1H NMR spectroscopy for the prediction of therapeutic outcome in patients with fulminant hepatic failure

The Potential Role of Metabolomics in Drug-Induced Liver Injury (DILI) Assessment

Drug-induced liver injury (DILI) is one of the most frequent adverse clinical reactions and a relevant cause of morbidity and mortality. Hepatotoxicity is among the major reasons for drug withdrawal during post-market and late development stages, representing a major concern to the pharmaceutical industry. The current biochemical parameters for the detection of DILI are based on enzymes (alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transpeptidase (GGT), alkaline phosphatase (ALP)) and bilirubin serum levels that are not specific of DILI and therefore there is an increasing interest on novel, specific, DILI biomarkers discovery. Metabolomics has emerged as a tool with a great potential for biomarker discovery, especially in disease diagnosis, and assessment of drug toxicity or efficacy. This review summarizes the multistep approaches in DILI biomarker research and discovery based on metabolomics and the principal outcomes from the research performed in this field. For that purpose, we have reviewed the recent scientific literature from PubMed, Web of Science, EMBASE, and PubTator using the terms “metabolomics”, “DILI”, and “humans”. Despite the undoubted contribution of metabolomics to our understanding of the underlying mechanisms of DILI and the identification of promising novel metabolite biomarkers, there are still some inconsistencies and limitations that hinder the translation of these research findings into general clinical practice, probably due to the variability of the methods used as well to the different mechanisms elicited by the DILI causing agent.

Mid-infrared spectroscopy of serum, a promising non-invasive method to assess prognosis in patients with ascites and cirrhosis

Background & aims

Prognostic tests are critical in the management of patients with cirrhosis and ascites. Biological tests or scores perform poorly in that situation. Mid-infrared fibre evanescent wave spectroscopy (MIR-FEWS) which allows for global serum metabolic profiling may provide more relevant information by measuring a wider range of metabolic parameters in serum. Here we present the accuracy of a MIR-FEWS based predictive model for the prognosis of 6 months survival in patients with ascites and cirrhosis.

Methods

Patients with ascites were prospectively included and followed up for 6 months. MIR-FEWS spectra were measured in serum samples. The most informative spectral variables obtained by MIR-FEWS were selected by FADA algorithm and then used to build the MIR model. Accuracy of this model was assessed by ROC curves and 90%/10% Monte Carlo cross-validation. MIR model accuracy for 6 months survival was compared to that of the Child-Pugh and MELD scores.

Results

119 patients were included. The mean age was 57.36±13.70, the MELD score was 16.32±6.26, and the Child-Pugh score was 9.5±1.83. During follow-up, 23 patients died (20%). The MIR model had an AUROC for 6 months mortality of 0.90 (CI95: 0.88–0.91), the MELD 0.77 (CI95: 0.66–0.89) and Child-Pugh 0.76 (CI95: 0.66–0.88). MELD and Child-Pugh AUROCs were significantly lower than that of the MIR model (p = 0.02 and p = 0.02 respectively). Multivariate logistic regression analysis showed that MELD (p<0.05, OR:0.86;CI95:0.76–0.97), Beta blockers (p = 0.036;OR:0.20;CI95:0.04–0.90), and the MIR model (p<0.001; OR:0.50; CI95:0.37–0.66), were significantly associated with 6 months mortality.

Conclusions

In this pilot study MIR-FEWS more accurately assess the 6-month prognosis of patients with ascites and cirrhosis than the MELD or Child-Pugh scores. These promising results, if confirmed by a larger study, suggest that mid infrared spectroscopy could be helpful in the management of these patients.

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.

