Title: Metabolic phenotyping applied to pre-clinical and clinical studies of acetaminophen
metabolism and hepatotoxicity
Author: Muireann Coen1
1
Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of
Medicine, Imperial College London, London SW7 2AZ, UK
m.coen@imperial.ac.uk
Tel: +44 207 5941179
Word Count: 9145 (minus abstract and references)
Keywords: Metabolic phenotyping, metabolomics / metabonomics, acetaminophen, NMR
spectroscopy, liquid chromatography-mass spectrometry
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Abstract
Acetaminophen (APAP, paracetamol, N-acetyl-p-aminophenol) is a widely used analgesic
that is safe at therapeutic doses but is a major cause of acute liver failure (ALF) following
overdose. APAP-induced hepatotoxicity is related to the formation of an electrophilic
reactive metabolite, N-acetyl-p-benzoquinone imine (NAPQI), which is detoxified through
conjugation with reduced glutathione (GSH). One method that has been applied to study
APAP metabolism and hepatotoxicity is that of metabolic phenotyping, which involves the
study of the small molecule complement of complex biological samples. This approach
involves the use of high-resolution analytical platforms such as NMR spectroscopy and mass
spectrometry to generate information-rich metabolic profiles that capture both endogenous
and xenobiotic metabolites that reflect both genetic and environmental influences. Data
modeling and mining and the subsequent identification of panels of candidate biomarkers
are typically approached with multivariate statistical tools. We review the application of
multi-platform metabolic profiling for the study of APAP metabolism in both in vivo models
and humans. We also review the application of metabolic profiling for the study of
endogenous metabolic pathway perturbations in response to APAP hepatotoxicity, with a
particular focus on metabolites involved in the biosynthesis of GSH and those that reflect
mitochondrial function such as long-chain acylcarnitines. Taken together, this body of work
sheds much light on the mechanism of APAP-induced hepatotoxicity and provides candidate
biomarkers that may prove of translational relevance for improved stratification of APAPinduced ALF.
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Introduction
Metabolic phenotyping is a recently invented term to cover the ‘top-down’ systems level
study of low molecular weight metabolites and is an inclusion of earlier metabolic profiling
methods generally grouped as metabonomics or metabolomics. Metabolic phenotyping
enables perturbations from metabolic homeostasis to be followed temporally and in
integrated cellular matrices, examining effects arising from environmental factors such as
drugs, diet or lifestyle or from modulated genetic backgrounds. Ultimately, this approach
enables the generation of unique metabolic phenotypes that hold a wealth of mechanistic
biochemical information and can be integrated with parallel ‘omics’ data. The field of
metabolic phenotyping has endless potential applications and to date has been widely
applied in disease diagnosis and personalized healthcare, large-scale molecular
epidemiological studies, preclinical and clinical pharmacology and toxicology, in addition to
improving the understanding of complex interactions between the host and the gut
microbiome, to name but a few.
High-resolution Analytical Platforms
The earliest applications of metabonomics were centered in the field of toxicology and
utilized high-field
1
H nuclear magnetic resonance (NMR) spectroscopy and pattern
recognition approaches to identify unique metabolic phenotypes that reflected the target
organ and site of toxicity (Nicholson et al., 2002, Nicholson et al., 1999) A major advantage
of the approach lay in the ability to acquire metabolic profiles of biofluids such as urine
across time, enabling the temporal systemic response to a toxin to be followed reflecting
onset, progression and potentially recovery from toxic insult.
Sample preparation is minimal for NMR spectroscopic analysis of biofluids, and detailed
protocols describing how to conduct this type of analysis are available (Dona et al., 2014,
Beckonert et al., 2007). One-Dimensional (1D) 1H NMR spectroscopic experiments are
applied to generate spectra that detect metabolites from diverse chemical classes and that,
depending upon the experimental parameters used to acquire them, are inherently
quantitative. Typically, up to 100 metabolites can be assigned from a high-resolution biofluid
1
H NMR spectrum. The information present in these spectra enables the simultaneous
identification of endogenous and xenobiotic metabolites. Two-dimensional (2D) NMR
spectroscopic experiments, such as homo-nuclear 1H-1H correlation spectroscopy (COSY) and
total correlation spectroscopy TOCSY and hetero-nuclear
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C-1H multiple bond correlation
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(HMBC) and heteronuclear single quantum correlation (HSQC), are employed to aid in
structural identification. In addition, databases of standard metabolites are available
commercially (Bruker S-BASE, Chenomx) and from online resources such as the biological
magnetic resonance biobank (BMRB) and the human metabolome database (HMDB) to aid
in structural identification. High-resolution magic angle spinning (MAS) NMR represents a
means to generate ‘solution-state like’ spectral profiles from intact tissue samples (typically
50 mg), such as clinical biopsies (Beckonert et al., 2010). This has been shown to be a
powerful, non-destructive tool for generating high-resolution metabolic profiles from tissues
such as liver, kidney or brain. Such spectra are complementary to biofluid profiles and have
found application in rapid diagnosis and staging of colorectal cancer (Jimenez et al., 2013,
Mirnezami et al., 2014).
Recently, the application of liquid chromatography and ultra-performance liquid
chromatography coupled with mass spectrometry (UPLC/LC-MS) in metabolic profiling
studies has rapidly increased. Mass spectrometry-based analysis offers a complementary
approach to NMR with higher (albeit structurally dependent) sensitivity and hence broader
coverage of the metabolome albeit with the need for stringent quality control strategies to
ensure reproducibility and reliability of data. Protocols for untargeted approaches that
attempt to cover the widest metabolome in both biofluids and tissues are now available,
and detail the inclusion of suitable quality control strategies (Want et al., 2010b, Want et al.,
2013, Dunn et al., 2011). Typically, more than 5000 metabolic features will be detected in a
single biofluid spectrum generated from a UPLC-quadrupole time-of-flight (QTOF)-MS
platform. The assignment of metabolic structures to these features can be both challenging
and time-consuming and involves the generation of MS/MS fragmentation data, derivation
of empirical formulae from accurate mass measurements and comparison with authentic
standards and databases. For profiling the weakly polar and non-polar metabolic
complement of urine reversed-phase liquid chromatography (RP-LC), usually obtained via
gradient separations on C18-bonded silica stationary phases, is typically applied. Hydrophilic
interaction chromatography (HILIC) has been applied to provide coverage of the more polar
urinary metabolites, as chromatographic retention of polar compounds is improved in this
mode of separation compared to RP-LC. In addition, metabolic profiling approaches also
include targeted LC-MS methods that focus on a particular class of analyte, for example bile
acids (Want et al., 2010a) or urinary steroid hormones (Dai et al., 2012) and often provide
the means of rapid identification and quantification of metabolites with stable-isotope
labeled standards. The stability and reproducibility of a UPLC-TOF-MS platform for urinary
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metabolic profiling was assessed by Benton et al. in a study of inter-site (n=3 laboratories)
and intra-site reproducibility which utilized stable isotope labeled metabolites and pooled
control human urine (Benton et al., 2012). This study showed good platform reproducibility
with coefficients of variation (CVs) of less than 18% across ionization modes and sites and
displayed excellent between-site reproducibility of 0.96 and 0.98 for positive and negative
ionization modes respectively. A schematic of a typical experimental work-flow for UPLC-MS
based analysis of urine together with the data analysis strategy is provided in Figure 1
adapted from (Want et al., 2013)
Alternative analytical platforms such as gas chromatography (GC) and capillary
electrophoresis (CE) coupled to MS are also widely used in metabolic profiling research, and
are detailed in the following review articles and experimental protocols (Chan et al., 2011,
Dunn et al., 2011, Ramautar et al., 2011, Ramautar et al., 2014).
Metabolic Profiling and Preclinical Toxicology
An exemplar for the application of metabolic profiling in the field of preclinical toxicology is
provided by the consortium for metabonomic toxicology (COMET) project. COMET evaluated
the role of metabolic profiling in preclinical toxicity studies, primarily through NMRspectroscopic based profiling of biofluids for a diverse set of toxins and treatments, with a
focus on renal toxins and hepatotoxins (n=150) (Lindon et al., 2005, Lindon et al., 2003).
