Uncovering the toxicity mechanisms of a series of carboxylic acids in liver cells through computational and experimental approaches.

Hepatotoxicity poses a significant concern in drug design due to the potential liver damage that can be caused by new drugs. Among common manifestations of hepatotoxic damage is lipid accumulation in hepatic tissue, resulting in liver steatosis or phospholipidosis. Carboxylic derivatives are prone to interfere with fatty acid metabolism and cause lipid accumulation in hepatocytes. This study investigates the toxic behaviour of 24 structurally related carboxylic acids in hepatocytes, specifically their ability to cause accumulation of fatty acids and phospholipids. Using high-content screening (HCS) assays, we identified two distinct lipid accumulation patterns. Subsequently, we developed structure-activity relationship (SAR) and quantitative structure-activity relationship (QSAR) models to determine relevant molecular substructures and descriptors contributing to these adverse effects. Additionally, we calculated physicochemical properties associated with lipid accumulation in hepatocytes and examined their correlation with our chemical structure characteristics. To assess the applicability of our findings to a wide range of chemical compounds, we employed two external datasets to evaluate the distribution of our QSAR descriptors. Our study highlights the significance of subtle molecular structural variations in triggering hepatotoxicity, such as the presence of nitrogen or the specific arrangement of substitutions within the carbon chain. By employing our comprehensive approach, we pinpointed specific molecules and elucidated their mechanisms of toxicity, thus offering valuable insights to guide future toxicology investigations.

Exploring Individual Variability in Drug-Induced Liver Injury (DILI) Responses through Metabolomic Analysis.

Drug-induced liver injury (DILI) is a serious adverse hepatic event presenting diagnostic and prognostic challenges. The clinical categorization of DILI into hepatocellular, cholestatic, or mixed phenotype is based on serum alanine aminotransferase (ALT) and alkaline phosphatase (ALP) values; however, this classification may not capture the full spectrum of DILI subtypes. With this aim, we explored the utility of assessing changes in the plasma metabolomic profiles of 79 DILI patients assessed by the RUCAM (Roussel Uclaf Causality Assessment Method) score to better characterize this condition and compare results obtained with the standard clinical characterization. Through the identification of various metabolites in the plasma (including free and conjugated bile acids and glycerophospholipids), and the integration of this information into predictive models, we were able to evaluate the extent of the hepatocellular or cholestatic phenotype and to assign a numeric value with the contribution of each specific DILI sub-phenotype into the patient's general condition. Additionally, our results showed that metabolomic analysis enabled the monitoring of DILI variability responses to the same drug, the transitions between sub-phenotypes during disease progression, and identified a spectrum of residual DILI metabolic features, which can be overlooked using standard clinical diagnosis during patient follow-up.

Report of the First ONTOX Stakeholder Network Meeting: Digging Under the Surface of ONTOX Together With the Stakeholders.

The first Stakeholder Network Meeting of the EU Horizon 2020-funded ONTOX project was held on 13-14 March 2023, in Brussels, Belgium. The discussion centred around identifying specific challenges, barriers and drivers in relation to the implementation of non-animal new approach methodologies (NAMs) and probabilistic risk assessment (PRA), in order to help address the issues and rank them according to their associated level of difficulty. ONTOX aims to advance the assessment of chemical risk to humans, without the use of animal testing, by developing non-animal NAMs and PRA in line with 21st century toxicity testing principles. Stakeholder groups (regulatory authorities, companies, academia, non-governmental organisations) were identified and invited to participate in a meeting and a survey, by which their current position in relation to the implementation of NAMs and PRA was ascertained, as well as specific challenges and drivers highlighted. The survey analysis revealed areas of agreement and disagreement among stakeholders on topics such as capacity building, sustainability, regulatory acceptance, validation of adverse outcome pathways, acceptance of artificial intelligence (AI) in risk assessment, and guaranteeing consumer safety. The stakeholder network meeting resulted in the identification of barriers, drivers and specific challenges that need to be addressed. Breakout groups discussed topics such as hazard versus risk assessment, future reliance on AI and machine learning, regulatory requirements for industry and sustainability of the ONTOX Hub platform. The outputs from these discussions provided insights for overcoming barriers and leveraging drivers for implementing NAMs and PRA. It was concluded that there is a continued need for stakeholder engagement, including the organisation of a 'hackathon' to tackle challenges, to ensure the successful implementation of NAMs and PRA in chemical risk assessment.

