Paracetamol metabolism, hepatotoxicity, biomarkers and therapeutic interventions: a perspective

After over 60 years of therapeutic use in the UK, paracetamol (acetaminophen, N-acetyl-p-aminophenol, APAP) remains the subject of considerable research into both its mode of action and toxicity. The pharmacological properties of APAP are the focus of some activity, with the role of the metabolite N-arachidonoylaminophenol (AM404) still a topic of debate. However, that the hepatotoxicity of APAP results from the production of the reactive metabolite N-acetyl-p-benzoquinoneimine (NAPQI/NABQI) that can deplete glutathione, react with cellular macromolecules, and initiate cell death, is now beyond dispute. The disruption of cellular pathways that results from the production of NAPQI provides a source of potential biomarkers of the severity of the damage. Research in this area has provided new diagnostic markers such as the microRNA miR-122 as well as mechanistic biomarkers associated with apoptosis, mitochondrial dysfunction, inflammation and tissue regeneration. Additionally, biomarkers of, and systems biology models for, glutathione depletion have been developed. Furthermore, there have been significant advances in determining the role of both the innate immune system and genetic factors that might predispose individuals to APAP-mediated toxicity. This perspective highlights some of the progress in current APAP-related research

A Unique Automation Platform for Measuring Low Level Radioactivity in Metabolite Identification Studies

Generation and interpretation of biotransformation data on drugs, i.e. identification of physiologically relevant metabolites, defining metabolic pathways and elucidation of metabolite structures, have become increasingly important to the drug development process. Profiling using 14C or 3H radiolabel is defined as the chromatographic separation and quantification of drug-related material in a given biological sample derived from an in vitro, preclinical in vivo or clinical study. Metabolite profiling is a very time intensive activity, particularly for preclinical in vivo or clinical studies which have defined limitations on radiation burden and exposure levels. A clear gap exists for certain studies which do not require specialized high volume automation technologies, yet these studies would still clearly benefit from automation. Use of radiolabeled compounds in preclinical and clinical ADME studies, specifically for metabolite profiling and identification are a very good example. The current lack of automation for measuring low level radioactivity in metabolite profiling requires substantial capacity, personal attention and resources from laboratory scientists. To help address these challenges and improve efficiency, we have innovated, developed and implemented a novel and flexible automation platform that integrates a robotic plate handling platform, HPLC or UPLC system, mass spectrometer and an automated fraction collector

The human early-life exposome (HELIX): project rationale and design

Background: Developmental periods in early life may be particularly vulnerable to impacts of environmental exposures. Human research on this topic has generally focused on single exposure–health effect relationships. The “exposome” concept encompasses the totality of exposures from conception onward, complementing the genome. Objectives: The Human Early-Life Exposome (HELIX) project is a new collaborative research project that aims to implement novel exposure assessment and biomarker methods to characterize early-life exposure to multiple environmental factors and associate these with omics biomarkers and child health outcomes, thus characterizing the “early-life exposome.” Here we describe the general design of the project. Methods: In six existing birth cohort studies in Europe, HELIX will estimate prenatal and postnatal exposure to a broad range of chemical and physical exposures. Exposure models will be developed for the full cohorts totaling 32,000 mother–child pairs, and biomarkers will be measured in a subset of 1,200 mother–child pairs. Nested repeat-sampling panel studies (n = 150) will collect data on biomarker variability, use smartphones to assess mobility and physical activity, and perform personal exposure monitoring. Omics techniques will determine molecular profiles (metabolome, proteome, transcriptome, epigenome) associated with exposures. Statistical methods for multiple exposures will provide exposure–response estimates for fetal and child growth, obesity, neurodevelopment, and respiratory outcomes. A health impact assessment exercise will evaluate risks and benefits of combined exposures. Conclusions: HELIX is one of the first attempts to describe the early-life exposome of European populations and unravel its relation to omics markers and health in childhood. As proof of concept, it will form an important first step toward the life-course exposome

Determinants of the urinary and serum metabolome in children from six European populations

Background Environment and diet in early life can affect development and health throughout the life course. Metabolic phenotyping of urine and serum represents a complementary systems-wide approach to elucidate environment–health interactions. However, large-scale metabolome studies in children combining analyses of these biological fluids are lacking. Here, we sought to characterise the major determinants of the child metabolome and to define metabolite associations with age, sex, BMI and dietary habits in European children, by exploiting a unique biobank established as part of the Human Early-Life Exposome project (http://www.projecthelix.eu). Methods Metabolic phenotypes of matched urine and serum samples from 1192 children (aged 6–11) recruited from birth cohorts in six European countries were measured using high-throughput 1H nuclear magnetic resonance (NMR) spectroscopy and a targeted LC-MS/MS metabolomic assay (Biocrates AbsoluteIDQ p180 kit). Results We identified both urinary and serum creatinine to be positively associated with age. Metabolic associations to BMI z-score included a novel association with urinary 4-deoxyerythronic acid in addition to valine, serum carnitine, short-chain acylcarnitines (C3, C5), glutamate, BCAAs, lysophosphatidylcholines (lysoPC a C14:0, lysoPC a C16:1, lysoPC a C18:1, lysoPC a C18:2) and sphingolipids (SM C16:0, SM C16:1, SM C18:1). Dietary-metabolite associations included urinary creatine and serum phosphatidylcholines (4) with meat intake, serum phosphatidylcholines (12) with fish, urinary hippurate with vegetables, and urinary proline betaine and hippurate with fruit intake. Population-specific variance (age, sex, BMI, ethnicity, dietary and country of origin) was better captured in the serum than in the urine profile; these factors explained a median of 9.0% variance amongst serum metabolites versus a median of 5.1% amongst urinary metabolites. Metabolic pathway correlations were identified, and concentrations of corresponding metabolites were significantly correlated (r > 0.18) between urine and serum. Conclusions We have established a pan-European reference metabolome for urine and serum of healthy children and gathered critical resources not previously available for future investigations into the influence of the metabolome on child health. The six European cohort populations studied share common metabolic associations with age, sex, BMI z-score and main dietary habits. Furthermore, we have identified a novel metabolic association between threonine catabolism and BMI of children

