Metabolomics Simultaneously Derives Benchmark Dose Estimates and Discovers Metabolic Biotransformations in a Rat Bioassay.

Benchmark dose (BMD) modeling estimates the dose of a chemical that causes a perturbation from baseline. Transcriptional BMDs have been shown to be relatively consistent with apical end point BMDs, opening the door to using molecular BMDs to derive human health-based guidance values for chemical exposure. Metabolomics measures the responses of small-molecule endogenous metabolites to chemical exposure, complementing transcriptomics by characterizing downstream molecular phenotypes that are more closely associated with apical end points. The aim of this study was to apply BMD modeling to in vivo metabolomics data, to compare metabolic BMDs to both transcriptional and apical end point BMDs. This builds upon our previous application of transcriptomics and BMD modeling to a 5-day rat study of triphenyl phosphate (TPhP), applying metabolomics to the same archived tissues. Specifically, liver from rats exposed to five doses of TPhP was investigated using liquid chromatography-mass spectrometry and 1H nuclear magnetic resonance spectroscopy-based metabolomics. Following the application of BMDExpress2 software, 2903 endogenous metabolic features yielded viable dose-response models, confirming a perturbation to the liver metabolome. Metabolic BMD estimates were similarly sensitive to transcriptional BMDs, and more sensitive than both clinical chemistry and apical end point BMDs. Pathway analysis of the multiomics data sets revealed a major effect of TPhP exposure on cholesterol (and downstream) pathways, consistent with clinical chemistry measurements. Additionally, the transcriptomics data indicated that TPhP activated xenobiotic metabolism pathways, which was confirmed by using the underexploited capability of metabolomics to detect xenobiotic-related compounds. Eleven biotransformation products of TPhP were discovered, and their levels were highly correlated with multiple xenobiotic metabolism genes. This work provides a case study showing how metabolomics and transcriptomics can estimate mechanistically anchored points-of-departure. Furthermore, the study demonstrates how metabolomics can also discover biotransformation products, which could be of value within a regulatory setting, for example, as an enhancement of OECD Test Guideline 417 (toxicokinetics).

Bilateral remote ischemic conditioning in children: A two-center, double-blind, randomized controlled trial in young children undergoing cardiac surgery.

Objective: The study objective was to determine whether adequately delivered bilateral remote ischemic preconditioning is cardioprotective in young children undergoing surgery for 2 common congenital heart defects with or without cyanosis. Methods: We performed a prospective, double-blind, randomized controlled trial at 2 centers in the United Kingdom. Children aged 3 to 36 months undergoing tetralogy of Fallot repair or ventricular septal defect closure were randomized 1:1 to receive bilateral preconditioning or sham intervention. Participants were followed up until hospital discharge or 30 days. The primary outcome was area under the curve for high-sensitivity troponin-T in the first 24 hours after surgery, analyzed by intention-to-treat. Right atrial biopsies were obtained in selected participants. Results: Between October 2016 and December 2020, 120 eligible children were randomized to receive bilateral preconditioning (n = 60) or sham intervention (n = 60). The primary outcome, area under the curve for high-sensitivity troponin-T, was higher in the preconditioning group (mean: 70.0 ± 50.9 µg/L/h, n = 56) than in controls (mean: 55.6 ± 30.1 µg/L/h, n = 58) (mean difference, 13.2 µg/L/h; 95% CI, 0.5-25.8; P = .04). Subgroup analyses did not show a differential treatment effect by oxygen saturations (pinteraction = .25), but there was evidence of a differential effect by underlying defect (pinteraction = .04). Secondary outcomes and myocardial metabolism, quantified in atrial biopsies, were not different between randomized groups. Conclusions: Bilateral remote ischemic preconditioning does not attenuate myocardial injury in children undergoing surgical repair for congenital heart defects, and there was evidence of potential harm in unstented tetralogy of Fallot. The routine use of remote ischemic preconditioning cannot be recommended for myocardial protection during pediatric cardiac surgery.

Clinical lipidomics in the era of the big data.

