ArticleToxicology and applied pharmacology2019
Mechanistic identification of biofluid metabolite changes as markers of acetaminophen-induced liver toxicity in rats.
Article in Toxicology and applied pharmacology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 37 citations in OpenAlex.
- Article
- Quantifying liver-toxic responses from dose-dependent chemical exposures using a rat genome-scale metabolic model.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
- Hepatotoxicity Induced by Methyl Eugenol: Insights from Toxicokinetics, Metabolomics, and Gut Microbiota.Current issues in molecular biology · 2024Article
- Identifying metabolic adaptations characteristic of cardiotoxicity using paired transcriptomics and metabolomics data integrated with a computational model of heart metabolism.PLoS computational biology · 2024Article
- Metabolomics in Preclinical Drug Safety Assessment: Current Status and Future Trends.Metabolites · 2024Review
- High-Throughput Transcriptomics Differentiates Toxic versus Non-Toxic Chemical Exposures Using a Rat Liver Model.International journal of molecular sciences · 2023Article
- Integrated Transcriptome and Metabolomics to Reveal the Mechanism of Adipose Mesenchymal Stem Cells in Treating Liver Fibrosis.International journal of molecular sciences · 2023Article
- Metabolic modeling of sex-specific liver tissue suggests mechanism of differences in toxicological responses.PLoS computational biology · 2023Article
- Metabolic modeling of sex-specific tissue predicts mechanisms of differences in toxicological responses.bioRxiv : the preprint server for biology · 2023Article
- Genomics and metabolomics of early-stage thioacetamide-induced liver injury: An interspecies study between guinea pig and rat.Toxicology and applied pharmacology · 2021Article
- Predicting changes in renal metabolism after compound exposure with a genome-scale metabolic model.Toxicology and applied pharmacology · 2021Article
- Toxicant-Induced Metabolic Alterations in Lipid and Amino Acid Pathways Are Predictive of Acute Liver Toxicity in Rats.International journal of molecular sciences · 2020Article
- The cardioprotective effects of the new crystal form of puerarin in isoproterenol-induced myocardial ischemia rats based on metabolomics.Scientific reports · 2020Article
- Genome-Scale Model-Based Identification of Metabolite Indicators for Early Detection of Kidney Toxicity.Toxicological sciences : an official journal of the Society of Toxicology · 2020Article
- LC-MS-Based Metabolomic Study of Oleanolic Acid-Induced Hepatotoxicity in Mice.Frontiers in pharmacology · 2020Article
- Genome-scale metabolic model of the rat liver predicts effects of diet restriction.Scientific reports · 2019Article
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
Abstract
Acetaminophen (APAP) is the most commonly used analgesic and antipyretic drug in the world. Yet, it poses a major risk of liver injury when taken in excess of the therapeutic dose. Current clinical markers do not detect the early onset of liver injury associated with excess APAP-information that is vital to reverse injury progression through available therapeutic interventions. Hence, several studies have used transcriptomics, proteomics, and metabolomics technologies, both independently and in combination, in an attempt to discover potential early markers of liver injury. However, the casual relationship between these observations and their relation to the APAP mechanism of liver toxicity are not clearly understood. Here, we used Sprague-Dawley rats orally gavaged with a single dose of 2 g/kg of APAP to collect tissue samples from the liver and kidney for transcriptomic analysis and plasma and urine samples for metabolomic analysis. We developed and used a multi-tissue, metabolism-based modeling approach to integrate these data, characterize the effect of excess APAP levels on liver metabolism, and identify a panel of plasma and urine metabolites that are associated with APAP-induced liver toxicity. Our analyses, which indicated that pathways involved in nucleotide-, lipid-, and amino acid-related metabolism in the liver were most strongly affected within 10 h following APAP treatment, identified a list of potential metabolites in these pathways that could serve as plausible markers of APAP-induced liver injury. Our approach identifies toxicant-induced changes in endogenous metabolism, is applicable to other toxicants based on transcriptomic data, and provides a mechanistic framework for interpreting metabolite alterations.
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