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The COVID19 pandemic accelerated opportunities for innovation within the decentralization process of clinical trials with opportunities for implementation of patient-centric workflows for efficiency and cost-reduction. Decentralized sample collection, particularly whole blood using dried blood spots (DBS) provides the ideal mechanism for patient driven sample collection with ease of access to sample generation, drug level assessments and metabolomic prMegofiling, providing longitudinal real-time measure of drug specific pharmacodynamic readout for safety and efficacy. In this study, we report the development of a protocol for the capture and comprehensive profiling of metabolomics using dried blood spots from a cohort of 49 healthy volunteer donors. Using liquid chromatography combined with mass spectrometric (UPLC-MS/MS) methods an untargeted metabolomic approach resulted in the identification of >800 biochemicals of which a significant subset was found to be presented in corresponding matched plasma (from whole blood) samples. The biochemicals identified from the DBS samples included metabolites that were part of the lipid, amino acid, nucleotide, peptide, cofactors, carbohydrate and energy super pathways. A significant number of metabolites identified in the DBS samples were xenobiotics including those representing the biotransformation products of drugs. The overall metabolite profiles were analyzed for precision and accuracy of measure, variability in performance and dynamic range to establish benchmarks for evaluation. An additional cohort with a longitudinal sampling as part of the protocol provided the reproducibility of the analytic method for inter-day variability of metabolite performance over time. Although metabolomic profiles varied between individuals from a population perspective, there was minimal variation observed within individuals when samples were profiled longitudinally over several weeks. Thus, the protocols for DBS collection and the corresponding capture of a large set of metabolites with reproducible performance provides an opportunity for its implementation in oncological clinical trials as part of a de-centralized clinical trial solution. Citation Format: Kelli Goodman, Megan R. Showalter, Anne M. Evans, Matthew W. Mitchell, Rangaprasad Sarangarajan. Dried blood spot (DBS) sample analysis for drug and metabolomic profiling in oncology clinical trials: Cost-effective decentralized sampling modality for precision oncology. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6607.

Declines in mitochondrial mass are thought to be a hallmark of mammalian aging, and a ketogenic diet (KD) may prevent the age-related decreases in mitochondrial content. The objective of this study was to investigate the impact of a KD on markers of mitochondrial mass. Mice were fed an isocaloric control diet (CD) or KD from 12 months of age. Tissues were collected after 1 month and 14 months of intervention, and a panel of commonly used markers of mitochondrial mass (mitochondrial enzyme activities and levels, mitochondrial to nuclear DNA ratio, and cardiolipin content) were measured. Our results showed that a KD stimulated activities of marker mitochondrial enzymes including citrate synthase, Complex I, and Complex IV in hindlimb muscle in aged mice. KD also increased the activity of citrate synthase and prevented an age-related decrease in Complex IV activity in aged brain. No other markers were increased in these tissues. Furthermore, the impacts of a KD on liver and kidney were mixed with no pattern indicative of a change in mitochondrial mass. In conclusion, results of the present study suggest that a KD induces tissue-specific changes in mitochondrial enzyme activities, or structure, rather than global changes in mitochondrial mass across tissues.

The mammalian brain relies on neurochemistry to fulfill its functions. Yet, the complexity of the brain metabolome and its changes during diseases or aging remain poorly understood. Here, we generate a metabolome atlas of the aging wildtype mouse brain from 10 anatomical regions spanning from adolescence to old age. We combine data from three assays and structurally annotate 1,547 metabolites. Almost all metabolites significantly differ between brain regions or age groups, but not by sex. A shift in sphingolipid patterns during aging related to myelin remodeling is accompanied by large changes in other metabolic pathways. Functionally related brain regions (brain stem, cerebrum and cerebellum) are also metabolically similar. In cerebrum, metabolic correlations markedly weaken between adolescence and adulthood, whereas at old age, cross-region correlation patterns reflect decreased brain segregation. We show that metabolic changes can be mapped to existing gene and protein brain atlases. The brain metabolome atlas is publicly available (https://mouse.atlas.metabolomics.us/) and serves as a foundation dataset for future metabolomic studies., Metabolites play an important role in physiology, yet the complexity of the metabolome and its interaction with disease and aging is poorly understood. Here the authors present a comprehensive atlas of the mouse brain metabolome and how it changes during aging.