Automated Generation of hiPSC-Derived Hepatic Progeny by Cost-Efficient Compounds.

Human pluripotent stem cell (hPSC)-derived hepatocyte-like cells (HLCs) hold great promise for liver disease modeling, drug discovery, and drug toxicity screens. Yet, several hurdles still need to be overcome, including among others decrease in the cost of goods to generate HLCs and automation of the differentiation process. We here describe that the use of an automated liquid handling system results in highly reproducible HLC differentiation from hPSCs. This enabled us to screen 92 chemicals to replace expensive growth factors at each step of the differentiation protocol to reduce the cost of goods of the differentiation protocol by approximately 79%. In addition, we also evaluated several recombinant extracellular matrices to replace Matrigel. We demonstrated that differentiation of hPSCs on Laminin-521 using an optimized small molecule combination resulted in HLCs that were transcriptionally identical to HLCs generated using the growth factor combinations. In addition, the HLCs created using the optimized small molecule combination secreted similar amounts of albumin and urea, and relatively low concentrations of alfa-fetoprotein, displayed similar CYP3A4 functionality, and a similar drug toxicity susceptibility as HLCs generated with growth factor cocktails. The broad applicability of the new differentiation protocol was demonstrated for 4 different hPSC lines. This allowed the creation of a scalable, xeno-free, and cost-efficient hPSC-derived HLC culture, suitable for high throughput disease modeling and drug screenings, or even for the creation of HLCs for regenerative therapies.

Comparing the direct assessment of steatosis in liver explants with mid- and near-infrared vibrational spectroscopy, prior to organ transplantation.

A fast and accurate assessment of liver steatosis is crucial during liver transplantation surgery as it can negatively impact its success. Recent research has shown that near-infrared (NIR) and attenuated total reflectance-Fourier transform mid-infrared (ATR-FTIR) spectroscopy could be used as real-time quantitative tools to assess steatosis during abdominal surgery. Here, in the frame of a clinical study, we explore the performance of NIR and ATR-FTIR spectroscopy for the direct assessment of steatosis in liver tissues. Results show that both NIR and ATR-FTIR spectroscopy are able to quantify the % of steatosis with cross-validation errors of 1.4 and 1.6%, respectively. Furthermore, the two portable instruments used both provided results within seconds and can be placed inside an operating room evidencing the potential of IR spectroscopy for initial characterization of grafts in liver transplantation surgery. We also evaluated the complementarity of the spectral ranges through correlation spectroscopy.

Gut Microbiota and Plasma Bile Acids Associated with Non-Alcoholic Fatty Liver Disease Resolution in Bariatric Surgery Patients.

Bariatric surgery (BS) has several benefits, including resolution of non-alcoholic fatty liver disease (NAFLD) in many patients. However, a significant percentage of patients do not experience improvement in fatty liver after BS, and more than 10% develop new or worsening NAFLD features. Therefore, a question that remains unanswered is why some patients experience resolved NAFLD after BS and others do not. In this study, we investigated the fecal microbiota and plasma bile acids associated with NAFLD resolution in twelve morbidly obese patients undergoing BS, of whom six resolved their steatosis one year after surgery and another six did not. Results indicate that the hallmark of the gut microbiota in responder patients is a greater abundance of Bacteroides, Akkermansia, and several species of the Clostridia class (genera: Blautia, Faecalibacterium, Roseburia, Butyricicoccusa, and Clostridium), along with a decreased abundance of Actinomycetes/Bifidobacterium and Faecalicatena. NAFLD resolution was also associated with a sustained increase in primary bile acids (particularly non-conjugated), which likely results from a reduction in bacterial gut species capable of generating secondary bile acids. We conclude that there are specific changes in gut microbiota and plasma bile acids that could contribute to resolving NAFLD in BS patients. The knowledge acquired can help to design interventions with prebiotics and/or probiotics to promote a gut microbiome that favors NAFLD resolution.

