Search

Background: Circulating lipids and lipoproteins mediate cardiovascular risk, however routine plasma lipid biochemistry provides limited information on pro-atherogenic remnant particles., Objective: We analysed plasma lipoprotein subclasses including very low-density and intermediate-density lipoprotein (VLDL and IDL); and assessed their associations with health and cardiometabolic risk., Methods: From 1,976 community-dwelling adults aged 45-67 years, 114/1071 women (10.6%) and 153/905 men (16.9%) were categorised as very healthy. Fasting plasma lipoprotein profiles comprising 112 parameters were measured using 1 H nuclear magnetic resonance (NMR) spectroscopy, and associations with health status and cardiometabolic risk factors examined., Results: HDL cholesterol was higher, and IDL and VLDL cholesterol and triglycerides lower, in very healthy women compared to other women, and women compared to men. IDL and VLDL cholesterol and triglyceride were lower in very healthy men compared to other men. HDL cholesterol and apolipoprotein (apo) A-I were inversely, and IDL and VLDL cholesterol, apoB-100, and apoB-100/apoA-I ratio directly associated with body mass index (BMI) in women and men. In women, LDL, IDL and VLDL cholesterol increased with age. Women with diabetes and cardiovascular disease had higher cholesterol, triglycerides, phospholipids and free cholesterol across IDL and VLDL fractions, with similar trends for men with diabetes., Conclusion: Lipoprotein subclasses and density fractions, and their lipid and apolipoprotein constituents, are differentially distributed by sex, health status and BMI. Very healthy women and men are distinguished by favorable lipoprotein profiles, particularly lower concentrations of VLDL and IDL, providing reference intervals for comparison with general populations and adults with cardiometabolic risk factors., (Copyright © 2023. Published by Elsevier Inc.)

Background: Production of SCFAs from food is a complex and dynamic saccharolytic fermentation process mediated by both human and gut microbial factors. Knowledge of SCFA production and of the relation between SCFA profiles and dietary patterns is lacking., Objectives: Temporal changes in SCFA concentrations in response to 2 contrasting diets were investigated using a novel GC-MS method., Methods: Samples were obtained from a randomized, controlled, crossover trial designed to characterize the metabolic response to 4 diets. Participants (n = 19) undertook these diets during an inpatient stay (of 72 h). Serum samples were collected 2 h after breakfast (AB), after lunch (AL), and after dinner (AD) on day 3, and a fasting sample (FA) was obtained on day 4. The 24-h urine samples were collected on day 3. In this substudy, samples from the 2 extreme diets representing a diet with high adherence to WHO healthy eating recommendations and a typical Western diet were analyzed using a bespoke GC-MS method developed to detect and quantify 10 SCFAs and precursors in serum and urine samples., Results: Considerable interindividual variation in serum SCFA concentrations was observed across all time points, and temporal fluctuations were observed for both diets. Although the sample collection timing exerted a greater magnitude of effect on circulating SCFA concentrations, the unhealthy diet was associated with a lower concentration of acetic acid (FA: coefficient: -17.0; SE: 5.8; P-trend = 0.00615), 2-methylbutyric acid (AL: coefficient: -0.1; SE: 0.028; P-trend = 4.13 × 10 -4 and AD: coefficient: -0.1; SE: 0.028; P-trend = 2.28 × 10 -3 ), and 2-hydroxybutyric acid (FA: coefficient: -15.8; SE: 5.11; P-trend: 4.09 × 10 -3 ). In contrast, lactic acid was significantly higher in the unhealthy diet (AL: coefficient: 750.2; SE: 315.2; P-trend = 0.024 and AD: coefficient: 1219.3; SE: 322.6; P-trend: 8.28 × 10 -4 )., Conclusions: The GC-MS method allowed robust mapping of diurnal patterns in SCFA concentrations, which were affected by diet, and highlighted the importance of standardizing the timing of SCFA measurements in dietary studies. This trial was registered on the NIHR UK clinical trial gateway and with ISRCTN as ISRCTN43087333., (Copyright © 2022 American Society for Nutrition.)