Mitochondrial trifunctional protein deficiency, due to mutations in hydratase subunit A (HADHA), results in sudden infant death syndrome with no cure. To reveal the disease etiology, we generated stem cell-derived cardiomyocytes from HADHA-deficient hiPSCs and accelerated their maturation via an engineered microRNA maturation cocktail that upregulated the epigenetic regulator, HOPX. Here we report, matured HADHA mutant cardiomyocytes treated with an endogenous mixture of fatty acids manifest the disease phenotype: defective calcium dynamics and repolarization kinetics which results in a pro-arrhythmic state. Single cell RNA-seq reveals a cardiomyocyte developmental intermediate, based on metabolic gene expression. This intermediate gives rise to mature-like cardiomyocytes in control cells but, mutant cells transition to a pathological state with reduced fatty acid beta-oxidation, reduced mitochondrial proton gradient, disrupted cristae structure and defective cardiolipin remodeling. This study reveals that HADHA (tri-functional protein alpha), a monolysocardiolipin acyltransferase-like enzyme, is required for fatty acid beta-oxidation and cardiolipin remodeling, essential for functional mitochondria in human cardiomyocytes.

Urine metabolites are used in many clinical and biomedical studies but usually only for a few classic compounds. Metabolomics detects vastly more metabolic signals that may be used to precisely define the health status of individuals. However, many compounds remain unidentified, hampering biochemical conclusions. Here, we annotate all metabolites detected by two untargeted metabolomic assays, hydrophilic interaction chromatography (HILIC)-Q Exactive HF mass spectrometry and charged surface hybrid (CSH)-Q Exactive HF mass spectrometry. Over 9,000 unique metabolite signals were detected, of which 42% triggered MS/MS fragmentations in data-dependent mode. On the highest Metabolomics Standards Initiative (MSI) confidence level 1, we identified 175 compounds using authentic standards with precursor mass, retention time, and MS/MS matching. An additional 578 compounds were annotated by precursor accurate mass and MS/MS matching alone, MSI level 2, including a novel library specifically geared at acylcarnitines (CarniBlast). The rest of the metabolome is usually left unannotated. To fill this gap, we used the in silico fragmentation tool CSI:FingerID and the new NIST hybrid search to annotate all further compounds (MSI level 3). Testing the top-ranked metabolites in CSI:Finger ID annotations yielded 40% accuracy when applied to the MSI level 1 identified compounds. We classified all MSI level 3 annotations by the NIST hybrid search using the ClassyFire ontology into 21 superclasses that were further distinguished into 184 chemical classes. ClassyFire annotations showed that the previously unannotated urine metabolome consists of 28% derivatives of organic acids, 16% heterocyclics, and 16% lipids as major classes.

Acute lymphoblastic leukemia (ALL) is among the most common cancers in children. With improvements in combination chemotherapy regimens, the overall survival has increased to over 90%. However, the current challenge is to mitigate adverse events resulting from the complex therapy. Several chemotherapies intercept cancer metabolism, but little is known about their collective role in altering host metabolism. We profiled the metabolomic changes in plasma of ALL patients initial- and post- induction therapy. We exploited a biorepository of non-fasted plasma samples derived from the Dana Farber Cancer Institute ALL Consortium; these samples were obtained from 50 ALL patients initial- and post-induction therapy. Plasma metabolites and complex lipids were analyzed by high resolution tandem mass spectrometry and differential mobility tandem mass spectrometry. Data were analyzed using a covariate-adjusted regression model with multiplicity adjustment. Pathway enrichment analysis and co-expression network analysis were performed to identify unique clusters of molecules. More than 1200 metabolites and complex lipids were identified in the total of global metabolomics and lipidomics platforms. Over 20% of those molecules were significantly altered. In the pathway enrichment analysis, lipids, particularly phosphatidylethanolamines (PEs), were identified. Network analysis indicated that the bioactive fatty acids, docosahexaenoic acid (DHA)-containing (22:6) triacylglycerols (TAGs), were decreased in the post-induction therapy. Metabolomic profiling in ALL patients revealed a large number of alterations following induction chemotherapy. In particular, lipid metabolism was substantially altered. The changes in metabolites and complex lipids following induction therapy could provide insight into the adverse events experienced by ALL patients.