NMR-based spectroscopic analysis of split urinary samples from a study of hydrazine toxicity
demonstrated that the platform was highly analytically reproducible and robust between
two independent laboratories (Keun et al., 2002). In addition, the COMET consortium
project database led to the generation of an expert system for prediction of the toxicity of
novel compounds based on urinary 1H NMR spectroscopic profiles (Ebbels et al., 2007). The
biobank and metabonomic database generated through this work represents a significant
resource for data mining and future mechanistically-driven studies. The second phase of the
COMET consortium project (COMET-2) applied a mechanistic approach for the study of a
model renal toxin and a hepatotoxin; namely bromoethanamine and galactosamine,
respectively. This involved the application of multiple analytical platforms to profile biofluids,
tissue extracts and intact tissues from preclinical models with a focus on understanding
inter-individual variability in response and protective mechanisms together with the use of
stable isotope labeled studies to explore xenobiotic metabolism (Coen, 2010, Shipkova et al.,
2011). The application of 1H NMR spectroscopy for large-scale urinary metabolic profiling in
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molecular epidemiology studies has also been tested and shown to be highly reproducible
and robust with respect to inter-site studies and displayed excellent analytical stability in
terms of inter- and intra-day variability (Dumas et al., 2006).
Multivariate statistical modeling
Statistical treatment of the complex data generated in metabolic phenotyping studies
depends largely on the study design, however such treatment typically involves application
of multivariate statistical tools to identify panels of discriminatory metabolites associated
with the biological outcome of interest, such as disease status or drug intervention. Data is
also often reduced to single candidate biomarkers and associations with an outcome of
interest assessed through univariate statistical methods. However, this approach is limited
by the assumption that variables/metabolites are independent and fails to utilize the
potential of a multivariate signature in identifying a panel of metabolites (rather than a
single metabolite) with high sensitivity/specificity and predictive power. Multivariate
regression tools commonly applied include principal components analysis (PCA), partial least
squares (PLS) and orthogonal partial least squares regression and discriminant analysis (OPLS/O-PLS-DA). PCA is an unsupervised approach (no a priori class information) that reduces
the high dimensionality of the data and enables inherent clusters within the data, together
with potential outliers, to be rapidly identified and visualized. Supervised approaches
include PLS which enables variance in the spectral data to be modeled with class
membership and hence, simplifies the identification of discriminatory metabolites of
relevance to the outcome. Chemometric modeling of metabolic profiling data have recently
been summarized and reviewed in depth in the following publications. (Madsen et al., 2010,
Trygg et al., 2007)
Application of metabolic profiling to study APAP metabolism and excretion
In this review, acetaminophen (APAP, N-acetyl-p-aminophenol, paracetamol) is used as an
exemplar to detail the application of metabolic profiling for the study of xenobiotic
metabolism and toxicity and to highlight the experimental approach. The literature reviewed
herein spans three decades of research, reflecting technological and methodological
advances and continued generation of novel data of mechanistic and translational relevance.
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The metabolic phenotyping approach that is outlined is equally applicable to the study of
others drugs, therapies or interventions.
APAP is a widely used analgesic and anti-pyretic agent that is safe at therapeutic doses.
However, APAP is the most common cause in the USA and Western Europe of acute liver
failure (ALF) as a result of both intentional and unintentional overdose (Bernal et al., 2010,
Bernal et al., 2013, Lee, 2012). The majority of APAP is glucuronidated in the liver, a phase II
conjugation reaction catalyzed by UDP-glucuronosyltransferases (UGTs). Glucuronidation of
APAP accounts for about 50-70% of the dose with subsequent urinary excretion of the
conjugate. In addition, about 25-35 % of APAP is hepatically sulfated by sulfotransferase
enzymes and then also excreted in urine. APAP is also metabolized via cytochrome P450
enzymes (primarily CYP2E1 in humans) to the reactive electrophilic oxidizing agent, N-acetylpara-benzoquinone imine (NAPQI) (Dahlin et al., 1984, Jollow et al., 1973). It is this route of
metabolism that is believed to represent the hepatotoxic liability of APAP via the
bioactivation of the drug. NAPQI is detoxified through conjugation with GSH, a reaction that
occurs both spontaneously and enzymatically via glutathione-S-transferase (GST) to form
APAP-GSH. The APAP-GSH conjugate is further metabolized to an N-acetyl L-cysteinyl
conjugate (APAP-NAC), a cysteinyl (APAP-CYS) and cysteinyl-glycine conjugate (APAP-CG). A
large fraction of APAP-GSH is excreted in the bile together with a mixture of the thiolcontaining derivatives, which are also excreted in urine. A scheme which summarizes the
hepatic metabolism of APAP is presented in Figure 2 (Nelson, 1982).
One of the first studies to apply 1H NMR spectroscopy to quantify the urinary excretion of
APAP and its metabolites, enabled rapid identification of APAP and its glucuronide (APAP-G),
sulfate (APAP-S), N-acetyl-L-cysteinyl (APAP-NAC), and L-cysteinyl (APAP-Cys) metabolites
(Bales et al., 1984b). The temporal excretion of APAP and its metabolites were quantified in
healthy human subjects and showed that the mean 24 hour excretion as determined by 1H
NMR reflected 77.3% of the dose (a single therapeutic 1g dose). In addition, the authors
described simultaneous profiling of the excretion of a range of additional endogenous
urinary metabolites that included creatinine, citrate, hippurate, and sarcosine. This
pioneering work outlined the future potential of the approach to simultaneously profile both
endogenous and xenobiotic metabolites. 1H NMR spectroscopy was also applied to study
both urine and plasma from subjects who had taken a therapeutic dose or an overdose (fatal
and non-fatal) of APAP (Bales et al., 1988). The ratio of glucuronide to sulfate conjugates
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was greatly elevated in overdose cases, as were levels of APAP-NAC and APAP-Cys, reflecting
increased detoxification of NAPQI. Perturbations in endogenous metabolites including
elevation of numerous amino acids were also simultaneously identified and believed to
reflect hepatic damage and impairment of deamination and transamination processes.
Representative 600 MHz 1H NMR spectra of an aqueous-soluble liver extract from a control
(vehicle-treated) and APAP-treated mouse at 2-hours post-treatment (C57BL/6, 300 mg/kg,
ip) are provided in Figure 3 (unpublished data). This representative example demonstrates
the high metabolic-information content of a typical 1D 1H NMR spectrum and displays the
parallel assignment of both endogenous and xenobiotic metabolites (colored in red for
APAP).
The study of the preclinical in vivo metabolism of APAP has also been approached with the
use of a UPLC-MS platform that enabled the urinary excretion of APAP and its major
metabolites to be followed in the rat (oral gavage with 400, 1600 mg/kg) and showed the
correlation of levels of the N-acetyl-L-cysteine conjugate (APAP-NAC) with toxic outcome as
determined from clinical chemistry and histopathology. (Sun et al., 2009)
Fractionation of complex biofluid samples to remove interfering or potentially confounding
metabolites from the metabolite/s of interest has also been successfully applied to aid in the
characterization of drug metabolites in biofluids, typically through the use of solid phase
extraction chromatography (SPEC). The utilization of SPEC provides a separation step leading
to generation of ‘cleaner’ fractions that can be profiled and those that contain metabolites
of interest can be further concentrated to improve sensitivity of the NMR analysis. This
approach has been applied to characterize drug metabolites in human urine, including APAP
in addition to ibuprofen, aspirin, oxpentifylline and naproxen (Wilson and Nicholson, 1988).
