Evidence map›Paper›PMID 26612583›Full record

ArticleScientific reports2015

Genome-wide DNA methylation map of human neutrophils reveals widespread inter-individual epigenetic variation.

Aniruddha Chatterjee, Peter A Stockwell, Euan J Rodger, Elizabeth J Duncan, Matthew F Parry, Robert J Weeks, Ian M Morison

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 6% 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

46 citing papers in PubMed, 1 synthesis or guideline pooled it, 80 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Application of DNA Methylome Analysis to Patients with ME/CFS.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Editing of DNA Methylation Patterns Using CRISPR-Based Tools.Methods in molecular biology (Clifton, N.J.) · 2022
    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

7 authors at 1 institution in 1 country.

Aniruddha ChatterjeeDepartment of Pathology, Dunedin School of Medicine, University of Otago, 270 Great King Street, Dunedin 9054, New Zealand.
Peter A StockwellDepartment of Biochemistry, University of Otago, 710 Cumberland Street, Dunedin 9054, New Zealand.
Euan J RodgerDepartment of Pathology, Dunedin School of Medicine, University of Otago, 270 Great King Street, Dunedin 9054, New Zealand.
Elizabeth J DuncanGravida: National Centre for Growth and Development, 2-6 Park Ave, Grafton, Auckland 1142, New Zealand.
Matthew F ParryDepartment of Mathematics and Statistics, University of Otago, P.O. Box 56, Dunedin, 9054, New Zealand.
Robert J WeeksDepartment of Pathology, Dunedin School of Medicine, University of Otago, 270 Great King Street, Dunedin 9054, New Zealand.
Ian M MorisonDepartment of Pathology, Dunedin School of Medicine, University of Otago, 270 Great King Street, Dunedin 9054, New Zealand.
University of Otago · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The extent of variation in DNA methylation patterns in healthy individuals is not yet well documented. Identification of inter-individual epigenetic variation is important for understanding phenotypic variation and disease susceptibility. Using neutrophils from a cohort of healthy individuals, we generated base-resolution DNA methylation maps to document inter-individual epigenetic variation. We identified 12851 autosomal inter-individual variably methylated fragments (iVMFs). Gene promoters were the least variable, whereas gene body and upstream regions showed higher variation in DNA methylation. The iVMFs were relatively enriched in repetitive elements compared to non-iVMFs, and were associated with genome regulation and chromatin function elements. Further, variably methylated genes were disproportionately associated with regulation of transcription, responsive function and signal transduction pathways. Transcriptome analysis indicates that iVMF methylation at differentially expressed exons has a positive correlation and local effect on the inclusion of that exon in the mRNA transcript.

Indexed as

DNA MethylationEpigenesis, GeneticGenetic VariationGenome, HumanTranscriptomeChromatinChromosome MappingCpG IslandsExonsGene Expression ProfilingGenome-Wide Association StudyHumansIntronsNeutrophilsPromoter Regions, GeneticSignal TransductionChromatin

Identifiers

PMID26612583
PMCPMC4661471
OpenAlexW2191709890

What OpenQuestion 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 OpenQuestion graph.