Evidence map›Paper›PMID 29295990›Full record

ArticleNature communications2018

Obligatory and facilitative allelic variation in the DNA methylome within common disease-associated loci.

Christopher G Bell, Fei Gao, Wei Yuan, Leonie Roos, Richard J Acton, Yudong Xia, Jordana Bell, Kirsten Ward, Massimo Mangino, Pirro G Hysi and 2 more

Abstract read
In one paragraph

Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. Hybrid origin and phenotype evolution of the modern maize.Journal of integrative plant biology · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Epigenomic insights into common human disease pathology.Cellular and molecular life sciences : CMLS · 2024
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

12 authors.

Christopher G BellDepartment of Twin Research & Genetic Epidemiology, King's College London, London, SE1 7EH, UK. cgb@mrc.soton.ac.uk.ORCID http://orcid.org/0000-0003-4601-1242
Fei GaoBGI-Shenzhen, Shenzhen, 518083, China.
Wei YuanDepartment of Twin Research & Genetic Epidemiology, King's College London, London, SE1 7EH, UK.
Leonie RoosDepartment of Twin Research & Genetic Epidemiology, King's College London, London, SE1 7EH, UK.ORCID http://orcid.org/0000-0001-7885-2105
Richard J ActonMRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, SO16 6YD, UK.ORCID http://orcid.org/0000-0002-2574-9611
Yudong XiaBGI-Shenzhen, Shenzhen, 518083, China.
Jordana BellDepartment of Twin Research & Genetic Epidemiology, King's College London, London, SE1 7EH, UK.
Kirsten WardDepartment of Twin Research & Genetic Epidemiology, King's College London, London, SE1 7EH, UK.
Massimo ManginoDepartment of Twin Research & Genetic Epidemiology, King's College London, London, SE1 7EH, UK.ORCID http://orcid.org/0000-0002-2167-7470
Pirro G HysiDepartment of Twin Research & Genetic Epidemiology, King's College London, London, SE1 7EH, UK.ORCID http://orcid.org/0000-0001-5752-2510
Jun WangMRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, SO16 6YD, UK.
Timothy D SpectorDepartment of Twin Research & Genetic Epidemiology, King's College London, London, SE1 7EH, UK.

Funding

European Research Council 250157Medical Research Council MC_UP_A620_1017Medical Research Council MC_UU_12011/4Wellcome Trust
6 · The paper itself

Abstract

Integrating epigenetic data with genome-wide association study (GWAS) results can reveal disease mechanisms. The genome sequence itself also shapes the epigenome, with CpG density and transcription factor binding sites (TFBSs) strongly encoding the DNA methylome. Therefore, genetic polymorphism impacts on the observed epigenome. Furthermore, large genetic variants alter epigenetic signal dosage. Here, we identify DNA methylation variability between GWAS-SNP risk and non-risk haplotypes. In three subsets comprising 3128 MeDIP-seq peripheral-blood DNA methylomes, we find 7173 consistent and functionally enriched Differentially Methylated Regions. 36.8% can be attributed to common non-SNP genetic variants. CpG-SNPs, as well as facilitative TFBS-motifs, are also enriched. Highlighting their functional potential, CpG-SNPs strongly associate with allele-specific DNase-I hypersensitivity sites. Our results demonstrate strong DNA methylation allelic differences driven by obligatory or facilitative genetic effects, with potential direct or regional disease-related repercussions. These allelic variations require disentangling from pure tissue-specific modifications, may influence array studies, and imply underestimated population variability in current reference epigenomes.

Indexed as

DNA MethylationGenetic VariationAllelesCpG IslandsDiseaseEpigenesis, GeneticGenetic Predisposition to DiseaseGenome, HumanGenome-Wide Association StudyHaplotypesHigh-Throughput Nucleotide SequencingHumansPolymorphism, Single NucleotideRisk Factors

Identifiers

PMID29295990
PMCPMC5750212

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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.