Serum metabolomics reveals γ-glutamyl dipeptides as biomarkers for discrimination among different forms of liver disease

Recent developments in capillary and microchip electroseparations of peptides (2011-2013)

The review presents a comprehensive survey of recent developments and applications of capillary and microchip electroseparation methods (zone electrophoresis, ITP, IEF, affinity electrophoresis, EKC, and electrochromatography) for analysis, isolation, purification, and physicochemical and biochemical characterization of peptides. Advances in the investigation of electromigration properties of peptides, in the methodology of their analysis, including sample preseparation, preconcentration and derivatization, adsorption suppression and EOF control, as well as in detection of peptides, are presented. New developments in particular CE and CEC modes are reported and several types of their applications to peptide analysis are described: conventional qualitative and quantitative analysis, determination in complex (bio)matrices, monitoring of chemical and enzymatical reactions and physical changes, amino acid, sequence and chiral analysis, and peptide mapping of proteins. Some micropreparative peptide separations are shown and capabilities of CE and CEC techniques to provide relevant physicochemical characteristics of peptides are demonstrated.

Dynamics of serum metabolites in patients with chronic hepatitis C receiving pegylated interferon plus ribavirin: a metabolomics analysis

OBJECTIVES

Serum samples from patients with chronic hepatitis C were subjected to metabolomics analysis to clarify the pretreatment characteristics of their metabolites and also changes in specific metabolites resulting from antiviral therapy with pegylated interferon plus ribavirin (PegIFN/RBV).

MATERIALS/METHODS

The serum levels of low-molecular-weight metabolites in the twenty patients before and 24weeks after completion of PegIFN/RBV therapy were analyzed using capillary electrophoresis and liquid chromatography-mass spectrometry.

RESULTS

Ten patients showed a non-virological response (NVR) and 10 achieved a sustained virological response (SVR) with eradication of viremia. The pretreatment levels of tryptophan were significantly higher in the patients of SVR than in those of NVR (p=0.010). The area under the curve (AUC) value of tryptophan calculated from the receiver operating characteristic (ROC) curve for discriminating SVR from NVR was 0.84 (95% confidential interval, 0.66-1.02, p=0.010). The ROC curve of multiple logistic regression model incorporating the pretreatment levels of tryptophan and γ-glutamate-arginine showed that the AUC value was highly significant (AUC=0.92, 95% confidential interval, 0.79-1.05, p=0.002). Twenty four weeks after completion of treatment, the levels of γ-glutamyl dipeptides, glutamic acid, 5-oxoproline, glucosamine and methionine sulfoxide were decreased, whereas those of 5-methoxy-3-indoleacetate, glutamine, kynurenine and lysine were increased significantly (p<0.05) in both the NVR and SVR patients.

CONCLUSIONS

The pretreatment serum levels of certain metabolites including tryptophan are associated with the response to PegIFN/RBV therapy. PegIFN/RBV therapy can ameliorate the oxidative stress responsible for glutathione metabolism.

Review of mass spectrometry-based metabolomics in cancer research

Metabolomics, the systematic investigation of all metabolites present within a biologic system, is used in biomarker development for many human diseases, including cancer. In this review, we investigate the current role of mass spectrometry-based metabolomics in cancer research. A literature review was carried out within the databases PubMed, Embase, and Web of Knowledge. We included 106 studies reporting on 21 different types of cancer in 7 different sample types. Metabolomics in cancer research is most often used for case-control comparisons. Secondary applications include translational areas, such as patient prognosis, therapy control and tumor classification, or grading. Metabolomics is at a developmental stage with respect to epidemiology, with the majority of studies including less than 100 patients. Standardization is required especially concerning sample preparation and data analysis. In the second part of this review, we reconstructed a metabolic network of patients with cancer by quantitatively extracting all reports of altered metabolites: Alterations in energy metabolism, membrane, and fatty acid synthesis emerged, with tryptophan levels changed most frequently in various cancers. Metabolomics has the potential to evolve into a standard tool for future applications in epidemiology and translational cancer research, but further, large-scale studies including prospective validation are needed.

Altered metabolites in the plasma of autism spectrum disorder: a capillary electrophoresis time-of-flight mass spectroscopy study

Clinical diagnosis and severity of autism spectrum disorders (ASD) are determined by trained clinicians based on clinical evaluations of observed behaviors. As such, this approach is inevitably dependent on the expertise and subjective assessment of those administering the clinical evaluations. There is a need to identify objective biological markers associated with diagnosis or clinical severity of the disorder. To identify novel candidate metabolites as potential biomarkers for ASD, the current study applied capillary electrophoresis time-of-flight mass spectroscopy (CE-TOFMS) for high-throughput profiling of metabolite levels in the plasma of 25 psychotropic-naïve adult males with high-functioning ASD and 28 age-matched typically-developed control subjects. Ten ASD participants and ten age-matched controls were assigned in the first exploration set, while 15 ASD participants and 18 controls were included in the second replication set. By CE-TOFMS analysis, a total of 143 metabolites were detected in the plasma of the first set. Of these, 17 metabolites showed significantly different relative areas between the ASD participants and the controls (p<0.05). Of the 17 metabolites, we consistently found that the ASD participants had significantly high plasma levels of arginine (p = 0.024) and taurine (p = 0.018), and significantly low levels of 5-oxoproline (p<0.001) and lactic acid (p = 0.031) compared with the controls in the second sample set. Further confirmatory analysis using quantification of absolute metabolite concentrations supported the robustness of high arginine (p = 0.001) and low lactic acid (p = 0.003) in the combined sample (n = 53). The present study identified deviated plasma metabolite levels associated with oxidative stress and mitochondrial dysfunction in individuals with ASD.

