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Abstract In this community effort, we compare measurements between 34 laboratories from 19 countries, utilizing mixtures of labelled authentic synthetic standards, to quantify by mass spectrometry four clinically used ceramide species in the NIST (National Institute of Standards and Technology) human blood plasma Standard Reference Material (SRM) 1950, as well as a set of candidate plasma reference materials (RM 8231). Participants either utilized a provided validated method and/or their method of choice. Mean concentration values, and intra- and inter-laboratory coefficients of variation (CV) were calculated using single-point and multi-point calibrations, respectively. These results are the most precise (intra-laboratory CVs ≤ 4.2%) and concordant (inter-laboratory CVs < 14%) community-derived absolute concentration values reported to date for four clinically used ceramides in the commonly analyzed SRM 1950. We demonstrate that calibration using authentic labelled standards dramatically reduces data variability. Furthermore, we show how the use of shared RM can correct systematic quantitative biases and help in harmonizing lipidomics. Collectively, the results from the present study provide a significant knowledge base for translation of lipidomic technologies to future clinical applications that might require the determination of reference intervals (RIs) in various human populations or might need to estimate reference change values (RCV), when analytical variability is a key factor for recall during multiple testing of individuals.

Abstract Background Isoprostanes and prostaglandins are biomarkers for oxidative stress and inflammation. Their role in Alzheimer's disease (AD) pathophysiology is yet unknown. In the current study, we aim to identify the association of isoprostanes and prostaglandins with the Amyloid, Tau, Neurodegeneration (ATN) biomarkers (Aβ-42, p-tau, and t-tau) of AD pathophysiology in mild cognitive impairment (MCI) subjects. Methods Targeted metabolomics profiling was performed using liquid chromatography-mass spectrometry (LCMS) in 147 paired plasma-CSF samples from the Ace Alzheimer Center Barcelona and 58 CSF samples of MCI patients from the Mannheim/Heidelberg cohort. Linear regression was used to evaluate the association of metabolites with CSF levels of ATN biomarkers in the overall sample and stratified by Aβ-42 pathology and APOE genotype. We further evaluated the role of metabolites in MCI to AD dementia progression. Results Increased CSF levels of PGF2α, 8,12-iso-iPF2α VI, and 5-iPF2α VI were significantly associated (False discovery rate (FDR)

Abstract Background Sarcopenia is characterized by loss of skeletal muscle mass and function, and is a major risk factor for disability and independence in the elderly. Effective medication is not available. Dietary restriction (DR) has been found to attenuate aging and aging‐related diseases, including sarcopenia, but the mechanism of both DR and sarcopenia are incompletely understood. Methods In this study, mice body weight, fore and all limb grip strength, and motor learning and coordination performance were first analysed to evaluate the DR effects on muscle functioning. Liquid chromatography–mass spectrometry (LC–MS) was utilized for the metabolomics study of the DR effects on sarcopenia in progeroid DNA repair‐deficient Ercc1∆/− and Xpg−/− mice, to identify potential biomarkers for attenuation of sarcopenia. Results Muscle mass was significantly (P

Abstract Background The gut-derived metabolite Trimethylamine N-oxide (TMAO) and its precursors - betaine, carnitine, choline, and deoxycarnitine – have been associated with an increased risk of cardiovascular disease, but their relation to cognition, neuroimaging markers, and dementia remains uncertain. Methods In the population-based Rotterdam Study, we used multivariable regression models to study the associations between plasma TMAO, its precursors, and cognition in 3,143 participants. Subsequently, we examined their link to structural brain MRI markers in 2,047 participants, with a partial validation in the Leiden Longevity Study (n = 318). Among 2,517 participants, we assessed the risk of incident dementia using multivariable Cox proportional hazard models. Following this, we stratified the longitudinal associations by medication use and sex, after which we conducted a sensitivity analysis for individuals with impaired renal function. Results Overall, plasma TMAO was not associated with cognition, neuroimaging markers or incident dementia. Instead, higher plasma choline was significantly associated with poor cognition (adjusted mean difference: -0.170 [95% confidence interval (CI) -0.297;-0.043]), brain atrophy and more markers of cerebral small vessel disease, such as white matter hyperintensity volume (0.237 [95% CI: 0.076;0.397]). By contrast, higher carnitine concurred with lower white matter hyperintensity volume (-0.177 [95% CI: -0.343;-0.010]). Only among individuals with impaired renal function, TMAO appeared to increase risk of dementia (hazard ratio (HR): 1.73 [95% CI: 1.16;2.60]). No notable differences were observed in stratified analyses. Conclusions Plasma choline, as opposed to TMAO, was found to be associated with cognitive decline, brain atrophy, and markers of cerebral small vessel disease. These findings illustrate the complexity of relationships between TMAO and its precursors, and emphasize the need for concurrent study to elucidate gut-brain mechanisms.

Abstract Microbial natural products form the basis of most of the antibiotics used in the clinic. The vast majority has not yet been discovered, among others because the hidden chemical space is obscured by previously identified (and typically abundant) antibiotics in culture extracts. Efficient dereplication is therefore key to the discovery of our future medicines. Here we present an analytical platform for the efficient identification and prioritization of low abundance bioactive compounds at nanoliter scale, called nanoRAPIDS. NanoRAPIDS encompasses analytical scale separation and nanofractionation of natural extracts, followed by the bioassay of interest, automated mass spectrometry identification, and Global Natural Products Social molecular networking (GNPS) for dereplication. As little as 10 μL crude extract is fractionated into 384 fractions. First, bioactive congeners of iturins and surfactins were identified in Bacillus, based on their bioactivity. Subsequently, bioactive molecules were identified in an extensive network of angucyclines elicited by catechol in cultures of Streptomyces sp. This allowed the discovery of a highly unusual N-acetylcysteine conjugate of saquayamycin, despite low production levels in an otherwise abundant molecular family. These data underline the utility and broad application of the technology for the prioritization of minor bioactive compounds in complex extracts.

