Metabolomics approaches for discovering biomarkers of drug-induced hepatotoxicity and nephrotoxicity
Introduction
New drugs can be approved by the Food and Drug Administration (FDA) after passing a series of clinical trials that demonstrate therapeutic efficacy and lack of serious adverse effects. During clinical trials, many of the serious side effects occur as a result of liver or kidney injury. One reason for the late detection of serous adverse effects induced by drugs is the lack of efficient and accurate injury biomarkers that can translate from the preclinical studies to clinical studies. Novel and specific translational biomarkers of injury in the liver and kidney induced by drug toxicity are therefore demanded that will reduce the time and cost associated with drug discovery and approval.
Clinical trials typically assess serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), and bilirubin levels to diagnose liver injuries and blood urea nitrogen (BUN) and creatinine to monitor acute kidney injury. In the case of BUN (Tilson and Moser, 1992, Bleecker, 2000, Adamcova et al., 2005, Vaidya and Bonventre, 2006) and creatinine, these clinical biomarkers do not deviate from normal levels until significant renal injury has already occurred (Espandiari et al., 2007, Zhou et al., 2008). Other biomarkers are either non-specific or inaccurate. ALT is a biomarker for hepatocyte injury, but its blood level can increase for a variety of reasons (Lewis, 1984, Sherman, 1991, Zeisel et al., 1991, Vaidya and Bonventre, 2006); its value alone therefore is not a reliable biomarker for liver injury (Amacher, 1998, Dufour et al., 2000, Kaplowitz, 2001, Kaplowitz, 2005, Dhami et al., 1979, Yamada et al., 1984a, Yamada et al., 1984b, Waner and Nyska, 1991). Therefore, the pharmaceutical industry and regulatory agencies have invested much effort toward discovering novel biomarkers that are organ specific and benefit both preclinical and clinical studies.
Preclinical studies can determine some adverse effects before investigational new drug (IND) submissions but many drug candidates enter clinical trials and subsequently cause adverse effects. The major reason for ending a drug in phase I trials is toxicity (Suter et al., 2004), but toxicity is still a reason for stopping drugs in phase II and phase III clinical trials. After a drug hits the market, toxicity is the major reason a drug is removed from the shelf or given a black box warning label. The fact that the number of serious adverse effects is growing faster than the number of prescriptions (Moore et al., 2007) clearly indicates there is a failure of animal safety studies to translate to human safety. The prevalence and associated costs of the failure of a drug candidate during the clinical trials and post-market significantly increase the cost of the drug development expenditure (Lazarou et al., 1998, Pirmohamed et al., 2004). Therefore, there is need for new efficient biomarkers that can translate effectively from preclinical trials to human studies. Additionally, personalized medicine biomarkers can be used to predict whether that individual will respond favorably or adversely to a drug or medical therapy. Metabolomics can play a role in providing translational biomarkers for organ injury and for predicting a susceptible subset of the population that should avoid specific drugs.
Global metabolic profiling is an emerging technology offering promise for identifying early toxicity biomarkers that are specific indicators of damage to a particular organ. The term global metabolic profiling encompasses both metabolomics and metabonomics studies, which have slightly different definitions. Metabolomics refers to the measurement of the metabolite pool that exists within a cell under a particular set of conditions (Fiehn, 2002) while metabonomics describes “the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification” (Nicholson et al., 1999). Metabolomics and metabonomics are metabolic profiling methods that offer the opportunity to identify biomarkers or patterns of biomarker changes related to drug toxicity in biofluid samples, such as urine and blood, which can be collected with relative ease. The overall pattern of metabolic biomarkers is expected to differ based upon the origin of the toxicity, specifically the organ that is targeted by a particular drug compound (Robertson et al., 2000, Lindon et al., 2005a, Lindon et al., 2005b, Ebbels et al., 2007, Nicholson et al., 2007). The terms metabolic profiling, metabolomics and metabonomics have been increasingly used interchangeably throughout the literature and this review uses all these terms at specific points because the titles of the manuscripts we are referencing used only one of these terms. We use metabolic profiling in giving general statements about metabonomics and metabolomics.
Section snippets
Metabolomics procedures
A general flow chart showing the logistical steps necessary for conducting metabolomics studies is displayed in Fig. 1. The first step is sample generation from a toxicity study. A well-planned toxicity study with multiple doses, multiple time points for sample collection and preparation are very important; if performed improperly the data generated could be invalid. Protocols for sample generation and collection need to be carefully designed before the study begins, so effects from factors
Metabolomics in drug toxicity
One of the major research areas that metabolic profiling will continue to impact is the investigation of drug toxicity (Nicholson et al., 2002, Ebbels et al., 2003, Heijne et al., 2005, Robertson, 2005, Portilla et al., 2006, Schnackenberg et al., 2006). There is a strong need to develop new biomarkers that can accurately predict toxicity in the preclinical development of new chemical entities (NCEs) early in the drug development process and are translatable to the clinic. Metabolic profiling
Importance of understanding phenotypic factors in drug toxicity studies
A better understanding of gene–environment interactions is needed for personalized medicine to be successful. Fig. 6 shows how genes and the environment interact with transcriptomics, proteomics, and metabolomics. The end product of transcriptomics is metabolites. Genetics relates the inherited genetic DNA of a patient with their health status and responses to medical treatments. Transcriptomics evaluates the level of mRNA expression, proteomics investigates alterations in proteins, and
Conclusions
Metabolomics has shown the potential to add physiological and metabolic pathway information to drug toxicity studies. Initially, NMR was the primary analytical technique used in metabolomics studies because of its ease of use, inherent quantitative ability and high reproducibility, but lately many groups have used LC/MS or GC/MS because of their greater sensitivity and selectivity capabilities. In the future, we expect that both NMR and MS analyses will be used in metabolomics studies as this
Acknowledgments and disclaimer
The views presented in this article do not necessarily reflect those of the U.S. Food and Drug Administration.
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