Plasma Metabolomic and Lipidomic Profiling of Metabolic Dysfunction-Associated Fatty Liver Disease in Humans Using an Untargeted Multiplatform Approach.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a complex disorder that is implicated in dysregulations in multiple biological pathways, orchestrated by interactions between genetic predisposition, metabolic syndromes and environmental factors. The limited knowledge of its pathogenesis is one of the bottlenecks in the development of prognostic and therapeutic options for MAFLD. Moreover, the extent to which metabolic pathways are altered due to ongoing hepatic steatosis, inflammation and fibrosis and subsequent liver damage remains unclear. To uncover potential MAFLD pathogenesis in humans, we employed an untargeted nuclear magnetic resonance (NMR) spectroscopy- and high-resolution mass spectrometry (HRMS)-based multiplatform approach combined with a computational multiblock omics framework to characterize the plasma metabolomes and lipidomes of obese patients without (n = 19) or with liver biopsy confirmed MAFLD (n = 63). Metabolite features associated with MAFLD were identified using a metabolome-wide association study pipeline that tested for the relationships between feature responses and MAFLD. A metabolic pathway enrichment analysis revealed 16 pathways associated with MAFLD and highlighted pathway changes, including amino acid metabolism, bile acid metabolism, carnitine shuttle, fatty acid metabolism, glycerophospholipid metabolism, arachidonic acid metabolism and steroid metabolism. These results suggested that there were alterations in energy metabolism, specifically amino acid and lipid metabolism, and pointed to the pathways being implicated in alerted liver function, mitochondrial dysfunctions and immune system disorders, which have previously been linked to MAFLD in human and animal studies. Together, this study revealed specific metabolic alterations associated with MAFLD and supported the idea that MAFLD is fundamentally a metabolism-related disorder, thereby providing new perspectives for diagnostic and therapeutic strategies.

Metabolomics with multi-block modelling of mass spectrometry and nuclear magnetic resonance in order to discriminate Haplosclerida marine sponges.

A comprehensive metabolomic strategy, integrating 1H NMR and MS-based multi-block modelling in conjunction with multi-informational molecular networking, has been developed to discriminate sponges of the order Haplosclerida, well known for being taxonomically contentious. An in-house collection of 33 marine sponge samples belonging to three families (Callyspongiidae, Chalinidae, Petrosiidae) and four different genera (Callyspongia, Haliclona, Petrosia, Xestospongia) was investigated using LC-MS/MS, molecular networking, and the annotations processes combined with NMR data and multivariate statistical modelling. The combination of MS and NMR data into supervised multivariate models led to the discrimination of, out of the four genera, three groups based on the presence of metabolites, not necessarily previously described in the Haplosclerida order. Although these metabolomic methods have already been applied separately, it is the first time that a multi-block untargeted approach using MS and NMR has been combined with molecular networking and statistically analyzed, pointing out the pros and cons of this strategy.

Plasma Metabolomics for Discovery of Early Metabolic Markers of Prostate Cancer Based on Ultra-High-Performance Liquid Chromatography-High Resolution Mass Spectrometry.

BACKGROUND: The prevention and early screening of PCa is highly dependent on the identification of new biomarkers. In this study, we investigated whether plasma metabolic profiles from healthy males provide novel early biomarkers associated with future risk of PCa. METHODS: Using the Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) cohort, we identified plasma samples collected from 146 PCa cases up to 13 years prior to diagnosis and 272 matched controls. Plasma metabolic profiles were characterized using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). RESULTS: Orthogonal partial least squares discriminant analysis (OPLS-DA) discriminated PCa cases from controls, with a median area under the receiver operating characteristic curve (AU-ROC) of 0.92 using a 1000-time repeated random sub-sampling validation. Sparse Partial Least Squares Discriminant Analysis (sPLS-DA) identified the top 10 most important metabolites (p < 0.001) discriminating PCa cases from controls. Among them, phosphate, ethyl oleate, eicosadienoic acid were higher in individuals that developed PCa than in the controls during the follow-up. In contrast, 2-hydroxyadenine, sphinganine, L-glutamic acid, serotonin, 7-keto cholesterol, tiglyl carnitine, and sphingosine were lower. CONCLUSION: Our results support the dysregulation of amino acids and sphingolipid metabolism during the development of PCa. After validation in an independent cohort, these signatures may promote the development of new prevention and screening strategies to identify males at future risk of PCa.