Postgenomics diagnostics: metabolomics approaches to human blood profiling

We live in exciting times with the prospects of postgenomics diagnostics. Metabolomics is a novel "omics" data-intensive science that is accelerating the development of postgenomics diagnostics, particularly with use of accessible peripheral tissue compartments. Metabolomics involves the study of a comprehensive set of low molecular weight substances (metabolites) present in biological systems. The metabolite profiles represent the molecular phenotype of biological systems and reflect the information encoded at the genomic level and implemented at the transcriptomic and proteomic levels. Analysis of the human blood metabolite profile is a universal and highly promising tool for clinical postgenomics applications because it reflects both the endogenous and exogenous (environmental) factors influencing an individual organism. This article presents a critical synthesis and original analysis of both the technical implementation of metabolic profiling of blood and statistical analysis of metabolite profiles for effective disease diagnostics and risk assessment in the present postgenomics era.

Pseudotargeted metabolomics method and its application in serum biomarker discovery for hepatocellular carcinoma based on ultra high-performance liquid chromatography/triple quadrupole mass spectrometry

Untargeted analysis performed using full-scan mass spectrometry (MS) coupled with liquid chromatography (LC) is commonly used in metabolomics. Although they are commonly employed, full-scan MS methods such as quadrupole-time-of-flight (Q-TOF) MS have been restricted by various factors including their limited linear range and complicated data processing. LC coupled with triple quadrupole (QQQ) MS operated in the multiple reaction monitoring (MRM) mode is the gold standard for metabolite quantification; however, only known metabolites are generally quantified, limiting its applications in metabolomic analysis. In this study, a pseudotargeted approach was proposed to perform serum metabolomic analysis using an ultra high-performance liquid chromatography (UHPLC)/QQQ MS system operated in the MRM mode, for which the MRM ion pairs were acquired from the serum samples through untargeted tandem MS using UHPLC/Q-TOF MS. The UHPLC/QQQ MRM MS-based pseudotargeted method displayed better repeatability and wider linear range than the traditional UHPLC/Q-TOF MS-based untargeted metabolomics method, and no complicated peak alignment was required. The developed method was applied to discover serum biomarkers for patients with hepatocellular carcinoma (HCC). Patients with HCC had decreased lysophosphatidylcholine, increased long-chain and decreased medium-chain acylcarnitines, and increased aromatic and decreased branched-chain amino acid levels compared to healthy controls. The novelty of this work is that it provides an approach to acquire MRM ion pairs from real samples, is not limited to metabolite standards, and it provides a foundation to achieve pseudotargeted metabolomic analysis on the widely used LC/QQQ MS platform.

Autophagy protects kidney proximal tubule epithelial cells from mitochondrial metabolic stress

Chronic metabolic stress is related to diseases, whereas autophagy supplies nutrients by recycling the degradative products. Cyclosporin A (CsA), a frequently used immunosuppressant, induces metabolic stress via effects on mitochondrial respiration, and thereby, its chronic usage is often limited. Here we show that autophagy plays a protective role against CsA-induced metabolic stress in kidney proximal tubule epithelial cells. Autophagy deficiency leads to decreased mitochondrial membrane potential, which coincides with metabolic abnormalities as characterized by decreased levels of amino acids, increased tricarboxylic acid (TCA) ratio (the levels of intermediates of the latter part of the TCA cycle, over levels of intermediates in the earlier part), and decreased products of oxidative phosphorylation (ATP). In addition to the altered profile of amino acids, CsA decreased the hyperpolarization of mitochondria with the disturbance of mitochondrial energy metabolism in autophagy-competent cells, i.e., increased TCA ratio and worsening of the NAD(+)/NADH ratio, coupled with decreased energy status, which suggests that adaptation to CsA employs autophagy to supply electron donors from amino acids via intermediates of the latter part of the TCA cycle. The TCA ratio of autophagy-deficient cells was further worsened with decreased levels of amino acids in response to CsA, and, as a result, the deficiency of autophagy failed to adapt to the CsA-induced metabolic stress. Deterioration of the TCA ratio further worsened energy status. The CsA-induced metabolic stress also activated regulatory genes of metabolism and apoptotic signals, whose expressions were accelerated in autophagy-deficient cells. These data provide new perspectives on autophagy in conditions of chronic metabolic stress in disease.

