Evidence map›Paper›PMID 37258688›Full record

ArticleArchives of toxicology2023

G × E interactions as a basis for toxicological uncertainty.

Ilinca Suciu, David Pamies, Roberta Peruzzo, Petra H Wirtz, Lena Smirnova, Giorgia Pallocca, Christof Hauck, Mark T D Cronin, Jan G Hengstler, Thomas Brunner and 3 more

Open access · hybridAbstract readEditorial
In one paragraph

Article in Archives of toxicology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

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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

13 authors at 6 institutions in 4 countries.

Ilinca SuciuIn Vitro Toxicology and Biomedicine, Department Inaugurated By the Doerenkamp-Zbinden Foundation, University of Konstanz, Universitaetsstr. 10, 78457, Constance, Germany.ORCID 0000-0002-8166-9982
David PamiesDepartment of Biological Sciences, University of Lausanne, 1005, Lausanne, Switzerland.
Roberta PeruzzoDepartment of Molecular and Cell Biology, University of California, Berkeley, CA, 94720, USA.
Petra H WirtzCentre for the Advanced Study of Collective Behaviour, University of Konstanz, 78457, Constance, Germany.
Lena SmirnovaCenter for Alternatives to Animal Testing (CAAT), Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, 21205, USA.
Giorgia PalloccaCAAT Europe, University of Konstanz, 78457, Constance, Germany.
Christof HauckDepartment of Cell Biology, University of Konstanz, 78457, Constance, Germany.
Mark T D CroninSchool of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK.
Jan G HengstlerLeibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, 44139, Dortmund, Germany.
Thomas BrunnerBiochemical Pharmacology, Department of Biology, University of Konstanz, 78457, Constance, Germany.
Thomas HartungCenter for Alternatives to Animal Testing (CAAT), Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, 21205, USA.
Ivano AmelioDivision for Systems Toxicology, Department of Biology, University of Konstanz, 78457, Constance, Germany.
Marcel LeistIn Vitro Toxicology and Biomedicine, Department Inaugurated By the Doerenkamp-Zbinden Foundation, University of Konstanz, Universitaetsstr. 10, 78457, Constance, Germany. marcel.leist@uni-konstanz.de.
University of Konstanz · DEJohns Hopkins University · USLiverpool John Moores University · GBTU Dortmund University · DEUniversity of California, Berkeley · USUniversity of Lausanne · CH

Funding

Carl-Zeiss-Stiftung 15972218Carl-Zeiss-Stiftung 15978021Carl-Zeiss-Stiftung P2022-5-003Deutsche Forschungsgemeinschaft EXC2117-422037984Horizon 2020 Framework Programme 101057014Horizon 2020 Framework Programme 963845Horizon 2020 Framework Programme 964518Horizon 2020 Framework Programme 964537Horizon 2020 Framework Programme R83950501
6 · The paper itself

Abstract

To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of "genetic" influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present "gene expression" influences is summarized here as G

Indexed as

Adverse Outcome PathwaysAnimalsHumansModels, BiologicalUncertaintyAOPEpigeneticsModel systemResilienceSafety factorToxicokinetics

Identifiers

PMID37258688
PMCPMC10256652
OpenAlexW4378906801

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.