Analysis of chloroformate-derivatised amino acids, dipeptides and polyamines by LC-MS/MS.

A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed which, with sample preparation using a commercially available kit, allows rapid quantitation of 39 chloroformate-derivatised amino acids (AAs), polyamines (PAs) and dipeptides (DPs) in complex biological matrices. Lower limits of quantitation (LOQ) were 20-150nM for putrescine, spermine, spermidine, cadaverine, agmatine, and below 5µM for all analytes. Responses were linear for all analytes between 0.5 and 50µM. Quantitative measurements of all 39 metabolites were achieved within a 15min runtime. The method was evaluated with a Pseudomonas aeruginosa cell extract study (n=24) and a larger human urine study (n=308). Batch effects were observed in the urine study and an investigation of instrument and sample stability showed a wave-like pattern in the MS responses. Both the run order and inter-batch variation were successfully corrected by normalising to pooled urine quality control data. Thus, this method should be suitable for diverse biological matrices and for large as well as small sample sets.

Targeted metabolomics identifies perturbations in amino acid metabolism that sub-classify patients with COPD.

BACKGROUND: COPD, a leading cause of mortality is currently assessed by spirometry (forced expiratory volume in 1 second, FEV(1)). However FEV(1) does not correlate with patient mortality. ECLIPSE (Evaluation of Chronic obstructive pulmonary disease to Longitudinally Identify Predictive Surrogate Endpoints) aims to identify biomarkers that correlate with clinically relevant COPD subtypes, and to assess how these may predict disease progression. New methods were developed and validated to evaluate small molecules as potential diagnostic tools in patients with COPD, COPD related cachexia and cancer related cachexia. METHODS AND FINDINGS: quantitative LC-MS/MS was developed to measure 34 amino acids and dipeptides for stratification of patient groups. Subsets of the ECLIPSE patients were used to assess biomarkers of lung obstruction; GOLD IV (n = 30) versus control (n = 30); emphysema (n = 38) versus airways disease (n = 21) and cachexia (n = 30) versus normal body mass index (n = 30). Serum from cachexic (n = 7) and non-cachexic (n = 5) pancreatic cancer patients were included as controls. Targeted LC-MS/MS distinguished GOLD IV patients from controls, patients with and without emphysema and patients with and without cachexia. Glutamine, aspartate and arginine were significantly increased (p < 0.05; FDR adjustment α < 0.1) in cachexia, emphysema and GOLD IV patients and aminoadipate was decreased. Several amino acid concentrations were significantly altered in patients with COPD but not patients with pancreatic cancer (serine, sarcosine, tryptophan, BCAAs and 3-methylhistdine). Increased γ-aminobutyrate (GABA, p < 0.01) levels were specific to cachexia in patients with pancreatic cancer. ß-aminoisobutyrate, 1-methylhistidine and asparagine (p < 0.05) were common across the patients with cachexia from both the COPD and pancreatic cancer cohorts. CONCLUSION: these results demonstrate that a metabolomic fingerprint has potential to stratify patients for the treatment of COPD and may provide a means of assessing response to therapy. GOLD IV patients were distinguished from smoker control subjects, patients with emphysema were distinguished from those without emphysema and COPD patients displaying cachexia were distinguished from those not displaying cachexia. General markers of cachexia were discovered reflecting both COPD- and pancreatic cancer-related cachexia (increased glutamine, aspartate, arginine, and asparagine and decreased aminoadipate, ß-aminoisobutyrate and 1-methylhistidine). Metabolomic biomarkers, particularly altered levels of GABA, could be exploited as a way of monitoring treatment efficacy and tumour recurrence for patients with pancreatic cancer experiencing cachexia.

Metabolic profiling detects biomarkers of protein degradation in COPD patients.

There is a paucity of biomarkers for chronic obstructive pulmonary disease (COPD). Metabolomics were applied to a defined COPD patient cohort from the ECLIPSE study (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points). Results were correlated with accepted biomarkers for the disease. Baseline control serum (n=66) and Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage II (n=70), III (n=64) and IV (n=44) COPD patients were analysed by proton nuclear magnetic resonance ((1)H NMR). Liquid chromatography with tandem mass spectrometry (LC-MS/MS) was used to confirm amino acid changes detected by (1)H NMR. Data were correlated with body composition, emphysema and systemic inflammation. (1)H NMR identified decreased lipoproteins, N,N-dimethylglycine, and increased glutamine, phenylalanine, 3-methylhistidine and ketone bodies in COPD patients with decreased branched-chain amino acids (BCAAs) observed in GOLD stage IV patients. BCAAs, their degradation products, 3-methylhistidine, ketone bodies, and triglycerides were correlated negatively with cachexia and positively with systemic inflammation. Emphysema patients also displayed decreased serum creatine, glycine and N,N-dimethylglycine. LC-MS/MS confirmed (1)H NMR findings relating to BCAAs, glutamine and 3-methylhistidine in GOLD stage IV patients. NMR-based metabolomics characterised COPD patients based on systemic effects and lung function parameters. Increased protein turnover occurred in all COPD patients with increased protein degradation in individuals with emphysema and cachexia.

