Multicenter Study of Acetaminophen Hepatotoxicity Reveals the Importance of Biological Endpoints in Genomic Analyses

Deletion of apoptosis signal-regulating kinase 1 attenuates acetaminophen-induced liver injury by inhibiting c-Jun N-terminal kinase activation

BACKGROUND & AIMS

Acetaminophen (APAP) overdose is the most frequent cause of drug-induced liver failure. C-jun N-terminal kinase (JNK) is thought to play a central role in APAP-induced liver injury, although its upstream activator has not yet been identified. Apoptosis signal-regulating kinase 1 (ASK1) is a member of the mitogen-activated protein kinase kinase kinase family and is important for stress-induced JNK activation. We tested the hypothesis that ASK1 was involved in APAP-induced JNK activation and liver injury.

METHODS

ASK1-deficient (ASK1(-/-)) mice and wild-type (WT) mice were given 300 mg/kg of APAP. Serum alanine aminotransferase levels and liver histology were assessed. To investigate the involvement of ASK1 in direct hepatocellular damage and the subsequent inflammatory response, we used primary hepatocytes and splenocytes from WT and ASK1(-/-) mice.

RESULTS

In ASK1(-/-) mouse liver, APAP toxicity was attenuated significantly and the prolonged activation of JNK was inhibited. In addition, thioredoxin, a direct ASK1 inhibitor, dissociated from ASK1 after APAP overdose with concomitant ASK1 activation. Although the prolonged activation of p38 also was attenuated in ASK1(-/-) mice, the p38 signaling pathway was not likely to be involved in APAP-induced liver injury. Primary hepatocyte culture also revealed that ASK1 and JNK, but not p38, contributed to direct APAP-induced cellular damage.

CONCLUSIONS

Our data suggest that ASK1 is activated by APAP overdose, most likely via a mechanism involving thioredoxin-ASK1 dissociation, and that it plays a role in APAP-induced liver injury through JNK activation.

Towards standards for data exchange and integration and their impact on a public database such as CEBS (Chemical Effects in Biological Systems)

Integration, re-use and meta-analysis of high content study data, typical of DNA microarray studies, can increase its scientific utility. Access to study data and design parameters would enhance the mining of data integrated across studies. However, without standards for which data to include in exchange, and common exchange formats, publication of high content data is time-consuming and often prohibitive. The MGED Society (www.mged.org) was formed in response to the widespread publication of microarray data, and the recognition of the utility of data re-use for meta-analysis. The NIEHS has developed the Chemical Effects in Biological Systems (CEBS) database, which can manage and integrate study data and design from biological and biomedical studies. As community standards are developed for study data and metadata it will become increasingly straightforward to publish high content data in CEBS, where they will be available for meta-analysis. Different exchange formats for study data are being developed: Standard for Exchange of Nonclinical Data (SEND; www.cdisc.org); Tox-ML (www.Leadscope.com) and Simple Investigation Formatted Text (SIFT) from the NIEHS. Data integration can be done at the level of conclusions about responsive genes and phenotypes, and this workflow is supported by CEBS. CEBS also integrates raw and preprocessed data within a given platform. The utility and a method for integrating data within and across DNA microarray studies is shown in an example analysis using DrugMatrix data deposited in CEBS by Iconix Pharmaceuticals.

Gene expression response in target organ and whole blood varies as a function of target organ injury phenotype

This report details the standardized experimental design and the different data streams that were collected (histopathology, clinical chemistry, hematology and gene expression from the target tissue (liver) and a bio-available tissue (blood)) after treatment with eight known hepatotoxicants (at multiple time points and doses with multiple biological replicates). The results of the study demonstrate the classification of histopathological differences, likely reflecting differences in mechanisms of cell-specific toxicity, using either liver tissue or blood transcriptomic data.

