Recent and potential developments of biofluid analyses in metabolomics

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Review

Recent and potential developments of biofluid analyses in metabolomics Aihua Zhang, Hui Sun, Ping Wang, Ying Han, Xijun Wang⁎ National TCM Key Lab of Serum Pharmacochemistry, Heilongjiang University of Chinese Medicine, Key Pharmacometabolomics Platform of Chinese Medicines, and Key Laboratory of Chinese Materia Medica, Ministry of Education, Heping Road 24, Harbin 150040, China

AR TIC LE I N FO

ABS TR ACT

Article history:

Metabolomics, one of the ‘omic’ sciences in systems biology, is the global assessment and

Received 4 October 2011

validation of endogenous small-molecule metabolites within a biologic system. Analysis

Accepted 26 October 2011

of these key metabolites in body fluids has become an important role to monitor the state

Available online 4 November 2011

of biological organisms and is a widely used diagnostic tool for disease. A majority of these metabolites are being applied to metabolic profiling of the biological samples, for ex-

Keywords:

ample, plasma and whole blood, serum, urine, saliva, cerebrospinal fluid, synovial fluid,

Metabolomics

semen, and tissue homogenates. However, the recognition of the need for a holistic ap-

System biology

proach to metabolism led to the application of metabolomics to biological fluids for disease

Biofluid analyses

diagnostics. A recent surge in metabolomic applications which are probably more accurate

Metabolites

than routine clinical practice, dedicated to characterizing the biological fluids. While devel-

Biomarkers

opments in the analysis of biofluid samples encompassing an important impediment, it

Disease diagnostics

must be emphasized that these biofluids are complementary. Metabolomics provides potential advantages that classical diagnostic approaches do not, based on following discovery of a suite of clinically relevant biomarkers that are simultaneously affected by the disease. Emerging as a promising biofocus, metabolomics will drive biofluid analyses and offer great benefits for public health in the long-term. © 2011 Elsevier B.V. All rights reserved.

Contents 1. 2. 3. 4. 5. 6. 7. 8.

Introduction . . . . . . . . . . . . . . . . Recent developments—metabolomics . . Urinalysis platform . . . . . . . . . . . . Blood plasma and serum . . . . . . . . . Cerebrospinal fluid . . . . . . . . . . . . Saliva . . . . . . . . . . . . . . . . . . . Tissue homogenates . . . . . . . . . . . Concluding remarks and future directions

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⁎ Corresponding author at: National TCM Key Lab of Serum Pharmacochemistry, Heilongjiang University of Chinese Medicine, Key Pharmacometabolomics Platform of Chinese Medicines, and Key Laboratory of Chinese Materia Medica, Ministry of Education, Heping Road 24, Harbin 150040, China. Tel./fax: + 86-451-82110818. E-mail addresses: [email protected], [email protected] (X. Wang). 1874-3919/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.jprot.2011.10.027

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Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1085 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1085 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1085

1.

Introduction

Metabolomics represents a comprehensive method for metabolite assessment that involves measuring the overall metabolites of biological samples [1]. It enables the parallel assessment of the levels of a broad range of endogenous and exogenous metabolites and has been shown to have a great impact on investigation of physiological status, diagnosing diseases, discovering biomarkers, identifying perturbed pathways due to disease or treatment. The small-molecule metabolites have an important role in biological systems and represent attractive candidates to understand disease phenotypes [2,3]. It represent a diverse group of low-molecularweight structures including lipids, amino acids, peptides, nucleic acids, and organic acids, vitamins, thiols, carbohydrates. Metabolite changes as a primary indicator of disease has made it possible to diagnose disease in individuals, and hence the measurement of metabolites has become an important part of clinical practice. Employing a range of biofluids including plasma and whole blood, serum, urine, saliva, cerebrospinal fluid (CSF), synovial fluid, semen, and tissue homogenates has a number of advantages that have ensured the widespread use of metabolites as a diagnostic tool in clinical practice [4]. Despite the significant advances in analytical technologies, the discovery of biomarkers in biological fluids remains a significant challenge. Traditional markers of conventional clinical chemistry and histopathology method are not region-specific and only increase significantly after serious disease or injury. Therefore, more sensitive markers of disease are needed. The ideal biomarkers will identify disease early, resulting in increased safer drugs. Metabolomics, an emerging and powerful discipline, has become a promising player in the disease arena, and its benefits have been demonstrated in diverse clinical areas [5]. The recent developments whose aim for complete characterization of the entire metabolome regardless of molecular size are distinguishable from traditional tests on one or two components. The metabolomic approach has substantial impact on development of diagnostics, therapeutics and drug development [6–8]. Particularly, for the early detection of disease, highly sensitive and specific biomarkers as primary indicators in bio-fluids are relatively more useful because these can be used for non-biopsy tests. Common analytical techniques applied to metabolomics are NMR, GC/MS and LC/MS. Among them, each technique has associated advantages and disadvantages. Within the field of metabolomics in biofluids, NMR provides an excellent technique for profiling biofluids and is especially adept at characterizing complex solutions. The volatile compounds can be analyzed by GC-MS after derivatization [9]. Hyphenated LC/MS technique is becoming a useful tool in the study of body fluids, represents a promising microseparation platform in metabolomics and has a strong potential to contribute to

