Metabolomics: a tool for early detection of toxicological effects and an opportunity for biology based grouping of chemicals-from QSAR to QBAR.

BASF has developed a Metabolomics database (MetaMap(®) Tox) containing approximately 500 data rich chemicals, agrochemicals and drugs. This metabolome-database has been built based upon 28-day studies in rats (adapted to OECD 407 guideline) with blood sampling and metabolic profiling after 7, 14 and 28 days of test substance treatment. Numerous metabolome patterns have been established for different toxicological targets (liver, kidney, thyroid, testes, blood, nervous system and endocrine system) which are specific for different toxicological modes of action. With these patterns early detection of toxicological effects and the underlying mechanism can now be obtained from routine studies. Early recognition of toxicological mode of action will help to develop new compounds with a more favourable toxicological profile and will also help to reduce the number of animal studies necessary to do so. Thus this technology contributes to animal welfare by means of reduction through refinement (2R), but also has potential as a replacement method by analyzing samples from in vitro studies. With respect to the REACH legislation for which a large number of animal studies will need to be performed, one of the most promising methods to reduce the number of animal experiments is grouping of chemicals and read-across to those which are data rich. So far mostly chemical similarity or QSAR models are driving the selection process of chemical grouping. However, "omics" technologies such as metabolomics may help to optimize the chemical grouping process by providing biologically based criteria for toxicological equivalence. "From QSAR to QBAR" (quantitative biological activity relationship).

The use of metabolomics for the discovery of new biomarkers of effect.

Will metabolomics have a greater chance of success in toxicology and biomarker assessment than genomics and proteomics? Metabolomics has the advantage that (1) it analyses the last step in a series of changes following a toxic insult, (2) many of the metabolites have a known function and (3) changes are detectable in blood. If the analysis of a great number of individual organs can be replaced by one matrix then this will provide significant advantages (less invasive method, no need to kill animals, time course analysis possible). We have chosen to perform the analysis of blood metabolites in such a way as to minimize the risk of artifacts and to have a high number of known metabolites. We have also reduced the amount of variation in the biological system as well as during analysis. In a series of proof of concept studies it could be demonstrated that (1) the metabolome of control animals was stable of a period of nearly 1 year, with a remarkable differentiation between males and females, (2) a dose response relationship in metabolome changes was induced by phenobarbital and that (3) different modes of action could be distinguished by blood metabolome analysis. To investigate the potential of metabolomics to find biomarkers or specific patterns of change we have analyzed the blood metabolome of rats treated with HPPD inhibitors, a novel class of herbicides. The results demonstrated that a single metabolite, tyrosine, can be used as a biomarker. In addition to tyrosine we also found a specific pattern of change that involved nine metabolites. Though the extent of change was less than for tyrosine the consistent change of these metabolites is diagnostic for this (toxicological) mode of action.

Detection of hepatotoxicity potential with metabolite profiling (metabolomics) of rat plasma.

While conventional parameters used to detect hepatotoxicity in drug safety assessment studies are generally informative, the need remains for parameters that can detect the potential for hepatotoxicity at lower doses and/or at earlier time points. Previous work has shown that metabolite profiling (metabonomics/metabolomics) can detect signals of potential hepatotoxicity in rats treated with doxorubicin at doses that do not elicit hepatotoxicity as monitored with conventional parameters. The current study extended this observation to the question of whether such signals could be detected in rats treated with compounds that can elicit hepatotoxicity in humans (i.e., drug-induced liver injury, DILI) but have not been reported to do so in rats. Nine compounds were selected on the basis of their known DILI potential, with six other compounds chosen as negative for DILI potential. A database of rat plasma metabolite profiles, MetaMap(®)Tox (developed by metanomics GmbH and BASF SE) was used for both metabolite profiles and mode of action (MoA) metabolite signatures for a number of known toxicities. Eight of the nine compounds with DILI potential elicited metabolite profiles that matched with MoA patterns of various rat liver toxicities, including cholestasis, oxidative stress, acetaminophen-type toxicity and peroxisome proliferation. By contrast, only one of the six non-DILI compounds showed a weak match with rat liver toxicity. These results suggest that metabolite profiling may indeed have promise to detect signals of hepatotoxicity in rats treated with compounds having DILI potential.