Early-onset pneumonia following bag-mask ventilation versus endotracheal intubation during cardiopulmonary resuscitation: A substudy of the CAAM trial.

AIM: Early-onset pneumonia (EOP) is a common in-hospital complication in survivors of out-of-hospital cardiac arrest. In this substudy of the CAAM trial, we aimed to compare whether bag mask ventilation (BMV) compared to endotracheal intubation (ETI) performed during cardiopulmonary resuscitation increases the risk of developing EOP. METHODS: Adult patients from the CAAM trial that survived beyond 12 h of hospitalization were included. Information about in-hospital management and outcome of study subjects was systematically collected. Our primary aim was to compare the incidence of EOP in the BMV and ETI group using a series of bivariate analysis adjusting for one variable at a time and a logistic regression controlled for survival beyond 96 h, age, gender, catecholamine administration, no flow time, and initial shockable rhythm. RESULTS: Of 627 patients from the CAAM trial that survived to hospital admission, 409 patients were hospitalized beyond 12 h and thus included (202 randomized to BMV and 20 7 randomized to ETI). Patients in the BMV group had a significantly longer period of unsecured airway during prehospital cardiopulmonary resuscitation (BMV (median): 33 min; ETI (median): 17 min, p < 0.0001). No significant difference in the development of EOP according to airway management was identified on univariate analysis (BMV: 53%, ETI: 53%, Odds Ratio 1.0 [0.7-1.5], p = 1.0). We found no difference in the development of EOP according to airway management in the series of bivariate analyses or in the multivariable regression analysis either. CONCLUSION: In this substudy of the CAAM trial, development of early-onset pneumonia in out-of-hospital cardiac arrest survivors did not depend on airway management technique during CPR.

A First Step Toward Unraveling the Energy Metabolism in Endurance Horses: Comparison of Plasma Nuclear Magnetic Resonance Metabolomic Profiles Before and After Different Endurance Race Distances.

Endurance racing places high demands on energy metabolism pathways. Metabolomics can be used to investigate biochemical responses to endurance exercise in humans, laboratory animals, and horses. Although endurance horses have previously been assessed in the field (i.e., during races) using broad-window Nuclear Magnetic Resonance metabolomics, these studies included several different race locations, race distances, age classes, and race statuses (finisher or elimination). The present NMR metabolomics study focused on 40 endurance horses racing in three race categories over 90, 120, or 160 km. The three races took place in the same location. Given that energy metabolism is closely related to exercise intensity and duration (and therefore distance covered), the study's objective was to determine whether the metabolic pathways recruited during the race varied as a function of the total ride distance. For each horse, a plasma sample was collected the day before the race, and another was collected at the end of the race. Sixteen, 15, and 9 horses raced over 90, 120, and 160 km, respectively. Proton NMR spectra (500 MHz) were acquired for these 80 plasma samples. After processing, the spectra were divided into bins representing the NMR variables and then classified using orthogonal projection on latent structure models supervised by the sampling time (pre- or post-race) or the distance covered. The models revealed that the post-race metabolomic profiles are associated to the total ride distance groups. By combining biochemical assay results and NMR data in multiblock models, we further showed that enzymatic activities and metabolites are significantly associated to the race category. In the highest race category (160 km), there appears to be a metabolic switch from carbohydrate consumption to lipid consumption in order to maintain glycaemia. Furthermore, signs of protein breakdown were more apparent in the longest race category. The metabolic shift seen in the different racing categories could be related to a mixture of three important factors that are the ride distance, the training status and the inherited endurance capacity of the various horses competing.

Nuclear magnetic resonance-based serum metabolomic analysis reveals different disease evolution profiles between septic shock survivors and non-survivors.

