Metabolites from cerebrospinal fluid in aneurysmal subarachnoid haemorrhage correlate with vasospasm and clinical outcome: a pattern-recognition 1H NMR study

Metabolomic Analysis in Neurocritical Care Patients

Metabolomics is the analytical study of metabolites in biological matrices using high-throughput profiling. Traditionally, the metabolome has been studied to identify various biomarkers for the diagnosis and pathophysiology of disease. Over the last decade, metabolomic research has grown to include the identification of prognostic markers, the development of novel treatment strategies, and the prediction of disease severity. In this review, we summarized the available evidence on the use of metabolome profiling in neurocritical care populations. Specifically, we focused on aneurysmal subarachnoid hemorrhage, traumatic brain injury, and intracranial hemorrhage to identify the gaps in the current literature and to provide direction for future studies. A primary literature search of the Medline and EMBASE databases was conducted. Upon removing duplicate studies, abstract screening and full-text screening were performed. We screened 648 studies and extracted data from 17 studies. Based on the current evidence, the utility of metabolomic profiling has been limited due to inconsistencies amongst studies and a lack of reproducible data. Studies identified various biomarkers for diagnosis, prognosis, and treatment modification. However, studies evaluated and identified different metabolites, resulting in an inability to compare the study results. Future research towards addressing the gaps in the current literature, including reproducing data on the use of specific metabolite panels, is needed.

Pursuing Experimental Reproducibility: An Efficient Protocol for the Preparation of Cerebrospinal Fluid Samples for NMR-based Metabolomics and Analysis of Sample Degradation

NMR-based metabolomics investigations of human biofluids offer great potential to uncover new biomarkers. In contrast to protocols for sample collection and biobanking, procedures for sample preparation prior to NMR measurements are still heterogeneous, thus compromising the comparability of the resulting data. Herein, we present results of an investigation of the handling of cerebrospinal fluid (CSF) samples for NMR metabolomics research. Origins of commonly observed problems when conducting NMR experiments on this type of sample are addressed, and suitable experimental conditions in terms of sample preparation and pH control are discussed. Sample stability was assessed by monitoring the degradation of CSF samples by NMR, hereby identifying metabolite candidates, which are potentially affected by sample storage. A protocol was devised yielding consistent spectroscopic data as well as achieving overall sample stability for robust analysis. We present easy to adopt standard operating procedures with the aim to establish a shared sample handling strategy that facilitates and promotes inter-laboratory comparison, and the analysis of sample degradation provides new insights into sample stability.

Haemoglobin scavenging in intracranial bleeding: biology and clinical implications

Haemoglobin is released into the CNS during the breakdown of red blood cells after intracranial bleeding. Extracellular free haemoglobin is directly neurotoxic. Haemoglobin scavenging mechanisms clear haemoglobin and reduce toxicity; these mechanisms include erythrophagocytosis, haptoglobin binding of haemoglobin, haemopexin binding of haem and haem oxygenase breakdown of haem. However, the capacity of these mechanisms is limited in the CNS, and they easily become overwhelmed. Targeting of haemoglobin toxicity and scavenging is, therefore, a rational therapeutic strategy. In this Review, we summarize the neurotoxic mechanisms of extracellular haemoglobin and the peculiarities of haemoglobin scavenging pathways in the brain. Evidence for a role of haemoglobin toxicity in neurological disorders is discussed, with a focus on subarachnoid haemorrhage and intracerebral haemorrhage, and emerging treatment strategies based on the molecular pathways involved are considered. By focusing on a fundamental biological commonality between diverse neurological conditions, we aim to encourage the application of knowledge of haemoglobin toxicity and scavenging across various conditions. We also hope that the principles highlighted will stimulate research to explore the potential of the pathways discussed. Finally, we present a consensus opinion on the research priorities that will help to bring about clinical benefits.

Cerebrospinal fluid untargeted metabolomic profiling of aneurysmal subarachnoid hemorrhage: an exploratory study

INTRODUCTION

Despite advancements in medical and surgical therapies, clinical outcomes of aneurysmal subarachnoid hemorrhage (aSAH) continue to be poor. Currently, aSAH pathophysiology remains poorly understood. No aSAH biomarkers are commonly used in the clinical setting. This exploratory study used metabolomics profiling to identify global metabolic changes and metabolite predictors of long-term outcome using cerebrospinal fluid (CSF) samples of aSAH patients.

METHODS AND METHODS

Gas chromatography time-of-flight mass spectrometry was applied to CSF samples collected from 15 consecutive high-grade aSAH patients (modified Fisher grade 3 or 4). Collected CSF samples were analyzed at two time points (admission and the anticipated vasospasm timeframe). Metabolite levels at both time points were compared and correlated with vasospasm status and Glasgow Outcome Scale (GOS) of patients at 1 year post-aSAH. Significance level was defined as p < 0.05 with false discovery rate correction for multiple comparisons.

RESULTS

Of 97 metabolites identified, 16 metabolites, primarily free amino acids, significantly changed between the two time points. These changes were magnified in modified Fisher grade 4 compared with grade 3. Six metabolites (2-hydroxyglutarate, tryptophan, glycine, proline, isoleucine, and alanine) correlated with GOS at 1 year post-aSAH independent of vasospasm status. When predicting patients who had low disability (GOS 5 vs. GOS ≤4), 2-hydroxyglutarate had a sensitivity and specificity of 0.89 and 0.83 respectively.

CONCLUSIONS

Our preliminary study suggests that specific metabolite changes occur in the brain during the course of aSAH and that quantification of specific CSF metabolites may be used to predict long-term outcome in patients with aSAH. This is the first study to implicate 2-hydroxyglutarate, a known marker of tissue hypoxia, in aSAH pathogenesis.