Lipidomics as a branch of metabolomics provides unique information on the complex lipid profile in biological materials. In clinically focused studies, hundreds of lipids together with available clinical information proved to be an effective tool in the discovery of biomarkers and understanding of pathobiochemistry. However, despite the introduction of lipidomics nearly twenty years ago, only dozens of big data studies using clinical lipidomics have been published to date. In this review, we discuss the lipidomics workflow, statistical tools, and the challenges of standartisation. The consequent summary divided into major clinical areas of cardiovascular disease, cancer, diabetes mellitus, neurodegenerative and liver diseases is demonstrating the importance of clinical lipidomics. In these publications, the potential of lipidomics for prediction, diagnosis or finding new targets for the treatment of selected diseases can be seen. The first of these results have already been implemented in clinical practice in the field of cardiovascular diseases, while in other areas we can expect the application of the results summarized in this review in the near future.

Dysregulation of Amino Acid, Lipid, and Acylpyruvate Metabolism in Idiopathic Intracranial Hypertension: A Non-targeted Case Control and Longitudinal Metabolomic Study.

Background: Idiopathic intracranial hypertension (IIH) is characterized by increased intracranial pressure occurring predominantly in women with obesity. The pathogenesis is not understood. We have applied untargeted metabolomic analysis using ultrahigh-performance liquid chromatography-mass spectrometry to characterize the cerebrospinal fluid (CSF) and serum in IIH compared to control subjects. Methods and findings: Samples were collected from IIH patients (n = 66) with active disease at baseline and again at 12 months following therapeutic weight loss. Control samples were collected from gender- and weight-matched healthy controls (n = 20). We identified annotated metabolites in CSF, formylpyruvate and maleylpyruvate/fumarylpyruvate, which were present at lower concentrations in IIH compared to control subjects and returned to values observed in controls following weight loss. These metabolites showed the opposite trend in serum at baseline. Multiple amino acid metabolic pathways and lipid classes were perturbed in serum and CSF in IIH alone. Serum lipid metabolite pathways were significantly increased in IIH. Conclusions: We observed a number of differential metabolic pathways related to amino acid, lipid, and acylpyruvate metabolism, in IIH compared to controls. These pathways were associated with clinical measures and normalized with disease remission. Perturbation of these metabolic pathways provides initial understanding of disease dysregulation in IIH.

Metabolomic, Lipidomic and Proteomic Characterisation of Lipopolysaccharide-induced Inflammation Mouse Model.

Neuroinflammation is an important feature in the pathogenesis and progression of central nervous system (CNS) diseases including Alzheimer's disease (AD). One of the widely used animal models of peripherally induced neuroinflammation and neurodegeneration is a lipopolysaccharide (LPS)-induced inflammation mouse model. An acute LPS administration has been widely used for investigation of inflammation-associated disease and testing inflammation-targeting drug candidates. In the present metabolomic, lipidomic and proteomic study, we investigated short-term effects of systemic inflammation induced by LPS administration on the mouse plasma and brain cortical and hippocampal metabolome, lipidome as well as expression of the brain cortical proteins which were shown to be involved in inflammation-associated CNS diseases. From a global perspective, the hippocampus was more vulnerable to the effects of LPS-induced systemic inflammation than the cortex. In addition, the study revealed several brain region-specific changes in metabolic pathways and lipids, such as statistically significant increase in several cortical and hippocampal phosphatidylcholines/phosphatidylethanolamines, and significantly decreased levels of brain cortical betaine after LPS treatment in mice. Moreover, LPS treatment in mice caused significantly increased protein expression of GluN1 receptor in the brain cortex. The revealed perturbations in the LPS-induced inflammation mouse model may give insight into the mechanisms underlying inflammation-associated CNS diseases. In addition, the finding of the study provide important information about the appropriate use of the model during target validation and drug candidate testing.

SLIDE-Novel Approach to Apocrine Sweat Sampling for Lipid Profiling in Healthy Individuals.

We designed a concept of 3D-printed attachment with porous glass filter disks-SLIDE (Sweat sampLIng DevicE) for easy sampling of apocrine sweat. By applying advanced mass spectrometry coupled with the liquid chromatography technique, the complex lipid profiles were measured to evaluate the reproducibility and robustness of this novel approach. Moreover, our in-depth statistical evaluation of the data provided an insight into the potential use of apocrine sweat as a novel and diagnostically relevant biofluid for clinical analyses. Data transformation using probabilistic quotient normalization (PQN) significantly improved the analytical characteristics and overcame the 'sample dilution issue' of the sampling. The lipidomic content of apocrine sweat from healthy subjects was described in terms of identification and quantitation. A total of 240 lipids across 15 classes were identified. The lipid concentrations varied from 10-10 to 10-4 mol/L. The most numerous class of lipids were ceramides (n = 61), while the free fatty acids were the most abundant ones (average concentrations of 10-5 mol/L). The main advantages of apocrine sweat microsampling include: (a) the non-invasiveness of the procedure and (b) the unique feature of apocrine sweat, reflecting metabolome and lipidome of the intracellular space and plasmatic membranes. The SLIDE application as a sampling technique of apocrine sweat brings a promising alternative, including various possibilities in modern clinical practice.