Integration of metabolomics and transcriptomics data to aid biomarker discovery in type 2 diabetes.

Type 2 diabetes (T2D), one of the most common diseases in the western world, is characterized by insulin resistance and impaired beta-cell function but currently it is difficult to determine the precise pathophysiology in individual T2D patients. Non-targeted metabolomics technologies have the potential for providing novel biomarkers of disease and drug efficacy, and are increasingly being incorporated into biomarker exploration studies. Contextualization of metabolomics results is enhanced by integration of study data from other platforms, such as transcriptomics, thus linking known metabolites and genes to relevant biochemical pathways. In the current study, urinary NMR-based metabolomic and liver, adipose, and muscle transcriptomic results from the db/db diabetic mouse model are described. To assist with cross-platform integration, integrative pathway analysis was used. Sixty-six metabolites were identified in urine that discriminate between the diabetic db/db and control db/+ mice. The combined analysis of metabolite and gene expression changes revealed 24 distinct pathways that were altered in the diabetic model. Several of these pathways are related to expected diabetes-related changes including changes in lipid metabolism, gluconeogenesis, mitochondrial dysfunction and oxidative stress, as well as protein and amino acid metabolism. Novel findings were also observed, particularly related to the metabolism of branched chain amino acids (BCAAs), nicotinamide metabolites, and pantothenic acid. In particular, the observed decrease in urinary BCAA catabolites provides direct corroboration of previous reports that have inferred that elevated BCAAs in diabetic patients are caused, in part, by reduced catabolism. In summary, the integration of metabolomics and transcriptomics data via integrative pathway mapping has facilitated the identification and contextualization of biomarkers that, presuming further analytical and biological validation, may be useful in future T2D clinical studies by identifying patient populations that share common disease pathophysiology and therefore may identify those patients that may respond better to a particular class of anti-diabetic drugs.

Metabolomic study of the LDL receptor null mouse fed a high-fat diet reveals profound perturbations in choline metabolism that are shared with ApoE null mice.

Failure to express or expression of dysfunctional low-density lipoprotein receptors (LDLR) causes familial hypercholesterolemia in humans, a disease characterized by elevated blood cholesterol concentrations, xanthomas, and coronary heart disease, providing compelling evidence that high blood cholesterol concentrations cause atherosclerosis. In this study, we used (1)H nuclear magnetic resonance spectroscopy to examine the metabolic profiles of plasma and urine from the LDLR knockout mice. Consistent with previous studies, these mice developed hypercholesterolemia and atherosclerosis when fed a high-fat/cholesterol/cholate-containing diet. In addition, multivariate statistical analysis of the metabolomic data highlighted significant differences in tricarboxylic acid cycle and fatty acid metabolism, as a result of high-fat/cholesterol diet feeding. Our metabolomic study also demonstrates that the effect of high-fat/cholesterol/cholate diet, LDLR gene deficiency, and the diet-genotype interaction caused a significant perturbation in choline metabolism, notably the choline oxidation pathway. Specifically, the loss in the LDLR caused a marked reduction in the urinary excretion of betaine and dimethylglycine, especially when the mice are fed a high-fat/cholesterol/cholate diet. Furthermore, as we demonstrate that these metabolic changes are comparable with those detected in ApoE knockout mice fed the same high-fat/cholesterol/cholate diet they may be useful for monitoring the onset of atherosclerosis across animal models.

Multi-platform investigation of the metabolome in a leptin receptor defective murine model of type 2 diabetes.

