Glucocerebrosidase reduces the spread of protein aggregation in a Drosophila melanogaster model of neurodegeneration by regulating proteins trafficked by extracellular vesicles.

Abnormal protein aggregation within neurons is a key pathologic feature of Parkinson's disease (PD). The spread of brain protein aggregates is associated with clinical disease progression, but how this occurs remains unclear. Mutations in glucosidase, beta acid 1 (GBA), which encodes glucocerebrosidase (GCase), are the most penetrant common genetic risk factor for PD and dementia with Lewy bodies and associate with faster disease progression. To explore how GBA mutations influence pathogenesis, we previously created a Drosophila model of GBA deficiency (Gba1b) that manifests neurodegeneration and accelerated protein aggregation. Proteomic analysis of Gba1b mutants revealed dysregulation of proteins involved in extracellular vesicle (EV) biology, and we found altered protein composition of EVs from Gba1b mutants. Accordingly, we hypothesized that GBA may influence pathogenic protein aggregate spread via EVs. We found that accumulation of ubiquitinated proteins and Ref(2)P, Drosophila homologue of mammalian p62, were reduced in muscle and brain tissue of Gba1b flies by ectopic expression of wildtype GCase in muscle. Neuronal GCase expression also rescued protein aggregation both cell-autonomously in brain and non-cell-autonomously in muscle. Muscle-specific GBA expression reduced the elevated levels of EV-intrinsic proteins and Ref(2)P found in EVs from Gba1b flies. Perturbing EV biogenesis through neutral sphingomyelinase (nSMase), an enzyme important for EV release and ceramide metabolism, enhanced protein aggregation when knocked down in muscle, but did not modify Gba1b mutant protein aggregation when knocked down in neurons. Lipidomic analysis of nSMase knockdown on ceramide and glucosylceramide levels suggested that Gba1b mutant protein aggregation may depend on relative depletion of specific ceramide species often enriched in EVs. Finally, we identified ectopically expressed GCase within isolated EVs. Together, our findings suggest that GCase deficiency promotes accelerated protein aggregate spread between cells and tissues via dysregulated EVs, and EV-mediated trafficking of GCase may partially account for the reduction in aggregate spread.

Increased Drp1 Acetylation by Lipid Overload Induces Cardiomyocyte Death and Heart Dysfunction.

RATIONALE: Lipid overload-induced heart dysfunction is characterized by cardiomyocyte death, myocardial remodeling, and compromised contractility, but the impact of excessive lipid supply on cardiac function remains poorly understood. OBJECTIVE: To investigate the regulation and function of the mitochondrial fission protein Drp1 (dynamin-related protein 1) in lipid overload-induced cardiomyocyte death and heart dysfunction. METHODS AND RESULTS: Mice fed a high-fat diet (HFD) developed signs of obesity and type II diabetes mellitus, including hyperlipidemia, hyperglycemia, hyperinsulinemia, and hypertension. HFD for 18 weeks also induced heart hypertrophy, fibrosis, myocardial insulin resistance, and cardiomyocyte death. HFD stimulated mitochondrial fission in mouse hearts. Furthermore, HFD increased the protein level, phosphorylation (at the activating serine 616 sites), oligomerization, mitochondrial translocation, and GTPase activity of Drp1 in mouse hearts, indicating that Drp1 was activated. Monkeys fed a diet high in fat and cholesterol for 2.5 years also exhibited myocardial damage and Drp1 activation in the heart. Interestingly, HFD decreased nicotinamide adenine dinucleotide (oxidized) levels and increased Drp1 acetylation in the heart. In adult cardiomyocytes, palmitate increased Drp1 acetylation, phosphorylation, and protein levels, and these increases were abolished by restoration of the decreased nicotinamide adenine dinucleotide (oxidized) level. Proteomics analysis and in vitro screening revealed that Drp1 acetylation at lysine 642 (K642) was increased by HFD in mouse hearts and by palmitate incubation in cardiomyocytes. The nonacetylated Drp1 mutation (K642R) attenuated palmitate-induced Drp1 activation, its interaction with voltage-dependent anion channel 1, mitochondrial fission, contractile dysfunction, and cardiomyocyte death. CONCLUSIONS: These findings uncover a novel mechanism that contributes to lipid overload-induced heart hypertrophy and dysfunction. Excessive lipid supply created an intracellular environment that facilitated Drp1 acetylation, which, in turn, increased its activity and mitochondrial translocation, resulting in cardiomyocyte dysfunction and death. Thus, Drp1 may be a critical mediator of lipid overload-induced heart dysfunction as well as a potential target for therapy.

