Evidence mapPaperPMID 37525248Full record

ArticleGenome biology2023

Genetic impacts on DNA methylation help elucidate regulatory genomic processes.

Sergio Villicaña, Juan Castillo-Fernandez, Eilis Hannon, Colette Christiansen, Pei-Chien Tsai, Jane Maddock, Diana Kuh, Matthew Suderman, Christine Power, Caroline Relton and 6 more

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 1 pooled it
10.9field-weighted citation impact, top 1% 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

52 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.

  1. Pooled it
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  15. Emerging opportunities for DNA methylation biomarkers in cattle improvement.The Journal of reproduction and development · 2026
    Review
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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

16 authors at 8 institutions in 1 country.

Sergio VillicañaDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK. sergio.villicana_munoz@kcl.ac.uk.ORCID 0000-0002-2455-7095
Juan Castillo-FernandezDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Eilis HannonUniversity of Exeter Medical School, Exeter, UK.
Colette ChristiansenDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Pei-Chien TsaiDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Jane MaddockMRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK.
Diana KuhMRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK.
Matthew SudermanMRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
Christine PowerPopulation, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK.
Caroline ReltonMRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
George PloubidisCentre for Longitudinal Studies, Institute of Education, University College London, London, UK.
Andrew WongMRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK.
Rebecca HardySchool of Sport, Exercise & Health Sciences, Loughborough University, Loughborough, UK.
Alissa GoodmanCentre for Longitudinal Studies, Institute of Education, University College London, London, UK.
Ken K OngMRC Epidemiology Unit and Department of Paediatrics, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
Jordana T BellDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK. jordana.bell@kcl.ac.uk.
King's College London · GBMRC Unit for Lifelong Health and Ageing · GBGreat Ormond Street Hospital · GBUniversity College London · GBLoughborough University · GBUniversity of Bristol · GBUniversity of Cambridge · GBUniversity of Exeter · GB

Funding

Biotechnology and Biological Sciences Research Council BB/S020845/1Biotechnology and Biological Sciences Research Council BB/T019980/1Medical Research Council ES/M008584/1Medical Research Council ES/N000498/1Medical Research Council G0000934Medical Research Council MC_UU_00006/2Medical Research Council MC_UU_00019/1Medical Research Council MC_UU_00019/2Medical Research Council MC_UU_00032/4
6 · The paper itself

Abstract

backgroundPinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk.

resultsWe report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1520 co-localisations across 1325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1 and DOCK7 (total cholesterol levels), and ICOSLG (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis-meQTLs (e.g. through disruption of transcription factor binding sites for CTCF and SMC3) and trans-meQTLs (e.g. through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites).

conclusionsOur findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk .

Indexed as

DNA MethylationGenomicsCpG IslandsGene Expression RegulationGenome-Wide Association StudyHumansPolymorphism, Single NucleotideQuantitative Trait LociDNA methylationGWASHeritabilitymeQTLMethylation quantitative trait loci

Identifiers

PMID37525248
PMCPMC10391992
OpenAlexW4385417498

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.