Metabolic Profiling Reveals Changes in Serum Predictive of Venous Ulcer Healing.

OBJECTIVE: The aim of this study was to identify potential biomarkers predictive of healing or failure to heal in a population with venous leg ulceration. SUMMARY BACKGROUND DATA: Venous leg ulceration presents important physical, psychological, social and financial burdens. Compression therapy is the main treatment, but it can be painful and time-consuming, with significant recurrence rates. The identification of a reliable biochemical signature with the ability to identify nonhealing ulcers has important translational applications for disease prognostication, personalized health care and the development of novel therapies. METHODS: Twenty-eight patients were assessed at baseline and at 20 weeks. Untargeted metabolic profiling was performed on urine, serum, and ulcer fluid, using mass spectrometry and nuclear magnetic resonance spectroscopy. RESULTS: A differential metabolic phenotype was identified in healing (n = 15) compared to nonhealing (n = 13) venous leg ulcer patients. Analysis of the assigned metabolites found ceramide and carnitine metabolism to be relevant pathways. In this pilot study, only serum biofluids could differentiate between healing and nonhealing patients. The ratio of carnitine to ceramide was able to differentiate between healing phenotypes with 100% sensitivity, 79% specificity, and 91% accuracy. CONCLUSIONS: This study reports a metabolic signature predictive of healing in venous leg ulceration and presents potential translational applications for disease prognostication and development of targeted therapies.

Enhanced Microbial Bile Acid Deconjugation and Impaired Ileal Uptake in Pregnancy Repress Intestinal Regulation of Bile Acid Synthesis.

Pregnancy is associated with progressive hypercholanemia, hypercholesterolemia, and hypertriglyceridemia, which can result in metabolic disease in susceptible women. Gut signals modify hepatic homeostatic pathways, linking intestinal content to metabolic activity. We sought to identify whether enteric endocrine signals contribute to raised serum bile acids observed in human and murine pregnancies, by measuring fibroblast growth factor (FGF) 19/15 protein and mRNA levels, and 7α-hydroxy-4-cholesten-3-one. Terminal ileal farnesoid X receptor (FXR)-mediated gene expression and apical sodium bile acid transporter (ASBT) protein concentration were measured by qPCR and western blotting. Shotgun whole-genome sequencing and ultra-performance liquid chromatography tandem mass spectrometry were used to determine the cecal microbiome and metabonome. Targeted and untargeted pathway analyses were performed to predict the systemic effects of the altered metagenome and metabolite profiles. Dietary CA supplementation was used to determine whether the observed alterations could be overcome by intestinal bile acids functioning as FXR agonists. Human and murine pregnancy were associated with reduced intestinal FXR signaling, with lower FGF19/15 and resultant increased hepatic bile acid synthesis. Terminal ileal ASBT protein was reduced in murine pregnancy. Cecal bile acid conjugation was reduced in pregnancy because of elevated bile salt hydrolase-producing Bacteroidetes. CA supplementation induced intestinal FXR signaling, which was not abrogated by pregnancy, with strikingly similar changes to the microbiota and metabonome as identified in pregnancy. Conclusion: The altered intestinal microbiota of pregnancy enhance bile acid deconjugation, reducing ileal bile acid uptake and lowering FXR induction in enterocytes. This exacerbates the effects mediated by reduced bile acid uptake transporters in pregnancy. Thus, in pregnant women and mice, there is reduced FGF19/15-mediated hepatic repression of hepatic bile acid synthesis, resulting in hypercholanemia.

Deep Vein Thrombosis Exhibits Characteristic Serum and Vein Wall Metabolic Phenotypes in the Inferior Vena Cava Ligation Mouse Model.