Metabolic Remodeling Promotes Cardiac Hypertrophy by Directing Glucose to Aspartate Biosynthesis.

RATIONALE: Hypertrophied hearts switch from mainly using fatty acids (FAs) to an increased reliance on glucose for energy production. It has been shown that preserving FA oxidation (FAO) prevents the pathological shift of substrate preference, preserves cardiac function and energetics, and reduces cardiomyocyte hypertrophy during cardiac stresses. However, it remains elusive whether substrate metabolism regulates cardiomyocyte hypertrophy directly or via a secondary effect of improving cardiac energetics. OBJECTIVE: The goal of this study was to determine the mechanisms of how preservation of FAO prevents the hypertrophic growth of cardiomyocytes. METHODS AND RESULTS: We cultured adult rat cardiomyocytes in a medium containing glucose and mixed-chain FAs and induced pathological hypertrophy by phenylephrine. Phenylephrine-induced hypertrophy was associated with increased glucose consumption and higher intracellular aspartate levels, resulting in increased synthesis of nucleotides, RNA, and proteins. These changes could be prevented by increasing FAO via deletion of ACC2 (acetyl-CoA-carboxylase 2) in phenylephrine-stimulated cardiomyocytes and in pressure overload-induced cardiac hypertrophy in vivo. Furthermore, aspartate supplementation was sufficient to reverse the antihypertrophic effect of ACC2 deletion demonstrating a causal role of elevated aspartate level in cardiomyocyte hypertrophy. 15N and 13C stable isotope tracing revealed that glucose but not glutamine contributed to increased biosynthesis of aspartate, which supplied nitrogen for nucleotide synthesis during cardiomyocyte hypertrophy. CONCLUSIONS: Our data show that increased glucose consumption is required to support aspartate synthesis that drives the increase of biomass during cardiac hypertrophy. Preservation of FAO prevents the shift of metabolic flux into the anabolic pathway and maintains catabolic metabolism for energy production, thus preventing cardiac hypertrophy and improving myocardial energetics.

Depletion of mitochondrial inorganic polyphosphate (polyP) in mammalian cells causes metabolic shift from oxidative phosphorylation to glycolysis.

Inorganic polyphosphate (polyP) is a linear polymer composed of up to a few hundred orthophosphates linked together by high-energy phosphoanhydride bonds, identical with those found in ATP. In mammalian mitochondria, polyP has been implicated in multiple processes, including energy metabolism, ion channels function, and the regulation of calcium signaling. However, the specific mechanisms of all these effects of polyP within the organelle remain poorly understood. The central goal of this study was to investigate how mitochondrial polyP participates in the regulation of the mammalian cellular energy metabolism. To accomplish this, we created HEK293 cells depleted of mitochondrial polyP, through the stable expression of the polyP hydrolyzing enzyme (scPPX). We found that these cells have significantly reduced rates of oxidative phosphorylation (OXPHOS), while their rates of glycolysis were elevated. Consistent with this, metabolomics assays confirmed increased levels of metabolites involved in glycolysis in these cells, compared with the wild-type samples. At the same time, key respiratory parameters of the isolated mitochondria were unchanged, suggesting that respiratory chain activity is not affected by the lack of mitochondrial polyP. However, we detected that mitochondria from cells that lack mitochondrial polyP are more fragmented when compared with those from wild-type cells. Based on these results, we propose that mitochondrial polyP plays an important role as a regulator of the metabolic switch between OXPHOS and glycolysis.

Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring.

Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

Evaluation of potential metabolomic-based biomarkers of protein, carbohydrate and fat intakes using a controlled feeding study.

PURPOSE: Objective biomarkers of dietary exposure are needed to establish reliable diet-disease associations. Unfortunately, robust biomarkers of macronutrient intakes are scarce. We aimed to assess the utility of serum, 24-h urine and spot urine high-dimensional metabolites for the development of biomarkers of daily intake of total energy, protein, carbohydrate and fat, and the percent of energy from these macronutrients (%E). METHODS: A 2-week controlled feeding study mimicking the participants' habitual diets was conducted among 153 postmenopausal women from the Women's Health Initiative (WHI). Fasting serum metabolomic profiles were analyzed using a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for aqueous metabolites and a direct-injection-based quantitative lipidomics platform. Urinary metabolites were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy at 800 MHz and by untargeted gas chromatography-mass spectrometry (GC-MS). Variable selection was performed to build prediction models for each dietary variable. RESULTS: The highest cross-validated multiple correlation coefficients (CV-R2) for protein intake (%E) and carbohydrate intake (%E) using metabolites only were 36.3 and 37.1%, respectively. With the addition of established dietary biomarkers (doubly labeled water for energy and urinary nitrogen for protein), the CV-R2 reached 55.5% for energy (kcal/d), 52.0 and 45.0% for protein (g/d, %E), 55.9 and 37.0% for carbohydrate (g/d, %E). CONCLUSION: Selected panels of serum and urine metabolites, without the inclusion of doubly labeled water and urinary nitrogen biomarkers, give a reliable and robust prediction of daily intake of energy from protein and carbohydrate.

Plasma lipidomic profiles after a low and high glycemic load dietary pattern in a randomized controlled crossover feeding study.

BACKGROUND: Dietary patterns low in glycemic load are associated with reduced risk of cardiometabolic diseases. Improvements in serum lipid concentrations may play a role in these observed associations. OBJECTIVE: We investigated how dietary patterns differing in glycemic load affect clinical lipid panel measures and plasma lipidomics profiles. METHODS: In a crossover, controlled feeding study, 80 healthy participants (n = 40 men, n = 40 women), 18-45 y were randomized to receive low-glycemic load (LGL) or high glycemic load (HGL) diets for 28 days each with at least a 28-day washout period between controlled diets. Fasting plasma samples were collected at baseline and end of each diet period. Lipids on a clinical panel including total-, VLDL-, LDL-, and HDL-cholesterol and triglycerides were measured using an auto-analyzer. Lipidomics analysis using mass-spectrometry provided the concentrations of 863 species. Linear mixed models and lipid ontology enrichment analysis were implemented. RESULTS: Lipids from the clinical panel were not significantly different between diets. Univariate analysis showed that 67 species on the lipidomics panel, predominantly in the triacylglycerol class, were higher after the LGL diet compared to the HGL (FDR < 0.05). Three species with FA 17:0 were lower after LGL diet with enrichment analysis (FDR < 0.05). CONCLUSION: In the context of controlled eucaloric diets with similar macronutrient distribution, these results suggest that there are relative shifts in lipid species, but the overall pool does not change. Further studies are needed to better understand in which compartment the different lipid species are transported in blood, and how these shifts are related to health outcomes. This trial was registered at clinicaltrials.gov as NCT00622661.

Cerebrospinal fluid lipidomics: effects of an intravenous triglyceride infusion and apoE status.

