Introduction Toxicogenomics

Nuwasyir and colleagues (1) in 1999 defined 'toxicogenomics' as the intersection of toxicology and genomics. They proposed that the goal of this new discipline is to identify potential toxicants and to clarify their mechanism of action with the help of genomics resources. Since then, major efforts have been undertaken to establish data sets that include a diversity of compounds and environmental stressors. This will eventually allow classification of unknown or novel compounds into mechanistic groups. By doing so, researchers hope to achieve toxicant or toxicant-group-specific genomic signatures which indicate exposure and initiation of toxic events. This might not only be valid for known and already well-defined toxicants, but perhaps more importantly, for unknown toxicants or compounds under development. Achieving this goal would allow identification of potential toxicity prior to indications of overt toxicity for novel compounds and could allow for very sensitive exposure monitoring. Several groups have undertaken efforts to classify compounds based on gene expression data. One of the first classification studies in toxicogenomics was published by Waring et al. in 2001 (2). Here the authors retrieved gene expression data from livers of rats exposed to 15 different hepatotoxicants and showed correlations between differentially expressed genes, histopathological and clinical chemistry changes. They also demonstrated that gene expression analysis allows for the identification of mechanistically related compounds and reveals a higher degree of similarity between RNA derived from animals treated with the same compound than to those exposed to other hepato-toxicants. Hamadeh and colleagues in 2002 performed the first toxicological classification study that included blinded samples. In this study, the authors first determined gene expression patterns for three different peroxisome proliferators and one barbiturate (3). This data was utilized as a training set and identified discriminating signatures between compounds. Coded RNA samples from animals exposed to either a barbiturate or peroxisome proliferators were subjected to gene expression analysis. This study demonstrated that it was possible to predict the class of compound to which the rats were exposed based on gene expression profiles for those blinded liver RNA samples (4).

Mechanisms of toxicity

Comparison of gene expression profiles of novel or poorly defined compounds with those from well-defined drugs or toxicants can not only assign those compounds to a known class, but also elucidate potential mechanisms of action. This is based on the assumption that monitoring global gene expression changes as a result of exposure gives indications about which physiological or pathological processes within the organ are activated or repressed. Waring and colleagues (5) demonstrated this analysis in a study in which rats were exposed to a thienopyridine inhibitor (A-277249) and liver tissue was examined for gene expression changes. Comparison of those changes with a database of profiles from 15 known hepatotoxicants elucidated greatest similarity of the test compound with two known activators of the aryl hydrocarbon nuclear receptor (AhR). They concluded that the activation of AhR mediated the hepatic toxicity observed after exposure to A-277249 (5).

Acetaminophen as a model compound

We chose acetaminophen (APAP), one of the most popular analgesics worldwide, as a model compound to study genomic responses in liver tissue. This choice was driven by several criteria we believe to be of crucial importance for compound selection. First, APAP is the focus of major health concerns in the US and Europe. Accidental overdoses and ingestions with suicidal intent make APAP the leading cause of drug-induced acute liver failure in the United States (6). Secondly, rodents metabolize APAP similar to humans and are therefore an appropriate model system. APAP is metabolized by several isoforms of cytochrome p450 to the highly reactive metabolite N-acetyl-p-benzoquinone imine (NAPQI). At low, therapeutic concentrations, this metabolite is detoxified by conjugation with glutathione (GSH). At high, toxic concentrations, the liver is depleted of GSH and NAPQI is covalently bound to proteins (7). Thirdly, significant information already exists about APAP metabolism and toxicity in the liver. Toxicogenomics as an emerging field can benefit from placing the results in context with a wealth of previously well-documented published findings - with the goal to recapitulate and expand existing knowledge.

Experimental design

In this study, we treated rats with a single dose of 0, 50, 150 or 1500 mg kg-1 body weight (BW) APAP and sacrificed them 6, 24 or 48 h after treatment. Livers were harvested for gene expression and histopathological analysis, and blood was collected for serum chemistry. While the two lower doses showed neither histopathological nor serum enzyme alterations, 1500 mg kg-1 APAP induced signs of centrilobular necrosis and significant serum enzyme elevations 24 and 48 h after treatment (8).