Background and Aims: Endothelial cell (EC) dysfunction in response to circulating plasma factors is a known causal factor in many systemic diseases. However, no appropriate assay is available to investigate this causality ex vivo. In liver cirrhosis, systemic inflammation is identified as central mechanism in progression from compensated to decompensated cirrhosis (DC), but the role of ECs therein is unknown. We aimed to develop a novel ex vivo assay for assessing EC responses to patient-derived plasma (PDP) and assess the potential of this assay in a cohort of liver cirrhosis patients. Methods: Image-based morphological profiling was utilized to assess the impact of PDP on cultured ECs. Endothelial cell (EC) monolayers were exposed to 25% stabilized PDP (20 compensated cirrhoses, 20 DCs, and 20 healthy controls (HCs). Single-cell morphological profiles were extracted by automated image-analysis following staining of multiple cellular components and high-content imaging. Patient profiles were created by dimension reduction and cell-to-patient data aggregation, followed by multivariate-analysis to stratify patients and identify discriminating features. Results: Patient-derived plasma (PDP) exposure induced profound changes in EC morphology, displaying clear differences between controls and DC patients. Compensated cirrhosis patients showed overlap with healthy controls and DC patients. Supervised analysis showed Child-Pugh (CP) class could be predicted from EC morphology. Most importantly, CP-C patients displayed distinct EC phenotypes, in which mitochondrial changes were most discriminative. Conclusion: Morphological profiling presents a viable tool to assess the endothelium ex vivo. We demonstrated that the EC phenotype corresponds with disease severity in liver cirrhosis. Moreover, our results suggest the presence of mitochondrial dysfunction in ECs of CP-C patient.

Abstract Trimethylamine N‐oxide (TMAO) is a circulating microbiome‐derived metabolite implicated in the development of atherosclerosis and cardiovascular disease (CVD). We investigated whether plasma levels of TMAO, its precursors (betaine, carnitine, deoxycarnitine, choline), and TMAO‐to‐precursor ratios are associated with clinical outcomes, including CVD and mortality. This was followed by an in‐depth analysis of their genetic, gut microbial, and dietary determinants. The analyses were conducted in five Dutch prospective cohort studies including 7834 individuals. To further investigate association results, Mendelian Randomization (MR) was also explored. We found only plasma choline levels (hazard ratio [HR] 1.17, [95% CI 1.07; 1.28]) and not TMAO to be associated with CVD risk. Our association analyses uncovered 10 genome‐wide significant loci, including novel genomic regions for betaine (6p21.1, 6q25.3), choline (2q34, 5q31.1), and deoxycarnitine (10q21.2, 11p14.2) comprising several metabolic gene associations, for example, CPS1 or PEMT. Furthermore, our analyses uncovered 68 gut microbiota associations, mainly related to TMAO‐to‐precursors ratios and the Ruminococcaceae family, and 16 associations of food groups and metabolites including fish‐TMAO, meat‐carnitine, and plant‐based food‐betaine associations. No significant association was identified by the MR approach. Our analyses provide novel insights into the TMAO pathway, its determinants, and pathophysiological impact on the general population.

Abstract Monoacylglycerol lipase (MAGL) regulates endocannabinoid 2-arachidonoylglycerol (2-AG) and eicosanoid signalling. MAGL inhibition provides therapeutic opportunities but clinical potential is limited by central nervous system (CNS)-mediated side effects. Here, we report the discovery of LEI-515, a peripherally restricted, reversible MAGL inhibitor, using high throughput screening and a medicinal chemistry programme. LEI-515 increased 2-AG levels in peripheral organs, but not mouse brain. LEI-515 attenuated liver necrosis, oxidative stress and inflammation in a CCl4-induced acute liver injury model. LEI-515 suppressed chemotherapy-induced neuropathic nociception in mice without inducing cardinal signs of CB1 activation. Antinociceptive efficacy of LEI-515 was blocked by CB2, but not CB1, antagonists. The CB1 antagonist rimonabant precipitated signs of physical dependence in mice treated chronically with a global MAGL inhibitor (JZL184), and an orthosteric cannabinoid agonist (WIN55,212-2), but not with LEI-515. Our data support targeting peripheral MAGL as a promising therapeutic strategy for developing safe and effective anti-inflammatory and analgesic agents.

Introduction The prevalence of non-alcoholic fatty liver disease (NAFLD) ranges from 25% in the general population to 90% in patients with obesity scheduled for bariatric surgery. NAFLD can progress towards non-alcoholic steatohepatitis (NASH) associated with complications such as cirrhosis, hepatocellular carcinoma and cardiovascular disease. To date, losing weight and lifestyle modifications are the best known treatments for NASH. Bariatric surgery significantly improves NAFLD/NASH in the short term. However, the extent of this improvement is not yet clear and long-term data on the natural course of NAFLD/NASH after bariatric surgery are lacking. The factors involved in NAFLD/NASH regression after bariatric surgery have not been elucidated.Methods and analysis This is an observational prospective cohort study including patients scheduled for bariatric surgery. Extensive metabolic and cardiovascular analyses will be carried out including measurements of carotid intima media thickness and pulse wave velocity. Genomic, proteomic, lipidomic and metabolomic studies will be done. Microbioma analyses before and 1 year after surgery will be done. Transient elastography measurements will be performed before and at 1, 3 and 5 years after surgery. For those with an elevated preoperative transient elastography measurement by Fibroscan, a laparoscopic liver biopsy will be performed during surgery. Primary outcome measures are the change of steatosis and liver fibrosis 5 years after surgery. Secondary outcome measure is the comparison of the transient elastography measurements with the NAFLD Activity Score from the biopsies.Ethics and dissemination The protocol has been approved by the Medical Research Ethics Committees United, Nieuwegein, on 1 March 2022 (registration code R21.103/NL79423.100.21). The study results will be submitted for publication in peer-reviewed journals and data will be presented at scientific meetings.Trial registration number NCT05499949.

The severity of COVID-19 is linked to an imbalanced immune response. The dysregulated metabolism of small molecules and bioactive lipids has also been associated with disease severity. To promote understanding of the disease biochemistry and provide targets for intervention, we applied a range of LC-MS platforms to analyze over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). This is the third publication in a series, and it reports the results of comprehensive lipidome profiling using targeted LC-MS/MS. We identified 1076 lipid features across 25 subclasses, including glycerophospholipids, sterols, glycerolipids, and sphingolipids, among which 531 lipid features were dramatically changed in the plasma of intensive care unit (ICU) patients compared to patients in the ward. Patients in the ICU showed 1.3–57-fold increases in ceramides, (lyso-)glycerophospholipids, diglycerides, triglycerides, and plasmagen phosphoethanolamines, and 1.3–2-fold lower levels of a cyclic lysophosphatidic acid, sphingosine-1-phosphates, sphingomyelins, arachidonic acid-containing phospholipids, lactosylceramide, and cholesterol esters compared to patients in the ward. Specifically, phosphatidylinositols (PIs) showed strong fatty acid saturation-dependent behavior, with saturated fatty acid (SFA)- and monosaturated fatty acid (MUFA)-derived PI decreasing and polystaturated (PUFA)-derived PI increasing. We also found ~4000 significant Spearman correlations between lipids and multiple clinical markers of immune response with |R| ≥ 0.35 and FDR corrected Q < 0.05. Except for lysophosphatidic acid, lysophospholipids were positively associated with the CD4 fraction of T cells, and the cytokines IL-8 and IL-18. In contrast, sphingosine-1-phosphates were negatively correlated with innate immune markers such as CRP and IL-6. Further indications of metabolic changes in moderate COVID-19 disease were demonstrated in recovering ward patients compared to those at the start of hospitalization, where 99 lipid species were altered (6 increased by 30–62%; 93 decreased by 1.3–2.8-fold). Overall, these findings support and expand on early reports that dysregulated lipid metabolism is involved in COVID-19.

