Detection of hepatotoxicity potential with metabolite profiling (metabolomics) of rat plasma. Toxicol Lett. 2014;230:467-478. [PMID: 25086301 DOI: 10.1016/j.toxlet.2014.07.021]

Molecular signatures of angiogenesis inhibitors: a single-embryo untargeted metabolomics approach in zebrafish

Angiogenesis is a key process in embryonic development, a disruption of this process can lead to severe developmental defects, such as limb malformations. The identification of molecular perturbations representative of antiangiogenesis in zebrafish embryo (ZFE) may guide the assessment of developmental toxicity from an endpoint- to a mechanism-based approach, thereby improving the extrapolation of findings to humans. Thus, the aim of the study was to discover molecular changes characteristic of antiangiogenesis and developmental toxicity. We exposed ZFEs to two antiangiogenic drugs (SU4312, sorafenib) and two developmental toxicants (methotrexate, rotenone) with putative antiangiogenic action. Molecular changes were measured by performing untargeted metabolomics in single embryos. The metabolome response was accompanied by the occurrence of morphological alterations. Two distinct metabolic effect patterns were observed. The first pattern comprised common effects of two specific angiogenesis inhibitors and the known teratogen methotrexate, strongly suggesting a shared mode of action of antiangiogenesis and developmental toxicity. The second pattern involved joint effects of methotrexate and rotenone, likely related to disturbances in energy metabolism. The metabolites of the first pattern, such as phosphatidylserines, pterines, retinol, or coenzyme Q precursors, represented potential links to antiangiogenesis and related developmental toxicity. The metabolic effect pattern can contribute to biomarker identification for a mechanism-based toxicological testing.

The short-term toxicity and metabolome of dicyclopentadiene

Dicyclopentadiene (DCPD) was investigated in a 14-day oral rat toxicity study based on the OECD 407 guideline in combination with plasma metabolomics. Wistar rats received the compound daily via gavage at dose levels of 0, 50 and 150 mg/kg bw. The high dose induced transient clinical signs of toxicity and in males only reduced body weight gain. High dose liver changes were characterized by altered clinical chemistry parameters in both sexes and pathological changes in females. In high dose males an accumulation of alpha-2 u-globulin in the kidney was noted. Comparing the DCPD metabolome with previously established specific metabolome patterns in the MetaMap® Tox data base suggested that the high dose would result in liver enzyme induction leading to increased breakdown of thyroid hormones for males and females. An indication for liver toxicity in males was also noted. Metabolomics also suggested an effect on the functionality of the adrenals in high dose males, which together with published data, is suggestive of a stress related effect in this organ. The results of the present 14-day combined toxicity and metabolome investigations were qualitatively in line with literature data from subchronic oral studies in rats with DCPD. Importantly no other types of organ toxicity, or hormone dysregulation beyond the ones associated with liver enzyme induction and stress were indicated, again in line with results of published 90-day studies. It is therefore suggested that short term "smart" studies, combining classical toxicity with 'omics technologies, could be a 2 R (refine and reduce) new approach method allowing for the reduction of in vivo toxicity testing.

Metabolomics in Preclinical Drug Safety Assessment: Current Status and Future Trends

Metabolomics is emerging as a powerful systems biology approach for improving preclinical drug safety assessment. This review discusses current applications and future trends of metabolomics in toxicology and drug development. Metabolomics can elucidate adverse outcome pathways by detecting endogenous biochemical alterations underlying toxicity mechanisms. Furthermore, metabolomics enables better characterization of human environmental exposures and their influence on disease pathogenesis. Metabolomics approaches are being increasingly incorporated into toxicology studies and safety pharmacology evaluations to gain mechanistic insights and identify early biomarkers of toxicity. However, realizing the full potential of metabolomics in regulatory decision making requires a robust demonstration of reliability through quality assurance practices, reference materials, and interlaboratory studies. Overall, metabolomics shows great promise in strengthening the mechanistic understanding of toxicity, enhancing routine safety screening, and transforming exposure and risk assessment paradigms. Integration of metabolomics with computational, in vitro, and personalized medicine innovations will shape future applications in predictive toxicology.

Application of high throughput in vitro metabolomics for hepatotoxicity mode of action characterization and mechanistic-anchored point of departure derivation: a case study with nitrofurantoin

Omics techniques have been increasingly recognized as promising tools for Next Generation Risk Assessment. Targeted metabolomics offer the advantage of providing readily interpretable mechanistic information about perturbed biological pathways. In this study, a high-throughput LC-MS/MS-based broad targeted metabolomics system was applied to study nitrofurantoin metabolic dynamics over time and concentration and to provide a mechanistic-anchored approach for point of departure (PoD) derivation. Upon nitrofurantoin exposure at five concentrations (7.5 µM, 15 µM, 20 µM, 30 µM and 120 µM) and four time points (3, 6, 24 and 48 h), the intracellular metabolome of HepG2 cells was evaluated. In total, 256 uniquely identified metabolites were measured, annotated, and allocated in 13 different metabolite classes. Principal component analysis (PCA) and univariate statistical analysis showed clear metabolome-based time and concentration effects. Mechanistic information evidenced the differential activation of cellular pathways indicative of early adaptive and hepatotoxic response. At low concentrations, effects were seen mainly in the energy and lipid metabolism, in the mid concentration range, the activation of the antioxidant cellular response was evidenced by increased levels of glutathione (GSH) and metabolites from the de novo GSH synthesis pathway. At the highest concentrations, the depletion of GSH, together with alternations reflective of mitochondrial impairments, were indicative of a hepatotoxic response. Finally, a metabolomics-based PoD was derived by multivariate PCA using the whole set of measured metabolites. This approach allows using the entire dataset and derive PoD that can be mechanistically anchored to established key events. Our results show the suitability of high throughput targeted metabolomics to investigate mechanisms of hepatoxicity and derive point of departures that can be linked to existing adverse outcome pathways and contribute to the development of new ones.