Nuclear Magnetic Resonance technique in tumor metabolism

Cancer is one of the most serious diseases that cause an enormous number of deaths all over the world. Tumor metabolism has great discrimination from that of normal tissues. Exploring the tumor metabolism may be one of the best ways to find biomarkers for cancer detection, diagnosis and to provide novel insights into internal physiological state where subtle changes may happen in metabolite concentrations. Nuclear Magnetic Resonance (NMR) technique nowadays is a popular tool to analyze cell extracts, tissues and biological fluids, etc, since it is a relatively fast and an accurate technique to supply abundant biochemical information at molecular levels for tumor research. In this review, approaches in tumor metabolism are discussed, including sample collection, data profiling and multivariate data analysis methods etc. Some typical applications of NMR are also summarized in tumor metabolism.

Metabonomics and intensive care

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency medicine 2016. Other selected articles can be found online at http://www.biomedcentral.com/collections/annualupdate2016. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

A hypothetical astrocyte-microglia lactate shuttle derived from a 1H NMR metabolomics analysis of cerebrospinal fluid from a cohort of South African children with tuberculous meningitis

Tuberculosis meningitis (TBM) is the most severe form of extra-pulmonary tuberculosis and is particularly intense in small children; there is no universally accepted algorithm for the diagnosis and substantiation of TB infection, which can lead to delayed intervention, a high risk factor for morbidity and mortality. In this study a proton magnetic resonance (¹H NMR)-based metabolomics analysis and several chemometric methods were applied to data generated from lumber cerebrospinal fluid (CSF) samples from three experimental groups: (1) South African infants and children with confirmed TBM, (2) non-meningitis South African infants and children as controls, and (3) neurological controls from the Netherlands. A total of 16 NMR-derived CSF metabolites were identified, which clearly differentiated between the controls and TBM cases under investigation. The defining metabolites were the combination of perturbed glucose and highly elevated lactate, common to some other neurological disorders. The remaining 14 metabolites of the host's response to TBM were likewise mainly energy-associated indicators. We subsequently generated a hypothesis expressed as an "astrocyte-microglia lactate shuttle" (AMLS) based on the host's response, which emerged from the NMR-metabolomics information. Activation of microglia, as implied by the AMLS hypothesis, does not, however, present a uniform process and involves intricate interactions and feedback loops between the microglia, astrocytes and neurons that hamper attempts to construct basic and linear cascades of cause and effect; TBM involves a complex integration of the responses from the various cell types present within the CNS, with microglia and the astrocytes as main players.

Pattern recognition and biomarker validation using quantitative1H-NMR-based metabolomics

The collection of global metabolic data and their interpretation (both spectral and biochemical) using modern spectroscopic techniques and appropriate statistical approaches, are known as 'metabolic profiling', 'metabonomics' or 'metabolomics'. This review addresses 1H-nuclear magnetic resonance (NMR)-based metabolomic principles and their application in biomedical science, with special emphasis on their potential in translational research in transplantation, oncology, and drug toxicity or discovery. Various steps in metabolomics analysis are described in order to illustrate the types of biological samples, their respective handling and preparation for 1H-NMR analysis; provide a rationale for using pattern-recognition techniques (spectral database concept) versus quantitative 1H-NMR-based metabolomics (metabolite database concept); and identify necessary technological and logistical future developments that will allow 1H-NMR-based metabolomics to become an established tool in biomedical research and patient care.

The 1H NMR profile of healthy dog cerebrospinal fluid

The availability of data for reference values in cerebrospinal fluid for healthy humans is limited due to obvious practical and ethical issues. The variability of reported values for metabolites in human cerebrospinal fluid is quite large. Dogs present great similarities with humans, including in cases of central nervous system pathologies. The paper presents the first study on healthy dog cerebrospinal fluid metabolomic profile using ¹H NMR spectroscopy. A number of 13 metabolites have been identified and quantified from cerebrospinal fluid collected from a group of 10 mix breed healthy dogs. The biological variability as resulting from the relative standard deviation of the physiological concentrations of the identified metabolites had a mean of 18.20% (range between 9.3% and 44.8%). The reported concentrations for metabolites may be used as normal reference values. The homogeneity of the obtained results and the low biologic variability show that the ¹H NMR analysis of the dog’s cerebrospinal fluid is reliable in designing and interpreting clinical and therapeutic trials in dogs with central nervous system pathologies.

The human urine metabolome

Urine has long been a "favored" biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca.

Metabolic changes in patients with aneurysmal subarachnoid hemorrhage apart from perfusion deficits: neuronal mitochondrial injury?

BACKGROUND AND PURPOSE

Neuronal damage in aSAH apart from perfusion deficits has been widely discussed. We aimed to test if cerebral injury occurs in aSAH independently from visible perfusion deficit by measuring cerebral metabolites in patients with aSAH without infarction or impaired perfusion.

MATERIALS AND METHODS

We performed 3T MR imaging including (1)H-MR spectroscopy, DWI, and MR perfusion in 58 patients with aSAH and 11 age-matched and sex-matched control patients with incidental aneurysm. We compared changes of NAA, Cho, Glx, Lac, and Cr between all patients with aSAH and controls, between patients with and without visible perfusion deficit or infarction and controls, and between patients with and without visible perfusion deficit or infarction by using the Wilcoxon signed-rank test.

RESULTS

We found that NAA significantly (P < .005) decreased in all patients with aSAH. Cho was significantly increased in all patients compared with controls (P < .05). In patients without impaired perfusion or infarction, Glx was significantly decreased compared with both controls (P = .005) and patients with impaired perfusion or infarction (P = .006).

