Evidence map›Paper›PMID 37560024›Full record

ReviewCambridge prisms. Precision medicine2023

Promises and challenges in pharmacoepigenetics.

Delaney A Smith, Marie C Sadler, Russ B Altman

Open access · diamondAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Cambridge prisms. Precision medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
4.3field-weighted citation impact, top 5% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. New Personalized Medicine Model for Medication Management.Journal of personalized medicine · 2026
    Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Review
  12. Review
  13. Article
  14. Pharmaco-Multiomics: A New Frontier in Precision Psychiatry.International journal of molecular sciences · 2025
    Review
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review
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

3 authors at 2 institutions in 2 countries.

Delaney A SmithDepartment of Bioengineering, Stanford University, Stanford, CA, USA.ORCID https://orcid.org/0000-0002-8687-7342
Marie C SadlerDepartment of Bioengineering, Stanford University, Stanford, CA, USA.ORCID https://orcid.org/0000-0002-2599-9207
Russ B AltmanDepartment of Bioengineering, Stanford University, Stanford, CA, USA.ORCID https://orcid.org/0000-0003-3859-2905
Stanford University · USSIB Swiss Institute of Bioinformatics · CH

Funding

PharmGKB: pharmacogenomics discovery and implementationU24HG010615 · NHGRI · STANFORD UNIVERSITY · PI TERI Ellen KLEIN, Michelle Whirl-Carrillo · 2020 to 2026
$9.5M
Undergraduate Summer Research Experiences Support for Combining systems biology and structural biology to find new therapeuticsR01GM102365 · NIGMS · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO · 2012 to 2021
$3.0M
NHGRI NIH HHS U24 HG010615NIGMS NIH HHS R01 GM102365
6 · The paper itself

Abstract

Pharmacogenetics, the study of how interindividual genetic differences affect drug response, does not explain all observed heritable variance in drug response. Epigenetic mechanisms, such as DNA methylation, and histone acetylation may account for some of the unexplained variances. Epigenetic mechanisms modulate gene expression and can be suitable drug targets and can impact the action of nonepigenetic drugs. Pharmacoepigenetics is the field that studies the relationship between epigenetic variability and drug response. Much of this research focuses on compounds targeting epigenetic mechanisms, called epigenetic drugs, which are used to treat cancers, immune disorders, and other diseases. Several studies also suggest an epigenetic role in classical drug response; however, we know little about this area. The amount of information correlating epigenetic biomarkers to molecular datasets has recently expanded due to technological advances, and novel computational approaches have emerged to better identify and predict epigenetic interactions. We propose that the relationship between epigenetics and classical drug response may be examined using data already available by (1) finding regions of epigenetic variance, (2) pinpointing key epigenetic biomarkers within these regions, and (3) mapping these biomarkers to a drug-response phenotype. This approach expands on existing knowledge to generate putative pharmacoepigenetic relationships, which can be tested experimentally. Epigenetic modifications are involved in disease and drug response. Therefore, understanding how epigenetic drivers impact the response to classical drugs is important for improving drug design and administration to better treat disease.

Indexed as

epigeneticsmolecular QTLspharmacoepigeneticspharmacoepigenomicspharmacogenomics

Identifiers

PMID37560024
PMCPMC10406571
OpenAlexW4319773498

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.