Metabolic characteristics of voriconazole - Induced liver injury in rats

Voriconazole (VOR) - induced liver injury is a common adverse reaction, and can lead to serious clinical outcomes. It is of great significance to describe the metabolic characteristics of VOR - induced liver injury and to elucidate the potential mechanisms. This study investigated the changes of plasma metabolic profiles in a rat model of VOR - induced liver injury by non - targeted metabolomics. Correlation analysis was performed between differentially expressed metabolites and plasma liver function indexes. The metabolites with strong correlation were determined for their predictive performance for liver injury using receiver operating characteristic (ROC) curve analysis. Potential biomarkers were then screened combined with liver pathological scores. Finally, the expression level of genes that involved in lipid metabolism were determined in rat liver to verify the mechanism of VOR - induced liver injury we proposed. VOR - induced liver injury in rats was characterized by plasma alanine aminotransferase (ALT) and aspartate aminotransferase (AST) elevation, the lipid droplets accumulation in liver, as well as inflammation and fibrosis. Significant changes of plasma metabolites were observed, with a decrease in lipid metabolites accounting for over 50% of all changed metabolites, and alterations of cholesterol and bile acids metabolites. The decrease of 3 phosphatidylcholine (PC) in plasma could indicate the occurrence of VOR - induced liver injury. Decreased fatty acids (FA) oxidation and bile acid excretion might be the potential mechanisms of VOR - induced liver injury. This study provided new insights into the molecular characterization of VOR - induced liver injury.

A metabolomics approach to reveal the mechanism of developmental toxicity in zebrafish embryos exposed to 6-propyl-2-thiouracil

A crucial component of a substance registration and regulation is the evaluation of human prenatal developmental toxicity. Current toxicological tests are based on mammalian models, but these are costly, time consuming and may pose ethical concerns. The zebrafish embryo has evolved as a promising alternative model to study developmental toxicity. However, the implementation of the zebrafish embryotoxicity test is challenged by lacking information on the relevance of observed morphological alterations in fish for human developmental toxicity. Elucidating the mechanism of toxicity could help to overcome this limitation. Through LC-MS/MS and GC-MS metabolomics, we investigated whether changes to the endogenous metabolites can indicate pathways associated with developmental toxicity. To this aim, zebrafish embryos were exposed to different concentrations of 6-propyl-2-thiouracil (PTU), a compound known to induce developmental toxicity. The reproducibility and the concentration-dependence of the metabolome response and its association with morphological alterations were studied. Major morphological findings were reduced eye size, and other craniofacial anomalies; major metabolic changes included increased tyrosine, pipecolic acid and lysophosphatidylcholine levels, decreased methionine levels, and disturbance of the 'Phenylalanine, tyrosine and tryptophan biosynthesis' pathway. This pathway, and the changes in tyrosine and pipecolic acid levels could be linked to the mode of action of PTU, i.e., inhibition of thyroid peroxidase (TPO). The other findings suggested neurodevelopmental impairments. This proof-of-concept study demonstrated that metabolite changes in zebrafish embryos are robust and provide mechanistic information associated with the mode of action of PTU.

Metabolomic Analysis of Pediatric Patients with Idiosyncratic Drug-Induced Liver Injury According to the Updated RUCAM

Hepatotoxicity, a common adverse drug effect, has been extensively studied in adult patients. However, it is equally important to investigate this condition in pediatric patients to develop personalized treatment strategies for children. This study aimed to identify plasma biomarkers that characterize hepatotoxicity in pediatric patients through an observational case-control study. Metabolomic analysis was conducted on 55 pediatric patients with xenobiotic liver toxicity and 88 healthy controls. The results revealed clear differences between the two groups. Several metabolites, including hydroxydecanoylcarnitine, octanoylcarnitine, lysophosphatidylcholine, glycocholic acid, and taurocholic acid, were identified as potential biomarkers (area under the curve: 0.817; 95% confidence interval: 0.696-0.913). Pathway analysis indicated involvement of primary bile acid biosynthesis and the metabolism of taurine and hypotaurine (p < 0.05). The findings from untargeted metabolomic analysis demonstrated an increase in bile acids in children with hepatotoxicity. The accumulation of cytotoxic bile acids should be further investigated to elucidate the role of these metabolites in drug-induced liver injury.

Assessing the Influence of Propylthiouracil and Phenytoin on the Metabolomes of the Thyroid, Liver, and Plasma in Rats

The thyroid hormones (THs) regulate various physiological mechanisms in mammals, such as cellular metabolism, cell structure, and membrane transport. The therapeutic drugs propylthiouracil (PTU) and phenytoin are known to induce hypothyroidism and decrease blood thyroid hormone levels. To analyze the impact of these two drugs on systemic metabolism, we focused on metabolic changes after treatment. Therefore, in a rat model, the metabolome of thyroid and liver tissue as well as from the blood plasma, after 2-week and 4-week administration of the drugs and after a following 2-week recovery phase, was investigated using targeted LC-MS/MS and GC-MS. Both drugs were tested at a low dose and a high dose. We observed decreases in THs plasma levels, and higher doses of the drugs were associated with a high decrease in TH levels. PTU administration had a more pronounced effect on TH levels than phenytoin. Both drugs had little or no influence on the metabolomes at low doses. Only PTU exhibited apparent metabolome alterations at high doses, especially concerning lipids. In plasma, acylcarnitines and triglycerides were detected at decreased levels than in the controls after 2- and 4-week exposure to the drug, while sphingomyelins and phosphatidylcholines were observed at increased levels. Interestingly, in the thyroid tissue, triglycerides were observed at increased concentrations in the 2-week exposure group to PTU, which was not observed in the 4-week exposure group and in the 4-week exposure group followed by the 2-week recovery group, suggesting an adaptation by the thyroid tissue. In the liver, no metabolites were found to have significantly changed. After the recovery phase, the thyroid, liver, and plasma metabolomic profiles showed little or no differences from the controls. In conclusion, although there were significant changes observed in several plasma metabolites in PTU/Phenytoin exposure groups, this study found that only PTU exposure led to adaptation-dependent changes in thyroid metabolites but did not affect hepatic metabolites.