Background: Surgical wound excision is a necessary procedure for burn patients that require the removal of eschar. The extent of excision is currently guided by clinical judgement, with excessinto healthy tissue potentially leading to excessive scar, or inadequate debridement increasing risk of infection. Thus, an objective real-time measure to facilitate accurate excision could support clinical judgement and improve this surgical procedure. This study was designed to investigate the potential use of Rapid evaporative ionisation mass spectrometry (REIMS) as a tool to support data-driven objective tissue excision., Methods: Data were acquired using a multi-platform approach that consisted of both Rapid Evaporative Ionisation Mass Spectrometry (REIMS) performed on intact skin, and comprehensive liquid chromatography-mass spectrometry (LC-MS/MS) lipidomics performed on homogenised skin tissue extracts. Data were analysed using principal components analysis (PCA) and multivariate orthogonal projections to latent squares discriminant analysis (OPLS-DA) and logistic regression to determine the predictability of the models., Results: PCA and OPLS-DA models of the REIMS and LC-MS/MS lipidomics data reported separation of excised and healthy tissue. Molecular fingerprints generated from REIMS analysis of healthy skin tissue revealed a high degree of heterogeneity, however, intra-individual variance was smaller than inter-individual variance. Both platforms indicated high levels of skin classification accuracy. In addition, OPLS-DA of the LC-MS/MS lipidomic data revealed significant differences in specific lipid classes between healthy control and excised skin samples; including lower free fatty acids (FFA), monoacylglycerols (MAG), lysophosphatidylglycerol (LPG) and lysophosphatidylethanolamines (LPE) in excised tissue and higher lactosylceramides (LCER) and cholesterol esters (CE) compared to healthy control tissue., Conclusions: Having established the heterogeneity in the biochemical composition of healthy skin using REIMS and LC-MS/MS, our data show that REIMS has the potential to distinguish between excied and healthy skin tissue samples. This pilot study suggests that REIMS may be an effective tool to support accurate tissue excision during burn surgery., Competing Interests: Conflict of interest The authors have no conflict of interest to declare., (Copyright © 2022 Elsevier Ltd and International Society of Burns Injuries. All rights reserved.)

Metabolic phenotyping using mass spectrometry (MS) is being applied to ever increasing sample numbers in clinical and epidemiology studies. High-throughput and robust methods are being developed for the accurate measurement of metabolites associated with disease. Traditionally, quantitative assays have utilized triple quadrupole (QQQ) MS based methods; however, the use of such focused methods removes the ability to perform discovery-based metabolic phenotyping. An integrated workflow for the hybrid simultaneous quantification of 34 biogenic amines in combination with full scan high-resolution accurate mass (HRAM) exploratory metabolic phenotyping is presented. Primary and secondary amines are derivatized with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate prior to revered-phase liquid chromatographic separation and mass spectrometric detection. Using the HRAM-MS data, retrospective phenotypic data mining could be performed, demonstrating the versatility of HRAM-MS instrumentation in a clinical and molecular epidemiological environment. Quantitative performance was assessed using two MS detector platforms: Waters TQ-XS (QQQ; n = 3) and Bruker Impact II QToF (HRAMS-MS; n = 2) and three human biofluids (plasma, serum and urine). Finally, each platform was assessed using a certified external reference sample (NIST SRM 1950 plasma). Intra- and inter-day accuracy and precision were comparable between the QQQ and QToF instruments (<15%), with excellent linearity (R 2  > 0.99) over the quantification range of 1-400 μmol L -1 . Quantitative values were comparable across all instruments for human plasma, serum and urine samples, and calculated concentrations were verified against certified reference values for NIST SRM 1950 plasma as an external reference. As a real-life biological exemplar, the method was applied to plasma samples obtained from SARS-CoV-2 positive patients versus healthy controls. Both the QQQ and QToF approaches were equivalent in being able to correctly classify SARS-CoV-2 positivity. Critically, the use of HRAM full scan data was also assessed for retrospective exploratory mining of data to extract additional biogenic amines of biomarker interest beyond the 34 quantified targets., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Tyrosine plays a key role in mammalian biochemistry and defects in its metabolism (e.g., tyrosinemia, alkaptonuria etc.) have significant adverse consequences for those affected if left untreated. In addition, gut bacterially-derived p-cresol and its metabolites are of interest as a result of various effects on host xenobiotic metabolism. A fit-for-purpose quantitative ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) assay was developed to target and quantify tyrosine and eleven metabolites in urine and plasma. Dansylation, using dansyl chloride, was used to improve chromatographic and mass spectral properties for tyrosine and nine phenolic metabolites, with detection using positive electrospray ionisation (ESI). The sulfate and glucuronide conjugates of p-cresol, where the phenol group was blocked, were quantified intact, using negative ESI via polarity switching during the same run. Sample preparation for urine and plasma involved deproteinization by solvent precipitation (of acetonitrile:isopropyl alcohol (1:1 v/v)) followed by in situ dansylation in 96 well plates. To minimize sample and solvent usage, and maximize sensitivity, analysis was performed using microbore reversed-phase gradient UPLC on a C8 phase with a 7.5 min. cycle time. The coefficients of variation obtained were <15%, with lower limits of quantification ranging from 5 to 250 nM depending upon the analyte. The method was applied to plasma and urine samples obtained from mice placed on a high tyrosine diet with one subgroup of animals subsequently receiving antibiotics to suppress the gut microbiota. Whilst plasma profiles were largely unaffected by antibiotic treatment clear reductions in the amount of p-cresol sulfate and p-cresol glucuronide excreted in the urine were observed for these mice., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: Alaska Native (AN) people have the world's highest recorded incidence of sporadic colorectal cancer (CRC) (∼91:100,000), whereas rural African (RA) people have the lowest risk (<5:100,000). Previous data supported the hypothesis that diet affected CRC risk through its effects on the colonic microbiota that produce tumor-suppressive or -promoting metabolites., Objectives: We investigated whether differences in these metabolites may contribute to the high risk of CRC in AN people., Methods: A cross-sectional observational study assessed dietary intake from 32 AN and 21 RA healthy middle-aged volunteers before screening colonoscopy. Analysis of fecal microbiota composition by 16S ribosomal RNA gene sequencing and fecal/urinary metabolites by 1H-NMR spectroscopy was complemented with targeted quantification of fecal SCFAs, bile acids, and functional microbial genes., Results: Adenomatous polyps were detected in 16 of 32 AN participants, but not found in RA participants. The AN diet contained higher proportions of fat and animal protein and less fiber. AN fecal microbiota showed a compositional predominance of Blautia and Lachnoclostridium, higher microbial capacity for bile acid conversion, and low abundance of some species involved in saccharolytic fermentation (e.g., Prevotellaceae, Ruminococcaceae), but no significant lack of butyrogenic bacteria. Significantly lower concentrations of tumor-suppressive butyrate (22.5 ± 3.1 compared with 47.2 ± 7.3 SEM µmol/g) coincided with significantly higher concentrations of tumor-promoting deoxycholic acid (26.7 ± 4.2 compared with 11 ± 1.9 µmol/g) in AN fecal samples. AN participants had lower quantities of fecal/urinary metabolites than RA participants and metabolite profiles correlated with the abundance of distinct microbial genera in feces. The main microbial and metabolic CRC-associated markers were not significantly altered in AN participants with adenomatous polyps., Conclusions: The low-fiber, high-fat diet of AN people and exposure to carcinogens derived from diet or environment are associated with a tumor-promoting colonic milieu as reflected by the high rates of adenomatous polyps in AN participants., (Copyright © The Author(s) 2019.)