Background: Metabolic changes induced by the host immune response to pathogens found in patients with community-acquired pneumonia (CAP) may provide insight into its pathogenesis. In this study, we characterized differences in the host metabolic response to common CAP-associated pathogens. Method: Targeted metabolomic profiling was performed on serum samples obtained from hospitalized CAP patients (n = 119) at admission. We quantified 347 unique metabolites across multiple biochemical classes, including amines, acylcarnitines, and signaling lipids. We evaluated if unique associations between metabolite levels and specific CAP-associated pathogens could be identified. Results: Several acylcarnitines were found to be elevated in C. burnetii and herpes simplex virus and lowered in M. pneumoniae as compared to other pathogens. Phenylalanine and kynurenine were found elevated in L. pneumophila as compared to other pathogens. S-methylcysteine was elevated in patients with M. pneumoniae, and these patients also showed lowered cortisol levels in comparison to almost all other pathogens. For the herpes simplex virus, we observed a unique elevation of eicosanoids and several amines. Many lysophosphatidylcholines showed an altered profile in C. burnetii versus S. pneumoniae, L. pneumophila, and respiratory syncytial virus. Finally, phosphatidylcholines were negatively affected by the influenza virus in comparison to S. pneumoniae. Conclusions: In this exploratory analysis, metabolites from different biochemical classes were found to be altered in serum samples from patients with different CAP-associated pathogens, which may be used for hypothesis generation in studies on differences in pathogen host response and pathogenesis of CAP.

Abstract The majority of disease modifying therapies for multiple sclerosis (MS) reduce inflammation, but do no’t target remyelination. Development of remyelinating therapies will benefit from a method to quantify myelin kinetics in patients with MS. We labeled myelin in vivo with deuterium, and modeled kinetics of myelin breakdown products β‐galactosylceramide (β‐GalC) and N‐Octadecanoyl‐sulfatide (NO‐Sulf). Five patients with MS received 120 ml 70% D2O daily for 70 days and were compared with six healthy subjects who previously received the same procedure. Mass spectrometry and compartmental modeling were used to quantify the turnover rate of β‐GalC and NO‐Sulf in cerebrospinal fluid (CSF). Turnover rate constants of the fractions of β‐GalC and NO‐Sulf with non‐negligible turnover were 0.00186 and 0.00714, respectively, in both healthy subjects and patients with MS. The turnover half‐life of β‐GalC and NO‐Sulf was calculated as 373 days and 96.5 days, respectively. The effect of MS on the NO‐Sulf (49.4% lower fraction with non‐negligible turnover) was more pronounced compared to the effect on β‐GalC turnover (18.3% lower fraction with non‐negligible turnover). Kinetics of myelin breakdown products in the CSF are different in patients with MS compared with healthy subjects. This may be caused by slower myelin production in these patients, by a higher level of degradation of a more stable component of myelin, or, most likely, by a combination of these two processes. Labeling myelin breakdown products is a useful method that can be used to quantify myelin turnover in patients with progressive MS and can therefore be used in proof‐of‐concept studies with remyelination therapies.

Abstract Streptomycetes are major producers of bioactive natural products, including the majority of the naturally produced antibiotics. While much of the low-hanging fruit has been discovered, it is predicted that less than 5% of the chemical space of natural products has been mined. Here, we describe the discovery of the novel actinomycins L1 and L2 produced by Streptomyces sp. MBT27, via application of metabolic analysis and molecular networking. Actinomycins L1 and L2 are diastereomers, and the structure of actinomycin L2 was resolved using NMR and single crystal X-ray crystallography. Actinomycin L is formed via spirolinkage of anthranilamide to the 4-oxoproline moiety of actinomycin X2, prior to the condensation of the actinomycin halves. Such a structural feature has not previously been identified in naturally occurring actinomycins. Adding anthranilamide to cultures of the actinomycin X2 producer Streptomyces antibioticus, which has the same biosynthetic gene cluster as Streptomyces sp. MBT27, resulted in the production of actinomycin L. This supports a biosynthetic pathway whereby actinomycin L is produced from two distinct metabolic routes, namely those for actinomycin X2 and for anthranilamide. Actinomycins L1 and L2 showed significant antimicrobial activity against Gram-positive bacteria. Our work shows how new molecules can still be identified even in the oldest of natural product families.

Abstract Protein arginine methyltransferase 3 (PRMT3) is a co-activator of liver X receptor capable of selectively modulating hepatic triglyceride synthesis. Here we investigated whether pharmacological PRMT3 inhibition can diminish the hepatic steatosis extent and lower plasma lipid levels and atherosclerosis susceptibility. Hereto, male hyperlipidemic low-density lipoprotein receptor knockout mice were fed an atherogenic Western-type diet and injected 3 times per week intraperitoneally with PRMT3 inhibitor SGC707 or solvent control. Three weeks into the study, SGC707-treated mice developed severe pruritus and scratching-associated skin lesions, leading to early study termination. SGC707-treated mice exhibited 50% lower liver triglyceride stores as well as 32% lower plasma triglyceride levels. Atherosclerotic lesions were virtually absent in all experimental mice. Plasma metabolite analysis revealed that levels of taurine-conjugated bile acids were ~ threefold increased (P