Connecting Gut Microbial Diversity with Plasma Metabolome and Fecal Bile Acid Changes Induced by the Antibiotics Tobramycin and Colistin Sulfate

The diversity of microbial species in the gut has a strong influence on health and development of the host. Further, there are indications that the variation in expression of gut bacterial metabolic enzymes is less diverse than the taxonomic profile, underlying the importance of microbiome functionality, particularly from a toxicological perspective. To address these relationships, the gut bacterial composition of Wistar rats was altered by a 28 day oral treatment with the antibiotics tobramycin or colistin sulfate. On the basis of 16S marker gene sequencing data, tobramycin was found to cause a strong reduction in the diversity and relative abundance of the microbiome, whereas colistin sulfate had only a marginal impact. Associated plasma and fecal metabolomes were characterized by targeted mass spectrometry-based profiling. The fecal metabolome of tobramycin-treated animals had a high number of significant alterations in metabolite levels compared to controls, particularly in amino acids, lipids, bile acids (BAs), carbohydrates, and energy metabolites. The accumulation of primary BAs and significant reduction of secondary BAs in the feces indicated that the microbial alterations induced by tobramycin inhibit bacterial deconjugation reactions. The plasma metabolome showed less, but still many alterations in the same metabolite groups, including reductions in indole derivatives and hippuric acid, and furthermore, despite marginal effects of colistin sulfate treatment, there were nonetheless systemic alterations also in BAs. Aside from these treatment-based differences, we also uncovered interindividual differences particularly centering on the loss of Verrucomicrobiaceae in the microbiome, but with no apparent associated metabolite alterations. Finally, by comparing the data set from this study with metabolome alterations in the MetaMapTox database, key metabolite alterations were identified as plasma biomarkers indicative of altered gut microbiomes resulting from a wide activity spectrum of antibiotics.

Gut Microbiota as Well as Metabolomes of Wistar Rats Recover within Two Weeks after Doripenem Antibiotic Treatment

An understanding of the changes in gut microbiome composition and its associated metabolic functions is important to assess the potential implications thereof on host health. Thus, to elucidate the connection between the gut microbiome and the fecal and plasma metabolomes, two poorly bioavailable carbapenem antibiotics (doripenem and meropenem), were administered in a 28-day oral study to male and female Wistar rats. Additionally, the recovery of the gut microbiome and metabolomes in doripenem-exposed rats were studied one and two weeks after antibiotic treatment (i.e., doripenem-recovery groups). The 16S bacterial community analysis revealed an altered microbial population in all antibiotic treatments and a recovery of bacterial diversity in the doripenem-recovery groups. A similar pattern was observed in the fecal metabolomes of treated animals. In the recovery group, particularly after one week, an over-compensation was observed in fecal metabolites, as they were significantly changed in the opposite direction compared to previously changed metabolites upon 28 days of antibiotic exposure. Key plasma metabolites known to be diagnostic of antibiotic-induced microbial shifts, including indole derivatives, hippuric acid, and bile acids were also affected by the two carbapenems. Moreover, a unique increase in the levels of indole-3-acetic acid in plasma following meropenem treatment was observed. As was observed for the fecal metabolome, an overcompensation of plasma metabolites was observed in the recovery group. The data from this study provides insights into the connectivity of the microbiome and fecal and plasma metabolomes and demonstrates restoration post-antibiotic treatment not only for the microbiome but also for the metabolomes. The importance of overcompensation reactions for health needs further studies.

Dose- and time-dependent manners of moxifloxacin induced liver injury by targeted metabolomics study

Moxifloxacin is the most widely prescribed antibiotics due to its excellent oral bioavailability and broad-spectrum antibacterial effect. Despite of its popularity, the rare and severe liver injury induced by moxifloxacin is a big concern that cannot be ignored in clinical practice. However, the early warning and related metabolic disturbances of moxifloxacin induced hepatoxicity were rarely reported. In this study, the dose- and time-dependent manners of moxifloxacin induced liver injury were investigated by a targeted metabolomics method. In dose-dependent experiment, three different dosages of moxifloxacin were administered to the rats, including 36 mg kg⁻¹ d⁻¹, 72 mg kg⁻¹ d⁻¹, and 108 mg kg⁻¹ d⁻¹. In time-dependent experiment, moxifloxacin was orally administered to the rats for 3, 7 or 14 consecutive days. Pathological analysis showed that moxifloxacin caused obvious transient hepatotoxicity, with the most serious liver injury occurred in the 7 days continuous administration group. The transient liver injury can be automatically restored over time. Serum levels of liver function related biochemical indicators, including ALT, AST, TBIL, alkaline phosphatase, superoxide dismutase, and malondialdehyde, were also measured for the evaluation of liver injury. However, these indicators can hardly be used for the early warning of hepatotoxicity caused by moxifloxacin due to their limited sensitivity and significant hysteresis. Targeted metabolomics study demonstrated that serum concentrations of fatty acyl carnitines, fatty acids and dehydroepiandrosterone can change dynamically with the severity of moxifloxacin related liver injury. The elevated serum levels of fatty acyl carnitine, fatty acid and dehydroepiandrosterone were promising in predicting the hepatotoxicity induced by moxifloxacin.

Gut microbiome and plasma metabolome changes in rats after oral gavage of nanoparticles: sensitive indicators of possible adverse health effects

BACKGROUND

The oral uptake of nanoparticles is an important route of human exposure and requires solid models for hazard assessment. While the systemic availability is generally low, ingestion may not only affect gastrointestinal tissues but also intestinal microbes. The gut microbiota contributes essentially to human health, whereas gut microbial dysbiosis is known to promote several intestinal and extra-intestinal diseases. Gut microbiota-derived metabolites, which are found in the blood stream, serve as key molecular mediators of host metabolism and immunity.

RESULTS

Gut microbiota and the plasma metabolome were analyzed in male Wistar rats receiving either SiO₂ (1000 mg/kg body weight/day) or Ag nanoparticles (100 mg/kg body weight/day) during a 28-day oral gavage study. Comprehensive clinical, histopathological and hematological examinations showed no signs of nanoparticle-induced toxicity. In contrast, the gut microbiota was affected by both nanoparticles, with significant alterations at all analyzed taxonomical levels. Treatments with each of the nanoparticles led to an increased abundance of Prevotellaceae, a family with gut species known to be correlated with intestinal inflammation. Only in Ag nanoparticle-exposed animals, Akkermansia, a genus known for its protective impact on the intestinal barrier was depleted to hardly detectable levels. In SiO₂ nanoparticles-treated animals, several genera were significantly reduced, including probiotics such as Enterococcus. From the analysis of 231 plasma metabolites, we found 18 metabolites to be significantly altered in Ag-or SiO₂ nanoparticles-treated rats. For most of these metabolites, an association with gut microbiota has been reported previously. Strikingly, both nanoparticle-treatments led to a significant reduction of gut microbiota-derived indole-3-acetic acid in plasma. This ligand of the arylhydrocarbon receptor is critical for regulating immunity, stem cell maintenance, cellular differentiation and xenobiotic-metabolizing enzymes.