Enhancing the accuracy of mid-infrared spectroscopy-based liver steatosis quantification using digital image analysis as a reference.

The assessment of liver steatosis is crucial in both hepatology and liver transplantation (LT) surgery. Steatosis can negatively impact the success of LT. Steatosis is a factor for excluding donated organs for LT, but the increasing demand for transplantable organs has led to the use of organs from marginal donors. The current standard for evaluating steatosis is a semi-quantitative grading based on the visual examination of a hematoxylin and eosin (H&E)-stained liver biopsy, but this method is time-consuming, subjective, and lacks reproducibility. Recent research has shown that infrared (IR) spectroscopy could be used as a real-time quantitative tool to assess steatosis during abdominal surgery. However, the development of IR-based methods has been hindered by the lack of appropriate quantitative reference values. In this study, we developed and validated digital image analysis methods for the quantitation of steatosis in H&E-stained liver sections using univariate and multivariate strategies including linear discriminant analysis (LDA), quadratic DA, logistic regression, partial least squares-DA (PLS-DA), and support vector machines. The analysis of 37 tissue samples with varying grades of steatosis demonstrates that digital image analysis provides accurate and reproducible reference values that improve the performance of IR spectroscopic models for steatosis quantification. A PLS model in the 1810-1052 cm-1 region using first derivative ATR-FTIR spectra provided RMSECV = 0.99%. The gained improvement in accuracy critically enhances the applicability of Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) to support an objective graft evaluation at the operation room, which might be especially relevant in cases of marginal liver donors to avoid unnecessary graft explantation.

The assessment of the potential hepatotoxicity of new drugs by in vitro metabolomics.

Drug hepatotoxicity assessment is a relevant issue both in the course of drug development as well as in the post marketing phase. The use of human relevant in vitro models in combination with powerful analytical methods (metabolomic analysis) is a promising approach to anticipate, as well as to understand and investigate the effects and mechanisms of drug hepatotoxicity in man. The metabolic profile analysis of biological liver models treated with hepatotoxins, as compared to that of those treated with non-hepatotoxic compounds, provides useful information for identifying disturbed cellular metabolic reactions, pathways, and networks. This can later be used to anticipate, as well to assess, the potential hepatotoxicity of new compounds. However, the applicability of the metabolomic analysis to assess the hepatotoxicity of drugs is complex and requires careful and systematic work, precise controls, wise data preprocessing and appropriate biological interpretation to make meaningful interpretations and/or predictions of drug hepatotoxicity. This review provides an updated look at recent in vitro studies which used principally mass spectrometry-based metabolomics to evaluate the hepatotoxicity of drugs. It also analyzes the principal drawbacks that still limit its general applicability in safety assessment screenings. We discuss the analytical workflow, essential factors that need to be considered and suggestions to overcome these drawbacks, as well as recent advancements made in this rapidly growing field of research.

Metabolomics-based strategy to assess drug hepatotoxicity and uncover the mechanisms of hepatotoxicity involved.

Toxicity studies, among them hepatotoxicity, are key throughout preclinical stages of drug development to minimise undesired toxic effects that might eventually appear in the course of the clinical use of the new drug. Understanding the mechanism of injury of hepatotoxins is essential to efficiently anticipate their potential risk of toxicity in humans. The use of in vitro models and particularly cultured hepatocytes represents an easy and robust alternative to animal drug hepatotoxicity testing for predicting human risk. Here, we envisage an innovative strategy to identify potential hepatotoxic drugs, quantify the magnitude of the alterations caused, and uncover the mechanisms of toxicity. This strategy is based on the comparative analysis of metabolome changes induced by hepatotoxic and non-hepatotoxic compounds on HepG2 cells, assessed by untargeted mass spectrometry. As a training set, we used 25 hepatotoxic and 4 non-hepatotoxic compounds and incubated HepG2 cells for 24 h at a low and a high concentration (IC10 and IC50) to identify mechanism-related and cytotoxicity related metabolomic biomarkers and to elaborate prediction models accounting for global hepatotoxicity and mechanisms-related toxicity. Thereafter, a second set of 69 chemicals with known predominant mechanisms of toxicity and 18 non-hepatotoxic compounds were analysed at 1, 10, 100 and 1000 µM concentrations from which and based on the magnitude of the alterations caused as compared with non-toxic compounds, we defined a "toxicity index" for each compound. In addition, we extracted from the metabolome data the characteristic signatures for each mechanism of hepatotoxicity. The integration of all this information allowed us to identify specific metabolic patterns and, based on the occurrence of that specific metabolome changes, the models predicted the likeliness of a compound to behave as hepatotoxic and to act through a given toxicity mechanism (i.e., oxidative stress, mitochondrial disruption, apoptosis and steatosis) for each compound and concentration.