Introduction Dimethyl sulfoxide (DMSO) is a widely used solvent to dissolve hydrophobic substances for clinical uses and experimental in vivo purposes. While usually regarded safe, our prior studies suggest changes to behavior following DMSO exposure. We therefore evaluated the effects of a five‐day, short‐term exposure to DMSO on postnatal infant rats (P6‐10). Methods DMSO was intraperitoneally injected for five days at 0.2, 2.0, and 4.0 ml/kg body mass. One cohort of animals was sacrificed 24 hr after DMSO exposure to analyze the neurometabolic changes in four brain regions (cortex, hippocampus, basal ganglia, and cerebellum) by hydrophilic interaction liquid chromatography. A second cohort of animals was used to analyze chronic alterations to behavior and pathological changes to glia and neuronal cells later in life (P21‐P40). Results 164 metabolites, including key regulatory molecules (retinoic acid, orotic acid, adrenic acid, and hypotaurine), were found significantly altered by DMSO exposure in at least one of the brain regions at P11 (p, Summary of cellular and metabolic brain changes following brief exposure to DMSO.

Although understudied relative to many phospholipids, accumulating evidence suggests that bis(monoacylglycero)phosphate (BMP) is an important class of regulatory lipid that plays key roles in lysosomal integrity and function. BMPs are rare in most mammalian tissues, comprising only a few percent of total cellular lipid content, but are elevated in cell types such as macrophages that rely heavily on lysosomal function. BMPs are markedly enriched in endosomal and lysosomal vesicles compared to other organelles and membranous structures, and their unique sn-1:sn-1′ stereoconfiguration may confer stability within the hydrolytic lysosomal environment. BMP-enriched vesicles serve in endosomal-lysosomal trafficking and function as docking structures for the activation of lysosomal hydrolytic enzymes, notably those involved in the catabolic breakdown of sphingolipids. BMP levels are dysregulated in lysosomal storage disorders, phospholipidosis, metabolic diseases, liver and kidney diseases and neurodegenerative disorders. However, whether BMP alteration is a mediator or simply a marker of pathological states is unclear. Likewise, although BMP acyl chain composition may be altered with disease states, the functional significance of specific BMP species remains to be resolved. Newly developed tools for untargeted lipidomic analysis, together with a deeper understanding of enzymes mediating BMP synthesis and degradation, will help shed further light on the functional significance of BMPs in cellular physiology and pathology.

Integration of the unique advantages of the fields of drug discovery and drug delivery is invaluable for the advancement of drug development. Here we propose a self-delivering one-component new-chemical-entity nanomedicine (ONN) strategy to improve cancer therapy through incorporation of the self-assembly principle into drug design. A lysosomotropic detergent (MSDH) and an autophagy inhibitor (Lys05) are hybridised to develop bisaminoquinoline derivatives that can intrinsically form nanoassemblies. The selected BAQ12 and BAQ13 ONNs are highly effective in inducing lysosomal disruption, lysosomal dysfunction and autophagy blockade and exhibit 30-fold higher antiproliferative activity than hydroxychloroquine used in clinical trials. These single-drug nanoparticles demonstrate excellent pharmacokinetic and toxicological profiles and dramatic antitumour efficacy in vivo. In addition, they are able to encapsulate and deliver additional drugs to tumour sites and are thus promising agents for autophagy inhibition-based combination therapy. Given their transdisciplinary advantages, these BAQ ONNs have enormous potential to improve cancer therapy., Integration of the unique advantages of the fields of drug discovery and drug delivery is invaluable for the advancement of drug development. Here, the authors generate single-drug nanoparticles by hybridising lysomotropic detergents and the bisaminoquinoline-based autophagy inhibitor, and show their therapeutic potential as autophagy-inhibition based combination therapy.

