A systems biology approach to understanding elevated serum alanine transaminase levels in a clinical trial with ximelagatran

Hepatotoxicity of AKR1C3 Inhibitor BAY1128688: Findings from an Early Terminated Phase IIa Trial for the Treatment of Endometriosis

INTRODUCTION

BAY1128688 is a selective inhibitor of aldo-keto reductase family 1 member C3 (AKR1C3), an enzyme implicated in the pathology of endometriosis and other disorders. In vivo animal studies suggested a potential therapeutic application of BAY1128688 in treating endometriosis. Early clinical studies in healthy volunteers supported the start of phase IIa.

OBJECTIVE

This manuscript reports the results of a clinical trial (AKRENDO1) assessing the effects of BAY1128688 in adult premenopausal women with endometriosis-related pain symptoms over a 12-week treatment period.

METHODS

Participants in this placebo-controlled, multicenter phase IIa clinical trial (NCT03373422) were randomized into one of five BAY1128688 treatment groups: 3 mg once daily (OD), 10 mg OD, 30 mg OD, 30 mg twice daily (BID), 60 mg BID; or a placebo group. The efficacy, safety, and tolerability of BAY1128688 were investigated.

RESULTS

Dose-/exposure-dependent hepatotoxicity was observed following BAY1128688 treatment, characterized by elevations in serum alanine transferase (ALT) occurring at around 12 weeks of treatment and prompting premature trial termination. The reduced number of valid trial completers precludes conclusions regarding treatment efficacy. The pharmacokinetics and pharmacodynamics of BAY1128688 among participants with endometriosis were comparable with those previously found in healthy volunteers and were not predictive of the subsequent ALT elevations observed.

CONCLUSIONS

The hepatotoxicity of BAY1128688 observed in AKRENDO1 was not predicted by animal studies nor by studies in healthy volunteers. However, in vitro interactions of BAY1128688 with bile salt transporters indicated a potential risk factor for hepatotoxicity at higher doses. This highlights the importance of in vitro mechanistic and transporter interaction studies in the assessment of hepatoxicity risk and suggests further mechanistic understanding is required.

CLINICAL TRIAL REGISTRATION

NCT03373422 (date registered: November 23, 2017).

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.

Matrix and Sampling Effects on Quantification of Protein Biomarkers of Drug-Induced Liver Injury

Macrophage colony stimulating factor 1 receptor (MCSF1R), osteopontin (OPN), high-mobility group protein B1 (HMGB1), glutamate dehydrogenase (GLDH), keratin 18 (K18), and caspase-cleaved keratin 18 (ccK18) are considered promising mechanistic biomarkers for the diagnosis of drug-induced liver injury. Here, we aim to elucidate the impact of the sample matrix and handling on the quantification of these emerging protein biomarkers. We investigated effects such as time from collection to centrifugation during serum (± gel) or EDTA plasma preparation on two assay platforms: immunoaffinity liquid chromatography mass spectrometric assays and sandwich immunoassays. Furthermore, we measured GLDH activity with an enzymatic activity assay. Matrix effects were observed particularly for HMGB1 and MCSF1R. HMGB1 levels were higher in serum than in plasma, whereas higher concentrations of MCSF1R were observed in plasma than in serum. A comparison of sample collection to centrifugation time ranging from 15 to 60 min demonstrated increasing levels of HMGB1 in serum, while MCSF1R, OPN, GLDH, and ccK18 concentrations remained stable. Additionally, there was a poor correlation in HMGB1 and ccK18 levels between serum and plasma. Considering the observed matrix effects, we recommend plasma as a matrix of choice and cross-study comparison studies to be limited to those using the same matrix.

Serum biomarkers of isoniazid-induced liver injury: Aminotransferases are insufficient, and OPN, L-FABP and HMGB1 can be promising novel biomarkers

Isoniazid (INH)-induced liver injury is a great challenge for tuberculosis treatment. Existing biomarkers cannot accurately determine the occurrence of this injury in the early stage. Therefore, developing early specific sensitive biomarkers of INH-induced liver injury is urgent. A rat model of liver injury was established with gastric infusion of INH or INH plus rifampicin (RFP). We examined seven potential novel serum biomarkers, namely, glutamate dehydrogenase (GLDH), liver-fatty acid-binding protein (L-FABP), high-mobility group box-1 (HMGB1), macrophage colony-stimulating factor receptor (MCSF1R), osteopontin (OPN), total cytokeratin 18 (K18), and caspase-cleaved cytokeratin-18 (ccK18), to evaluate their sensitivity and specificity on INH-induced liver injury. With the increase of drug dosage, combining with RFP and prolonging duration of administration, the liver injury was aggravated, showing as decreased weight of the rats, upgraded liver index and oxidative stress level, and histopathological changes of liver becoming marked. But the activity of serum aminotransferases decreased significantly. The area under the curve (AUC) of receiver-operating characteristic (ROC) curve of OPN, L-FABP, HMGB1, MCSF1R, and GLDH was 0.88, 0.87, 0.85, 0.71, and 0.70 (≥0.7), respectively, and 95% confidence interval of them did not include 0.5, with statistical significance, indicating their potential abilities to become biomarkers of INH-induced liver injury. In conclusion, we found traditional biomarkers ALT and AST were insufficient to discover the INH-induced liver injury accurately and OPN, L-FABP, and HMGB1 can be promising novel biomarkers.