disease diagnosis [10,11]. Integrated platforms have been frequently used to provide the sensitive and reproducible detection of thousands of metabolites in a biofluid sample. Thus, a combination of different analytical technologies must be used to gain a broad perspective of the metabolome. The diagnostic potential of body fluids is underscored by the number of publications devoted to this area. One of the attractive properties of metabolomics is the ability to generate profiles from these fluids following simple preparation, allowing the analyst to gain a naturalistic, largely unbiased view of their composition that is highly representative of the in vivo situation [12,13]. It must be emphasized that these biofluids are complementary, although urine is without a doubt the preferred sample for metabolome analysis. Thus, this review gives a brief description of the development and applications of biofluid analysis in metabolomics, and discusses their significance in the postgenomic era. Especially, this review focuses on the important roles of the endogenous small-molecule metabolites in metabolomics and emphasis will be placed on the biomarker discovery and the potentials and limitations as well as some new trends in the development of biofluids are also discussed.

2.

Recent developments—metabolomics

Metabolomics, a promising ‘omics’ platform whose aim is the comprehensive analysis of low molecular weight metabolites in a biological sample, shows great potential in biomarker discovery, especially in disease diagnosis and pharmaceutical areas [14]. Flowchart of metabolomic analysis is shown in Fig. 1. As a new approach, it is the systematic study of the full complement of metabolites in a biological sample. This technology consists of two sequential steps: (a) an experimental technique, based on MS or NMR spectroscopy, designed to profile low molecular weight compounds, and (b) multivariate data analysis [15]. Metabolomics has recently demonstrated significant potential in many fields such as responses to environmental stress [16,17], toxicology [18–20], nutrition [21–23], studying global effects of genetic manipulation [24–26], cancer [27–32], comparing different growth stages [33–35], diabetes [36,37], disease diagnosis [38], natural product discovery [39,40], and traditional medicine [41,42]. As a novel strategy trying to find markers under a situation, metabolomics has rapidly focused attention on the identification of markers responsible for disease [43]. Metabolomic analysis of biofluids or tissues has been successfully used in the fields of physiology, diagnostics, functional genomics, pharmacology, toxicology and nutrition [44]. It represents one of the new omics sciences and capitalizes on the unique presence and concentration of small molecules in tissues and body fluids to construct a ‘fingerprint’ which can be unique to the individual and environmental influences. As such, metabolomics has the potential to serve an important role in diagnosis and

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Fig. 1 – The overall flowchart of metabolomic investigation.

management of human conditions. Metabolomics is a diagnostic tool for metabolic classification of individuals. The great asset of this platform is the quantitative, non-invasive analysis of easily accessible body fluids [45]. Metabolic profiling of biofluids and tissues can provide a panoramic view of abundant changes of endogenous metabolites in monitoring cellular responses to perturbations such as diseases and drug treatments [46]. Precise identification and accurate quantification of metabolites facilitate downstream pathway and network analysis for the discovery of clinically accessible and minimally invasive biomarkers of drug efficacy and toxicity. On the other hand, metabolomics offers potential advantages that classical diagnostic approaches do not, based on following discovery of a suite of clinically relevant biomarkers that are simultaneously affected by the disease [47–50]. With the aim of addressing these issues, this article proposes reporting guidelines and potential developments for biofluid entities.