INTRODUCTION: High-fat diets increase risk for Alzheimer's disease, but individuals with the risk gene APOE ε4 (E4) paradoxically have improved memory soon after high fat feeding. Little is known about how dietary lipids affect CNS lipids, especially in older adults. OBJECTIVES: We analyzed the lipidomic signature of cerebrospinal fluid (CSF) in older adults who underwent both a saline and TG infusion. We further analyzed these data by E4 carrier status. METHODS: Older adults (n = 21, age 67.7 ± 8.6) underwent a 5-h TG and saline infusion on different days in random crossover design; lumbar CSF was collected at the end of the infusion. Lipids were extracted using dichloromethane/methanol and 13 classes of lipids analyzed using the Lipidyzer platform consisting of an AB Sciex 5500 MS/MS QTraps system equipped with a SelexION for differential mobility spectrometry (DMS). Multiple reaction monitoring was used to target and quantify 1070 lipids in positive and negative ionization modes with and without DMS. RESULTS: The TG infusion increased total lipids in the CSF, including the appearance of more lipids at the detection limit in the TG samples compared to saline (Chi square p < 0.0001). The infusion increased the total level of diacylglycerols and lysophosphatidylcholines and reduced dihydroceramides. Of the possible 1070 lipids detectable, we found 348 after saline and 365 after TG infusion. Analysis using MetaboAnalyst revealed 11 specific lipids that changed; five of these lipids decreased after TG infusion, and four of them differed by E4 status, but none differed by cognitive diagnosis or sex. CONCLUSION: These results in older adults show that blood lipids affect lipid profiles in CSF and such profiles are modified by APOE status. This suggests that how the CNS handles lipids may be important in the AD phenotype.

Multiplatform Metabolomics Investigation of Antiadipogenic Effects on 3T3-L1 Adipocytes by a Potent Diarylheptanoid.

Obesity is fast becoming a serious health problem worldwide. Of the many possible antiobesity strategies, one interesting approach focuses on blocking adipocyte differentiation and lipid accumulation to counteract the rise in fat storage. However, there is currently no drug available for the treatment of obesity that works by inhibiting adipocyte differentiation. Here we use a broad-based metabolomics approach to interrogate and better understand metabolic changes that occur during adipocyte differentiation. In particular, we focus on changes induced by the antiadipogenic diarylheptanoid, which was isolated from a traditional Chinese medicine Dioscorea zingiberensis and identified as (3 R,5 R)-3,5-dihydroxy-1-(3,4-dihydroxyphenyl)-7-(4-hydroxyphenyl)-heptane (1). Targeted aqueous metabolic profiling indicated that a total of 14 metabolites involved in the TCA cycle, glycolysis, amino acid metabolism, and purine catabolism participate in regulating energy metabolism, lipogenesis, and lipolysis in adipocyte differentiation and can be modulated by diarylheptanoid 1. As indicated by lipidomics analysis, diarylheptanoid 1 restored the quantity and degree of unsaturation of long-chain free fatty acids and restored the levels of 171 lipids mainly from 10 lipid classes in adipocytes. In addition, carbohydrate metabolism in diarylheptanoid-1-treated adipocytes further demonstrated the delayed differentiation process by flux analysis. Our results provide valuable information for further understanding the metabolic adjustment in adipocytes subjected to diarylheptanoid 1 treatment. Moreover, this study offers new insight into developing antiadipogenic leading compounds based on metabolomics.

NMR-Guided Mass Spectrometry for Absolute Quantitation of Human Blood Metabolites.

Broad-based, targeted metabolite profiling using mass spectrometry (MS) has become a major platform used in the field of metabolomics for a variety of applications. However, quantitative MS analysis is challenging owing to numerous factors including (1) the need for, ideally, isotope-labeled internal standards for each metabolite, (2) the fact that such standards may be unavailable or prohibitively costly, (3) the need to maintain the standards' concentrations close to those of the target metabolites, and (4) the alternative use of time-consuming calibration curves for each target metabolite. Here, we introduce a new method in which metabolites from a single serum specimen are quantified on the basis of a recently developed NMR method [ Nagana Gowda et al. Anal. Chem. 2015 , 87 , 706 ] and then used as references for absolute metabolite quantitation using MS. The MS concentrations of 30 metabolites thus derived for test serum samples exhibited excellent correlations with the NMR ones (R2 > 0.99) with a median CV of 3.2%. This NMR-guided-MS quantitation approach is simple and easy to implement and offers new avenues for the routine quantification of blood metabolites using MS. The demonstration that NMR and MS data can be compared and correlated when using identical sample preparations allows improved opportunities to exploit their combined strengths for biomarker discovery and unknown-metabolite identification. Intriguingly, however, metabolites including glutamine, pyroglutamic acid, glucose, and sarcosine correlated poorly with NMR data because of stability issues in their MS analyses or weak or overlapping signals. Such information is potentially important for improving biomarker discovery and biological interpretations. Further, the new quantitation method demonstrated here for human blood serum can in principle be extended to a variety of biological mixtures.

