Literature DB >> 24136188

Utilization of causal reasoning of hepatic gene expression in rats to identify molecular pathways of idiosyncratic drug-induced liver injury.

Daphna Laifenfeld1, Luping Qiu, Rachel Swiss, Jennifer Park, Michael Macoritto, Yvonne Will, Husam S Younis, Michael Lawton.   

Abstract

Drug-induced liver injury (DILI) represents a leading cause of acute liver failure. Although DILI can be discovered in preclinical animal toxicology studies and/or early clinical trials, some human DILI reactions, termed idiosyncratic DILI (IDILI), are less predictable, occur in a small number of individuals, and do not follow a clear dose-response relationship. The emergence of IDILI poses a critical health challenge for patients and a financial challenge for the pharmaceutical industry. Understanding the cellular and molecular mechanisms underlying IDILI is key to the development of models that can assess potential IDILI risk. This study used Reverse Causal Reasoning (RCR), a method to assess activation of molecular signaling pathways, on gene expression data from rats treated with IDILI or pharmacologic/chemical comparators (NON-DILI) at the maximum tolerated dose to identify mechanistic pathways underlying IDILI. Detailed molecular networks involved in mitochondrial injury, inflammation, and endoplasmic reticulum (ER) stress were found in response to IDILI drugs but not negative controls (NON-DILI). In vitro assays assessing mitochondrial or ER function confirmed the effect of IDILI compounds on these systems. Together our work suggests that using gene expression data can aid in understanding mechanisms underlying IDILI and can guide in vitro screening for IDILI. Specifically, RCR should be considered for compounds that do not show evidence of DILI in preclinical animal studies positive for mitochondrial dysfunction and ER stress assays, especially when the therapeutic index toward projected human maximum drug plasma concentration is low.

Entities:  

Keywords:  biological modeling; liver; risk assessment; safety evaluation; systems biology; systems toxicology.; toxicogenomics

Mesh:

Substances:

Year:  2013        PMID: 24136188     DOI: 10.1093/toxsci/kft232

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


  10 in total

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Review 2.  Drug-induced liver injury: Advances in mechanistic understanding that will inform risk management.

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Journal:  Clin Pharmacol Ther       Date:  2017-01-11       Impact factor: 6.875

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Journal:  Toxicol Sci       Date:  2017-04-01       Impact factor: 4.849

Review 4.  Preclinical models of idiosyncratic drug-induced liver injury (iDILI): Moving towards prediction.

Authors:  Antonio Segovia-Zafra; Daniel E Di Zeo-Sánchez; Carlos López-Gómez; Zeus Pérez-Valdés; Eduardo García-Fuentes; Raúl J Andrade; M Isabel Lucena; Marina Villanueva-Paz
Journal:  Acta Pharm Sin B       Date:  2021-11-18       Impact factor: 11.413

5.  Human-relevant mechanisms and risk factors for TAK-875-Induced liver injury identified via a gene pathway-based approach in Collaborative Cross mice.

Authors:  Merrie Mosedale; Yanwei Cai; J Scott Eaddy; Patrick J Kirby; Francis S Wolenski; Yvonne Dragan; William Valdar
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6.  DNA damage-induced apoptosis and mitogen-activated protein kinase pathway contribute to the toxicity of dronedarone in hepatic cells.

Authors:  Si Chen; Zhen Ren; Dianke Yu; Baitang Ning; Lei Guo
Journal:  Environ Mol Mutagen       Date:  2018-02-05       Impact factor: 3.216

7.  Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix River basin, MN, WI, USA.

Authors:  Anthony L Schroeder; Dalma Martinović-Weigelt; Gerald T Ankley; Kathy E Lee; Natalia Garcia-Reyero; Edward J Perkins; Heiko L Schoenfuss; Daniel L Villeneuve
Journal:  Environ Pollut       Date:  2016-12-08       Impact factor: 8.071

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Journal:  BMC Bioinformatics       Date:  2016-08-24       Impact factor: 3.169

Review 9.  Bioinformatics Mining and Modeling Methods for the Identification of Disease Mechanisms in Neurodegenerative Disorders.

Authors:  Martin Hofmann-Apitius; Gordon Ball; Stephan Gebel; Shweta Bagewadi; Bernard de Bono; Reinhard Schneider; Matt Page; Alpha Tom Kodamullil; Erfan Younesi; Christian Ebeling; Jesper Tegnér; Luc Canard
Journal:  Int J Mol Sci       Date:  2015-12-07       Impact factor: 5.923

10.  Dynamic imaging of adaptive stress response pathway activation for prediction of drug induced liver injury.

Authors:  Steven Wink; Steven W Hiemstra; Suzanne Huppelschoten; Janna E Klip; Bob van de Water
Journal:  Arch Toxicol       Date:  2018-03-03       Impact factor: 5.153

  10 in total

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