3.

Urinalysis platform

Monitoring certain metabolite levels in urine fluid which is the most commonly used biofluid in metabolomics, has become an important way to detect early stages in disease [51]. Due to relatively less complex sample pre-treatment, lower protein content and sample complexity including less intermolecular interaction, urine as an analytical tool has a number of advantages over other biofluids. The simple, noninvasive collection techniques make urine a particularly suitable biofluid for metabolomic approach for meaningful diagnostic information. Urinary metabolomic approaches are likely to be used to screen for potentially earlier diagnostic and prognostic biomarkers of disease.

The urinary metabolome of type 2 diabetes mellitus (T2DM) was well characterized and examined by highresolution ultra-performance liquid chromatography coupled with mass spectrometry (UPLC/MS) to enhance understanding of the metabolic indicators [52]. It was found that when compared with the normal group, urinary metabolites in the T2DM significantly increased, including glycine betaine, citric acid, kynurenic acid, glucose, and pipecolic acid. These metabolites as indicators were useful in enhancing understanding of the T2DM disease pathogenesis and progression. Nontargeted urinary metabolomic technologies are increasingly being incorporated into biomarker and relevant biochemical pathways exploration of T2D [53]. In a study, McClay et al. used NMR metabolomics as a screening tool for identifying novel urinary biomarkers of lung function [54]. Taylor et al. utilized a urinary analysis based GC/MS metabolomics to study kidney disease [55]. Several biologically relevant metabolic pathways were altered very early in this disease, and the most highly represented being the purine and galactose metabolism pathways. Specific candidate biomarkers augmented in the urine were identified, including allantoic acid and adenosine. These markers and pathways, once extended to human disease, may prove useful as a noninvasive means of diagnosing kidney diseases and suggest novel therapeutic approaches. They have great diagnostic potential for renal disorders and deserve further study. The urinary metabolomic method was applied to the urine profile samples of breast cancer patients and normal persons [56]. Among nine altered metabolic pathways, four metabolic biomarkers were identified to be different in cancer and normal subjects (p <0.05). Urinary metabolomic analysis has potential to lead to a diagnostic assay for renal cell carcinoma [57]. Various metabolic biomarkers related to glycolysis, mitochondrial citric cycle

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acid, choline and fatty acid metabolism, were reported to play important roles in cancer development and responsiveness to anticancer treatment using NMR-based metabolic profiling [58]. Jung et al. applied NMR urinary metabolomics to investigate the altered metabolic profiles in patients with stroke and sought to identify key metabolic biomarkers [59]. The characterized metabolites detected from stroke patients demonstrated that urinary metabolomic approach may be useful for the effective diagnosis of stroke pathogenesis. Untargeted metabolic profiles from urine have revealed the potential to characterize asthma and enabled the identification of metabolites that may have a role in the underlying pathogenic mechanisms [60]. Urine samples from patients diagnosed with non-functioning adrenal incidentalomas and 30 healthy subjects were used to analyze possible markers [61]. Five altered urinary metabolites, including α-cortol, tetrahydrocorticosterone, tetrahydrocortisol, allo-tetrahydrocortisol and etiocholanolone, were identified as potential biomarkers of pathological adrenal function and reflected pathological metabolism of cortisol and cortisone. This research proved that urinary metabolomic analysis is a suitable tool for disease research. The interleukin-10-deficient (I-10-D) mouse develops colon inflammation in response to normal intestinal microflora and has been used as a model of Crohn's disease. Urine metabolite profiling from I-10-D and wild-type mice was used to identify mass spectral ions differing in intensity between these two genotypes [62]. Results showed that three significantly different metabolites evaluated as potential biomarkers of colon inflammation were found to be associated with the degree of inflammation in I-10-D mice. They can prove useful as biomarkers of colon inflammation. UPLC/MS metabolomics was conducted on urine samples from wildtype and hepatocyte nuclear factor 1α (Hnf1α)-null mice [63]. Although the phenotype of the Hnf1a-null mouse is complex, urinary metabolomics has opened the door to investigation of several physiological systems in which Hnf1α may be a critical regulatory component. Urinary metabolic profile identified early, noninvasive biomarkers of alcohol-induced liver disease pathogenesis in Ppara-null mouse model by Manna and colleagues [64]. It was found that the exclusive elevation of indole-3-lactic acid is mechanistically related to the molecular events associated with development of liver disease in alcohol-treated Ppara-null mice. The non-targeted approach of urine could provide new intake biomarkers, contributing to the development of the food metabolome [65]. For example, Miccheli et al. had evaluated the systemic effects of drinking a green tea extract-based carbohydrate/hydroelectrolyte sports beverage on the metabolic status of athletes by means of NMR-based urinary metabolic profiling [66]. Results showed an effect of the green teabased sports drink on acetone, 3-OH-butyrate, and lactate levels that related with energy metabolism of athletes during recovery by postexercise rehydration. An LC/MS-based metabolomic approach was used for exploring human urinary metabolome modifications after cocoa consumption [67]. Results confirm that metabolomics will contribute to better characterization of the urinary metabolome in order to further explore the metabolism of phytochemicals and its relation to human health. Xiaoyaosan, a famous Chinese prescription,

