Achieving the ability to identify individuals who are susceptible to drug-induced liver injury (DILI) would represent a major advance in personalized medicine. Clayton et al. demonstrated that the pattern of endogenous metabolites in urine could predict susceptibility to acetaminophen-induced liver injury in rats. We designed a clinical study to test this approach in healthy adults who received 4 g of acetaminophen per day for 7 days. Urine metabolite profiles obtained before the start of treatment were not sufficient to distinguish which of the subjects would develop mild liver injury, as indicated by a rise in alanine aminotransferase (ALT) to a level more than twice the baseline value (responders). However, profiles obtained shortly after the start of treatment, but prior to ALT elevation, could distinguish responders from nonresponders. Statistical analyses revealed that predictive metabolites included those derived from the toxic metabolite N-acetyl paraquinone imine (NAPQI), but that the inclusion of endogenous metabolites was required for significant prediction. This "early-intervention pharmaco-metabonomics" approach should now be tested in clinical trials of other potentially hepatotoxic drugs.

Metabolomic evaluation of urine and liver was conducted to assess the biochemical changes that occur as a result of alcohol-induced liver injury. Male C57BL/6J mice were fed an isocaloric control-or alcohol-containing liquid diet with 35% of calories from corn oil, 18% protein and 47% carbohydrate/alcohol for up to 36 days ad libitum. Alcohol treatment was initiated at 7 g/kg/day and gradually reached a final dose of 21 g/kg/day. Urine samples were collected at 22, 30 and 36 days and in additional treatment groups, liver and serum samples were harvested at 28 days. Steatohepatitis was induced in the alcohol-fed group since a 5-fold increase in serum alanine aminotransferase activity, a 6-fold increase in liver injury score (necrosis, inflammation and steatosis) and an increase in lipid peroxidation in liver were observed. Liver and urine samples were analyzed by nuclear magnetic resonance spectroscopy and electrospray infusion/Fourier transform ion cyclotron resonance-mass spectrometry. In livers of alcohol-treated mice the following changes were noted. Hypoxia and glycolysis were activated as evidenced by elevated levels of alanine and lactate. Tyrosine, which is required for L-DOPA and dopamine as well as thyroid hormones, was elevated possibly reflecting alterations of basal metabolism by alcohol. A 4-fold increase in the prostacyclin inhibitor 7,10,13,16-docosatetraenoic acid, a molecule important for regulation of platelet formation and blood clotting, may explain why chronic drinking causes serious bleeding problems. Metabolomic analysis of the urine revealed that alcohol treatment leads to decreased excretion of taurine, a metabolite of glutathione, and an increase in lactate, n-acetylglutamine and n-acetylglycine. Changes in the latter two metabolites suggest an inhibition of the kidney enzyme aminoacylase I and may be useful as markers for alcohol consumption.

For both the urinary and serum metabolome, a single day of dietary standardization appears to provide all of the normalization that is achievable within the strict controls implemented in a clinical research setting. After 24 h, the subjects remain in their metabolic space; the remaining intra- and intersubject variations appear to be influenced by variables such as genetics, age, and lifestyle.

Cancer cachexia remains a challenging clinical problem with complex pathophysiology and unreliable diagnostic tools. A blood test to detect this metabolic derangement would aid in early treatment of these patients. A 1 H NMR-based metabolomics approach was used to determine the unique metabolic fingerprint of cachexia and to search for biomarkers in serum samples taken from an established murine model of cancer cachexia. Male CD2F1 mice received a subcutaneous flank injection of C26 adenocarcinoma cells to induce experimental cancer-related cachexia. Two molecular markers of muscle atrophy, upregulation of the E3 ubiquitin ligase Muscle Ring Finger 1 (MuRF1) and aberrant glycosylation of b-dystroglycan (b-DG), were used to confirm muscle wasting in the tumorbearing mice. Serum samples were collected for metabolomic analysis during the development of the cachexia: at baseline, when the tumor was palpable, and when the mice demonstrated cachexia. The unsupervised statistical analysis demonstrated a distinct metabolic profile with the onset of cachexia. The critical metabolic changes associated with cachexia included increased levels of very low density lipoprotein (VLDL) and low density lipoprotein (LDL), with decreased serum glucose levels. Regression analysis demonstrated a very high correlation of the presence of aberrant glycosylation of b-DG with the unique metabolic profile of cachexia. This study demonstrates for the first time that metabolomics has potential as a diagnostic tool in cancer cachexia, and in further elucidating simultaneous metabolic pathway alterations due to this syndrome. In addition, variations in VLDL and LDL deserve more investigation as surrogate serum biomarkers for cancer cachexia.

