Evidence map›Paper›PMID 36790133›Full record

ArticleHuman molecular genetics2023

Rare genetic variants underlie outlying levels of DNA methylation and gene-expression.

V Kartik Chundru, Riccardo E Marioni, James G D Prendergast, Tian Lin, Allan J Beveridge, Nicholas G Martin, Grant W Montgomery, David A Hume, Ian J Deary, Peter M Visscher and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Human molecular genetics, 2023. 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
0.8field-weighted citation impact, top 28% 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.

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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

12 authors at 6 institutions in 2 countries.

V Kartik ChundruInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.ORCID 0000-0002-6348-5565
Riccardo E MarioniCentre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh EH4 2XU, UK.
James G D PrendergastThe Roslin Institute, The University of Edinburgh, Midlothian EH25 9RG, UK.
Tian LinInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.
Allan J BeveridgeGlasgow Polyomics, Wolfson Wohl Cancer Research Centre, The University of Glasgow, Glasgow G61 1QH, UK.
Nicholas G MartinQIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia.
Grant W MontgomeryInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.
David A HumeMater Research Institute, The University of Queensland, Brisbane, QLD 4102, Australia.
Ian J DearyLothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh EH8 9JZ, UK.
Peter M VisscherInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.
Naomi R WrayInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.
Allan F McRaeInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.ORCID 0000-0001-5286-5485
The University of Queensland · AUEdinburgh Cancer Research · GBQIMR Berghofer Medical Research Institute · AURoslin Institute · GBUniversity of Edinburgh · GBUniversity of Glasgow · GB

Funding

Biotechnology and Biological Sciences Research CouncilChief Scientist OfficeMedical Research Council MR/K026992/1Medical Research Council MR/M013111/1Wellcome Trust
6 · The paper itself

Abstract

Testing the effect of rare variants on phenotypic variation is difficult due to the need for extremely large cohorts to identify associated variants given expected effect sizes. An alternative approach is to investigate the effect of rare genetic variants on DNA methylation (DNAm) as effect sizes are expected to be larger for molecular traits compared with complex traits. Here, we investigate DNAm in healthy ageing populations-the Lothian Birth Cohorts of 1921 and 1936-and identify both transient and stable outlying DNAm levels across the genome. We find an enrichment of rare genetic single nucleotide polymorphisms (SNPs) within 1 kb of DNAm sites in individuals with stable outlying DNAm, implying genetic control of this extreme variation. Using a family-based cohort, the Brisbane Systems Genetics Study, we observed increased sharing of DNAm outliers among more closely related individuals, consistent with these outliers being driven by rare genetic variation. We demonstrated that outlying DNAm levels have a functional consequence on gene expression levels, with extreme levels of DNAm being associated with gene expression levels toward the tails of the population distribution. This study demonstrates the role of rare SNPs in the phenotypic variation of DNAm and the effect of extreme levels of DNAm on gene expression.

Indexed as

DNA MethylationGene Expression RegulationEpigenesis, GeneticHumansMultifactorial InheritancePhenotype

Identifiers

PMID36790133
PMCPMC10196672
OpenAlexW4320856997

What OpenQuestion holds

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LicenceCC BY-NC
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 OpenQuestion graph.