has anti-depression activity and been widely used in the clinic for treating mental disorders. A urinary metabolomic method was applied to evaluate the efficacy of xiaoyaosan on rat model of chronic unpredictable mild stress [68]. It was found that urinary metabolomics is a valuable tool in studying the efficacy and potential biomarkers of therapeutic effects of complex prescriptions. This work also confirmed that the urinary metabolomic approach provides effective tools for screening multiple metabolic components of Chinese herbal medicines in vivo. The combined application of global and targeted metabolic profiling of urine could be a useful tool for the discovery of drug safety biomarkers for atorvastatin [69]. Metabolic profiling of urine provides a fingerprint of personalized endogenous metabolite markers that correlate to a number of factors such as gender, disease, diet, toxicity, medication, and age [70]. It has been validated for predicting valproic acid-induced hepatotoxicity and discovery of novel biomarkers in rat [71]. Valproic acid therapy is associated with hepatotoxicity as well as renal toxicity. LC/MS-based metabolomic approach of urine has been capable of identifying valproic acid-related metabolites and altered endogenous metabolites, and is a powerful tool for the discovery of potential early biomarkers related to perturbations in liver and kidney function [72].

4.

Blood plasma and serum

Blood plasma or serum contains a wide range of macromolecules which can overlap with peaks from small molecule metabolites, under specific physiological or pathologic states [73]. Large-scale metabolites of blood plasma or serum are increasingly gaining attention for their use in the diagnosis of human disease. Soga and colleagues had applied serum metabolomics to analyze low molecular weight metabolites from patients with nine types of liver disease and healthy controls, to discover noninvasive and reliable biomarkers for rapid-screening diagnosis of liver diseases [74]. It was found that γ-Glutamyl dipeptides are key biomarkers for liver diseases, and varying levels of individual or groups of these peptides have the power to discriminate among different forms of hepatic disease. A serum metabolic profile obtained by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology. The anti-platelet effect and influence of Radix paeoniae rubra and Radix paeoniae alba on rat's endogenous metabolites were analyzed by UPLC/ MS based serum metabolomic method [75,76]. The potential markers have proved to be significant expressed biomarkers. Oral cancer is the eighth most common cancer worldwide and represents a significant disease burden. If detected at an early stage, survival from oral cancer is better than 90% at 5 years, whereas late stage disease survival is only 30%. Therefore, there is an obvious clinical utility for novel metabolic markers that help to diagnose oral cancer at an early stage and to monitor treatment response. The blood samples of oral cancer patients were analyzed using NMR to derive a significant metabolic signature for oral cancer [77]. An LC-MS serum metabolomics-based diagnostic has the potential to monitor the progression of onchocerciasis in both endemic and nonendemic geographic areas, as well as provide an essential tool