Effect of bisphenol A on rat metabolic profiling studied by using capillary electrophoresis time-of-flight mass spectrometry

Bisphenol A (BPA), a chemical widely used in the manufacture of polycarbonate plastics, has raised considerable concern in recent decades because of its hormone-like properties. Whether BPA exposure is a health risk remains controversial in many countries. A metabolomics study based on capillary electrophoresis time-of-flight mass spectrometry (CE-TOF/MS) was performed to study the urine metabolic profiles of Sprague-Dawley rats fed with four dose levels of BPA (0, 1, 10, and 100 μg/kg body weight) for 45 days. Multivariate pattern recognition directly reflected the metabolic perturbations caused by BPA. On the basis of univariate analysis, 42 metabolites including amino acids, polyamines, nucleosides, organic acids, carbohydrates, pterins, polyphenols, and sugar phosphates were found as the most significantly differential metabolites. The marked perturbations were related with valine, leucine and isoleucine biosynthesis, D-glutamine and D-glutamate metabolism, etc. Significant alterations of neurotransmitters (glutamate, gamma-aminobutyric acid, and noradrenaline) and neurotransmitter-related metabolites (tyrosine, histamine, valine, and taurine) suggested that the toxic effects of small-dose BPA (below 50 mg/kg/day) may contribute to its interactions with the neuromediating system. Our study demonstrated that metabolomics may offer more specific insights into the molecular changes underlying the physiological effects of BPA.

Metabolic characterization of hepatocellular carcinoma using nontargeted tissue metabolomics

Hepatocellular carcinoma has a poor prognosis due to its rapid development and early metastasis. In this report, we characterized the metabolic features of hepatocellular carcinoma using a nontargeted metabolic profiling strategy based on liquid chromatography-mass spectrometry. Fifty pairs of liver cancer samples and matched normal tissues were collected from patients having hepatocellular carcinoma, including tumor tissues, adjacent noncancerous tissues, and distal noncancerous tissues, and 105 metabolites were filtered and identified from the tissue metabolome. The principal metabolic alternations in HCC tumors included elevated glycolysis, gluconeogenesis, and β-oxidation with reduced tricarboxylic acid cycle and Δ-12 desaturase. Furthermore, increased levels of glutathione and other antioxidative molecules, together with decreased levels of inflammatory-related polyunsaturated fatty acids and phospholipase A2, were observed. Differential metabolite levels in tissues were tested in 298 serum specimens from patients with chronic hepatitis, cirrhosis, and hepatocellular carcinoma. Betaine and propionylcarnitine were confirmed to confer good diagnostic potential to distinguish hepatocellular carcinoma from chronic hepatitis and cirrhosis. External validation of cirrhosis and hepatocellular carcinoma serum specimens further showed that this combination biomarker is useful for diagnosis of hepatocellular carcinoma with a supplementary role to α-fetoprotein.

Human liver tissue metabolic profiling research on hepatitis B virus-related hepatocellular carcinoma

AIM: To select characteristic endogenous metabolites in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients and to identify their molecular mechanism and potential clinical value.

METHODS: An ultra performance liquid chromatography and linear trap quadrupole-Orbitrap XL-mass spectrometry platform was used to analyze endogenous metabolites in the homogenate of central tumor tissue, adjacent tissue and distant tissue obtained from 10 HBV-related HCC patients. After pretreatment with Mzmine software, including peak detection, alignment and normalization, the acquired data were treated with Simca-P+software to establish multivariate statistical analysis based on a pattern recognition technique and characteristic metabolites highly correlated with changing trends in metabolic profiling were selected and further identified.

RESULTS: Based on data acquired using Mzmine software, a principal component analysis model (R2X = 66.9%, Q2 = 21.7%) with 6 principal components and an orthogonal partial least squares discriminant analysis model (R2X = 76.5%, R2Y = 93.7%, Q2 = 68.7%) with 2 predicted principal components and 5 orthogonal principal components were established in the three tissue groups. Forty-nine ions were selected, 33 ions passed the 2 related samples nonparametric test (P < 0.05) and 14 of these were further identified as characteristic metabolites that showed significant differences in levels between the central tumor tissue group and distant tumor tissue group, including 9 metabolites (L-phenylalanine, glycerophosphocholine, lysophosphatidylcholines, lysophosphatidylethanolamines and chenodeoxycholic acid glycine conjugate) which had been reported as serum metabolite biomarkers for HCC diagnosis in previous research, and 5 metabolites (beta-sitosterol, quinaldic acid, arachidyl carnitine, tetradecanal, and oleamide) which had not been reported before.

CONCLUSION: Characteristic metabolites and metabolic pathways highly related to HCC pathogenesis and progression are identified through metabolic profiling analysis of HCC tissue homogenates.

Metabolomics discloses potential biomarkers for the noninvasive diagnosis of idiopathic portal hypertension

OBJECTIVES

Idiopathic portal hypertension (IPH) is a rare cause of portal hypertension that lacks a specific diagnostic test. Requiring ruling-out other causes of portal hypertension it is frequently misdiagnosed. This study evaluates whether using high-throughput techniques there is a metabolomic profile allowing a noninvasive diagnosis of IPH.