Oxidative Stress in Drug-Induced Liver Injury (DILI): From Mechanisms to Biomarkers for Use in Clinical Practice

Idiosyncratic drug-induced liver injury (DILI) is a type of hepatic injury caused by an uncommon drug adverse reaction that can develop to conditions spanning from asymptomatic liver laboratory abnormalities to acute liver failure (ALF) and death. The cellular and molecular mechanisms involved in DILI are poorly understood. Hepatocyte damage can be caused by the metabolic activation of chemically active intermediate metabolites that covalently bind to macromolecules (e.g., proteins, DNA), forming protein adducts-neoantigens-that lead to the generation of oxidative stress, mitochondrial dysfunction, and endoplasmic reticulum (ER) stress, which can eventually lead to cell death. In parallel, damage-associated molecular patterns (DAMPs) stimulate the immune response, whereby inflammasomes play a pivotal role, and neoantigen presentation on specific human leukocyte antigen (HLA) molecules trigger the adaptive immune response. A wide array of antioxidant mechanisms exists to counterbalance the effect of oxidants, including glutathione (GSH), superoxide dismutase (SOD), catalase, and glutathione peroxidase (GPX), which are pivotal in detoxification. These get compromised during DILI, triggering an imbalance between oxidants and antioxidants defense systems, generating oxidative stress. As a result of exacerbated oxidative stress, several danger signals, including mitochondrial damage, cell death, and inflammatory markers, and microRNAs (miRNAs) related to extracellular vesicles (EVs) have already been reported as mechanistic biomarkers. Here, the status quo and the future directions in DILI are thoroughly discussed, with a special focus on the role of oxidative stress and the development of new biomarkers.

Next-Generation DILI Biomarkers: Prioritization of Biomarkers for Qualification and Best Practices for Biospecimen Collection in Drug Development

The diagnosis and management of drug-induced liver injury (DILI) remains a challenge in clinical trials in drug development. The qualification of emerging biomarkers capable of predicting DILI soon after the initiation of treatment, differentiating DILI from underlying liver disease, identifying the causal entity, and assigning appropriate treatment options after DILI is diagnosed are needed. Qualification efforts have been hindered by lack of properly stored and consented biospecimens that are linked to clinical data relevant to a specific context of use. Recommendations are made for biospecimen collection procedures, with the focus on clinical trials, and for specific emerging biomarkers to focus qualification efforts.

Metabolomics in pharmacology - a delve into the novel field of pharmacometabolomics

Introduction: Pharmacometabolomics is an emerging science pursuing the application of precision medicine. Combining both genetic and environmental factors, the so-called pharmacometabolomic approach guides patient selection and stratification in clinical trials and optimizes personalized drug dosage, improving efficacy and safety.Areas covered: This review illustrates the progressive introduction of pharmacometabolomics as an innovative solution for enhancing the discovery of novel drugs and improving research and development (R&D) productivity of the pharmaceutical industry. An extended analysis on published pharmacometabolomics studies both in animal models and humans includes results obtained in several areas such as hepatology, gastroenterology, nephrology, neuropsychiatry, oncology, drug addiction, embryonic cells, neonatology, and microbiomics.Expert opinion: a tailored, individualized therapy based on the optimization of pharmacokinetics and pharmacodynamics, the improvement of drug efficacy, and the abolition of drug toxicity and adverse drug reactions is a key issue in precision medicine. Genetics alone has become insufficient for deciphring intra- and inter-individual variations in drug-response, since they originate both from genetic and environmental factors, including human microbiota composition. The association between pharmacogenomics and pharmacometabolomics may be considered the new strategy for an in-deep knowledge on changes and alterations in human and microbial metabolic pathways due to the action of a drug.

Candidate biomarkers for the diagnosis and prognosis of drug-induced liver injury: An international collaborative effort

Current blood biomarkers are suboptimal in detecting drug-induced liver injury (DILI) and predicting its outcome. We sought to characterize the natural variabilty and performance characteristics of 14 promising DILI biomarker candidates. Serum or plasma from multiple cohorts of healthy volunteers (n = 192 and n = 81), subjects who safely took potentially hepatotoxic drugs without adverse effects (n = 55 and n = 92) and DILI patients (n = 98, n = 28, and n = 143) were assayed for microRNA-122 (miR-122), glutamate dehydrogenase (GLDH), total cytokeratin 18 (K18), caspase cleaved K18, glutathione S-transferase α, alpha-fetoprotein, arginase-1, osteopontin (OPN), sorbitol dehydrogenase, fatty acid binding protein, cadherin-5, macrophage colony-stimulating factor receptor (MCSFR), paraoxonase 1 (normalized to prothrombin protein), and leukocyte cell-derived chemotaxin-2. Most candidate biomarkers were significantly altered in DILI cases compared with healthy volunteers. GLDH correlated more closely with gold standard alanine aminotransferase than miR-122, and there was a surprisingly wide inter- and intra-individual variability of miR-122 levels among healthy volunteers. Serum K18, OPN, and MCSFR levels were most strongly associated with liver-related death or transplantation within 6 months of DILI onset. Prediction of prognosis among DILI patients using the Model for End-Stage Liver Disease was improved by incorporation of K18 and MCSFR levels. Conclusion: GLDH appears to be more useful than miR-122 in identifying DILI patients, and K18, OPN, and MCSFR are promising candidates for prediction of prognosis during an acute DILI event. Serial assessment of these biomarkers in large prospective studies will help further delineate their role in DILI diagnosis and management.