Furthermore, hyphenated analytical platforms have been applied to characterize the urinary
excretion of APAP and its metabolites. Applications have included the direct coupling of
reversed-phase high performance liquid chromatography (RP-HPLC) with high-field NMR
spectroscopy that incorporated gradient HPLC elution and direct acquisition of both oneand two-dimensional NMR spectroscopic data in stopped-flow mode (Spraul et al., 1994).
This approach was useful for rapid detection of APAP and its major metabolites in human
urine, rat urine and rat bile and to be widely translatable to the identification of drug
metabolites, for example those containing a UV chromophore. In addition, the hyphenation
of NMR, HPLC and ion-trap mass spectrometry was achieved in continuous-flow mode and
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applied to study the excretion of APAP in human urine. This approach enabled the
unequivocal detection of urinary APAP-G and APAP-S, together with endogenous
metabolites such as phenylacetylglutamine (Shockcor et al., 1996). This hyphenated
analytical approach was extended to incorporate the use of a cryo-flow probe to couple LCMS and NMR and improve the NMR limit of detection (Spraul et al., 2003). The cryogenic
cooling of the NMR radio-frequency coils and electronics greatly increases the signal to noise
(S/N) ratio and hence allows for analysis of much lower sample volumes (for example, 100 l
of urine) resulting in the detection of many minor APAP metabolites that would otherwise
be below the limit of detection. The hyphenation of analytical platforms also demonstrated
the complementarity of NMR and MS, for example in the characterization of ‘NMR-silent’
APAP metabolites by MS (Spraul et al., 2003, Shockcor et al., 1996). The hyphenation of LCSPE-NMR-MS was also applied to the study of a minor human urinary APAP metabolite that
was unequivocally identified as the ether glucuronide of 3-methoxy-acetaminophen.
(Godejohann et al., 2004)
1
H and 2H NMR spectroscopy has also been applied to study the metabolism and excretion
of APAP in rat, using APAP with a stable-label incorporated into the acetyl group as C2H3 or
13
CH3 (Nicholls et al., 1995). The introduction of these labeled acetyl groups enabled the
extent of deacetylation followed by reacetylation (“futile deacetylation”) to be determined.
The 13C-labelled form was included in the study for comparison of the influence of kinetic
isotope effects on the extent of deacetylation, as in general smaller kinetic isotope effects
are seen with 13C-labelled compounds than with 2H-labelled compounds. When the recovery
of the labeled-APAP metabolites was ascertained, excretion of the metabolites of the
deuterated-APAP form was found to be lower than that of the 13C-labelled version, which
may have been a reflection of deuterium isotope effects on the disposition of the drug. Thus,
the excretion and recovery of 13CH3-APAP and its metabolites as calculated from 1H NMR
spectroscopic analysis was 100% while that of the 2H3 form was about 61 %. This study
revealed that the extent of futile deacetylation (deacetylation followed by reacetylation) of
APAP in the rat was far higher than previously thought and provided a means of assessing
this pathway which was believed to be relevant with respect to induction of nephrotoxicity
by 4-aminophenol (deacetylated APAP). This elegant isotope exchange study was further
extended through direct coupling of NMR with HPLC and through use of a double-labeled
acetyl group: 13CO-13CH3. The level of futile deacetylation was characterized for the sulfate
and, following an SPE step and HPLC-NMR analysis for the glucuronide and was found to be
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approximately 9% for each metabolite. The work was also translated to study the futile
deacetylation of each conjugated metabolite in human (ca. 1-2%) (Nicholls et al., 1997).
LC-NMR-MS was also applied to study glutathione GSH conjugation of NAPQI, and identified
2’-GS-APAP and 3’-GS-APAP as the major conjugates together with a novel labile ipso adduct.
This was a mechanistically relevant finding as the ipso adduct was shown to reduce back to
NAPQI and potentially migrate from its site of formation and interact with other cellular
compartments with the liability to oxidize or covalently bind protein thiols (Chen et al.,
1999).
An LC-MS based approach was also applied to study APAP metabolism and toxicity in
CYP2E1-null mice and wild-type mice, with resistance to APAP observed in the null mice on
the basis of serum aminotransferase activities and blood urea nitrogen levels (Chen et al.,
2008). The contribution of CYP2E1 to APAP metabolism was delineated from this study
design, which unexpectedly revealed that CYP2E1 contribution to APAP metabolism
decreased as the dose administered increased. The simultaneous measurement of hepatic
GSH and hydrogen peroxide enabled assessment of the oxidative stress associated with the
toxic response. Novel metabolites of APAP were determined in wild-type mice that included;
3-methoxy-APAP glucuronide and S-(5-acetylamino-2-hydroxyphenyl)mercaptopyruvic acid
(formed by renal APAP-CYS transamination), 3,3'-biacetaminophen (a dimer of APAP), and a
benzothiazine compound (originating from deacetylated APAP).
These novel minor
metabolites provided mechanistic insight into APAP-induced toxicity as they were associated
with dose, time and genotype. This study represented a powerful combined application of
genetically modified animals and metabolic profiling to identify novel minor metabolites of
mechanistic relevance with the potential to serve as biomarkers.
In addition, LC-MS-based metabolomic approaches have been used to screen for reactive
metabolites through identification of conjugates formed in ‘trapping’ experiments with
nucleophiles such as GSH (Li et al., 2011). This approach was applied to study APAP in human
liver microsomes (HLMs) that contained cytochrome P450 enzymes and the presence or
absence of NADPH and trapping agents such as GSH, semicarbazide and potassium cyanide.
Supernatants from the incubations were fractionated using SPEC and analyzed by UPLC-TOFMS. In parallel, mice were treated with vehicle or 300 mg/kg APAP (ip, n = 4), the livers were
collected 30 minutes post-treatment and aqueous soluble liver extracts were prepared for
UPLC-TOF-MS analysis. The APAP and GSH trapping experiment in HLMs identified four
conjugated metabolites, one of which was a ‘novel GSH-trapped reactive metabolite’, that
reflected conjugation of deacetylated APAP with GSH (PAP-GS). Characterization of the in
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vivo liver extracts also showed increased levels of the major APAP-GSH conjugate (3’
position) and lesser levels of the PAP-GS conjugate, albeit with the limitation that this was
not quantified nor identified in the loadings S-plot. The authors also applied this approach to
study reactive metabolites of pulegone and clozapine (Li et al., 2011).
Additional approaches to characterize complex drug metabolism signatures whilst avoiding
analytical separation of the mixture components have included statistical total correlation
spectroscopy (STOCSY), originally described in an application to large-scale human molecular
epidemiology studies (Cloarec et al., 2005). STOCSY has proved to be powerful in structural
elucidation and in enhancing information recovery from complex metabonomic analytical
datasets. The application of STOCSY to 1D 1H NMR metabolic profiles of human urine
enabled the separation of APAP-derived xenobiotic signatures through the generation of
statistical connectivities based on the covariance of spectral resonances in independent 1D
spectra (Holmes et al., 2007). The STOCSY approach is demonstrated in Figure 4 where the
correlation matrix for a 1-dimensional dataset is generated from a single data point (driver
peak), in this case for D-3-hydroxybutryate. The highest correlations are identified between
resonances from the same molecule and lesser correlations are observed for additional drug
metabolites and endogenous metabolites in what could be termed ‘pathway’ connectivities.
STOCSY has rapidly found new application, for example in the analysis of heteronuclear data
such as 1H-31P and 1H-19F data (Keun et al., 2008, Coen et al., 2007), for uncovering intra- and
inter-metabolite relationships in iterative STOCSY (Sands et al., 2011), and for the study of
reaction kinetics as exemplified in acyl migration reactions of 1-beta-O-acyl glucuronides
(Johnson et al., 2008). A comprehensive review of the myriad of STOCSY-related tools and
applications in metabolic profiling and systems medicine has been provided (Robinette et al.,
2013). It is likely that the continued development and application of STOCSY holds significant
potential in enhancing the study of drug metabolism and systems toxicology in the context
of improving information recovery from metabolic profiling datasets.