Metabolomic and lipidomic changes triggered by lipopolysaccharide-induced systemic inflammation in transgenic APdE9 mice.

Peripheral infections followed by systemic inflammation may contribute to the onset of Alzheimer`s disease (AD) and accelerate the disease progression later in life. Yet, the impact of systemic inflammation on the plasma and brain tissue metabolome and lipidome in AD has not been investigated. In this study, targeted metabolomic and untargeted lipidomic profiling experiments were performed on the plasma, cortices, and hippocampi of wild-type (WT) mice and transgenic APdE9 mice after chronic lipopolysaccharide (LPS) treatment, as well as saline-treated APdE9 mice. The lipidome and the metabolome of these mice were compared to saline-treated WT animals. In the brain tissue of all three models, the lipidome was more influenced than the metabolome. The LPS-treated APdE9 mice had the highest number of changes in brain metabolic pathways with significant alterations in levels of lysine, myo-inositol, spermine, phosphocreatine, acylcarnitines and diacylglycerols, which were not observed in the saline-treated APdE9 mice. In the WT mice, the effect of the LPS administration on metabolome and lipidome was negligible. The study provided exciting information about the biochemical perturbations due to LPS-induced inflammation in the transgenic AD model, which can significantly enhance our understanding of the role of systemic inflammation in AD pathogenesis.

An improved strategy for analysis of lipid molecules utilising a reversed phase C30 UHPLC column and scheduled MS/MS acquisition.

Measuring physiochemically diverse molecules (including lipids) which vary significantly in their concentrations poses a great analytical challenge. In untargeted lipidomics studies, reversed phase chromatography coupled with data-dependent MS/MS acquisition (DDA) is frequently applied. The optimal assay should deliver a high number of detected compounds with associated fragmentation data. In this work, we introduce novel 30 and 50 min UHPLC assays utilising lipid separation on a C30 stationary phase with a modified DDA strategy using smaller precursor m/z ranges scheduled for different lipid classes across the retention time range (defined as scheduled MS/MS). To evaluate the efficiency of the novel assays, mammalian tissue extracts (lamb liver, kidney and heart) were analysed and data were compared to a 15 min reversed phase C18 assay with multiple traditional DDA injections. The 30 min C30 assay detected double the number of detected compounds compared to the 15 min C18 assay. Applying the scheduled MS/MS DDA strategy with a single injection, a similar number of annotated lipids were reported compared to the traditional DDA strategy applied with five replicate injections on a C18 column. A longer 50 min C30 chromatographic assay did not result in an expected improvement in the chromatographic separation of overlapping isomer peaks compared to the 30 min method but did result in loss of accuracy of peak picking algorithms. We recommend the 30 min C30 assay with scheduled MS/MS acquisition as an efficient tool to analyse complex biological matrices and to annotate lipid species based on MS/MS data.

Chorioamnionitis alters lung surfactant lipidome in newborns with respiratory distress syndrome.

BACKGROUND: Chorioamnionitis is associated with preterm delivery and morbidities; its role in lung disease is controversial. The aim of this study is to assess the effect of chorioamnionitis on metabolite and lipid profiles of epithelial lining fluid in preterm newborns with respiratory distress syndrome (RDS). METHODS: The study involved 30 newborns with RDS, born from mothers with or without histological chorioamnionitis (HCA): HCA+, N = 10; HCA-, N = 20. Patients had a gestational age ≤30 weeks; the groups were matched for age and birth weights. Tracheal aspirates were collected within 24 h after birth and analyzed using liquid chromatography/mass spectrometry-based untargeted lipidomics. RESULTS: According to Mann-Whitney U tests, 570 metabolite features had statistically significantly higher or lower concentrations (p < 0.05) in tracheal aspirates of HCA+ compared to HCA-, and 241 metabolite features were putatively annotated and classified. The most relevant changes involved higher levels of glycerophospholipids (fold change 2.42-17.69) and sphingolipids, with lower concentration of all annotated sphingomyelins in HCA+ (fold change 0.01-0.50). CONCLUSIONS: Untargeted lipidomics of tracheal aspirates suggested the production of lipid mediators in the context of an ongoing inflammatory status in HCA+ babies. However, the effect of chorioamnionitis on epithelial lining fluid composition deserves further investigations on a larger group of infants. IMPACT: Our lipidomics investigation on tracheal aspirates of preterm newborns at birth suggested that exposure to maternal histological chorioamnionitis may cause changes in epithelial lining fluid composition. This is the first description of epithelial lining fluid lipidomic profiles in preterm infants with and without exposition to chorioamnionitis. These results could provide novel link between placental membrane inflammation and newborns' respiratory outcome.