METHODS

Thirty-three IPH patients were included. Matched patients with cirrhosis (CH) and healthy volunteers (HV) were included as controls. Metabolomic analysis of plasma samples was performed using UPLC-time-of-flight-mass spectrometry. We computed Student's P-values, corrected by multiple comparison and VIP score (Variable Importance in the Projection). The metabolites were selected with an adjusted Benjamini Hochberg P value <0.05. We use markers with a greater VIP score, to build partial least squares projection to latent structures regression with discriminant analysis (PLS-DA) representative models to discriminate IPH from CH and from HV. The performance of the PLS-DA model was evaluated using R(2) and Q(2) parameter. An additional internal cross-validation was done.

RESULTS

PLS-DA analysis showed a clear separation of IPH from CH with a model involving 28 metabolites (Q(2)=0.67, area under the curve (AUC)=0.99) and a clear separation of IPH from healthy subjects with a model including 31 metabolites (Q(2)=0.75, AUC=0.98). After cross-validation, both models showed high rates of sensitivity (94.8 and 97.5), specificity (89.1 and 89.7), and AUC (0.98 and 0.98), reinforcing the strength of our findings.

CONCLUSIONS

A metabolomic profile clearly differentiating patients with IPH from CH and healthy subjects has been identified using subsets of 28 and 31 metabolites, respectively. Therefore, metabolomic analysis appears to be a valuable tool for the noninvasive diagnosis of IPH.

Power of metabolomics in diagnosis and biomarker discovery of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the commonest primary hepatic malignancy and the third most common cause of cancer-related death worldwide. Incidence remains highest in the developing world and is steadily increasing across the developed world. Current diagnostic modalities, of ultrasound and α-fetoprotein, are expensive and lack sensitivity in tumor detection. Because of its asymptomatic nature, HCC is usually diagnosed at late and advanced stages, for which there are no effective therapies. Thus, biomarkers for early detection and molecular targets for treating HCC are urgently needed. Emerging high-throughput metabolomics technologies have been widely applied, aiming at the discovery of candidate biomarkers for cancer staging, prediction of recurrence and prognosis, and treatment selection. Metabolic profiles, which are affected by many physiological and pathological processes, may provide further insight into the metabolic consequences of this severe liver disease. Small-molecule metabolites have an important role in biological systems and represent attractive candidates to understand HCC phenotypes. The power of metabolomics allows an unparalleled opportunity to query the molecular mechanisms of HCC. This technique-driven review aims to demystify the metabolomics pathway, while also illustrating the potential of this technique, with recent examples of its application in HCC.

Method development and validation for rat serum fingerprinting with CE-MS: application to ventilator-induced-lung-injury study

In the search for a noninvasive and reliable rapid screening method to detect biomarkers, a metabolomics fingerprinting approach was developed and applied to rat serum samples using capillary electrophoresis coupled to an electrospray ionization-time of flight-mass spectrometer (CE-TOF-MS). An ultrafiltration method was used for sample pretreatment. To evaluate performance the method was validated with carnitine, choline, ornithine, alanine, acetylcarnitine, betaine, and citrulline, covering the entire electropherogram of pool of rat serum. The linearity for all metabolites was >0.99, with good recovery and precision. Approximately 34 compounds were also confirmed in the pool of rat serum. The method was successfully applied to real serum samples from rats with ventilator-induced lung injury, an experimental rat model for acute lung injury (ALI), giving a total of 1163 molecular features. By use of univariate and multivariate statistics 18 significant compounds were found, of which five were confirmed. The involvement of arginase and nitric oxide synthase has been proved for other lung diseases, meaning the increase of asymmetric dimethyl arginine (ADMA) and ornithine and the decrease of arginine found were in accordance with published literature. Ultimately this fingerprinting approach offers the possibility of identifying biomarkers that could be regularly screened for as part of routine disease control. In this way it might be possible to prevent the development of ALI in patients in critical care units.

Accuracy of prediction scores and novel biomarkers for predicting nonalcoholic fatty liver disease in obese children

BACKGROUND

Accurate prediction scores for liver steatosis are demanded to enable clinicians to noninvasively screen for nonalcoholic fatty liver disease (NAFLD). Several prediction scores have been developed, however external validation is lacking.

OBJECTIVE

The aim was to determine the diagnostic accuracy of four existing prediction scores in severely obese children, to develop a new prediction score using novel biomarkers and to compare these results to the performance of ultrasonography.

DESIGN AND RESULTS

Liver steatosis was measured using proton magnetic resonance spectroscopy in 119 severely obese children (mean age 14.3 ± 2.1 years, BMI z-score 3.35 ± 0.35). Prevalence of steatosis was 47%. The four existing predictions scores ("NAFLD liver fat score," "fatty liver index," "hepatic steatosis index," and the pediatric prediction score) had only moderate diagnostic accuracy in this cohort (positive predictive value (PPV): 70, 61, 61, 69% and negative predictive value (NPV) 77, 69, 68, 75%, respectively). A new prediction score was built using anthropometry, routine biochemistry and novel biomarkers (leptin, adiponectin, TNF-alpha, IL-6, CK-18, FGF-21, and adiponutrin polymorphisms). The final model included ALT, HOMA, sex, and leptin. This equation (PPV 79% and NPV 80%) did not perform substantially better than the four other equations and did not outperform ultrasonography for excluding NAFLD (NPV 82%).