Pharmacometabonomics: The Prediction of Drug Effects Using Metabolic Profiling

Metabonomics, also known as metabolomics, is concerned with the study of metabolite profiles in humans, animals, plants and other systems in order to assess their health or other status and their responses to experimental interventions. Metabonomics is thus widely used in disease diagnosis and in understanding responses to therapies such as drug administration. Pharmacometabonomics, also known as pharmacometabolomics, is a related methodology but with a prognostic as opposed to diagnostic thrust. Pharmacometabonomics aims to predict drug effects including efficacy, safety, metabolism and pharmacokinetics, prior to drug administration, via an analysis of pre-dose metabolite profiles. This article will review the development of pharmacometabonomics as a new field of science that has much promise in helping to deliver more effective personalised medicine, a major goal of twenty-first century healthcare.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

Biomarkers of drug-induced liver injury: progress and utility in research, medicine, and regulation

INTRODUCTION

The difficulty of understanding and diagnosing drug-induced liver injury (DILI) has led to proliferation of serum and genetic biomarkers. Many applications of these biomarkers have been proposed, including investigation of mechanisms, prediction of DILI during early trials or before initiation of therapy in patients, and diagnosis of DILI during therapy. Areas covered: We review the definition and categories of DILI, describe recent developments in DILI biomarker development, and provide guidance for future directions in DILI biomarker research. Expert commentary: There are major obstacles to DILI biomarker development and implementation, including the low prevalence of idiosyncratic DILI (IDILI), weak associations of IDILI with genetic variants, and lack of specificity of many biomarkers for the liver. Certain serum biomarkers, like miR-122, may have clinical utility in early-presenting patients with either intrinsic or idiosyncratic DILI in the future, while others likely will not find use. Future research should focus on implementation of biomarkers to predict later injury and outcome in early presenters with intrinsic DILI, and on development of biomarkers of adaptation and repair in the liver that can be used to determine if a liver test abnormality is likely to be clinically significant in IDILI.

Application of Multiplex Biomarker Approaches to Accelerate Drug Discovery and Development

Multiplex biomarker tests are becoming an essential part of the drug development process. This chapter explores the role of biomarker-based tests as effective tools in improving preclinical research and clinical development, and the challenges that this presents. The potential of incorporating biomarkers in the clinical pipeline to improve decision making, accelerate drug development, improve translation, and reduce development costs is discussed. This chapter also discusses the latest biomarker technologies in use to make this possible and details the next steps that must undertaken to keep driving this process forwards.

NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine

Metabolic profiling by NMR spectroscopy or hyphenated mass spectrometry, known as metabonomics or metabolomics, is an important tool for systems-based approaches in biology and medicine. The experiments are typically done in a diagnostic fashion where changes in metabolite profiles are interpreted as a consequence of an intervention or event; be that a change in diet, the administration of a drug, physical exertion or the onset of a disease. By contrast, pharmacometabonomics takes a prognostic approach to metabolic profiling, in order to predict the effects of drug dosing before it occurs. Differences in pre-dose metabolite profiles between groups of subjects are used to predict post-dose differences in response to drug administration. Thus the paradigm is inverted and pharmacometabonomics is the metabolic equivalent of pharmacogenomics. Although the field is still in its infancy, it is expected that pharmacometabonomics, alongside pharmacogenomics, will assist with the delivery of personalised or precision medicine to patients, which is a critical goal of 21st century healthcare.

HLA-DR7 and HLA-DQ2: Transgenic mouse strains tested as a model system for ximelagatran hepatotoxicity