We describe a multi-platform ((1)H NMR, LC-MS, microarray) investigation of metabolic disturbances associated with the leptin receptor defective (db/db) mouse model of type 2 diabetes using novel assignment methodologies. For the first time, several urinary metabolites were found to be associated with diabetes and/or diabetes progression and confirmed in both NMR and LC-MS datasets. The confirmed metabolites were trimethylamine-n-oxide (TMAO), creatine, carnitine, and phenylalanine. TMAO and phenylalanine were both elevated in db/db mice and decreased in these mice with age. Levels of both creatine and carnitine increase in diabetic mice with age and creatine was also significantly decreased in db/db mice. Additionally, many metabolic markers were found by either NMR or LC-MS, but could not be found in both, due to instrumental limitations. This indicates that the combined use of NMR and LC-MS instrumentation provides complementary information that would be otherwise unattainable. Pathway analyses of urinary metabolites and liver, muscle, and adipose tissue transcripts from the db/db model were also performed to identify altered biochemical processes in the diabetic mice. Metabolite and liver transcript levels associated with the TCA cycle and steroid processes were altered in db/db mice. In addition, gene expression in muscle and liver associated with fatty acid processing was altered in the diabetic mice and similar evidence was observed in the LC-MS data. Our findings highlight the importance of a number of processes known to be associated with diabetes and reveal tissue specific responses to the condition. When studying metabolic disorders such as diabetes, multiple platform integrated profiling of metabolite alterations in biofluids can provide important insights into the processes underlying the disease.

Weighted least-squares deconvolution method for discovery of group differences between complex biofluid 1H NMR spectra.

Biomarker discovery through analysis of high-throughput NMR data is a challenging, time-consuming process due to the requirement of sophisticated, dataset specific preprocessing techniques and the inherent complexity of the data. Here, we demonstrate the use of weighted, constrained least-squares for fitting a linear mixture of reference standard data to complex urine NMR spectra as an automated way of utilizing current assignment knowledge and the ability to deconvolve confounded spectral regions. Following the least-squares fit, univariate statistics were used to identify metabolites associated with group differences. This method was evaluated through applications on simulated datasets and a murine diabetes dataset. Furthermore, we examined the differential ability of various weighting metrics to correctly identify discriminative markers. Our findings suggest that the weighted least-squares approach is effective for identifying biochemical discriminators of varying physiological states. Additionally, the superiority of specific weighting metrics is demonstrated in particular datasets. An additional strength of this methodology is the ability for individual investigators to couple this analysis with laboratory specific preprocessing techniques.

Peak alignment of urine NMR spectra using fuzzy warping.

Proton nuclear magnetic resonance (1H NMR) spectroscopic analysis of mixtures has been used extensively for a variety of applications ranging from the analysis of plant extracts, wine, and food to the evaluation of toxicity in animals. For example, NMR analysis of urine samples has been used extensively for biomarker discovery and, more simply, for the construction of classification models of toxicity, disease, and biochemical phenotype. However, NMR spectra of complex mixtures typically show unwanted local peak shifts caused by matrix and instrument variability, which must be compensated for prior to statistical analysis and interpretation of the data. One approach is to align the spectral peaks across the data set. An efficient and fast warping algorithm is required as the signals typically contain ca. 32,000-64,000 data points and there can be several thousand spectra in a data set. As demonstrated in our study, the iterative fuzzy warping algorithm fulfills these requirements and can be used on-line for an alignment of the NMR spectra. Correlation coefficients between the aligned and target spectra are used as the evaluation function for the algorithm, and its performance is compared with those of other published warping methods.

Tryptophan-NAD+ pathway metabolites as putative biomarkers and predictors of peroxisome proliferation.

