Systems toxicology of chemically induced liver and kidney injuries: histopathology‐associated gene co‐expression modules

Te, Jerez A.; AbdulHameed, Mohamed Diwan M.; Wallqvist, Anders

doi:10.1002/jat.3278

Cited by 21 publications

(24 citation statements)

References 36 publications

(49 reference statements)

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“…We have developed 8 kidney and 11 liver injury modules, which are co-expressed gene sets (modules) associated with specific histopathological injury phenotypes in the liver and kidney ( Te et al, 2016 ). The number of co-expressed genes in each injury module ranges from 8 to 126, with a total of 629 unique genes.…”

Section: Resultsmentioning

confidence: 99%

“…However, the selection of injury-specific modules was partly based on biological information and the presence of known biomarkers. Recently, we developed an unbiased protocol to assign injury modules to specific histopathological injuries in the liver and kidney based on gene co-expression profiles ( Te et al, 2016 ). This protocol is applicable for any organ and has an advantage over, e.g., gene signatures, in that no biological or mechanistic information is needed as input other than gene expression data.…”

Section: Introductionmentioning

confidence: 99%

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Identification of the Toxicity Pathways Associated With Thioacetamide-Induced Injuries in Rat Liver and Kidney

et al. 2018

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Ingestion or exposure to chemicals poses a serious health risk. Early detection of cellular changes induced by such events is vital to identify appropriate countermeasures to prevent organ damage. We hypothesize that chemically induced organ injuries are uniquely associated with a set (module) of genes exhibiting significant changes in expression. We have previously identified gene modules specifically associated with organ injuries by analyzing gene expression levels in liver and kidney tissue from rats exposed to diverse chemical insults. Here, we assess and validate our injury-associated gene modules by analyzing gene expression data in liver, kidney, and heart tissues obtained from Sprague-Dawley rats exposed to thioacetamide, a known liver toxicant that promotes fibrosis. The rats were injected intraperitoneally with a low (25 mg/kg) or high (100 mg/kg) dose of thioacetamide for 8 or 24 h, and definite organ injury was diagnosed by histopathology. Injury-associated gene modules indicated organ injury specificity, with the liver being most affected by thioacetamide. The most activated liver gene modules were those associated with inflammatory cell infiltration and fibrosis. Previous studies on thioacetamide toxicity and our histological analyses supported these results, signifying the potential of gene expression data to identify organ injuries.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of the Toxicity Pathways Associated With Thioacetamide-Induced Injuries in Rat Liver and Kidney

et al. 2018

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“…We used the 8 kidney-and 11 liver-injury modules we identified and evaluated in previous work [18,19]. Several injury phenotypes may coexist, such as cellular infiltration and bile duct proliferation, which are early injury responses.…”

Section: Analysis Of Injury-module Activationmentioning

confidence: 99%

“…Using gene expression data from the Open Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System (TG-GATEs) database, which contains data from Sprague-Dawley rats exposed to different chemicals for 4 to 29 days [17], we derived 11 and 8 chemical-induced injury modules (i.e., gene modules, each uniquely associated with a specific organ-injury phenotype) for the liver and kidney, respectively, based on the histopathological injury phenotypes documented in the same database [18]. In a subsequent study, we validated these injury modules in vivo by treating Sprague-Dawley rats with thioacetamide [19], an organosulfur compound extensively used in animal studies as a fibrosis-promoting liver toxicant [20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Concordance between Thioacetamide-Induced Liver Injury in Rat and Human In Vitro Gene Expression Data

Schyman

Printz

Estes

et al. 2020

IJMS

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The immense resources required and the ethical concerns for animal-based toxicological studies have driven the development of in vitro and in silico approaches. Recently, we validated our approach in which the expression of a set of genes is uniquely associated with an organ-injury phenotype (injury module), by using thioacetamide, a known liver toxicant. Here, we sought to explore whether RNA-seq data obtained from human cells (in vitro) treated with thioacetamide-S-oxide (a toxic intermediate metabolite) would correlate across species with the injury responses found in rat cells (in vitro) after exposure to this metabolite as well as in rats exposed to thioacetamide (in vivo). We treated two human cell types with thioacetamide-S-oxide (primary hepatocytes with 0 (vehicle), 0.125 (low dose), or 0.25 (high dose) mM, and renal tubular epithelial cells with 0 (vehicle), 0.25 (low dose), or 1.00 (high dose) mM) and collected RNA-seq data 9 or 24 h after treatment. We found that the liver-injury modules significantly altered in human hepatocytes 24 h after high-dose treatment involved cellular infiltration and bile duct proliferation, which are linked to fibrosis. For high-dose treatments, our modular approach predicted the rat in vivo and in vitro results from human in vitro RNA-seq data with Pearson correlation coefficients of 0.60 and 0.63, respectively, which was not observed for individual genes or KEGG pathways.

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“…Considerable effort has been invested applying transcript profiling to risk assessment using methodologies such as gene signatures, 12 pathway-based enrichment analysis, 13 co-expression networks, 14,15 and adverse outcome pathways. 16 However, toxicogenomic approaches to safety testing remain challenging and have achieved only modest utility in addressing uncertainty in safety predictions, largely as an investigative tool.…”

Section: Introductionmentioning

confidence: 99%

Toxicogenomic module associations with pathogenesis: a network-based approach to understanding drug toxicity

et al. 2017

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Despite investment in toxicogenomics, nonclinical safety studies are still used to predict clinical liabilities for new drug candidates. Network-based approaches for genomic analysis help overcome challenges with whole-genome transcriptional profiling using limited numbers of treatments for phenotypes of interest. Herein, we apply co-expression network analysis to safety assessment using rat liver gene expression data to define 415 modules, exhibiting unique transcriptional control, organized in a visual representation of the transcriptome (the 'TXG-MAP'). Accounting for the overall transcriptional activity resulting from treatment, we explain mechanisms of toxicity and predict distinct toxicity phenotypes using module associations. We demonstrate that early network responses complement traditional histology-based assessment in predicting outcomes for longer studies and identify a novel mechanism of hepatotoxicity involving endoplasmic reticulum stress and Nrf2 activation. Module-based molecular subtypes of cholestatic injury derived using rat translate to human. Moreover, compared to gene-level analysis alone, combining module and gene-level analysis performed in sequence identifies significantly more phenotype-gene associations, including established and novel biomarkers of liver injury.

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Systems toxicology of chemically induced liver and kidney injuries: histopathology‐associated gene co‐expression modules

Cited by 21 publications

References 36 publications

Identification of the Toxicity Pathways Associated With Thioacetamide-Induced Injuries in Rat Liver and Kidney

Identification of the Toxicity Pathways Associated With Thioacetamide-Induced Injuries in Rat Liver and Kidney

Concordance between Thioacetamide-Induced Liver Injury in Rat and Human In Vitro Gene Expression Data

Toxicogenomic module associations with pathogenesis: a network-based approach to understanding drug toxicity

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