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 APAP-

induced 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 1H 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 1H 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 13C-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 NMR-

spectroscopic 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 (O-

PLS/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-acetyl-

para-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 thiol-

containing 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 was

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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 one-

and 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 LC-

MS 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 LC-

SPE-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) 1H 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 C 2H3 or 13CH3 (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-TOF-

MS. 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 APAP-

induced 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 multi-

compartment 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 poly-

unsaturated 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. 31P 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 5-

Oxoproline (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 drug-

induced 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-treatment,

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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 gamma-

glutamyl 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 note-

worthy 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 post-

treatment, 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 2-

aminobutyrate (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 gamma-

glutamylcysteine 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 circulating biomarker of hepatic oxidative stress. The further study of OA and its upstream

15

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 gamma-

glutamyl-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

glycochenodeoxycholate) and depletion of taurine conjugated bile acids (taurocholate and

16

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 CYP2E1-

null mice revealed significantly elevated levels of long-chain acylcarnitines

(palmitoylcarnitine, myristoylcarnitine, oleoylcarnitine and palmitoleoylcarnitine) at early

17

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 β-

oxidation. 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 post-

treatment 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

predicting clinical outcomes and their potential to serve as mitochondrial toxicity biomarkers

18

(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,

McGill et al., 2014b). This would enable improved understanding of the mechanisms

19

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 pre-

treatment 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 long-

chain 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

xenobiotic intervention in an individual based on a mathematical model of pre-intervention

20

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 pre-

dose 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

not taking drugs, dietary supplements or herbal medicines, with additional restrictions

21

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/APAP-

G 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

and female,(Winnike et al., 2010)). Based on the serum ALT activity levels the authors

22

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

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

23

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 newly-

developed 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).

Declaration of Interest

The MRC ITTP scheme is acknowledged for funding to MC.

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Abbreviations:

APAP, Acetaminophen, paracetamol, N-acetyl-p-aminophenolALF, acute liver failure ALT, alanine aminotransferaseAPAP-G, APAP-glucuronide APAP-CG, APAP-cysteinyl-glycineAPAP-Cys, APAP-L-cysteinyl APAP-NAC, APAP-N-acetyl-L-cysteinylAPAP-S, APAP-sulfateAST, aspartate aminotransferase;BSO, buthionine sulfoximine CE, capillary electrophoresis CV, coefficient of variation COMET, Consortium for Metabonomic Toxicology COSY, correlation spectroscopyCYP450, cytochrome P450DEM, diethylmaleate GCS, gamma-glutamylcysteine synthetase GC, gas-chromatography GLDH, glutamate dehydrogenase GSH, reduced glutathioneGSSG, oxidized glutathione HLM, human liver microsomes HILIC, Hydrophilic interaction chromatography IP, intra-peritonealLC, liquid-chromatographyMAS, magic angle spinningMHS, mean histology score MS, mass spectrometryNAPQI, N-acetyl-p-benzoquinone imine NMR, nuclear magnetic resonance spectroscopyO-PLS-DA, orthogonal-projection on latent structures discriminant analysisOA, ophthalmic acid PAPS, 3’-phosphoadenosine-5’-phosphosulfate PCA, principal components analysis PLS, partial least squares PPAR-, peroxisome proliferator-activated receptor alphaQC, quality control ROS, reactive oxygen species RP-LC, reversed-phase liquid chromatography STOCSY, statistical total correlation spectroscopyTOCSY, total correlation spectroscopyHMBC, Heteronuclear Multiple Bond CorrelationHSQC, Heteronuclear Single Quantum CorrelationUGT, UDP-glucuronosyltransferase UPLC–MS, ultra-performance liquid chromatography–mass spectrometry 5-OP, 5-Oxo-proline

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Figure 1

Figure 2

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Figure 3

Figure 4

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Figure 5

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Figure 6

Figure 7

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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 Cyp2e1-null 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.

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Figure 7: Pre-dose discrimination of the degree of liver damage obtained in paracetamol-dosed 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)

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