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to multinational programs in the ongoing fight against tropical diseases [78]. Serum samples from 27 healthy women, and samples from 28 benign ovarian tumors, and 29 epithelial ovarian cancer were analyzed by using LC-MS based nontargeted metabolomics [79]. Six key metabolites were considered as potential biomarker candidates, ready for early stage detection. Targeted NMR metabolomic profiling of serum could be employed to distinguish the effects of obesity from those of diet in mice [80]. The serum metabolomic profile may be useful for distinguishing benign from malignant pancreatic lesions and would facilitate the diagnosis and potentially prevent unnecessary surgery [81]. NMR-based metabolomic analysis of serum could be useful in predicting exercise-inducible ischemia in patients with suspected coronary artery disease [82]. This capability could be useful in screening and risk stratification of patients with coronary risk factors. Serum metabolite analysis has been conducted to compare animals with and without a large tumor burden. Intriguingly, the results suggested that the widespread metabolites identified could be capable and useful as a marker for intra-tumoral hypoxia [83]. The pathogenic mechanism of ulcerative colitis, a dextran sulfate sodium-induced acute colitis model was sussesfully examined by serum metabolomic analysis [84]. These studies demonstrate the feasibility of high-throughput serum metabolomics for identifying disease changes at omics levels.

5.

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subtypes of ALS in relation to controls [89]. Using CSF samples, they identified over 30 metabolites within key neurotransmitter pathways and alterations involved in tyrosine, tryptophan, purine, and tocopherol pathways in patients with Alzheimer's disease (AD) [90]. CSF screening by NMR spectroscopy could be a useful, simple and low cost tool to improve the early diagnosis of ALS, indicating a perturbation of glucose metabolism, and the need to further explore cerebral energetic metabolism [91]. Analysis of sialic acid metabolites in CSF is important for clinical diagnosis. In a study, LC/MS method for free sialic acid and total sialic acid in human CSF has been validated [92]. To standardize the use of CSF for biomarker research, a set of stability studies has been performed on porcine samples to investigate the influence of common sample handling procedures on proteins, peptides, metabolites and free amino acids [93]. Large volumes of CSF are required to maximize sensitivity and establish a provisional diagnosis. Himmelreich et al. had utilized NMR spectroscopy to rapidly characterize the biochemical profile of CSF from normal rats and animals with pneumococcal or cryptococcal meningitis [94]. A global metabolomic approach was used to find and identify metabolites differentially regulated in the CSF with CNS disease, and this might provide biomarkers of virus-induced CNS damage [95]. Consequently, these results provide convincing evidence of the power of CSF-metabolomics for identifying functional changes at many levels in the omics pipeline.

Cerebrospinal fluid 6.

Analysis of CSF samples holds great promise to diagnose neurological pathologies and gain insight into the molecular background of the pathologies [85]. Sensitive CSF-derived marker candidates exist, but given the invasiveness of sample collection their use in routine diagnostics may be limited. Metabolomic methods provide invaluable information on the biomolecular content of CSF and thereby on the possible status of the central nervous system, including neurological pathologies. The analysis of CSF is used in biomarker discovery studies for various neurodegenerative central nervous system (CNS) disorders. Metabolomic analysis was performed by means of GC/MS and NMR, resulting in the detection of more than 100 metabolites [86]. Additionally, human CSF using a global LC/MS metabolomic strategy is examined [87]. The platform shows small analytical variation with a median coefficient of variation of 15–16% for CSF sample matrixes. It demonstrated the reproducibility of the global metabolomics platform using LC/MS and revealed the robustness of the approach for biomarker discovery. CSF metabolites were analyzed by using metabolome analysis in order to search for the specific biomarkers of patients with influenza-associated encephalopathy [88]. It was found that the two molecular weights detected in CSF would be primary markers for the diagnosis of influenza-associated encephalopathy. Global metabolomics can be used for detecting changes in the CSF metabolome associated with the fatal neurodegenerative disease amyotrophic lateral sclerosis (ALS). Using GC/ MS and multivariate statistical modeling, Wuolikainen and colleagues had simultaneously studied the metabolome signature of 120 small metabolites in the CSF patients with ALS, stratified according to hereditary disposition and clinical