A comprehensive Collision Cross Section (CCS) library was obtained via Travelling Wave Ion Guide mobility measurements through direct infusion (DI). The library consists of CCS and Mass Spectral (MS) data in negative and positive ElectroSpray Ionisation (ESI) mode for 463 and 479 endogenous metabolites, respectively. For both ionisation modes combined, TW CCS N2 data were obtained for 542 non-redundant metabolites. These data were acquired on two different ion mobility enabled orthogonal acceleration QToF MS systems in two different laboratories, with the majority of the resulting TW CCS N2 values (from detected compounds) found to be within 1% of one another. Validation of these results against two independent, external TW CCS N2 data sources and predicted TW CCS N2 values indicated to be within 1-2% of these other values. The same metabolites were then analysed using a rapid reversed-phase ultra (high) performance liquid chromatographic (U(H)PLC) separation combined with IM and MS (IM-MS) thus providing retention time (t r ), m/z and TW CCS N2 values (with the latter compared with the DI-IM-MS data). Analytes for which TW CCS N2 values were obtained by U(H)PLC-IM-MS showed good agreement with the results obtained from DI-IM-MS. The repeatability of the TW CCS N2 values obtained for these metabolites on the different ion mobility QToF systems, using either DI or LC, encouraged the further evaluation of the U(H)PLC-IM-MS approach via the analysis of samples of rat urine, from control and methotrexate-treated animals, in order to assess the potential of the approach for metabolite identification and profiling in metabolic phenotyping studies. Based on the database derived from the standards 63 metabolites were identified in rat urine, using positive ESI, based on the combination of t r , TW CCS N2 and MS data., (Copyright © 2019 Elsevier B.V. All rights reserved.)