The present study was designed to provide further information about the relevance of raised urinary levels of N-methylnicotinamide (NMN), and/or its metabolites N-methyl-4-pyridone-3-carboxamide (4PY) and N-methyl-2-pyridone-3-carboxamide (2PY), to peroxisome proliferation by dosing rats with known peroxisome proliferator-activated receptor alpha (PPARalpha) ligands [fenofibrate, diethylhexylphthalate (DEHP) and long-chain fatty acids (LCFA)] and other compounds believed to modulate lipid metabolism via PPARalpha-independent mechanisms (simvastatin, hydrazine and chlorpromazine). Urinary NMN was correlated with standard markers of peroxisome proliferation and serum lipid parameters with the aim of establishing whether urinary NMN could be used as a biomarker for peroxisome proliferation in the rat. Data from this study were also used to validate a previously constructed multivariate statistical model of peroxisome proliferation (PP) in the rat. The predictive model, based on 1H nuclear magnetic resonance (NMR) spectroscopy of urine, uses spectral patterns of NMN, 4PY and other endogenous metabolites to predict hepatocellular peroxisome count. Each treatment induced pharmacological (serum lipid) effects characteristic of their class, but only fenofibrate, DEHP and simvastatin increased peroxisome number and raised urinary NMN, 2PY and 4PY, with simvastatin having only a transient effect on the latter. These compounds also reduced mRNA expression for aminocarboxymuconate-semialdehyde decarboxylase (ACMSDase, EC 4.1.1.45), the enzyme believed to be involved in modulating the flux of tryptophan through this pathway, with decreasing order of potency, fenofibrate (-10.39-fold) >DEHP (-3.09-fold) >simvastatin (-1.84-fold). Of the other treatments, only LCFA influenced mRNA expression of ACMSDase (-3.62-fold reduction) and quinolinate phosphoribosyltransferase (QAPRTase, EC 2.4.2.19) (-2.42-fold) without any change in urinary NMN excretion. Although there were no correlations between urinary NMN concentration and serum lipid parameters, NMN did correlate with peroxisome count (r2=0.63) and acyl-CoA oxidase activity (r2=0.61). These correlations were biased by the large response to fenofibrate compared to the other treatments; nevertheless the data do indicate a relationship between the tryptophan-NAD+ pathway and PPARalpha-dependent pathways, making this metabolite a potentially useful biomarker to detect PP. In order to strengthen the observed link between the metabolites associated with the tryptophan-NAD+ pathway and more accurately predict PP, other urinary metabolites were included in a predictive statistical model. This statistical model was found to predict the observed PP in 26/27 instances using a pre-determined threshold of 2-fold mean control peroxisome count. The model also predicted a time-dependent increase in peroxisome count for the fenofibrate group, which is important when considering the use of such modelling to predict the onset and progression of PP prior to its observation in samples taken at autopsy.

Integrated metabonomic analysis of the multiorgan effects of hydrazine toxicity in the rat.

Hydrazine is a model toxin that induces both hepatotoxic and neurotoxic effects in experimental animals. The direct biochemical effects of hydrazine in kidney, liver, and brain tissue were assessed in male Sprague-Dawley rats using magic angle spinning nuclear magnetic resonance (NMR) spectroscopy. A single dose of hydrazine (90 mg/kg) resulted in changes to the biochemical composition of the liver after 24 h including an increase in triglycerides and beta-alanine, together with a decrease in hepatic glycogen, glucose, choline, taurine, and trimethylamine-N-oxide (TMAO). From histopathology measurements of liver tissue, minimal to mild hepatocyte alteration was observed in all animals at 24 h. The NMR spectra of the renal cortex at 24 h after dosing were dominated by a marked increase in the tissue concentration of 2-aminoadipate (2-AA) and beta-alanine, concomitant with depletions in TMAO, myo-inositol, choline, taurine, glutamate, and lysine. No alteration to the NMR spectral profile of the substantia nigra was observed after hydrazine administration, but perturbations to the relative concentrations of creatine, aspartate, myo-inositol, and N-acetyl aspartate were apparent in the hippocampus of hydrazine-treated animals at 24 h postdose. No overt signs of histopathological toxicity were observed in either the kidney or the brain regions examined. Elevated alanine levels were observed in all tissues indicative of a general inhibition of alanine transaminase activity. By 168 h postdose, NMR spectral profiles of treated rats appeared similar to those of matched controls for all tissue types indicative of recovery from toxic insult.

Effects of feeding and body weight loss on the 1H-NMR-based urine metabolic profiles of male Wistar Han rats: implications for biomarker discovery.