OBJECTIVES: Deep vein thrombosis (DVT) is a major health problem, responsible for significant morbidity and mortality. The identification of a simple and effective diagnostic biomarker of DVT remains a challenge. Metabolomics have recently emerged as a new powerful scientific tool to characterise metabolic phenotypes of complex diseases and investigate small molecules in biofluids. The aim of the study was to identify the blood and vein wall metabolomic signature of DVT in a murine experimental model. METHODS: An established inferior vena cava ligation mouse model of DVT (n=10) was used and compared with sham surgery controls (n=10). Comprehensive untargeted metabolic profiling of serum and vein wall extracts was undertaken using liquid chromatography coupled mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy. RESULTS: Multivariate and univariate statistical analysis demonstrated a differential metabolic profile when comparing DVT mice and control animals. Serum from DVT mice was characterised by differential concentrations of adenosine (decreased in DVT mice 9.6 fold), adenine (decreased 10.6 fold), and tricyclic acid cycle (TCA) intermediates, including citrate, succinate, and fumarate (1.5, 2.3, and 2.8 fold decreases, respectively). l-carnitine was found to be of greater abundance in the serum of DVT animals (67.0 fold change). A number of lipid moiety classes, including sphingomyelins, phosphatidylcholines, and triglycerides, were differentially abundant. Several metabolites were found in vein wall, including acetylcarnitine (increased in DVT mice 1.9 fold), adenosine (increased 2.2 fold), and ceramide (increased 2.7 fold). Correlation analysis illustrated the biochemical relationships between assigned metabolites, with the discriminatory molecules being highly correlated with each other, in both serum and vein wall. CONCLUSIONS: The present findings demonstrate that metabolic dysregulations in DVT centre on energy metabolism, sphingolipid, and adenosine metabolism, representing a DVT specific metabolite signature in a murine experimental model.

Improving Visualization and Interpretation of Metabolome-Wide Association Studies: An Application in a Population-Based Cohort Using Untargeted 1H NMR Metabolic Profiling.

1H NMR spectroscopy of biofluids generates reproducible data allowing detection and quantification of small molecules in large population cohorts. Statistical models to analyze such data are now well-established, and the use of univariate metabolome wide association studies (MWAS) investigating the spectral features separately has emerged as a computationally efficient and interpretable alternative to multivariate models. The MWAS rely on the accurate estimation of a metabolome wide significance level (MWSL) to be applied to control the family wise error rate. Subsequent interpretation requires efficient visualization and formal feature annotation, which, in-turn, call for efficient prioritization of spectral variables of interest. Using human serum 1H NMR spectroscopic profiles from 3948 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), we have performed a series of MWAS for serum levels of glucose. We first propose an extension of the conventional MWSL that yields stable estimates of the MWSL across the different model parameterizations and distributional features of the outcome. We propose both efficient visualization methods and a strategy based on subsampling and internal validation to prioritize the associations. Our work proposes and illustrates practical and scalable solutions to facilitate the implementation of the MWAS approach and improve interpretation in large cohort studies.

Development and Application of Ultra-Performance Liquid Chromatography-TOF MS for Precision Large Scale Urinary Metabolic Phenotyping.

To better understand the molecular mechanisms underpinning physiological variation in human populations, metabolic phenotyping approaches are increasingly being applied to studies involving hundreds and thousands of biofluid samples. Hyphenated ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) has become a fundamental tool for this purpose. However, the seemingly inevitable need to analyze large studies in multiple analytical batches for UPLC-MS analysis poses a challenge to data quality which has been recognized in the field. Herein, we describe in detail a fit-for-purpose UPLC-MS platform, method set, and sample analysis workflow, capable of sustained analysis on an industrial scale and allowing batch-free operation for large studies. Using complementary reversed-phase chromatography (RPC) and hydrophilic interaction liquid chromatography (HILIC) together with high resolution orthogonal acceleration time-of-flight mass spectrometry (oaTOF-MS), exceptional measurement precision is exemplified with independent epidemiological sample sets of approximately 650 and 1000 participant samples. Evaluation of molecular reference targets in repeated injections of pooled quality control (QC) samples distributed throughout each experiment demonstrates a mean retention time relative standard deviation (RSD) of <0.3% across all assays in both studies and a mean peak area RSD of <15% in the raw data. To more globally assess the quality of the profiling data, untargeted feature extraction was performed followed by data filtration according to feature intensity response to QC sample dilution. Analysis of the remaining features within the repeated QC sample measurements demonstrated median peak area RSD values of <20% for the RPC assays and <25% for the HILIC assays. These values represent the quality of the raw data, as no normalization or feature-specific intensity correction was applied. While the data in each experiment was acquired in a single continuous batch, instances of minor time-dependent intensity drift were observed, highlighting the utility of data correction techniques despite reducing the dependency on them for generating high quality data. These results demonstrate that the platform and methodology presented herein is fit-for-use in large scale metabolic phenotyping studies, challenging the assertion that such screening is inherently limited by batch effects. Details of the pipeline used to generate high quality raw data and mitigate the need for batch correction are provided.