Metabonomics Research Progress on Liver Diseases

Metabolomics as the new omics technique develops after genomics, transcriptomics, and proteomics and has rapid development at present. Liver diseases are worldwide public health problems. In China, chronic hepatitis B and its secondary diseases are the common liver diseases. They can be diagnosed by the combination of history, virology, liver function, and medical imaging. However, some patients seldom have relevant physical examination, so the diagnosis may be delayed. Many other liver diseases, such as drug-induced liver injury (DILI), alcoholic liver disease (ALD) and nonalcoholic fatty liver disease (NAFLD), and autoimmune liver diseases, still do not have definite diagnostic markers; the diagnosis consists of history, medical imaging, and the relevant score. As a result, the clinical work becomes very complex. So it has broad prospects to explore the specific and sensitive biomarkers of liver diseases with metabolomics. In this paper, there are several summaries which are related to the current research progress and application of metabolomics on biomarkers of liver diseases.

Multivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis

BACKGROUND & AIMS

Predicting survival in decompensated cirrhosis (DC) is important in decision making for liver transplantation and resource allocation. We investigated whether high-resolution metabolic profiling can determine a metabolic phenotype associated with 90-day survival.

METHODS

Two hundred and forty-eight subjects underwent plasma metabotyping by (1)H nuclear magnetic resonance (NMR) spectroscopy and reversed-phase ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC-TOF-MS; DC: 80-derivation set, 101-validation; stable cirrhosis (CLD) 20 and 47 healthy controls (HC)).

RESULTS

(1)H NMR metabotyping accurately discriminated between surviving and non-surviving patients with DC. The NMR plasma profiles of non-survivors were attributed to reduced phosphatidylcholines and lipid resonances, with increased lactate, tyrosine, methionine and phenylalanine signal intensities. This was confirmed on external validation (area under the receiver operating curve [AUROC]=0.96 (95% CI 0.90-1.00, sensitivity 98%, specificity 89%). UPLC-TOF-MS confirmed that lysophosphatidylcholines and phosphatidylcholines [LPC/PC] were downregulated in non-survivors (UPLC-TOF-MS profiles AUROC of 0.94 (95% CI 0.89-0.98, sensitivity 100%, specificity 85% [positive ion detection])). LPC concentrations negatively correlated with circulating markers of cell death (M30 and M65) levels in DC. Histological examination of liver tissue from DC patients confirmed increased hepatocyte cell death compared to controls. Cross liver sampling at time of liver transplantation demonstrated that hepatic endothelial beds are a source of increased circulating total cytokeratin-18 in DC.

CONCLUSION

Plasma metabotyping accurately predicts mortality in DC. LPC and amino acid dysregulation is associated with increased mortality and severity of disease reflecting hepatocyte cell death.

Sequential Serum Metabolomic Profiling after Radiofrequency Ablation of Hepatocellular Carcinoma Reveals Different Response Patterns According to Etiology

Radiofrequency ablation (RFA) is commonly performed as a curative approach in patients with hepatocellular carcinoma (HCC); however, the risk of tumor recurrence is difficult to predict due to a lack of reliable clinical and biological markers, and identification of new biomarkers poses a major challenge for improving prognoses. Metabolomics is a promising technique that may lead to the identification and characterization of new disease fingerprints. The objective of the present study was to explore, preoperatively and at various time points post-RFA, the metabolic profile of serum samples from HCC patients to identify factors associated with treatment response and recurrence. Sequential sera obtained before and after RFA procedures for 120 patients with HCC due to cirrhosis were investigated using nuclear magnetic resonance metabolomics. A multilevel orthogonal projection to latent structure analysis was used to discriminate intraindividual metabolic changes in response to RFA treatment. Recurrence-free survival differed depending on the underlying cause of cirrhosis. The statistical model showed significant differences depending on whether the liver disease had a viral or nonviral etiology before RFA intervention (explained variance of R(2)Y = 0.89 and predictability of Q(2)Y = 0.34). These profiles were also associated with specific and distinct metabolic responses after RFA.

