Evidence map›Paper›PMID 41654882›Full record

ArticleGenome biology2026

Genetic impacts on within-pair DNA methylation variance in monozygotic twins capture gene-environment interactions and cell-type effects.

Xiaopu Zhang, Idil Yet, Sergio Villicaña, Juan Castillo-Fernandez, Massimo Mangino, Jouke Jan Hottenga, Pei-Chien Tsai, Josine L Min, Mario Falchi, Andrew Wong and 4 more

Abstract readTwin Study
In one paragraph

Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing 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.

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

14 authors.

Xiaopu ZhangDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK. xiaopu.1.zhang@kcl.ac.uk.ORCID http://orcid.org/0000-0002-4345-3443
Idil YetDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Sergio VillicañaDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Juan Castillo-FernandezDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Massimo ManginoDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Jouke Jan HottengaDepartment of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Pei-Chien TsaiDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Josine L MinMRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
Mario FalchiDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Andrew WongMRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK.
Dorret I BoomsmaDepartment of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Ken K OngMRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, L3 Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
Jenny van DongenDepartment of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Jordana T BellDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK. jordana.bell@kcl.ac.uk.ORCID http://orcid.org/0000-0002-3858-5986

Funding

Economic and Social Research Council ES/N000404/1
6 · The paper itself

Abstract

backgroundGenetic variants that are associated with phenotypic variability, or variance quantitative trait loci (vQTLs), have been detected for multiple human traits. Gene-environment interactions can lead to differential phenotypic variability across genotype groups, therefore, genetic variants that interact with environmental exposures can manifest as vQTLs. Although changes in DNA methylation variability have been observed in several diseases, vQTLs for methylation levels (vmeQTL) have not yet been explored in depth.

resultsWe optimize the value of monozygotic twin studies to identify and replicate vmeQTLs for blood DNA methylation variance at 358 CpGs in 988 adult monozygotic twin pairs from two European twin registries. Over a third of vmeQTLs capture identical vmeQTL-environmental factor interactions in both datasets, and the majority of interactions are observed with blood cell counts. Correspondingly, over 60% of CpGs affected by genotype-monocyte and genotype-T cell interactions replicate as CpGs affected by genetic effects in the relevant cell type in an independent dataset. Most vmeQTLs also replicate in 1,348 UK non-twin adults and show longitudinal stability in a sample subset. Integrating gene expression and phenotype association results identifies multiple vmeQTLs that capture GxE effects relevant to human health. Examples include vmeQTLs interacting with blood cell type to influence DNA methylation in FAM65A, NAPRT, and CSGALNACT1 underlying immune disease susceptibility and progression.

conclusionsOur findings identify novel genetic effects on human DNA methylation variability within a unique monozygotic twin study design. The results show the potential of vmeQTLs to identify gene-environment interactions and provide novel insights into complex traits.

Indexed as

DNA MethylationGene-Environment InteractionQuantitative Trait LociTwins, MonozygoticAdultCpG IslandsFemaleGenotypeHumansMalePhenotypeDNA methylationDNA methylation variabilityGene-environment interactionsVariance methylation quantitative trait lociVmeQTL

Identifiers

PMID41654882
PMCPMC12977833

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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.