BACKGROUND: Dysregulation of l-arginine metabolism has been proposed to occur in patients with severe asthma. The effects of l-arginine supplementation on l-arginine metabolite profiles in these patients are unknown. We hypothesized that individuals with severe asthma with low fractional exhaled nitric oxide (FeNO) would have fewer exacerbations with the addition of l-arginine to their standard asthma medications compared with placebo and would demonstrate the greatest changes in metabolite profiles. METHODS: Participants were enrolled in a single-center, crossover, double-blind l-arginine intervention trial at UCD. Subjects received placebo or l-arginine, dosed orally at 0.05 mg/kg (ideal body weight) twice daily. The primary end point was moderate asthma exacerbations. Longitudinal plasma metabolite levels were measured using mass spectrometry. A linear mixed-effect model with subject-specific intercepts was used for testing treatment effects. RESULTS: A cohort of 50 subjects was included in the final analysis. l-Arginine did not significantly decrease asthma exacerbations in the overall cohort. Higher citrulline levels and a lower arginine availability index (AAI) were associated with higher FeNO (P = 0.005 and P = 2.51 × 10(–9), respectively). Higher AAI was associated with lower exacerbation events. The eicosanoid prostaglandin H(2) (PGH(2)) and N(α)-acetyl-l-arginine were found to be good predictors for differentiating clinical responders and nonresponders. CONCLUSIONS: There was no statistically significant decrease in asthma exacerbations in the overall cohort with l-arginine intervention. PGH(2), N(α)-acetyl-l-arginine, and the AAI could serve as predictive biomarkers in future clinical trials that intervene in the arginine metabolome. TRIAL REGISTRATION: ClinicalTrials.gov NCT01841281. FUNDING: This study was supported by NIH grants R01HL105573, DK097154, UL1 TR001861, and K08HL114882. Metabolomics analysis was supported in part by a grant from the University of California Tobacco-Related Disease Research Program program (TRDRP).

INTRODUCTION AND OBJECTIVE:The initiation of androgen deprivation therapy (ADT) induces susceptibilities in prostate cancer (PC) cells that make them amenable to synergistic treatments and improved...

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives.

Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS-based annotation of chemical structures is impacted by instrumental settings and requirements, data acquisition modes including data-dependent and data-independent methods, library scoring algorithms, as well as post-curation steps. We critically discuss parameters that influence search results, such as mass accuracy, precursor ion isolation width, intensity thresholds, centroiding algorithms, and acquisition speed. A range of publicly and commercially available MS/MS databases such as NIST, MassBank, MoNA, LipidBlast, Wiley MSforID, and METLIN are surveyed. In addition, software tools including NIST MS Search, MS-DIAL, Mass Frontier, SmileMS, Mass++, and XCMS(2) to perform fast MS/MS search are discussed. MS/MS scoring algorithms and challenges during compound annotation are reviewed. Advanced methods such as the in silico generation of tandem mass spectra using quantum chemistry and machine learning methods are covered. Community efforts for curation and sharing of tandem mass spectra that will allow for faster distribution of scientific discoveries are discussed.

