Evidence map›Paper›PMID 39706196›Full record

ArticleAmerican journal of human genetics2025

DNA methylation-based predictors of metabolic traits in Scottish and Singaporean cohorts.

Hannah M Smith, Hong Kiat Ng, Joanna E Moodie, Danni A Gadd, Daniel L McCartney, Elena Bernabeu, Archie Campbell, Paul Redmond, Adele Taylor, Danielle Page and 11 more

Abstract read
In one paragraph

Article in American journal of human genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

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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

21 authors.

Hannah M SmithCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Hong Kiat NgLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Joanna E MoodieLothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.
Danni A GaddCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Daniel L McCartneyCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Elena BernabeuCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Archie CampbellCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Paul RedmondLothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.
Adele TaylorLothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.
Danielle PageLothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.
Janie CorleyLothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.
Sarah E HarrisLothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.
Darwin TayLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Ian J DearyLothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.
Kathryn L EvansCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Matthew R RobinsonInstitute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria.
John C ChambersLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Marie LohLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A(∗)STAR), Singapore, Singapore.
Simon R CoxLothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.
Riccardo E MarioniCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK. Electronic address: riccardo.marioni@ed.ac.uk.
Robert F HillaryCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exploring the molecular correlates of metabolic health measures may identify their shared and unique biological processes and pathways. Molecular proxies of these traits may also provide a more objective approach to their measurement. Here, DNA methylation (DNAm) data were used in epigenome-wide association studies (EWASs) and for training epigenetic scores (EpiScores) of six metabolic traits: body mass index (BMI), body fat percentage, waist-hip ratio, and blood-based measures of glucose, high-density lipoprotein cholesterol, and total cholesterol in >17,000 volunteers from the Generation Scotland (GS) cohort. We observed a maximum of 12,033 significant findings (p < 3.6 × 10

Indexed as

Body Mass IndexDNA MethylationGenome-Wide Association StudyAdultAgedBayes TheoremCohort StudiesEpigenesis, GeneticEpigenomeFemaleHumansMaleMiddle AgedScotlandSingaporeWaist-Hip RatioDNA methylationepigenetic scoresepigenome-wide association studiesgeneral cognitive functionmetabolic traits

Identifiers

PMID39706196
PMCPMC11739919

What Socratic holds

Textmetadata
LicenceCC BY
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.