Nuclear magnetic resonance based metabolomics and liver diseases: Recent advances and future clinical applications

Metabolomics is defined as the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification. It is an “omics” technique that is situated downstream of genomics, transcriptomics and proteomics. Metabolomics is recognized as a promising technique in the field of systems biology for the evaluation of global metabolic changes. During the last decade, metabolomics approaches have become widely used in the study of liver diseases for the detection of early biomarkers and altered metabolic pathways. It is a powerful technique to improve our pathophysiological knowledge of various liver diseases. It can be a useful tool to help clinicians in the diagnostic process especially to distinguish malignant and non-malignant liver disease as well as to determine the etiology or severity of the liver disease. It can also assess therapeutic response or predict drug induced liver injury. Nevertheless, the usefulness of metabolomics is often not understood by clinicians, especially the concept of metabolomics profiling or fingerprinting. In the present work, after a concise description of the different techniques and processes used in metabolomics, we will review the main research on this subject by focusing specifically on in vitro proton nuclear magnetic resonance spectroscopy based metabolomics approaches in human studies. We will first consider the clinical point of view enlighten physicians on this new approach and emphasis its future use in clinical “routine”.

An NMR-based metabolomic approach to investigate the effects of supplementation with glutamic acid in piglets challenged with deoxynivalenol

Deoxynivalenol (DON) has various toxicological effects in humans and pigs that result from the ingestion of contaminated cereal products. This study was conducted to investigate the protective effects of dietary supplementation with glutamic acid on piglets challenged with DON. A total of 20 piglets weaned at 28 d of age were randomly assigned to receive 1 of 4 treatments (5 piglets/treatment): 1) basal diet, negative control (NC); 2) basal diet +4 mg/kg DON (DON); 3) basal diet +2% (g/g) glutamic acid (GLU); 4) basal diet +4 mg/kg DON +2% glutamic acid (DG). A 7-d adaptation period was followed by 30 days of treatment. A metabolite analysis using nuclear magnetic resonance spectroscopy (1H-NMR)-based metabolomic technology and the determination of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities for plasma, as well as the activity of Caspase-3 and the proliferation of epithelial cells were conducted. The results showed that contents of low-density lipoprotein, alanine, arginine, acetate, glycoprotein, trimethylamine-N-oxide (TMAO), glycine, lactate, and urea, as well as the glutamate/creatinine ratio were higher but high-density lipoprotein, proline, citrate, choline, unsaturated lipids and fumarate were lower in piglets of DON treatment than that of NC treatment (P<0.05). Compared with DON treatment, dietary supplementation with glutamic acid increased the plasma concentrations of proline, citrate, creatinine, unsaturated lipids, and fumarate, and decreased the concentrations of alanine, glycoprotein, TMAO, glycine, and lactate, as well as the glutamate/creatinine ratio (P<0.05). Addition glutamic acid to DON treatment increased the plasma activities of SOD and GSH-Px and the proliferating cell nuclear antigen (PCNA) labeling indexes for the jejunum and ileum (P<0.05). These novel findings indicate that glutamic acid has the potential to repair the injuries associated with oxidative stress as well as the disturbances of energy and amino acid metabolism induced by DON.

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 (¹H-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 ¹H-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 (Q²Y) and the explained variance was 0.63 (R²Y). 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 ¹H-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.

Low- and high-grade bladder cancer determination via human serum-based metabolomics approach

To address the shortcomings of urine cytology and cystoscopy for probing and grading urinary bladder cancer (BC), we applied (1)H nuclear magnetic resonance (NMR) spectroscopy as a surrogate method for the identification of BC. This study includes 99 serum samples comprising low-grade (LG; n = 36) and high-grade (HG; n = 31) BC as well as healthy controls (HC; n = 32). (1)H NMR-derived serum data were analyzed using orthogonal partial least-squares discriminant analysis (OPLS-DA). OPLS-DA-derived model validity was confirmed using an internal and external cross-validation. Internal validation was performed using the initial samples (n = 99) data set. External validation was performed on a new batch of suspected BC patients (n = 106) through a double-blind study. Receiver operating characteristic (ROC) curve analysis was also performed. OPLS-DA-derived serum metabolomics (six biomarkers, ROC; 0.99) were able to discriminate 95% of BC cases with 96% sensitivity and 94% specificity when compared to HC. Likewise (three biomarkers, ROC; 0.99), 98% of cases of LG were able to differentiate from HG with 97% sensitivity and 99% specificity. External validation reveals comparable results to the internal validation. (1)H NMR-based serum metabolic screening appears to be a promising and less invasive approach for probing and grading BC in contrast to the highly invasive and painful cystoscopic approach for BC detection.