A UPLC-MS/MS assay, employing a reversed-phase separation, has been applied to the analysis of a number of common amino acids and biogenic amines in rat urine. Analytes were derivatised, using 6‑aminoquinolyl‑N‑hydroxysuccinimidyl carbamate (AccQTag Ultra™ ) . Derivatisation with this reagent, by increasing the hydrophobicity of the analytes, enables better retention by improving reversed-phase chromatographic properties and also improves ionisation efficiency to enhance MS-detection. The method allows for the determination of 38 amino compounds in 7.5 min, including baseline resolution of critical isomers. The assay has been validated for the absolute quantification of 29 amino compounds in rat urine, over a concentration range of 0.6-200 μM, for the purpose of exploratory metabolite phenotyping. Acceptable linearity (R 2  > 0.995) and intra- and inter-day accuracy (<20.7%) and precision (<20.1%) for these analytes was achieved. The limits of detection ranged from 1.2-12 fmol on column with 20 μL of sample. The remaining nine amines examined were not accurately quantified by this method but can be monitored for relative/fold change in biological samples. The use of the method is exemplified by the monitoring of changes in healthy male Sprague-Dawley rat urinary amino acid concentrations over a 7-day period., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Obstructive cholestasis causes liver injury via accumulation of toxic bile acids (BAs). Therapeutic options for cholestatic liver disease are limited, partially because the available murine disease models lack translational value. Profiling of time-related changes following bile duct ligation (BDL) in Gold Syrian hamsters revealed a biochemical response similar to cholestatic patients in terms of BA pool composition, alterations in hepatocyte BA transport and signaling, suppression of BA production, and adapted BA metabolism. Hamsters tolerated cholestasis well for up to 28days and progressed relatively slowly to fibrotic liver injury. Hepatocellular necrosis was absent, which coincided with preserved intrahepatic energy levels and only mild oxidative stress. The histological response to cholestasis in hamsters was similar to the changes seen in 17 patients with prolonged obstructive cholestasis caused by cholangiocarcinoma. Hamsters moreover upregulated hepatic fibroblast growth factor 15 (Fgf15) expression in response to BDL, which is a cytoprotective adaptation to cholestasis that hitherto had only been documented in cholestatic human livers. Hamster models should therefore be added to the repertoire of animal models used to study the pathophysiology of cholestatic liver disease., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background: Interindividual variation in the response to diet is common, but the underlying mechanism for such variation is unclear., Objective: The objective of this study was to use a metabolic profiling approach to identify a panel of urinary metabolites representing individuals demonstrating typical (homogeneous) metabolic responses to healthy diets, and subsequently to define the association of these metabolites with improvement of risk factors for cardiovascular diseases (CVDs)., Design: 24-h urine samples from 158 participants with pre-hypertension and stage 1 hypertension, collected at baseline and following the consumption of a carbohydrate-rich, a protein-rich, and a monounsaturated fat-rich healthy diet (6 wk/diet) in a randomized, crossover study, were analyzed by proton (1H) nuclear magnetic resonance (NMR) spectroscopy. Urinary metabolite profiles were interrogated to identify typical and variable responses to each diet. We quantified the differences in absolute excretion of metabolites, distinguishing between dietary comparisons within the typical response groups, and established their associations with CVD risk factors using linear regression., Results: Globally all 3 diets induced a similar pattern of change in the urinary metabolic profiles for the majority of participants (60.1%). Diet-dependent metabolic variation was not significantly associated with total cholesterol or low-density lipoprotein (LDL) cholesterol concentration. However, blood pressure (BP) was found to be significantly associated with 6 urinary metabolites reflecting dietary intake [proline-betaine (inverse), carnitine (direct)], gut microbial co-metabolites [hippurate (direct), 4-cresyl sulfate (inverse), phenylacetylglutamine (inverse)], and tryptophan metabolism [N-methyl-2-pyridone-5-carboxamide (inverse)]. A dampened clinical response was observed in some individuals with variable metabolic responses, which could be attributed to nonadherence to diet (≤25.3%), variation in gut microbiome activity (7.6%), or a combination of both (7.0%)., Conclusions: These data indicate interindividual variations in BP in response to dietary change and highlight the potential influence of the gut microbiome in mediating this relation. This approach provides a framework for stratification of individuals undergoing dietary management. The original OmniHeart intervention study and the metabolomics study were registered at www.clinicaltrials.gov as NCT00051350 and NCT03369535, respectively.

