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Contextualization of causal regulatory networks from toxicogenomics data applied to drug-induced liver injury

View ORCID ProfilePanuwat Trairatphisan, View ORCID ProfileTerezinha Maria de Souza, Jos Kleinjans, View ORCID ProfileDanyel Jennen, View ORCID ProfileJulio Saez-Rodriguez
doi: https://doi.org/10.1101/2021.01.31.429025
Panuwat Trairatphisan
1Heidelberg University, Faculty of Medicine, Institute of Computational Biomedicine, 69120 Heidelberg, Germany
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Terezinha Maria de Souza
2Department of Toxicogenomics (TGX), GROW School of Oncology and Development Biology, Maastricht University, 6200 MD, Maastricht, The Netherlands
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Jos Kleinjans
2Department of Toxicogenomics (TGX), GROW School of Oncology and Development Biology, Maastricht University, 6200 MD, Maastricht, The Netherlands
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Danyel Jennen
2Department of Toxicogenomics (TGX), GROW School of Oncology and Development Biology, Maastricht University, 6200 MD, Maastricht, The Netherlands
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Julio Saez-Rodriguez
1Heidelberg University, Faculty of Medicine, Institute of Computational Biomedicine, 69120 Heidelberg, Germany
3RWTH Aachen University, Faculty of Medicine, Joint Research Centre for Computational Biomedicine (JRC-COMBINE), 52074, Aachen, Germany
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  • For correspondence: julio.saez@uni-heidelberg.de
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Abstract

Toxicogenomics studies typically reveal a group of genes relevant to the pathophysiology of drug-induced organ injury. In recent years, network-based methods have become an attractive analytical approach as they can capture not only the global changes of regulatory gene networks but also the relationships between their components. Among them, a causal reasoning approach additionally depicts the mechanisms of regulation that connect upstream regulators in signaling networks towards their downstream gene targets.

In this work, we applied CARNIVAL, a causal network contextualisation tool, to infer upstream regulatory signaling networks based on gene expression microarray data from the TG-GATEs database. We focussed on six compounds that induce observable histopathologies linked to drug-induced liver injury (DILI) from repeated dosing experiments in rats. We compared responses in vitro and in vivo to identify potential cross-platform concordances in rats as well as network preservations between rat and human. Our results showed similarities of enriched pathways and network motifs between compounds. These pathways and motifs induce the same pathology in rats but not in humans. In particular, the causal interactions “LCK activates SOCS3, which in turn inhibits TFDP1” was commonly identified as a regulatory path among the fibrosis-inducing compounds. This potential pathology-inducing regulation illustrates the value of our approach to generate hypotheses that can be further validated experimentally.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted February 02, 2021.
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Contextualization of causal regulatory networks from toxicogenomics data applied to drug-induced liver injury
Panuwat Trairatphisan, Terezinha Maria de Souza, Jos Kleinjans, Danyel Jennen, Julio Saez-Rodriguez
bioRxiv 2021.01.31.429025; doi: https://doi.org/10.1101/2021.01.31.429025
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Contextualization of causal regulatory networks from toxicogenomics data applied to drug-induced liver injury
Panuwat Trairatphisan, Terezinha Maria de Souza, Jos Kleinjans, Danyel Jennen, Julio Saez-Rodriguez
bioRxiv 2021.01.31.429025; doi: https://doi.org/10.1101/2021.01.31.429025

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