Prediction of clinically relevant safety signals of nephrotoxicity through plasma metabolite profiling.

Addressing safety concerns such as drug-induced kidney injury (DIKI) early in the drug pharmaceutical development process ensures both patient safety and efficient clinical development. We describe a unique adjunct to standard safety assessment wherein the metabolite profile of treated animals is compared with the MetaMap Tox metabolomics database in order to predict the potential for a wide variety of adverse events, including DIKI. To examine this approach, a study of five compounds (phenytoin, cyclosporin A, doxorubicin, captopril, and lisinopril) was initiated by the Technology Evaluation Consortium under the auspices of the Drug Safety Executive Council (DSEC). The metabolite profiles for rats treated with these compounds matched established reference patterns in the MetaMap Tox metabolomics database indicative of each compound's well-described clinical toxicities. For example, the DIKI associated with cyclosporine A and doxorubicin was correctly predicted by metabolite profiling, while no evidence for DIKI was found for phenytoin, consistent with its clinical picture. In some cases the clinical toxicity (hepatotoxicity), not generally seen in animal studies, was detected with MetaMap Tox. Thus metabolite profiling coupled with the MetaMap Tox metabolomics database offers a unique and powerful approach for augmenting safety assessment and avoiding clinical adverse events such as DIKI.

Reproducibility and robustness of metabolome analysis in rat plasma of 28-day repeated dose toxicity studies.

BASF has developed a rat plasma metabolomics database (MetaMap®Tox) containing the metabolome of more than 500 chemicals, agrochemicals and drugs, for which the toxicity is well known, derived from 28-day repeated dose toxicity studies in rats. The quality/reproducibility of data was assessed by comparing the metabolome of 16 reference compounds tested at least twice under identical experimental conditions at three time points (day 7, day 14 and day 28). Statistical correlation analysis showed that the repeated treatment induced very similar changes to the metabolome. For all repetitions the modes of action of the compounds were always correctly identified. Moreover, when compared against the metabolome of all compounds available in the MetaMap®Tox database, the repetitions showed in most cases the highest degree of overall similarity with the metabolome of the original study. In addition, we also evaluated the robustness of our metabolomics technique, displayed by constancy of variability in control groups over time. Based on these results, it can be concluded, that metabolomics can reproducibly be applied during toxicological in vivo testing in rats under the conditions applied here.

Increased toxicity when fibrates and statins are administered in combination--a metabolomics approach with rats.

Combination therapies with fibrates and statins are used to treat cardiovascular diseases, because of their synergistic effect on lowering plasma lipids. However, fatal side-effects like rhabdomyolysis followed by acute renal necrosis sometimes occur. To elucidate biochemical changes resulting from the interaction of fibrates and statins, doses of 100 mg/kg fenofibrate, 50mg/kg clofibrate, 70 mg/kg atorvastatin and 200 mg/kg pravastatin as well as combinations thereof were administered to Crl:Wi(Han) rats for 4 weeks. Plasma metabolome profile was measured on study days 7, 14 and 28. Upon study termination, clinical pathology parameters were measured. In a separate experiment plasmakinetic data were measured in male rats after 1 week of drug administration in monotherapy as well as in combinations. Lowering of blood lipid levels as well as toxicological effects, like liver cell degradation (statins) and anemia (fibrates) and distinct blood metabolite level alterations were observed in monotherapy. When fibrates and statins were co-administered metabolite profile interactions were generally underadditive or at the utmost additive according to the linear mixed effect model. However, more metabolite levels were significantly altered during combination therapy. New effects on the antioxidant status and the cardiovascular system were found which may be related to a development of rhabdomyolysis. Accumulation of drugs during the combination therapy was not observed.

Application of in vivo metabolomics to preclinical/toxicological studies: case study on phenytoin-induced systemic toxicity.