A robust reprogramming strategy for generating hepatocyte-like cells usable in pharmaco-toxicological studies.

BACKGROUND: High-throughput pharmaco-toxicological testing frequently relies on the use of established liver-derived cell lines, such as HepG2 cells. However, these cells often display limited hepatic phenotype and features of neoplastic transformation that may bias the interpretation of the results. Alternate models based on primary cultures or differentiated pluripotent stem cells are costly to handle and difficult to implement in high-throughput screening platforms. Thus, cells without malignant traits, optimal differentiation pattern, producible in large and homogeneous amounts and with patient-specific phenotypes would be desirable. METHODS: We have designed and implemented a novel and robust approach to obtain hepatocytes from individuals by direct reprogramming, which is based on a combination of a single doxycycline-inducible polycistronic vector system expressing HNF4A, HNF1A and FOXA3, introduced in human fibroblasts previously transduced with human telomerase reverse transcriptase (hTERT). These cells can be maintained in fibroblast culture media, under standard cell culture conditions. RESULTS: Clonal hTERT-transduced human fibroblast cell lines can be expanded at least to 110 population doublings without signs of transformation or senescence. They can be easily differentiated at any cell passage number to hepatocyte-like cells with the simple addition of doxycycline to culture media. Acquisition of a hepatocyte phenotype is achieved in just 10 days and requires a simple and non-expensive cell culture media and standard 2D culture conditions. Hepatocytes reprogrammed from low and high passage hTERT-transduced fibroblasts display very similar transcriptomic profiles, biotransformation activities and show analogous pattern behavior in toxicometabolomic studies. Results indicate that this cell model outperforms HepG2 in toxicological screening. The procedure also allows generation of hepatocyte-like cells from patients with given pathological phenotypes. In fact, we succeeded in generating hepatocyte-like cells from a patient with alpha-1 antitrypsin deficiency, which recapitulated accumulation of intracellular alpha-1 antitrypsin polymers and deregulation of unfolded protein response and inflammatory networks. CONCLUSION: Our strategy allows the generation of an unlimited source of clonal, homogeneous, non-transformed induced hepatocyte-like cells, capable of performing typical hepatic functions and suitable for pharmaco-toxicological high-throughput testing. Moreover, as far as hepatocyte-like cells derived from fibroblasts isolated from patients suffering hepatic dysfunctions, retain the disease traits, as demonstrated for alpha-1-antitrypsin deficiency, this strategy can be applied to the study of other cases of anomalous hepatocyte functionality.

In vitro/in silico prediction of drug induced steatosis in relation to oral doses and blood concentrations by the Nile Red assay.