Early prognostic markers for fatal fulminant hepatic failure cases with viral hepatitis: proton nuclear magnetic resonance spectroscopic studies of serum

BACKGROUND

Fulminant hepatic failure is associated with liver metabolic derangements which could have fatal consequences. The aim of the present study is to identify serum markers for early prediction of the outcome.

METHODS

Proton nuclear magnetic resonance spectroscopic studies of serum of fulminant hepatic failure patients due to viral hepatitis with grade II/III of encephalopathy (twenty-four: ten prospective and fourteen retrospective) and twenty-five controls were undertaken. Of the twenty-four patients, fifteen survived with medical management alone while nine had fatal outcome.

RESULTS

The results demonstrated significantly elevated indices of amino acids (alanine, lysine, glutamine, histidine, tyrosine, phenylalanine and 1,2-propanediol) in fatal cases compared to survivors and controls. Principal component analysis showed clear separation of fatal and surviving cases. Liver function parameters were significantly deranged in patients but they failed to provide early significant differences between surviving and fatal cases. Compared to model for end-stage liver disease scores, principal component analysis appear to be better as an early prognostic indicator. Biochemical mapping of pathways suggested interruptions in amino acid metabolism and urea cycle.

CONCLUSIONS

Proton nuclear magnetic resonance studies of serum have the potential of rapidly identifying patients with irreversible fulminant hepatic failure requiring liver transplantation as life saving option.

Metabolomics of urinary tract infection: a new uroscope in town

Urinary tract infection (UTI) is a potentially life-threatening infectious disease. For rapid directed therapy of UTIs, it is essential to determine the causative microorganism. To date, there is no single test that has been proven to reliably, rapidly and accurately identify the etiologic organism in UTI. The molecular methods for diagnosing the cause of UTI and prognostic development of clinically important metabolomic evaluations and their limitations for use in the diagnosis and monitoring of infections are discussed in this review article. The application of the emerging investigative device NMR spectroscopy as a surrogate method for the diagnosis of UTI is also addressed.

Systematic review: acute liver failure - one disease, more than 40 definitions

BACKGROUND

Acute liver failure (ALF) is a clinical syndrome with very high mortality estimates ranging between 60% and 80%.

AIM

To investigate the explicitness and extent of variability in the used ALF definitions in the ALF prognostic literature.

METHODS

All studies that pertain to the prognosis of patients with ALF were electronically searched in MEDLINE (1950-2012) and EMBASE (1950-2012). Identified titles and abstracts were independently screened by three reviewers to determine eligibility for additional review. We included English articles that reported original data from clinical trials or observational studies on ALF patients.

RESULTS

A total of 103 studies were included. Of these studies 87 used 41 different ALF definitions and the remaining 16 studies did not report any explicit ALF definition. Four components underlying ALF definitions accounted for the differences: presence and/or grading of hepatic encephalopathy (HE); the interval between onset of disease and occurrence of HE; presence of coagulopathy and pre-existing liver disease.

CONCLUSIONS

The diversity in acute liver failure definitions hinders comparability and quantitative analysis among studies. There is room for improvement in the reporting of acute liver failure definitions in prognostic studies. The result of this review may be useful as a starting point to create a uniform acute liver failure definition.