Bariatric surgery modulates circulating and cardiac metabolites.

Bariatric procedures such as the Roux-en-Y gastric bypass (RYGB) operation offer profound metabolic enhancement in addition to their well-recognized weight loss effects. They are associated with significant reduction in cardiovascular disease risk and mortality, which suggests a surgical modification on cardiac metabolism. Metabolic phenotyping of the cardiac tissue and plasma postsurgery may give insight into cardioprotective mechanisms. The aim of the study was to compare the metabolic profiles of plasma and heart tissue extracts from RYGB- and sham-operated Wistar rats to identify the systemic and cardiac signature of metabolic surgery. A total of 27 male Wistar rats were housed individually for a week and subsequently underwent RYGB (n = 13) or sham (n = 14) operation. At week 8 postoperation, a total of 27 plasma samples and 16 heart tissue samples (8 RYGB; 8 Sham) were collected from animals and analyzed using (1)H nuclear magnetic resonance (NMR) spectroscopy and ultra performance liquid chromatography (UPLC-MS) to characterize the global metabolite perturbation induced by RYGB operation. Plasma bile acids, phosphocholines, amino acids, energy-related metabolites, nucleosides and amine metabolites, and cardiac glycogen and amino acids were found to be altered in the RYGB operated group. Correlation networks were used to identify metabolite association. The metabolic phenotype of this bariatric surgical model inferred systematic change in both myocardial and systemic activity post surgery. The altered metabolic profile following bariatric surgery reflects an enhancement of cardiac energy metabolism through TCA cycle intermediates, cardiorenal protective activity, and biochemical caloric restriction. These surgically induced metabolic shifts identify some of the potential mechanisms that contribute toward bariatric cardioprotection through gut microbiota ecological fluxes and an enterocardiac axis to shield against metabolic syndrome of cardiac dysfunction.

Endogenous and xenobiotic metabolite profiling of liver extracts from SCID and chimeric humanized mice following repeated oral administration of troglitazone.

1. Metabonomic analysis, via a combination of untargeted and targeted liquid chromatography-mass spectrometry (LC-MS) and untargeted (1)H NMR spectroscopy-based metabolite profiling, was performed on aqueous (AQ) and organic liver extracts from control (SCID) and chimeric humanized (PXB) mice dosed with troglitazone at 0, 300 and 600 mg/kg/day for seven days. 2. LC-MS analysis of AQ liver extracts showed a more "human-like" profile for troglitazone metabolites for PXB, compared with SCID, mice. 3. LC-MS detected differences in endogenous metabolites, particularly lipid species in dosed mice, including elevated triacylglycerols and 1-alkyl,2-acylglycerophosphates as well as lowered diacylglycerophosphocholines and 1-alkyl,2-acylglycerophosphocholines for PXB compared with SCID mouse liver extracts. Following drug administration changes in the relative proportions of the ions for various unsaturated fatty acids were observed for both types of mouse, some of which were specific to PXB or SCID mice. 4. (1)H NMR spectroscopy revealed that AQ PXB mouse liver extracts had elevated amounts of inosine, fumarate, creatine, aspartate, trimethylamine N-oxide, glycerophosphocholine, phosphocholine, choline, glutamine, glutamate, acetate, alanine and lactate relative to SCID mice and decreased histidine, glycogen, α- and ß-glucose, taurine, and glutathione. Increased uracil and tyrosine concentrations were detected for PXB mice on troglitazone administration. 5. Metabonomic profiling thus showed clear differences between humanized and SCID mice, including after administration of troglitazone.

Systemic gut microbial modulation of bile acid metabolism in host tissue compartments.

