Clare A. Daykin

Proposed minimum reporting standards for chemical analysis

There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at http://msi-workgroups.sourceforge.net/ or http://Msi-workgroups-feedback@lists.sourceforge.net. Further, community input related to this document can also be provided via this electronic forum.

Summary recommendations for standardization and reporting of metabolic analyses.

The Standard Metabolic Reporting Structures (SMRS) working group outlines its vision for an open,community-driven specification for the standardization and reporting of metabolic studies.The Standard Metabolic Reporting Structures (SMRS) working group outlines its vision for an open,community-driven specification for the standardization and reporting of metabolic studies.

Standard reporting requirements for biological samples in metabolomics experiments: mammalian/in vivo experiments

With the increasing production of metabolomic data there is an awareness of a need for a standardised description of this data to aid assessment, exchange, storage and curation of information from metabolomic studies. In this manuscript the first draft of a minimum requirement for the description of the biological context of a metabolomic study involving mammalian subjects is described. This recommendation has been produced by the Metabolomics Standards Initiative–Mammalian Context Working Sub-Group (MSI-MCWSG) as part of the wider standardisation initiative led by the Metabolomics society. The experiments considered include functional genomic studies, drug toxicology, nutrigenomics, clinical trials, and other human studies. Two reporting requirements are described for pre-clinical (e.g. functional genomics, toxicology) and clinical (e.g. clinical trials, nutrigenomics) studies. It is planned that this will lead to the development of a tool for the description of metabolomic experiments that enables storage, retrieval and manipulation of large amounts of data. This will benefit the assessment and dissemination of metabolomic data from mammalian studies.

Study of metabolite composition of eccrine sweat from healthy male and female human subjects by 1H NMR spectroscopy

The aim of the study was to evaluate metabolite variability in human eccrine sweat using a metabonomics based approach. Eccrine sweat is a dilute electrolyte solution whose primary function is to control body temperature via evaporative cooling. Although the composition of sweat is primarily water, previous studies have shown that a diverse array of organic and inorganic compounds are also present. Human eccrine sweat samples from 30 female and 30 male subjects were analysed using high-resolution 1H nuclear magnetic resonance (NMR) spectroscopy in conjunction with statistical pattern recognition. High-resolution 1H NMR spectroscopy produced spectra of the sweat samples that readily identified and quantified many different metabolites. The major metabolite classes found to be present were lactate, amino acids and lipids, with lactate being by far the most dominant metabolite found in all samples. Principal Components Analysis, Principal Components-Discriminant Analysis and Partial Least Squares-Discriminant Analysis of the eccrine sweat samples, revealed no significant differences in metabolite composition and concentration between female and male subjects. Also, the variation between subjects did not appear to be correlated with any other clinical information provided by the subjects. Overall, the spectra data set demonstrates the large physiological variability in terms of number of metabolites present and concentrations between subjects i.e. human eccrine sweat samples exhibit a high degree of inter-individual variability.

Enhanced NMR-based profiling of polyphenols in commercially available grape juices using solid-phase extraction.

Grapes and related products, such as juices, and in particular, their polyphenols, have previously been associated with many health benefits, such as protection against cardiovascular disease. Within grapes, a large range of structurally diverse polyphenols can be present, and their characterisation stands as a challenge. 1H NMR spectroscopy in principle would provide a rapid, nondestructive and straightforward method for profiling of polyphenols. However, polyphenol profiling and identification in grape juices is hindered because of signals of prevailing carbohydrates causing spectral overlap and compromising dynamic range. This study describes the development of an extraction method prior to analysis using 1H NMR spectroscopy, which can, potentially, significantly increase the number of detectable polyphenols and aid their identification, by reduction of signal overlap and selective removal of heavily dominating compounds such as sugars. Copyright

Measurement of ischaemia–reperfusion in patients with intermittent claudication using NMR-based metabonomics

Intermittent claudication has proved to be a good in vivo model for ischaemia–reperfusion. For assessment of ischaemia–reperfusion damage, the known biochemical markers all have disadvantages with respect to sensitivity and interference with other physiological events. In this work, we studied the metabolic effects of ischaemia–reperfusion in patients with intermittent claudication, and the effects of vitamin C and E intervention, using both traditional biochemical measurements and 1H‐NMR‐based metabonomics on urine and plasma. The 1H‐NMR spectra were subjected to multivariate modelling using principal components discriminant analysis, and the observed clusters were validated using joint deployment of univariate analysis of variance and Tukey–Kramer honestly significant difference (HSD) testing. The study involved 14 patients with intermittent claudication and three healthy volunteers, who were monitored during a walking test, before and after a vitamin C/E intervention, and after a washout period. The effect of exercise was only observable for a limited number of biochemical markers, whereas 1H NMR revealed an effect in line with anaerobic ATP production via glycolysis in exercising (ischaemic) muscle of the claudicants. Thus, the beneficial effect of vitamins C and E in claudicants was more pronounced when observed by metabonomics than by traditional biochemical markers. The main effect was more rapid recovery from exercise to resting state metabolism. Furthermore, after intervention, claudicants tended to have lower concentrations of lactate and glucose and several other citric acid cycle metabolites, whereas acetoacetate was increased. The observed metabolic changes in the plasma suggest that intake of vitamin C/E leads to increased muscle oxidative metabolism. Copyright