The accumulation of lipid droplets in hepatocytes is a key feature of drug-induced liver injury (DILI) and can be induced by a subset of hepatotoxic compounds. In the present study, we optimized and evaluated an in vitro technique based on the fluorescent dye Nile Red, further named Nile Red assay to quantify lipid droplets induced by the exposure to chemicals. The Nile Red assay and a cytotoxicity test (CTB assay) were then performed on cells exposed concentration-dependently to 60 different compounds. Of these, 31 were known to induce hepatotoxicity in humans, and 13 were reported to also cause steatosis. In order to compare in vivo relevant blood concentrations, pharmacokinetic models were established for all compounds to simulate the maximal blood concentrations (Cmax) at therapeutic doses. The results showed that several hepatotoxic compounds induced an increase in lipid droplets at sub-cytotoxic concentrations. To compare how well (1) the cytotoxicity test alone, (2) the Nile Red assay alone, and (3) the combination of the cytotoxicity test and the Nile Red assay (based on the lower EC10 of both assays) allow the differentiation between hepatotoxic and non-hepatotoxic compounds, a previously established performance metric, the Toxicity Separation Index (TSI) was calculated. In addition, the Toxicity Estimation Index (TEI) was calculated to determine how well blood concentrations that cause an increased DILI risk can be estimated for hepatotoxic compounds. Our findings indicate that the combination of both assays improved the TSI and TEI compared to each assay alone. In conclusion, the study demonstrates that inclusion of the Nile Red assay into in vitro test batteries may improve the prediction of DILI compounds.

Quantitative Prediction of Steatosis in Patients with Non-Alcoholic Fatty Liver by Means of Hepatic MicroRNAs Present in Serum and Correlating with Hepatic Fat.

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent form of chronic liver disease worldwide, but a reliable non-invasive method to quantify liver steatosis in primary healthcare is not available. Circulating microRNAs have been proposed as biomarkers of severe/advanced NAFLD (steatohepatitis and fibrosis). However, the use of circulating miRNAs to quantitatively assess the % of liver fat in suspected NAFLD patients has not been investigated. We performed global miRNA sequencing in two sets of samples: human livers from organ donors (n = 20), and human sera from biopsy-proven NAFLD patients (n = 23), both with a wide range of steatosis quantified in their liver biopsies. Partial least squares (PLS) regression combined with recursive feature elimination (RFE) was used to select miRNAs associated with steatosis. Moreover, regression models with only 2 or 3 miRNAs, with high biological relevance, were built. Comprehensive microRNA sequencing of liver and serum samples resulted in two sets of abundantly expressed miRNAs (418 in liver and 351 in serum). Pearson correlation analyses indicated that 18% of miRNAs in liver and 14.5% in serum were significantly associated with the amount of liver fat. PLS-RFE models demonstrated that 50 was the number of miRNAs providing the lowest error in both liver and serum models predicting steatosis. Comparison of the two miRNA subsets showed 19 coincident miRNAs that were ranked according to biological significance (guide/passenger strand, relative abundance in liver and serum, number of predicted lipid metabolism target genes, correlation significance, etc.). Among them, miR-10a-5p, miR-98-5p, miR-19a-3p, miR-30e-5p, miR-32-5p and miR-145-5p showed the highest biological relevance. PLS regression models with serum levels of 2−3 of these miRNAs predicted the % of liver fat with errors <5%.

Modeling a Novel Variant of Glycogenosis IXa Using a Clonal Inducible Reprogramming System to Generate "Diseased" Hepatocytes for Accurate Diagnosis.

The diagnosis of inherited metabolic disorders is a long and tedious process. The matching of clinical data with a genomic variant in a specific metabolic pathway is an essential step, but the link between a genome and the clinical data is normally difficult, primarily for new missense variants or alterations in intron sequences. Notwithstanding, elucidation of the pathogenicity of a specific variant might be critical for an accurate diagnosis. In this study, we described a novel intronic variant c.2597 + 5G > T in the donor splice sequence of the PHKA2 gene. To investigate PHKA2 mRNA splicing, as well as the functional consequences on glycogen metabolism, we generated hepatocyte-like cells from a proband's fibroblasts by direct reprogramming. We demonstrated an aberrant splicing of PHKA2, resulting in the incorporation of a 27 bp upstream of intron 23 into exon 23, which leads to an immediate premature STOP codon. The truncated protein was unable to phosphorylate the PYGL protein, causing a 4-fold increase in the accumulation of glycogen in hepatocyte-like cells. Collectively, the generation of personalized hepatocyte-like cells enabled an unequivocal molecular diagnosis and qualified the sister's proband, a carrier of the same mutation, as a candidate for a preimplantation genetic diagnosis. Additionally, our direct reprogramming strategy allows for an unlimited source of "diseased" hepatocyte-like cells compatible with high-throughput platforms.