CONCLUSION

The conclusion is in severely obese children and adolescents existing prediction scores and the tested novel biomarkers have insufficient diagnostic accuracy for diagnosing or excluding NAFLD.

Metabolome analysis of erythrocytes from patients with chronic hepatitis C reveals the etiology of ribavirin-induced hemolysis

Ribavirin is one of the major agents used in combination therapy with interferon for chronic hepatitis C, but is often associated with hemolytic anemia as a serious adverse event. Employing metabolome analysis, we demonstrated that the concentrations of intermediate metabolites produced by glycolysis and the pentose phosphate cycle in patients' erythrocytes were significantly decreased after administration of ribavirin. Our findings suggest that hemolysis associated with ribavirin is triggered by an energy crisis and consequent oxidative stress, thus having implications for the prevention of such hemolysis.

CE-MS for metabolomics: developments and applications in the period 2010-2012

CE-MS has emerged as a powerful technique for the profiling of (highly) polar and charged metabolites in biological samples. This review provides an update of the most recent developments in CE-MS for metabolomics covering the scientific literature from July 2010 to June 2012. The present paper is an update of two previous review papers covering the years 2000-2010 (Electrophoresis 2009, 30, 276-291; Electrophoresis 2011, 32, 52-65). Emerging technological developments used in CE-MS for metabolomics are discussed, such as the use of novel interfacing techniques for coupling CE to MS. Representative examples illustrate the applicability of CE-MS in the fields of biomedical, clinical, microbial, plant, environmental and food metabolomics. Concerning targeted and non-targeted approaches, a comprehensive overview of recent CE-MS-based metabolomics studies is given in a table. Information on sample type and pretreatment, capillary coatings and MS detection mode is provided. Finally, general conclusions and perspectives are provided.

Serum metabolic profiling study of hepatocellular carcinoma infected with hepatitis B or hepatitis C virus by using liquid chromatography-mass spectrometry

The objective of the present study was to explore the common and specific metabolic alterations of hepatocellular carcinoma (HCC) infected with hepatitis B virus (HBV) or hepatitis C virus (HCV). Serum profiling data revealed that the two HCC groups shared a mainly similar metabolic profile, providing a basis for investigating their common tumor pathogenesis mechanism and early diagnosis biomarkers. Arachidonic acid as a pro-inflammatory precursor increased significantly in the HCC group compared to the cirrhosis and healthy control. And the lysophosphatidylcholines (lysoPCs) with polyunsaturated fatty acid acyl chain with potent anti-inflammatory activity significantly decreased in the HCC and cirrhosis groups compared to those in the healthy control group, which may partly contribute to maintaining chronic inflammation and benefit the initiation and progression of the malignant hepatic tumor. The decreased ratios of polyunsaturated lysoPCs to saturated lysoPCs in HCC groups compared to chronic liver diseases infected with HBV or HCV and healthy control further demonstrated that a malignant liver tumor exerts profound influences independent of virus infection. Especially, serum endocannabinoids anandamide (AEA) and palmitylethanolamide (PEA) were found significantly elevated in HCC groups compared to healthy control, and in HCC with HCV compared to corresponding chronic liver diseases. AEA, PEA, or their combination showed better sensitivity, specificity, and the area under the curve for distinguishing HCC from chronic liver diseases, showing they are potential biomarkers to distinguish the HCC from cirrhosis infected with HCV.

Sheathless capillary electrophoresis-mass spectrometry with a high-sensitivity porous sprayer for cationic metabolome analysis

Sheath-flow capillary electrophoresis-mass spectrometry (CE-MS) has emerged as a new tool for comprehensive analysis of charged metabolites. However, it needs to be more sensitive. Here, we report a sheathless capillary electrophoresis-electrospray ionization-mass spectrometry method for cationic metabolome analysis. This system used a high-sensitivity porous sprayer interface and 10% (v/v) acetic acid as the background electrolyte (BGE). Under optimized conditions, 53 cationic metabolites, including amino acids and their derivatives, amines, nucleic acids and small peptides, were successfully separated and selectively detected with a time-of-flight mass spectrometer. At a signal-to-noise ratio of three, the concentration detection limits for these compounds were between 0.004 and 0.8 μmol L(-1) (amount detection limit, 0.01 to 2 fmol) with pressure injection at 20.7 kPa for 5 s (2.6 nL). Compared with conventional sheath-flow CE-MS, the detection limit of the present method was increased more than 5-fold for 21 (40%) of the compounds detected. When the method was applied to the analysis of cationic metabolites obtained from human urine, there was a 10-fold increase in the number of detected peaks compared with conventional methods. More than 180 successive runs could be conducted without any problems, and only the BGE needed to be changed.