Data handling for interactive metabolomics: tools for studying the dynamics of metabolome-macromolecule interactions

All published metabolomics studies investigate changes in either absolute or relative quantities of metabolites. However, blood plasma, one of the most commonly studied biofluids for metabolomics applications, is a complex, heterogeneous mixture of lipoproteins, proteins, small organic molecules and ions which together undergo a variety of possible molecular interactions including metal complexation, chemical exchange processes, micellular compartmentation of metabolites, enzyme-mediated biotransformations and small-molecule-macromolecule binding. In particular, many low molecular weight (MW) compounds (including drugs) can exist both ‘free’ in solution and bound to proteins or within organised aggregates of macromolecules. To study the effects of e.g. disease on these interactions we suggest that new approaches are needed. We have developed a technique termed ‘interactive metabolomics’ or i-metabolomics. i-metabolomics can be defined as: “The study of interactions between low MW biochemicals and macromolecules in heterogeneous biosamples such as blood plasma, without pre-selection of the components of interest”. Standard 1D NMR experiments commonly used in metabolomics allow metabolite concentration differences between samples to be investigated because the intensity of each peak depends on the concentration of the compound in question. On the other hand, the instrument can be set-up to measure molecular interactions by monitoring the diffusion coefficients of molecules. According to the Stokes–Einstein equation, the diffusion coefficient of a molecule is inversely proportional to its effective size, as represented by the hydrodynamic radius. Therefore, when low MW compounds are non-covalently bound to proteins, the observed diffusion coefficient for the compound will be intermediate between those of its free and bound forms. By measuring diffusion by NMR, the degree of protein binding can be estimated for either low MW endogenous biochemicals or xenobiotics. This type of experiment is referred to as either Diffusion-Ordered Spectroscopy (DOSY) or Diffusion-Edited Spectroscopy, depending on the type of post-acquisition data processing applied to the spectra. Results presented in this paper demonstrate approaches for the non-selective modelling of metabolite-macromolecule interactions (i-metabolomics), whilst additionally highlighting some of the all too frequently ignored issues associated with interpretation of data derived from profiling of blood plasma.

Nutrimetabolomics: development of a bio-identification toolbox to determine the bioactive compounds in grape juice.

BACKGROUND Grape juice and related products have previously been associated with many health benefits, such as protection against cardiovascular disease. Current consensus is that the polyphenols are the likely bioactive species in these products. RESULTS Extracts of commercially available grape juices exhibited biological antioxidant activities ranging from 19.30 to 3099.51 µM trolox equivalents, as determined by cell-based assay in which J774 macrophages were stimulated with lipopolysaccaride at a concentration of 100 µg/ml for 1 h. Partial least-squares regression was then used to determine covariance between the antioxidant activity and 400 MHz (1)H NMR spectral profiles using models with R(2)X and R(2)Y values of 0.64 and 0.95, respectively, using three latent variables: the Q(2)(cum) was 0.63. Hydroxycinnamic acids and their derivatives were identified as being the most positively correlated with the antioxidant activity. CONCLUSION The work presented here describes a strategy for the bioinformatic linkage of plant metabolomic data with in vitro biological activity as an initial step towards determining structure-activity relationships.

Validation of proteomic biomarkers previously found to be differentially expressed in women with Polycystic Ovary Syndrome: a cross-sectional study

Abstract Objectives: The aim of this study was to independently validate proteomic biomarkers previously reported to be differentially expressed in women with Polycystic Ovary Syndrome (PCOS) compared with controls. This study focused on plasma proteomic biomarkers. Methods: This was a cross-sectional study at the University of Nottingham, in which samples from 30 PCOS and 30 control women were analysed by Western blotting. Results: Mean abundance ratios from Western blots of plasma total haptoglobin and haptoglobin beta proteins were 1.25 (CI 1.11–1.4) and 1.24 (CI 1.04–1.44). The mean abundance ratio from the blots of alpha-2 macroglobulin was however 1.05 (CI, 1–1.1). The mean PCOS/control BMI ratio was 1.18 (CI 1.17–1.20). There was no correlation between PCOS/control BMI ratio and alpha-2 macroglobulin, total haptoglobin and haptoglobin beta abundance ratios. There was also no correlation between PCOS/control insulin ratio and alpha-2 macroglobulin, total haptoglobin and haptoglobin beta abundance ratios. Conclusions: Total haptoglobin and haptoglobin beta chain protein abundance was found to be elevated in women with PCOS compared with controls. We were unable to confirm decreased alpha-2 macroglobulin levels as reported in a previous study. Independent validation studies are required to validate early promising proteomic biomarkers in PCOS.