We elucidate the detailed effects of gut microbial depletion on the bile acid sub-metabolome of multiple body compartments (liver, kidney, heart, and blood plasma) in rats. We use a targeted ultra-performance liquid chromatography with time of flight mass-spectrometry assay to characterize the differential primary and secondary bile acid profiles in each tissue and show a major increase in the proportion of taurine-conjugated bile acids in germ-free (GF) and antibiotic (streptomycin/penicillin)-treated rats. Although conjugated bile acids dominate the hepatic profile (97.0 ± 1.5%) of conventional animals, unconjugated bile acids comprise the largest proportion of the total measured bile acid profile in kidney (60.0 ± 10.4%) and heart (53.0 ± 18.5%) tissues. In contrast, in the GF animal, taurine-conjugated bile acids (especially taurocholic acid and tauro-ß-muricholic acid) dominated the bile acid profiles (liver: 96.0 ± 14.5%; kidney: 96 ± 1%; heart: 93 ± 1%; plasma: 93.0 ± 2.3%), with unconjugated and glycine-conjugated species representing a small proportion of the profile. Higher free taurine levels were found in GF livers compared with the conventional liver (5.1-fold; P < 0.001). Bile acid diversity was also lower in GF and antibiotic-treated tissues compared with conventional animals. Because bile acids perform important signaling functions, it is clear that these chemical communication networks are strongly influenced by microbial activities or modulation, as evidenced by farnesoid X receptor-regulated pathway transcripts. The presence of specific microbial bile acid co-metabolite patterns in peripheral tissues (including heart and kidney) implies a broader signaling role for these compounds and emphasizes the extent of symbiotic microbial influences in mammalian homeostasis.

Microbial-mammalian cometabolites dominate the age-associated urinary metabolic phenotype in Taiwanese and American populations.

Understanding the metabolic processes associated with aging is key to developing effective management and treatment strategies for age-related diseases. We investigated the metabolic profiles associated with age in a Taiwanese and an American population. ¹H NMR spectral profiles were generated for urine specimens collected from the Taiwanese Social Environment and Biomarkers of Aging Study (SEBAS; n = 857; age 54-91 years) and the Mid-Life in the USA study (MIDUS II; n = 1148; age 35-86 years). Multivariate and univariate linear projection methods revealed some common age-related characteristics in urinary metabolite profiles in the American and Taiwanese populations, as well as some distinctive features. In both cases, two metabolites--4-cresyl sulfate (4CS) and phenylacetylglutamine (PAG)--were positively associated with age. In addition, creatine and ß-hydroxy-ß-methylbutyrate (HMB) were negatively correlated with age in both populations (p < 4 × 10⁻6). These age-associated gradients in creatine and HMB reflect decreasing muscle mass with age. The systematic increase in PAG and 4CS was confirmed using ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). Both are products of concerted microbial-mammalian host cometabolism and indicate an age-related association with the balance of host-microbiome metabolism.

Optimizing the use of quality control samples for signal drift correction in large-scale urine metabolic profiling studies.

The evident importance of metabolic profiling for biomarker discovery and hypothesis generation has led to interest in incorporating this technique into large-scale studies, e.g., clinical and molecular phenotyping studies. Nevertheless, these lengthy studies mandate the use of analytical methods with proven reproducibility. An integrated experimental plan for LC-MS profiling of urine, involving sample sequence design and postacquisition correction routines, has been developed. This plan is based on the optimization of the frequency of analyzing identical quality control (QC) specimen injections and using the QC intensities of each metabolite feature to construct a correction trace for all the samples. The QC-based methods were tested against other current correction practices, such as total intensity normalization. The evaluation was based on the reproducibility obtained from technical replicates of 46 samples and showed the feature-based signal correction (FBSC) methods to be superior to other methods, resulting in ~1000 and 600 metabolite features with coefficient of variation (CV) < 15% within and between two blocks, respectively. Additionally, the required frequency of QC sample injection was investigated and the best signal correction results were achieved with at least one QC injection every 2 h of urine sample injections (n = 10). Higher rates of QC injections (1 QC/h) resulted in slightly better correction but at the expense of longer total analysis time.

Technical and biological variation in UPLC-MS-based untargeted metabolic profiling of liver extracts: application in an experimental toxicity study on galactosamine.

