Evidence map›Paper›PMID 23444110›Full record

ReviewEnvironmental and molecular mutagenesis2013

The fate is not always written in the genes: epigenomics in epidemiologic studies.

Scott M Langevin, Karl T Kelsey

Abstract readReview
In one paragraph

Review in Environmental and molecular mutagenesis, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
–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

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Current and future therapies for small cell lung carcinoma.Journal of hematology & oncology · 2025
    Review
  3. Multi-omics in Crohn's disease: New insights from inside.Computational and structural biotechnology journal · 2023
    Review
  4. Observational
  5. Article
  6. DNA methylation studies in cattle.Journal of applied genetics · 2021
    Review
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  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

2 authors.

Scott M LangevinDepartment of Epidemiology, Brown University, Providence, Rhode Island, USA.
Karl T Kelsey

Funding

TRAINING IN ENVIRONMENTAL PATHOLOGYT32ES007272 · NIEHS · BROWN UNIVERSITY · PI ZHITKOVICH, ANATOLY · 1992 to 2021
$7.5M
NIEHS NIH HHS T32 ES007272
6 · The paper itself

Abstract

Cost-effective, high-throughput epigenomic technologies have begun to emerge, rapidly replacing the candidate gene approach to molecular epidemiology and offering a comprehensive strategy for the study of epigenetics in human subjects. Epigenome-wide association studies (EWAS) provide new opportunities for advancing our understanding of epigenetic changes associated with complex disease states. However, such analyses are complicated by the dynamic nature of DNA methylation. In contrast to genomic studies, where genotype is essentially constant across somatic cells, EWAS present a new set of challenges, largely due to differential DNA methylation across distinct cell types, particularly for studies involving heterogeneous tissue sources, and changes in the epigenetic profile that occur over time. This review describes potential applications of EWAS from the viewpoint of the molecular epidemiologist, along with special considerations and pitfalls involved in the design of such studies.

Indexed as

Epigenesis, GeneticGenomicsMolecular EpidemiologyAgingDNA MethylationHumansDNA methylationEWASmolecular epidemiology

Identifiers

PMID23444110
PMCPMC4093796

What OpenQuestion holds

Textmetadata
LicenceTDM
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.