Quantitative analysis in magnetic resonance spectroscopy: from metabolic profiling to in vivo biomarkers

Nuclear magnetic resonance spectroscopy (called NMR for ex vivo techniques and MRS for in vivo techniques) has become a useful analytical and diagnostic tool in biomedicine. In the past two decades, an MR-based spectroscopic approach for translational and clinical research has emerged that allows for biochemical characterization of the tissue of interest either ex vivo (NMR-based metabolomics) or in vivo (localized MRS-single voxel or multivoxel-spectroscopic imaging). The greatest advantages of MRS techniques are their ability to detect multiple tissue-specific metabolites in a single experiment, their quantitative nature and translational component (in vitro/ex vivo-discovered metabolic biomarkers can be translated into noninvasive spectroscopic imaging protocols). Disadvantages of MRS include low sensitivity and spectral resolution and, in case of NMR-metabolomics, metabolite degradation and incomplete recovery in processed samples. In vivo MRS has worse spectral resolution than ex vivo high-resolution NMR due to the inherently wider lines of metabolites in vivo and the difficulty of using traditional line-narrowing methods (e.g., sample spinning). It also suffers from poor time-resolution, therefore offering fewer metabolic biomarkers to be followed in vivo. In the present review article, we provide considerations for establishing reliable protocols (both in vivo and ex vivo) for metabolite detection, recovery and quantification from in vivo and ex vivo MR spectra.

Quantitative analysis of urea in human urine and serum by 1H nuclear magnetic resonance

A convenient and fast method for quantifying urea in biofluids is demonstrated using NMR analysis and the solvent water signal as a concentration reference. The urea concentration can be accurately determined with errors less than 3% between 1 mM and 50 mM, and less than 2% above 50 mM in urine and serum. The method is promising for various applications with advantages of simplicity, high accuracy, and fast non-destructive detection. With an ability to measure other metabolites simultaneously, this NMR method is also likely to find applications in metabolic profiling and system biology.

Metabolomic approach by 1H NMR spectroscopy of serum for the assessment of chronic liver failure in patients with cirrhosis

Assessment of chronic liver failure (CLF) in cirrhotic patients is needed to make therapeutic decisions. A biological score is usually performed, using the Model for End-Stage Liver Disease (MELD), to evaluate CLF. Nevertheless, MELD does not take into account metabolic perturbations produced by liver-function impairment. In contrast, metabolomics can investigate many metabolic perturbations within biological systems. The purpose of this study was to assess whether metabolomic profiles of serum, obtained by proton NMR spectroscopy from cirrhotic patients, are affected by the severity of CLF. An orthogonal projection to latent-structure analysis was performed to compare MELD scores and NMR spectra of 124 patients with cirrhosis. The statistical model obtained showed a good explained variance (R(2)X = 0.87 and R(2)Y = 0.86) and a good predictability (Q(2)Y = 0.64). Metabolomic profiles showed significant differences regarding various metabolites depending of severity of CLF: levels of high-density lipoprotein and phosphocholine resonances were significantly higher in patients with mild CLF compared to severe CLF. Other metabolites such as lactate, pyruvate, glucose, amino acids, and creatinine were significantly higher in patients with severe CLF than mild CLF. Our conclusion is that metabolomic NMR analysis provides new insights into metabolic processes related to the severity of hepatic function impairment in cirrhosis.

Human bile as a rich source of biomarkers for hepatopancreatobiliary cancers

Metabolic profiling of biofluids is emerging as an important area with a promising number of applications in clinical medicine, including early diagnosis of numerous diseases that normally remain silent until late in the progress of disease. While blood and urine are more often used to explore biomarkers that distinguish he healthy from disease conditions, human bile is emerging as a rich source of biomarkers specifically for the cancers of the liver (hepatocellular carcinoma), bile ducts (cholangiocarcinoma), gallbladder and pancreas. This is owing to the fact that metabolites linked to the pathways of tumor cell metabolism are rich in bile by virtue of its association or proximity to the pathological source. Recent methodological developments have enabled the identification of a number of bile metabolites that have links with hepatopancreatobiliary diseases. Investigations of human bile are also considered to help the biomarker discovery process in vitro and provide avenues for translational research in detecting and following dynamic variations of biomarkers in clinical settings using noninvasive approaches, such as in vivo magnetic resonance spectroscopy. This article reviews the current status and potential applications of human bile as a source of biomarkers, with emphasis on metabolites, for early detection of cancers associated with the hepatopancreatobiliary system.