Cerebrospinal Fluid Metabolomics: Pilot Study of Using Metabolomics to Assess Diet and Metabolic Interventions in Alzheimer's Disease and Mild Cognitive Impairment.

Brain glucose hypometabolism is an early sign of Alzheimer's disease (AD), and interventions which offset this deficit, such as ketogenic diets, show promise as AD therapeutics. Conversely, high-fat feeding may exacerbate AD risk. We analyzed the metabolomic profile of cerebrospinal fluid (CSF) in a pilot study of older adults who underwent saline and triglyceride (TG) infusions. Older adults (12 cognitively normal (CN), age 65.3 ± 8.1, and 9 with cognitive impairment (CI), age 70.9 ± 8.6) underwent a 5 h TG or saline infusion on different days using a random crossover design; CSF was collected at the end of infusion. Aqueous metabolites were measured using a targeted mass spectroscopy (MS) platform focusing on 215 metabolites from over 35 different metabolic pathways. Data were analyzed using MetaboAnalyst 4.0 and SAS. Of the 215 targeted metabolites, 99 were detectable in CSF. Only one metabolite significantly differed by treatment: the ketone body 3-hydroxybutyrate (HBA). Post hoc analyses showed that HBA levels were associated with age and markers of metabolic syndrome and demonstrated different correlation patterns for the two treatments. When analyzed by cognitive diagnosis group, TG-induced increases in HBA were over 3 times higher for those with cognitive impairment (change score CN +9.8 uM ± 8.3, CI +32.4 ± 7.4, p = 0.0191). Interestingly, individuals with cognitive impairment had higher HBA levels after TG infusion than those with normal cognition. These results suggest that interventions that increase plasma ketones may lead to higher brain ketones in groups at risk for AD and should be confirmed in larger intervention studies.

The lipidomes of C. elegans with mutations in asm-3/acid sphingomyelinase and hyl-2/ceramide synthase show distinct lipid profiles during aging.

Lipid metabolism affects cell and physiological functions that mediate animal healthspan and lifespan. Lipidomics approaches in model organisms have allowed us to better understand changes in lipid composition related to age and lifespan. Here, using the model C. elegans, we examine the lipidomes of mutants lacking enzymes critical for sphingolipid metabolism; specifically, we examine acid sphingomyelinase (asm-3), which breaks down sphingomyelin to ceramide, and ceramide synthase (hyl-2), which synthesizes ceramide from sphingosine. Worm asm-3 and hyl-2 mutants have been previously found to be long- and short-lived, respectively. We analyzed longitudinal lipid changes in wild type animals compared to mutants at 1-, 5-, and 10-days of age. We detected over 700 different lipids in several lipid classes. Results indicate that wildtype animals exhibit increased triacylglycerols (TAG) at 10-days compared to 1-day, and decreased lysophoshatidylcholines (LPC). We find that 10-day hyl-2 mutants have elevated total polyunsaturated fatty acids (PUFA) and increased LPCs compared to 10-day wildtype animals. These changes mirror another short-lived model, the daf-16/FOXO transcription factor that is downstream of the insulin-like signaling pathway. In addition, we find that hyl-2 mutants have poor oxidative stress response, supporting a model where mutants with elevated PUFAs may accumulate more oxidative damage. On the other hand, 10-day asm-3 mutants have fewer TAGs. Intriguingly, asm-3 mutants have a similar lipid composition as the long-lived, caloric restriction model eat-2/mAChR mutant. Together, these analyses highlight the utility of lipidomic analyses to characterize metabolic changes during aging in C. elegans.

