Methapyrilene hepatotoxicity is associated with increased hepatic glutathione, the formation of glucuronide conjugates, and enterohepatic recirculation

An entropy weight method to integrate big omics and mechanistically evaluate DILI

BACKGROUND AND AIMS

DILI accounts for more than half of acute liver failure cases in the United States and is a major health care issue for the public worldwide. As investigative toxicology is playing an evolving role in the pharmaceutical industry, mechanistic insights into drug hepatotoxicity can facilitate drug development and clinical medication.

METHODS

By integrating multisource datasets including gene expression profiles of rat livers from open TG-GATE database and DrugMatrix, drug labels from FDA Liver Toxicity Knowledge Base, and clinical reports from LiverTox, and with the employment of bioinformatic and computational tools, this study developed an approach to characterize and predict DILI based on the molecular understanding of the processes (toxicity pathways).

RESULTS

A panel of 11 pathways widely covering biological processes and stress responses was established using a training set of six positive and one negative DILI drugs from open TG-GATEs. An entropy weight method-based model was developed to weight responsive genes within a pathway, and an interpretable machine-learning (ML) model XGBoot-SHAP was trained to rank the importance of pathways to the panel activity. The panel activity was proven to differentiate between injured and noninjured sample points and characterize DILI manifestation using six training drugs. Next, the model was tested using an additional 89 drugs (61 positives + 28 negatives), and a precision of 86% and higher can be achieved.

CONCLUSIONS

This study provides a novel approach to mechanisms-driven prediction modeling, as well as big data integration for insights into pharmacology and other human biology areas.

Phenotypic and biomarker evaluation of zebrafish larvae as an alternative model to predict mammalian hepatotoxicity

Zebrafish phenotypic assays have shown promise to assess human hepatotoxicity, though scoring of liver morphology remains subjective and difficult to standardize. Liver toxicity in zebrafish larvae at 5 days was assessed using gene expression as the biomarker approach, complementary to phenotypic analysis and analytical data on compound uptake. This approach aimed to contribute to improved hepatotoxicity prediction, with the goal of identifying biomarker(s) as a step towards the development of transgenic models for prioritization. Morphological effects of hepatotoxic compounds (acetaminophen, amiodarone, coumarin, methapyrilene and myclobutanil) and saccharin as the negative control were assessed after exposure in zebrafish larvae. The hepatotoxic compounds induced the expected zebrafish liver degeneration or changes in size, whereas saccharin did not have any phenotypic adverse effect. Analytical methods based on liquid chromatography-mass spectrometry were optimized to measure stability of selected compounds in exposure medium and internal concentration in larvae. All compounds were stable, except amiodarone for which precipitation was observed. There was a wide variation between the levels of compound in the zebrafish larvae with a higher uptake of amiodarone, methapyrilene and myclobutanil. Detection of hepatocyte markers (CP, CYP3A65, GC and TF) was accomplished by in situ hybridization of larvae to coumarin and myclobutanil and confirmed by real-time reverse transcription-quantitative polymerase chain reaction. Experiments showed decreased expression of all markers. Next, other liver-specific biomarkers (i.e. FABP10a and NR1H4) and apoptosis (i.e. CASP-3 A and TP53) or cytochrome P450-related (CYP2K19) and oxidoreductase activity-related (ZGC163022) genes, were screened. Links between basic mechanisms of liver injury and results of biomarker responses are described. Copyright © 2016 John Wiley & Sons, Ltd.

Toxicity Originating from Thiophene Containing Drugs: Exploring the Mechanism using Quantum Chemical Methods

Drug metabolism of thiophene containing substrates by cytochrome P450s (CYP450) leads to toxic side effects, for example, nephrotoxicity (suprofen, ticlopidine), hepatotoxicity (tienilic acid), thrombotic thrombocytopenic purpura (clopidogrel), and aplastic anemia (ticlopidine). The origin of toxicity in these cases has been attributed to two different CYP450 mediated metabolic reactions: S-oxidation and epoxidation. In this work, the molecular level details of the bioinorganic chemistry associated with the generation of these competitive reactions are reported. Density functional theory was utilized (i) to explore the molecular mechanism for S-oxidation and epoxidation using the radical cationic center Cpd I [(iron(IV)-oxo-heme porphine system with SH(-) as the axial ligand, to mimic CYP450s] as the model oxidant, (ii) to establish the 3D structures of the reactants, transition states, and products on both the metabolic pathways, and (iii) to examine the potential energy (PE) profile for both the pathways to determine the energetically preferred toxic metabolite formation. The energy barrier required for S-oxidation was observed to be 14.75 kcal/mol as compared to that of the epoxidation reaction (13.23 kcal/mol) on the doublet PE surface of Cpd I. The formation of the epoxide metabolite was found to be highly exothermic (-23.24 kcal/mol), as compared to S-oxidation (-8.08 kcal/mol). Hence, on a relative scale the epoxidation process was observed to be thermodynamically and kinetically more favorable. The energy profiles associated with the reactions of the S-oxide and epoxide toxic metabolites were also explored. This study helps in understanding the CYP450-catalyzed toxic reactions of drugs containing the thiophene ring at the atomic level.