Application of metabolic profiling to the study of the endogenous metabolic
consequences of APAP administration
Metabolic profiling has also been applied to study the endogenous metabolic consequences
of APAP administration in order to further explore and elucidate the mechanism of APAPinduced toxicity. In addition, the potential this approach has for identification of a novel
panel of biomarkers that would ultimately prove of translational relevance for the clinical
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setting and prediction of prognosis with respect to APAP-induced ALF is undergoing
exploration. A review of the most-noteworthy literature with respect to understanding
APAP-induced endogenous metabolic perturbations and identification of novel biomarkers
in both pre-clinical and clinical studies is provided below.
Early pre-clinical application of untargeted metabolic profiling
Following on from the early work described above (Bales et al., 1988, Bales et al., 1984a,
Bales et al., 1985, Ghauri et al., 1993), the application of NMR-based metabonomics to
comprehensively profile the systems-wide endogenous metabolic consequences of APAP
administration was first reported by Coen et al., (Coen et al., 2003). This approach involved
an integrated systems level approach and was anchored with traditional clinical chemistry
and histopathological assessment. The study design encompassed treatment of mice
(Alderley Park-1) with differential doses of APAP (0, 50, 150 mg/kg, intra-peritoneal) and
terminal time-points of 15, 30, 60, 120 and 240 min post-treatment (Coen et al., 2003).
Magic angle spinning (MAS) NMR was applied to study intact liver tissue (ca. 10 mg) as this
technique enables the acquisition of high-resolution NMR spectroscopic data which is
comparable to solution-state NMR and also non-destructive (Beckonert et al., 2010). In
parallel, metabolic profiles were acquired for plasma and both aqueous and lipid-soluble
hepatic extracts. The metabolic consequences of APAP administration were determined
from both time- and dose-dependent PCA multivariate models. Clinical chemistry and
histopathology enabled ‘gold-standard’ assessment of hepatic damage induced by APAP,
which was anchored with the metabolic phenotype data. 1H NMR profiles revealed the
detection of APAP, APAP-S, APAP-G and APAP-NAC in the plasma spectra and APAP-G in
spectra of intact liver tissue and aqueous soluble liver extracts. Integration of the multicompartment data revealed a general perturbation of energy metabolism, as reflected by
elevated triglyceride levels in liver and plasma. 1H and 31P NMR profiles of lipid soluble tissue
extracts enabled the detailed study of lipid species that spanned mono- and polyunsaturated fatty acids, cholesterol and phospholipids such as phosphatidylethanolamine
and phosphatidylcholine. In response to APAP an increase in hepatic monounsaturated fatty
acids was observed, suggestive of impairment of mitochondrial oxidative phosphorylation.
The level of polyunsaturated fatty acids decreased, suggestive of increased -oxidation
activity of peroxisomes which may have reflected a compensatory response to counteract
depleted energy levels. Histopathological assessment revealed APAP-induced generation of
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mega-mitochondria that were reported to be ATP depleted, supportive of metabolic
perturbations in energy metabolism. Reduced hepatic glycogen and glucose were observed
together with increased lactate, suggestive of increased rates of glycogenolysis and
glycolysis.
31
P NMR spectroscopy of the lipid soluble tissue extracts indicated depletion of all
phospholipidic species, and an increase in the phospholipid degradation products, choline
and phosphocholine were observed in the aqueous-soluble liver extracts. The degradation of
phospholipids may have reflected an increase in the activity of hepatic phospholipase, an
inhibition of enzymes involved in phospholipid synthesis or APAP-induced free radical
damage or lipid peroxidation. Elevation of numerous hepatic amino acids suggested
perturbation of transamination reactions as a result of impairment of the citric acid cycle.
Transcriptomic data was also generated in parallel for this study and integrated with the
metabonomic data and many of the significantly differentially expressed genes were found
to correlate biologically with the metabonomic changes, suggesting APAP-induced global
energy failure. For example, down-regulation of lipoprotein lipase mRNA, which is
responsible for hydrolysis of triglycerides and very-low-density lipoprotein, correlated with
the observed metabonomic increase of hepatic triglycerides. (Coen et al., 2004)
The COMET consortium initiative involved both acute and chronic dose studies of APAP in
both the rat (Sprague-Dawley) and mouse (male B6C3F1). A metabonomic study of APAP in
the rat was analyzed independently and reported by Sun et al., (Sun et al., 2008) who
applied a multi-platform NMR and UPLC-MS approach to study both chronic and acute
dosing of APAP in Sprague-Dawley rats (acute dosing 0, 400 and 1600 mg/kg by oral gavage;
chronic dosing 0, 200, 400, 800 mg/kg by oral intubation for 7 days). Clinical chemistry
revealed elevated plasma alanine transaminase (ALT) activity in the acute dosing study at
1600 mg/kg with no perturbation identified in the chronic dose study, reflective of the
established resistance of the rat to APAP (McGill et al., 2012b). Histopathological assessment
revealed the presence of multifocal, centrilobular hepatic necrosis at 48 hours following the
acute administration of the high dose of APAP (1600 mg/kg), with inter-individual variability
in the severity of the necrotic response ranging from mild to severe. Regenerative changes
were identified as early as 48 hours post-treatment with resolution of necrosis by 168 hours.
In addition, renal necrosis of the epithelial cells of the proximal convoluted tubules was
observed (APAP 1600 mg/kg) albeit with a minimal score in terms of severity. The parallel
urinary metabolic profiling component revealed similar qualitative endogenous metabolic
perturbations in both the chronic and acute studies and identified APAP-related metabolites
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using both NMR and UPLC-MS technologies which provided evidence for GSH conjugation of
NAPQI. However, hepatic metabolic profiles or GSH levels were not assessed in this study.
The urinary metabolic profiles paralleled histopathological assessment, with respect to
regeneration and adaptation reflected in the re-establishment of metabolic homeostasis
(metabolic profiles returned to pre-treatment or control states) in the acute dosing study. In
contrast, the chronic dose study revealed persistent perturbations of endogenous
metabolites and the absence of a return to homeostasis across the 13-day study time-course.
Analysis of the NMR urinary profiles representing toxic response (acute dose of 1600 mg/kg)
revealed significant perturbation of TCA cycle intermediates suggestive of a shift in energy
metabolism.
In addition, depletion of S-adenosylmethionine, taurine and N-
methylnicotinate suggested a response to oxidative stress and potential upregulation of the
trans-sulfuration pathway in an attempt to regenerate hepatic GSH stores.
Glutathione biosynthesis, one carbon metabolism and the trans-sulfuration pathway
The targeted application of metabolic profiling to study the effect of APAP administration on
GSH biosynthesis and one carbon metabolism and trans-sulfuration has provided important
mechanistic insight into hepatotoxic insult.
A pioneering study in this regard involved the 1H NMR spectroscopic detection of urinary 5Oxoproline (pyroglutamate, 5-OP), an intermediate in the biosynthesis of GSH, with its
urinary excretion potentially representing a non-invasive means of assessing hepatocellular
GSH status. The first report of elevated urinary concentrations of 5-OP in response to druginduced depletion of glutathione was shown in a study of chronic APAP administration in the
rat (1% in the diet for up to 10 weeks)(Ghauri et al., 1993). 5-Oxoprolinuria (pyroglutamic
aciduria), in the context of APAP administration, was first observed using high-resolution 1H
NMR spectroscopy following 2 weeks of APAP dosing, with urinary excretion at high levels
thereafter (up to 1M absolute urinary concentration). 5-Oxoprolinuria was absent in animals
supplemented with methionine, suggesting that chronic dosing of APAP resulted in a severe
impairment of the total sulfur pool, which was restored with methionine supplementation.
Elevation of 5-OP in urine, liver and plasma was also reported from a 1H NMR spectroscopic
based metabonomic study of acute dosing of bromobenzene (1.5 g/kg Han-Wistar
rats)(Waters et al., 2006). Bromobenzene, which causes centrilobular hepatic necrosis, is
known to lead to GSH depletion as a result of detoxification of reactive epoxides (Lau et al.,
1984). The induction of 5-oxoprolinuria which occurred between 31 and 55 hours post-
14
treatment, was believed to result from the bromobenzene-induced inhibition of GSH
synthase and the lack of negative feedback inhibition of gamma-glutamyl-cysteine
synthetase.