Demographic, Health and Lifestyle Factors Associated with the Metabolome in Older Women.

Demographic and clinical factors influence the metabolome. The discovery and validation of disease biomarkers are often challenged by potential confounding effects from such factors. To address this challenge, we investigated the magnitude of the correlation between serum and urine metabolites and demographic and clinical parameters in a well-characterized observational cohort of 444 post-menopausal women participating in the Women's Health Initiative (WHI). Using LC-MS and lipidomics, we measured 157 aqueous metabolites and 756 lipid species across 13 lipid classes in serum, along with 195 metabolites detected by GC-MS and NMR in urine and evaluated their correlations with 29 potential disease risk factors, including demographic, dietary and lifestyle factors, and medication use. After controlling for multiple testing (FDR < 0.01), we found that log-transformed metabolites were mainly associated with age, BMI, alcohol intake, race, sample storage time (urine only), and dietary supplement use. Statistically significant correlations were in the absolute range of 0.2-0.6, with the majority falling below 0.4. Incorporation of important potential confounding factors in metabolite and disease association analyses may lead to improved statistical power as well as reduced false discovery rates in a variety of data analysis settings.

Predictive Modeling of Alzheimer's and Parkinson's Disease Using Metabolomic and Lipidomic Profiles from Cerebrospinal Fluid.

In recent years, metabolomics has been used as a powerful tool to better understand the physiology of neurodegenerative diseases and identify potential biomarkers for progression. We used targeted and untargeted aqueous, and lipidomic profiles of the metabolome from human cerebrospinal fluid to build multivariate predictive models distinguishing patients with Alzheimer's disease (AD), Parkinson's disease (PD), and healthy age-matched controls. We emphasize several statistical challenges associated with metabolomic studies where the number of measured metabolites far exceeds sample size. We found strong separation in the metabolome between PD and controls, as well as between PD and AD, with weaker separation between AD and controls. Consistent with existing literature, we found alanine, kynurenine, tryptophan, and serine to be associated with PD classification against controls, while alanine, creatine, and long chain ceramides were associated with AD classification against controls. We conducted a univariate pathway analysis of untargeted and targeted metabolite profiles and find that vitamin E and urea cycle metabolism pathways are associated with PD, while the aspartate/asparagine and c21-steroid hormone biosynthesis pathways are associated with AD. We also found that the amount of metabolite missingness varied by phenotype, highlighting the importance of examining missing data in future metabolomic studies.

A Metabolomic Aging Clock Using Human Cerebrospinal Fluid.

Quantifying the physiology of aging is essential for improving our understanding of age-related disease and the heterogeneity of healthy aging. Recent studies have shown that, in regression models using "-omic" platforms to predict chronological age, residual variation in predicted age is correlated with health outcomes, and suggest that these "omic clocks" provide measures of biological age. This paper presents predictive models for age using metabolomic profiles of cerebrospinal fluid (CSF) from healthy human subjects and finds that metabolite and lipid data are generally able to predict chronological age within 10 years. We use these models to predict the age of a cohort of subjects with Alzheimer's and Parkinson's disease and find an increase in prediction error, potentially indicating that the relationship between the metabolome and chronological age differs with these diseases. However, evidence is not found to support the hypothesis that our models will consistently overpredict the age of these subjects. In our analysis of control subjects, we find the carnitine shuttle, sucrose, biopterin, vitamin E metabolism, tryptophan, and tyrosine to be the most associated with age. We showcase the potential usefulness of age prediction models in a small data set (n = 85) and discuss techniques for drift correction, missing data imputation, and regularized regression, which can be used to help mitigate the statistical challenges that commonly arise in this setting. To our knowledge, this work presents the first multivariate predictive metabolomic and lipidomic models for age using mass spectrometry analysis of CSF.

Persistent metabolomic alterations characterize chronic critical illness after severe trauma.