Bioactivation potential of thiophene-containing drugs

Thiophene is a five-membered, sulfur-containing heteroaromatic ring commonly used as a building block in drugs. It is considered to be a structural alert, as its metabolism can lead to the formation of reactive metabolites. Thiophene S-oxides and thiophene epoxides are highly reactive electrophilic thiophene metabolites whose formation is cytochrome P450-dependent. These reactive thiophene-based metabolites are quite often responsible for drug-induced hepatotoxicity. Tienilic acid is an example of a thiophene-based drug that was withdrawn from the market after only a few months of use, due to severe cases of immune hepatitis. However, inclusion of the thiophene moiety in drugs does not necessarily result in toxic effects. The presence of other, less toxic metabolic pathways, as well as an effective detoxification system in our body, protects us from the bioactivation potential of the thiophene ring. Thus, the presence of a structural alert itself is insufficient to predict a compound's toxicity. The question therefore arises as to which factors significantly influence the toxicity of thiophene-containing drugs. There is no easy way to answer this question. However, the findings presented here indicate that, for a number of reasons, daily dose and alternative metabolic pathways are important factors when predicting toxicity and will therefore be discussed together with examples.

Assessment of the genotoxic and carcinogenic potentials of 3-aminothiophene derivatives using in vitro and in silico methodologies

Thiophene derivatives, a class of compounds widely used in products such as pharmaceuticals, agrochemicals or dyestuffs, represent chemicals of concern. Indeed, the thiophene ring is often considered as a structural moiety that may be involved in toxic effects in humans. We primarily focus on the genotoxic/mutagenic and carcinogenic potentials of the methyl 3-amino-4-methylthiophene-2-carboxylate (1), a precursor of the articaine local anesthetic (4) which falls within the scope of the European REACH (Registration, Evaluation, Authorisation and restriction of CHemicals) legislation. To discern some structure-toxicity relationships, we also studied two related compounds, namely the 3-amino 4-methylthiophene (2) and the 2-acetyl 4-chlorothiophene (3). Techniques employed to assess mutagenic and DNA-damaging effects involved the Salmonella mutagenicity assay (or Ames test) and the single-cell gel electrophoresis assay (or Comet assay). In the range of tested doses, none of these derivatives led to a positive response in the Ames tests and DNA damage was only observed in the Comet assay after high concentration exposure of 2. The study of their carcinogenic potential using the in vitro SHE (Syrian Hamster Embryo) cell transformation assay (CTA) highlighted the activity of compound 2. A combination of experimental data with in silico predictions of the reactivity of thiophene derivatives towards cytochrome P450 (CYP450), enabled us to hypothesize possible pathways leading to these toxicological profiles.

Modeling drug- and chemical-induced hepatotoxicity with systems biology approaches

We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of “toxicity pathways” is described in the context of the 2007 US National Academies of Science report, “Toxicity testing in the 21st Century: A Vision and A Strategy.” Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity) – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular “virtual tissue” model of the liver lobule that combines molecular circuits in individual hepatocytes with cell–cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the aryl hydrocarbon receptor toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsym™) to understand drug-induced liver injury (DILI), the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

HPLC-MS/MS methods for the quantitative analysis of ophthalmic acid in rodent plasma and hepatic cell line culture medium

Ophthalmic acid (OA), an endogenous tripeptide analogue of glutathione, has been suggested as a potential biomarker for paracetamol/acetaminophen hepatotoxicity. Here HPLC-MS/MS methods have been developed for the precise, sensitive and specific detection and quantification of OA in in vitro cell culture medium and plasma. For the cell culture medium the LLOQ was found to be 1 ng/ml, with less than 1% between sample carry over at all concentrations and precision below 15% for within day and below 9% for between day analyses. For rat plasma the presence of endogenous OA resulted in the LLOQ being 25 ng/ml (defined as the lowest concentration on the calibration curve where the base peak was less than 20% of the LLOQ). For the plasma assay the percentage carry over was less than 1% for all concentrations and within and between batch precision was below 21%. The methods were linear for both sample types from the LLOQ up to 5 μg/ml. The method was successfully applied to the determination of OA in samples obtained following the chronic administration of the rat hepatotoxin methapyrilene, where plasma OA concentrations were observed to show a weak negative correlation with those of established liver injury biomarkers such as aspartate aminotransferase (AST).