Transcriptional biomarkers--high throughput screening, quantitative verification, and bioinformatical validation methods

Molecular biomarkers found their way into many research fields, especially in molecular medicine, medical diagnostics, disease prognosis, risk assessment but also in other areas like food safety. Different definitions for the term biomarker exist, but on the whole biomarkers are measureable biological molecules that are characteristic for a specific physiological status including drug intervention, normal or pathological processes. There are various examples for molecular biomarkers that are already successfully used in clinical diagnostics, especially as prognostic or diagnostic tool for diseases. Molecular biomarkers can be identified on different molecular levels, namely the genome, the epigenome, the transcriptome, the proteome, the metabolome and the lipidome. With special "omic" technologies, nowadays often high throughput technologies, these molecular biomarkers can be identified and quantitatively measured. This article describes the different molecular levels on which biomarker research is possible including some biomarker candidates that have already been identified. Hereby the transcriptomic approach will be described in detail including available high throughput methods, molecular levels, quantitative verification, and biostatistical requirements for transcriptional biomarker identification and validation.

Proteome and computational analyses reveal new insights into the mechanisms of hepatitis C virus-mediated liver disease posttransplantation

Liver transplant tissues offer the unique opportunity to model the longitudinal protein abundance changes occurring during hepatitis C virus (HCV)-associated liver disease progression in vivo. In this study, our goal was to identify molecular signatures, and potential key regulatory proteins, representative of the processes influencing early progression to fibrosis. We performed global protein profiling analyses on 24 liver biopsy specimens obtained from 15 HCV(+) liver transplant recipients at 6 and/or 12 months posttransplantation. Differentially regulated proteins associated with early progression to fibrosis were identified by analysis of the area under the receiver operating characteristic curve. Analysis of serum metabolites was performed on samples obtained from an independent cohort of 60 HCV(+) liver transplant patients. Computational modeling approaches were applied to identify potential key regulatory proteins of liver fibrogenesis. Among 4,324 proteins identified, 250 exhibited significant differential regulation in patients with rapidly progressive fibrosis. Patients with rapid fibrosis progression exhibited enrichment in differentially regulated proteins associated with various immune, hepatoprotective, and fibrogenic processes. The observed increase in proinflammatory activity and impairment in antioxidant defenses suggests that patients who develop significant liver injury experience elevated oxidative stresses. This was supported by an independent study demonstrating the altered abundance of oxidative stress-associated serum metabolites in patients who develop severe liver injury. Computational modeling approaches further highlight a potentially important link between HCV-associated oxidative stress and epigenetic regulatory mechanisms impacting on liver fibrogenesis.

CONCLUSION

Our proteome and metabolome analyses provide new insights into the role for increased oxidative stress in the rapid fibrosis progression observed in HCV(+) liver transplant recipients. These findings may prove useful in prognostic applications for predicting early progression to fibrosis.

Disruption of phospholipid and bile acid homeostasis in mice with nonalcoholic steatohepatitis

Nonalcoholic steatohepatitis (NASH) is a progressive form of nonalcoholic fatty liver disease that can develop into cirrhosis, hepatic failure, and hepatocellular carcinoma. Although several metabolic pathways are disrupted and endogenous metabolites may change in NASH, the alterations in serum metabolites during NASH development remain unclear. To gain insight into the disease mechanism, serum metabolite changes were assessed using metabolomics with ultraperformance liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry and a conventional mouse NASH model induced by a methionine- and choline-deficient (MCD) diet. Significant decreases in serum palmitoyl-, stearoyl-, and oleoyl-lysophosphatidylcholine (LPC) and marked increases in tauro-β-muricholate, taurocholate and 12-hydroxyeicosatetraenoic acid (12-HETE) were detected in mice with NASH. In agreement with these metabolite changes, hepatic mRNAs encoding enzymes and proteins involved in LPC degradation (lysophosphatidylcholine acyltransferase [Lpcat] 1-4), basolateral bile acid excretion (ATP-binding cassette subfamily C member [Abcc] 1/4/5 and organic solute transporter β), and 12-HETE synthesis (arachidonate 12-lipoxygenase) were significantly up-regulated. In contrast, the expression of solute carrier family 10 member 1 (Slc10a1) and solute carrier organic anion transporter family member (Slco) 1a1 and 1b2, responsible for transporting bile acids into hepatocytes, were markedly suppressed. Supplementation of the MCD diet with methionine revealed that the changes in serum metabolites and the related gene expression were derived from steatohepatitis, but not dietary choline deficiency or steatosis. Furthermore, tumor necrosis factor-α and transforming growth factor-β1 induced the expression of Lpcat2/4 and Abcc1/4 and down-regulated Slc10a1 and Slco1a1 in primary hepatocytes, suggesting an association between the changes in serum LPC and bile acids and proinflammatory cytokines. Finally, induction of hepatitis in ob/ob mice by D-galactosamine injection led to similar changes in serum metabolites and related gene expression.

CONCLUSION

Phospholipid and bile acid metabolism is disrupted in NASH, likely due to enhanced hepatic inflammatory signaling.