The oral thrombin inhibitor ximelagatran was withdrawn in the late clinical trial phase because it adversely affected the liver. In approximately 8% of treated patients, drug-induced liver injury (DILI) was expressed as transient alanine transaminase (ALT) elevations. No evidence of DILI had been revealed in the pre-clinical in vivo studies. A whole genome scan study performed on the clinical study material identified a strong genetic association between the major histocompatibility complex alleles for human leucocyte antigens (HLA) (HLA-DR7 and HLA-DQ2) and elevated ALT levels in treated patients. An immune-mediated pathogenesis was suggested. Here, we evaluated whether HLA transgenic mice models could be used to investigate whether the expression of relevant HLA molecules was enough to reproduce the DILI effects in humans. In silico modelling performed in this study revealed association of both ximelagatran (pro-drug) and melagatran (active drug) to the antigen-presenting groove of the homology modelled HLA-DR7 molecule suggesting “altered repertoire” as a key initiating event driving development of DILI in humans. Transgenic mouse strains (tgms) expressing HLA of serotype HLA-DR7 (HLA-DRB1*0701, -DRA*0102), and HLA-DQ2 (HLA-DQB1*0202,–DQA1*0201) were created. These two lines were crossed with a human (h)CD4 transgenic line, generating the two tgms DR7xhCD4 and DQ2xhCD4. To investigate whether the DILI effects observed in humans could be reproduced in tgms, the mice were treated for 28 days with ximelagatran. Results revealed no signs of DILI when biomarkers for liver toxicity were measured and histopathology was evaluated. In the ximelagatran case, presence of relevant HLA-expression in a pre-clinical model did not fulfil the prerequisite for reproducing DILI observed in patients. Nonetheless, for the first time an HLA-transgenic mouse model has been investigated for use in HLA-associated DILI induced by a low molecular weight compound. This study shows that mimicking of genetic susceptibility, expressed as DILI-associated HLA-types in mice, is not sufficient for reproducing the complex pathogenesis leading to DILI in man.

Drug-induced liver injury: recent advances in diagnosis and risk assessment

Idiosyncratic drug-induced liver injury (IDILI) is a rare but potentially severe adverse drug reaction that should be considered in patients who develop laboratory criteria for liver injury secondary to the administration of a potentially hepatotoxic drug. Although currently used liver parameters are sensitive in detecting DILI, they are neither specific nor able to predict the patient's subsequent clinical course. Genetic risk assessment is useful mainly due to its high negative predictive value, with several human leucocyte antigen alleles being associated with DILI. New emerging biomarkers which could be useful in assessing DILI include total keratin18 (K18) and caspase-cleaved keratin18 (ccK18), macrophage colony-stimulating factor receptor 1, high mobility group box 1 and microRNA-122. From the numerous in vitro test systems that are available, monocyte-derived hepatocytes generated from patients with DILI show promise in identifying the DILI-causing agent from among a panel of coprescribed drugs. Several computer-based algorithms are available that rely on cumulative scores of known risk factors such as the administered dose or potential liabilities such as mitochondrial toxicity, inhibition of the bile salt export pump or the formation of reactive metabolites. A novel DILI cluster score is being developed which predicts DILI from multiple complimentary cluster and classification models using absorption-distribution-metabolism-elimination-related as well as physicochemical properties, diverse substructural descriptors and known structural liabilities. The provision of more advanced scientific and regulatory guidance for liver safety assessment will depend on validating the new diagnostic markers in the ongoing DILI registries, biobanks and public-private partnerships.

Nuclear magnetic resonance metabolomics and human liver diseases: The principles and evidence associated with protein and carbohydrate metabolism

During the last decade, metabolomics has become widely used in the field of human diseases. Numerous studies have demonstrated that this is a powerful technique for improving the understanding, diagnosis and management of various types of liver disease, such as acute and chronic liver diseases, and liver transplantation. Nuclear magnetic resonance (NMR) spectroscopy is one of the two most commonly applied methods for metabolomics. The aim of the present review was to investigate the results from recent key publications focusing on aspects of protein and carbohydrate metabolism. The review includes existing procedures, which are currently used for NMR data acquisition and statistical analysis. In addition, notable results obtained by these studies on protein and carbohydrate metabolism concerning human liver diseases are presented.

Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future

Metabolomics and lipidomics are emerging methods for detailed phenotyping of small molecules in samples. It is hoped that such data will: (i) enhance baseline prediction of patient response to pharmacotherapies (beneficial or adverse); (ii) reveal changes in metabolites shortly after initiation of therapy that may predict patient response, including adverse effects, before routine biomarkers are altered; and( iii) give new insights into mechanisms of drug action, particularly where the results of a trial of a new agent were unexpected, and thus help future drug development. In these ways, metabolomics could enhance research findings from intervention studies. This narrative review provides an overview of metabolomics and lipidomics in early clinical intervention studies for investigation of mechanisms of drug action and prediction of drug response (both desired and undesired). We highlight early examples from drug intervention studies associated with cardiometabolic disease. Despite the strengths of such studies, particularly the use of state-of-the-art technologies and advanced statistical methods, currently published studies in the metabolomics arena are largely underpowered and should be considered as hypothesis-generating. In order for metabolomics to meaningfully improve stratified medicine approaches to patient treatment, there is a need for higher quality studies, with better exploitation of biobanks from randomized clinical trials i.e. with large sample size, adjudicated outcomes, standardized procedures, validation cohorts, comparison witth routine biochemistry and both active and control/placebo arms. On the basis of this review, and based on our research experience using clinically established biomarkers, we propose steps to more speedily advance this area of research towards potential clinical impact.