Saliva

The metabolome is now considered by some to be the most predictive phenotype, consequently the comprehensive and quantitative study of metabolites is a desirable tool for diagnosing disease, identifying new therapeutic targets and enabling appropriate treatments. A wealth of information about metabolite profiles in biological samples, particularly saliva, has been accumulated with global profiling tools and several candidate technologies for metabolomic studies are now available [96]. Saliva is a readily accessible and informative biofluid, making it ideal for the early detection of a wide range of diseases including cardiovascular, renal, and autoimmune diseases, viral and bacterial infections and, importantly, cancers [97]. Saliva-based diagnostics, particularly those based on metabolomic technology, are emerging and offer a promising clinical strategy, characterizing the association between salivary analytes and a particular disease. The identified principal metabolites are promising biomarkers for accurately predicting the probability of disease, to discriminate healthy controls from each disease. They suggest that cancer-specific signatures are embedded in saliva metabolites. Metabolic profiling of human saliva samples was investigated and evaluated by NMR, and multivariate data analysis revealed that the 92 morning and night samples from 46 subjects could be distinguished with a predictability of 85% [98]. The diurnal effect on the salivary metabolite profile was ascribed to changes in intensities of several metabolites including trimethylamine oxide, choline, propionate, alanine, methanol, and N-acetyl groups. Salivary metabolomics as a disease diagnostic and stratification tool was explored to evaluate the potential of salivary metabolome for detection of oral

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squamous cell carcinoma (OSCC) [99]. A panel of five salivary metabolites including γ-aminobutyric acid, phenylalanine, valine, n-eicosanoic acid and lactic acid were selected using orthogonal projection to latent structures analysis (OPLS-DA) model with S-plot, demonstrating the salivary metabolome could improve disease diagnostics for oral cancer, complementing the clinical detection of OSCC. Early diagnosis of OSCC and precursor lesions is an attractive strategy to decrease patient morbidity and mortality. Metabolic profiling of noninvasive saliva samples can properly enable the detection of the pathologic characteristics of OSCC, achieving 100% accuracy in diagnosis of test samples [100]. This approach is noninvasive, efficient and low-cost, and it can be developed as a promising method for population-based screening of cancers and precancers in the oral cavity.

7.

Tissue homogenates

Metabolomics is an approach in which the profiles of metabolites in different tissues are investigated to understand the changes induced following a modulation. Global determination of metabolite concentrations in the tissues provides novel anatomical aspects of pathological conditions that cannot be obtained from target-specific fluid measurements. The measurement of metabolites in tissues is of great importance in metabolomic research in the biomedical sciences, providing more relevant information than is available from systemic biofluids. The liver is the most important organ/tissue for most biochemical reactions, and the metabolites in the liver are of great interest to scientists. Moazzami et al. used metabolomic approach to investigate the biochemical effects of α-tocopherol in the liver using a rat model [101]. Livers were homogenized in methanol-chloroform-water (3:1:1, v/v/v), and the polar phase extracts of the liver samples were analyzed using NMR. The changes in carnitine and glucose suggested a possible shift in energy metabolism. The metabolic profiles of intact liver tissues were applied to evaluate the beneficial effects of cordycepin, a natural monomer compound, on endogenous metabolic profiles of liver from hyperlipidemic Syrian golden hamsters, using NMR spectroscopy [102]. The results showed higher contents of lipids, lactate, acetate, alanine, glutamine together with lower contents of choline-containing compounds, glucose, and glycogen in liver samples from hyperlipidemic hamsters than those in controls. A protocol for the metabolic profiling of rat liver was developed based on UPLC-Q-TOF/MS to explore metabolic state directly [103]. Liver tissues from diabetic and control rats enrolled in the subsequent study indicated that the established method is suitable and reliable for liver tissue metabolic profiling. Liver tissue samples have been used to analyze and develop robust and reliable sample processing and mass spectrometry protocols for studying human liver metabolomic profiles [104]. Results indicated that the approximately 1245 features were acquired using metabolomic profiling for tissue homogenization. To develop an optimized extraction method and comprehensive profiling technique for liver metabolites, organic solvents of various compositions were designed using design of experiments to extract metabolites from the liver, and the metabolites were profiled by GC/MS [105]. The optimal solvent