Assessment of human plasma and urine sample preparation for reproducible and high-throughput UHPLC-MS clinical metabolic phenotyping.

Clinical metabolic phenotyping employs metabolomics and lipidomics to detect and measure hundreds to thousands of metabolites and lipids within human samples. This approach aims to identify metabolite and lipid changes between phenotypes (e.g. disease status) that aid understanding of biochemical mechanisms driving the phenotype. Sample preparation is a critical step in clinical metabolic phenotyping: it must be reproducible and give a high extraction yield of metabolites and lipids, and in high-throughput studies it needs to be rapid. Here, we assessed the extraction of polar metabolites from human urine and polar metabolites and lipids from human plasma for analysis by ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) metabolomics and lipidomics. We evaluated several monophasic (urine and plasma) and biphasic (plasma) extractions, and we also tested alterations to (a) solvent-biofluid incubation time and temperature during monophasic extraction, and (b) phase partitioning time during biphasic extraction. Extracts were analysed by three UHPLC-MS assays: (i) hydrophilic interaction chromatography (HILIC) for urine and plasma, (ii) C18 aqueous reversed phase for urine, and (iii) C18 reversed phase for plasma lipids, and the yield and reproducibility of each method was assessed. We measured UHPLC-MS injection reproducibility as well as sample preparation reproducibility to assess sample solvent composition compatibility with UHPLC-MS and to pinpoint the origin of variance within the methods. For HILIC UHPLC-MS plasma and urine analysis, monophasic 50 : 50 methanol : acetonitrile had the most detected putatively-identified polar metabolites with high method reproducibility. This method had the highest lipid yield for plasma extracts analysed by the HILIC method. If lipid removal from the plasma polar HILIC extract is required, then the biphasic methanol/chloroform/water method is recommended. For C18 (aqueous) UHPLC-MS urine analysis, 50 : 50 methanol : water had high reproducibility and yield. For C18 UHPLC-MS plasma lipidomics, monophasic 100% isopropanol had the highest detection response of all annotated lipid classes with high reproducibility. Increasing monophasic incubation time and temperature had little benefit on metabolite and lipid yield and reproducibility for all methods.

Multi-Omics Analysis of Diabetic Heart Disease in the db/db Model Reveals Potential Targets for Treatment by a Longevity-Associated Gene.

Characterisation of animal models of diabetic cardiomyopathy may help unravel new molecular targets for therapy. Long-living individuals are protected from the adverse influence of diabetes on the heart, and the transfer of a longevity-associated variant (LAV) of the human BPIFB4 gene protects cardiac function in the db/db mouse model. This study aimed to determine the effect of LAV-BPIFB4 therapy on the metabolic phenotype (ultra-high-performance liquid chromatography-mass spectrometry, UHPLC-MS) and cardiac transcriptome (next-generation RNAseq) in db/db mice. UHPLC-MS showed that 493 cardiac metabolites were differentially modulated in diabetic compared with non-diabetic mice, mainly related to lipid metabolism. Moreover, only 3 out of 63 metabolites influenced by LAV-BPIFB4 therapy in diabetic hearts showed a reversion from the diabetic towards the non-diabetic phenotype. RNAseq showed 60 genes were differentially expressed in hearts of diabetic and non-diabetic mice. The contrast between LAV-BPIFB4- and vehicle-treated diabetic hearts revealed eight genes differentially expressed, mainly associated with mitochondrial and metabolic function. Bioinformatic analysis indicated that LAV-BPIFB4 re-programmed the heart transcriptome and metabolome rather than reverting it to a non-diabetic phenotype. Beside illustrating global metabolic and expressional changes in diabetic heart, our findings pinpoint subtle changes in mitochondrial-related proteins and lipid metabolism that could contribute to LAV-BPIFB4-induced cardio-protection in a murine model of type-2 diabetes.

