Literature DB >> 23143927

Application of an updated physiologically based pharmacokinetic model for chloroform to evaluate CYP2E1-mediated renal toxicity in rats and mice.

Alan F Sasso1, Paul M Schlosser, Gregory L Kedderis, Mary Beth Genter, John E Snawder, Zheng Li, Susan Rieth, John C Lipscomb.   

Abstract

Physiologically based pharmacokinetic (PBPK) models are tools for interpreting toxicological data and extrapolating observations across species and route of exposure. Chloroform (CHCl(3)) is a chemical for which there are PBPK models available in different species and multiple sites of toxicity. Because chloroform induces toxic effects in the liver and kidneys via production of reactive metabolites, proper characterization of metabolism in these tissues is essential for risk assessment. Although hepatic metabolism of chloroform is adequately described by these models, there is higher uncertainty for renal metabolism due to a lack of species-specific data and direct measurements of renal metabolism. Furthermore, models typically fail to account for regional differences in metabolic capacity within the kidney. Mischaracterization of renal metabolism may have a negligible effect on systemic chloroform levels, but it is anticipated to have a significant impact on the estimated site-specific production of reactive metabolites. In this article, rate parameters for chloroform metabolism in the kidney are revised for rats, mice, and humans. New in vitro data were collected in mice and humans for this purpose and are presented here. The revised PBPK model is used to interpret data of chloroform-induced kidney toxicity in rats and mice exposed via inhalation and drinking water. Benchmark dose (BMD) modeling is used to characterize the dose-response relationship of kidney toxicity markers as a function of PBPK-derived internal kidney dose. Applying the PBPK model, it was also possible to characterize the dose response for a recent data set of rats exposed via multiple routes simultaneously. Consistent BMD modeling results were observed regardless of species or route of exposure.

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Year:  2012        PMID: 23143927     DOI: 10.1093/toxsci/kfs320

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  6 in total

1.  Cytochrome P450-2E1 is involved in aging-related kidney damage in mice through increased nitroxidative stress.

Authors:  Mohamed A Abdelmegeed; Youngshim Choi; Seung-Kwoon Ha; Byoung-Joon Song
Journal:  Food Chem Toxicol       Date:  2017-08-24       Impact factor: 6.023

2.  Global optimization of the Michaelis-Menten parameters using physiologically-based pharmacokinetic (PBPK) modeling and chloroform vapor uptake data in F344 rats.

Authors:  Marina V Evans; Christopher R Eklund; David N Williams; Yusupha M Sey; Jane Ellen Simmons
Journal:  Inhal Toxicol       Date:  2020-04-02       Impact factor: 2.724

Review 3.  Trichloroethylene biotransformation and its role in mutagenicity, carcinogenicity and target organ toxicity.

Authors:  Lawrence H Lash; Weihsueh A Chiu; Kathryn Z Guyton; Ivan Rusyn
Journal:  Mutat Res Rev Mutat Res       Date:  2014 Oct-Dec       Impact factor: 5.657

4.  NKT cell modulates NAFLD potentiation of metabolic oxidative stress-induced mesangial cell activation and proximal tubular toxicity.

Authors:  Firas Alhasson; Diptadip Dattaroy; Suvarthi Das; Varun Chandrashekaran; Ratanesh Kumar Seth; Rick G Schnellmann; Saurabh Chatterjee
Journal:  Am J Physiol Renal Physiol       Date:  2015-10-07

5.  Towards a qAOP framework for predictive toxicology - Linking data to decisions.

Authors:  Alicia Paini; Ivana Campia; Mark T D Cronin; David Asturiol; Lidia Ceriani; Thomas E Exner; Wang Gao; Caroline Gomes; Johannes Kruisselbrink; Marvin Martens; M E Bette Meek; David Pamies; Julia Pletz; Stefan Scholz; Andreas Schüttler; Nicoleta Spînu; Daniel L Villeneuve; Clemens Wittwehr; Andrew Worth; Mirjam Luijten
Journal:  Comput Toxicol       Date:  2022-02

6.  Micronuclei in bone marrow and liver in relation to hepatic metabolism and antioxidant response due to coexposure to chloroform, dichloromethane, and toluene in the rat model.

Authors:  Javier Belmont-Díaz; Ana Paulina López-Gordillo; Eunice Molina Garduño; Luis Serrano-García; Elvia Coballase-Urrutia; Noemí Cárdenas-Rodríguez; Omar Arellano-Aguilar; Regina D Montero-Montoya
Journal:  Biomed Res Int       Date:  2014-05-14       Impact factor: 3.411

  6 in total

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