The need for rapid and efficient high throughput metabolic phenotyping (metabotyping) in metabolomic/metabonomic studies often requires compromises to be made between analytical speed and metabolome coverage. Here the effect of column length (150, 75 and 30 mm) and gradient duration (15, 7.5 and 3 min respectively) on the number of features detected when untargeted metabolic profiling of human urine using reversed-phase gradient ultra performance chromatography with, and without, ion mobility spectrometry, has been examined. As would be expected, reducing column length from 150 to 30 mm, and gradient duration, from 15 to 3 min, resulted in a reduction in peak capacity from 311 to 63 and a similar reduction in the number of features detected from over ca. 16,000 to ca. 6500. Under the same chromatographic conditions employing UPLC/IMS/MS to provide an additional orthogonal separation resulted in an increase in the number of MS features detected to nearly 20,000 and ca. 7500 for the 150 mm and the 30 mm columns respectively. Based on this limited study the potential of LC/IMS/MS as a tool for improving throughput and increasing metabolome coverage clearly merits further in depth study., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

The gut microbiota has both direct and indirect effects on drug and xenobiotic metabolisms, and this can have consequences for both efficacy and toxicity. Indeed, microbiome-driven drug metabolism is essential for the activation of certain prodrugs, for example, azo drugs such as prontosil and neoprontosil resulting in the release of sulfanilamide. In addition to providing a major source of reductive metabolizing capability, the gut microbiota provides a suite of additional reactions including acetylation, deacylation, decarboxylation, dehydroxylation, demethylation, dehalogenation, and importantly, in the context of certain types of drug-related toxicity, conjugates hydrolysis reactions. In addition to direct effects, the gut microbiota can affect drug metabolism and toxicity indirectly via, for example, the modulation of host drug metabolism and disposition and competition of bacterial-derived metabolites for xenobiotic metabolism pathways. Also, of course, the therapeutic drugs themselves can have effects, both intended and unwanted, which can impact the health and composition of the gut microbiota with unforeseen consequences., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Supercritical fluid chromatography (SFC) is frequently used for the analysis and separation of non-polar metabolites, but remains relatively underutilised for the study of polar molecules, even those which pose difficulties with established reversed-phase (RP) or hydrophilic interaction liquid chromatographic (HILIC) methodologies. Here, we present a fast SFC-MS method for the analysis of medium and high-polarity (-7≤cLogP≤2) compounds, designed for implementation in a high-throughput metabonomics setting. Sixty polar analytes were first screened to identify those most suitable for inclusion in chromatographic test mixtures; then, a multi-dimensional method development study was conducted to determine the optimal choice of stationary phase, modifier additive and temperature for the separation of such analytes using SFC. The test mixtures were separated on a total of twelve different column chemistries at three different temperatures, using CO2-methanol-based mobile phases containing a variety of polar additives. Chromatographic performance was evaluated with a particular emphasis on peak capacity, overall resolution, peak distribution and repeatability. The results suggest that a new generation of stationary phases, specifically designed for improved robustness in mixed CO2-methanol mobile phases, can improve peak shape, peak capacity and resolution for all classes of polar analytes. A significant enhancement in chromatographic performance was observed for these urinary metabolites on the majority of the stationary phases when polar additives such as ammonium salts (formate, acetate and hydroxide) were included in the organic modifier, and the use of water or alkylamine additives was found to be beneficial for specific subsets of polar analytes. The utility of these findings was confirmed by the separation of a mixture of polar metabolites in human urine using an optimised 7min gradient SFC method, where the use of the recommended column and co-solvent combination resulted in a significant improvement in chromatographic performance., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Background & Aims: Predicting survival in decompensated cirrhosis (DC) is important in decision making for liver transplantation and resource allocation. We investigated whether high-resolution metabolic profiling can determine a metabolic phenotype associated with 90-day survival., Methods: Two hundred and forty-eight subjects underwent plasma metabotyping by (1)H nuclear magnetic resonance (NMR) spectroscopy and reversed-phase ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC-TOF-MS; DC: 80-derivation set, 101-validation; stable cirrhosis (CLD) 20 and 47 healthy controls (HC))., Results: (1)H NMR metabotyping accurately discriminated between surviving and non-surviving patients with DC. The NMR plasma profiles of non-survivors were attributed to reduced phosphatidylcholines and lipid resonances, with increased lactate, tyrosine, methionine and phenylalanine signal intensities. This was confirmed on external validation (area under the receiver operating curve [AUROC]=0.96 (95% CI 0.90-1.00, sensitivity 98%, specificity 89%). UPLC-TOF-MS confirmed that lysophosphatidylcholines and phosphatidylcholines [LPC/PC] were downregulated in non-survivors (UPLC-TOF-MS profiles AUROC of 0.94 (95% CI 0.89-0.98, sensitivity 100%, specificity 85% [positive ion detection])). LPC concentrations negatively correlated with circulating markers of cell death (M30 and M65) levels in DC. Histological examination of liver tissue from DC patients confirmed increased hepatocyte cell death compared to controls. Cross liver sampling at time of liver transplantation demonstrated that hepatic endothelial beds are a source of increased circulating total cytokeratin-18 in DC., Conclusion: Plasma metabotyping accurately predicts mortality in DC. LPC and amino acid dysregulation is associated with increased mortality and severity of disease reflecting hepatocyte cell death., (Copyright © 2016 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)

