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Title: Asking the Right Questions With Animal Models: Methionine- and Choline-Deficient Model in Predicting Adverse Drug Reactions in Human NASH.

Authors: Li, Hui; Toth, Erica; Cherrington, Nathan J

Published In Toxicol Sci, (2018 Jan 01)

Abstract: In the past few decades, great conceptual and technological advances have been made in the field of toxicology, but animal model-based research still remains one of the most widely used and readily available tools for furthering our current knowledge. However, animal models are not perfect in predicting all systemic toxicity in humans. Extrapolating animal data to accurately predict human toxicities remains a challenge, and researchers are obligated to question the appropriateness of their chosen animal model. This paper provides an assessment of the utility of the methionine- and choline-deficient (MCD) diet fed animal model in reflecting human nonalcoholic steatohepatitis (NASH) and the potential risks of adverse drug reactions and toxicities that are associated with the disease. As a commonly used NASH model, the MCD model fails to exhibit most metabolic abnormalities in a similar manner to the human disease. The MCD model, on the other hand, closely resembles human NASH histology and reflects signatures of drug transporter alterations in humans. Due to the nature of the MCD model, it should be avoided in studies of NASH pathogenesis, metabolic parameter evaluation, and biomarker identification. But it can be used to accurately predict altered drug disposition due to NASH-associated transporter alterations.

PubMed ID: 29145614 Exiting the NIEHS site

MeSH Terms: Animals; Biological Transport; Choline Deficiency/complications*; Cytochrome P-450 Enzyme System/genetics; Cytochrome P-450 Enzyme System/metabolism; Diet; Disease Models, Animal*; Drug-Related Side Effects and Adverse Reactions/metabolism*; Humans; Methionine/deficiency*; Non-alcoholic Fatty Liver Disease/etiology; Non-alcoholic Fatty Liver Disease/metabolism*; Pharmaceutical Preparations/metabolism; Predictive Value of Tests; Tissue Distribution

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