The diagnosis and management of drug-induced liver injury (DILI) is hindered by the limited utility of traditional clinical chemistries. It has recently been shown that hepatotoxicants can produce compound-specific changes in the peripheral blood (PB) transcriptome in rodents, suggesting that the blood transcriptome might provide new biomarkers of DILI. To investigate in humans, we used DNA microarrays as well as serum metabolomic methods to characterize changes in the transcriptome and metabolome in serial PB samples obtained from six healthy adults treated with a 4-g bolus dose of acetaminophen (APAP) and from three receiving placebo. Treatment did not cause liver injury as assessed by traditional liver chemistries. However, 48 hours after exposure, treated subjects showed marked downregulation of genes involved in oxidative phosphorylation/mitochondrial function that was not observed in the placebos (P < 1.66E-19). The magnitude of down-regulation was positively correlated with the percent of APAP converted to the reactive metabolite N-acetylp-benzoquinone-imide (NAPQI) (r ‫؍‬ 0.739; P ‫؍‬ 0.058). In addition, unbiased analysis of the serum metabolome revealed an increase in serum lactate from 24 to 72 hours postdosing in the treated subjects alone (P < 0.005). Similar PB transcriptome changes were observed in human overdose patients and rats receiving toxic doses. Conclusion: The single 4-g APAP dose produced a transcriptome signature in PB cells characterized by down-regulation of oxidative phosphorylation genes accompanied by increased serum lactate. Similar gene expression changes were observed in rats and several patients after consuming hepatotoxic doses of APAP. The timing of the changes and the correlation with NAPQI production are consistent with mechanisms known to underlie APAP hepatoxicity. These studies support the further exploration of the blood transcriptome for biomarkers of DILI. (HEPATOLOGY 2010;51:227-236.)

We compared the performance of gas chromatography time-of-flight mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) for metabolite biomarker discovery. Metabolite extracts from 109 human serum samples were analyzed on both platforms with a pooled serum sample analyzed after every 9 biological samples for the purpose of quality control (QC). The experimental data derived from the pooled QC samples showed that the GC×GC-MS platform detected about three times as many peaks as the GC-MS platform at a signal-to-noise ratio SNR ≥ 50, and three times the number of metabolites were identified by mass spectrum matching with a spectral similarity score Rsim ≥ 600. Twenty-three metabolites had statistically significant abundance changes between the patient samples and the control samples in the GC-MS data set while 34 metabolites in the GC×GC-MS data set showed statistically significant differences. Among these two groups of metabolite biomarkers, nine metabolites were detected in both the GC-MS and GC×GC-MS data sets with the same direction and similar magnitude of abundance changes between the control and patient sample groups. Manual verification indicated that the difference in the number of the biomarkers discovered using these two platforms was mainly due to the limited resolution of chromatographic peaks by the GC-MS platform, which can result in severe peak overlap making subsequent spectrum deconvolution for metabolite identification and quantification difficult.

To date, no targeted therapies are available to treat triple negative breast cancer (TNBC), while other breast cancer subtypes are responsive to current therapeutic treatment. Metabolomics was conducted to reveal differences in two hormone receptor-negative TNBC cell lines and two hormone receptor-positive Luminal A cell lines. Studies were conducted in the presence and absence of paclitaxel (Taxol®). TNBC cell lines had higher levels of amino acids, branched-chain amino acids, nucleotides and nucleotide sugars, and lower levels of proliferation-related metabolites like choline compared with Luminal A cell lines. In the presence of paclitaxel, each cell line showed unique metabolic responses, with some similarities by type. For example, in the Luminal A cell lines, levels of lactate and creatine decreased while certain choline metabolites and myo-inositol increased with paclitaxel. In the TNBC cell lines levels of glutamine, glutamate, and glutathione increased, whereas lysine, proline and valine decreased in the presence of drug. Profiling secreted inflammatory cytokines in the conditioned media demonstrated a greater response to paclitaxel in the hormone positive Luminal cells compared to a secretion profile that suggested greater drug resistance in the TNBC cells. The most significant differences distinguishing the cell types based on pathway enrichment analyses were related to amino acid, lipid and carbohydrate metabolism pathways, whereas several biological pathways were differentiated between the cell lines following treatment.

Background-Diagnostic delays are common for multiple sclerosis (MS) since diagnosis typically depends on the presentation of nonspecific clinical symptoms together with radiologically-determined central nervous system (CNS) lesions. It is important to reduce diagnostic delays as earlier initiation of disease modifying therapies mitigates long-term disability. Developing a metabolomic blood-based MS biomarker is attractive, but prior efforts have largely focused on specific subsets of metabolite classes or analytical platforms. Thus, there are opportunities to interrogate metabolite profiles using more expansive and comprehensive approaches for developing MS biomarkers and for advancing our understanding of MS pathogenesis.Methods-To identify putative blood-based MS biomarkers, we comprehensively interrogated the metabolite profiles in 12 non-Hispanic white, non-smoking, male MS cases who were drug naïve for 3 months prior to biospecimen collection and 13 non-Hispanic white, non-smoking male controls who were frequency matched to cases by age and BMI. We performed untargeted twodimensional gas chromatography and time-of-flight mass spectrometry (GCxGC-TOFMS) and targeted lipidomic and amino acid analysis on serum. 325 metabolites met quality control and *