CONCLUSIONS

The significant decrease of NAA and Glx in patients with aSAH but without impaired perfusion or infarction strongly suggests global metabolic changes independent from visible perfusion deficits that might reflect neuronal mitochondrial injury. Further, impaired perfusion in aSAH seems to induce additional metabolic changes from increasing neuronal stress that might, to some extent, mask the global metabolic changes.

Metabolic fingerprints of serum, brain, and liver are distinct for mice with cerebral and noncerebral malaria: a ¹H NMR spectroscopy-based metabonomic study

Cerebral malaria (CM) is a life-threatening disease in humans caused by Plasmodium falciparum, leading to high mortality. Plasmodium berghei ANKA (PbA) infection in C57Bl/6 mice induces pathologic symptoms similar to that in human CM. However, experimental CM incidence in mice is variable, and there are no known metabolic correlates/fingerprints for the animals that develop CM. Here, we have used (1)H NMR-based metabonomics to investigate the metabolic changes in the mice with CM with respect to the mice that have noncerebral malaria (NCM) of the same batchmates with identical genetic backgrounds and infected simultaneously. The metabolic profile of the infected mice (both CM and NCM) was separately compared with the metabolite profile of uninfected control mice of same genetic background. The objective of this study was to search for metabolic changes/fingerprints of CM and identify the pathways that might be differentially altered in mice that succumbed to CM. The results show that brain, liver, and sera exhibit unique metabolic fingerprints for CM over NCM mice. Some of the major fingerprints are increased level of triglycerides, VLDL-cholesterol in sera of CM mice, and decreased levels of glutamine in the sera concomitant with increased levels of glutamine in the brain of the mice with CM. Moreover, glycerophosphocholine is decreased in both the brain and the liver of animals with CM, and myo-inositol and histamine are increased in the liver of CM mice. The metabolic fingerprints in brain, sera, and liver of mice with CM point toward perturbation in the ammonia detoxification pathway and perturbation in lipid and choline metabolism in CM specifically. The study helps us to understand the severity of CM over NCM and in unrevealing the specific metabolic pathways that are compromised in CM.

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.

Qualitative metabolome analysis of human cerebrospinal fluid by 13C-/12C-isotope dansylation labeling combined with liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry

Metabolome analysis of human cerebrospinal fluid (CSF) is challenging because of low abundance of metabolites present in a small volume of sample. We describe and apply a sensitive isotope labeling LC-MS technique for qualitative analysis of the CSF metabolome. After a CSF sample is divided into two aliquots, they are labeled by (13)C-dansyl and (12)C-dansyl chloride, respectively. The differentially labeled aliquots are then mixed and subjected to LC-MS using Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS). Dansylation offers significant improvement in the performance of chromatography separation and detection sensitivity. Moreover, peaks detected in the mass spectra can be readily analyzed for ion pair recognition and database search based on accurate mass and/or retention time information. It is shown that about 14,000 features can be detected in a 25-min LC-FTICR MS run of a dansyl-labeled CSF sample, from which about 500 metabolites can be profiled. Results from four CSF samples are compared to gauge the detectability of metabolites by this method. About 261 metabolites are commonly detected in replicate runs of four samples. In total, 1132 unique metabolite ion pairs are detected and 347 pairs (31%) matched with at least one metabolite in the Human Metabolome Database. We also report a dansylation library of 220 standard compounds and, using this library, about 85 metabolites can be positively identified. Among them, 21 metabolites have never been reported to be associated with CSF. These results illustrate that the dansylation LC-FTICR MS method can be used to analyze the CSF metabolome in a more comprehensive manner.

Genomic and metabolomic advances in the identification of disease and adverse event biomarkers

Incomplete knowledge of tissue pathogenesis is hampering the identification of biomarkers for the appropriate therapeutic targets to prevent or inhibit disease processes, and the prediction and diagnosis of injury due to disease and adverse events of drug therapy. The revolution in genomics and metabolomics, combined with advanced bioinformatics and computational methods for mining such large, complex data sets, are beginning to provide critical insights into tissue injury. Such results will move us closer to the promise of personalized medicine.

A sample preparation protocol for 1H nuclear magnetic resonance studies of water-soluble metabolites in blood and urine

We describe a general protocol for preparing protein-containing biofluids for (1)H nuclear magnetic resonance (NMR) metabolomic studies. In this protocol, untreated samples are diluted in deuterated solvents to precipitate proteins and recover metabolites quantitated relative to standard reference compounds such as 3-trimethylsilylpropionic acid (TSP) and 2,2-dimethyl-2-silapentane-5-sulfonic acid (DSS). The efficacy of this protocol was tested using a bovine serum albumin/metabolite mix and human serum samples. This sample preparation method can be readily applied to any protein-containing biofluid for (1)H NMR studies.

Rapid etiological classification of meningitis by NMR spectroscopy based on metabolite profiles and host response

Bacterial meningitis is an acute disease with high mortality that is reduced by early treatment. Identification of the causative microorganism by culture is sensitive but slow. Large volumes of cerebrospinal fluid (CSF) are required to maximise sensitivity and establish a provisional diagnosis.

We have utilised nuclear magnetic resonance (NMR) spectroscopy to rapidly characterise the biochemical profile of CSF from normal rats and animals with pneumococcal or cryptococcal meningitis. Use of a miniaturised capillary NMR system overcame limitations caused by small CSF volumes and low metabolite concentrations. The analysis of the complex NMR spectroscopic data by a supervised statistical classification strategy included major, minor and unidentified metabolites.