Methylamines are biologically-active metabolites present in serum and urine samples, which play complex roles in metabolic diseases. Methylamines can be detected by proton nuclear magnetic resonance (NMR), but specific methods remain to be developed for their routine assay in human serum in clinical settings. Here we developed and validated a novel reliable "methylamine panel" method for simultaneous quantitative analysis of trimethylamine (TMA), its major detoxification metabolite trimethylamine-N-oxide (TMAO), and precursors choline, betaine and l-carnitine in human serum using Ultra Performance Liquid Chromatography (UPLC) coupled to High Resolution Mass Spectrometry (HRMS). Metabolite separation was carried out on a HILIC stationary phase. For all metabolites, the assay was linear in the range of 0.25-12.5 μmol/L and enabled to reach limit of detection of about 0.10 μmol/L. Relative standard deviations were below 16% for the three levels of concentrations. We demonstrated the strong reliability and robustness of the method, which was applied to serum samples from healthy individuals to establish the range of concentrations of the metabolites and their correlation relationships and detect gender differences. Our data provide original information for implementing in a clinical environment a MS-based diagnostic method with potential for targeted metabolic screening of patients at risk of cardiometabolic diseases., (Copyright © 2016 Elsevier Inc. All rights reserved.)

One aim of systems toxicology is to deliver mechanistic, mathematically rigorous, models integrating biochemical and pharmacological processes that result in toxicity to enhance the assessment of the risk posed to humans by drugs and other xenobiotics. The benefits of such 'in silico' models would be in enabling the rapid and robust prediction of the effects of compounds over a range of exposures, improving in vitro-in vivo correlations and the translation from preclinical species to humans. Systems toxicology models of organ toxicities that result in high attrition rates during drug discovery and development, or post-marketing withdrawals (e.g., drug-induced liver injury (DILI)) should facilitate the discovery of safe new drugs. Here, systems toxicology as applied to the effects of paracetamol (acetaminophen, N-acetyl-para-aminophenol (APAP)) is used to exemplify the potential of the approach., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Linear multivariate projection methods are frequently applied for predictive modeling of spectroscopic data in metabonomic studies. The OPLS method is a commonly used computational procedure for characterizing spectral metabonomic data, largely due to its favorable model interpretation properties providing separate descriptions of predictive variation and response-orthogonal structured noise. However, when the relationship between descriptor variables and the response is non-linear, conventional linear models will perform sub-optimally. In this study we have evaluated to what extent a non-linear model, kernel-based orthogonal projections to latent structures (K-OPLS), can provide enhanced predictive performance compared to the linear OPLS model. Just like its linear counterpart, K-OPLS provides separate model components for predictive variation and response-orthogonal structured noise. The improved model interpretation by this separate modeling is a property unique to K-OPLS in comparison to other kernel-based models. Simulated annealing (SA) was used for effective and automated optimization of the kernel-function parameter in K-OPLS (SA-K-OPLS). Our results reveal that the non-linear K-OPLS model provides improved prediction performance in three separate metabonomic data sets compared to the linear OPLS model. We also demonstrate how response-orthogonal K-OPLS components provide valuable biological interpretation of model and data. The metabonomic data sets were acquired using proton Nuclear Magnetic Resonance (NMR) spectroscopy, and include a study of the liver toxin galactosamine, a study of the nephrotoxin mercuric chloride and a study of Trypanosoma brucei brucei infection. Automated and user-friendly procedures for the kernel-optimization have been incorporated into version 1.1.1 of the freely available K-OPLS software package for both R and Matlab to enable easy application of K-OPLS for non-linear prediction modeling., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Background: Metabolic phenotyping of humans allows information to be captured on the interactions between dietary, xenobiotic, other lifestyle and environmental exposures, and genetic variation, which together influence the balance between health and disease risks at both individual and population levels., Objectives: We describe here the main procedures in large-scale metabolic phenotyping and their application to metabolome-wide association (MWA) studies., Methods: By use of high-throughput technologies and advanced spectroscopic methods, application of metabolic profiling to large-scale epidemiologic sample collections, including metabolome-wide association (MWA) studies for biomarker discovery and identification., Discussion: Metabolic profiling at epidemiologic scale requires optimization of experimental protocol to maximize reproducibility, sensitivity, and quantitative reliability, and to reduce analytical drift. Customized multivariate statistical modeling approaches are needed for effective data visualization and biomarker discovery with control for false-positive associations since 100s or 1,000s of complex metabolic spectra are being processed., Conclusion: Metabolic profiling is an exciting addition to the armamentarium of the epidemiologist for the discovery of new disease-risk biomarkers and diagnostics, and to provide novel insights into etiology, biological mechanisms, and pathways.