Literature-based compound profiling: application to toxicogenomics

Introduction: To reduce continuously increasing costs in drug development, adverse effects of drugs need to be detected as early as possible in the process. In recent years, compound-induced gene expression profiling methodologies have been developed to assess compound toxicity, including Gene Ontology term and pathway over-representation analyses. The objective of this study was to introduce an additional approach, in which literature information is used for compound profiling to evaluate compound toxicity and mode of toxicity. Methods: Gene annotations were built by text mining in Medline abstracts for retrieval of co-publications between genes, pathology terms, biological processes and pathways. This literature information was used to generate compound-specific keyword fingerprints, representing over-represented keywords calculated in a set of regulated genes after compound administration. To see whether keyword fingerprints can be used for assessment of compound toxicity, we analyzed microarray data sets of rat liver treated with 11 hepatotoxicants. Results: Analysis of keyword fingerprints of two genotoxic carcinogens, two nongenotoxic carcinogens, two peroxisome proliferators and two randomly generated gene sets, showed that each compound produced a specific keyword fingerprint that correlated with the experimentally observed histopathological events induced by the individual compounds. By contrast, the random sets produced a flat aspecific keyword profile, indicating that the fingerprints induced by the compounds reflect biological events rather than random noise. A more detailed analysis of the keyword profiles of diethylhexylphthalate, dimethylnitrosamine and methapyrilene (MPy) showed that the differences in the keyword fingerprints of these three compounds are based upon known distinct modes of action. Visualization of MPy-linked keywords and MPy-induced genes in a literature network enabled us to construct a mode of toxicity proposal for MPy, which is in agreement with known effects of MPy in literature. Conclusion: Compound keyword fingerprinting based on information retrieved from literature is a powerful approach for compound profiling, allowing evaluation of compound toxicity and analysis of the mode of action.

Identification of genes implicated in methapyrilene-induced hepatotoxicity by comparing differential gene expression in target and nontarget tissue

BACKGROUND

Toxicogenomics experiments often reveal thousands of transcript alterations that are related to multiple processes, making it difficult to identify key gene changes that are related to the toxicity of interest.

OBJECTIVES

The objective of this study was to compare gene expression changes in a nontarget tissue to the target tissue for toxicity to help identify toxicity-related genes.

METHODS

Male rats were given the hepatotoxicant methapyrilene at two dose levels, with livers and kidneys removed 24 hr after one, three, and seven doses for gene expression analysis. To identify gene changes likely to be related to toxicity, we analyzed genes on the basis of their temporal pattern of change using a program developed at the National Institute of Environmental Health Sciences, termed "EPIG" (extracting gene expression patterns and identifying co-expressed genes).

RESULTS

High-dose methapyrilene elicited hepatic damage that increased in severity with the number of doses, whereas no treatment-related lesions were observed in the kidney. High-dose methapyrilene elicited thousands of gene changes in the liver at each time point, whereas many fewer gene changes were observed in the kidney. EPIG analysis identified patterns of gene expression correlated to the observed toxicity, including genes associated with endoplasmic reticulum stress and the unfolded protein response.

CONCLUSIONS

By factoring in dose level, number of doses, and tissue into the analysis of gene expression elicited by methapyrilene, we were able to identify genes likely to not be implicated in toxicity, thereby allowing us to focus on a subset of genes to identify toxicity-related processes.

System-wide analysis of hepatotoxicological responses: tissomics is key

BACKGROUND

Combining diverse data streams across different levels of biological observation, such as molecular, cellular, and clinical chemistry responses, support a system-wide diagnostic approach. Recent progress in slide-based cytometry contributes to the development of tissomics, a high-throughput and high-content phenotyping methodology that provides data-rich profiles of cellular heterogeneity in tissues enabling correlative statistical treatments over multiple scales of biological hierarchies.

METHODS

Phenotypical data are covariants that can be used as biomarkers to identify relevant candidate genes by associating initiating molecular events with phenotypical changes and adverse outcomes. We introduce a procedure of combined statistical and analytical tools to identify and visualize such associations for nonpooled entities. The new utility is applied to a time-controlled, low-dose toxicological study including a control and two xenobiotic compounds.

RESULTS

An integrated analysis identified specific molecular and phenotypical biomarkers, which support the classification of animals in the absence of any visual indicators from pathology readings.