Urease-immobilized magnetic microparticles in urine sample preparation for metabolomic analysis by gas chromatography-mass spectrometry.

Urea, as an end product of protein metabolism and an abundant polar compound, significantly complicates the metabolomic analysis of urine by GC-MS. We developed a sample preparation method removing urea from urine samples prior the GC-MS analysis. The method based on urease immobilized on magnetic microparticles was compared with the others that are conventionally used (liquid-liquid extraction, free urease protocol), and samples without any treatment. To study the impact of sample preparation approaches on the quality of analytical data, we employed comprehensive metabolomic analysis (using both GC-MS and LC-MS/MS platforms) of standard material based on human urine. Multivariate statistical analysis has shown that immobilized urease treatment provides similar results to a free urease approach. However, significant alterations in the profiles of metabolites were observed in the samples without any treatment and after the extraction. Compared to other approaches that were tested, the immobilization of urease on microparticles reduces both the number of artifacts and the variability of the metabolites (average CV of extraction 19.7%, no treatment 11.4%, free urease 5.0%, and immobilized urease 2.5%). The method that was developed was applied in a GC-MS metabolomic experiment of glutaric aciduria type I, where both known diagnostically important biomarkers and unknowns, as the most discriminating compounds, were found.

Collection of Untargeted Metabolomic Data for Mammalian Urine Applying HILIC and Reversed Phase Ultra Performance Liquid Chromatography Methods Coupled to a Q Exactive Mass Spectrometer.

Ultra performance liquid chromatography-mass spectrometry (UPLC-MS) is the most frequently applied analytical platform in the untargeted metabolomic study of mammalian urine. Here we describe two complementary UPLC-MS methods for metabolomic analysis or urine, a reversed phase C18 method and a hydrophilic interaction liquid chromatography (HILIC) method. We discuss the inclusion of pooled quality control (QC) samples and a recommended analysis list construction. Up to 96 injections can be performed every 24 h, and up to 2000 metabolites can be routinely detected.

Toll-Like Receptor 7/8 Ligand, S28463, Suppresses Ascaris suum-induced Allergic Asthma in Nonhuman Primates.

S28463 (S28), a ligand for Toll-like receptor 7/8, has been shown to have antiinflammatory properties in rodent models of allergic asthma. The principle goal of this study was to assess whether these antiinflammatory effects can also be observed in a nonhuman primate (NHP) model of allergic asthma. NHPs were sensitized then challenged with natural allergen, Ascaris suum extract. The animals were treated with S28 orally before each allergen challenge. The protective effect of S28 in NHPs was assessed by measuring various asthma-related phenotypes. We also characterized the metabolomic and proteomic signatures of the lung environment and plasma to identify markers associated with the disease and treatment. Our data demonstrate that clinically relevant parameters, such as wheal and flare response, blood IgE levels, recruitment of white blood cells to the bronchoalveolar space, and lung responsiveness, are decreased in the S28-treated allergic NHPs compared with nontreated allergic NHPs. Furthermore, we also identified markers that can distinguish allergic from nonallergic or allergic and drug-treated NHPs, such as metabolites, phosphocreatine and glutathione, in the plasma and BAL fluid, respectively; and inflammatory cytokines, IL-5 and IL-13, in the bronchoalveolar lavage fluid. Our preclinical study demonstrates that S28 has potential as a treatment for allergic asthma in primate species closely related to humans. Combined with our previous findings, we demonstrate that S28 is effective in different models of asthma and in different species, and has the antiinflammatory properties clinically relevant for the treatment of allergic asthma.

Structural elucidation of novel biomarkers of known metabolic disorders based on multistage fragmentation mass spectra.