Enzymatic transformations of primary, canonical metabolites generate active biomolecules that regulate important cellular and physiological processes. Roles include regulation of histone demethylation in epigenetics, inflammation in tissue injury, insulin sensitivity, cancer cell invasion, stem cell pluripotency status, inhibition of nitric oxide signaling and others. Such modified compounds, defined as epimetabolites, have functions distinct from classic hormones as well as removed from generic anabolism and catabolism. Epimetabolites are discovered by untargeted metabolomics using liquid- or gas chromatography–high resolution mass spectrometry and structurally annotated by in-silico fragmentation prediction tools. Their specific biological functions are subsequently investigated by targeted metabolomics methods.

Mouse knockouts allow studying gene functions. Often, multiple phenotypes are impacted when a gene is inactivated. The International Mouse Phenotyping Consortium (IPMC) has generated thousands of mouse knockouts and catalogued their phenotype data. We have acquired metabolomics data from 220 plasma samples of 30 mouse gene knockouts and corresponding wildtype mice from IMPC. To acquire comprehensive metabolomics data, we have used liquid chromatography (LC) combined with mass spectrometry (MS) for detecting polar and lipophilic compounds in an untargeted approach. We have also used targeted methods to measure bile acids, steroids and oxylipins. In addition, we have used gas chromatography GC-TOFMS for measuring primary metabolites. The metabolomics dataset reports 832 unique structurally identified metabolites from 124 chemical classes as determined by ChemRICH software. The GCMS and LCMS raw data files, intermediate and finalized data matrices, R-Scripts, annotation databases and extracted ion chromatograms are provided in this data descriptor. The dataset can be used for subsequent studies to link genetic variants with molecular mechanisms and phenotypes.Data SetThe dataset is available at the MetabolomicsWorkbench repository (accession ID: ST001154)Data Set Licenselicense under which the data set is made available (CC0).

Mouse knockouts facilitate the study ofgene functions. Often, multiple abnormal phenotypes are induced when a gene is inactivated. The International Mouse Phenotyping Consortium (IMPC) has generated thousands of mouse knockouts and catalogued their phenotype data. We have acquired metabolomics data from 220 plasma samples from 30 unique mouse gene knockouts and corresponding wildtype mice from the IMPC. To acquire comprehensive metabolomics data, we have used liquid chromatography (LC) combined with mass spectrometry (MS) for detecting polar and lipophilic compounds in an untargeted approach. We have also used targeted methods to measure bile acids, steroids and oxylipins. In addition, we have used gas chromatography GC-TOFMS for measuring primary metabolites. The metabolomics dataset reports 832 unique structurally identified metabolites from 124 chemical classes as determined by ChemRICH software. The GCMS and LCMS raw data files, intermediate and finalized data matrices, R-Scripts, annotation databases, and extracted ion chromatograms are provided in this data descriptor. The dataset can be used for subsequent studies to link genetic variants with molecular mechanisms and phenotypes.

Mesenchymal stem cell (MSC) based therapies are currently being evaluated as a putative therapeutic in numerous human clinical trials. Recent reports have established that exosomes mediate much of the therapeutic properties of MSCs. Exosomes are nanovesicles which mediate intercellular communication, transmitting signals between cells which regulate a diverse range of biological processes. MSC-derived exosomes are packaged with numerous types of proteins and RNAs, however, their metabolomic and lipidomic profiles to date have not been well characterized. We previously reported that MSCs, in response to priming culture conditions that mimic the invivo microenvironmental niche, substantially modulate cellular signaling and significantly increase the secretion of exosomes. Here we report that MSCs exposed to such priming conditions undergo glycolytic reprogramming, which homogenizes MSCs' metabolomic profile. In addition, we establish that exosomes derive from primed MSCs are packaged with numerous metabolites that have been directly associated with immunomodulation, including M2 macrophage polarization and regulatory T lymphocyte induction.