For almost two decades, 1H-NMR spectroscopy has been used as an 'open' system to study the temporal changes in the biochemical composition of biofluids, including urine, in response to adverse toxic events. Many of these in vivo studies have reported changes in individual metabolites and patterns of metabolites that correlated with toxicological changes. However, many of the proposed novel biomarkers are common to a number of different types of toxicity. These may therefore reflect non-specific effects of toxicity, such as weight loss, rather than a specific pathology. A study was carried out to investigate the non-specific effects on urinary metabolite profiles by administering four hepatotoxic compounds, as a single dose, to rats at two dose levels: hydrazine hydrate (0.06 or 0.08 g kg (1)), 1,2-dimethylhydrazine (0.1 or 0.3 g kg (-1)), alpha-napthylisothiocyanate (0.1 or 0.15 g kg(-1)) and carbon tetrachloride (1.58 or 3.16 g kg(-1)). The study included weight-matched control animals along with those that were dosed, which were then 'pair-fed' with the treated animals so they achieved a similar weight loss. The urinary metabolite profiles were investigated over time using 1H-NMR spectroscopy and compared with the pathology from the same animals. The temporal changes were analysed statistically using multivariate statistical data analysis including principal component analysis, partial least squares, parallel factor analysis and Fisher's criteria. A number of metabolites associated with energy metabolism or which are partially dietary in origin, such as creatine, creatinine, tricarboxylic acid (TCA) cycle intermediates, phenylacetylglycine, fumarate, glucose, taurine, fatty acids and N-methylnicotinamide, showed altered levels in the urine of treated and pair-fed animals. Many of these changes correlated well with weight loss. Interestingly, there was no increase in ketone bodies (acetate and beta-hydroxybutyrate), which might be expected if energy metabolism was switched from glycolysis to fatty acid beta-oxidation. In some instances, the metabolites that changed were considered to be non-specific markers of toxicity, but were also identified as markers of a specific type of toxicity. For example, taurine was raised significantly in carbon tetrachloride-treated animals but reduced in the pair-fed group. However, raised urinary bile acid levels were only seen after alpha-napthylisothiocyanate treatment. The methodology, statistical analysis used and the data generated will help improve the identification of specific markers or patterns of urinary markers of specific toxic effects.

Development of a multivariate statistical model to predict peroxisome proliferation in the rat, based on urinary 1H-NMR spectral patterns.

A previous report of this work (Ringeissen et al. 2003) described the use of nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical data analysis (MVDA) to identify novel biomarkers of peroxisome proliferation (PP) in Wistar Han rats. Two potential biomarkers of peroxisome proliferation in the rat were described, N-methylnicotinamide (NMN) and N-methyl-4-pyridone-3-carboxamide (4PY). The inference from these results was that the tryptophan-nicotinamide adenine dinucleotide (NAD(+)) pathway was altered in correlation with peroxisome proliferation, a hypothesis subsequently confirmed by TaqMan analysis of the relevant genes encoding two key enzymes in the pathway, aminocarboxymuconate-semialdehyde decarboxylase (EC 4.1.1.45) and quinolinate phosphoribosyltransferase (EC 2.4.2.19). The objective of the present study was to investigate these data further and identify other metabolites in the NMR spectrum correlating equally with PP. MVDA Partial Least Squares (PLS) models were constructed that provided a better prediction of PP in Wistar Han rats than levels of 4PY and NMN alone. The resulting Wistar Han rat predictive models were then used to predict PP in a test group of Sprague Dawley rats following administration of fenofibrate. The models predicted the presence or absence of PP (above on arbitrary threshold of >2-fold mean control) in all Sprague Dawley rats in the test group.

Potential urinary and plasma biomarkers of peroxisome proliferation in the rat: identification of N-methylnicotinamide and N-methyl-4-pyridone-3-carboxamide by 1H nuclear magnetic resonance and high performance liquid chromatography.

This study identified two potential novel biomarkers of peroxisome proliferation in the rat. Three peroxisome proliferator-activated receptor (PPAR) ligands, chosen for their high selectivity towards the PPARalpha, -delta and -gamma subtypes, were given to rats twice daily for 7 days at doses known to cause a pharmacological effect or peroxisome proliferation. Fenofibrate was used as a positive control. Daily treatment with the PPARalpha and -delta agonists produced peroxisome proliferation and liver hypertrophy. 1H nuclear magnetic resonance spectroscopy and multivariate statistical data analysis of urinary spectra from animals given the PPARalpha and -delta agonists identified two new potential biomarkers of peroxisome proliferation--N-methylnicotinamide (NMN) and N-methyl-4-pyridone-3-carboxamide (4PY)--both endproducts of the tryptophan-nicotinamide adenine dinucleotide (NAD+) pathway. After 7 days, excretion of NMN and 4PY increased 24- and three-fold, respectively, following high doses of fenofibrate. The correlation between total NMN excretion over 7 days and the peroxisome count was r=0.87 (r2=0.76). Plasma NMN, measured using a sensitive high performance liquid chromatography method, was increased up to 61-fold after 7 days' treatment with high doses of fenofibrate. Hepatic gene expression of aminocarboxymuconate-semialdehyde decarboxylase (EC 4.1.1.45) was downregulated following treatment with the PPARalpha and -delta agonists. The decrease was up to 11-fold compared with controls in the groups treated with high doses of fenofibrate. This supports the link between increased NMN and 4PY excretion and regulation of the tryptophan-NAD+ pathway in the liver. In conclusion, NMN, and possibly other metabolites in the pathway, are potential non-invasive surrogate biomarkers of peroxisome proliferation in the rat.