Reproducible spectral profiles were generated within less than three minutes, and revealed differences in the relative amounts of glucose, lactate, citrate, amino acid residues, acetate and polyols in the three groups. Contributions from microbial metabolism and inflammatory cells were evident. The computerised statistical classification strategy is based on both major metabolites and minor, partially unidentified metabolites. This data analysis proved highly specific for diagnosis (100% specificity in the final validation set), provided those with visible blood contamination were excluded from analysis; 6–8% of samples were classified as indeterminate.

This proof of principle study suggests that a rapid etiologic diagnosis of meningitis is possible without prior culture. The method can be fully automated and avoids delays due to processing and selective identification of specific pathogens that are inherent in DNA-based techniques.

Metabolomics tools for identifying biomarkers for neuropsychiatric diseases

The repertoire of biochemicals (or small molecules) present in cells, tissue, and body fluids is known as the metabolome. Today, clinicians utilize only a very small part of the information contained in the metabolome, as revealed by the quantification of a limited set of analytes to gain information on human health. Examples include measuring glucose or cholesterol to monitor diabetes and cardiovascular health, respectively. With a focus on comprehensively studying the metabolome, the rapidly growing field of metabolomics captures the metabolic state of organisms at the global or "-omics" level. Given that the overall health status of an individual is captured by his or her metabolic state, which is a reflection of what has been encoded by the genome and modified by environmental factors, metabolomics has the potential to have a great impact upon medical practice by providing a wealth of relevant biochemical data. Metabolomics promises to improve current, single metabolites-based clinical assessments by identifying metabolic signatures (biomarkers) that embody global biochemical changes in disease, predict responses to treatment or medication side effects (pharmachometabolomics). State of the art metabolomic analytical platforms and informatics tools are being used to map potential biomarkers for a multitude of disorders including those of the central nervous system (CNS). Indeed, CNS disorders are linked to disturbances in metabolic pathways related to neurotransmitter systems (dopamine, serotonin, GABA and glutamate); fatty acids such as arachidonic acid-cascade; oxidative stress and mitochondrial function. Metabolomics tools are enabling us to map in greater detail perturbations in many biochemical pathways and links among these pathways this information is key for development of biomarkers that are disease-specific. In this review, we elaborate on some of the concepts and technologies used in metabolomics and its promise for biomarker discovery. We also highlight early findings from metabolomic studies in CNS disorders such as schizophrenia, Major Depressive Disorder (MDD), Bipolar Disorder (BD), Amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD).

Metabolomics of cancer

Metabolomics, one of the "omic" sciences in systems biology, is the global assessment and validation of endogenous small-molecule biochemicals (metabolites) within a biologic system. Initially, putative quantitative metabolic biomarkers for cancer detection and/or assessment of efficacy of anticancer treatment are usually discovered in a preclinical setting (using animal and human cell cultures), followed by translational validation of these biomarkers in biofluid or tumor tissue. Based on the tumor origin, various biofluids, such as blood, urine, and expressed prostatic secretions, can be used for validating metabolic biomarkers noninvasively in cancer patients. Metabolite detection and quantification is usually carried out by nuclear magnetic resonance (NMR) spectroscopy, while mass spectrometry (MS) provides another highly sensitive metabolomics technology. Usually, sophisticated statistical analyses are carried out either on spectroscopic or on quantitative metabolic data sets to provide meaningful information about the metabolic makeup of the sample. Various metabolic biomarkers, related to glycolysis, mitochondrial citric cycle acid, choline and fatty acid metabolism, were recently reported to play important roles in cancer development and responsiveness to anticancer treatment using NMR-based metabolic profiling.Carefully designed and validated protocols for sample handling and sample extraction followed by appropriate NMR techniques and statistical analyses, which are required to establish quantitative (1)H-NMR-based metabolomics as a reliable analytical tool in the area of cancer biomarker discovery, are discussed in the present chapter.

Metabolomics: a global biochemical approach to the study of central nervous system diseases

Metabolomics, the omics science of biochemistry, is a global approach to understanding regulation of metabolic pathways and metabolic networks of a biological system. Metabolomics complements data derived from genomics, transcriptomics, and proteomics to assist in providing a systems approach to the study of human health and disease. In this review we focus on applications of metabolomics for the study of diseases of the nervous system. We share concepts in metabolomics, tools used in metabolic profiling and early findings from the study of neuropsychiatric diseases, and drugs used to treat these diseases. Metabolomics emerges as another powerful tool in central nervous system research.

Metabolomics: a global biochemical approach to drug response and disease

Metabolomics is the study of metabolism at the global level. This rapidly developing new discipline has important potential implications for pharmacologic science. The concept that metabolic state is representative of the overall physiologic status of the organism lies at the heart of metabolomics. Metabolomic studies capture global biochemical events by assaying thousands of small molecules in cells, tissues, organs, or biological fluids-followed by the application of informatic techniques to define metabolomic signatures. Metabolomic studies can lead to enhanced understanding of disease mechanisms and to new diagnostic markers as well as enhanced understanding of mechanisms for drug or xenobiotic effect and increased ability to predict individual variation in drug response phenotypes (pharmacometabolomics). This review outlines the conceptual basis for metabolomics as well as analytical and informatic techniques used to study the metabolome and to define metabolomic signatures. It also highlights potential metabolomic applications to pharmacology and clinical pharmacology.

Piecewise multivariate modelling of sequential metabolic profiling data

Background

Modelling the time-related behaviour of biological systems is essential for understanding their dynamic responses to perturbations. In metabolic profiling studies, the sampling rate and number of sampling points are often restricted due to experimental and biological constraints.