BACKGROUND: Septic shock is the most severe phase of sepsis and is associated with high rates of mortality. However, early stage prediction of septic shock outcomes remains difficult. Metabolomic techniques have emerged as a promising tool for improving prognosis. METHODS: Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) models separating the serum metabolomes of survivors from those of non-survivors were established with samples obtained at the intensive care unit (ICU) admission (H0) and 24 h later (H24). For 51 patients with available H0 and H24 samples, multi-level modeling was performed to provide insight into different metabolic evolutions that occurred between H0 and H24 in the surviving and non-surviving patients. Relative quantification and receiver operational characteristic curves (ROC) were applied to estimate the predictability of key discriminatory metabolites for septic shock mortality. RESULTS: Metabolites that were involved in energy supply and protein breakdown were primarily responsible for differentiating survivors from non-survivors. This was not only seen in the H0 and H24 discriminatory models, but also in the H0-H24 paired models. Reanalysis of extra H0-H24 paired samples in the established multi-level model demonstrated good performance of the model for the classification of samplings. According to the ROC results, nine discriminatory metabolites defined consistently from the unpaired model and the H0-H24 time-trend change (ΔH24-H0) show good prediction of mortality. These results suggest that NMR-based metabolomic analysis is useful for a better overall assessment of septic shock patients. CONCLUSIONS: Dysregulation of the metabolites identified by this study is associated with poor outcomes for septic shock. Evaluation of these compounds during the first 24 h after ICU admission in the septic shock patient may be helpful for estimating the severity of cases and for predicting outcomes. TRIAL REGISTRATION: All human serum samples were collected and stored, provided by the "center of biologic resources for liver disease", in Jean Verdier Hospital, Bondy, France (BB-0033-00027).

Nuclear magnetic resonance metabolic fingerprint of bevacizumab in mutant IDH1 glioma cells.

Background Malignant gliomas are rapidly growing tumours that extensively invade the brain and have bad prognosis. Our study was performed to assess the metabolic effects of bevacizumab on the glioma cells carrying the IDH1 mutation, a mutation, associated with better prognosis and treatment outcome. Bevacizumab is known to inhibit tumour growth by neutralizing the biological activity of vascular endothelial growth factor (VEGF). However, the direct effects of bevacizumab on tumour cells metabolism remain poorly known. Materials and methods The immunoassay and MTT assay were used to assess the concentration of secreted VEGF and cell viability after bevacizumab exposure. Metabolomic studies on cells were performed using high resolution magic angle spinning spectroscopy (HRMAS). Results mIDH1-U87 cells secreted VEGF (13 ng/mL). Regardless, bevacizumab had no cytotoxic effect, even after a 72h exposure and with doses as high as 1 mg/mL. Yet, HRMAS analysis showed a significant effect of bevacizumab (0.1 mg/mL) on the metabolic phenotype of mIDH1-U87 cells with elevation of 2-hydroxyglutarate and changes in glutamine group metabolites (alanine, glutamate, glycine) and lipids (polyunsaturated fatty acids [PUFA], glycerophosphocholine, and phosphocholine). Conclusions In mIDH1-U87 cells, changes in glutamine group metabolites and lipids were identified as metabolic markers of bevacizumab treatment. These data support the possibility of a functional tricarboxylic acid cycle that runs in reductive manner, as a probable mechanism of action of bevacizumab in IDH1 mutated gliomas and propose a new target pathway for effective treatment of malignant gliomas.

Surface enhanced Raman scattering sensor for highly sensitive and selective detection of ochratoxin A.

The trace detection of toxic compounds in complex matrices is a major concern, in particular when it comes to mycotoxins in food. We developed a highly sensitive and specific SERS sensor for the detection of ochratoxin A using a simple rough gold film as a substrate. When adding the analyte, we observed spectral variations related to the interaction of the analyte with the specific aptamer used as a bioreceptor. Using a partial least squares regression method, our sensor is able to detect concentrations down to the picomolar range, which is much lower than the minimum legal concentration allowed in food products. Moreover, we demonstrate the accurate detection of the analyte in a wide concentration range from the picomolar up to the micromolar level. The detection was validated with negative detection tests using deoxynivalenol and bovine serum albumin.

The impact of moderate altitude on exercise metabolism in recreational sportsmen: a nuclear magnetic resonance metabolomic approach.