DISCUSSION

The introduction of controlled perturbations to tissues provides a prototypical setting to develop a sensitive, systems-based analysis methodology suitable for a broader range of biomedical applications.

Systems Toxicology: Integrated Genomic, Proteomic and Metabonomic Analysis of Methapyrilene Induced Hepatotoxicity in the Rat

Administration of high doses of the histamine antagonist methapyrilene to rats causes periportal liver necrosis. The mechanism of toxicity is ill-defined and here we have utilized an integrated systems approach to understanding the toxic mechanisms by combining proteomics, metabonomics by 1H NMR spectroscopy and genomics by microarray gene expression profiling. Male rats were dosed with methapyrilene for 3 days at 150 mg/kg/day, which was sufficient to induce liver necrosis, or a subtoxic dose of 50 mg/kg/day. Urine was collected over 24 h each day, while blood and liver tissues were obtained at 2 h after the final dose. The resulting data further define the changes that occur in signal transduction and metabolic pathways during methapyrilene hepatotoxicity, revealing modification of expression levels of genes and proteins associated with oxidative stress and a change in energy usage that is reflected in both gene/protein expression patterns and metabolites. The difficulties of combining and interpreting multiomic data are considered.

The acquisition and application of absorption, distribution, metabolism, and excretion (ADME) data in agricultural chemical safety assessments

A proposal has been developed by the Agricultural Chemical Safety Assessment (ACSA) Technical Committee of the ILSI Health and Environmental Sciences Institute (HESI) for an improved approach to assessing the safety of crop protection chemicals. The goal is to ensure that studies are scientifically appropriate and necessary without being redundant, and that tests emphasize toxicological endpoints and exposure durations that are relevant for risk assessment. Incorporation of pharmacokinetic studies describing absorption, distribution, metabolism, and excretion is an essential tool for improving the design and interpretation of toxicity studies and their application for safety assessment. A tiered approach is described in which basic pharmacokinetic studies, similar to those for pharmaceuticals, are conducted for regulatory submission. Subsequent tiers provide additional information in an iterative manner, depending on pharmacokinetic properties, toxicity study results, and the intended uses of the compound.

Gene expression analysis of the hepatotoxicant methapyrilene in primary rat hepatocytes: an interlaboratory study

Genomics technologies are used in several disciplines, including toxicology. However, these technologies are relatively new, and their applications require further investigations. When investigators apply these technologies to in vitro experiments, two major issues need to be clarified: a) can in vitro toxicity studies, in combination with genomics analyses, be used to predict the toxicity of a compound; and b) are the generated toxicogenomics data reproducible between laboratories? These questions were addressed by an interlaboratory study with laboratories of four pharmaceutical companies. We evaluated gene expression patterns from cultured rat primary hepatocytes after a 24-hr incubation with methapyrilene (MP). Extensive data analysis showed that comparison of genomics data from different sources is complex because both experimental and statistical variability are important confounding factors. However, appropriate statistical tools allowed us to use gene expression profiles to distinguish high-dose-treated cells from vehicle-treated cells. Moreover, we correctly identified MP in an independently generated in vitro database, underlining that in vitro toxicogenomics could be a predictive tool for toxicity. From a mechanistic point of view, despite the observed site-to-site variability, there was good concordance regarding the affected biologic processes. Several subsets of regulated genes were obtained by analyzing the data sets with one method or using different statistical analysis methods. The identified genes are involved in cellular processes that are associated to the exposure of primary hepatocytes to MP. Whether they are specific for MP and are cause or consequence of the toxicity requires further investigations.

Methapyrilene toxicity: anchorage of pathologic observations to gene expression alterations

Methapyrilene (MP) exposure of animals can result in an array of adverse pathological responses including hepatotoxicity. This study investigates gene expression and histopathological alterations in response to MP treatment in order to 1) utilize computational approaches to classify samples derived from livers of MP treated rats based on severity of toxicity incurred in the corresponding tissue, 2) to phenotypically anchor gene expression pattems, and 3) to gain insight into mechanism(s) of methapyrilene hepatotoxicity. Large-scale differential gene expression levels associated with the exposure of male Sprague-Dawley rats to the rodent hepatic carcinogen MP for 1, 3, or 7 days after daily dosage with 10 or 100 mg/kg/day were monitored. Hierarchical clustering and principal component analysis were successful in classifying samples in agreement with microscopic observations and revealed low-dose effects that were not observed histopathologically. Data from cDNA microarray analysis corroborated observed histopathological alterations such as hepatocellular necrosis, bile duct hyperplasia, microvesicular vacuolization, and portal inflammation observed in the livers of MP exposed rats and provided insight into the role of specific genes in the studied toxicological processes.