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Mining Public Toxicogenomic Data Reveals Insights and Challenges in Delineating Liver Steatosis Adverse Outcome Pathways

Exposure to chemicals contributes to the development and progression of fatty liver, or steatosis, a process characterized by abnormal accumulation of lipids within liver cells. However, lack of knowledge on how chemicals cause steatosis has prevented any large-scale assessment of the 80,000+ chemic...

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Autores principales: AbdulHameed, Mohamed Diwan M., Pannala, Venkat R., Wallqvist, Anders
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6813744/
https://www.ncbi.nlm.nih.gov/pubmed/31681434
http://dx.doi.org/10.3389/fgene.2019.01007
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author AbdulHameed, Mohamed Diwan M.
Pannala, Venkat R.
Wallqvist, Anders
author_facet AbdulHameed, Mohamed Diwan M.
Pannala, Venkat R.
Wallqvist, Anders
author_sort AbdulHameed, Mohamed Diwan M.
collection PubMed
description Exposure to chemicals contributes to the development and progression of fatty liver, or steatosis, a process characterized by abnormal accumulation of lipids within liver cells. However, lack of knowledge on how chemicals cause steatosis has prevented any large-scale assessment of the 80,000+ chemicals in current use. To address this gap, we mined a large, publicly available toxicogenomic dataset associated with 18 known steatogenic chemicals to assess responses across assays (in vitro and in vivo) and species (i.e., rats and humans). We identified genes that were differentially expressed (DEGs) in rat in vivo, rat in vitro, and human in vitro studies in which rats or in vitro primary cell lines were exposed to the chemicals at different doses and durations. Using these DEGs, we performed pathway enrichment analysis, analyzed the molecular initiating events (MIEs) of the steatosis adverse outcome pathway (AOP), and predicted metabolite changes using metabolic network analysis. Genes indicative of oxidative stress were among the DEGs most frequently observed in the rat in vivo studies. Nox4, a pro-fibrotic gene, was down-regulated across these chemical exposure conditions. We identified eight genes (Cyp1a1, Egr1, Ccnb1, Gdf15, Cdk1, Pdk4, Ccna2, and Ns5atp9) and one pathway (retinol metabolism), associated with steatogenic chemicals and whose response was conserved across the three in vitro and in vivo systems. Similarly, we found the predicted metabolite changes, such as increases of saturated and unsaturated fatty acids, conserved across the three systems. Analysis of the target genes associated with the MIEs of the current steatosis AOP did not provide a clear association between these 18 chemicals and the MIEs, underlining the multi-factorial nature of this disease. Notably, our overall analysis implicated mitochondrial toxicity as an important and overlooked MIE for chemical-induced steatosis. The integrated toxicogenomics approach to identify genes, pathways, and metabolites based on known steatogenic chemicals, provide an important mean to assess development of AOPs and gauging the relevance of new testing strategies.
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spelling pubmed-68137442019-11-01 Mining Public Toxicogenomic Data Reveals Insights and Challenges in Delineating Liver Steatosis Adverse Outcome Pathways AbdulHameed, Mohamed Diwan M. Pannala, Venkat R. Wallqvist, Anders Front Genet Genetics Exposure to chemicals contributes to the development and progression of fatty liver, or steatosis, a process characterized by abnormal accumulation of lipids within liver cells. However, lack of knowledge on how chemicals cause steatosis has prevented any large-scale assessment of the 80,000+ chemicals in current use. To address this gap, we mined a large, publicly available toxicogenomic dataset associated with 18 known steatogenic chemicals to assess responses across assays (in vitro and in vivo) and species (i.e., rats and humans). We identified genes that were differentially expressed (DEGs) in rat in vivo, rat in vitro, and human in vitro studies in which rats or in vitro primary cell lines were exposed to the chemicals at different doses and durations. Using these DEGs, we performed pathway enrichment analysis, analyzed the molecular initiating events (MIEs) of the steatosis adverse outcome pathway (AOP), and predicted metabolite changes using metabolic network analysis. Genes indicative of oxidative stress were among the DEGs most frequently observed in the rat in vivo studies. Nox4, a pro-fibrotic gene, was down-regulated across these chemical exposure conditions. We identified eight genes (Cyp1a1, Egr1, Ccnb1, Gdf15, Cdk1, Pdk4, Ccna2, and Ns5atp9) and one pathway (retinol metabolism), associated with steatogenic chemicals and whose response was conserved across the three in vitro and in vivo systems. Similarly, we found the predicted metabolite changes, such as increases of saturated and unsaturated fatty acids, conserved across the three systems. Analysis of the target genes associated with the MIEs of the current steatosis AOP did not provide a clear association between these 18 chemicals and the MIEs, underlining the multi-factorial nature of this disease. Notably, our overall analysis implicated mitochondrial toxicity as an important and overlooked MIE for chemical-induced steatosis. The integrated toxicogenomics approach to identify genes, pathways, and metabolites based on known steatogenic chemicals, provide an important mean to assess development of AOPs and gauging the relevance of new testing strategies. Frontiers Media S.A. 2019-10-18 /pmc/articles/PMC6813744/ /pubmed/31681434 http://dx.doi.org/10.3389/fgene.2019.01007 Text en Copyright © 2019 AbdulHameed, Pannala and Wallqvist http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
AbdulHameed, Mohamed Diwan M.
Pannala, Venkat R.
Wallqvist, Anders
Mining Public Toxicogenomic Data Reveals Insights and Challenges in Delineating Liver Steatosis Adverse Outcome Pathways
title Mining Public Toxicogenomic Data Reveals Insights and Challenges in Delineating Liver Steatosis Adverse Outcome Pathways
title_full Mining Public Toxicogenomic Data Reveals Insights and Challenges in Delineating Liver Steatosis Adverse Outcome Pathways
title_fullStr Mining Public Toxicogenomic Data Reveals Insights and Challenges in Delineating Liver Steatosis Adverse Outcome Pathways
title_full_unstemmed Mining Public Toxicogenomic Data Reveals Insights and Challenges in Delineating Liver Steatosis Adverse Outcome Pathways
title_short Mining Public Toxicogenomic Data Reveals Insights and Challenges in Delineating Liver Steatosis Adverse Outcome Pathways
title_sort mining public toxicogenomic data reveals insights and challenges in delineating liver steatosis adverse outcome pathways
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6813744/
https://www.ncbi.nlm.nih.gov/pubmed/31681434
http://dx.doi.org/10.3389/fgene.2019.01007
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