Evidence map›Paper›PMID 39821420›Full record

ArticleToxicological sciences : an official journal of the Society of Toxicology2025

Quantifying liver-toxic responses from dose-dependent chemical exposures using a rat genome-scale metabolic model.

Venkat R Pannala, Archana Hari, Mohamed Diwan M AbdulHameed, Michele R Balik-Meisner, Deepak Mav, Dhiral P Phadke, Elizabeth H Scholl, Ruchir R Shah, Scott S Auerbach, Anders Wallqvist

Abstract read
In one paragraph

Article in Toxicological sciences : an official journal of the Society of Toxicology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

10 authors.

Venkat R PannalaDepartment of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD 21702, United States.ORCID 0000-0002-3368-2496
Archana HariDepartment of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD 21702, United States.
Mohamed Diwan M AbdulHameedDepartment of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD 21702, United States.
Michele R Balik-MeisnerSciome LLC, Research Triangle Park, NC 27709, United States.
Deepak MavSciome LLC, Research Triangle Park, NC 27709, United States.
Dhiral P PhadkeSciome LLC, Research Triangle Park, NC 27709, United States.
Elizabeth H SchollSciome LLC, Research Triangle Park, NC 27709, United States.
Ruchir R ShahSciome LLC, Research Triangle Park, NC 27709, United States.
Scott S AuerbachDivision of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, United States.ORCID 0000-0002-6294-3069
Anders WallqvistDepartment of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD 21702, United States.

Funding

Scientific Cyberinfrastructure Research ProgramZIAES103385 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WALKER, VICKIE · 2022 to 2025
$17.4M
Environmental Health Perspectives, NIEHS27302C0031 · NIEHS · 2008 to 2008
$1.2M
BHSAINIEHS NIH HHS 27302C0031NIEHS NIH HHS ZIAES103385NIHThe Henry M. Jackson FoundationU.S. Army Medical Research and Development Command W81XWH20C0031
6 · The paper itself

Abstract

Because the liver plays a vital role in the clearance of exogenous chemical compounds, it is susceptible to chemical-induced toxicity. Animal-based testing is routinely used to assess the hepatotoxic potential of chemicals. Although large-scale high-throughput sequencing data can indicate the genes affected by chemical exposures, we need system-level approaches to interpret these changes. To this end, we developed an updated rat genome-scale metabolic model to integrate large-scale transcriptomics data and utilized a chemical structure similarity-based ToxProfiler tool to identify chemicals that bind to specific toxicity targets to understand the mechanisms of toxicity. We used high-throughput transcriptomics data from a 5-day in vivo study where rats were exposed to different non-toxic and hepatotoxic chemicals at increasing concentrations and investigated how liver metabolism was differentially altered between the non-toxic and hepatotoxic chemical exposures. Our analysis indicated that the genes identified via toxicity target analysis and those mapped to the metabolic model showed a distinct gene expression pattern, with the majority showing upregulation for hepatotoxicants compared with non-toxic chemicals. Similarly, when we mapped the metabolic genes at the pathway level, we identified several pathways in carbohydrate, amino acid, and lipid metabolism that were significantly upregulated for hepatotoxic chemicals. Furthermore, using our system-level integration of gene expression data with the rat metabolic model, we could differentiate metabolites in these pathways that were systematically elevated or suppressed due to hepatotoxic versus non-toxic chemicals. Thus, using our combined approach, we were able to identify a set of potential gene signatures that clearly differentiated liver toxic responses from non-toxic chemicals, which helped us identify potential metabolic pathways and metabolites that are systematically associated with the toxicant exposure.

Indexed as

Chemical and Drug Induced Liver InjuryGenomeLiverModels, BiologicalAnimalsDose-Response Relationship, DrugGene Expression ProfilingMaleRatsRats, Sprague-DawleyTranscriptomechemical structure-based analysisenvironmental chemicalshigh-throughput transcriptomicsliver toxicitymetabolite predictionstoxicity targets

Identifiers

PMID39821420
PMCPMC11939075

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.