Accurate prediction of preterm birth is currently challenging, resulting in unnecessary maternal hospital admittance and fetal overexposure to antenatal corticosteroids. Novel biomarkers like volatile organic compounds (VOCs) hold potential for predictive, bed-side clinical applicability. In a proof of principle study, we aimed to assess the predictive potential of urinary volatile organic compounds in the identification of pregnant women at risk for preterm birth. Urine samples of women with a high risk for preterm birth (≧24 + 0 until 36 + 6 weeks) were collected prospectively and analyzed for VOCs using gas chromatography coupled with an ion mobility spectrometer (GS-IMS). Urinary VOCs of women delivering preterm were compared with urine samples of women with suspicion of preterm birth collected at the same gestation period but delivering at term. Additionally, the results were also interpreted in combination with patient characteristics, such as physical examination at admission, microbial cultures, and placental pathology. In our cohort, we found that urinary VOCs of women admitted for imminent preterm birth were not significantly different in the overall group of women delivering preterm vs. term. However, urinary VOCs of women admitted for imminent preterm birth and delivering between 28 + 0 until 36 + 6 weeks compared to women with a high risk for preterm birth during the same gestation period and eventually delivering at term (>37 + 0 weeks) differed significantly (area under the curve: 0.70). In addition, based on the same urinary VOCs, we could identify women with a confirmed chorioamnionitis (area under the curve: 0.72) and urinary tract infection (area under the curve: 0.97). In conclusion, urinary VOCs hold potential for non-invasive, bedside prediction of preterm birth and on the spot identification of intra-uterine infection and urinary tract infections. We suggest these observations are further explored in larger populations.

Summary: Background: Fatty acid-derived lipid mediators including oxylipins, endocannabinoids (eCBs), and their analogues, have emerged as key metabolites in the inflammatory and immune response to physiological stressors. Methods: This report was based on a sub-study and secondary analyses the ACTIBATE single-center unblinded randomized controlled trial (ClinicalTrials.gov ID: NCT02365129). The study was performed in the Sport and Health University Research Institute and the Virgen de las Nieves University Hospital of the University of Granada. Eligible participants were young, sedentary adults with no chronic diseases. Here, we performed both an acute endurance and resistance exercise sub-studies (n.ß=.ß14 and 17 respectively), and a 24-week supervised exercise intervention, combining endurance and resistance exercise training at moderate-intensity (MOD-EX) or vigorous-intensity (VIG-EX) exercise groups, in young sedentary adults. Randomization was performed by unrestricted randomization. Plasma levels of oxylipins, eCBs, and their analogues were measured using liquid chromatography-tandem mass spectrometry. Findings: Both endurance and resistance exercise increased by.ß+50% the plasma levels of dihomo-..-linolenic acid and arachidonic acid (AA) omega-6 derived oxylipins, as well as eicosapentaenoic acid and docosahexaenoic acid omega-3 derived after 3 and 120.ßmin of the bout of exercise (all ..2.ß....ß0.219 and P.ß..±.ß0.039). These exercise modalities also increased the levels of anandamide and eCBs analogues (+25%). 145 young sedentary adults were assigned to a control (CON, n.ß=.ß54), a MOD-EX (n.ß=.ß48) or a VIG-EX (n.ß=.ß43). 102 participants were included in the final long-term analyses (CON, n.ß=.ß36; MOD-EX, n.ß=.ß33; and VIG-EX, n.ß=.ß33) of the trial. After 24-week of supervised exercise, MOD-EX decreased plasma levels of omega-6 oxylipins, concretely linoleic acid (LA) and adrenic acid derived oxylipins, and the eCBs analogues OEA and LEA in comparison to the CON (all P.ß..±.ß0.021). VIG-EX decreased LA-derived oxylipins and LEA compared to CON. No relevant adverse events were recorded. Interpretation: Endurance and resistance exercises acutely increased plasma levels of oxylipins, eCBs, and their analogues, whereas 24 weeks of exercise training decreased fasting plasma levels of omega-6 oxylipins, and eCBs analogues in young, sedentary adults. Funding: See Acknowledgments section.

Abstract Background Leptin plays a critical role in the regulation of metabolic homeostasis. However, the molecular mechanism and cross talks between leptin and metabolic pathways leading to metabolic homeostasis across different species are not clear. This study aims to explore the effects of leptin in mice and zebrafish larvae by integration of metabolomics and transcriptomics. Different metabolomic approaches including mass spectrometry, nuclear magnetic resonance (NMR) and high-resolution magic-angle-spinning NMR spectrometry were used to investigate the metabolic changes caused by leptin deficiency in mutant ob/ob adult mice and lepb −/− zebrafish larvae. For transcriptome studies, deep RNA sequencing was used. Results Thirteen metabolites were identified as common biomarkers discriminating ob/ob mice and lepb −/− zebrafish larvae from their respective wild type controls: alanine, citrulline, ethanolamine, glutamine, glycine, histidine, isoleucine, leucine, methionine, phenylalanine, putrescine, serine and threonine. Moreover, we also observed that glucose and lipid levels were increased in lepb −/− zebrafish larvae compared to the lepb +/+ group. Deep sequencing showed that many genes involved in proteolysis and arachidonic acid metabolism were dysregulated in ob/ob mice heads and lepb mutant zebrafish larvae compared to their wild type controls, respectively. Conclusions Leptin deficiency leads to highly similar metabolic alterations in metabolites in both mice and zebrafish larvae. These metabolic changes show similar features as observed during progression of tuberculosis in human patients, mice and zebrafish larvae. In addition, by studying the transcriptome, we found similar changes in gene regulation related to proteolysis and arachidonic acid metabolism in these two different in vivo models.

Although all the technical components supporting fully orchestrated Digital Twins (DT) currently exist, what remains missing is a conceptual clarification and analysis of a more generalized concept of a DT that is made FAIR, that is, universally machine actionable. This methodological overview is a first step toward this clarification. We present a review of previously developed semantic artifacts and how they may be used to compose a higher-order data model referred to here as a FAIR Digital Twin (FDT). We propose an architectural design to compose, store and reuse FDTs supporting data intensive research, with emphasis on privacy by design and their use in GDPR compliant open science.

Abstract Background Lysophosphatidic acids (LPAs) are bioactive signaling phospholipids that have been implicated in Alzheimer’s disease (AD). It is largely unknown whether LPAs are associated with AD pathology and progression from mild cognitive impairment (MCI) to AD. Methods The current study was performed on cerebrospinal fluid (CSF) and plasma samples of 182 MCI patients from two independent cohorts. We profiled LPA-derived metabolites using liquid chromatography-mass spectrometry. We evaluated the association of LPAs with CSF biomarkers of AD, Aβ-42, p-tau, and total tau levels overall and stratified by APOE genotype and with MCI to AD progression. Results Five LPAs (C16:0, C16:1, C22:4, C22:6, and isomer-LPA C22:5) showed significant positive association with CSF biomarkers of AD, Aβ-42, p-tau, and total tau, while LPA C14:0 and C20:1 associated only with Aβ-42 and alkyl-LPA C18:1, and LPA C20:1 associated with tau pathology biomarkers. Association of cyclic-LPA C16:0 and two LPAs (C20:4, C22:4) with Aβ-42 levels was found only in APOE ε4 carriers. Furthermore, LPA C16:0 and C16:1 also showed association with MCI to AD dementia progression, but results did not replicate in an independent cohort. Conclusions Our findings provide evidence that LPAs may contribute to early AD pathogenesis. Future studies are needed to determine whether LPAs play a role in upstream of AD pathology or are downstream markers of neurodegeneration.