5-Oxoprolinuria has also been reported in patients with inherited disorders of the gammaglutamyl cycle such as a deficiency in GSH synthetase (EC 6.3.2.3) or in 5-oxoprolinase (EC
3.5.2.9) (Shi et al., 1996, Dahl et al., 1997, Calpena et al., 2013). 5-Oxoprolinuria has also
been reported clinically in anion gap metabolic acidosis and is associated with exposure to
APAP in the context of certain risk factors that include chronic use, pre-existing hepatic or
renal disease, sepsis, malnutrition, female gender and pregnancy (Dempsey et al., 2000,
O'Brien et al., 2012).
With respect to further understanding perturbation of GSH homeostasis a particularly noteworthy study involved the application of CE-TOF-MS to profile aqueous-soluble liver extracts
and serum following APAP administration (male C57BL/6 mice, 150 mg/kg, ip) with a focus
on the study of metabolites involved in GSH homeostasis (Soga et al., 2006). A major
reduction in both hepatic GSH and GSH disulfide (GSSG) was observed at 2 hours posttreatment, together with a reduction of numerous metabolites involved in the taurine shunt
and the biosynthesis of GSH as summarized in Figure 5. Metabolites that were upstream of
the cysteine biosynthesis pathway, such as methionine, were found to be significantly
elevated. Interestingly, the authors found significantly increased levels of ophthalmic acid
(OA), a non-sulfur-containing analogue of GSH, in which cysteine is replaced with 2aminobutyrate (gamma-Glu-2-AB-Gly, a thiol group is replaced with a methyl group). OA can
be formed in vivo from 2-aminobutyrate in two reactions catalyzed by gammaglutamylcysteine synthetase (GCS) to form gamma-Glu-2AB and GSH synthetase (GS) to form
OA. In support of this pathway elevated levels of gamma-Glu-2AB were also identified,
which suggested induction of GCS. Critically, the authors carried out mechanistically driven
experiments in which they they perturbed hepatic GSH levels via differential mechanisms
through administration of diethylmaleate (DEM) or buthionine sulfoximine (BSO). BSO is
known to inhibit GCS and thus reduce downstream metabolites, including GSH whereas DEM
is known to oxidize the GSH thiol group and lead to lipid peroxidation and necrotic cell death.
The BSO pre-treated group revealed reduced hepatic and serum levels of gamma-Glu-2AB,
GSH and OA compared to the DEM pre-treated group, which resulted in increased levels of
gamma-Glu-2AB and OA, with close concordance between serum and liver for OA and
gamma-Glu-2AB. These data suggested that GCS inhibition, following oxidative stress and
the utilization of GSH, resulted in increased synthesis of OA, and that OA may represent a
15
circulating biomarker of hepatic oxidative stress. The further study of OA and its upstream
metabolites as potential biomarkers of oxidative stress together with translation to the
clinical setting is warranted.
Furthermore, a systems toxicology approach that generated a mathematical model of the
gamma-glutamyl pathway in response to detoxification of APAP, on the basis of data
generated following APAP exposure to a human liver-derived THLE cell line exposed to APAP,
and transfected with human cytochrome CYP2E1 (THLE-2E1 cells), revealed that both OA
and 5-OP levels alone depend not only on hepatocellular GSH levels but also on methionine
status. Hence, it was concluded that both markers should be measured simultaneously to
report on hepatic GSH status (Geenen et al., 2012). The authors identified an adaptive
response experimentally, with respect to up-regulation of glutamyl cysteine synthetase,
which explained the inability of the model to fully predict the experimental metabolite
concentrations and flux data. With incorporation of this adaptive response the mathematical
model revealed that 5-OP and OA were useful predictive biomarkers of GSH status when
analyzed together and that methionine was critical in terms of detoxification capacity. The
translation of this work to in vivo pre-clinical studies and the clinical setting will further
strengthen the application of this model for prediction of GSH status and toxicological
response.
HPLC-MS/MS methods have recently been developed that enable the quantitative and
targeted determination of both OA and 5-OP in both cellular media (THLE-CYP cell lines) and
rat plasma and will prove invaluable for future studies of the clinical utility and predictive
ability of these markers in the context of drug-induced liver injury and understanding
cellular response to GSH perturbation (Geenen et al., 2011a, Geenen et al., 2011b).
The wider cellular effects of perturbed GSH biosynthesis have been alluded to through the
parallel profiling of perturbations in taurine and its downstream products, which provides
potential to improve understanding of broad sulfur-dependent metabolic processes. Hepatic
taurine and hypotaurine were found to be depleted following acute exposure to APAP in the
rat (500 and 1000 mg/kg), in a metabolomic study of 14 different hepatotoxins (Yamazaki et
al., 2013). The effect on taurine homeostasis was further explored through profiling of GSH
and associated metabolites, and revealed that reduced hepatic GSH was associated with
increased levels of OA, 2-aminobutyrate and the GSH catabolites that included gammaglutamyl-dipeptides and 5-OP. In addition, the targeted analysis of bile acids in this study
showed increased plasma levels of glycine conjugated primary bile acids (glycocholate and
16
glycochenodeoxycholate) and depletion of taurine conjugated bile acids (taurocholate and
taurochenodeoxycholate) following exposure to APAP. Taken together, this data suggests
that the depletion of GSH, which was reflected in increased hepatic levels of 5-OP, OA and
gamma-glutamyldipeptides, led to the increased utilization of cysteine for GSH resynthesis
at the expense of taurine. The depletion of taurine supported the reduction in both hepatic
and plasma taurine-conjugated bile acids. Given the complex task of reporting the clinical
chemistry, pathological and targeted metabolic profiling (>1900 metabolites) of urine,
plasma and liver for 14 hepatotoxins, it would be insightful to present the data for APAP
alone and explore it at a deeper mechanistic level. The perturbation in the overall profile
and conjugation pattern of bile acids is of interest for future study and could be extended to
detail primary and secondary bile acid profiles in multiple matrices with assessment of their
mechanistic specificity. A recent clinical study has explored serum bile acid profiles following
APAP overdose in survivors and non-survivors (Woolbright et al., 2014) and found that
glycodeoxycholic acid was significantly elevated in non-survivors and was modestly
predictive of survival at admission to hospital (AUC 0.7) and when ALT peaked (AUC 0.68).
This study focused on six bile acids that represented greater than 95% of the systemic bile
acid pool and were present at high concentrations in the serum, namely,
glycochenodeoxycholic acid (GCDCA), taurochenodeoxycholic acid (TCDCA), glycocholic acid
(GCA), taurocholic acid (TCA), glycodeoxycholic acid (GDCA) and taurodeoxycholic acid
(TDCA).
Mitochondrial function and long-chain acylcarnitines
Perturbation of serum acylcarnitines in response to APAP-induced toxicity has been reported
and is of potential significance as a mechanistic means of assessing mitochondrial toxicity.
Furthermore, the potential for serum acylcarnitines to act as mechanistic and predictive
biomarkers of APAP-induced mitochondrial toxicity and clinical prognosis is compelling.
Acylcarnitines are formed following conjugation of long-chain fatty acids with carnitine and
are essential for the transport of long-chain fatty acids into mitochondria where they are
subsequently metabolized by β-oxidation.