CONCLUSIONS

The combined profiling of intestinal microbiome and plasma metabolome may serve as an early and sensitive indicator of gut microbiome changes induced by orally administered nanoparticles; this will help to recognize potential adverse effects of these changes to the host.

Preclinical models of idiosyncratic drug-induced liver injury (iDILI): Moving towards prediction

Idiosyncratic drug-induced liver injury (iDILI) encompasses the unexpected harms that prescription and non-prescription drugs, herbal and dietary supplements can cause to the liver. iDILI remains a major public health problem and a major cause of drug attrition. Given the lack of biomarkers for iDILI prediction, diagnosis and prognosis, searching new models to predict and study mechanisms of iDILI is necessary. One of the major limitations of iDILI preclinical assessment has been the lack of correlation between the markers of hepatotoxicity in animal toxicological studies and clinically significant iDILI. Thus, major advances in the understanding of iDILI susceptibility and pathogenesis have come from the study of well-phenotyped iDILI patients. However, there are many gaps for explaining all the complexity of iDILI susceptibility and mechanisms. Therefore, there is a need to optimize preclinical human in vitro models to reduce the risk of iDILI during drug development. Here, the current experimental models and the future directions in iDILI modelling are thoroughly discussed, focusing on the human cellular models available to study the pathophysiological mechanisms of the disease and the most used in vivo animal iDILI models. We also comment about in silico approaches and the increasing relevance of patient-derived cellular models.

Safety assessment of cosmetics by read across applied to metabolomics data of in vitro skin and liver models

As a result of the cosmetics testing ban, safety evaluations of cosmetics ingredients must now be conducted using animal-free methods. A common approach is read across, which is mainly based on structural similarities but can also be conducted using biological endpoints. Here, metabolomics was used to assess biological effects to enable a read across between a candidate cosmetic ingredient, DIV665, only studied using in vitro assays, and a structurally similar reference compound, PA102, previously investigated using traditional in vivo toxicity methods. The (1) cutaneous distribution after topical application, (2) skin metabolism, (3) liver metabolism and (4) effect on the intracellular metabolomic profiles of in vitro skin and hepatic models, SkinEthic^®RHE model and HepaRG^® cells were investigated. The compounds exhibited similar skin penetration and skin and liver metabolism, with small differences attributed to their physicochemical properties. The effects of both compounds on the metabolome of RHE and HepaRG^® cells were similarly small, both in terms of the metabolites modulated and the magnitude of changes. The patterns of metabolome changes did not fit with any known signature relating to a mode of action known to be linked to liver toxicity e.g. modification of the Krebs cycle, urea synthesis and lipid metabolism, were more reflective of transient adaptive responses. Overall, these studies indicate that PA102 is biologically similar to DIV665, allowing read across of safety endpoints, such as in vivo sub-chronic (but not reproduction toxicity) studies, for the former to be applied to DIV665. Based on this, in the absence of animal data (which is prohibited for new chemicals), it could be concluded that DIV665 applied according to the consumer topical use scenario, is similar to PA102, and is predicted to exhibit low local skin and systemic toxicity.

Analytical and Omics-Based Advances in the Study of Drug-Induced Liver Injury

Drug-induced liver injury (DILI) is a significant clinical issue, affecting 1-1.5 million patients annually, and remains a major challenge during drug development-toxicity and safety concerns are the second-highest reason for drug candidate failure. The future prevalence of DILI can be minimized by developing a greater understanding of the biological mechanisms behind DILI. Both qualitative and quantitative analytical techniques are vital to characterizing and investigating DILI. In vitro assays are capable of characterizing specific aspects of a drug's hepatotoxic nature and multiplexed assays are capable of characterizing and scoring a drug's association with DILI. However, an even deeper insight into the perturbations to biological pathways involved in the mechanisms of DILI can be gained through the use of omics-based analytical techniques: genomics, transcriptomics, proteomics, and metabolomics. These omics analytical techniques can offer qualitative and quantitative insight into genetic susceptibilities to DILI, the impact of drug treatment on gene expression, and the effect on protein and metabolite abundance. This review will discuss the analytical techniques that can be applied to characterize and investigate the biological mechanisms of DILI and potential predictive biomarkers.

Influence of pregnancy and non-fasting conditions on the plasma metabolome in a rat prenatal toxicity study

The current parameters for determining maternal toxicity (e.g. clinical signs, food consumption, body weight development) lack specificity and may underestimate the extent of effects of test compounds on the dams. Previous reports have highlighted the use of plasma metabolomics for an improved and mechanism-based identification of maternal toxicity. To establish metabolite profiles of healthy pregnancies and evaluate the influence of food consumption as a confounding factor, metabolite profiling of rat plasma was performed by gas- and liquid-chromatography-tandem mass spectrometry techniques. Metabolite changes in response to pregnancy, food consumption prior to blood sampling (non-fasting) as well as the interaction of both conditions were studied. In dams, both conditions, non-fasting and pregnancy, had a marked influence on the plasma metabolome and resulted in distinct individual patterns of changed metabolites. Non-fasting was characterized by increased plasma concentrations of amino acids and diet related compounds and lower levels of ketone bodies. The metabolic profile of pregnant rats was characterized by lower amino acids and glucose levels and higher concentrations of plasma fatty acids, triglycerides and hormones, capturing the normal biochemical changes undergone during pregnancy. The establishment of metabolic profiles of pregnant non-fasted rats serves as a baseline to create metabolic fingerprints for prenatal and maternal toxicity studies.

Metabolomic analysis to discriminate drug-induced liver injury (DILI) phenotypes

Drug-induced liver injury (DILI) is an adverse toxic hepatic clinical reaction associated to the administration of a drug that can occur both at early clinical stages of drug development, as well after normal clinical usage of approved drugs. Because of its unpredictability and clinical relevance, it is of medical concern. Three DILI phenotypes (hepatocellular, cholestatic, and mixed) are currently recognized, based on serum alanine aminotransferase (ALT) and alkaline phosphatase (ALP) values. However, this classification lacks accuracy to distinguish among the many intermediate mixed types, or even to estimate the magnitude and progression of the injury. It was found desirable to have additional elements for better evaluation criteria of DILI. With this aim, we have examined the serum metabolomic changes occurring in 79 DILI patients recruited and monitored using established clinical criteria, along the course of the disease and until recovery. Results revealed that free and conjugated bile acids, and glycerophospholipids were among the most relevant metabolite classes for DILI phenotype characterization. Using an ensemble of PLS-DA models, metabolomic information was integrated into a ternary diagram to display the disease phenotype, the severity of the liver damage, and its progression. The modeling implemented and the use of such compiled information in an easily understandable and visual manner facilitates a straightforward DILI phenotyping and allow to monitor its progression and recovery prediction, usefully complementing the concise information drawn out by the ALT and ALP classification.