Although it is known that altitude impairs performance in endurance sports, there is no consensus on the involvement of energy substrates in this process. The objective of the present study was to determine whether the metabolomic pathways used during endurance exercise differ according to whether the effort is performed at sea level or at moderate altitude (at the same exercise intensity, using proton nuclear magnetic resonance, 1H NMR). Twenty subjects performed two 60-min endurance exercise tests at sea level and at 2150 m at identical relative intensity on a cycle ergometer. Blood plasma was obtained from venous blood samples drawn before and after exercise. 1H NMR spectral analysis was then performed on the plasma samples. A multivariate statistical technique was applied to the NMR data. The respective relative intensities of the sea level and altitude endurance tests were essentially the same when expressed as a percentage of the maximal oxygen uptake measured during the corresponding incremental maximal exercise test. Lipid use was similar at sea level and at altitude. In the plasma, levels of glucose, glutamine, alanine, and branched-chain amino acids had decreased after exercise at altitude but not after exercise at sea level. The decrease in plasma glucose and free amino acid levels observed after exercise at altitude indicated that increased involvement of the protein pathway was necessary but not sufficient for the maintenance of glycaemia. Metabolomics is a powerful means of gaining insight into the metabolic changes induced by exercise at altitude.

Nuclear magnetic resonance metabolomics and human liver diseases: The principles and evidence associated with protein and carbohydrate metabolism.

During the last decade, metabolomics has become widely used in the field of human diseases. Numerous studies have demonstrated that this is a powerful technique for improving the understanding, diagnosis and management of various types of liver disease, such as acute and chronic liver diseases, and liver transplantation. Nuclear magnetic resonance (NMR) spectroscopy is one of the two most commonly applied methods for metabolomics. The aim of the present review was to investigate the results from recent key publications focusing on aspects of protein and carbohydrate metabolism. The review includes existing procedures, which are currently used for NMR data acquisition and statistical analysis. In addition, notable results obtained by these studies on protein and carbohydrate metabolism concerning human liver diseases are presented.

Cardiopulmonary resuscitation duration and survival in out-of-hospital cardiac arrest patients.

AIM: Relationship between cardiopulmonary arrest and resuscitation (CPR) durations and survival after out-of-hospital cardiac arrest (OHCA) remain unclear. Our primary aim was to determine the association between survival without neurologic sequelae and cardiac arrest intervals in the setting of witnessed OHCA. METHODS: We analyzed 27,301 non-traumatic, witnessed OHCA patients in France included in the national registry from June 1, 2011 through December 1, 2015. We analyzed cardiac arrest intervals, designated as no-flow (NF; from collapse to start of CPR) and low-flow (LF; from start of CPR to cessation of resuscitation) in relation to 30-day survival without sequelae. We determined the influence of recognized prognostic factors (age, gender, initial rhythm, location of cardiac arrest) on this relation. RESULTS: For the entire cohort, the area delimited by a value of NF greater than 12min (95% confidence interval: 11-13min) and LF greater than 33min (95% confidence interval: 29-45min), yielded a probability of 30-day survival of less than 1%. These sets of values were greatly influenced by initial cardiac arrest rhythm, age, sex and location of cardiac arrest. Extended CPR duration (greater than 40min) in the setting of initial shockable cardiac rhythm is associated with greater than 1% survival with NF less than 18min. The NF interval was highly influential on the LF interval regardless of outcome, whether return of spontaneous circulation (p<0.001) or death (p<0.001). CONCLUSION: NF duration must be considered in determining CPR duration in OHCA patients. The knowledge of (NF, LF) curves as function of age, initial rhythm, location of cardiac arrest or gender may aid in decision-making vis-à-vis the termination of CPR or employment of advanced techniques.

Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis.

Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR), to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid), sham (pricked with an aseptic needle), and unmanipulated (positive control). We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate.

Energetics of endurance exercise in young horses determined by nuclear magnetic resonance metabolomics.