The Potential Role of Metabolomics in Drug-Induced Liver Injury (DILI) Assessment.

Drug-induced liver injury (DILI) is one of the most frequent adverse clinical reactions and a relevant cause of morbidity and mortality. Hepatotoxicity is among the major reasons for drug withdrawal during post-market and late development stages, representing a major concern to the pharmaceutical industry. The current biochemical parameters for the detection of DILI are based on enzymes (alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transpeptidase (GGT), alkaline phosphatase (ALP)) and bilirubin serum levels that are not specific of DILI and therefore there is an increasing interest on novel, specific, DILI biomarkers discovery. Metabolomics has emerged as a tool with a great potential for biomarker discovery, especially in disease diagnosis, and assessment of drug toxicity or efficacy. This review summarizes the multistep approaches in DILI biomarker research and discovery based on metabolomics and the principal outcomes from the research performed in this field. For that purpose, we have reviewed the recent scientific literature from PubMed, Web of Science, EMBASE, and PubTator using the terms "metabolomics", "DILI", and "humans". Despite the undoubted contribution of metabolomics to our understanding of the underlying mechanisms of DILI and the identification of promising novel metabolite biomarkers, there are still some inconsistencies and limitations that hinder the translation of these research findings into general clinical practice, probably due to the variability of the methods used as well to the different mechanisms elicited by the DILI causing agent.

Derivation of healthy hepatocyte-like cells from a female patient with ornithine transcarbamylase deficiency through X-inactivation selection.

Autologous cell replacement therapy for inherited metabolic disorders requires the correction of the underlying genetic mutation in patient's cells. An unexplored alternative for females affected from X-linked diseases is the clonal selection of cells randomly silencing the X-chromosome containing the mutant allele, without in vivo or ex vivo genome editing. In this report, we have isolated dermal fibroblasts from a female patient affected of ornithine transcarbamylase deficiency and obtained clones based on inactivation status of either maternally or paternally inherited X chromosome, followed by differentiation to hepatocytes. Hepatocyte-like cells derived from these clones display indistinct features characteristic of hepatocytes, but express either the mutant or wild type OTC allele depending on X-inactivation pattern. When clonally derived hepatocyte-like cells were transplanted into FRG® KO mice, they were able to colonize the liver and recapitulate OTC-dependent phenotype conditioned by X-chromosome inactivation pattern. This approach opens new strategies for cell therapy of X-linked metabolic diseases and experimental in vitro models for drug development for such diseases.

A Novel UPLC-MS Metabolomic Analysis-Based Strategy to Monitor the Course and Extent of iPSC Differentiation to Hepatocytes.

Typical protocols to differentiate induced pluripotent stem cells (iPSCs) from hepatocyte-like cells (HLCs) imply complex strategies that include transfection with key hepatic transcription factors and the addition to culture media of nutrients, growth factors, and cytokines. A main constraint to evaluate the hepatic phenotype achieved arises from the way the grade of differentiation is determined. Currently, it relies on the assessment of the expression of a limited number of hepatic gene transcripts, less frequently by assessing certain hepatic metabolic functions, and rarely by the global metabolic performance of differentiated cells. We envisaged a new strategy to assess the extent of differentiation achieved, based on the analysis of the cellular metabolome along the differentiation process and its quantitative comparison with that of primary human hepatocytes (PHHs). To validate our approach, we examined the changes in the metabolome of three iPSC progenies (transfected with/without key transcription factors), cultured in three differentiation media, and compared them to PHHs. Results revealed consistent metabolome changes along differentiation and evidenced the factors that more strongly promote changes in the metabolome. The integrated dissimilarities between the PHHs and HLCs retrieved metabolomes were used as a numerical reference for quantifying the degree of iPSCs differentiation. This newly developed metabolome-analysis approach evidenced its utility in assisting us to select a cell's source, culture conditions, and differentiation media, to achieve better-differentiated HLCs.

Molecular mechanisms of hepatotoxic cholestasis by clavulanic acid: Role of NRF2 and FXR pathways.