Multi-omics studies are popular but lack rigorous criteria for experimental design. We define Figures of Merit across omics to comparatively describe their performance, and present new algorithms for sample size calculation in multi-omics experiments aiming either at feature selection or sample classification.

Blood metabolite levels are under the influence of environmental and genetic factors. Here, Hagenbeek et al. perform heritability estimations for metabolite measures and determine the contribution of known metabolite loci to metabolite levels using data from 40 genome-wide association studies.

Immunometabolism, which concerns the interplay between metabolism and the immune system, is increasingly recognized as a potential source of novel drug targets and biomarkers. In this context, the use of metabolomics to identify metabolic characteristics associated with specific functional immune response processes is of value. Currently, there is a lack of tools to determine known associations between metabolites and immune processes. Consequently, interpretation of metabolites in metabolomics studies in terms of their role in the immune system, or selection of the most relevant metabolite classes to include in metabolomics studies, is challenging. Here, we describe the Immunometabolic Atlas (IMA), a public web application and library of R functions to infer immune processes associated with specific metabolites and vice versa. The IMA derives metabolite-immune process associations utilizing a protein-metabolite network analysis algorithm that associates immune system-associated annotated proteins in Gene Ontology to metabolites. We evaluated IMA inferred metabolite-immune system associations using a text mining strategy, identifying substantial overlap, but also demonstrating a significant chemical space of immune system-associated metabolites that should be confirmed experimentally. Overall, the IMA facilitates the interpretation and design of immunometabolomics studies by the association of metabolites to specific immune processes.

Trained sensory panels are regularly used to rate food products but do not allow for data-driven approaches to steer food product development. This study evaluated the potential of a molecular-based strategy by analyzing 27 tomato soups that were enhanced with yeast-derived flavor products using a sensory panel as well as LC-MS and GC-MS profiling. These data sets were used to build prediction models for 26 different sensory attributes using partial least squares analysis. We found driving separation factors between the tomato soups and metabolites predicting different flavors. Many metabolites were putatively identified as dipeptides and sulfur-containing modified amino acids, which are scientifically described as related to umami or having “garlic-like” and “onion-like” attributes. Proposed identities of high-impact sensory markers (methionyl-proline and asparagine-leucine) were verified using MS/MS. The overall results highlighted the strength of combining sensory data and metabolomics platforms to find new information related to flavor perception in a complex food matrix.

Scopeas the leading cause of perinatal mortality and morbidity worldwide, the impact of premature delivery is undisputable. Thus far, non-invasive, cost-efficient and accurate biochemical markers to predict preterm delivery are scarce. The aim of this systematic review is to investigate the potential of non-invasive metabolomic biomarkers for the prediction of preterm delivery.Methods and ResultsDatabases were systematically searched from March 2019 up to May 2020 resulting in 4062 articles, of which 45 were retrieved for full-text assessment. The resulting metabolites used for further analyses, such as ferritin, prostaglandin and different vitamins were obtained from different human anatomical compartments or sources (vaginal fluid, serum, urine and umbilical cord) and compared between groups of women with preterm and term delivery. None of the reported metabolites showed uniform results, however, a combination of metabolomics biomarkers may have potential to predict preterm delivery and need to be evaluated in future studies.

The endothelial cells from the microvasculature are key drivers and targets of inflammatory and thrombotic processes in microvascular diseases. The study of bioactive lipids in inflammatory processes has been largely based on two-dimensional endothelial cell cultures. Three-dimensional microvessels-on-a-chip provides an opportunity to monitor the inflammatory phenotype of human microvessels in a more physiological-relevant environment. This protocol describes the culture of endothelial cells as three-dimensional microvessels in the OrganoPlate. The microvessels are treated with tumor necrosis factor alpha to induce inflammation. The collection of samples from the microvessels is optimized for measuring bioactive lipids with liquid chromatography-mass spectrometry, providing a more informative metabolic readout as compared with functional assays.

Item‐level data from composite scales can be analyzed with pharmacometric item response theory (IRT) models to improve the quantification of disease severity compared with the use of total composite scores. However, regular IRT models assume unidimensionality, which is violated in the scale measuring iatrogenic withdrawal in children because some items are also affected by pain, undersedation, or delirium. Here, we compare regular IRT modelling of pediatric iatrogenic withdrawal symptom data with two new analysis approaches in which the latent variable is guided towards the condition of interest using numerical withdrawal severity scored by nurses as a “supervising variable:” supervised IRT (sIRT) and supervised multi‐dimensional (smIRT) modelling. In this example, in which the items scores are affected by multiple conditions, regular IRT modeling is worse to quantify disease severity than the total composite score, whereas improved performance compared with the composite score is observed for the sIRT and smIRT models.

The prevalence of type 2 diabetes mellitus (T2DM) is increasing rapidly worldwide. Because of the limited success of generic interventions, the focus of the disease study has shifted toward personalized strategies, particularly in the early stages of the disease. Traditional Chinese medicine (TCM) is based on a systems view combined with personalized strategies and has improved our knowledge of personalized diagnostics. From a systems biology perspective, the understanding of personalized diagnostics can be improved to yield a biochemical basis for such strategies; for example, metabolomics can be used in combination with other system-based diagnostic methods such as ultra-weak photon emission (UPE). In this study, we investigated the feasibility of using plasma metabolomics obtained from 44 pre-T2DM subjects to stratify the following TCM-based subtypes: Qi-Yin deficiency, Qi-Yin deficiency with dampness, and Qi-Yin deficiency with stagnation. We studied the relationship between plasma metabolomics and UPE with respect to TCM-based subtyping in order to obtain biochemical information for further interpreting disease subtypes. Principal component analysis of plasma metabolites revealed differences among the TCM-based pre-T2DM subtypes. Relatively high levels of lipids (e.g., cholesterol esters and triglycerides) were important discriminators of two of the three subtypes and may be associated with a higher risk of cardiovascular disease. Plasma metabolomics data indicate that the lipid profile is an essential component captured by UPE with respect to stratifying subtypes of T2DM. The results suggest that metabolic differences exist among different TCM-based subtypes of pre-T2DM, and profiling plasma metabolites can be used to discriminate among these subtypes. Plasma metabolomics thus provides biochemical insights into system-based UPE measurements. Keywords: Type 2 diabetes mellitus, Plasma metabolites, Disease subtypes, Ultra-weak photon emission, Correlation networks