Specific diagnostic markers are the key to effective diagnosis and treatment of inborn errors of metabolism (IEM). Untargeted metabolomics allows for the identification of potential novel diagnostic biomarkers. Current separation techniques coupled to high-resolution mass spectrometry provide a powerful tool for structural elucidation of unknown compounds in complex biological matrices. This is a proof-of-concept study testing this methodology to determine the molecular structure of as yet uncharacterized m/z signals that were significantly increased in plasma samples from patients with phenylketonuria and 3-hydroxy-3-methylglutaryl-CoA lyase deficiency. A hybrid linear ion trap-orbitrap high resolution mass spectrometer, capable of multistage fragmentation, was used to acquire accurate masses and product ion spectra of the uncharacterized m/z signals. In order to determine the molecular structures, spectral databases were searched and fragmentation prediction software was used. This approach enabled structural elucidation of novel compounds potentially useful as biomarkers in diagnostics and follow-up of IEM patients. Two new conjugates, glutamyl-glutamyl-phenylalanine and phenylalanine-hexose, were identified in plasma of phenylketonuria patients. These novel markers showed high inter-patient variation and did not correlate to phenylalanine levels, illustrating their potential added value for follow-up. As novel biomarkers for 3-hydroxy-3-methylglutaryl-CoA lyase deficiency, three positional isomers of 3-methylglutaconyl carnitine could be detected in patient plasma. Our results highlight the applicability of current accurate mass multistage fragmentation techniques for structural elucidation of unknown metabolites in human biofluids, offering an unprecedented opportunity to gain further biochemical insights in known inborn errors of metabolism by enabling high confidence identification of novel biomarkers.

Metabolic status of CSF distinguishes rats with tauopathy from controls.

BACKGROUND: Tauopathies represent heterogeneous groups of neurodegenerative diseases that are characterised by abnormal deposition of the microtubule-associated protein tau. Alzheimer's disease is the most prevalent tauopathy, affecting more than 35 million people worldwide. In this study we investigated changes in metabolic pathways associated with tau-induced neurodegeneration. METHODS: Cerebrospinal fluid (CSF), plasma and brain tissue were collected from a transgenic rat model for tauopathies and from age-matched control animals. The samples were analysed by targeted and untargeted metabolomic methods using high-performance liquid chromatography coupled to mass spectrometry. Unsupervised and supervised statistical analysis revealed biochemical changes associated with the tauopathy process. RESULTS: Energy deprivation and potentially neural apoptosis were reflected in increased purine nucleotide catabolism and decreased levels of citric acid cycle intermediates and glucose. However, in CSF, increased levels of citrate and aconitate that can be attributed to glial activation were observed. Other significant changes were found in arginine and phosphatidylcholine metabolism. CONCLUSIONS: Despite an enormous effort invested in development of biomarkers for tauopathies during the last 20 years, there is no clinically used biomarker or assay on the market. One of the most promising strategies is to create a panel of markers (e.g., small molecules, proteins) that will be continuously monitored and correlated with patients' clinical outcome. In this study, we identified several metabolic changes that are affected during the tauopathy process and may be considered as potential markers of tauopathies in humans.

Novel sulphur-containing imatinib metabolites found by untargeted LC-HRMS analysis.

Untargeted metabolite profiling using high-resolution mass spectrometry coupled with liquid chromatography (LC-HRMS), followed by data analysis with the Compound Discoverer 2.0™ software, was used to study the metabolism of imatinib in humans with chronic myeloid leukemia. Plasma samples from control (drug-free) and patient (treated with imatinib) groups were analyzed in full-scan mode and the unknown ions occurring only in the patient group were then, as potential imatinib metabolites, subjected to multi-stage fragmentation in order to elucidate their structure. The application of an untargeted approach, as described in this study, enabled the detection of 24 novel structurally unexpected metabolites. Several sulphur-containing compounds, probably originating after the reaction of reactive intermediates of imatinib with endogenous glutathione, were found and annotated as cysteine and cystine adducts. In the proposed mechanism, the cysteine adducts were formed after the rearrangement of piperazine moiety to imidazoline. On the contrary, in vivo S-N exchange occurred in the case of the cystine adducts. In addition, N-O exchange was observed in the collision cell in the course of the fragmentation of the cystine adducts. The presence of sulphur in the cysteine and cystine conjugates was proved by means of ultra-high resolution measurements using Orbitrap Elite. The detection of metabolites derived from glutathione might improve knowledge about the disposition of imatinib towards bioactivation and help to improve understanding of the mechanism of its hepatotoxicity or nephrotoxicity in humans.

Influence of Mass Resolving Power in Orbital Ion-Trap Mass Spectrometry-Based Metabolomics.