Integration of the unique advantages of the fields of drug discovery and drug delivery is invaluable for the advancement of drug development. Here we propose a self-delivering one-component new-chemical-entity nanomedicine (ONN) strategy to improve cancer therapy through incorporation of the self-assembly principle into drug design. A lysosomotropic detergent (MSDH) and an autophagy inhibitor (Lys05) are hybridised to develop bisaminoquinoline derivatives that can intrinsically form nanoassemblies. The selected BAQ12 and BAQ13 ONNs are highly effective in inducing lysosomal disruption, lysosomal dysfunction and autophagy blockade and exhibit 30-fold higher antiproliferative activity than hydroxychloroquine used in clinical trials. These single-drug nanoparticles demonstrate excellent pharmacokinetic and toxicological profiles and dramatic antitumour efficacy in vivo. In addition, they are able to encapsulate and deliver additional drugs to tumour sites and are thus promising agents for autophagy inhibition-based combination therapy. Given their transdisciplinary advantages, these BAQ ONNs have enormous potential to improve cancer therapy.

Mitochondrial trifunctional protein deficiency, due to mutations in hydratase subunit A (HADHA), results in sudden infant death syndrome with no cure. To reveal the disease etiology, we generated stem cell-derived cardiomyocytes from HADHA-deficient hiPSCs and accelerated their maturation via an engineered microRNA maturation cocktail that upregulated the epigenetic regulator, HOPX. Here we report, matured HADHA mutant cardiomyocytes treated with an endogenous mixture of fatty acids manifest the disease phenotype: defective calcium dynamics and repolarization kinetics which results in a pro-arrhythmic state. Single cell RNA-seq reveals a cardiomyocyte developmental intermediate, based on metabolic gene expression. This intermediate gives rise to mature-like cardiomyocytes in control cells but, mutant cells transition to a pathological state with reduced fatty acid beta-oxidation, reduced mitochondrial proton gradient, disrupted cristae structure and defective cardiolipin remodeling. This study reveals that HADHA (tri-functional protein alpha), a monolysocardiolipin acyltransferase-like enzyme, is required for fatty acid beta-oxidation and cardiolipin remodeling, essential for functional mitochondria in human cardiomyocytes., Mutations in the gene HADHA result in mitochondrial tri-functional protein (MTP) deficiency and can result in sudden infant death syndrome for which there is no treatment. Here the authors show that the MTP deficient pathology in human cardiomyocytes leads to an abnormal cardiolipin pattern and suggests that cardiolipin affecting compounds may serve as a potential therapy.

Inborn errors of metabolism (IEMs) are a group of inherited diseases with variable incidences. IEMs are caused by disrupting enzyme activities in specific metabolic pathways by genetic mutations, either directly or indirectly by cofactor deficiencies, causing altered levels of compounds associated with these pathways. While IEMs may present with multiple overlapping symptoms and metabolites, early and accurate diagnosis of IEMs is critical for the long-term health of affected subjects. The prevalence of IEMs differs between countries, likely because different IEM classifications and IEM screening methods are used. Currently, newborn screening programs exclusively use targeted metabolic assays that focus on limited panels of compounds for selected IEM diseases. Such targeted approaches face the problem of false negative and false positive diagnoses that could be overcome if metabolic screening adopted analyses of a broader range of analytes. Hence, we here review the prospects of using untargeted metabolomics for IEM screening. Untargeted metabolomics and lipidomics do not rely on predefined target lists and can detect as many metabolites as possible in a sample, allowing to screen for many metabolic pathways simultaneously. Examples are given for nontargeted analyses of IEMs, and prospects and limitations of different metabolomics methods are discussed. We conclude that dedicated studies are needed to compare accuracy and robustness of targeted and untargeted methods with respect to widening the scope of IEM diagnostics.