From Metabonomics to Pharmacometabonomics: The Role of Metabolic Profiling in Personalized Medicine

Variable patient responses to drugs are a key issue for medicine and for drug discovery and development. Personalized medicine, that is the selection of medicines for subgroups of patients so as to maximize drug efficacy and minimize toxicity, is a key goal of twenty-first century healthcare. Currently, most personalized medicine paradigms rely on clinical judgment based on the patient's history, and on the analysis of the patients' genome to predict drug effects i.e., pharmacogenomics. However, variability in patient responses to drugs is dependent upon many environmental factors to which human genomics is essentially blind. A new paradigm for predicting drug responses based on individual pre-dose metabolite profiles has emerged in the past decade: pharmacometabonomics, which is defined as “the prediction of the outcome (for example, efficacy or toxicity) of a drug or xenobiotic intervention in an individual based on a mathematical model of pre-intervention metabolite signatures.” The new pharmacometabonomics paradigm is complementary to pharmacogenomics but has the advantage of being sensitive to environmental as well as genomic factors. This review will chart the discovery and development of pharmacometabonomics, and provide examples of its current utility and possible future developments.

Hepatotoxicity of New Oral Anticoagulants (NOACs)

Case reports and analyses of clinical studies and of pharmacovigilance data suggest that new oral anticoagulants (NOACs) are associated with a small risk for hepatotoxicity. The objective of this publication is to summarize the current data about this subject, with a special emphasis on pharmacovigilance data in the World Health Organization (WHO) Global Individual Case Safety Reports (ICSR) database and on potential mechanisms of hepatotoxicity. For that, all available case reports as well as published analyses of clinical studies were obtained with a detailed search in PubMed. In addition, pharmacovigilance data from VigiBase(®), the WHO Global ICRS database, were extracted and analyzed. The data show that liver injury associated with NOACs was reported in clinical studies and in pharmacovigilance databases. Several case reports described potentially life-threatening hepatotoxicity in patients treated with rivaroxaban or dabigatran. For rivaroxaban, most affected patients were symptomatic and liver injury was most often hepatocellular or mixed. The frequency was between 0.1 and 1 % in clinical studies and was by trend lower than for comparators (mostly enoxaparin or warfarin). Comparing the pharmacovigilance reports for the individual NOACs, more hepatic adverse events were reported for rivaroxaban than for dabigatran or apixaban. With the exception of edoxaban, for which only few reports are available, patients with acute liver failure have been reported for every NOAC, but most patients had concomitant drugs or diseases. So far, there are no clear mechanisms explaining the hepatotoxicity of these drugs. We conclude that hepatotoxicity appears to be associated with all NOACs currently on the market. Hepatotoxicity associated with NOACs is idiosyncratic; it appears at therapeutic doses, is rare and the mechanism is not related to the pharmacological action of these drugs. Prescribers should inform patients about possible symptoms of hepatotoxicity and stop these drugs in patients presenting with severe liver injury.

Nuclear magnetic resonance based metabolomics and liver diseases: Recent advances and future clinical applications

Metabolomics is defined as the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification. It is an “omics” technique that is situated downstream of genomics, transcriptomics and proteomics. Metabolomics is recognized as a promising technique in the field of systems biology for the evaluation of global metabolic changes. During the last decade, metabolomics approaches have become widely used in the study of liver diseases for the detection of early biomarkers and altered metabolic pathways. It is a powerful technique to improve our pathophysiological knowledge of various liver diseases. It can be a useful tool to help clinicians in the diagnostic process especially to distinguish malignant and non-malignant liver disease as well as to determine the etiology or severity of the liver disease. It can also assess therapeutic response or predict drug induced liver injury. Nevertheless, the usefulness of metabolomics is often not understood by clinicians, especially the concept of metabolomics profiling or fingerprinting. In the present work, after a concise description of the different techniques and processes used in metabolomics, we will review the main research on this subject by focusing specifically on in vitro proton nuclear magnetic resonance spectroscopy based metabolomics approaches in human studies. We will first consider the clinical point of view enlighten physicians on this new approach and emphasis its future use in clinical “routine”.

Preventing Drug-Induced Liver Injury: How Useful Are Animal Models?

Drug-induced liver injury (DILI) is the most common organ toxicity encountered in regulatory animal toxicology studies required prior to the clinical development of new drug candidates. Very few reports have evaluated the value of these studies for predicting DILI in humans. Indeed, compounds inducing liver toxicity in regulatory toxicology studies are not always correlated with a risk of DILI in humans. Conversely, compounds associated with the occurrence of DILI in phase 3 studies or after market release are often tested negative in regulatory toxicology studies. Idiosyncratic DILI is a rare event that is precipitated in an individual by the simultaneous occurrence of several critical factors. These factors may relate to the host (e.g. human leukocyte antigen polymorphism, inflammation), the drug (e.g. reactive metabolites) or the environment (e.g. diet/microbiota). This type of toxicity therefore cannot be detected in conventional animal toxicology studies. Several animal models have recently been proposed for the identification of drugs with the potential to cause idiosyncratic DILI: rats treated with lipopolysaccharide, Sod2(+/-) mice, panels of inbred mouse strains or chimeric mice with humanized livers. These models are not suitable for use in the prospective screening of new drug candidates. Humans therefore constitute the best model for predicting and assessing idiopathic DILI.