The metabolic profiling of a wide range of chemical classes relevant to understanding sarcopenia under conditions in which sample availability is limited, e.g., from mouse models, small muscles, or muscle biopsies, is desired. Several existing metabolomics platforms that include diverse classes of signaling lipids, energy metabolites, and amino acids and amines would be informative for suspected biochemical pathways involved in sarcopenia. The sample limitation requires an optimized sample preparation method with minimal losses during isolation and handling and maximal accuracy and reproducibility. Here, two developed sample preparation methods, BuOH-MTBE-Water (BMW) and BuOH-MTBE-More-Water (BMMW), were evaluated and compared with previously reported methods, Bligh-Dyer (BD) and BuOH-MTBE-Citrate (BMC), for their suitability for these classes. The most optimal extraction was found to be the BMMW method, with the highest extraction recovery of 63% for the signaling lipids and 81% for polar metabolites, and an acceptable matrix effect (close to 1.0) for all metabolites of interest. The BMMW method was applied on muscle tissues as small as 5 mg (dry weight) from the well-characterized, prematurely aging, DNA repair-deficient Ercc1∆/− mouse mutant exhibiting multiple–morbidities, including sarcopenia. We successfully detected 109 lipids and 62 polar targeted metabolites. We further investigated whether fast muscle tissue isolation is necessary for mouse sarcopenia studies. A muscle isolation procedure involving 15 min at room temperature revealed a subset of metabolites to be unstable; hence, fast sample isolation is critical, especially for more oxidative muscles. Therefore, BMMW and fast muscle tissue isolation are recommended for future sarcopenia studies. This research provides a sensitive sample preparation method for the simultaneous extraction of non-polar and polar metabolites from limited amounts of muscle tissue, supplies a stable mouse muscle tissue collection method, and methodologically supports future metabolomic mechanistic studies of sarcopenia.

COVID-19 is characterised by a dysregulated immune response, that involves signalling lipids acting as mediators of the inflammatory process along the innate and adaptive phases. To promote understanding of the disease biochemistry and provide targets for intervention, we applied a range of LC-MS platforms to analyse over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). The second publication in a series reports the results of quantitative LC-MS/MS profiling of 63 small lipids including oxylipins, free fatty acids, and endocannabinoids. Compared to samples taken from ward patients, intensive care unit (ICU) patients had 2–4-fold lower levels of arachidonic acid (AA) and its cyclooxygenase-derived prostanoids, as well as lipoxygenase derivatives, exhibiting negative correlations with inflammation markers. The same derivatives showed 2–5-fold increases in recovering ward patients, in paired comparison to early hospitalisation. In contrast, ICU patients showed elevated levels of oxylipins derived from poly-unsaturated fatty acids (PUFA) by non-enzymatic peroxidation or activity of soluble epoxide hydrolase (sEH), and these oxylipins positively correlated with markers of macrophage activation. The deficiency in AA enzymatic products and the lack of elevated intermediates of pro-resolving mediating lipids may result from the preference of alternative metabolic conversions rather than diminished stores of PUFA precursors. Supporting this, ICU patients showed 2-to-11-fold higher levels of linoleic acid (LA) and the corresponding fatty acyl glycerols of AA and LA, all strongly correlated with multiple markers of excessive immune response. Our results suggest that the altered oxylipin metabolism disrupts the expected shift from innate immune response to resolution of inflammation.

The COVID-19 pandemic raised a need to characterise the biochemical response to SARS-CoV-2 infection and find biological markers to identify therapeutic targets. In support of these aims, we applied a range of LC-MS platforms to analyse over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). The first publication in a series reports the results of quantitative LC-MS/MS profiling of 56 amino acids and derivatives. A comparison between samples taken from ICU and ward patients revealed a notable increase in ten post-translationally modified amino acids that correlated with markers indicative of an excessive immune response: TNF-alpha, neutrophils, markers for macrophage, and leukocyte activation. Severe patients also had increased kynurenine, positively correlated with CRP and cytokines that induce its production. ICU and ward patients with high IL-6 showed decreased levels of 22 immune-supporting and anti-oxidative amino acids and derivatives (e.g., glutathione, GABA). These negatively correlated with CRP and IL-6 and positively correlated with markers indicative of adaptive immune activation. Including corresponding alterations in convalescing ward patients, the overall metabolic picture of severe COVID-19 reflected enhanced metabolic demands to maintain cell proliferation and redox balance, alongside increased inflammation and oxidative stress.

Diagnosis of microbial disease etiology in community-acquired pneumonia (CAP) remains challenging. We undertook a large-scale metabolomics study of serum samples in hospitalized CAP patients to determine if host-response associated metabolites can enable diagnosis of microbial etiology, with a specific focus on discrimination between the major CAP pathogen groups S. pneumoniae, atypical bacteria, and respiratory viruses. Targeted metabolomic profiling of serum samples was performed for three groups of hospitalized CAP patients with confirmed microbial etiologies: S. pneumoniae (n = 48), atypical bacteria (n = 47), or viral infections (n = 30). A wide range of 347 metabolites was targeted, including amines, acylcarnitines, organic acids, and lipids. Single discriminating metabolites were selected using Student's T-test and their predictive performance was analyzed using logistic regression. Elastic net regression models were employed to discover metabolite signatures with predictive value for discrimination between pathogen groups. Metabolites to discriminate S. pneumoniae or viral pathogens from the other groups showed poor predictive capability, whereas discrimination of atypical pathogens from the other groups was found to be possible. Classification of atypical pathogens using elastic net regression models was associated with a predictive performance of 61% sensitivity, 86% specificity, and an AUC of 0.81. Targeted profiling of the host metabolic response revealed metabolites that can support diagnosis of microbial etiology in CAP patients with atypical bacterial pathogens compared to patients with S. pneumoniae or viral infections.