Results

A supervised multivariate modelling approach with the objective to model the time-related variation in the data for short and sparsely sampled time-series is described. A set of piecewise Orthogonal Projections to Latent Structures (OPLS) models are estimated, describing changes between successive time points. The individual OPLS models are linear, but the piecewise combination of several models accommodates modelling and prediction of changes which are non-linear with respect to the time course. We demonstrate the method on both simulated and metabolic profiling data, illustrating how time related changes are successfully modelled and predicted.

Conclusion

The proposed method is effective for modelling and prediction of short and multivariate time series data. A key advantage of the method is model transparency, allowing easy interpretation of time-related variation in the data. The method provides a competitive complement to commonly applied multivariate methods such as OPLS and Principal Component Analysis (PCA) for modelling and analysis of short time-series data.

New strategies to identify molecular markers predicting chemotherapy activity and toxicity in breast cancer

Despite significant improvements in the treatment and outcomes of early-stage breast cancer, the quest continues to find biological and molecular markers that would enable earlier diagnosis or better prediction of treatment efficacy and toxicity. Metabolomics--the latest and one of the most exciting of the 'omic' sciences--has shown early promise as a non-invasive diagnostic aid in ovarian cancer, and may allow the detection of subtle metabolic changes that could have diagnostic, prognostic or predictive value in breast cancer. Routine monitoring of circulating tumour cells (CTCs) has also been advocated as a novel means of detecting breast cancer progression earlier, and identifying alterations in tumour cells that might signal the need for therapy changes. Ongoing studies should help to answer important questions relating to the use of metabolomics and CTC evaluation as new strategies to monitor cancer progression and identify markers of chemotherapy activity and toxicity.

Metabolomic investigation of CLN6 neuronal ceroid lipofuscinosis in affected South Hampshire sheep

The neuronal ceroid lipofuscinoses (NCLs; Batten disease) are a group of fatal inherited neurodegenerative diseases in humans and animals distinguished by a common clinical pathology, characteristic storage body accumulation in cells, and gross brain atrophy. An (1)H NMR spectroscopy- and GC-MS-based metabolomic investigation of changes in the cerebellum, frontal and occipital lobes, and cerebrospinal fluid (CSF) of CLN6 NCL affected South Hampshire sheep charted changes from the preclinical state to advanced disease. Glutamine and succinate concentrations increased in all brain regions in affected sheep relative to controls, whereas concentrations of aspartate, acetate, glutamate, N-acetyl aspartate (NAA), and gamma-aminobutyric acid (GABA) decreased. Changes in the concentrations of inositols, NAA, and GABA were consistent with glial cell activation and neurodegeneration beginning in the frontal and occipital lobes, in agreement with previous histopathological data. Further metabolic deficits were defined in all regions at earlier time points, including the cerebellum, where very little neurological degeneration has been reported. Biochemical abnormalities in the CSF of affected sheep at 18-31 months include relative increases in lactate, acetate, tyrosine, and creatine/creatinine concentrations and decreases in myo- and scyllo-inositol and citrate concentrations. The changes detected in the CSF and brain tissue mirrored those previously apparent in NCL mouse models, suggesting that they are common to all NCLs. However, the changes in glutamate and glutamine concentrations in CSF occurred after clinical disease, indicating that any changes in glutamate/glutamine cycling occur as a consequence of the primary deficits associated with the NCLs.

Metabolomic mapping of atypical antipsychotic effects in schizophrenia

Schizophrenia is associated with impairments in neurotransmitter systems and changes in neuronal membrane phospholipids. Several atypical antipsychotic drugs induce weight gain and hypertriglyceridemia. To date, there has not been a comprehensive evaluation and mapping of global lipid changes in schizophrenia, and upon treatment with antipsychotics. Such mapping could provide novel insights about disease mechanisms and metabolic side effects of therapies used for its treatment. We used a specialized metabolomics platform 'lipidomics' that quantifies over 300 polar and nonpolar lipid metabolites (across seven lipid classes) to evaluate global lipid changes in schizophrenia and upon treatment with three commonly used atypical antipsychotics. Lipid profiles were derived for 50 patients with schizophrenia before and after treatment for 2-3 weeks with olanzapine (n=20), risperidone (n=14) or aripiprazole (n=16). Patients were recruited in two cohorts (study I, n=27 and study II, n=23) to permit an internal replication analyses. The change from baseline to post-treatment was then compared among the three drugs. Olanzapine and risperidone affected a much broader range of lipid classes than aripiprazole. Approximately 50 lipids tended to be increased with both risperidone and olanzapine and concentrations of triacylglycerols increased and free fatty acids decreased with both drugs but not with aripiprazole. Phosphatidylethanolamine concentrations that were suppressed in patients with schizophrenia were raised by all three drugs. Drug specific differences were also detected. A principal component analysis (PCA) identified baseline lipid alterations, which correlated with acute treatment response. A more definitive long-term randomized study of these drugs correlating global lipid changes with clinical outcomes could yield biomarkers that define drug-response phenotypes.