Succinate dehydrogenase inhibitors: in silico flux analysis and in vivo metabolomics investigations show no severe metabolic consequences for rats and humans

Succinate dehydrogenase complex II inhibitors (SDHIs) are widely used fungicides since the 1960s. Recently, based on published in vitro cell viability data, potential health effects via disruption of the mitochondrial respiratory chain and tricarboxylic acid cycle have been postulated in mammalian species. As primary metabolic impact of SDH inhibition, an increase in succinate, and compensatory ATP production via glycolysis resulting in excess lactate levels was hypothesized. To investigate these hypotheses, genome-scale metabolic models of Rattus norvegicus and Homo sapiens were used for an in silico analysis of mammalian metabolism. Moreover, plasma samples from 28-day studies with the SDHIs boscalid and fluxapyroxad were subjected to metabolome analyses, to assess in vivo metabolite changes induced by SDHIs. The outcome of in silico analyses indicated that mammalian metabolic networks are robust and able to compensate different types of metabolic perturbation, e.g., partial or complete SDH inhibition. Additionally, the in silico comparison of rat and human responses suggested no noticeable differences between both species, evidencing that the rat is an appropriate testing organism for toxicity of SDHIs. Since no succinate or lactate accumulation were found in rats, such an accumulation is also not expected in humans as a result of SDHI exposure.

A network pharmacology-integrated metabolomics strategy for clarifying the action mechanisms of Schisandrae Chinensis Fructus for treating drug-induced liver injury by acetaminophen

Schisandrae Chinensis Fructus (SCF) was a Traditional Chinese Medicine (TCM) for protecting liver. However, underlying therapeutic mechanisms of SCF for drug-induced liver injury (DILI) by acetaminophen (APAP) are still unclear. This study aims to discover the potential regulation mechanisms of SCF in the treatment of DILI by APAP using the integrated network pharmacology, plasma metabolomics profiling with UPLC-Q-TOF-MS approach. The key targets in the shared pathways of network pharmacology and metabolomics were screened and experimentally validated by Quantitative Real-time PCR analysis. The results showed that SCF could exert excellent effects on DILI by APAP probably through regulating ErbB signaling pathway and Arachidonic acid metabolism pathway, which was reflected by the reduced gene expression of TNF-α, IL-6, IL-1β, COX-2 and EGFR, as well as the increased gene expression of Nrf2, HO-1, MDM2, MAPK8, SRC, PLD1, CYP2E1, CYP1A2, CYP3A1. This study systematically explored the pharmacological mechanisms of SCF in the treatment of DILI, meanwhile, metabolomics combine with network pharmacology approach might be a useful strategy for early diagnosis of DILI by APAP.

A Metabonomics Approach to Drug Toxicology in Liver Disease and its Application in Traditional Chinese Medicine

BACKGROUND

The progression of liver disease causes metabolic transformation in vivo and thus affects corresponding endogenous small molecular compounds. Metabonomics is a powerful technology which is able to assess global low-molecular-weight endogenous metabolites in a biological system. This review is intended to provide an overview of a metabonomics approach to the drug toxicology of diseases of the liver.

METHODS

The regulation of, and relationship between, endogenous metabolites and diseases of the liver is discussed in detail. Furthermore, the metabolic pathways involved in drug interventions of liver diseases are reviewed. Evaluation of the protective mechanisms of traditional Chinese medicine in liver diseases using metabonomics is also reviewed. Examples of applications of metabolite profiling concerning biomarker discovery are highlighted. In addition, new developments and future prospects are described.

RESULTS

Metabonomics can measure changes in metabolism relating to different stages of liver disease, so metabolic differences can provide a basis for the diagnosis, treatment and prognosis of various diseases.

CONCLUSION

Metabonomics has great advantages in all aspects of the therapy of liver diseases, with good prospects for clinical application.

Use cases, best practice and reporting standards for metabolomics in regulatory toxicology

Metabolomics is a widely used technology in academic research, yet its application to regulatory science has been limited. The most commonly cited barrier to its translation is lack of performance and reporting standards. The MEtabolomics standaRds Initiative in Toxicology (MERIT) project brings together international experts from multiple sectors to address this need. Here, we identify the most relevant applications for metabolomics in regulatory toxicology and develop best practice guidelines, performance and reporting standards for acquiring and analysing untargeted metabolomics and targeted metabolite data. We recommend that these guidelines are evaluated and implemented for several regulatory use cases.

Understanding the effect of repeated administration of meloxicam on feline renal cortex and medulla: A lipidomics and metabolomics approach

Repeated administration of meloxicam can cause kidney damage in cats by mechanisms that remain unclear. Metabolomics and lipidomics are powerful, noninvasive approaches used to investigate tissue response to drug exposure. Thus, the objective of this study was to assess the effects of meloxicam on the feline kidney using untargeted metabolomics and lipidomics approaches. Female young-adult purpose-breed cats were allocated into the control (n = 4) and meloxicam (n = 4) groups. Cats in the control and meloxicam groups were treated daily with saline and meloxicam at 0.3 mg/kg subcutaneously for 17 days, respectively. Renal cortices and medullas were collected at the end of the treatment period. Random forest and metabolic pathway analyses were used to identify metabolites that discriminate meloxicam-treated from saline-treated cats and to identify disturbed metabolic pathways in renal tissue. Our results revealed that the repeated administration of meloxicam to cats altered the kidney metabolome and lipidome and suggest that at least 40 metabolic pathways were altered in the renal cortex and medulla. These metabolic pathways included lipid, amino acid, carbohydrate, nucleotide and energy metabolisms, and metabolism of cofactors and vitamins. This is the first study using a pharmacometabonomics approach for studying the molecular effects of meloxicam on feline kidneys.