Optimisation of collection, storage and preparation of rat plasma for 1H NMR spectroscopic analysis in toxicology studies to determine inherent variation in biochemical profiles.

Biofluid 1H NMR spectroscopy has been assessed as a tool for toxicological investigations for almost two decades, with most studies focussing on urinary changes. This study has examined variations in the 1H NMR spectroscopy spectra of plasma collected from control rats at different times of the day. The collection, preparation and storage of samples were optimised and potential sources of variation in samples taken for toxicology studies identified. Plasma samples were collected into heparinised containers and analysed following a standard dilution with D(2)O. The value of deproteinising plasma with acetonitrile to look at low molecular weight metabolites has also been assessed. Variations in lactate and citrate levels in whole blood plasma were found and are consistent with the observation that lactate is one of the most variable metabolites in human plasma. Lipids levels also varied, in particular higher levels of lipids were found in spectra from male rats compared to female rats, and in samples collected in the morning following the feeding period. No significant changes were identified in samples which were snap-frozen and stored for up to 9 months at -80 degrees C. More changes were observed after storage at 4 degrees C or room temperature, including an increase in glycerol and choline levels, which may have resulted from lipid hydrolysis.

Application of directly coupled high performance liquid chromatography-NMR-mass spectometry and 1H NMR spectroscopic studies to the investigation of 2,3-benzofuran metabolism in Sprague-Dawley rats.

The urinary excretion of metabolites of 2,3-benzofuran was studied in Sprague-Dawley rats (n = 5) given a single dose of 150 mg/kg i.p. Urine samples were collected at defined intervals up to 7 days postdose and analyzed using (1). H NMR and directly coupled high performance liquid chromatography (HPLC)-NMR, HPLC-(mass spectrometry) MS and HPLC-MS-NMR methods. The principal metabolites were determined to be 2-hydroxyphenylacetic acid and 2-(2-hydroxyethyl)phenyl hydrogen sulfate, representing 24.3 +/- 6.0% and 19.6 +/- 6.4% of the dose, respectively. This indicates that metabolism of benzofuran to the polar species excreted in urine involves cleavage of the furan ring.

Metabonomics: the use of electrospray mass spectrometry coupled to reversed-phase liquid chromatography shows potential for the screening of rat urine in drug development.

The application of liquid chromatography/mass spectrometry (LC/MS) followed by principal components analysis (PCA) has been successfully applied to the screening of rat urine following the administration of three candidate pharmaceuticals. With this methodology it was possible to differentiate the control samples from the dosed samples and to identify the components of the mass spectrum responsible for the separation. These data clearly show that LC/MS is a viable alternative, or complementary, technique to proton NMR for metabonomics applications in drug discovery and development.

The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by (1)H nuclear magnetic resonance spectroscopy.

Blood plasma is the major vehicle by which metabolites are transported around the body in mammalian species, and chemical analysis of plasma can provide a wealth of information relating to the biochemical status of an individual and is important for diagnostic purposes. However, plasma is very complex in physicochemical terms because it is composed of a range of organic and inorganic constituents with a wide range of molecular weights and chemical classes and this makes analysis non-trivial. It is now well established that high-resolution (1)H NMR spectroscopy of blood plasma provides useful qualitative and quantitative biochemical information relating to metabolic disorders. However, one of the problems encountered in NMR spectroscopic analysis of blood plasma is the extensive peak overlap or presence of broad macromolecule peaks in the (1)H NMR spectrum, which can severely limit the amount of obtainable information. Even with spectroscopic editing, information relating to low-molecular-weight (MW) metabolites is frequently lost. Therefore, the efficiency of a range of conventional protein removal methods, in combination with the use of one- and two-dimensional NMR spectroscopic methods for evaluation, have been compared for the extraction of NMR-observable low-MW metabolites. It has been shown that these "deproteinization" methods vary considerably in recovery of low MW metabolites and a judicious choice is crucial for optimal extraction of a given analyte. The results presented here show that while ultrafiltration provides the "safest" method of plasma deproteinization, the signal-to-noise ratio of the resultant (1)H NMR spectra is poor. On the other hand, acetonitrile precipitation at physiological pH allows the detection of more low-MW metabolites and at higher concentrations than any other method and provides the further advantages of being a rapid and simple procedure.