Treatment of ß-lactamase positive bacterial infections with a combination of amoxicillin (AMOX) and clavulanic acid (CLAV) causes idiosyncratic drug-induced liver injury (iDILI) in a relevant number of patients, often with features of intrahepatic cholestasis. This study aims to determine serum bile acid (BA) levels in amoxicillin/clavulanate (A+C)-iDILI patients and to investigate the mechanism of cholestasis by A+C in human in vitro hepatic models. In six A+C-iDILI patients, significant elevations of serum primary conjugated BA definitely demonstrated A+C-induced cholestasis. In cultured human Upcyte hepatocytes and HepG2 cells, CLAV was more cytotoxic than AMOX, and, at subcytotoxic concentrations, it altered the expression of more than 1,300 genes. CLAV, but not AMOX, downregulated the expression of key genes for BA transport (BSEP, NTCP, OSTα and MDR2) and synthesis (CYP7A1 and CYP8B1). CLAV also caused early oxidative stress, with reduced GSH/GSSG ratio, along with induction of antioxidant nuclear factor erythroid 2-related factor 2 (NRF2) target genes. Activation of NRF2 by sulforaphane also resulted in downregulation of NTCP, OSTα, ABCG5, CYP7A1 and CYP8B1. CLAV also inhibited the BA-sensor farnesoid X receptor (FXR), in agreement with the downregulation of FXR targets BSEP, OSTα and ABCG5. We conclude that CLAV, the culprit molecule in A+C, downregulates several key biliary transporters by modulating NRF2 and FXR signaling, thus likely promoting intrahepatic cholestasis. On top of that, increased ROS production and GSH depletion may aggravate the cholestatic injury by A+C.

A Model-Based Workflow to Benchmark the Clinical Cholestasis Risk of Drugs.

We present a generic workflow combining physiology-based computational modeling and in vitro data to assess the clinical cholestatic risk of different drugs systematically. Changes in expression levels of genes involved in the enterohepatic circulation of bile acids were obtained from an in vitro assay mimicking 14 days of repeated drug administration for 10 marketed drugs. These changes in gene expression over time were contextualized in a physiology-based bile acid model of glycochenodeoxycholic acid. The simulated drug-induced response in bile acid concentrations was then scaled with the applied drug doses to calculate the cholestatic potential for each compound. A ranking of the cholestatic potential correlated very well with the clinical cholestasis risk obtained from medical literature. The proposed workflow allows benchmarking the cholestatic risk of novel drug candidates. We expect the application of our workflow to significantly contribute to the stratification of the cholestatic potential of new drugs and to support animal-free testing in future drug development.

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.

The in vitro assessment of the toxicity of volatile, oxidisable, redox-cycling compounds: phenols as an example.

Phenols are regarded as highly toxic chemicals. Their effects are difficult to study in in vitro systems because of their ambiguous fate (degradation, auto-oxidation and volatility). In the course of in vitro studies of a series of redox-cycling phenols, we found evidences of cross-contamination in several in vitro high-throughput test systems, in particular by trimethylbenzene-1, 4-diol/trimethylhydroquinone (TMHQ) and 2,6-di-tertbutyl-4-ethylphenol (DTBEP), and investigated in detail the physicochemical basis for such phenomenon and how to prevent it. TMHQ has fast degradation kinetics followed by significant diffusion rates of the resulting quinone to adjacent wells, other degradation products being able to air-diffuse as well. DTBEP showed lower degradation kinetics, but a higher diffusion rate. In both cases the in vitro toxicity was underestimated because of a decrease in concentration, in addition to cross-contamination to neighbouring wells. We identified four degradation products for TMHQ and five for DTBEP indicating that the current effects measured on cells are not only attributable to the parent phenolic compound. To overcome these drawbacks, we investigated in detail the physicochemical changes occurring in the course of the incubation and made use of gas-permeable and non-permeable plastic seals to prevent it. Diffusion was greatly prevented by the use of both plastic seals, as revealed by GC-MS analysis. Gas non-permeable plastic seals, reduced to a minimum compounds diffusion as well oxidation and did not affect the biological performance of cultured cells. Hence, no toxicological cross-contamination was observed in neighbouring wells, thus allowing a more reliable in vitro assessment of phenol-induced toxicity.