Network Modeling of Liver Metabolism to Predict Plasma Metabolite Changes During Short-Term Fasting in the Laboratory Rat

The liver—a central metabolic organ that integrates whole-body metabolism to maintain glucose and fatty-acid regulation, and detoxify ammonia—is susceptible to injuries induced by drugs and toxic substances. Although plasma metabolite profiles are increasingly investigated for their potential to detect liver injury earlier than current clinical markers, their utility may be compromised because such profiles are affected by the nutritional state and the physiological state of the animal, and by contributions from extrahepatic sources. To tease apart the contributions of liver and non-liver sources to alterations in plasma metabolite profiles, here we sought to computationally isolate the plasma metabolite changes originating in the liver during short-term fasting. We used a constraint-based metabolic modeling approach to integrate central carbon fluxes measured in our study, and physiological flux boundary conditions gathered from the literature, into a genome-scale model of rat liver metabolism. We then measured plasma metabolite profiles in rats fasted for 5–7 or 10–13 h to test our model predictions. Our computational model accounted for two-thirds of the observed directions of change (an increase or decrease) in plasma metabolites, indicating their origin in the liver. Specifically, our work suggests that changes in plasma lipid metabolites, which are reliably predicted by our liver metabolism model, are key features of short-term fasting. Our approach provides a mechanistic model for identifying plasma metabolite changes originating in the liver.

Profiling and comparison of toxicant metabolites in hair and urine using a mass spectrometry-based metabolomic data processing method

Urine and hair are used for assessing human exposure to toxicants. Urine tests can show acute toxicant exposure. Hair analysis can be used to determine chronic toxicant exposure after months to years; however, compared to urine, hair analysis in exposure assessments is much less frequently investigated. Urine and hair are different matrices, and their mechanisms of toxicant metabolite incorporation are different. The toxicant metabolites present in urine and hair may also be different. To clarify this issue, a procedure was developed to identify toxicant metabolites in rat samples using a mass spectrometry-based metabolomic data processing method. Di-(2-propylheptyl) phthalate (DPHP), an industrial plasticizer, was used as the model toxicant. The developed procedure identified not only known DPHP metabolites (mono-(propyl-6-oxo-heptyl) phthalate, mono-(propyl-6-hydroxyheptyl) phthalate, and mono-(propyl-6-carboxyhexyl) phthalate) but also novel metabolites that were structurally related to DPHP in the rat samples, indicating that the developed procedure successfully identified toxicant metabolites in in vivo samples. Among the 62 tentative metabolites identified from the 7^th-day urine and the 28^th-day hair samples, 33 were detected in only the urine samples, 19 were detected in only the hair samples, and 10 were identified in both the urine and hair samples. A total of 15 out of the 62 metabolites were confirmed as DPHP structure-related metabolites based on MS/MS analysis. Among the 15 DPHP structure-related metabolites, only 2 metabolites were present in both the urine and hair samples. These results suggested that the metabolites identified in urine could not be applied to exposure assessments based on hair analysis.

Impact of lincosamides antibiotics on the composition of the rat gut microbiota and the metabolite profile of plasma and feces

The importance of the gut microorganisms and their wide range of interactions with the host are well-acknowledged. In this study, lincomycin and clindamycin were used to modulate microbial communities of Wistar rats to gain a comprehensive understanding of the implications of microbiome alterations. A metabolomics approach and taxonomic profiling were applied to characterize the effects of these antibiotics on the functionality of the microbiome and to identify microbiome-related metabolites. After treatment, the diversity of the microbial community was drastically reduced. Bacteroidetes and Verrucomicrobia were drastically reduced, Tenericutes and Deferribacteres completely disappeared, while abundance of Firmicutes and Proteobacteria were highly increased. Changes in plasma and feces metabolites were observed for metabolites belonging mainly to the class of complex lipids, fatty acids and related metabolites as well as amino acids and related compounds. Bile acid metabolism was markedly affected: taurocholic acid, glycochenodeoxycholic acid and cholic acid presented abrupt changes showing a specific metabolite pattern indicating disruption of the microbial community. In both plasma and feces taurocholic acid was highly upregulated upon treatment whereas glycochenodeoxycholic acid was downregulated. Cholic acid was upregulated in feces but downregulated in plasma. These results show that changes in the gut microbial community lead to alterations of the metabolic profile in blood and feces of the host and can be used to identify potentially microbiome-related metabolites. This implies that metabolomics could be a suitable tool to estimate the extent of changes induced in the intestinal microbiome with respect to consequences for the host.

Development of Decision Forest Models for Prediction of Drug-Induced Liver Injury in Humans Using A Large Set of FDA-approved Drugs

Drug-induced liver injury (DILI) presents a significant challenge to drug development and regulatory science. The FDA’s Liver Toxicity Knowledge Base (LTKB) evaluated >1000 drugs for their likelihood of causing DILI in humans, of which >700 drugs were classified into three categories (most-DILI, less-DILI, and no-DILI). Based on this dataset, we developed and compared 2-class and 3-class DILI prediction models using the machine learning algorithm of Decision Forest (DF) with Mold2 structural descriptors. The models were evaluated through 1000 iterations of 5-fold cross-validations, 1000 bootstrapping validations and 1000 permutation tests (that assessed the chance correlation). Furthermore, prediction confidence analysis was conducted, which provides an additional parameter for proper interpretation of prediction results. We revealed that the 3-class model not only had a higher resolution to estimate DILI risk but also showed an improved capability to differentiate most-DILI drugs from no-DILI drugs in comparison with the 2-class DILI model. We demonstrated the utility of the models for drug ingredients with warnings very recently issued by the FDA. Moreover, we identified informative molecular features important for assessing DILI risk. Our results suggested that the 3-class model presents a better option than the binary model (which most publications are focused on) for drug safety evaluation.

Prediction of liver toxicity and mode of action using metabolomics in vitro in HepG2 cells

Liver toxicity is a leading systemic toxicity of drugs and chemicals demanding more human-relevant, high throughput, cost effective in vitro solutions. In addition to contributing to animal welfare, in vitro techniques facilitate exploring and understanding the molecular mechanisms underlying toxicity. New ‘omics technologies can provide comprehensive information on the toxicological mode of action of compounds, as well as quantitative information about the multi-parametric metabolic response of cellular systems in normal and patho-physiological conditions. Here, we combined mass-spectroscopy metabolomics with an in vitro liver toxicity model. Metabolite profiles of HepG2 cells treated with 35 test substances resulted in 1114 cell supernatants and 3556 intracellular samples analyzed by metabolomics. Control samples showed relative standard deviations of about 10–15%, while the technical replicates were at 5–10%. Importantly, this procedure revealed concentration–response effects and patterns of metabolome changes that are consistent for different liver toxicity mechanisms (liver enzyme induction/inhibition, liver toxicity and peroxisome proliferation). Our findings provide evidence that identifying organ toxicity can be achieved in a robust, reliable, human-relevant system, representing a non-animal alternative for systemic toxicology.