Regulation of embryonic diapause, dormancy that interrupts the tight connection between developmental stage and time, is still poorly understood. Here, we characterize the transcriptional and metabolite profiles of mouse diapause embryos and identify unique gene expression and metabolic signatures with activated lipolysis, glycolysis, and metabolic pathways regulated by AMPK. Lipolysis is increased due to mTORC2 repression, increasing fatty acids to support cell survival. We further show that starvation in pre-implantation ICM-derived mouse ESCs induces a reversible dormant state, transcriptionally mimicking the in vivo diapause stage. During starvation, Lkb1, an upstream kinase of AMPK, represses mTOR, which induces a reversible glycolytic and epigenetically H4K16Ac-negative, diapause-like state. Diapause furthermore activates expression of glutamine transporters SLC38A1/2. We show by genetic and small molecule inhibitors that glutamine transporters are essential for the H4K16Ac-negative, diapause state. These data suggest that mTORC1/2 inhibition, regulated by amino acid levels, is causal for diapause metabolism and epigenetic state.

Alzheimer’s disease (AD) is a major public health priority with a large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) and the Alzheimer Disease Neuroimaging Initiative (ADNI) aim to gain new biological insights in the disease etiology. We report here an untargeted lipidomics of serum specimens of 806 subjects within the ADNI1 cohort (188 AD, 392 mild cognitive impairment and 226 cognitively normal subjects) along with 83 quality control samples. Lipids were detected and measured using an ultra-high-performance liquid chromatography quadruple/time-of-flight mass spectrometry (UHPLC-QTOF MS) instrument operated in both negative and positive electrospray ionization modes. The dataset includes a total 513 unique lipid species out of which 341 are known lipids. For over 95% of the detected lipids, a relative standard deviation of better than 20% was achieved in the quality control samples, indicating high technical reproducibility. Association modeling of this dataset and available clinical, metabolomics and drug-use data will provide novel insights into the AD etiology. These datasets are available at the ADNI repository at http://adni.loni.usc.edu/

Background: Over 200 individual molecular lipid species have been found to reside on high-density lipoproteins (HDL). The effects of exercise on the HDL lipidome profile is unknown. Methods: We examined changes in the HDL lipidome after regular exercise in 20 individuals who completed a 20-week endurance exercise program as part of the HERITAGE Family Study. The 20 subjects were selected based on discordance for exercise-induced increases in mean HDL particle (HDL-P) size (10 high-responders, 10 non-responders). The abundance of 184 known individual lipid species was quantified in baseline and post-training HDL plasma samples by UPLC-QTOF-MS. HDL was isolated through gel filtration chromatography. Results: Seven lipid species, particularly classes of triacylglycerols, cholesteryl esters, phosphatidylcholines, and sphingomyelins, showed nominal (pFigure 1 ). Three lipids showed differential responses to exercise between high- and non-responders of HDL-P size, including one lipid and metabolite each that showed an overall effect of training ( Figure 1 ). For example, the abundance of sphingomyelin d39:2 decreased by an average of 23% in the high-responders of HDL size to exercise, whereas abundance increased by 71% in the non-responders (p=0.004 for difference between groups). None of the exercise-induced changes in lipid levels were statistically significant after accounting for multiple testing. Discussion: This pilot study showed limited evidence of systematic remodeling of the HDL lipidome in response to regular endurance exercise. Future studies are needed with larger sample sizes, diverse populations, and differing exercise protocols to further examine how the molecular composition of HDL particles changes in response to exercise and potentially contributes to its atheroprotective functions.

Obesity and accompanying metabolic disease is negatively correlated with lung health yet the exact mechanisms by which obesity affects the lung are not well characterized. Since obesity is associated with lung diseases as chronic bronchitis and asthma, we designed a series of experiments to measure changes in lung metabolism in mice fed obesogenic diets. Mice were fed either control or high fat/sugar diet (45%kcal fat/17%kcal sucrose), or very high fat diet (60%kcal fat/7% sucrose) for 150 days. We performed untargeted metabolomics by GC-TOFMS and HILIC-QTOFMS and lipidomics by RPLC-QTOFMS to reveal global changes in lung metabolism resulting from obesity and diet composition. From a total of 447 detected metabolites, we found 91 metabolite and lipid species significantly altered in mouse lung tissues upon dietary treatments. Significantly altered metabolites included complex lipids, free fatty acids, energy metabolites, amino acids and adenosine and NAD pathway members. While some metabolites were altered in both obese groups compared to control, others were different between obesogenic diet groups. Furthermore, a comparison of changes between lung, kidney and liver tissues indicated few metabolic changes were shared across organs, suggesting the lung is an independent metabolic organ. These results indicate obesity and diet composition have direct mechanistic effects on composition of the lung metabolome, which may contribute to disease progression by lung-specific pathways.