A particularly note-worthy study and the first published example that showed acylcarnitine
perturbations in response to APAP incorporated the use of a knock-out mouse model (Chen
et al., 2009). The application of LC-MS to phenotype serum from both wild-type and CYP2E1null
mice
revealed
significantly
elevated
levels
of
long-chain
acylcarnitines
17
(palmitoylcarnitine, myristoylcarnitine, oleoylcarnitine and palmitoleoylcarnitine) at early
time-points post APAP treatment (Figure 6A, B). In addition, the simultaneous detection of
elevated levels of triglycerides and free fatty acids in wild-type mice suggested that there
was an APAP-induced perturbation of fatty acid -oxidation. The elevation of long-chain
acylcarnitine concentrations was persistent in wild-type mice but returned to control levels
in CYP2E1-null mice within 24 hours of APAP treatment. The temporal elevation in serum
acylcarnitines occurred at a different time-point than the observed increase in aspartate
transaminase (AST) activity (Figure 6C), which it preceded, and the depletion of hepatic GSH
(Figure 6D), which it followed. This suggested that serum acylcarnitine profiles informed
upon a unique cellular phenotype and that they may serve as complementary to traditional
markers of liver injury or function. The role of the nuclear transcription factor, peroxisome
proliferator-activated receptor alpha (PPAR-) in raising serum concentrations of
acylcarnitines was explored through the study of response to a fasting challenge in wild-type
and PPAR- null mice. PPAR- null mice that were either fed or fasted exhibited gross
metabolome differences in comparison to wild-type mice, which included accumulation of
acylcarnitines, suggesting a link with inhibition of PPAR- function and regulation of βoxidation. This was further explored through a targeted study of PPAR- gene expression
following APAP challenge, which revealed that activation of PPAR- was more persistent in
CYP2E1-null mice leading to greater up-regulation of PPAR- genes involved in β-oxidation.
An additional pre-clinical, targeted LC-MS based metabolomic study of serum acylcarnitines
involved exposure to APAP to male B6C3F1 mice (200 mg/kg ip), following an overnight fast
(Bhattacharyya et al., 2013). This study also revealed statistically significantly increased
amounts of palmitoyl, oleoyl and myristoylcarnitine by 2 hours post-treatment with peak
levels observed by 4 hours post-treatment. Interestingly, the quantities of these long-chain
acylcarnitines fell below those of the controls at 8 hours and up to 48 hours post-treatment.
In comparison, L-carnitine was found to be increased at 8 hours post-treatment with
reduced levels of acetyl-carnitine found at all time-points. The elevation of acylcarnitines
was modest and reflected the reduction in hepatic GSH levels and presence of APAP protein
adducts. The reduction in the levels of palmitoylcarnitine relative to controls from 8h posttreatment onwards was not observed in the earlier study (Chen et al., 2009) which may be
attributable to differences in the study design such as the mouse strain, dose level, length of
fasting or analytical platform and experiments that were utilized.
A more recent study evaluated serum acylcarnitines in a pre-clinical model of APAP toxicity
together with clinical APAP overdose patients, to assess the role of these metabolites in
18
predicting clinical outcomes and their potential to serve as mitochondrial toxicity
biomarkers (McGill et al., 2014a). This study involved a pre-clinical component in which male
C57BL/6 mice were treated with APAP (fasted; 300 and fed; 600 mg/kg, ip) and included a
treatment group that was given N-acetylcysteine 1.5 hours post APAP-treatment. The study
also included administration of furosemide as a negative control, given the known induction
of centrilobular necrosis that is similar to that induced by APAP but with no known
mitochondrial perturbation. Histopathology revealed the presence of a severe necrotic
lesion at 12 hours post-treatment with both dose levels of APAP, together with significantly
elevated levels of ALT activity. RP-UPLC-MS analysis revealed the elevation of three serum
acylcarnitines; palmitoylcarnitine, linoleoylcarnitine and oleoylcarnitine, within 3 hours of
administration of APAP, at both dose levels, until 12 hours post-treatment. Interestingly this
elevation was observed for the differential nutritional status groups (fasted; 600 mg/kg, fed;
300 mg/kg) and was not observed following furosemide treatment, suggesting that the
increased acylcarnitine levels were reflective of mitochondrial toxicity. However, in this
study no elevation of acylcarnitines was found in patients with both normal (n=14) and
abnormal liver function (n=16, based on ALT activity) compared to healthy controls (n=6)
following APAP overdose. This negative result may simply reflect the late presentation of
patients to hospital and the subsequent sampling, that missed an early increase in
circulating acylcarnitines. However a more plausible confounding factor in this analysis,
discussed by the authors, was the treatment of all patients with N-acetylcysteine (NAC) prior
to sampling. NAC is the principal antidote used in APAP-overdose: it restores GSH levels and
improves hepatic mitochondrial bioenergetics through supply of Krebs cycle intermediates
and restoration of hepatic ALT levels (Saito et al., 2010). The authors studied the effect of
supplementation with NAC (140 mg/kg) 1.5 hours post-APAP treatment in mice on serum
acylcarnitine levels and found significant depletion in the co-treatment group, reflecting the
therapeutic action of NAC. This led to the hypothesis that NAC improved mitochondrial
function and hence resulted in a reduction in serum acylcarnitine levels. The underlying
assumption was that NAC did not simply scavenge NAPQI or reactive oxygen species (ROS)
since NAPQI covalent binding is known to plateau at the time-point chosen. The study
represents an important addition to the literature given the comparative and detailed
mechanistic analysis between the pre-clinical model and the patient. The clinical element of
this study needs to be expanded to larger cohorts and integrated and anchored with
recently identified biomarkers of mitochondrial damage that include nuclear DNA
fragmentation, mtDNA and glutamate dehydrogenase (GDH) activity (McGill et al., 2012a,
19
McGill et al., 2014b). This would enable improved understanding of the mechanisms
underlying clinical APAP-induced toxicity and could be validated in independent cohorts and
potentially lead to enhanced stratification of patient with respect to prognosis. The future
identification of novel biomarkers that are predictive and prognostic in APAP overdose are
ultimately dependent on extensive biobank cohorts that are well phenotyped from multiple
perspectives and reflect the patient journey from an early stage.
A final example of the targeted study of acylcarnitine perturbation in response to APAP
involved the preclinical study of the protective effect of Wuzhi (Schisandra sphenanthera
extract) in acute APAP-induced toxicity in C57BL/6 mice, 400 mg/kg APAP and pre-treatment
for three days with Wuzhi). This study revealed considerable protection following pretreatment with Wuzhi, with respect to a dramatically reduced ALT response and no
histopathological evidence of necrosis. (Bi et al., 2013) The APAP-induced increase in longchain serum acylcarnitines that included palmitoylcarnitine and oleoylcarnitine was
ameliorated through Wuzhi pre-treatment at both 2 and 24 hours post-treatment, providing
further evidence for the utility of acylcarnitines as biomarkers of APAP-induced
hepatotoxicity and mitochondrial dysfunction. Furthermore, a dramatic increase in serum
triglycerides and free fatty acid levels was observed only in the APAP-treated animals and
not in the Wuhzi pre-treatment group providing evidence for a lack of disruption to fatty
acid -oxidation in the pre-treatment group. However, the APAP-induced depletion of
hepatic GSH was not prevented by pre-treatment with Wuzhi although a marginal increase
in GSH levels was reported following treatment with Wuzhi alone.
However, this
perturbation was statistically insignificant which suggested alternative, and as of yet
unknown, mechanisms were responsible for the protective effect. The validity and
translational relevance of studies that assess the protection of natural products against
APAP hepatotoxicity, in which the natural product is administered prior to APAP, have been
questioned (Jaeschke et al., 2012). Recent review articles have outlined the generation of
pharmacologically and clinically relevant data from carefully designed studies together with
detailed assessments of protective mechanisms post-APAP ingestion (Jaeschke et al., 2010,
Jaeschke et al., 2013).