Drug Induced Liver Injury: Review with a Focus on Genetic Factors, Tissue Diagnosis, and Treatment Options

Drug-induced liver injury (DILI) is a rare but potentially life threatening adverse drug reaction. DILI may mimic any morphologic characteristic of acute or chronic liver disease, and the histopathologic features of DILI may be indistinguishable from those of other causes of liver injury, such as acute viral hepatitis. In this review article, we provide an update on causative agents, clinical features, pathogenesis, diagnosis modalities, and outcomes of DILI. In addition, we review results of recently reported genetic studies and updates on pharmacological and invasive treatments.

[Investigation of Predisposition Biomarkers to Identify Risk Factors for Drug-induced Liver Injury in Humans: Analyses of Endogenous Metabolites in an Animal Model Mimicking Human Responders to APAP-induced Hepatotoxicity]

Drug-induced liver injury is a main reason of regulatory action pertaining to drugs, including restrictions to clinical indications and withdrawal from the marketplace. Acetaminophen (APAP) is a commonly used and effective analgesic/antipyretic agent and relatively safe drug even in long-term treatment. However, it is known that APAP at therapeutic doses may cause hepatotoxicity in some individuals. Hence great efforts have been made to identify risk factors for APAP-induced chronic hepatotoxicity. We investigated the contribution of undernourishment to susceptibility to APAP-induced chronic hepatotoxicity using an animal model. We employed daytime restricted fed (RF) rats as a modified-nutritional state model for human APAP-induced hepatotoxicity. RF and ad libitum fed (ALF) rats were given APAP at 0, 300, and 500 mg/kg for 3 months. Plasma and urinary glutathione-related metabolomes and liver function parameters were measured during the dosing period. Endogenous metabolites forming at different levels between the RF and ALF rats could be potential predisposition biomarkers for APAP-induced hepatotoxicity. In addition, RF rats were considered a useful model to estimate the contribution of nutritional state of patients to APAP-induced chronic hepatotoxicity. In this article we report our current research focusing on nutritional state as risk factor for APAP-induced chronic hepatotoxicity and our findings of hepatotoxicity biomarkers.

Drug-induced liver injury: the dawn of biomarkers?

Drug-induced liver injury (DILI) is a potentially fatal adverse event with significant medical and economic impact. Many drugs, especially anti-infective, neurologic or pain-modifying substances, act as hepatotoxins. With cardiovascular toxicity, liver toxicity is one of the two leading causes for drug withdrawal from the market. The liver can be affected directly, in a predictable and dose-dependent manner, or idiosyncratically, independent of the dose and therefore unpredictable.

Currently DILI is a diagnosis of exclusion that physicians have to bear in mind in patients with an unexplained increase of liver enzymes. The type of injury is categorized into hepatocellular, cholestatic, or mixed by the respective enzyme pattern of injury. Symptoms of affected patients can mimic any other liver disease.

Therefore, new diagnostic and prognostic biomarkers for early liver injury are currently being evaluated in multi-centre clinical trials that are conducted by international consortia and other initiatives. Pharmacogenetic testing, next-generation sequencing, proteomics, metabolomics and mechanistic markers can help to preselect susceptible patient populations and tailor drug therapy to individual patients. Proposed DILI indicators that are under investigation include microRNAs, cytokeratin-18 (CK18), high mobility group box protein 1 (HMGB-1), and several other biomarkers. These developments can change clinical practice, and improve patients' safety and management. However, they have not been translated into clinical practice or approved for routine use yet. Management of DILI usually consists of initial withdrawal of the suspected drug and—if applicable—administration of specific antidotes, such as N-acetylcysteine. However, the overall management of DILI could change in the near future with the advent of novel diagnostic and prognostic DILI markers.

Pathogenesis of idiosyncratic drug-induced liver injury and clinical perspectives

Idiosyncratic drug-induced liver injury (DILI) is a rare disease that develops independently of drug dose, route, or duration of administration. Furthermore, idiosyncratic DILI is not a single disease entity but rather a spectrum of rare diseases with varying clinical, histological, and laboratory features. The pathogenesis of DILI is not fully understood. Standardization of the DILI nomenclature and methods to assess causality, along with the information provided by the LiverTox Web site, will harmonize and accelerate research on DILI. Studies of new serum biomarkers such as glutamate dehydrogenase, high mobility group box protein 1, and microRNA-122 could provide information for use in diagnosis and prognosis and provide important insights into the mechanisms of the pathogenesis of DILI. Single nucleotide polymorphisms in the HLA region have been associated with idiosyncratic hepatotoxicity attributed to flucloxacillin, ximelagatran, lapatinib, and amoxicillin-clavulanate. However, genome-wide association studies of pooled cases have not associated any genetic factors with idiosyncratic DILI. Whole genome and whole exome sequencing analyses are under way to study cases of DILI attributed to a single medication. Serum proteomic, transcriptome, and metabolome as well as intestinal microbiome analyses will increase our understanding of the mechanisms of this disorder. Further improvements to in vitro and in vivo test systems should advance our understanding of the causes, risk factors, and mechanisms of idiosyncratic DILI.