that had the highest extraction efficiency was methanol– water which was applied to extract metabolites in liver. Results suggest that liver metabolomics is a valuable technique and that the combined analysis of systemic biofluids and local tissues is effective and complementary, recovering more comprehensive metabolomic data than either analysis alone. The metabolite profile of liver tissue was investigated with GC/MS to evaluate the alteration in biochemical composition from exhaustive and endurance exercises in trained rats modifying the physiological status of the body differently [106]. Changes in liver metabolism involved metabolites such as amino acids, fatty acids, organic acids, and carbohydrates. Endurance training elevated the greater rate of tricarboxylic acid cycle and antioxidant activity, and exhaustive exercise led to accumulated urea markers and an inflammation response in liver. In addition, tissue-based metabolomic analysis is a promising tool to investigate a pathological status with different exercise programs. A combined NMR spectroscopy and GC/MS approach has been used to examine metabolism in the liver, heart, skeletal muscle and adipose tissue in PPAR-alpha-null mice and wild-type controls during aging changes [107]. The findings indicated reductions of the concentrations of glucose and glycogen in both the liver and muscle tissue, reflecting known expression targets of the PPARalpha receptor. Hepatic glycogen and glucose also decreased with age for both genotypes. A metabolomic approach based on high-resolution magic-angle spinning NMR spectroscopy was applied to investigate the metabolite composition in intact hepatic tissues from an animal model of type 2 diabetes mellitus [108]. Compared to the control group, the hepatic tissues of diabetic mice have elevated levels of triglyceride and bile acid and declined levels of trimethylamine-N-oxide, phosphocholine, glycerophosphocholine, and choline. Metabolomic protocol could also be extended to other tissues. Kidney homogenate was investigated to identify the changes in the levels of metabolites in rats with Li-induced renal injury for bipolar affective disorders associated with a variety of renal side effects using high-resolution NMR spectroscopy coupled with pattern recognition methods [109]. The concentrations of metabolites in kidney homogenates were rapidly and accurately measured using the targetprofiling procedure, and the difference in the levels of metabolites was compared using multivariate analysis. Major endogenous metabolites for kidney homogenates contained products of glycolysis and amino acids, as well as organic osmolytes. Many metabolites revealed changes in their levels, including decreased levels of organic osmolytes and amino acids in the inner medulla. Taken together, metabolomics of kidney tissue based on NMR spectroscopy could provide insight into the effects of Li-induced renal injury. Druginduced nephrotoxicity is a major concern, since many pharmacological compounds are filtered through the kidneys for excretion into urine. Using a combination of GC/MS and LC/ MS, a global, nontargeted metabolomicsanalysis was performed on kidney tissue collected to discover biochemical biomarkers useful for early identification of nephrotoxicity [110–112]. A panel of biomarkers could provide a noninvasive method to detect kidney injury long before the onset of histopathological kidney damage. These results illustrate the potential of tissue based metabolomics in combination with

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multivariate statistical analysis, and may uncover the metabolic phenotype of a particular disease and help to explore disease from a new perspective.

8. Concluding remarks and future directions for biofluid metabolomics Metabolomics is an emerging technology that reveals homeostatic imbalances in biological systems and has the capability of providing comprehensive information on biofluids including plasma and whole blood, serum, urine, saliva, CSF, and tissue homogenates. It has shown the potential to enable mapping of perturbations of early biochemical changes in disease and hence provides an opportunity to develop predictive biomarkers that can trigger earlier interventions as well as provide valuable insights on the mechanisms of disease. We delineate and evaluate the current status of biofluid analysis in metabolomics, with an emphasis on specific high-throughput noninvasive biomarkers. New novel and specific biomarkers which detect earlier than the traditional clinical chemistry and histopathology methods, could facilitate and improve the development of disease treatments, thus benefiting public health. The significance of recent advancements in the potential application of biofluid analyses in metabolomics is highlighted once more. In the future, a combination of different biological fluid markers, rather than a single marker, may prove a useful tool for the diagnosis and follow-up of patients.

Abbreviations CSF T2DM I-10-D Hnf1α CNS ALS AD OSCC PLS-DA OPLS-DS

cerebrospinal fluid type 2 diabetes mellitus interleukin-10-deficient hepatocyte nuclear factor 1α central nervous system amyotrophic lateral sclerosis Alzheimer's disease oral squamous cell carcinoma partial least squares-discriminant analysis orthogonal projection to latent structures analysis

Acknowledgments This work was supported by grants from the Key Program of the Natural Science Foundation of the State (Grant No. 90709019), the National Key Program on the Subject of Drug Innovation (Grant No. 2009ZX09502-005), the National Specific Program on the Subject of Public Welfare (Grant No. 200807014), and the National Program for Key Basic Research Projects in China (Grant No. 2005CB523406).

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