Global transcriptome and deletome profiles of yeast exposed to transition metals

A variety of pathologies are associated with exposure to supraphysiological concentrations of essential metals and to non-essential metals and metalloids. The molecular mechanisms linking metal exposure to human pathologies have not been clearly defined. To address these gaps in our understanding of the molecular biology of transition metals, the genomic effects of exposure to Group IB (copper, silver), IIB (zinc, cadmium, mercury), VIA (chromium), and VB (arsenic) elements on the yeast Saccharomyces cerevisiae were examined. Two comprehensive sets of metal-responsive genomic profiles were generated following exposure to equi-toxic concentrations of metal: one that provides information on the transcriptional changes associated with metal exposure (transcriptome), and a second that provides information on the relationship between the expression of ∼4,700 non-essential genes and sensitivity to metal exposure (deletome). Approximately 22% of the genome was affected by exposure to at least one metal. Principal component and cluster analyses suggest that the chemical properties of the metal are major determinants in defining the expression profile. Furthermore, cells may have developed common or convergent regulatory mechanisms to accommodate metal exposure. The transcriptome and deletome had 22 genes in common, however, comparison between Gene Ontology biological processes for the two gene sets revealed that metal stress adaptation and detoxification categories were commonly enriched. Analysis of the transcriptome and deletome identified several evolutionarily conserved, signal transduction pathways that may be involved in regulating the responses to metal exposure. In this study, we identified genes and cognate signaling pathways that respond to exposure to essential and non-essential metals. In addition, genes that are essential for survival in the presence of these metals were identified. This information will contribute to our understanding of the molecular mechanism by which organisms respond to metal stress, and could lead to an understanding of the connection between environmental stress and signal transduction pathways.

Environmental and human health threats are posed by contamination from transition metals. A variety of pathologies are associated with exposure to supraphysiological concentrations of essential metals and to non-essential metals and metalloids. To defend against metal toxicity, sophisticated defense mechanisms have evolved. Although many of the genes and regulatory pathways have been identified, the consequence of metal exposure on a systematic level has not been examined. To better define the mechanism involved in the metal response, we examined the effects of zinc, cadmium, mercury, copper, silver, chromium, and arsenic on gene expression in the yeast Saccharomyces cerevisiae. In addition, the roles of ∼4,500 non-essential genes in protecting yeast from metal toxicity were determined. Data analyses suggest that the chemical properties of the metal are major determinants in defining its biological effect on cells. Furthermore, cells may have developed common or convergent regulatory mechanisms to accommodate metal exposure. Several evolutionarily conserved regulatory pathways were identified that link metal exposure, disruption of normal metabolism and gene expression. These results provide a global understanding of the biological responses to metal exposure and the stress response.

Pathway analysis tools and toxicogenomics reference databases for risk assessment

The pharmaceutical industry has begun to leverage a range of new technologies (proteomics, pharmacogenomics, metabolomics and molecular toxicology [e.g., toxicogenomics]) and analysis tools that are becoming increasingly integrated in the area of drug discovery and development. The approach of analyzing the vast amount of toxicogenomics data generated using molecular pathway and networks analysis tools in combination with analysis of reference data will be the main focus of this review. We will demonstrate how this combined approach can increase the understanding of the molecular mechanisms that lead to chemical-induced toxicity and application of this knowledge to compound risk assessment. We will provide an example of the insights achieved through a molecular toxicology analysis based on the well-known hepatotoxicant lipopolysaccharide to illustrate the utility of these new tools in the analysis of complex data sets, both in vivo and in vitro. The ultimate objective is a better lead selection process that improves the chances for success across the different stages of drug discovery and development.

The plasma proteome, adductome and idiosyncratic toxicity in toxicoproteomics research

Toxicoproteomics uses the discovery potential of proteomics in toxicology research by applying global protein measurement technologies to biofluids and tissues after host exposure to injurious agents. Toxicoproteomic studies thus far have focused on protein profiling of major organs and biofluids such as liver and blood in preclinical species exposed to model toxicants. The slow pace of discovery for new biomarkers, toxicity signatures and mechanistic insights is partially due to the limited proteome coverage derived from analysis of native organs, tissues and body fluids by traditional proteomic platforms. Improved toxicoproteomic analysis would result by combining higher data density LC-MS/MS platforms with stable isotope labelled peptides and parallel use of complementary platforms. Study designs that remove abundant proteins from biofluids, enrich subcellular structures and include cell specific isolation from heterogeneous tissues would greatly increase differential expression capabilities. By leveraging resources from immunology, cell biology and nutrition research communities, toxicoproteomics could make particular contributions in three inter-related areas to advance mechanistic insights and biomarker development: the plasma proteome and circulating microparticles, the adductome and idiosyncratic toxicity.