Modern separation methods in conjunction with high-resolution accurate mass (HRAM) spectrometry can provide an enormous number of features characterized by exact mass and chromatographic behavior. Higher mass resolving power usually requires longer scanning times, and thus fewer data points are acquired across the target peak. This could cause difficulties for quantification, feature detection and deconvolution. The aim of this work was to describe the influence of mass spectrometry resolving power on profiling metabolomics experiments. From metabolic databases (HMDB, LipidMaps, KEGG), a list of compounds (41 474) was compiled and potential adducts and isotopes were calculated (622 110 features). The number of distinguishable masses was calculated for up to 3840k resolution. To evaluate these models, human plasma samples were analyzed by LC-HRMS on an Orbitrap Elite hybrid mass spectrometer (Thermo Fisher Scientific, CA, USA) at resolving power settings of 15k (7.8 Hz) up to a maximum of 480k (1.2 Hz). Software XCMS 1.44, MZmine 2.13.1, and Compound Discoverer 2.0.0.303 were used for evaluation. In plasma samples, the number of detected features increased sharply up to 60k in both positive and negative mode. However, beyond these values, it either flattened out or decreased owing to technical limitations. In conclusion, the most effective mass resolving powers for profiling analyses of metabolite rich biofluids on the Orbitrap Elite were around 60 000-120 000 fwhm to retrieve the highest amount of information. The region between 400-800 m/z was influenced the most by resolution.

Oxidized phosphatidylcholines suggest oxidative stress in patients with medium-chain acyl-CoA dehydrogenase deficiency.

Inborn errors of metabolism encompass a large group of diseases caused by enzyme deficiencies and are therefore amenable to metabolomics investigations. Medium chain acyl-CoA dehydrogenase deficiency (MCADD) is a defect in ß-oxidation of fatty acids, and is one of the most well understood disorders. We report here the use of liquid chromatography-mass spectrometry (LC-MS) based untargeted metabolomics and targeted flow injection analysis-tandem mass spectrometry (FIA-TMS) that lead to discovery of novel compounds of oxidative stress. Dry blood spots of controls (n=25) and patient samples (n=25) were extracted by methanol/water (1/1, v/v) and these supernatants were analyzed by LC-MS method with detection by an Orbitrap Elite MS. Data were processed by XCMS and CAMERA followed by dimension reduction methods. Patients were clearly distinguished from controls in PCA. S-plot derived from OPLS-DA indicated that medium-chain acylcarnitines (octanoyl, decenoyl and decanoyl carnitines) as well as three phosphatidylcholines (PC(16:0,9:0(COOH))), PC(18:0,5:0(COOH)) and PC(16:0,8:0(COOH)) were important metabolites for differentiation between patients and healthy controls. In order to biologically validate these discriminatory molecules as indicators for oxidative stress, a second cohort of individuals were analyzed, including MCADD (n=25) and control (n=250) samples. These were measured by a modified newborn screening method using FIA-TMS (API 4000) in MRM mode. Calculated p-values for PC(16:0,9:0(COOH)), PC(18:0,5:0(COOH)) and PC(16:0,8:0(COOH)) were 1.927×10(-14), 2.391×10(-15) and 3.354×10(-15) respectively. These elevated oxidized phospholipids indeed show an increased presence of oxidative stress in MCADD patients as one of the pathophysiological mechanisms of the disease.

Untargeted metabolomic analysis of urine samples in the diagnosis of some inherited metabolic disorders.

BACKGROUND: Metabolomics is becoming an important tool in clinical research and the diagnosis of human diseases. It has been used in the diagnosis of inherited metabolic disorders with pronounced biochemical abnormalities. The aim of this study was to determine if it could be applied in the diagnosis of inherited metabolic disorders (IMDs) with less clear biochemical profiles from urine samples using an untargeted metabolomic approach. METHODS: A total of 14 control urine samples and 21 samples from infants with cystinuria, maple syrup urine disease, adenylosuccinate lyase deficiency and galactosemia were tested. Samples were analyzed by liquid chromatography on aminopropyl column in aqueous normal phase separation system using gradient elution of acetonitrile/ammonium acetate. Detection was performed by time-of-flight mass spectrometer fitted with electrospray ionisation in positive mode. The data were statistically processed using principal component analysis (PCA), principal component discriminant function analysis (PCA-DFA) and partial least squares (PLS) regression. RESULTS: All patient samples were first distinguished from controls using unsupervised PCA. Discrimination of the patient samples was then unambiguously verified using supervised PCA-DFA. Known markers of the diseases in question were successfully confirmed and a potential new marker emerged from the PLS regression. CONCLUSION: This study showed that untargeted metabolomics can be applied in the diagnosis of mild IMDs with less clear biochemical profiles.