S NguyenDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
M L GroveHuman Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
E M WongGenetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, VIC, Australia.
A M HodgeCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
J K BassettCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
L M FitzGeraldCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
H TsimiklisGenetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, VIC, Australia.
L BagliettoDepartment of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.
G SeveriHuman Genetics Foundation (HuGeF), Torino, Italy.
D F SchmidtCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.
D D BuchananCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.
R J MacInnisCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
J L HopperCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.
J S PankowDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
E W DemerathDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
M C SoutheyGenetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, VIC, Australia.
G G GilesCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
D R EnglishCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
R L MilneCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
University of Melbourne · AUCancer Council Victoria · AUUniversity of Minnesota · USThe University of Texas Health Science Center at Houston · USUniversité Paris-Saclay · FRUniversity of Pisa · ITVictorian Comprehensive Cancer Centre · AU

Funding

Building on GWAS for NHLBI-disease: the CHARGE consortiumRC2HL102419 · NHLBI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI BOERWINKLE, ERIC A. · 2009 to 2010
$27.6M
ARRA NIH HHSNHLBI NIH HHS HHSN268201700001INHLBI NIH HHS HHSN268201700002INHLBI NIH HHS HHSN268201700003INHLBI NIH HHS HHSN268201700004INHLBI NIH HHS HHSN268201700005INHLBI NIH HHS RC2 HL102419
6 · The paper itself

Abstract

BACKGROUND/

objectivesThere is increasing evidence of a relationship between blood DNA methylation and body mass index (BMI). We aimed to assess associations of BMI with individual methylation measures (CpGs) through a cross-sectional genome-wide DNA methylation association study and a longitudinal analysis of repeated measurements over time. SUBJECTS/

methodsUsing the Illumina Infinium HumanMethylation450 BeadChip, DNA methylation measures were determined in baseline peripheral blood samples from 5361 adults recruited to the Melbourne Collaborative Cohort Study (MCCS) and selected for nested case-control studies, 2586 because they were subsequently diagnosed with cancer (cases) and 2775 as controls. For a subset of 1088 controls, these measures were repeated using blood samples collected at wave 2 follow-up, a median of 11 years later; weight was measured at both time points. Associations between BMI and blood DNA methylation were assessed using linear mixed-effects regression models adjusted for batch effects and potential confounders. These were applied to cases and controls separately, with results combined through fixed-effects meta-analysis.

resultsCross-sectional analysis identified 310 CpGs associated with BMI with P<1.0 × 10

conclusionsTogether, these findings suggest that BMI is associated with blood DNA methylation at a large number of CpGs across the genome, several of which are located in or near genes involved in ATP-binding cassette transportation, tumour necrosis factor signalling, insulin resistance and lipid metabolism.

Indexed as

Body Mass IndexAdultAgedAustraliaCross-Sectional StudiesDNADNA MethylationFemaleGene Regulatory NetworksGenome-Wide Association StudyHumansMaleMiddle AgedNeoplasmsDNA

Identifiers

PMID29278407
OpenAlexW2777970856

What OpenQuestion holds

Textmetadata
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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.