Consensus-Phenotype Integration of Transcriptomic and Metabolomic Data Implies a Role for Metabolism in the Chemosensitivity of Tumour Cells

Using transcriptomic and metabolomic measurements from the NCI60 cell line panel, together with a novel approach to integration of molecular profile data, we show that the biochemical pathways associated with tumour cell chemosensitivity to platinum-based drugs are highly coincident, i.e. they describe a consensus phenotype. Direct integration of metabolome and transcriptome data at the point of pathway analysis improved the detection of consensus pathways by 76%, and revealed associations between platinum sensitivity and several metabolic pathways that were not visible from transcriptome analysis alone. These pathways included the TCA cycle and pyruvate metabolism, lipoprotein uptake and nucleotide synthesis by both salvage and de novo pathways. Extending the approach across a wide panel of chemotherapeutics, we confirmed the specificity of the metabolic pathway associations to platinum sensitivity. We conclude that metabolic phenotyping could play a role in predicting response to platinum chemotherapy and that consensus-phenotype integration of molecular profiling data is a powerful and versatile tool for both biomarker discovery and for exploring the complex relationships between biological pathways and drug response

Metabolic Hydrolysis of Aromatic Amides in Selected Rat, Minipig, and Human In Vitro Systems

The release of aromatic amines from drugs and other xenobiotics resulting from the hydrolysis of metabolically labile amide bonds presents a safety risk through several mechanisms, including geno-, hepato- and nephrotoxicity. Whilst multiple in vitro systems used for studying metabolic stability display serine hydrolase activity, responsible for the hydrolysis of amide bonds, they vary in their efficiency and selectivity. Using a range of amide-containing probe compounds (0.5–10 µM), we have investigated the hydrolytic activity of several rat, minipig and human-derived in vitro systems - including Supersomes, microsomes, S9 fractions and hepatocytes - with respect to their previously observed human in vivo metabolism. In our hands, human carboxylesterase Supersomes and rat S9 fractions systems showed relatively poor prediction of human in vivo metabolism. Rat S9 fractions, which are commonly utilised in the Ames test to assess mutagenicity, may be limited in the detection of genotoxic metabolites from aromatic amides due to their poor concordance with human in vivo amide hydrolysis. In this study, human liver microsomes and minipig subcellular fractions provided more representative models of human in vivo hydrolytic metabolism of the aromatic amide compounds tested

Yale school of public health symposium on lifetime exposures and human health: the exposome; summary and future reflections

The exposome is defined as "the totality of environmental exposures encountered from birth to death" and was developed to address the need for comprehensive environmental exposure assessment to better understand disease etiology. Due to the complexity of the exposome, significant efforts have been made to develop technologies for longitudinal, internal and external exposure monitoring, and bioinformatics to integrate and analyze datasets generated. Our objectives were to bring together leaders in the field of exposomics, at a recent Symposium on "Lifetime Exposures and Human Health: The Exposome," held at Yale School of Public Health. Our aim was to highlight the most recent technological advancements for measurement of the exposome, bioinformatics development, current limitations, and future needs in environmental health. In the discussions, an emphasis was placed on moving away from a one-chemical one-health outcome model toward a new paradigm of monitoring the totality of exposures that individuals may experience over their lifetime. This is critical to better understand the underlying biological impact on human health, particularly during windows of susceptibility. Recent advancements in metabolomics and bioinformatics are driving the field forward in biomonitoring and understanding the biological impact, and the technological and logistical challenges involved in the analyses were highlighted. In conclusion, further developments and support are needed for large-scale biomonitoring and management of big data, standardization for exposure and data analyses, bioinformatics tools for co-exposure or mixture analyses, and methods for data sharing

Simultaneous enantiospecific detection of multiple compounds in mixtures using NMR spectroscopy.

Chirality plays a fundamental role in nature, but its detection and quantification still face many limitations. To date, the enantiospecific analysis of mixtures necessarily requires prior separation of the individual components. The simultaneous enantiospecific detection of multiple chiral molecules in a mixture represents a major challenge, which would lead to a significantly better understanding of the underlying biological processes; for example, via enantiospecifically analysing metabolites in their native environment. Here, we report on the first in situ enantiospecific detection of a thirty-nine-component mixture. As a proof of concept, eighteen essential amino acids at physiological concentrations were simultaneously enantiospecifically detected using NMR spectroscopy and a chiral solvating agent. This work represents a first step towards the simultaneous multicomponent enantiospecific analysis of complex mixtures, a capability that will have substantial impact on metabolism studies, metabolic phenotyping, chemical reaction monitoring, and many other fields where complex mixtures containing chiral molecules require efficient characterisation