Background: New food biomarkers are needed to objectively evaluate the effect of diet on health and to check adherence to dietary recommendations and healthy eating patterns., Objective: We developed a strategy for food biomarker discovery, which combined nutritional intervention with metabolic phenotyping and biomarker validation in a large-scale epidemiologic study., Design: We administered a standardized diet to 8 individuals and established a putative urinary biomarker of fruit consumption by using (1)H nuclear magnetic resonance (NMR) spectroscopic profiling. The origin of the biomarker was confirmed by using targeted NMR spectroscopy of various fruit. Excretion kinetics of the biomarker were measured. The biomarker was validated by using urinary NMR spectra from UK participants of the INTERMAP (International Collaborative Study of Macronutrients, Micronutrients, and Blood Pressure) (n = 499) in which citrus consumption was ascertained from four 24-h dietary recalls per person. Finally, dietary patterns of citrus consumers (n = 787) and nonconsumers (n = 1211) were compared., Results: We identified proline betaine as a putative biomarker of citrus consumption. High concentrations were observed only in citrus fruit. Most proline betaine was excreted < or =14 h after a first-order excretion profile. Biomarker validation in the epidemiologic data showed a sensitivity of 86.3% for elevated proline betaine excretion in participants who reported citrus consumption and a specificity of 90.6% (P < 0.0001). In comparison with noncitrus consumers, citrus consumers had lower intakes of fats, lower urinary sodium-potassium ratios, and higher intakes of vegetable protein, fiber, and most micronutrients., Conclusion: The biomarker identification and validation strategy has the potential to identify biomarkers for healthier eating patterns associated with a reduced risk of major chronic diseases. The trials were registered at clinicaltrials.gov as NCT01102049 and NCT01102062.

Proton ((1)H) Nuclear Magnetic Resonance (NMR) spectroscopy was used to investigate the biochemical response of bank voles and wood mice (two wild rodent species frequently found on metal-contaminated sites) to chronic cadmium (Cd) insult. Similar effects, in terms of both metabolic changes (consistent with cellular acidosis) and induced metallothionin (MT) production were observed in all animals. These changes appeared to be an adaptation of the liver to toxic insult rather than onset of a toxic effect, and, in common with previous studies, were more marked in bank voles than wood mice. This may have reflected the greater Cd intake and assimilation of the former but was not explained by differences in concentrations of free (non MT-bound) Cd; concentrations of which were negligible in both voles and mice. Responses to Cd insult were detected in both species even though their bodies contained cadmium concentrations well below the World Health Organisation critical renal concentration of 200 mug/g dry mass.

ICP-MS, HPLC-ICP-MS and HPLC-ICP-MS/ESI-MS have been applied to determine the disposition and metabolic fate of 2-, 3- and 4-iodobenzoic acids following intraperitoneal administration at 50 mg kg(-1) to male bile duct cannulated rats. Quantitative excretion balance studies based on the determination of the total iodine content of urine and bile showed that all three iodobenzoic acids were rapidly excreted. Recoveries ranging from 95 to 105% of the administered doses were achieved within 24 h of administration. Metabolite profiles for urine and bile showed extensive metabolism with unchanged iodobenzoic acids forming a minor part of the total. A combination of alkaline hydrolysis and MS enabled the identification of the major metabolites of all three iodobenzoic acids as glycine and ester glucuronide conjugates with very little if any of the parent compounds excreted unchanged., (Copyright 2004 Elsevier B.V.)