BACKGROUND: Following trauma, persistent inflammation, immunosuppression, and catabolism may characterize delayed recovery or failure to recover. Understanding the metabolic response associated with these adverse outcomes may facilitate earlier identification and intervention. We characterized the metabolic profiles of trauma victims who died or developed chronic critical illness (CCI) and hypothesized that differences would be evident within 1-week postinjury. METHODS: Venous blood samples from trauma victims with shock who survived at least 7 days were analyzed using mass spectrometry. Subjects who died or developed CCI (intensive care unit length of stay of ≥14 days with persistent organ dysfunction) were compared with subjects who recovered rapidly (intensive care unit length of stay, ≤7 days) and uninjured controls. We used partial least squares discriminant analysis, t tests, linear mixed effects regression, and pathway enrichment analyses to make broad comparisons and identify differences in metabolite concentrations and pathways. RESULTS: We identified 27 patients who died or developed CCI and 33 who recovered rapidly. Subjects were predominantly male (65%) with a median age of 53 years and Injury Severity Score of 36. Healthy controls (n = 48) had similar age and sex distributions. Overall, from the 163 metabolites detected in the samples, 56 metabolites and 21 pathways differed between injury outcome groups, and partial least squares discriminant analysis models distinguished injury outcome groups as early as 1-day postinjury. Differences were observed in tryptophan, phenylalanine, and tyrosine metabolism; metabolites associated with oxidative stress via methionine metabolism; inflammatory mediators including kynurenine, arachidonate, and glucuronic acid; and products of the gut microbiome including indole-3-propionate. CONCLUSIONS: The metabolic profiles in subjects who ultimately die or develop CCI differ from those who have recovered. In particular, we have identified differences in markers of inflammation, oxidative stress, amino acid metabolism, and alterations in the gut microbiome. Targeted metabolomics has the potential to identify important metabolic changes postinjury to improve early diagnosis and targeted intervention. LEVEL OF EVIDENCE: Prognostic/epidemiologic, level III.

A DMS Shotgun Lipidomics Workflow Application to Facilitate High-Throughput, Comprehensive Lipidomics.

Differential mobility spectrometry (DMS) is highly useful for shotgun lipidomic analysis because it overcomes difficulties in measuring isobaric species within a complex lipid sample and allows for acyl tail characterization of phospholipid species. Despite these advantages, the resulting workflow presents technical challenges, including the need to tune the DMS before every batch to update compensative voltages settings within the method. The Sciex Lipidyzer platform uses a Sciex 5500 QTRAP with a DMS (SelexION), an LC system configured for direction infusion experiments, an extensive set of standards designed for quantitative lipidomics, and a software package (Lipidyzer Workflow Manager) that facilitates the workflow and rapidly analyzes the data. Although the Lipidyzer platform remains very useful for DMS-based shotgun lipidomics, the software is no longer updated for current versions of Analyst and Windows. Furthermore, the software is fixed to a single workflow and cannot take advantage of new lipidomics standards or analyze additional lipid species. To address this multitude of issues, we developed Shotgun Lipidomics Assistant (SLA), a Python-based application that facilitates DMS-based lipidomics workflows. SLA provides the user with flexibility in adding and subtracting lipid and standard MRMs. It can report quantitative lipidomics results from raw data in minutes, comparable to the Lipidyzer software. We show that SLA facilitates an expanded lipidomics analysis that measures over 1450 lipid species across 17 (sub)classes. Lastly, we demonstrate that the SLA performs isotope correction, a feature that was absent from the original software.

Quantitative global lipidomics analysis of patients with ovarian cancer versus benign adnexal mass.