Drug-Induced Liver Injury in Children: Clinical Observations, Animal Models, and Regulatory Status

Drug-induced liver injury in children (cDILI) accounts for about 1% of all reported adverse drug reactions throughout all age groups, less than 10% of all clinical DILI cases, and around 20% of all acute liver failure cases in children. The overall DILI susceptibility in children has been assumed to be lower than in adults. Nevertheless, controversial evidence is emerging about children's sensitivity to DILI, with children's relative susceptibility to DILI appearing to be highly drug-specific. The culprit drugs in cDILI are similar but not identical to DILI in adults (aDILI). This is demonstrated by recent findings that a drug frequently associated with aDILI (amoxicillin/clavulanate) was rarely associated with cDILI and that the drug basiliximab caused only cDILI but not aDILI. The fatality in reported cDILI studies ranged from 4% to 31%. According to the US Food and Drug Administration-approved drugs labels, valproic acid, dactinomycin, and ampicillin appear more likely to cause cDILI. In contrast, deferasirox, isoniazid, dantrolene, and levofloxacin appear more likely to cause aDILI. Animal models have been explored to mimic children's increased susceptibility to valproic acid hepatotoxicity or decreased susceptibility to acetaminophen or halothane hepatotoxicity. However, for most drugs, animal models are not readily available, and the underlying mechanisms for the differential reactions to DILI between children and adults remain highly hypothetical. Diagnosis tools for cDILI are not yet available. A critical need exists to fill the knowledge gaps in cDILI. This review article provides an overview of cDILI and specific drugs associated with cDILI.

Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions

The laboratory rat has been used as a surrogate to study human biology for more than a century. Here we present the first genome-scale network reconstruction of Rattus norvegicus metabolism, iRno, and a significantly improved reconstruction of human metabolism, iHsa. These curated models comprehensively capture metabolic features known to distinguish rats from humans including vitamin C and bile acid synthesis pathways. After reconciling network differences between iRno and iHsa, we integrate toxicogenomics data from rat and human hepatocytes, to generate biomarker predictions in response to 76 drugs. We validate comparative predictions for xanthine derivatives with new experimental data and literature-based evidence delineating metabolite biomarkers unique to humans. Our results provide mechanistic insights into species-specific metabolism and facilitate the selection of biomarkers consistent with rat and human biology. These models can serve as powerful computational platforms for contextualizing experimental data and making functional predictions for clinical and basic science applications.

The rat is a widely-used model for human biology, but we must be aware of metabolic differences. Here, the authors reconstruct the genome-scale metabolic network of the rat, and after reconciling it with an improved human metabolic model, demonstrate the power of the models to integrate toxicogenomics data, providing species-specific biomarker predictions in response to a panel of drugs.

Concurrent profiling of polar metabolites and lipids in human plasma using HILIC-FTMS

Blood plasma is the most popularly used sample matrix for metabolite profiling studies, which aim to achieve global metabolite profiling and biomarker discovery. However, most of the current studies on plasma metabolite profiling focused on either the polar metabolites or lipids. In this study, a comprehensive analysis approach based on HILIC-FTMS was developed to concurrently examine polar metabolites and lipids. The HILIC-FTMS method was developed using mixed standards of polar metabolites and lipids, the separation efficiency of which is better in HILIC mode than in C5 and C18 reversed phase (RP) chromatography. This method exhibits good reproducibility in retention times (CVs < 3.43%) and high mass accuracy (<3.5 ppm). In addition, we found MeOH/ACN/Acetone (1:1:1, v/v/v) as extraction cocktail could achieve desirable gathering of demanded extracts from plasma samples. We further integrated the MeOH/ACN/Acetone extraction with the HILIC-FTMS method for metabolite profiling and smoking-related biomarker discovery in human plasma samples. Heavy smokers could be successfully distinguished from non smokers by univariate and multivariate statistical analysis of the profiling data, and 62 biomarkers for cigarette smoke were found. These results indicate that our concurrent analysis approach could be potentially used for clinical biomarker discovery, metabolite-based diagnosis, etc.

Exploration of Biomarkers for Amoxicillin/Clavulanate-Induced Liver Injury: Multi-Omics Approaches

To explore potential biomarkers for amoxicillin/clavulanate‐induced liver injury (AC‐DILI), we conducted a clinical trial in 32 healthy subjects based on multi‐omics approaches. Every subject was administered amoxicillin/clavulanate for 14 days. The liver‐specific microRNA‐122 (miR‐122) level increased prior to and correlated well with the observed alanine aminotransferase (ALT) level increase. This result indicates its potential as a sensitive early marker for AC‐DILI. We also identified urinary metabolites, such as azelaic acid and 7‐methylxanthine, with levels that significantly differed among the groups classified by ALT elevation level on day 8 after drug administration (P < 0.05). Lymphocyte proliferation in response to the drug was also observed. These findings demonstrate sequential changes in the process of AC‐DILI, including metabolic changes, increased miR‐122 level, increased liver enzyme activity, and enhanced lymphocyte proliferation after drug administration. In conclusion, this study provides potential biomarkers for AC‐DILI based on currently known mechanisms using comprehensive multi‐omics approaches.

