Evidence mapPaperPMID 39223311Full record

ReviewNature reviews. Genetics2025

Progress in toxicogenomics to protect human health.

Matthew J Meier, Joshua Harrill, Kamin Johnson, Russell S Thomas, Weida Tong, Julia E Rager, Carole L Yauk

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2025. 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. Systematic comparison of temporal hepatotoxicant-induced gene network responses across 3 liver test systems.Toxicological sciences : an official journal of the Society of Toxicology · 2026
    Article
  2. Review
  3. Review
  4. Review
  5. Review
  6. Essence of toxicology research to Saudi Arabia Vision 2030 and beyond: Current state and future perspectives.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2026
    Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. TGx-DDI (toxicogenomic DNA damage-inducing) biomarker validation: multi-site ring trial supporting regulatory use.Toxicological sciences : an official journal of the Society of Toxicology · 2025
    Article
  12. Review
  13. The OASIS Consortium: integrating multi-omics technologies to transform chemical safety assessment.Toxicological sciences : an official journal of the Society of Toxicology · 2025
    Article
  14. Navigating complexity in modern toxicology: the role of omics in short-term in vivo studies.Toxicological sciences : an official journal of the Society of Toxicology · 2025
    Review
  15. Article
  16. AIVIVE: a novel AI framework for enhanced in vitro to in vivo extrapolation (IVIVE) of toxicogenomics data.Toxicological sciences : an official journal of the Society of Toxicology · 2025
    Article
  17. Review
  18. Article
  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

7 authors.

Matthew J MeierEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario, Canada.ORCID http://orcid.org/0000-0001-8199-8754
Joshua HarrillCenter for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.ORCID http://orcid.org/0000-0003-4317-6391
Kamin JohnsonPredictive Safety Center, Corteva Agriscience, Indianapolis, IN, USA.ORCID http://orcid.org/0000-0003-4550-5566
Russell S ThomasCenter for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
Weida TongDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, AR, USA.ORCID http://orcid.org/0000-0003-3488-6148
Julia E RagerCurriculum in Toxicology & Environmental Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA.
Carole L YaukDepartment of Biology, University of Ottawa, Ottawa, Ontario, Canada. carole.yauk@uottawa.ca.ORCID http://orcid.org/0000-0002-6725-3454

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Toxicogenomics measures molecular features, such as transcripts, proteins, metabolites and epigenomic modifications, to understand and predict the toxicological effects of environmental and pharmaceutical exposures. Transcriptomics has become an integral tool in contemporary toxicology research owing to innovations in gene expression profiling that can provide mechanistic and quantitative information at scale. These data can be used to predict toxicological hazards through the use of transcriptomic biomarkers, network inference analyses, pattern-matching approaches and artificial intelligence. Furthermore, emerging approaches, such as high-throughput dose-response modelling, can leverage toxicogenomic data for human health protection even in the absence of predicting specific hazards. Finally, single-cell transcriptomics and multi-omics provide detailed insights into toxicological mechanisms. Here, we review the progress since the inception of toxicogenomics in applying transcriptomics towards toxicology testing and highlight advances that are transforming risk assessment.

Indexed as

ToxicogeneticsTranscriptomeGene Expression ProfilingHumansRisk Assessment

Identifiers

What Socratic 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 Socratic graph.