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.

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.

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.

Comparing Targeted vs. Untargeted MS2 Data-Dependent Acquisition for Peak Annotation in LC-MS Metabolomics.

One of the most widely used strategies for metabolite annotation in untargeted LCMS is based on the analysis of MSn spectra acquired using data-dependent acquisition (DDA), where precursor ions are sequentially selected from MS scans based on user-selected criteria. However, the number of MSn spectra that can be acquired during a chromatogram is limited and a trade-off between analytical speed, sensitivity and coverage must be ensured. In this research, we compare four different strategies for automated MS2 DDA, which can be easily implemented in the frame of standard QA/QC workflows for untargeted LC-MS. These strategies consist of (i) DDA in the MS working range; (ii) iterated DDA split into several m/z intervals; (iii) dynamic iterated DDA of (pre)selected potentially informative features; and (iv) dynamic iterated DDA of (pre)annotated metabolic features using a reference database. Their performance was assessed using the analysis of human milk samples as model example by comparing the percentage of LC-MS features selected as the precursor ion for MS2, the number, and class of annotated features, the speed and confidence of feature annotation, and the number of LC runs required.

The Vitamin D Receptor Regulates Glycerolipid and Phospholipid Metabolism in Human Hepatocytes.

The vitamin D receptor (VDR) must be relevant to liver lipid metabolism because VDR deficient mice are protected from hepatosteatosis. Therefore, our objective was to define the role of VDR on the overall lipid metabolism in human hepatocytes. We developed an adenoviral vector for human VDR and performed transcriptomic and metabolomic analyses of cultured human hepatocytes upon VDR activation by vitamin D (VitD). Twenty percent of the VDR responsive genes were related to lipid metabolism, including MOGAT1, LPGAT1, AGPAT2, and DGAT1 (glycerolipid metabolism); CDS1, PCTP, and MAT1A (phospholipid metabolism); and FATP2, SLC6A12, and AQP3 (uptake of fatty acids, betaine, and glycerol, respectively). They were rapidly induced (4-6 h) upon VDR activation by 10 nM VitD or 100 µM lithocholic acid (LCA). Most of these genes were also upregulated by VDR/VitD in mouse livers in vivo. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS) metabolomics demonstrated intracellular accumulation of triglycerides, with concomitant decreases in diglycerides and phosphatidates, at 8 and 24 h upon VDR activation. Significant alterations in phosphatidylcholines, increases in lyso-phosphatidylcholines and decreases in phosphatidylethanolamines and phosphatidylethanolamine plasmalogens were also observed. In conclusion, active VitD/VDR signaling in hepatocytes triggers an unanticipated coordinated gene response leading to triglyceride synthesis and to important perturbations in glycerolipids and phospholipids.

Epistane, an anabolic steroid used for recreational purposes, causes cholestasis with elevated levels of cholic acid conjugates, by upregulating bile acid synthesis (CYP8B1) and cross-talking with nuclear receptors in human hepatocytes.

Anabolic-androgenic steroids are testosterone derivatives, used by body-builders to increase muscle mass. Epistane (EPI) is an orally administered 17α-alkylated testosterone derivative with 2a-3a epithio ring. We identified four individuals who, after EPI consumption, developed long-lasting cholestasis. The bile acid (BA) profile of three patients was characterized, as well the molecular mechanisms involved in this pathology. The serum BA pool was increased from 14 to 61-fold, basically on account of primary conjugated BA (cholic acid (CA) conjugates), whereas secondary BA were very low. In in vitro experiments with cultured human hepatocytes, EPI caused the accumulation of glycoCA in the medium. Moreover, as low as 0.01 µM EPI upregulated the expression of key BA synthesis genes (CYP7A1, by 65% and CYP8B1, by 67%) and BA transporters (NTCP, OSTA and BSEP), and downregulated FGF19. EPI increased the uptake/accumulation of a fluorescent BA analogue in hepatocytes by 50-70%. Results also evidenced, that 40 µM EPI trans-activated the nuclear receptors LXR and PXR. More importantly, 0.01 µM EPI activated AR in hepatocytes, leading to an increase in the expression of CYP8B1. In samples from a human liver bank, we proved that the expression of AR was positively correlated with that of CYP8B1 in men. Taken together, we conclude that EPI could cause cholestasis by inducing BA synthesis and favouring BA accumulation in hepatocytes, at least in part by AR activation. We anticipate that the large phenotypic variability of BA synthesis enzymes and transport genes in man provide a putative explanation for the idiosyncratic nature of EPI-induced cholestasis.

Monitoring of system conditioning after blank injections in untargeted UPLC-MS metabolomic analysis.

Ultra-performance liquid chromatography - mass spectrometry (UPLC-MS) is widely used for untargeted metabolomics in biomedical research. To optimize the quality and precision of UPLC-MS metabolomic analysis, evaluation of blank samples for the elimination of background features is required. Although blanks are usually run either at the beginning or at the end of a sequence of samples, a systematic analysis of their effect of the instrument performance has not been properly documented. Using the analysis of two common bio-fluids (plasma and urine), we describe how the injection of blank samples within a sequence of samples may affect both the chromatographic and MS detection performance depending on several factors, including the sample matrix and the physicochemical properties of the metabolites of interest. The analysis of blanks and post-blank conditioning samples using t-tests, PCA and guided-PCA provides useful information for the elimination of background UPLC-MS features, the identification of column carry over and the selection of the number of samples required to achieve a stable performance.

Determination of non-steroidal anti-inflammatory drugs in water and urine using selective molecular imprinted polymer extraction and liquid chromatography.

A selective solid-phase extraction was employed for the improvement of the determination of non-steroidal anti-inflammatory drugs (NSAIDs) in continental water and urine samples. Ketoprofen, naproxen, diclofenac, and ibuprofen were selected as target analytes due to they are the most frequently administered and consumed NSAIDs. These compounds were extracted using molecular imprinted polymers and determined by liquid chromatography with diode array (DAD), and tandem-mass spectrometry (MS-MS) detectors. Performance of DAD and MS-MS detectors was evaluated throughout this study. The obtained limits of quantification, after a 50-fold preconcentration solid-phase extraction, varied from 20 to 30µgL-1 for DAD, and from 0.007 to 0.017µgL-1 for MS-MS for both types of sample matrixes. Quantitative recoveries were found for blank-samples spiked at different NSAIDs concentration levels, ranging from 0.05 to 10mgL-1 for urine and from 0.5 to 500µgL-1 for water. The proposed methodology was applied for the determination of NSAID residues in urine of prescribed individuals, and continental waters.