Long-term endurance exercise severely affects metabolism in both human and animal athletes resulting in serious risk of metabolic disorders during or after competition. Young horses (up to 6 years old) can compete in races up to 90 km despite limited scientific knowledge of energetic metabolism responses to long distance exercise in these animals. The hypothesis of this study was that there would be a strong effect of endurance exercise on the metabolomic profiles of young horses and that the energetic metabolism response in young horses would be different from that of more experienced horses. Metabolomic profiling is a powerful method that combines Nuclear Magnetic Resonance (NMR) spectrometry with supervised Orthogonal Projection on Latent Structure (OPLS) statistical analysis. (1)H-NMR spectra were obtained from plasma samples drawn from young horses (before and after competition). The spectra obtained before and after the race from the same horse (92 samples) were compared using OPLS. The statistical parameters showed the robustness of the model (R2Y = 0.947, Q2Y = 0.856 and cros-validated ANOVA p < 0.001). For confirmation of the predictive value of the model, a test set of 104 sample spectra were projected by the model, which provided perfect predictions as the area under the receiving-operator curve was 1. The metabolomic profile determined with the OPLS model showed that glycemia after the race was lower than glycemia before the race, despite the involvement of lipid and protein catabolism. An OPLS model was calculated to compare spectra obtained on plasma taken after the race from 6-year-old horses and from experienced horses (cross-validated ANOVA p < 0.001). The comparison of metabolomic profiles in young horses to those from experienced horses showed that experienced horses maintained their glycemia with higher levels of lactate and a decrease of plasma lipids after the race.

Can we trust untargeted metabolomics? Results of the metabo-ring initiative, a large-scale, multi-instrument inter-laboratory study.

The metabo-ring initiative brought together five nuclear magnetic resonance instruments (NMR) and 11 different mass spectrometers with the objective of assessing the reliability of untargeted metabolomics approaches in obtaining comparable metabolomics profiles. This was estimated by measuring the proportion of common spectral information extracted from the different LCMS and NMR platforms. Biological samples obtained from 2 different conditions were analysed by the partners using their own in-house protocols. Test #1 examined urine samples from adult volunteers either spiked or not spiked with 32 metabolite standards. Test #2 involved a low biological contrast situation comparing the plasma of rats fed a diet either supplemented or not with vitamin D. The spectral information from each instrument was assembled into separate statistical blocks. Correlations between blocks (e.g., instruments) were examined (RV coefficients) along with the structure of the common spectral information (common components and specific weights analysis). In addition, in Test #1, an outlier individual was blindly introduced, and its identification by the various platforms was evaluated. Despite large differences in the number of spectral features produced after post-processing and the heterogeneity of the analytical conditions and the data treatment, the spectral information both within (NMR and LCMS) and across methods (NMR vs. LCMS) was highly convergent (from 64 to 91 % on average). No effect of the LCMS instrumentation (TOF, QTOF, LTQ-Orbitrap) was noted. The outlier individual was best detected and characterised by LCMS instruments. In conclusion, untargeted metabolomics analyses report consistent information within and across instruments of various technologies, even without prior standardisation.

PLS/OPLS models in metabolomics: the impact of permutation of dataset rows on the K-fold cross-validation quality parameters.

Among all the software packages available for discriminant analyses based on projection to latent structures (PLS-DA) or orthogonal projection to latent structures (OPLS-DA), SIMCA (Umetrics, Umeå Sweden) is the more widely used in the metabolomics field. SIMCA proposes many parameters or tests to assess the quality of the computed model (the number of significant components, R2, Q2, pCV-ANOVA, and the permutation test). Significance thresholds for these parameters are strongly application-dependent. Concerning the Q2 parameter, a significance threshold of 0.5 is generally admitted. However, during the last few years, many PLS-DA/OPLS-DA models built using SIMCA have been published with Q2 values lower than 0.5. The purpose of this opinion note is to point out that, in some circumstances frequently encountered in metabolomics, the values of these parameters strongly depend on the individuals that constitute the validation subsets. As a result of the way in which the software selects members of the calibration and validation subsets, a simple permutation of dataset rows can, in several cases, lead to contradictory conclusions about the significance of the models when a K-fold cross-validation is used. We believe that, when Q2 values lower than 0.5 are obtained, SIMCA users should at least verify that the quality parameters are stable towards permutation of the rows in their dataset.

Metabolic impact of anti-angiogenic agents on U87 glioma cells.