BASF and Metanomics have built-up the database MetaMap(®)-Tox containing rat plasma metabolome data for more than 500 reference compounds. Phenytoin was administered to five Wistar rats of both sexes at dietary dose levels of 600 and 2400 ppm over 28 days and metabolome analysis was performed on days 7, 14 and 28. Clinical pathology did not indicate clear evidence for liver toxicity, whereas liver histopathology revealed slight centrilobular hepatocellular hypertrophy. The metabolome analysis of phenytoin shows metabolome changes at both dose levels and the comparison with MetaMap-Tox indicated strong evidence for liver enzyme induction, as well as liver toxicity. Moreover, evidence for kidney and indirect thyroid effects were observed. This assessment was based on the metabolite changes induced, similarities to specific toxicity patterns and the whole metabolome correlation within MetaMap-Tox. As compared with the classical read-out, a more comprehensive picture of phenytoin's effects is obtained from the metabolome analysis, demonstrating the added value of metabolome data in preclinical/ toxicological studies.

Nutritional impact on the plasma metabolome of rats.

Metabolite profiling (metabolomics) elucidates changes in biochemical pathways under various conditions, e.g., different nutrition scenarios or compound administration. BASF and metanomics have obtained plasma metabolic profiles of approximately 500 compounds (agrochemicals, chemicals and pharmaceuticals) from 28-day rat studies. With these profiles the establishment of a database (MetaMap(®)Tox) containing specific metabolic patterns associated with many toxicological modes of action was achieved. To evaluate confounding factors influencing metabolome patterns, the effect of fasting vs. non-fasting prior to blood sampling, the influence of high caloric diet and caloric restriction as well as the administration of corn oil and olive oil was studied for its influence on the metabolome. All mentioned treatments had distinct effects: triacylglycerol, phospholipids and their degradation product levels (fatty acids, glycerol, lysophosphatidylcholine) were often altered depending on the nutritional status. Also some amino acid and related compounds were changed. Some metabolites derived from food (e.g. alpha-tocopherol, ascorbic acid, beta-sitosterol, campesterol) were biomarkers related to food consumption, whereas others indicated a changed energy metabolism (e.g. hydroxybutyrate, pyruvate). Strikingly, there was a profound difference in the metabolite responses to diet restriction in male and female rats. Consequently, when evaluating the metabolic profile of a compound, the effect of nutritional status should be taken into account.

The individual and combined metabolite profiles (metabolomics) of dibutylphthalate and di(2-ethylhexyl)phthalate following a 28-day dietary exposure in rats.

Metabolite profiles (metabolomics) of plasma samples of Wistar rats dosed with di(2-ethylhexyl)phthalate (DEHP - 3000ppm) and dibutylphthalate (DBP - 150, 1000 and 7000ppm) were individually determined in 28 days dietary studies. In addition, profiles of combined exposure to 3000ppm DEHP and either 150, 1000 or 7000ppm DBP were determined. High dose levels induced more profound metabolite changes in males than in females for both compounds. At 150ppm DBP (NOEL for toxicity) there were very few (

Influence of strain and sex on the metabolic profile of rats in repeated dose toxicological studies.

The impact of the strain on the metabolite profile of plasma samples in rats dosed with 2500 ppm 2-methyl-4-chlorophenoxyacetic acid (MCPA acid) or 45 mg/kg bw/day 4-chloro-3-nitroaniline (4C3N) for 4 weeks was evaluated. Four different strains were used: two Wistar strains (Crl:WI(Han), Han:RCC:WIST(SPF)), one Sprague-Dawley (Crl:CD) and one Fisher strain (F-344/Crl). The metabolite profiles in the plasma were measured by LC-MS and GC-MS. The profound changes of the metabolite values induced by the MCPA acid treatment outweighed slight deviations caused by physiological variations between the different rat strains. The metabolome changes of the MCPA acid in all strains could be related to toxicological "mode of action" patterns (peroxisome proliferator, renal organic anionic transporter inhibition) with Crl:WI(Han) rats as reference strain. 4C3N administration led to extravascular hemolytic anemia with a small number of metabolome changes, which were strain dependent. The metabolome pattern associated with "hemolytic anemia" established with the reference strain (Crl:Wi(Han)) was not sufficiently similar in other strains. Thus, comparable metabolome profiles were obtained in different rat strains for a compound inducing profound metabolite changes. For a compound with a weak profile the results were more variable and appeared to be strain dependent.