The role of magnetic resonance imaging and spectroscopy in hepatic encephalopathy

Hepatic encephalopathy (HE) is a diverse manifestation of acute and chronic liver failure, ranging from cognitive impairment, only detectable on psychometric evaluation through to confusion, coma and death from cerebral oedema. While there is widespread acceptance of its importance, there is little consensus on how best to diagnose and monitor HE. Clinical descriptions, psychometric testing, electroencephalography and magnetic resonance (MR) imaging (and lately, MR spectroscopy) have all been proposed. MR techniques, in contrast to other modalities, have the benefit of objectivity and of being able to interrogate the brain directly with respect to changes in brain size, function and the metabolic disturbances thought to underlie HE, particularly in the context of astrocyte swelling. Modern clinical MRI scanners with multinuclear MR spectroscopy capabilities and brain mapping software can demonstrate structural and functional cellular changes using volumetric MRI, magnetization transfer MRI, diffusion-weighting MRI, functional MRI with oxygenation measurements and in vivo and in vitro (1)H and (31)P MR spectroscopy. This review describes the relative merits of these techniques and provides guidance on the directions for future research and translation into clinical practice.

Combining nuclear magnetic resonance spectroscopy and mass spectrometry in biomarker discovery

Metabolic profiling of biological specimens is emerging as a promising approach for discovering specific biomarkers in the diagnosis of a number of diseases. Amongst many analytical techniques, nuclear magnetic resonance spectroscopy and mass spectrometry are the most information-rich tools that enable high-throughput and global analysis of hundreds of metabolites in a single step. Although only one of the two techniques is utilized in a majority of metabolomics applications, there is a growing interest in combining the data from the two methods to effectively unravel the mammoth complexity of biological samples. In this article, current developments in nuclear magnetic resonance, mass spectrometry and multivariate statistical analysis methods are described. While some general applications that utilize the combination of the two analytical methods are presented briefly, the emphasis is laid on the recent applications of nuclear magnetic resonance and mass spectrometry methods in the studies of hepatopancreatobiliary and gastrointestinal malignancies.

Intestinal ischemia/reperfusion injury: defining the role of the gut microbiome

Intestinal ischemia/reperfusion (I/R) injury initiates a systemic inflammatory response syndrome with a high associated mortality rate. Early diagnosis is essential for reducing surgical mortality, yet current clinical biomarkers are insufficient. Metabonomics is a novel strategy for studying intestinal I/R, which may be used as part of a systems approach for quantitatively analyzing the intestinal microbiome during gut injury. By deconvolving the mammalian–microbial symbiotic relationship systems biology thus has the potential for personalized risk stratification in patients exposed to intestinal I/R. This review describes the mechanism of intestinal I/R and explores the essential role of the intestinal microbiota in the initiation of systemic inflammatory response syndrome. Furthermore, it analyzes current and future approaches for elucidating the mechanism of this condition.

Dynamic metabonomic analysis of BALB/c mice with different outcomes after D-galactosamine/lipopolysaccharide-induced fulminant hepatic failure