The relative importance of technical versus bio-logical variation in UPLC-MS liver metabolic profiling studies was assessed on liver samples collected as part of an in vivo hepatotoxicity study. Biological variability within and between two treatment groups (three rats treated with galactosamine and three with galactosamine+uridine) was compared with sampling/extraction variability (three portions extracted from each rat liver section) and UPLC-MS platform variability (triplicate injections of each extract) for aqueous and organic extracts. The impact of scaling on error measurement was investigated on replicate injections of a quality control sample, and consequently started log-transformation was used to stabilize the variance across the ion intensity range. For aqueous extracts, technical variability was two to four times lower than within group interanimal variability. Similar results were obtained for organic extracts for the galactosamine group, sampling/extraction variability being more elevated in the galactosamine+uridine group. For both extract types, differences between treatment groups were the principal source of observed variation, and triplicate injections clustered closely in PCA plots and in HCA dendrograms, indicating small instrument variability compared to observed biological variation. This protocol can be applied to investigate differences in liver metabolic profiles between animal groups in toxicology studies and clinical investigations of liver disease.

HILIC-UPLC-MS for exploratory urinary metabolic profiling in toxicological studies.

Hydrophilic interaction ultra performance liquid chromatography (HILIC-UPLC) permits the analysis of highly polar metabolites, providing complementary information to reversed-phase (RP) chromatography. HILIC-UPLC-TOF-MS was investigated for the global metabolic profiling of rat urine samples generated in an experimental hepatotoxicity study of galactosamine (galN) and the concomitant investigation of the protective effect of glycine. Within-run repeatability and stability over a large sample batch (>200 samples, 60 h run-time) was assessed through the repeat analysis of a quality control sample. Following system equilibration, excellent repeatability was observed in terms of retention time (CV < 1.7%), signal intensity (CV < 14%), and mass variability (<0.005 amu), providing a good measure of reproducibility. Classification of urinary metabolic profiles according to treatment was observed, with significant changes in specific metabolites after galN exposure, including increased urocanic acid, N-acetylglucosamine, and decreased 2-oxoglutarate. A novel finding from this HILIC-UPLC-MS approach was elevated urinary tyramine in galN-treated rats, reflecting disturbed amino acid metabolism. These results show HILIC-UPLC-MS to be a promising method for global metabolic profiling, demonstrating high within-run repeatability, even over an extended run time. Retention of polar endogenous analytes and xenobiotic metabolites was improved compared with RP studies, including galN, N-acetylglucosamine, oxoglutarate, and urocanic acid, enhancing metabolome coverage and potentially improving biomarker discovery.

Hydrophilic interaction chromatography coupled to MS for metabonomic/metabolomic studies.

Hydrophilic interaction chromatography (HILIC) is a relatively recently introduced mode of liquid-phase separations. Recently, HILIC has been used for coupling to MS in metabonomic/metabolomic studies to provide a complementary tool to the widely used reversed-phase (RP) chromatographic separations. The combination of HILIC with MS detection covers a number of polar metabolites that are typically nonretained in RPLC-mode separations and thus enlarging the number of detected analytes. This way of metabolite profiling thus provides more comprehensive metabolome coverage than using RP chromatography alone. This review describes the applications and the utility of HILIC-MS in metabolomic/metabonomic studies and highlights certain characteristic examples in the life and plant-food sciences.

A systematic review of clinical prediction scores for deep vein thrombosis.

Objective Diagnosis of deep vein thrombosis remains a challenging problem. Various clinical prediction rules have been developed in order to improve diagnosis and decision making in relation to deep vein thrombosis. The purpose of this review is to summarise the available clinical scores and describe their applicability and limitations. Methods A systematic search of PubMed, MEDLINE and EMBASE databases was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance using the keywords: clinical score, clinical prediction rule, risk assessment, clinical probability, pretest probability, diagnostic score and medical Subject Heading terms: 'Venous Thromboembolism/diagnosis' OR 'Venous Thrombosis/diagnosis'. Both development and validation studies were eligible for inclusion. Results The search strategy returned a total of 2036 articles, of which 102 articles met a priori criteria for inclusion. Eight different diagnostic scores were identified. The development of these scores differs in respect of the population included (hospital inpatients, hospital outpatients or primary care patients), the exclusion criteria, the inclusion of distal deep vein thrombosis and the use of D-dimer. The reliability and applicability of the scores in the context of specific subgroups (inpatients, cancer patients, elderly patients and those with recurrent deep vein thrombosis) remains controversial. Conclusion Detailed knowledge of the development of the various clinical prediction scores for deep vein thrombosis is essential in understanding the power, generalisability and limitations of these clinical tools.

A survey on the reactivity of phenyliodonium ylide of 2-hydroxy-1,4-naphthoquinone with amino compounds.