BACKGROUND: Glioma cells not only secrete high levels of vascular endothelial growth factor (VEGF) but also express VEGF receptors (VEGFR), supporting the existence of an autocrine loop. The direct impact on glioma cells metabolism of drugs targeting the VEGF pathway, such as Bevacizumab (Bev) or VEGFR Tyrosine Kinase Inhibitor (TKI), is poorly known. MATERIAL AND METHODS: U87 cells were treated with Bev or SU1498, a selective VEGFR2 TKI. VEGFR expression was checked with FACS flow cytometry and Quantitative Real-Time PCR. VEGF secretion into the medium was assessed with an ELISA kit. Metabolomic studies on cells were performed using High Resolution Magic Angle Spinning Spectroscopy (HR-MAS). RESULTS: U87 cells secreted VEGF and expressed low level of VEGFR2, but no detectable VEGFR1. Exposure to SU1498, but not Bev, significantly impacted cell proliferation and apoptosis. Metabolomic studies with HR MAS showed that Bev had no significant effect on cell metabolism, while SU1498 induced a marked increase in lipids and a decrease in glycerophosphocholine. Accordingly, accumulation of lipid droplets was seen in the cytoplasm of SU1498-treated U87 cells. CONCLUSION: Although both drugs target the VEGF pathway, only SU1498 showed a clear impact on cell proliferation, cell morphology and metabolism. Bevacizumab is thus less likely to modify glioma cells phenotype due to a direct therapeutic pressure on the VEGF autocrine loop. In patients treated with VEGFR TKI, monitoring lipids with magnetic resonance spectroscopic (MRS) might be a valuable marker to assess drug cytotoxicity.

Protein catabolism and high lipid metabolism associated with long-distance exercise are revealed by plasma NMR metabolomics in endurance horses.

During long distance endurance races, horses undergo high physiological and metabolic stresses. The adaptation processes involve the modulation of the energetic pathways in order to meet the energy demand. The aims were to evaluate the effects of long endurance exercise on the plasma metabolomic profiles and to investigate the relationships with the individual horse performances. The metabolomic profiles of the horses were analyzed using the non-dedicated methodology, NMR spectroscopy and statistical multivariate analysis. The advantage of this method is to investigate several metabolomic pathways at the same time in a single sample. The plasmas were obtained before exercise (BE) and post exercise (PE) from 69 horses competing in three endurance races at national level (130-160 km). Biochemical assays were also performed on the samples taken at PE. The proton NMR spectra were compared using the supervised orthogonal projection on latent structure method according to several factors. Among these factors, the race location was not significant whereas the effect of the race exercise (sample BE vs PE of same horse) was highly discriminating. This result was confirmed by the projection of unpaired samples (only BE or PE sample of different horses). The metabolomic profiles proved that protein, energetic and lipid metabolisms as well as glycoproteins content are highly affected by the long endurance exercise. The BE samples from finisher horses could be discriminated according to the racing speed based on their metabolomic lipid content. The PE samples could be discriminated according to the horse ranking position at the end of the race with lactate as unique correlated metabolite. As a conclusion, the metabolomic profiles of plasmas taken before and after the race provided a better understanding of the high energy demand and protein catabolism pathway that could expose the horses to metabolic disorders.

Serum 1H-NMR metabolomic fingerprints of acute-on-chronic liver failure in intensive care unit patients with alcoholic cirrhosis.

INTRODUCTION: Acute-on-chronic liver failure is characterized by acute deterioration of liver function in patients with compensated or decompensated, but stable, cirrhosis. However, there is no accurate definition of acute-on-chronic liver failure and physicians often use this term to describe different clinical entities. Metabolomics investigates metabolic changes in biological systems and identifies the biomarkers or metabolic profiles. Our study assessed the metabolomic profile of serum using proton nuclear magnetic resonance ((1)H-NMR) spectroscopy to identify metabolic changes related to acute-on-chronic liver failure. PATIENTS: Ninety-three patients with compensated or decompensated cirrhosis (CLF group) but stable liver function and 30 patients with cirrhosis and hospitalized for the management of an acute event who may be responsible of acute-on-chronic liver failure (ACLF group), were fully analyzed. Blood samples were drawn at admission, and sera were separated and stored at -80°C until (1)H-NMR spectral analysis. Using orthogonal projection to latent-structure discriminant analyses, various metabolites contribute to the complete separation between these both groups. RESULTS: The predictability of the model was 0.73 (Q(2) Y) and the explained variance was 0.63 (R(2) Y). The main metabolites that had increased signals related to acute-on-chronic liver failure were lactate, pyruvate, ketone bodies, glutamine, phenylalanine, tyrosine, and creatinine. High-density lipids were lower in the ALCF group than in CLF group. CONCLUSION: A serum metabolite fingerprint for acute-on-chronic liver failure, obtained with (1)H-NMR, was identified. Metabolomic profiling may aid clinical evaluation of patients with cirrhosis admitted into intensive care units with acute-on-chronic liver failure, and provide new insights into the metabolic processes involved in acute impairment of hepatic function.