Recent advances in metabolomics in oncology

The burden of cancer is growing worldwide and with it a more desperate need for better tools to detect, diagnose and monitor the disease is required. It is well recognized that cancer cells are characterized by distinct metabolic perturbations. The metabolomics approach involves the comprehensive profiling of the full complement of low MW compounds in a biological system. By applying advanced analytical and statistical tools, the 'metabolome' is mined for biomarkers that are associated with the state of cancer. This review presents an introduction to the main analytical platforms used in metabolomics analyses, such as NMR spectroscopy and MS, as well as the statistical tools used to mine these datasets. The discussion focuses on 'state-of-the-art' investigations on the four cancer types that have received the most study by metabolomics, namely breast, prostate, colorectal and liver cancer.

Bioinformatics Tools for Mass Spectroscopy-Based Metabolomic Data Processing and Analysis

Biological systems are increasingly being studied in a holistic manner, using omics approaches, to provide quantitative and qualitative descriptions of the diverse collection of cellular components. Among the omics approaches, metabolomics, which deals with the quantitative global profiling of small molecules or metabolites, is being used extensively to explore the dynamic response of living systems, such as organelles, cells, tissues, organs and whole organisms, under diverse physiological and pathological conditions. This technology is now used routinely in a number of applications, including basic and clinical research, agriculture, microbiology, food science, nutrition, pharmaceutical research, environmental science and the development of biofuels. Of the multiple analytical platforms available to perform such analyses, nuclear magnetic resonance and mass spectrometry have come to dominate, owing to the high resolution and large datasets that can be generated with these techniques. The large multidimensional datasets that result from such studies must be processed and analyzed to render this data meaningful. Thus, bioinformatics tools are essential for the efficient processing of huge datasets, the characterization of the detected signals, and to align multiple datasets and their features. This paper provides a state-of-the-art overview of the data processing tools available, and reviews a collection of recent reports on the topic. Data conversion, pre-processing, alignment, normalization and statistical analysis are introduced, with their advantages and disadvantages, and comparisons are made to guide the reader.

Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases

Patients with chronic liver diseases (CLD) including chronic hepatitis B and hepatic cirrhosis (CIR) are the major high-risk population of hepatocellular carcinoma (HCC). The differential diagnosis between CLD and HCC is a challenge. This work aims to study the related metabolic deregulations in HCC and CLD to promote the discovery of the differential metabolites for distinguishing the different liver diseases. Serum metabolic profiling analysis from patients with CLD and HCC was performed using a liquid chromatography-mass spectrometry system. The acquired large amount of metabolic information was processed with the random forest-recursive feature elimination method to discover important metabolic changes. It was found that long-chain acylcarnitines accumulated, whereas free carnitine, medium and short-chain acylcarnitines decreased with the severity of the non-malignant liver diseases, accompanied with corresponding alterations of enzyme activities. However, the general changing extent was smaller in HCC than in CIR, possibly due to the special energy-consumption mechanism of tumor cells. These observations may help to understand the mechanism of HCC occurrence and progression on the metabolic level and provide information for the identification of early and differential metabolic markers for HCC.

Metabonomic profiles discriminate hepatocellular carcinoma from liver cirrhosis by ultraperformance liquid chromatography-mass spectrometry

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and usually develops in patients with liver cirrhosis (LC). Biomarkers that discriminate HCC from LC are important but are limited. In the present study, an ultraperformance liquid chromatography-mass spectrometry (UPLC-MS)-based metabonomics approach was used to characterize serum profiles from HCC (n = 82), LC (n = 48), and healthy subjects (n = 90), and the accuracy of UPLC-MS profiles and alpha-fetoprotein (AFP) levels were compared for their use in HCC diagnosis. By multivariate data and receiver operating characteristic curves analysis, metabolic profiles were capable of discriminating not only patients from the controls but also HCC from LC with 100% sensitivity and specificity. Thirteen potential biomarkers were identified and suggested that there were significant disturbances of key metabolic pathways, such as organic acids, phospholipids, fatty acids, bile acids, and gut flora metabolism, in HCC patients. Canavaninosuccinate was first identified as a metabolite that exhibited a significant decrease in LC and an increase in HCC. In addition, glycochenodeoxycholic acid was suggested to be an important indicator for HCC diagnosis and disease prognosis. UPLC-MS signatures, alone or in combination with AFP levels, could be an efficient and convenient tool for early diagnosis and screening of HCC in high-risk populations.

Serum glycerophosphate levels are increased in Japanese men with type 2 diabetes

OBJECTIVE

To identify metabolites showing changes in serum levels among Japanese male with diabetes.

METHODS

We performed metabolite profiling by coupling capillary electrophoresis with electrospray ionization time-of-flight mass spectrometry using fasting serum samples from Japanese male subjects with diabetes (n=17), impaired glucose tolerance (IGT; n=5) and normal glucose tolerance (NGT; n=14).