Translational application of metabolic profiling and pharmacometabonomics
The field of pharmacometabonomics was conceptualized in a paper by Clayton et al., and
defined as ‘the prediction of the outcome (for example, efficacy or toxicity) of a drug or
20
xenobiotic intervention in an individual based on a mathematical model of pre-intervention
metabolite signatures’ (Clayton et al., 2006). The authors reported on the application of
NMR spectroscopy to profile urine from both pre-and post-treatment time-points following
a single toxic-threshold dose of APAP in rats. Clinical chemistry and histopathology were
applied to assess the severity of liver damage with generation of a mean histology score
(MHS) for each animal based on microscopic observation of damage in each of five liver
lobes. The post-treatment spectra were utilized to quantify the 24 hour excretion of APAP,
APAP-S, APAP-G and APAP-NAC. The MHS and the mole ratio of APAP-metabolites revealed
considerable inter-animal variability and both end-points were modeled against the predose urinary metabolic profiles reflecting the endogenous metabolic complement. A
predictive partial least squares (PLS) model of the mole ratio of APAP-G to APAP revealed a
positive correlation (r = 0.48) to the spectral region spanning 5.06-5.14 ppm. This region
contained the anomeric proton resonance of APAP-G and would be expected to also reflect
the presence of endogenous ether glucuronides. The spectral region was hypothesized to be
predictive of the individual glucuronidation capacity of each animal.
The authors also explored the separation of the pre-dose urinary profiles based on three
discrete post-treatment classes that were identified from the MHS (reflecting no/minimal
necrosis (class 1), mild necrosis (class 2) and moderate necrosis (class 3)) using unsupervised
principal components analysis (PCA), as shown in Figure 7. Partial separation was observed
between class 1 and 3 in principal component 2 (PC2) which was identified as due to
differential levels of taurine, trimethylamine N-oxide (TMAO) and betaine. For example,
higher amounts of pre-dose urinary taurine were associated with a lower MHS, and higher
levels of both TMAO and betaine were associated with increased severity of liver necrosis.
The authors hypothesized that taurine levels might reflect the availability of inorganic
sulfate and more broadly of phosphoadenosine phosphosulfate (PAPS), which correlated
with the observation that animals with more severe liver necrosis showed lower levels of
APAP-sulfate. The presence of higher levels of pre-dose urinary TMAO was interpreted as
being reflective of differential gut microfloral populations which may have played a role in
determination of the extent of APAP-induced liver injury. This work represented the first
exemplar of the potential for pharmacometabonomics to predict xenobiotic transformation
and toxic outcomes from pre-clinical baseline metabolic phenotypes.
The first ‘proof-of-principle’ of the translation of pharmacometabonomics to a
human/clinical study also used APAP as the exemplar (Clayton et al., 2009). A clinical trial
design involved recruitment of healthy male volunteers (n=99) who were non-smokers and
21
not taking drugs, dietary supplements or herbal medicines, with additional restrictions
placed on diet and alcohol intake. A single ‘spot’ urine was collected pre-dose, following
which 1g of APAP was ingested orally and urine was collected from 0-3 hours and 3-6 hours
post-treatment. NMR spectroscopic urinary profiles were acquired and the excretion of
APAP and its major metabolites quantified. The analysis focused on calculation of the
excretion ratio of APAP-S to APAP-G from the integral of the N-acetyl spectral peaks in both
post-treatment time-points (with the correlation of excretion calculations based on the
corresponding aromatic signals also given). The post-dose outcome (APAP-S/APAP-G ratio),
that reflected inter-individual variability in the metabolism of a therapeutic dose of APAP
was modeled against the pre-treatment creatinine-normalized spot urine profiles. The
application of PLS-based approaches did not reveal any significant associations between the
pre-treatment profiles and the post-dose outcome, unlike the earlier pre-clinical result
(detailed above – Figure 6). The authors proceeded with a detailed visual comparison of the
pre-treatment spectra at the extreme ends of the S/G distribution (high and low ratios) and
identified two metabolites; p-cresol-sulfate (PCS) and phenylacetylglutamine (PAG), for
which higher levels of these metabolites were visually associated with a lower APAP-S/APAPG ratio. The authors found a statistically significant association between the post-dose
excretion of APAP-S/APAP-G to pre-dose levels of PCS/creatinine (Bonferroni correction for
multiple testing). P-cresol is produced from tyrosine largely by the colonic microflora and
believed to be sulfated by the cytosolic
sulfotransferase, SULT1A1,
and 3’-
phosphoadenosine-5’-phosphosulfate (PAPS). Hence, the authors hypothesized that high
production of pre-dose endogenous p-cresol may reduce the capacity of an individual to
sulfate APAP through competitive sulfonation, given their structural similarities and suggest
this may occur in both the colon and the liver. This study provided novel and interesting data,
to support the role of environmental factors such as the gut microflora in the alteration of
drug metabolism and may translate to the mechanistic understanding of differential
response, for example in drug-induced liver injury. This warrants further research that
validates and tests these findings in independent clinical cohorts and that elucidates the
mechanism and means of assessment of competitive sulfonation. Indeed, to date metabolic
profiling has played a significant role in further understanding the complex interactions
between the host and gut microbiome (Holmes et al., 2012, Li and Jia, 2013, Nicholson et al.,
2012).
An additional clinical metabonomic study of APAP was carried out by Winnike et al., in which
4g of APAP was administered daily and across seven days to healthy volunteers (n=71, male
22
and female,(Winnike et al., 2010)). Based on the serum ALT activity levels the authors
identified three sub-classes termed ‘responders’ (n=17) who showed increased ALT (>2.0
times the baseline level) following onset of dosing and ‘non-responders’ (n=18) who showed
little change in ALT (< 1.5 times the baseline level) and ‘intermediate responders’ (between
1.5 and 2.0 times the baseline level). The authors focused on discrimination of the spectral
profiles of responders from non-responders, both pre-dose and post-dose, using a
multivariate approach comprised of both supervised and unsupervised statistical methods.
O-PLS-DA models revealed separation of both the day 5 and day 9 urine collections for
responders and non-responders based on a combination of endogenous and APAP related
metabolites, reflecting perturbations that mirrored the ALT rise (day 9) and those that
preceded it and this approach was classified as ‘early intervention pharmacometabonomics’
(day 5). However, generation of a robust O-PLS-DA model that discriminated the pre-dose
urinary profiles on the basis of outcome was not possible. An important distinction from the
analyses performed by Clayton et al., is that quantification of the excretion of APAP and its
metabolites was not carried out by Winnike et al. It would be interesting to quantify the
excretion of APAP-S and APAP-G and to test for an association between excretion of these
metabolites and endogenous PCS, as was identified by Clayton et al., albeit in a different
study design with respect to the clinical cohort and the dose and time-course. This
important study, together with the concept of ‘early intervention pharmacometabonomics’,
may play a significant role in the clinical setting in understanding the inter-individual balance
between efficacy and toxicity of therapies. The growing number of original research
contributions to the field of pharmacometabonomics, which span multiple compounds both
pre-clinically and clinically, has been reviewed most recently by Everett et al., 2013 (Everett
et al., 2013).
Future Perspectives
The targeted study of classes of metabolites such as long-chain acylcarnitines and
metabolites involved in the biosynthesis of GSH represent intriguing exemplars of the power
of the approach to identify novel biomarkers that may prove of mechanistic specificity.
However, the power of untargeted, global profiling approaches also warrants further study
as it presents significant potential for the identification of novel metabolites or classes of
metabolites that inform on or predict hepatotoxicity. The continued and expanded study of
metabolites that reflect mitochondrial metabolism and dysfunction may provide
23
mechanism-specific markers together with an understanding of the causal or down-stream
and up-stream events for a given mechanism of hepatotoxicity. In addition, the extension of
current research to encompass wider metabolic pathway coverage is crucial, for example, to
profile the totality of sulfur-containing metabolites and sulfur-dependent processes in
response to hepatotoxic insult.
The study of a CYP2E1 knock-out animal model has provided mechanism-specific
understanding of APAP-induced changes on the metabolome, specifically in understanding
the role of PPAR- in the inhibition of fatty acid -oxidation following an APAP challenge. It
is anticipated that continued application of knock-out models together with newlydeveloped humanized mice models are anticipated to provide further insight into critical
pathway perturbations and data of clinical relevance and allow for the testing and validation
of hypotheses generated at the early, untargeted experimental stage.