Metabolomics as a tool for personalizing medicine: 2012 update

Numerous factors in conjunction with an individual’s genetic make up will determine predisposition to disease, adverse or beneficial effects of drug treatment or therapy, and disease progression. A major limitation of current clinical measures is that the disease phenotype, which is comprised of the genotype and other environmental factors, is underestimated. Rather, each disease is treated similarly even though the disease process is highly complex. Methods that evaluate the interaction of genotype and environmental factors would likely be a better indicator of patients’ response to medical treatments. The omics technologies, specifically metabolomics, will play a major role in the movement towards personalized medicine. Metabolomics is phenotype driven and should provide better clinical biomarkers. Furthermore, recent studies have shown that associations between genetic variants and downstream metabolite changes can provide a unique description of an individual’s genotype and phenotype, which will further enhance the movement towards personalized medicine.

Serum proteomic profiling in patients with drug-induced liver injury

BACKGROUND

Idiosyncratic drug-induced liver injury (DILI) is a complex disorder that is difficult to predict, diagnose and treat.

AIM

To describe the global serum proteome of patients with DILI and controls.

METHODS

A label-free, mass spectrometry-based quantitative proteomic approach was used to explore protein expression in serum samples from 74 DILI patients (collected within 14 days of DILI onset) and 40 controls. A longitudinal analysis was conducted in a subset of 21 DILI patients with available 6-month follow-up serum samples.

RESULTS

Comparison of DILI patients based on pattern, severity and causality assessment of liver injury revealed many differentially expressed priority 1 proteins among groups. Expression of fumarylacetoacetase was correlated with alanine aminotransferase (ALT; r = 0.237; P = 0.047), aspartate aminotransferase (AST; r = 0.389; P = 0.001) and alkaline phosphatase (r = -0.240; P = 0.043), and this was the only protein with significant differential expression when comparing patients with hepatocellular vs. cholestatic or mixed injury. In the longitudinal analysis, expression of 53 priority 1 proteins changed significantly from onset of DILI to 6-month follow-up, and nearly all proteins returned to expression levels comparable to control subjects. Ninety-two serum priority 1 proteins with significant differential expression were identified when comparing the DILI and control groups. Pattern analysis revealed proteins that are components of inflammation, immune system activation and several hepatotoxicity-specific pathways. Apolipoprotein E expression had the greatest power to differentiate DILI patients from controls (89% correct classification; AUROC = 0.97).

CONCLUSION

This proteomic analysis identified differentially expressed proteins that are components of pathways previously implicated in the pathogenesis of idiosyncratic drug-induced liver injury.

A "crossomics" study analysing variability of different components in peripheral blood of healthy caucasoid individuals

Background

Different immunotherapy approaches for the treatment of cancer and autoimmune diseases are being developed and tested in clinical studies worldwide. Their resulting complex experimental data should be properly evaluated, therefore reliable normal healthy control baseline values are indispensable.

Methodology/Principal Findings

To assess intra- and inter-individual variability of various biomarkers, peripheral blood of 16 age and gender equilibrated healthy volunteers was sampled on 3 different days within a period of one month. Complex “crossomics” analyses of plasma metabolite profiles, antibody concentrations and lymphocyte subset counts as well as whole genome expression profiling in CD4⁺T and NK cells were performed. Some of the observed age, gender and BMI dependences are in agreement with the existing knowledge, like negative correlation between sex hormone levels and age or BMI related increase in lipids and soluble sugars. Thus we can assume that the distribution of all 39.743 analysed markers is well representing the normal Caucasoid population. All lymphocyte subsets, 20% of metabolites and less than 10% of genes, were identified as highly variable in our dataset.

Conclusions/Significance

Our study shows that the intra-individual variability was at least two-fold lower compared to the inter-individual one at all investigated levels, showing the importance of personalised medicine approach from yet another perspective.

Review article: Drug-induced liver injury--its pathophysiology and evolving diagnostic tools

BACKGROUND

Drug-induced liver injury (DILI) is a significant cause of morbidity and mortality accounting for at least 13% of acute liver failure cases in the US. It is the leading cause of acute liver failure among patients referred for liver transplantation and the most common reason that drugs in development do not obtain FDA approval. The incidence of DILI has been reported to be one in 10,000 to one in 100,000 patients; however, the actual incidence is probably higher due in part to the difficulty of diagnosis.

AIM

To present a review of the current literature on DILI with a focus on its pathophysiology and evolving diagnostic modalities.

METHODS

A PubMed literature search was conducted using the terms 'drug induced liver injury', 'pathophysiology', 'causality', 'diagnosis', 'toxicogenomics' and 'pharmacogenetics'.

RESULTS

Drug-induced liver injury is an area of ongoing research. From the time it was first recognised, our understanding of the pathophysiology, its classification, diagnosis and reporting by established national networks continues to challenge and evolve. Metabonomics, pharmacogenetics, proteomics and transcriptomics are more recent areas of study that have been applied to further the understanding of DILI.

CONCLUSIONS

Despite recent advances in our understanding of drug-induced liver injury, many aspects of its pathophysiology and clinical impact remain unclear. In addition, genomic-based studies are evolving concepts, which undoubtedly continue to contribute to our understanding of the underlying mechanisms of drug-induced liver injury.

