Evidence map›Paper›PMID 34297908›Full record

ReviewAmerican journal of human genetics2021

Anatomy of DNA methylation signatures: Emerging insights and applications.

Eric Chater-Diehl, Sarah J Goodman, Cheryl Cytrynbaum, Andrei L Turinsky, Sanaa Choufani, Rosanna Weksberg

Open access · bronzeAbstract readReview
In one paragraph

Review in American journal of human genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
4.7field-weighted citation impact, top 4% 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

40 citing papers in PubMed, 59 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Expanding Upon Genomics in Rare Diseases: Epigenomic Insights.International journal of molecular sciences · 2024
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  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

6 authors at 1 institution in 1 country.

Eric Chater-DiehlGenetics and Genome Biology, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.
Sarah J GoodmanGenetics and Genome Biology, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.
Cheryl CytrynbaumGenetics and Genome Biology, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Division of Clinical and Metabolic Genetics, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S, Canada.
Andrei L TurinskyGenetics and Genome Biology, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Centre for Computational Medicine, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.
Sanaa ChoufaniGenetics and Genome Biology, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.
Rosanna WeksbergGenetics and Genome Biology, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Division of Clinical and Metabolic Genetics, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S, Canada; Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada; Department of Pediatrics, University of Toronto, Toronto, ON M5S 1A1, Canada. Electronic address: rweksb@sickkids.ca.
Hospital for Sick Children · CA

Funding

CIHR IGH-155182CIHR MOP-126054
6 · The paper itself

Abstract

DNA methylation (DNAm) signatures are unique patterns of DNAm alterations defined for rare disorders caused by pathogenic variants in epigenetic regulatory genes. The potential of DNAm signatures (also known as "episignatures") is just beginning to emerge as there are >300 known epigenetic regulatory genes, ∼100 of which are linked to neurodevelopmental disorders. To date, approximately 50 signatures have been identified, which have proven unexpectedly successful as predictive tools for classifying variants of uncertain significance as pathogenic or benign. The molecular basis of these signatures is poorly understood. Furthermore, their relationships to primary disease pathophysiology have yet to be adequately investigated, despite clear demonstrations of potential connections. There are currently no published guidelines for signature development. As signatures are highly dependent on the samples and methods used to derive them, we propose a framework for consideration in signature development including sample size, statistical parameters, cell type of origin, and the value of detailed clinical and molecular information. We illustrate the relationship between signature output/efficacy and sample size by generating and testing 837 DNAm signatures of Kleefstra syndrome using downsampling analysis. Our findings highlight that no single DNAm signature encompasses all DNAm alterations present in a rare disorder, and that a substandard study design can generate a DNAm signature that misclassifies variants. Finally, we discuss the importance of further investigating DNAm signatures to inform disease pathophysiology and broaden their scope as a functional assay.

Indexed as

DNA MethylationEpigenesis, GeneticGene Expression RegulationMutationAnimalsHumansNeurodevelopmental Disorders

Identifiers

PMID34297908
PMCPMC8387466
OpenAlexW3184514443

What OpenQuestion holds

Textmetadata
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.