Variation in metabolite levels reflects individual differences in genetic and environmental factors. Here, we investigated the role of these factors in urinary metabolomics data in children. We examined the effects of sex and age on 86 metabolites, as measured on three metabolomics platforms that target amines, organic acids, and steroid hormones. Next, we estimated their heritability in a twin cohort of 1300 twins (age range: 5.7–12.9 years). We observed associations between age and 50 metabolites and between sex and 21 metabolites. The monozygotic (MZ) and dizygotic (DZ) correlations for the urinary metabolites indicated a role for non-additive genetic factors for 50 amines, 13 organic acids, and 6 steroids. The average broad-sense heritability for these amines, organic acids, and steroids was 0.49 (range: 0.25–0.64), 0.50 (range: 0.33–0.62), and 0.64 (range: 0.43–0.81), respectively. For 6 amines, 7 organic acids, and 4 steroids the twin correlations indicated a role for shared environmental factors and the average narrow-sense heritability was 0.50 (range: 0.37–0.68), 0.50 (range; 0.23–0.61), and 0.47 (range: 0.32–0.70) for these amines, organic acids, and steroids. We conclude that urinary metabolites in children have substantial heritability, with similar estimates for amines and organic acids, and higher estimates for steroid hormones.

TNFα signaling in the vascular endothelium elicits multiple inflammatory responses that drive vascular destabilization and leakage. Bioactive lipids are main drivers of these processes. In vitro mechanistic studies of bioactive lipids have been largely based on two-dimensional endothelial cell cultures that, due to lack of laminar flow and the growth of the cells on non-compliant stiff substrates, often display a pro-inflammatory phenotype. This complicates the assessment of inflammatory processes. Three-dimensional microvessels-on-a-chip models provide a unique opportunity to generate endothelial microvessels in a more physiological environment. Using an optimized targeted liquid chromatography–tandem mass spectrometry measurements of a panel of pro- and anti-inflammatory bioactive lipids, we measure the profile changes upon administration of TNFα. We demonstrate that bioactive lipid profiles can be readily detected from three-dimensional microvessels-on-a-chip and display a more dynamic, less inflammatory response to TNFα, that resembles more the human situation, compared to classical two-dimensional endothelial cell cultures.

Biomarkers are of interest as potential diagnostic and predictive instruments in personalized medicine. We present the first urinary metabolomics biomarker study of childhood aggression. We aim to examine the association of urinary metabolites and neurotransmitter ratios involved in key metabolic and neurotransmitter pathways in a large cohort of twins (N = 1,347) and clinic-referred children (N = 183) with an average age of 9.7 years. This study is part of ACTION (Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies), in which we developed a standardized protocol for large-scale collection of urine samples in children. Our analytical design consisted of three phases: a discovery phase in twins scoring low or high on aggression (N = 783); a replication phase in twin pairs discordant for aggression (N = 378); and a validation phase in clinical cases and matched twin controls (N = 367). In the discovery phase, 6 biomarkers were significantly associated with childhood aggression, of which the association of O-phosphoserine (β = 0.36; SE = 0.09; p = 0.004), and gamma-L-glutamyl-L-alanine (β = 0.32; SE = 0.09; p = 0.01) remained significant after multiple testing. Although non-significant, the directions of effect were congruent between the discovery and replication analyses for six biomarkers and two neurotransmitter ratios and the concentrations of 6 amines differed between low and high aggressive twins. In the validation analyses, the top biomarkers and neurotransmitter ratios, with congruent directions of effect, showed no significant associations with childhood aggression. We find suggestive evidence for associations of childhood aggression with metabolic dysregulation of neurotransmission, oxidative stress, and energy metabolism. Although replication is required, our findings provide starting points to investigate causal and pleiotropic effects of these dysregulations on childhood aggression.

Summary: Ebola virus, for which we lack effective countermeasures, causes hemorrhagic fever in humans, with significant case fatality rates. Lack of experimental human models for Ebola hemorrhagic fever is a major obstacle that hinders the development of treatment strategies. Here, we model the Ebola hemorrhagic syndrome in a microvessel-on-a-chip system and demonstrate its applicability to drug studies. Luminal infusion of Ebola virus-like particles leads to albumin leakage from the engineered vessels. The process is mediated by the Rho/ROCK pathway and is associated with cytoskeleton remodeling. Infusion of Ebola glycoprotein (GP1,2) generates a similar phenotype, indicating the key role of GP1,2 in this process. Finally, we measured the potency of a recently developed experimental drug FX06 and a novel drug candidate, melatonin, in phenotypic rescue. Our study confirms the effects of FX06 and identifies melatonin as an effective, safe, inexpensive therapeutic option that is worth investigating in animal models and human trials. : Virology; Screening in Health Technology; Biological Sciences Research Methodologies Subject Areas: Virology, Screening in Health Technology, Biological Sciences Research Methodologies

Polar hydrophilic metabolites have been identified as important actors in many biochemical pathways. Despite continuous improvement and refinement of hydrophilic interaction liquid chromatography (HILIC) platforms, its application in global polar metabolomics has been underutilized. In this study, we aimed to systematically evaluate polar stationary phases for untargeted metabolomics by using HILIC columns (neutral and zwitterionic) that have been exploited widely in targeted approaches. To do so, high-resolution mass spectrometry was applied to thoroughly investigate selectivity, repeatability and matrix effect at three pH conditions for 9 classes of polar compounds using 54 authentic standards and plasma matrix. The column performance for utilization in untargeted metabolomics was assessed using plasma samples with diverse phenotypes. Our results indicate that the ZIC-c HILIC column operated at neutral pH exhibited several advantages, including superior performance for different classes of compounds, better isomer separation, repeatability and high metabolic coverage. Regardless of the column type, the retention of inorganic ions in plasma leads to extensive adduct formation and co-elution with analytes, which results in ion-suppression as part of the overall plasma matrix effect. In ZIC-c HILIC, the sodium chloride ion effect was particularly observed for amino acids and amine classes. Successful performance of HILIC for separation of plasma samples with different phenotypes highlights this mode of separation as a valuable approach in global profiling of plasma sample and discovering the metabolic changes associated with health and disease.