Pattern recognition techniques are effective tools for reducing the information contained in large spectral data sets to a much smaller number of significant features which can then be used to make interpretations about the chemical or biochemical system under study. Often the effectiveness of such approaches is impeded by experimental and instrument induced variations in the position, phase, and line width of the spectral peaks. Although characterizing the cause and magnitude of these fluctuations could be important in its own right (pH-induced NMR chemical shift changes, for example) in general they obscure the process of pattern discovery. One major area of application is the use of large databases of (1)H NMR spectra of biofluids such as urine for investigating perturbations in metabolic profiles caused by drugs or disease, a process now termed metabonomics. Frequency shifts of individual peaks are the dominant source of such unwanted variations in this type of data. In this paper, an automatic procedure for aligning the individual peaks in the data set is described and evaluated. The proposed method will be vital for the efficient and automatic analysis of large metabonomic data sets and should also be applicable to other types of data.

The 1H nuclear magnetic resonance (NMR) spectra of biological samples, such as blood plasma and tissues, are information rich but data complex owing to superposition of the resonances from a multitude of different chemical entities in multiple-phase compartments, hampering detection and subsequent resonance assignments. To overcome these problems, several spectral-editing NMR experiments are described here, combining spin-relaxation filters (based on T(1), T(rho), and T(2)) with both one-dimensional and two-dimensional (2D) NMR spectroscopy. These techniques enable the separation of NMR resonances based on their relaxation times and allow simplification of the complex spectra. In this paper, the approach is exemplified using a control human blood plasma, which is a complex mixture of proteins, lipoproteins, and small-molecule metabolites. In the case of T(1rho)- and T(2)-edited 2D NMR experiments, a "flip-back" pulse was introduced after the relaxation editing to make the phase cycling of the "relaxation filter" and the 2D NMR part independent, thus enabling easy implementation of the phase-sensitive 2D NMR experiments. These methods also permit much higher receiver gains to be used to reduce digitization error, in particular, for the small resonances, which are sometimes vitally important for metabonomics studies. Both pulse sequences and experimental results are discussed for T(1)-, T(1rho)-, and T(2)-filtered COSY, T(2)-filtered phase-sensitive DQF-COSY, and T(1), T(1rho)-, and T(2)-filtered TOCSY NMR.

This study describes the first metabonomic approach to determining biochemical modifications following dietary intervention in humans. Significant interest in the mechanisms of action of soy isoflavones has predominantly stemmed from in vitro experiments but to date the availability of analytical tools for studying the mechanisms of action in vivo have been limited. Here a metabonomic approach based on chemometric analysis of 1H nuclear magnetic resonance spectra of blood plasma has been used to investigate metabolic changes following dietary intervention with soy isoflavones in healthy premenopausal women under controlled environmental conditions. Clear differences in the plasma lipoprotein, amino acid, and carbohydrate profiles were observed following soy intervention, suggesting a soy-induced alteration in energy metabolism.

Principal component analysis (PCA) has been applied to three nuclear magnetic resonance (NMR) spectral editing methods, namely, the Carr-Purcell-Meiboom-Gill spin-echo, diffusion editing, and skyline projection of a two-dimensional J-resolved spectrum, obtained from high-resolution magic-angle spinning NMR spectroscopy of liver tissues, to distinguish between control and hydrazine-treated rats. The effects of the toxin on rat liver biochemistry were directly observed and characterized by depleted levels of liver glycogen, choline, taurine, trimethylamine N-oxide, and glucose and by elevated levels of lipids and alanine. The highly unsaturated omega-3-type fatty acid was observed for the first time in hydrazine-treated rat liver. The contributions of the metabolites to the separation of control from dosed liver tissues varied depending on the type of spectral editing method used. We have shown that subtle changes in the metabolic profiles can be selectively amplified using a metabonomics approach based on the different NMR spectral editing techniques in conjunction with PCA.

Several essential and non-essential metals (typically those from periods 4, 5 and 6 in groups 11-15 in the periodic table) are commonly detoxified in higher plants by complexation with phytochelatin. The genetic and gross metabolic basis of metal tolerance in plants is, however, poorly understood. Here, we have analyzed plant cell extracts using 1H NMR spectroscopy combined with multivariate statistical analysis of the data to investigate the biochemical consequences of Cd(2+) exposure in Silene cucubalus cell cultures. Principal components analysis of 1H NMR spectra showed clear discrimination between control and Cd(2+) dosed groups, demonstrating the metabolic effects of Cd(2+) and thus allowing the identification of increases in malic acid and acetate, and decreases in glutamine and branched chain amino acids as consequences of Cd(2+) exposure. This work shows the value of NMR-based metabolomic approaches to the determination of biochemical effects of pollutants in naturally selected populations.

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., ((c) 2002 Elsevier Science (USA))