Identification of serum proton NMR metabolomic fingerprints associated with hepatocellular carcinoma in patients with alcoholic cirrhosis.

PURPOSE: Metabolomics depicts metabolic changes in biologic systems using a multiparametric analysis technique. This study assessed the metabolomic profiles of serum, obtained by proton nuclear magnetic resonance (NMR) spectroscopy, from cirrhotic patients with and without hepatocellular carcinoma (HCC). EXPERIMENTAL DESIGN: The study included 154 consecutive patients with compensated biopsy-proven alcoholic cirrhosis. Among these, 93 had cirrhosis without HCC, 28 had biopsy-proven HCC within the Milan criteria and were eligible for curative treatment (small HCC), and 33 had HCC outside the Milan criteria (large HCC). Proton spectra were acquired at 500 MHz. An orthogonal partial latent structure [orthogonal projection to latent structure (OPLS)] analysis model was built to discriminate large HCC spectra from cirrhotic spectra. Small HCC spectra were secondarily projected using previously built OPLS discriminant components. RESULTS: The OPLS model showed discrimination between cirrhotic and large HCC spectra. Metabolites that significantly increased with large HCC were glutamate, acetate, and N-acetyl glycoproteins, whereas metabolites that correlated with cirrhosis were lipids and glutamine. Projection of small HCC samples into the OPLS model showed a heterogeneous distribution between large HCC and cirrhotic samples. Small HCC patients with metabolomic profile similar to those of large HCC group had higher incidences of recurrence or death during follow-up. CONCLUSIONS: Serum NMR-based metabolomics identified metabolic fingerprints that could be specific to large HCC in cirrhotic livers. From a metabolomic standpoint, some patients with small HCC, who are eligible for curative treatments, seem to behave as patients with advanced cancerous disease. It would be useful to further prospectively investigate these patients to define a subgroup with a worse prognosis.

NMR metabolomics for assessment of exercise effects with mouse biofluids.

Exercise modulates the metabolome in urine or blood as demonstrated previously for humans and animal models. Using nuclear magnetic resonance (NMR) metabolomics, the present study compares the metabolic consequences of an exhaustive exercise at peak velocity (Vp) and at critical velocity (Vc) on mice. Since small-volume samples (blood and urine) were collected, dilution was necessary to acquire NMR spectra. Consequently, specific processing methods were applied before statistical analysis. According to the type of exercise (control group, Vp group and Vc group), 26 male mice were divided into three groups. Mice were sacrificed 2 h after the end of exercise, and urine and blood samples were drawn from each mouse. Proton NMR spectra were acquired with urine and deproteinized blood. The NMR data were aligned with the icoshift method and normalised using the probabilistic quotient method. Finally, data were analysed with the orthogonal projection of latent-structure analysis. The spectra obtained with deproteinized blood can neither discriminate the control mice from exercised mice nor discriminate according to the duration of the exercise. With urine samples, a significant statistical model can be estimated when comparing the control mice to both groups, Vc and Vp. The best model is obtained according to the exercise duration with all mice. Taking into account the spectral regions having the highest correlations, the discriminant metabolites are allantoin, inosine and branched-chain amino acids. In conclusion, metabolomic profiles assessed with NMR are highly dependent on the exercise. These results show that urine samples are more informative than blood samples and that the duration of the exercise is a more important parameter to influence the metabolomic status than the exercise velocity.