Predicting and preventing acute drug-induced liver injury: what's new in 2010?

IMPORTANCE OF THE FIELD

The field of drug-induced liver injury (DILI) continues to expand in terms of global registries and with new agents added every year. Given the need to improve on our current methods of preclinical testing and monitoring for DILI during both clinical trials and in the post-approval setting, there is increasing research aimed at better understanding why injury occurs and who is most susceptible. To this end, the active pursuit of biomarkers that will predict injury prior to its occurrence and genetic testing that can identify individuals at risk of DILI continue to be at the forefront.

AREAS COVERED IN THIS REVIEW

While alanine aminotransferase (ALT) testing remains the workhorse of biochemical monitoring, it only detects hepatic injury after it has occurred and, therefore, is not a true predictor. The utility and shortcomings of ALT and other liver tests are reviewed along with a synopsis of several other candidate biomarkers that are being studied. In addition, we review the recent data supporting testing for genetic predisposition to DILI and how identifying clinical risk factors may translate into better means for preventing DILI.

WHAT THE READER WILL GAIN

We update the basis on which age and gender are considered risk factors for DILI, and review the latest reports detailing the association of several candidate genes and the development of DILI in a susceptible patient. Human leukocyte antigen-B*5701 is closely linked to the hypersensitivity reaction seen with abacavir, and such screening has been successfully incorporated into HIV treatment around the globe and offers the promise that testing for other genetic markers will soon become a routine part of clinical practice. At present, candidate genes conferring specific susceptibility to DILI have been identified for a relatively few agents (e.g., flucloxacillin, amoxicillin-clavulanate, ximelagatran and isoniazid), but many more are under study. Preventing DILI often comes down to avoiding the use of potentially hepatotoxic drugs in certain situations, and we review the clinical scenarios in which this is most relevant.

TAKE HOME MESSAGE

Given the number and range of studies aimed at identifying predictors of DILI, the focus of this review is to summarize what we consider to be the most relevant new information published on the topics of clinical and genetic factors that predispose to DILI, the use of biomarkers as predictors of acute DILI, along with advances in prevention strategies.

Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms

BACKGROUND

data generated using 'omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of subjects in the study. In this paper, we consider issues relevant in the design of biomedical studies in which the goal is the discovery of a subset of features and an associated algorithm that can predict a binary outcome, such as disease status. We compare the performance of four commonly used classifiers (K-Nearest Neighbors, Prediction Analysis for Microarrays, Random Forests and Support Vector Machines) in high-dimensionality data settings. We evaluate the effects of varying levels of signal-to-noise ratio in the dataset, imbalance in class distribution and choice of metric for quantifying performance of the classifier. To guide study design, we present a summary of the key characteristics of 'omics' data profiled in several human or animal model experiments utilizing high-content mass spectrometry and multiplexed immunoassay based techniques.

RESULTS

the analysis of data from seven 'omics' studies revealed that the average magnitude of effect size observed in human studies was markedly lower when compared to that in animal studies. The data measured in human studies were characterized by higher biological variation and the presence of outliers. The results from simulation studies indicated that the classifier Prediction Analysis for Microarrays (PAM) had the highest power when the class conditional feature distributions were Gaussian and outcome distributions were balanced. Random Forests was optimal when feature distributions were skewed and when class distributions were unbalanced. We provide a free open-source R statistical software library (MVpower) that implements the simulation strategy proposed in this paper.

CONCLUSION

no single classifier had optimal performance under all settings. Simulation studies provide useful guidance for the design of biomedical studies involving high-dimensionality data.

Pharmacogenetics of drug-induced liver injury

Recent progress in research on drug-induced liver injury (DILI) has been determined by key developments in two areas. First, new technologies allow the identification of genetic risk factors with improved sensitivity, specificity, and efficiency. Second, new mechanistic concepts of DILI emphasize the importance of unspecific "downstream" events following drug-specific initial "upstream" hepatocyte injury and of complex interactions between environmental and genetic risk factors. The integration of genetic and mechanistic concepts is essential for current research approaches, and genetic studies of DILI now focus on targets that affect the function and transcriptional regulation of genes relating not only to drug metabolism but also to human leukocyte antigens (HLAs), cytokines, oxidative stress, and hepatobiliary transporters. Risk factors affecting unspecific downstream mechanisms may be identified using pooled DILI cases caused by various drugs. The power to detect variants that confer a low risk can be increased by recruitment of strictly selected cases through large networks, whereas controls may also be obtained from genotyped reference populations. The first genomewide studies of DILI identified HLA variants as risk factors for hepatotoxicity associated with flucloxacillin and ximelagatran, and their design has defined a new standard for pharmacogenetic studies. From a clinical and regulatory point of view, there is a need for genetic tests that identify patients at increased hepatotoxic risk. However, DILI is a rare complex disease, and pharmacogenetic studies have so far not been able to identify interactions of several risk factors defining a high population-attributable risk and clinically relevant absolute risk for DILI.