The Journey From Metabolic Profiling to Biomarkers: The Potential of NMR Spectroscopy Based Metabolomics in Neurodegenerative Disease Research

Neurodegenerative diseases have become a “hot” topic in recent years. A major factor for this is that as life expectancy of the population in developed countries increases, so does the probability of developing neurodegenerative disorders such as Alzheimer’s disease (AD) and Parkinson’s disease (PD), to name the two most well-known. In many cases, however, neurological and mental diseases are poorly understood. In particular, there is a lack of specific biomarkers which would allow early unambiguous identification of a neurodegenerative disease, distinguishing between e.g. AD; PD; PD with dementia; and Dementia with Lewy bodies, or indicating therapeutic effects. Ultimately, this complicates the search for effective treatments. Thus, there is a high demand for preclinical work to elucidate underlying disease mechanisms and pave the way for disease management. In terms of biomarker research, hope has been set on small molecules that participate in metabolism, since they provide a closer link between cellular mechanisms (with genetic as well as environmental inputs) and the disease phenotype. More specifically, it is expected that not one but a combination of several metabolites may serve as an indicator for disease onset and progression, given that neurodegenerative diseases, whilst often described as “idiopathic”, are understood to arise from complex pathologies expressing themselves with a broad spectrum of phenotypes. Therefore, non-targeted metabolic profiling appears to offer great potential for biomarker discovery in this area. One of the major technical platforms for non-targeted metabolic profiling is high resolution nuclear magnetic resonance (NMR) spectroscopy, a technique that is also available for the non-invasive application in vivo. Hence, in theory, biomarker discovery research using NMR spectroscopy based metabolomics provides a promising means for translation from in vitro/ex vivo research to eventual clinical use. This review will therefore discuss the potential for NMR spectroscopy based metabolomics to be applied to biomarker discovery in the field of neurodegenerative disease. Keywords: Brain, metabolites, metabolomics, metabonomics, metabolic profiling, NMR spectroscopy, neurodegenerative diseases. INTRODUCTION Metabolic Profiling of Brain and its Diseases Numerous publications in recent years demonstrate the successful application of metabolic profiling techniques to biofluids and tissues for the purposes of characterising metabolic perturbations associated with diseased states. These include cardiovascular conditions e.g. [1‐4], disorders associated with metabolic syndrome [5-8] and cancer [9] to name but a few. In most cases, multifactorial metabolic changes were identified in those disorders suggestive of the human biocomplexity and indicating that more than just one singular marker is necessary for their comprehension. The application of metabolic profiling techniques to brain diseases has consequently been proposed as a novel approach to shed light onto cellular mechanisms preceding, underlying and following complex neurological and mental conditions. Most of these disorders are incompletely *Address corresponence to this author at the MetaboConsult UK, Heanor, Derbyshire, DE75 7UY, UK; Tel: +44
(0)1773530326;

 E-mail: clare.daykin@metaboconsult.co.uk
 understood, resulting in poor diagnostic accuracy and unsatisfactory disease management [10, 11]. Although often explained as “idiopathic” (of unknown origin), genetic predisposition as well as environmental inputs are believed to contribute to a number of neurodegenerative diseases and psychiatric illnesses expressing themselves in altered gene expressions and proteinaceous states [12, 13]. Given that the metabolic state of a biological system, at least in principle, incorporates both genetic (including transcriptional and proteinaceous) and environmental influences, metabolic profiling techniques, with their power to capture information relating to a great number of metabolites in a single analytical run, should be well placed to aid our understanding of the biochemical perturbations associated with these diseases. It is therefore hoped that this relatively novel approach aids the metabolic characterisation of central nervous system (CNS) diseases and hence, the search for valid biomarkers of brain disease onset, progression or therapeutic effects. Further, given the recent late-development stage failure of several AD drugs from pharmaceutical companies, Pfizer, Johnson & Johnson (J&J) and Elan, in Phase III trials, the potential value of a metabolomics approach within this field is clear [14]. 2213-23 /13