Predicting drug-induced liver injury in human with Naïve Bayes classifier approach

Drug-induced liver injury (DILI) is one of the major safety concerns in drug development. Although various toxicological studies assessing DILI risk have been developed, these methods were not sufficient in predicting DILI in humans. Thus, developing new tools and approaches to better predict DILI risk in humans has become an important and urgent task. In this study, we aimed to develop a computational model for assessment of the DILI risk with using a larger scale human dataset and Naïve Bayes classifier. The established Naïve Bayes prediction model was evaluated by 5-fold cross validation and an external test set. For the training set, the overall prediction accuracy of the 5-fold cross validation was 94.0 %. The sensitivity, specificity, positive predictive value and negative predictive value were 97.1, 89.2, 93.5 and 95.1 %, respectively. The test set with the concordance of 72.6 %, sensitivity of 72.5 %, specificity of 72.7 %, positive predictive value of 80.4 %, negative predictive value of 63.2 %. Furthermore, some important molecular descriptors related to DILI risk and some toxic/non-toxic fragments were identified. Thus, we hope the prediction model established here would be employed for the assessment of human DILI risk, and the obtained molecular descriptors and substructures should be taken into consideration in the design of new candidate compounds to help medicinal chemists rationally select the chemicals with the best prospects to be effective and safe.

Key Challenges and Opportunities Associated with the Use of In Vitro Models to Detect Human DILI: Integrated Risk Assessment and Mitigation Plans

Drug-induced liver injury (DILI) is a major cause of late-stage clinical drug attrition, market withdrawal, black-box warnings, and acute liver failure. Consequently, it has been an area of focus for toxicologists and clinicians for several decades. In spite of considerable efforts, limited improvements in DILI prediction have been made and efforts to improve existing preclinical models or develop new test systems remain a high priority. While prediction of intrinsic DILI has improved, identifying compounds with a risk for idiosyncratic DILI (iDILI) remains extremely challenging because of the lack of a clear mechanistic understanding and the multifactorial pathogenesis of idiosyncratic drug reactions. Well-defined clinical diagnostic criteria and risk factors are also missing. This paper summarizes key data interpretation challenges, practical considerations, model limitations, and the need for an integrated risk assessment. As demonstrated through selected initiatives to address other types of toxicities, opportunities exist however for improvement, especially through better concerted efforts at harmonization of current, emerging and novel in vitro systems or through the establishment of strategies for implementation of preclinical DILI models across the pharmaceutical industry. Perspectives on the incorporation of newer technologies and the value of precompetitive consortia to identify useful practices are also discussed.

Screening and validation for plasma biomarkers of nephrotoxicity based on metabolomics in male rats

Currently, drug-induced nephrotoxicity is widespread and seriously affects human health. However, the conventional indexes of renal function lack sensitivity, leading to a delay in the detection of nephrotoxicity. Therefore, we need to identify more sensitive indexes for evaluating nephrotoxicity. In this study, we used gentamicin (100 mg kg-1), etimicin (100 mg kg-1) and amphotericin B (4 mg kg-1) to establish renal injury models in rats, and we collected information using ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry in the screening stage. Thirteen nephrotoxicity metabolites were selected after multivariate statistical and integration analyses. Then, we conducted trend analysis to select 5 nephrotoxicity biomarkers [thymidine, LysoPC(16:1), LysoPC(18:4), LysoPC(20:5), and LysoPC(22:5)] whose content changed consistently at different timepoints after drug administration. To verify the sensitivity and specificity of these biomarkers for nephrotoxicity, receiver operating characteristic (ROC) and support vector machine (SVM) analyses were applied. The area under the curve of the 5 biomarkers were 0.806-0.901 at the 95% confidence interval according to the ROC analysis. We used the SVM classified model to verify these biomarkers, and the prediction rate was 95.83%. Therefore, the 5 biomarkers have strong sensitivity and high accuracy; these biomarkers are more sensitive indexes for evaluating renal function to identify nephrotoxicity and initiate prompt treatment.

The Need for Biomarkers in Diagnosis and Prognosis of Drug-Induced Liver Disease: Does Metabolomics Have Any Role?

Drug-induced liver injury (DILI) is a potentially fatal adverse event and the leading cause of acute liver failure in the US and in the majority of Europe. The liver can be affected directly, in a dose-dependent manner, or idiosyncratically, independently of the dose, and therefore unpredictably. Currently, DILI is a diagnosis of exclusion that physicians should suspect in patients with unexplained elevated liver enzymes. Therefore, new diagnostic and prognostic biomarkers are necessary to achieve an early and reliable diagnosis of DILI and thus improve the prognosis. Although several DILI biomarkers have been found through analytical and genetic tests and pharmacokinetic approaches, none of them have been able to display enough specificity and sensitivity, so new approaches are needed. In this sense, metabolomics is a strongly and promising emerging field that, from biofluids collected through minimally invasive procedures, can obtain early biomarkers of toxicity, which may constitute specific indicators of liver damage.

Liver cell injury caused by bad habits

Apoptosis and necrosis of liver cells induced by environmental or genetic factors are the main features of liver injury. Liver injury is usually caused by apoptosis of liver cells, which is controlled by a complex regulatory system involved in liver damage and secondary inflammation. This article aims to review liver injury caused by bad habits and the underlying molecular mechanisms.

The Art and Science of Diagnosing and Managing Drug-induced Liver Injury in 2015 and Beyond

Drug-induced liver injury (DILI) remains a leading reason why new compounds are dropped from further study or are the subject of product warnings and regulatory actions. Hy's Law of drug-induced hepatocellular jaundice causing a case-fatality rate or need for transplant of 10% or higher has been validated in several large national registries, including the ongoing, prospective U.S. Drug-Induced Liver Injury Network. It serves as the basis for stopping rules in clinical trials and in clinical practice. Because DILI can mimic all known causes of acute and chronic liver disease, establishing causality can be difficult. Histopathologic findings are often nonspecific and rarely, if ever, considered pathognomonic. A daily drug dose >50-100 mg is more likely to be hepatotoxic than does <10 mg, especially if the compound is highly lipophilic or undergoes extensive hepatic metabolism. The quest for a predictive biomarker to replace alanine aminotransferase is ongoing. Markers of necrosis and apoptosis such as microRNA-122 and keratin 18 may prove useful in identifying patients at risk for severe injury when they initially present with a suspected acetaminophen overdose. Although a number of drugs causing idiosyncratic DILI have HLA associations that may allow for pre-prescription testing to prevent hepatotoxicity, the cost and relatively low frequency of injury among affected patients limit the current usefulness of such genome-wide association studies. Alanine aminotransferase monitoring is often recommended but has rarely been shown to be an effective method to prevent serious DILI. Guidelines on the diagnosis and management of DILI have recently been published, although specific therapies remain limited. The LiverTox Web site has been introduced as an interactive online virtual textbook that makes the latest information on more than 650 agents available to clinicians, regulators, and drug developers alike.