Lactate Contents From Cerebrospinal Fluid in Experimental Subarachnoid Hemorrhage, Well Correlate With Vasospasm

The role of lactate composition of cerebrospinal fluid (CSF) with vasospasm severity and rabbit neurologic status in subarachnoid hemorrhage was determined. The neurologic status of 20 New Zealand rabbits were graded initially and then, anesthetized and basal angiograms were performed. Then 1.0 mL of CSF was withdrawn through cisterna magna and then 1 mL autologous arterial blood was injected in all rabbits over 1 minute. After 5 days, neurologic severity score (NSS) and vertebrobasilar angiograms of all rabbits were repeated. Rabbits without radiologic vasospasm or spasm under 50% (n=7) were termed as group 1. Rabbits whose cerebral vasospasm were 50% or over 50% (n=7) and NSS is lesser than 3 were termed as groups 2, and rabbits whose cerebral vasospasm were 50% or above 50% (n=7) and NSS is greater than 3 were termed groups 3. On day 7, the CSF lactate values of each group were significantly different (P<0.05) with each other. But when compared with only CSF baseline lactate values groups 2 and 3 were significantly different (P<0.05). However, the NSSs were similar in groups 1 and 2, but group 3 significantly differed from groups 1 and 2 (P<0.05). All groups significantly differed from baseline NSSs (P<0.05). The data showed clearly that the degree of vasospasm correlates not only with neurologic status but also with CSF lactate levels. We suggest that CSF lactate level may be useful as a surrogate marker of cerebral vasospasm degree after subarachnoid hemorrhage in clinics where invasive cerebral angiography could not be assessed for whatever reasons.

A preliminary metabolomic analysis of older adults with and without depression

BACKGROUND

Metabolomics, the global science of biochemistry, is an emerging field that enables detection and quantification of small molecules involved in metabolic and signaling pathways. Metabolic signatures for disease and its treatment could provide valuable biomarkers and insights about disease mechanisms. In this pilot study, we evaluate the potential of metabolomics in the study of older depressed patients.

METHODS

We performed a metabolomic analysis of blood plasma from nine depressed, 11 remitted, and ten never-depressed older adults. Approximately 800 metabolites were analyzed, with comparisons made among the three groups.

RESULTS

Metabolites that were altered in currently depressed patients when compared with controls included several fatty acids, glycerol and gamma-aminobutyric acid (GABA). Analyses comparing concentrations in remitted and currently depressed patients revealed a pattern of metabolite alterations similar to the control vs currently depressed analyses. One difference observed in the remitted patients relative to the depressed patients was elevation of the concentration of the ketone 3-hydroxybutanoic acid.

CONCLUSION

These observations suggest that the depressed state may be associated with alterations in the metabolism of lipids and neurotransmitters, and that treatment with antidepressants adjusts some of the aberrant pathways in disease so that the patients in remission have a metabolic profile more similar to controls than to the depressed population. These results will need to be examined and validated in larger longitudinal cohorts.

Metabonomics in pharmaceutical R&D

This minireview is based on a lecture given at the First Maga Circe Conference on metabolomics held at Sabaudia, Italy, in March 2006 in which the analytical and statistical techniques used in metabonomics, efforts at standardization and some of the major applications to pharmaceutical research and development are reviewed. Metabonomics involves the determination of multiple metabolites simultaneously in biofluids, tissues and tissue extracts. Applications to preclinical drug safety studies are illustrated by the Consortium for Metabonomic Toxicology, a collaboration involving several major pharmaceutical companies. This consortium was able, through the measurement of a dataset of NMR spectra of rodent urine and serum samples, to build a predictive expert system for liver and kidney toxicity. A secondary benefit was the elucidation of the endogenous biochemicals responsible for the classification. The use of metabonomics in disease diagnosis and therapy monitoring is discussed with an exemplification from coronary artery disease, and the concept of pharmaco-metabonomics as a way of predicting an individual's response to treatment is exemplified. Finally, some advantages and perceived difficulties of the metabonomics approach are summarized.

Diagnosing diabetic nephropathy by 1H NMR metabonomics of serum

OBJECT

The most severe complication of type 1 diabetes (T1DM) is diabetic nephropathy. It is associated with a high risk of cardiovascular complications and premature death and requires early detection to be efficiently treated. The clinical practice to diagnose diabetic nephropathy is also a non-optimal and tedious set up based on albumin excretion rate in multiple overnight or 24h urine samples. Conversely, in this study, these independent diagnostic data are used to provide a realistic testing case for applying (1)H NMR metabonomics of serum in a diagnostic fashion.

MATERIALS AND METHODS

182 T1DM and 21 non-diabetic (non-T1DM) individuals were studied. The (1)H NMR of serum at 500 MHz was targeted at two molecular windows: lipoprotein lipids and low-molecular-weight metabolites.

RESULTS

T1DM and non-T1DM individuals were exclusively separated by (1)H NMR. For diabetic nephropathy diagnosis in the T1DM patients, (1)H NMR data (and clinical biochemistry data) gave a sensitivity of 87.1% (83.9%) and a specificity of 87.7% (95.9%). The predictive values of positive and negative tests were 89.0% (95.5%) and 83.6% (79.2%), respectively.

CONCLUSIONS

(1)H NMR metabonomics clearly distinguishes metabolic characteristics of T1DM and appears approximately as good a means to diagnose diabetic nephropathy from serum as an advanced set of biochemical variables.

Brain metabolic markers reflect susceptibility status in cytokine gene knockout mice with murine cerebral malaria

Treatment of cerebral malaria, a complication of the world's most significant parasitic disease, remains problematic due to lack of understanding of its pathogenesis. Metabolic changes, along with cytokine expression alterations and blood cell sequestration in the brain, have previously been reported during severe disease in human infection and mouse models leading to the "cytopathic hypoxia" and "sequestration" theories of pathogenesis. Here, to determine the robustness of the metabolic changes and their relationship to disease development, we investigated changes in cerebral metabolic markers in a mouse model of cerebral malaria (CM) in wildtype (C57BL/6) and cytokine knockout (TNF(-/-), IFNgamma(-/-) and LTalpha(-/-)) mice using multinuclear magnetic resonance spectroscopy. Mice susceptible to CM (wildtype, TNF(-/-)) showed decreased cerebral glucose use, decreased Krebs cycle metabolism and decreased high-energy phosphates. Conversely, mice resistant to CM (IFNgamma(-/-), LTalpha(-/-)) showed little sign of these effects, despite identical levels of parasitemia. Previously reported changes in lactate were shown to be strain dependent. Elevated glutamine and decreased phosphorylation potential emerged as robust metabolic markers of susceptibility, further implicating the trytophan/NAD(+) pathway in disease development. Thus these metabolic changes are firmly linked both to the immune system response to malaria and to the occurrence of pathogenic changes in experimental CM.