The continued development of improved bioinformatics strategies to enhance spectral
information recovery and ultimately aid in identification of novel biomarkers will play an
important role in the development of this field and its future clinical applications,
particularly with respect to information-rich and complex LC-MS data and in large-scale
clinical phenotyping.
Conclusion
In conclusion, the application of metabolic phenotyping to study APAP metabolism and
hepatotoxicity has provided a significant contribution to the scientific literature and
continues to provide novel mechanistic insight from an ever-growing number of applications.
There is immense future potential for the identification of panels of metabolic biomarkers
that hold translational clinical relevance for improved patient stratification and the
prediction of disease prognosis, with respect to APAP-induced acute liver failure and
possibly more broadly to other forms of hepatic disease.
Acknowledgements:
Professors Ian Wilson and John Lindon are acknowledged for their insightful discussion and
for proof-reading the manuscript. Mr Michael Kyriakides is acknowledged for provision of
Figure 3 (unpublished data).
24
Declaration of Interest
The MRC ITTP scheme is acknowledged for funding to MC.
25
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Abbreviations:
APAP, Acetaminophen, paracetamol, N-acetyl-p-aminophenol
ALF, acute liver failure
ALT, alanine aminotransferase
APAP-G, APAP-glucuronide
APAP-CG, APAP-cysteinyl-glycine
APAP-Cys, APAP-L-cysteinyl
APAP-NAC, APAP-N-acetyl-L-cysteinyl
APAP-S, APAP-sulfate
AST, aspartate aminotransferase;
BSO, buthionine sulfoximine
CE, capillary electrophoresis
CV, coefficient of variation
COMET, Consortium for Metabonomic Toxicology
COSY, correlation spectroscopy
CYP450, cytochrome P450
DEM, diethylmaleate
GCS, gamma-glutamylcysteine synthetase
GC, gas-chromatography
GLDH, glutamate dehydrogenase
GSH, reduced glutathione
GSSG, oxidized glutathione
HLM, human liver microsomes
HILIC, Hydrophilic interaction chromatography
IP, intra-peritoneal
LC, liquid-chromatography
MAS, magic angle spinning
MHS, mean histology score
MS, mass spectrometry
NAPQI, N-acetyl-p-benzoquinone imine
NMR, nuclear magnetic resonance spectroscopy
O-PLS-DA, orthogonal-projection on latent structures discriminant analysis
OA, ophthalmic acid
PAPS, 3’-phosphoadenosine-5’-phosphosulfate
PCA, principal components analysis
PLS, partial least squares
PPAR-, peroxisome proliferator-activated receptor alpha
QC, quality control
ROS, reactive oxygen species
RP-LC, reversed-phase liquid chromatography
STOCSY, statistical total correlation spectroscopy
TOCSY, total correlation spectroscopy
HMBC, Heteronuclear Multiple Bond Correlation
HSQC, Heteronuclear Single Quantum Correlation
UGT, UDP-glucuronosyltransferase
UPLC–MS, ultra-performance liquid chromatography–mass spectrometry
5-OP, 5-Oxo-proline
33
Figure 1
Figure 2
34
Figure 3
Figure 4
35
Figure 5
36
Figure 6
Figure 7
37
Figure Legends
Figure 1: Typical experimental UPLC-MS based workflow for urine samples, including quality
control (QC) sample preparation and data analysis. CV, coefficient of variation; PCA, principal
components analysis; QC, quality control; UPLC-MS, ultra-performance liquid
chromatography coupled with mass spectrometry. Adapted from (Want et al., 2013)
Figure 2: Scheme of hepatic acetaminophen (APAP) metabolism. (Nelson, 1982)
Figure 3: 600 MHz 1H NMR spectrum of an aqueous-soluble liver extract from a control and
APAP-treated C57BL/6 mouse (300 mg/kg, ip) at 2 hours post-treatment revealing the
presence of APAP metabolites (red) and numerous endogenous metabolites representing a
wide chemical space (unpublished data). APAP, acetaminophen
Figure 4: Statistical total correlation spectroscopy (STOCSY): (A) one-dimensional (1D) and
(B) two-dimensional (2D) STOCSY correlation/covariance plots of a urinary NMR data set.
Here, lineshapes are calculated by covariance ([−∞,∞]) while colors are set by correlation
([−1,1]). One-dimensional STOCSY plots (A) are traces of the two-dimensional STOCY (B,
black box) at a given chemical shift taken from the “driver” peak. For the maxima of the
doublet of 3-hydroxybutryic acid at 1.2 ppm (“driver” peak), high positive correlation
coefficients are both sensitive and specific indicators of structural connectivity, and
“pathway” connectivities show mostly negative correlations. For other metabolite signals
seen in the 2D STOCSY, high positive correlations such as those between lactate (1.33 ppm),
alanine (1.48 ppm), and glucose (∼3.5–4 ppm) indicate coordinated excretion rather than
structural relationships. From (Robinette et al., 2013) Copyright approved.
Figure 5: Hepatic metabolic changes induced by APAP (2 hours post-dose in male C57BL/6
mice) and identified through a CE-TOF-MS metabolic profiling study. Metabolic
perturbations are mapped onto the glutathione biosynthesis pathway. (Soga et al., 2006)
Copyright approved.
Figure 6: Time-dependent changes in wild-type and Cyp2e1-null mice following 400 mg/kg
APAP treatment and comparison of the biomarkers of APAP toxicity. Serum and liver
samples were collected at 0, 0.5, 1, 2, 4, 8, 16 and 24 hours after APAP treatment. A, Scores
plot of PCA analysis on serum metabolomes. Details of data acquisition, processing and
model construction were described in the Experimental procedures. Each data point
represents the average of 4-8 samples in each sample group (wild-type mice: • and Cyp2e1null mice: ○). The timing of sample collection was labeled beside the data point. The t[1] and
t[2] values represent the scores of each sample group in principal component 1 and 2,
respectively. Fitness (R2) and prediction power (Q2) of this PCA model are 0.388 and 0.251,
respectively. B, Quantitation of serum palmitoylcarnitine level in wild-type and Cyp2e1-null
mice (mean ± SD, n=4 mice/group). Palmitoylcarnitine levels in serum was measured using
the multiple reactions monitoring mode in LC-MS. [2H3]palmitoylcarnitine was used as
internal standard. C, Time course of AST activity in wild-type and Cyp2e1-null mice (mean ±
SD, n=4). D, Time course of hepatic glutathione level in wild-type and Cyp2e1-null mice
(mean ± SD, n=4). Glutathione level in liver was measured using the multiple reactions
monitoring mode in LC-MS. From (Chen et al., 2009) Copyright approved. APAP,
acetaminophen; AST, aspartate transaminase; LC-MS, liquid chromatography coupled with
mass spectrometry; PCA, principal component analysis.
38
Figure 7: Pre-dose discrimination of the degree of liver damage obtained in paracetamoldosed rats. a, A scores plot from PCA of the pre-dose NMR data. Each point represents a
single rat and is colour-coded by its histology class (with increasing severity of damage, class
1 is green, class 2 is blue, class 3 is red; see Table 1). b, Plot of mean histology score (MHS)
versus the PC score obtained from the above PCA, with colour-coding as before. c, A scores
plot from PCA of the pre-dose NMRdata for rats in histology classes 1 and 3. Each point
represents a single rat,with colour-coding as before. d, A loadings plot corresponding to c,
showing the variables making the largest contributions to PC2, and the direction of each
contribution. Individual 0.04 p.p.m.-wide spectral segments are identified by the chemical
shifts at their midpoints, and variables corresponding to particular compounds are identified
by name. Tau, taurine; Citr, citrate; Oxog, 2-oxoglutarate; TMAO, trimethylamine-N-oxide;
Bet, betaine. ‘2Tau’ indicates doubling of the Tau values. From (Clayton et al., 2006)
39