Nonalcoholic fatty liver disease (NAFLD) in non-obese patients remains a clinical condition with unclear etiology and pathogenesis. Using a metabolomics approach in a mouse model that recapitulates almost all the characteristic features of non-obese NAFLD, we aimed to advance mechanistic understanding of this disorder. Mice fed high fat, high cholesterol, cholate (HFHCC) diet for three weeks consistently developed hepatic pathology similar to NAFLD and nonalcoholic steatohepatitis (NASH) without changes to body weight or fat pad weights. Gas- and liquid chromatography/mass spectrometry-based profiling of lipidomic and primary metabolism changes in the liver and plasma revealed that systemic mechanisms leading to steatosis and hepatitis in this non-obese NAFLD model were driven by a combination of effects directed by elevated free cholesterol, cholesterol esters and cholic acid, and associated changes to metabolism of sphingomyelins and phosphatidylcholines. These results demonstrate that mechanisms underlying cholesterol-induced non-obese NAFLD are distinct from NAFLD occurring as a consequence of metabolic syndrome. In addition, this investigation provides one of the first metabolite reference profiles for interpreting effects of dietary and hepatic cholesterol in human non-obese NAFLD/NASH patients.

© 2016 The Author(s). Ischemic stroke represents a major, worldwide health burden with increasing incidence. Patients affected by ischemic strokes currently have few clinically approved treatment options available. Most currently approved treatments for ischemic stroke have narrow therapeutic windows, severely limiting the number of patients able to be treated. Mesenchymal stem cells represent a promising novel treatment for ischemic stroke. Numerous studies have demonstrated that mesenchymal stem cells functionally improve outcomes in rodent models of ischemic stroke. Recent studies have also shown that exosomes secreted by mesenchymal stem cells mediate much of this effect. In the present review, we summarize the current literature on the use of mesenchymal stem cells to treat ischemic stroke. Further studies investigating the mechanisms underlying mesenchymal stem cells tissue healing effects are warranted and would be of benefit to the field.

Recent advances in mass spectrometry have led to the development of novel methods applicable in food chemistry and technology. Specifically, mass spectrometry-based omics sciences have introduced high-throughput methods permitting complex assessment of food authenticity and detection of adulteration. In this chapter, we focus mainly on mass spectrometry-based omics approaches such as (1) proteomics and peptidomics for targeting large-molecular-weight compounds and (2) metabolomics and lipidomics for studying small molecules in different food commodities (meat, fish, milk, cheese, wine, beer, coffee, honey, and olive oil). Emphasis has been placed on studies with either a large number of samples, to maximize the chance of obtaining robust statistical models, or where high species-specific selectivity was reported.

For nearly a century developmental biologists have recognized that cells from embryos can differ in their potential to differentiate into distinct cell types. Recently, it has been recognized that embryonic stem cells derived from both mice and humans exhibit two stable yet epigenetically distinct states of pluripotency: naive and primed. We now show that nicotinamide N-methyltransferase (NNMT) and the metabolic state regulate pluripotency in human embryonic stem cells (hESCs). Specifically, in naive hESCs, NNMT and its enzymatic product 1-methylnicotinamide are highly upregulated, and NNMT is required for low S-adenosyl methionine (SAM) levels and the H3K27me3 repressive state. NNMT consumes SAM in naive cells, making it unavailable for histone methylation that represses Wnt and activates the HIF pathway in primed hESCs. These data support the hypothesis that the metabolome regulates the epigenetic landscape of the earliest steps in human development.