The phenyliodonium ylide of 2-hydroxy-1,4-naphthoquinone reacts with aminoesters, ureas, aminoalcohols and aminophenols in refluxing dichloromethane to afford good yields of indanedione 2-carboxamido compounds, that in solution exist in an enol-amide form. The same reactants in a copper-catalyzed reaction afford mainly the corresponding N-arylo compounds. Arylhydrazines are mainly oxidized by the ylide and arylation occurs only in a low yield.

UPLC-MS metabolic profiling of second trimester amniotic fluid and maternal urine and comparison with NMR spectral profiling for the identification of pregnancy disorder biomarkers.

We report on the first untargeted UPLC-MS study of 2nd trimester maternal urine and amniotic fluid (AF), to investigate the possible metabolic effects of fetal malformations (FM), gestational diabetes mellitus (GDM) and preterm delivery (PTD). For fetal malformations, considerable metabolite variations were identified in AF and, to a lesser extent, in urine. Using validated PLS-DA models and statistical correlations between UPLC-MS data and previously acquired NMR data, a metabolic picture of fetal hypoxia, enhanced gluconeogenesis, TCA activity and hindered kidney development affecting FM pregnancies was reinforced. Moreover, changes in carnitine, pyroglutamate and polyols were newly noted, respectively, reflecting lipid oxidation, altered placental amino acid transfer and alterations in polyol pathways. Higher excretion of conjugated products in maternal urine was seen suggesting alterations in conjugation reactions. For the pre-diagnostic GDM group, no significant changes were observed, either considering amniotic fluid or maternal urine, whereas, for the pre-PTD group, some newly observed changes were noted, namely, the decrease of particular amino acids and the increase of an hexose (possibly glucose), suggesting alteration in placental amino acid fluxes and a possible tendency for hyperglycemia. This work shows the potential of UPLC-MS for the study of fetal and maternal biofluids, particularly when used in tandem with comparable NMR data. The important roles played by sampling characteristics (e.g. group dimensions) and the specific experimental conditions chosen for MS methods are discussed.

Metabolic profiling in disease diagnosis, toxicology and personalized healthcare.

Metabolic profiling employs a combination of sophisticated analytical tools to obtain global "untargeted" metabolic profiles from tissues, cells or biofluids. The resulting complex multivariate data are then modeled statistically to reveal differences between classes (e.g. dosed vs. control) and identify discriminatory metabolites. Metabolic profiling has a wide range of applications, encompassing nutrition, disease diagnosis, epidemiology and toxicology, providing insights into altered biological pathways and offering fresh mechanistic perspectives. Further, the untargeted nature of metabolic profiling can allow for new biomarkers of disease or toxic effect to be uncovered. In this review, key metabolic profiling technologies will be introduced and data analysis approaches described briefly. The role of metabolic profiling in disease diagnosis, toxicology and personalized healthcare will be discussed.

A GC-MS metabolic profiling study of plasma samples from mice on low- and high-fat diets.

Metabolic profiling of biofluids, based on the quantitative analysis of the concentration profile of their free low molecular mass metabolites, has been playing increasing role employed as a means to gain understanding of the progression of metabolic disorders, including obesity. Chromatographic methods coupled with mass spectrometry have been established as a strategy for metabolic profiling. Among these, GC-MS, targeting mainly the primary metabolism intermediates, offers high sensitivity, good peak resolution and extensive databases. However, the derivatization step required for many involatile metabolites necessitates specific data validation, normalization and analysis protocols to ensure accurate and reproducible performance. In this study, the GC-MS metabolic profiles of plasma samples from mice maintained on 12- or 15-month long low (10 kcal%) or high (60 kcal%) fat diets were obtained. The profiles of the trimethylsilyl(TMS)-methoxime(MeOx) derivatives of the free polar metabolites were acquired through GC-(ion trap)MS, using [U-(13)C]-glucose as the internal standard. After the application of a recently developed data correction and normalization/filtering protocol for GC-MS metabolomic datasets, the profiles of 48 out of the 77 detected metabolites were used in multivariate statistical analysis. Data mining suggested a decrease in the activity of the energy metabolism with age. In addition, the metabolic profiles indicated the presence of subpopulations with different physiology within the high- and low-fat diet mice, which correlated well with the difference in body weight among the animals and current knowledge about hyperglycemic conditions.