RESULTS

Other than the expected differences in characteristics related to abnormal glucose metabolism, the percent body fat was significantly different among subjects with diabetes, IGT and NGT (27.3±6.2, 22.2±4.5 and 19.2±6.0%, respectively, p=0.0022). Therefore, percent body fat was considered as a possible confounding factor in subsequent analyses. Of 560 metabolites detected using our platform, the levels of 74 metabolites were quantified in all of the serum samples. Significant differences between diabetes and NGT were observed for 24 metabolites. The top-ranked metabolite was glycerol-3-phophate (glycerophosphate), which was significantly higher in subjects with diabetes than in those with NGT, even after Bonferroni correction for multiple testing (11.7±3.6 vs. 6.4±1.9 µM, respectively; corrected p=0.0222). Stepwise multiple regression analyses revealed that serum glycerophosphate levels were significantly correlated with 2-h plasma glucose after a 75-g oral glucose tolerance test (r=0.553, p=0.0005), independently of other characteristics, including FPG and HbA1c.

CONCLUSION

Serum glycerophosphate levels were found to be elevated in Japanese men with diabetes, and correlated with 2-h PG, independent of FPG and HbA1c. Namely, serum glycerophosphate level at fasting condition can be a marker for predicting glucose intolerance. These results warrant further studies to evaluate the relevance of glycerophosphate in the pathophysiology of diabetes.

Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis

The aim of this study is to find the potential biomarkers from the rat hepatocellular carcinoma (HCC) disease model by using a non-target metabolomics method, and test their usefulness in early human HCC diagnosis. The serum metabolic profiling of the diethylnitrosamine-induced rat HCC model, which presents a stepwise histopathological progression that is similar to human HCC, was performed using liquid chromatography-mass spectrometry. Multivariate data analysis methods were utilized to identify the potential biomarkers. Three metabolites, taurocholic acid, lysophosphoethanolamine 16:0, and lysophosphatidylcholine 22:5, were defined as "marker metabolites," which can be used to distinguish the different stages of chemical hepatocarcinogenesis. These metabolites represented the abnormal metabolism during the progress of hepatocarcinogenesis, which could also be found in patients. To test their diagnosis potential 412 sera from 262 patients with HCC, 76 patients with cirrhosis and 74 patients with chronic hepatitis B were collected and studied, it was found that 3 marker metabolites were effective for the discrimination of small liver tumor (solitary nodules of less than 2 cm in diameter) patients, achieved a sensitivity of 80.5% and a specificity of 80.1%,which is better than those of α-fetoprotein (53 and 64%, respectively). Moreover, they were also effective for the discrimination of all HCCs and chronic liver disease patients, which could achieve a sensitivity of 87.5% and a specificity of 72.3%, better than those of α-fetoprotein (61.2 and 64%). These results indicate metabolomics method has the potential of finding biomarkers for the early diagnosis of HCC.

A comprehensive untargeted metabonomic analysis of human steatotic liver tissue by RP and HILIC chromatography coupled to mass spectrometry reveals important metabolic alterations

Steatosis, or excessive accumulation of lipids in the liver, is a generally accepted previous step to the development of more severe conditions like nonalcoholic steatohepatitis, fibrosis, and cirrhosis. We aimed to characterize the metabolic profile that defines simple steatosis in human tissue and to identify potential disturbances in the hepatic metabolism that could favor the switch to progressive liver damage. A total of 46 samples, 23 from steatotic and 23 from nonsteatotic human livers, were analyzed following a holistic LC-MS-based metabonomic analysis that combines RP and HILIC chromatographic separations. Multivariate statistical data analysis satisfactorily classified samples and revealed steatosis-associated biomarkers. Increased levels of bile acids and phospholipid degradation products, and decreased levels of antioxidant species, were found in steatotic livers, indicating disturbances in lipid and bile acid homeostasis and mitochondrial dysfunction. Changes in hypoxanthine, creatinine, glutamate, glutamine, or γ-glutamyl-dipeptides concentrations, suggestive of alterations in energy metabolism and amino acid metabolism and transport, were also found. The results show that the proposed analytical strategy is suitable to achieve a comprehensive metabolic profile of steatotic human liver tissue and provide new insights into the metabolic alterations occurring in fatty liver that could contribute to its predisposition to damage evolution.

Metabolomic profile of hepatitis C virus-infected hepatocytes

Hepatitis C virus (HCV) is capable of disrupting different facets of lipid metabolism and lipids have been shown to play a crucial role in the viral life cycle. The aim of this study was to examine the effect HCV infection has on the hepatocyte metabolome. Huh-7.5 cells were infected using virus produced by the HCV J6/JFH1 cell culture system and cells were harvested 24, 48, and 72-hours following infection. Metabolic profiling was performed using a non-targeted multiple platform methodology combining ultrahigh performance liquid chromatography/tandem mass spectrometry (UHPLC/MS/MS²) and gas chromatography/mass spectrometry (GC/MS). There was a significant increase in a number of metabolites involved in nucleotide synthesis and RNA replication during early HCV infection. NAD levels were also significantly increased along with several amino acids. A number of lipid metabolic pathways were disrupted by HCV infection, resulting in an increase in cholesterol and sphingolipid levels, altered phospholipid metabolism and a possible disruption in mitochondrial fatty acid transport. Fluctuations in 5′-methylthioadenosine levels were also noted, along with alterations in the glutathione synthesis pathway. These results highlight a number of previously unreported metabolic interactions and give a more in depth insight into the effect HCV has on host cell biochemical processes.