Metabolic profiling of CSF: evidence that early intervention may impact on disease progression and outcome in schizophrenia

BACKGROUND

The identification of schizophrenia biomarkers is a crucial step towards improving current diagnosis, developing new presymptomatic treatments, identifying high-risk individuals and disease subgroups, and assessing the efficacy of preventative interventions at a rate that is not currently possible.

METHODS AND FINDINGS

(1)H nuclear magnetic resonance spectroscopy in conjunction with computerized pattern recognition analysis were employed to investigate metabolic profiles of a total of 152 cerebrospinal fluid (CSF) samples from drug-naïve or minimally treated patients with first-onset paranoid schizophrenia (referred to as "schizophrenia" in the following text) and healthy controls. Partial least square discriminant analysis showed a highly significant separation of patients with first-onset schizophrenia away from healthy controls. Short-term treatment with antipsychotic medication resulted in a normalization of the disease signature in over half the patients, well before overt clinical improvement. No normalization was observed in patients in which treatment had not been initiated at first presentation, providing the first molecular evidence for the importance of early intervention for psychotic disorders. Furthermore, the alterations identified in drug-naïve patients could be validated in a test sample set achieving a sensitivity and specificity of 82% and 85%, respectively.

CONCLUSIONS

Our findings suggest brain-specific alterations in glucoregulatory processes in the CSF of drug-naïve patients with first-onset schizophrenia, implying that these abnormalities are intrinsic to the disease, rather than a side effect of antipsychotic medication. Short-term treatment with atypical antipsychotic medication resulted in a normalization of the CSF disease signature in half the patients well before a clinical improvement would be expected. Furthermore, our results suggest that the initiation of antipsychotic treatment during a first psychotic episode may influence treatment response and/or outcome.

Metabolic profiling of patients with schizophrenia

Kaddurah-Daouk discusses a new study that found that patients with schizophrenia have an abnormal cerebrospinal fluid composition. In half of the patients, the composition returned to normal with antipsychotic therapy.

Application of proton nuclear magnetic resonance spectroscopy to the study of Cryptococcus and cryptococcosis

Proton nuclear magnetic resonance spectroscopy is a nondestructive technique that identifies chemicals in solution and in living cells. It has been used in cryptococcal research to identify the primary structure of capsular glucuronoxylomannans, link cellular apoptosis susceptibility (CAS) genes to positioning of residues on the mannose backbone of glucuronoxylomannan, and verify that the cryptococcal virulence determinant, phospholipase B, is elaborated in vivo. Promising clinical applications include speciation (Cryptococcus neoformans and Cryptococcus gattii), with preliminary evidence that varieties neoformans and grubii can also be distinguished, non-invasive diagnosis of cerebral cryptococcomas, and, in cases of meningitis, monitoring therapeutic response by analysis of cerebrospinal fluid.

Metabonomics techniques and applications to pharmaceutical research & development

In this review, the background to the approach known as metabonomics is provided, giving a brief historical perspective and summarizing the analytical and statistical techniques used. Some of the major applications of metabonomics relevant to pharmaceutical Research & Development are then reviewed including the study of various influences on metabolism, such as diet, lifestyle, and other environmental factors. The applications of metabonomics in drug safety studies are explained with special reference to the aims and achievements of the Consortium for Metabonomic Toxicology. Next, the role that metabonomics might have in disease diagnosis and therapy monitoring is provided with some examples, and the concept of pharmacometabonomics as a way of predicting an individual's response to treatment is highlighted. Some discussion is given on the strengths and weaknesses, opportunities of, and threats to metabonomics.

Immunopathogenesis of cerebral malaria

Malaria is one of the most important global health problems, potentially affecting more than one third of the world's population. Cerebral malaria (CM) is a deadly complication of Plasmodium falciparum infection, yet its pathogenesis remains incompletely understood. In this review, we discuss some of the principal pathogenic events that have been described in murine models of the disease and relate them to the human condition. One of the earliest events in CM pathogenesis appears to be a mild increase in the permeability to protein of the blood-brain barrier. Recent studies have shown a role for CD8+T cells in mediating damage to the microvascular endothelium and this damage can result in the leakage of cytokines, malaria antigens and other potentially harmful molecules across the blood-brain barrier into the cerebral parenchyma. We suggest that this, in turn, leads to the activation of microglia and the activation and apoptosis of astrocytes. The role of hypoxia in the pathogenesis of cerebral malaria is also discussed, with particular reference to the local reduction of oxygen consumption in the brain as a consequence of vascular obstruction, to cytokine-driven changes in glucose metabolism, and to cytopathic hypoxia. Interferon-gamma, a cytokine known to be produced in malaria infection, induces increased expression, by microvascular endothelial cells, of the haem enzyme indoleamine 2,3-dioxygenase, the first enzyme in the kynurenine pathway of tryptophan metabolism. Enhanced indoleamine 2,3-dioxygenase expression leads to increased production of a range of biologically active metabolites that may be part of a tissue protective response. Damage to astrocytes may result in reduced production of the neuroprotectant molecule kynurenic acid, leading to a decrease in its ratio relative to the neuroexcitotoxic molecule quinolinic acid, which might contribute to some of the neurological symptoms of cerebral malaria. Lastly, we discuss the role of other haem enzymes, cyclooxygenase-2, inducible nitric oxide synthase and haem oxygenase-1, as potentially being components of mechanisms that protect host tissue against the effects of cytokine- and leukocyte-mediated stress induced by malaria infection.