In order to perform gene expression analysis, total RNA was isolated from liver tissue and microarray analysis was performed as described in the Protocols. The complete data set is available at: http://dir.niehs.nih.gov/ microarray/datasets/home-pub.htm. After performing cluster analysis (9) with all differentially expressed genes across all doses and time points, it became obvious that a distinct subset of genes was regulated similarly after low and high dose exposure to APAP (8). Further analysis of these gene expression responses revealed that those genes regulated in common after high- and low-dose exposure belonged to distinct metabolic pathways. Many of the genes down-regulated after treatment with 50 or 150 mg kg-1 APAP were involved in energy consuming biochemical pathways like gluco-neogenesis, fatty acid synthesis, cholesterol synthesis, porphyrin synthesis, sterol synthesis and the urea cycle (8). Analysis of differentially expressed genes after 1500 mg kg-1 APAP showed, besides other changes, a strong down regulation of genes in those same energy demanding processes. Not only were similar gene changes observed after this higher dose, but more members of the same biological pathway were changed.

The converse was true with up-regulated genes involving energy production. After treatment with 150 mg kg-1 APAP, genes involved in energy producing biochemical pathways like glycolysis and mitochondrial ra-hydroxylation were up regulated. Exposure to 1500 mg kg-1 APAP resulted in a more pronounced effect on the same processes, as well as additional genes in those processes that were over-expressed in comparison to control livers. Also, genes in other energy producing pathways like the tricarboxylic acid cycle, pentose phosphate pathway, and mitochondrial P-oxidation were up-regulated after exposure to 1500 mg kg-1 APAP.

We concluded from these results that the liver appeared to be compensating for energy depletion after exposure to an overtly toxic dose of APAP (1500 mg kg-1). Strikingly, similar responses were seen in livers following exposure to sub-toxic doses of APAP (50 and 150 mg kg-1), even though there was no histopathological evidence of toxicity after those low doses. As might be predicted, these attempts of the liver to compensate for energy depletion were more pronounced after exposure to the clearly toxic dose of 1500 mg kg-1 APAP.

To test the hypothesis that the liver suffered from energy depletion after exposure to APAP, we performed measurements of ATP levels in liver tissue after exposure to high and low doses of APAP. As shown in Figure 2.1, statistically significant decreases in ATP levels were found only at 3 and 48 h after exposure to 1500 mg kg-1 APAP. Doses of 50 and 150 mg kg-1 APAP did not produce any significant decreases of ATP levels as measured in this assay.

The gene expression profile suggested energy depletion after all doses. We suspected that the ATP assay lacked the necessary sensitivity to show slight decreases, since energy depletion may have occurred only in a small subpopulation of hepatocytes immediately adjacent to the central vein where toxicity is first seen. As the production of ATP in the cell is primarily a function of mitochondria, we hypothesized that the energy depletion after APAP exposure was caused by mitochondrial damage. Therefore we performed ultrastructural analysis on liver tissue after treatment with 0, 50, 150 or 1500 mg kg-1 APAP. Six hours after treatment with 150 and

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Figure 2.1.

Hepatic ATP levels after exposure to APAP: (A) 3 h, (B) 6 h, (C) 24 h and (D) 48 h after exposure to acetaminophen. Bar graphs represent pmol ATP per |jg protein (mean ± S.E.). Asterisks indicates p <0.02 for statistical differences between animals treated with APAP and sham-treated control animals (n =3).

1500 mg kg-1 APAP we found mitochondria that had lost electron density, indicative of mitochondrial damage after those doses (Figure 2.2). At 150 mg kg-1 only a few hepatocytes immediately adjacent to the central vein had evidence of mitochondrial toxicity. This suggests that, at least for acetaminophen, gene expression changes may be a more sensitive indicator of potential toxicity than traditional toxicology endpoints such as histopathology and clinical chemistry.

We concluded from our study that liver gene expression profiles in response to exposure to sub-toxic doses of APAP have the ability to indicate potential toxicity of higher doses of this hepatotoxicant. We identified gene expression changes indicative of cellular ATP depletion after sub-toxic doses (50 and 150 mg kg-1 APAP), and found that those changes became more pronounced after exposure to a toxic dose (1500 mg kg-1 APAP). Therefore, microarray analysis appears to be an extremely useful and sensitive tool to predict potential adverse effects of exposures.

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