Fulminant hepatic failure (FHF) is one of the most challenging gastrointestinal emergencies encountered in clinical practice. Early identification of patients with FHF who need liver transplantation is very important. To construct a prediction model for the early diagnosis and prognosis of FHF, we studied the dynamics of metabolic intermediates and metabolic profiles with a D-galactosamine (GalN)/lipopolysaccharide (LPS)-treated BALB/c mouse model of FHF. Levels of plasma metabolites were quantified with gas chromatography/time-of-flight mass spectrometry, and data were processed with partial least squares discriminant analysis (PLS-DA). Distinct clustering differences were observed 5 and 6 hours after GalN/LPS treatment between mice that survived and those that died, but there were no differences between these groups 4 hours after treatment. Five hours after treatment, plasma levels of some metabolites differed significantly between the survival, dead, and control groups. Ketogenesis and the tricarboxylic acid cycle were inhibited in both the survival and dead groups, but in the dead group, the urea cycle was also inhibited, and glycolysis was elevated. PLS-DA indicated that principal component weighting was greatest for plasma levels of phosphate, beta-hydroxybutyrate, urea, glucose, and lactate. The Y-predicted scatter plot in the partial least squares (PLS) model assigned samples to the survival or dead groups with an a priori cutoff of 0.10 with 100% sensitivity and specificity. Similar results were observed in 11 FHF patients with different outcomes. In conclusion, the PLS model based on metabonomic analysis can be used to predict outcomes well, and plasma levels of phosphate, beta-hydroxybutyrate, urea, glucose, and lactate may constitute a set of markers for the early diagnosis and prognosis of FHF.

Class selection of amino acid metabolites in body fluids using chemical derivatization and their enhanced 13C NMR

We report a chemical derivatization method that selects a class of metabolites from a complex mixture and enhances their detection by 13C NMR. Acetylation of amines directly in aqueous medium with 1,1'-13C(2) acetic anhydride is a simple method that creates a high sensitivity and quantitative label in complex biofluids with minimal sample pretreatment. Detection using either 1D or 2D 13C NMR experiments produces highly resolved spectra with improved sensitivity. Experiments to identify and compare amino acids and related metabolites in normal human urine and serum samples as well as in urine from patients with the inborn errors of metabolism tyrosinemia type II, argininosuccinic aciduria, homocystinuria, and phenylketonuria demonstrate the method. The use of metabolite derivatization and 13C NMR spectroscopy produces data suitable for metabolite profiling analysis of biofluids on a time scale that allows routine use. Extension of this approach to enhance the NMR detection of other classes of metabolites has also been accomplished. The improved detection of low-concentration metabolites shown here creates opportunities to improve the understanding of the biological processes and develop improved disease detection methodologies.

Early detection of graft failure using the blood metabolic profile of a liver recipient

In this case report we describe the blood metabolic profile ("metabolomics") by nuclear magnetic resonance (NMR) spectroscopy and principle component analysis (PCA) from a patient who underwent two consecutive liver transplantations. The first graft from a living-related donor failed and was followed by a second successful transplant from a deceased donor. Using quantitative high-resolution H-NMR spectroscopy, 48 endogenous metabolites were analyzed in whole blood samples at baseline and different time points after each transplantation. From 48 analyzed metabolites, six metabolites were identified by PCA as metabolic markers consistent with a non-functional liver after first transplantation. Importantly, this distinctive metabolic profile was present as early as two hours after first transplant surgery when no other variable or conventional laboratory tests indicated poor graft function. This article reports the potential usefulness of quantitative H-NMR based metabolomics to diagnose early graft dysfunction in liver transplantation.

Early detection of graft failure using the blood metabolic profile of a liver recipient

In this case report we describe the blood metabolic profile ("metabolomics") by nuclear magnetic resonance (NMR) spectroscopy and principle component analysis (PCA) from a patient who underwent two consecutive liver transplantations. The first graft from a living-related donor failed and was followed by a second successful transplant from a deceased donor. Using quantitative high-resolution H-NMR spectroscopy, 48 endogenous metabolites were analyzed in whole blood samples at baseline and different time points after each transplantation. From 48 analyzed metabolites, six metabolites were identified by PCA as metabolic markers consistent with a non-functional liver after first transplantation. Importantly, this distinctive metabolic profile was present as early as two hours after first transplant surgery when no other variable or conventional laboratory tests indicated poor graft function. This article reports the potential usefulness of quantitative H-NMR based metabolomics to diagnose early graft dysfunction in liver transplantation.