Huntington disease patients and transgenic mice have similar pro-catabolic serum metabolite profiles

There has been considerable progress recently towards developing therapeutic strategies for Huntington's disease (HD), with several compounds showing beneficial effects in transgenic mouse models. However, human trials in HD are difficult, costly and time-consuming due to the slow disease course, insidious onset and patient-to-patient variability. Identification of molecular biomarkers associated with disease progression will aid the development of effective therapies by allowing further validation of animal models and by providing hopefully more sensitive measures of disease progression. Here, we apply metabolic profiling by gas chromatography-time-of-flight-mass spectrometry to serum samples from human HD patients and a transgenic mouse model in a hypothesis-generating search for disease biomarkers. We observed clear differences in metabolic profiles between transgenic mice and wild-type littermates, with a trend for similar differences in human patients and control subjects. Thus, the metabolites responsible for distinguishing transgenic mice also comprised a metabolic signature tentatively associated with the human disease. The candidate biomarkers composing this HD-associated metabolic signature in mouse and humans are indicative of a change to a pro-catabolic phenotype in early HD preceding symptom onset, with changes in various markers of fatty acid breakdown (including glycerol and malonate) and also in certain aliphatic amino acids. Our data raise the prospect of a robust molecular definition of progression of HD prior to symptom onset, and if validated in a genuinely prospective fashion these biomarker trajectories could facilitate the development of useful therapies for this disease.

An NMR metabolomic investigation of early metabolic disturbances following traumatic brain injury in a mammalian model

The effects of traumatic brain injury (TBI) on brain chemistry and metabolism were examined in three groups of rats using high-resolution (1)H NMR metabolomics of brain tissue extracts and plasma. Brain injury in the TBI group (n = 6) was produced by lateral fluid percussion and regional changes in brain metabolites were analyzed at 1 h after injury in hippocampus, cortex and plasma and compared with changes in both a sham-surgery control group (n = 6) and an untreated control group (n = 6). Evidence was found of oxidative stress (e.g. decreases in ascorbate of 16.4% (p<0.01) and 29.7% (p<0.05) in cortex and hippocampus, respectively) in TBI rats versus the untreated control group, as well as excitotoxic damage (e.g. decreases in glutamate of 14.7% (p<0.05) and 12.3% (p<0.01) in the cortex and hippocampus, respectively), membrane disruption (e.g. decreases in the total level of phosphocholine and glycerophosphocholine of 23.0% (p<0.01) and 19.0% (p<0.01) in the cortex and hippocampus, respectively) and neuronal injury (e.g. decreases in N-acetylaspartate of 15.3% (p<0.01) and 9.7% (p>0.05) in the cortex and hippocampus, respectively). Significant changes in the overall pattern of NMR-observable metabolites using principal components analysis were also observed in TBI animals. Although TBI clearly had an effect on the metabolic profile found in brain tissue, no clear effects could be discerned in plasma samples. This was at least partly due to large variability in dominant glucose and lactate peaks in plasma. However, disruption of the blood-brain barrier and the subsequent movement of metabolites from brain into blood may have been relatively small and below the detection limits of our analytical procedures. Overall, these data indicate that TBI results in several significant changes in brain metabolism early after trauma and that a metabolomic approach based on (1)H NMR spectroscopy can provide a metabolic profile comprising several metabolite classes and allow for relative quantification of such changes within specific brain regions. The results also provide support for further development and application of metabolomic technologies for studying TBI and for the utilization of multivariate models for classifying the extent of trauma within an individual.

Proton nuclear magnetic resonance-based metabonomics for rapid diagnosis of meningitis and ventriculitis

BACKGROUND

Reduction of mortality associated with bacterial meningitis and postsurgical cerebral ventriculitis is dependent on early diagnosis and institution of appropriate therapy. Metabonomics rapidly defines metabolic profiles of biological fluids through the use of high-throughput analytical techniques combined with statistical pattern recognition tools.

METHODS

Proton nuclear magnetic resonance (1H NMR)-based metabonomics was applied to (1) lumbar cerebrospinal fluid samples collected prospectively from a cohort of patients with bacterial, fungal, or viral meningitis and from control subjects without neurological disease and (2) ventricular cerebrospinal fluid samples from patients with ventriculitis associated with an external ventricular drain and from control subjects. 1H NMR spectra were analyzed by the unsupervised statistical method of principal components analysis.

RESULTS

Metabonomic analysis clearly distinguished patients with bacterial or fungal meningitis (11 patients) from patients with viral meningitis (12) and control subjects (27) and clearly distinguished patients with postsurgical ventriculitis (5) from postsurgical control subjects (10). Metabolites of microbial and host origin that were responsible for class separation were determined. Metabonomic data also correlated with the onset and course of infection in a patient with 2 episodes of bacterial ventriculitis and with response to therapy in another patient with cryptococcal meningitis.

CONCLUSIONS

Metabonomic analysis is rapid, requires minimal sample processing, and is not targeted to specific microbial pathogens, making the platform potentially suitable for use in the diagnostic laboratory. This pilot study indicates that metabonomic analysis of cerebrospinal fluid is feasible and a potentially more powerful diagnostic tool than conventional rapid laboratory indicators for distinguishing bacterial from viral meningitis and for monitoring therapy. This should have important implications for early management, reduced empirical use of antibiotics, and treatment duration.