Altered lipid metabolism has emerged as an important feature of ovarian cancer (OC), yet the translational potential of lipid metabolites to aid in diagnosis and triage remains unproven. We conducted a multi-level interrogation of lipid metabolic phenotypes in patients with adnexal masses, integrating quantitative lipidomics profiling of plasma and ascites with publicly-available tumor transcriptome data. Using Sciex Lipidyzer, we assessed concentrations of > 500 plasma lipids in two patient cohorts-(i) a pilot set of 100 women with OC (50) or benign tumor (50), and (ii) an independent set of 118 women with malignant (60) or benign (58) adnexal mass. 249 lipid species and several lipid classes were significantly reduced in cases versus controls in both cohorts (FDR < 0.05). 23 metabolites-triacylglycerols, phosphatidylcholines, cholesterol esters-were validated at Bonferroni significance (P < 9.16 × 10-5). Certain lipids exhibited greater alterations in early- (diacylglycerols) or late-stage (lysophospholipids) cases, and multiple lipids in plasma and ascites were positively correlated. Lipoprotein receptor gene expression differed markedly in OC versus benign tumors. Importantly, several plasma lipid species, such as DAG(16:1/18:1), improved the accuracy of CA125 in differentiating early-stage OC cases from benign controls, and conferred a 15-20% increase in specificity at 90% sensitivity in multivariate models adjusted for age and BMI. This study provides novel insight into systemic and local lipid metabolic differences between OC and benign disease, further implicating altered lipid uptake in OC biology, and advancing plasma lipid metabolites as a complementary class of circulating biomarkers for OC diagnosis and triage.

Metabolomic profiling for juvenile Chinook salmon exposed to contaminants of emerging concern.

Both targeted and non-targeted metabolomic analyses were conducted on juvenile ocean-type fall Chinook salmon (Oncorhynchus tshawytscha) residing in two estuaries receiving wastewater treatment plant (WWTP) effluent and one reference estuary. The data show that the metabolome patterns for fish from the two WWTP-receiving estuaries were more similar to each other compared to that for the reference site fish. Also, a comparison of the metabolome for fish from the reference site and fish from a hatchery upstream of one of the effluent-receiving estuaries indicated no differences, implying that residency for fish in the contaminated estuary resulted in major changes to the metabolome. Based on general health parameters including whole-body lipid content and condition factor, plus the availability of prey for these fish, we conclude that juvenile Chinook salmon in these contaminated estuaries may have been experiencing metabolic disruption without any overt signs of impairment. Additionally, a non-targeted analysis was performed on hatchery summer Chinook salmon from a laboratory study where fish were dosed for 32 days with feed containing 16 of the most common contaminants of emerging concern (CECs) detected in wild fish. In the laboratory experiment a relationship was observed between dose and the number of liver metabolites that were different between control and treatment fish. Laboratory fish were exposed to only 16 CECs, but are generally exposed to hundreds of these compounds in contaminated aquatic environments. These results have implications for the health of juvenile Chinook salmon and the likelihood of a successful life cycle when exposed to effluent-related chemicals.

Small changes in glucose variability induced by low and high glycemic index diets are not associated with changes in ß-cell function in adults with pre-diabetes.

Oscillating glucose levels can increase oxidative stress and may contribute to ß-cell dysfunction. We tested the hypothesis that increased glycemic variability contributes to ß-cell dysfunction by experimentally altering glucose variability with controlled diets varying in glycemic index (GI). Fifty-two adults with prediabetes received a 2-week moderate GI (GI = 55-58) control diet followed by randomization to a four-week low GI (LGI: GI < 35) or high GI (HGI HI > 70) diet. Those on the HGI diet were randomized to placebo or the antioxidant N-acetylcysteine (NAC). Participants underwent blinded CGMS, fasting oxidative stress markers and an intravenous glucose tolerance test to estimate ß-cell function (disposition index: DI). On the control diet, DI was inversely correlated with SD glucose (r = -0.314, p = 0.03), but neither DI nor glucose variability were associated with oxidative stress markers. The LGI diet decreased SD glucose (Control 0.96 ±â€¯0.08 vs. LGI 0.79 ±â€¯0.06, p = 0.02) while the HGI diet increased it (Control 0.88 ±â€¯0.06 vs. HGI 1.06 ±â€¯0.07, p = 0.03). Neither DI nor oxidative stress markers changed after the LGI or HGI diets. NAC had no effect on DI, glucose variability or oxidative stress markers. We conclude small changes in glucose variability induced by dietary GI in adults with pre-diabetes are unlikely to contribute to ß-cell dysfunction.