Abstract Background We previously identified, in newly diagnosed rheumatoid arthritis (RA) patients, networks of co-expressed genes and proteomic biomarkers associated with achieving sustained drug-free remission (sDFR) after treatment with tocilizumab- or methotrexate-based strategies. The aim of this study was to identify, within the same patients, metabolic pathways important for achieving sDFR and to subsequently study the complex interactions between different components of the biological system and how these interactions might affect the therapeutic response in early RA. Methods Serum samples were analyzed of 60 patients who participated in the U-Act-Early trial (ClinicalTrials.gov number NCT01034137) and initiated treatment with methotrexate, tocilizumab, or the combination and who were thereafter able to achieve sDFR (n = 37); as controls, patients were selected who never achieved a drug-free status (n = 23). Metabolomic measurements were performed using mass spectrometry on oxidative stress, amine, and oxylipin platforms covering various compounds. Partial least square discriminant analyses (PLSDA) were performed to identify, per strategy arm, relevant metabolites of which the biological pathways were studied. In addition, integrative analyses were performed correlating the previously identified transcripts and proteins with the relevant metabolites. Results In the tocilizumab plus methotrexate, tocilizumab, and methotrexate strategy, respectively, 19, 13, and 12 relevant metabolites were found, which were subsequently used for pathway analyses. The most significant pathway in the tocilizumab plus methotrexate strategy was “histidine metabolism” (p

Abstract Background Breast cancer is the most common invasive cancer among women. Currently, there are only a few models used for therapy selection, and they are often poor predictors of therapeutic response or take months to set up and assay. In this report, we introduce a microfluidic OrganoPlate® platform for extracellular matrix (ECM) embedded tumor culture under perfusion as an initial study designed to investigate the feasibility of adapting this technology for therapy selection. Methods The triple negative breast cancer cell lines MDA-MB-453, MDA-MB-231 and HCC1937 were selected based on their different BRCA1 and P53 status, and were seeded in the platform. We evaluate seeding densities, ECM composition (Matrigel®, BME2rgf, collagen I) and biomechanical (perfusion vs static) conditions. We then exposed the cells to a series of anti-cancer drugs (paclitaxel, olaparib, cisplatin) and compared their responses to those in 2D cultures. Finally, we generated cisplatin dose responses in 3D cultures of breast cancer cells derived from 2 PDX models. Results The microfluidic platform allows the simultaneous culture of 96 perfused micro tissues, using limited amounts of material, enabling drug screening of patient-derived material. 3D cell culture viability is improved by constant perfusion of the medium. Furthermore, the drug response of these triple negative breast cancer cells was attenuated by culture in 3D and differed from that observed in 2D substrates. Conclusions We have investigated the use of a high-throughput organ-on-a-chip platform to select therapies. Our results have raised the possibility to use this technology in personalized medicine to support selection of appropriate drugs and to predict response to therapy in a real time fashion.

Abstract South Asians have a higher risk to develop obesity and related disorders compared to white Caucasians. This is likely in part due to their lower resting energy expenditure (REE) as related with less energy-combusting brown adipose tissue (BAT). Since overactivation of the endocannabinoid system is associated with obesity and low BAT activity, we hypothesized that South Asians have a higher endocannabinoid tone. Healthy lean white Caucasian (n = 10) and South Asian (n = 10) men were cold-exposed to activate BAT. Before and after cooling, REE was assessed and plasma was collected for analysis of endocannabinoids and lipids. At thermoneutrality, South Asians had higher plasma levels of 2-arachidonoylglycerol (2-AG; 11.36 vs 8.19 pmol/mL, p

Efforts to determine the effects of drugs on epithelial barriers could benefit from better in vitro models. Here the authors develop a microfluidic device supporting the growth and function of extracellular matrix-supported intestinal tubules, and evaluate the effect of staurosporine and acetylsalicylic acid on barrier integrity.

Abstract In recent years, excessive oxidative metabolism has been reported as a critical determinant of pathogenicity in many diseases. The advent of a simple tool that can provide a physiological readout of oxidative stress would be a major step towards monitoring this dynamic process in biological systems, while also improving our understanding of this process. Ultra-weak photon emission (UPE) has been proposed as a potential tool for measuring oxidative processes due to the association between UPE and reactive oxygen species. Here, we used HL-60 cells as an in vitro model to test the potential of using UPE as readout for dynamically monitoring oxidative stress after inducing respiratory burst. In addition, to probe for possible changes in oxidative metabolism, we performed targeted metabolomics on cell extracts and culture medium. Lastly, we tested the effects of treating cells with the NADPH oxidase inhibitor diphenyleneiodonium chloride (DPI). Our results show that UPE can be used as readout for measuring oxidative stress metabolism and related processes.

Endocannabinoids, a class of lipid messengers, have emerged as crucial regulators of synaptic communication in the CNS. Dysregulation of these compounds has been implicated in many brain disorders. Although some studies have identified and quantified a limited number of target compounds, a method that provides comprehensive quantitative information on endocannabinoids and related N-acylethanolamines (NAEs) in cerebrospinal fluid (CSF) is currently lacking, as measurements are challenging due to low concentrations under normal physiological conditions. Here we developed and validated a high-throughput nano LC-ESI-MS/MS platform for the simultaneous quantification of endocannabinoids (anandamide and 2-arachidonoylglycerol), ten related NAEs, and eight additional putatively annotated NAEs in human CSF. Requiring only 200 μl of CSF, our method has limits of detection from 0.28 to 61.2 pM with precisions of relative SD

Abstract Introduction Identification of blood‐based metabolic changes might provide early and easy‐to‐obtain biomarkers. Methods We included 127 Alzheimer's disease (AD) patients and 121 control subjects with cerebrospinal fluid biomarker‐confirmed diagnosis (cutoff tau/amyloid β peptide 42: 0.52). Mass spectrometry platforms determined the concentrations of 53 amine compounds, 22 organic acid compounds, 120 lipid compounds, and 40 oxidative stress compounds. Multiple signatures were assessed: differential expression (nested linear models), classification (logistic regression), and regulatory (network extraction). Results Twenty‐six metabolites were differentially expressed. Metabolites improved the classification performance of clinical variables from 74% to 79%. Network models identified five hubs of metabolic dysregulation: tyrosine, glycylglycine, glutamine, lysophosphatic acid C18:2, and platelet‐activating factor C16:0. The metabolite network for apolipoprotein E (APOE) ε4 negative AD patients was less cohesive compared with the network for APOE ε4 positive AD patients. Discussion Multiple signatures point to various promising peripheral markers for further validation. The network differences in AD patients according to APOE genotype may reflect different pathways to AD.

The endocannabinoid 2-arachidonoylglycerol (2-AG) is involved in neuronal differentiation. This study aimed to identify the biosynthetic enzymes responsible for 2-AG production during retinoic acid (RA)-induced neurite outgrowth of Neuro-2a cells. First, we confirmed that RA stimulation of Neuro-2a cells increases 2-AG production and neurite outgrowth. The diacylglycerol lipase (DAGL) inhibitor DH376 blocked 2-AG production and reduced neuronal differentiation. Surprisingly, CRISPR/Cas9-mediated knockdown of DAGLα and DAGLβ in Neuro-2a cells did not reduce 2-AG levels, suggesting another enzyme capable of producing 2-AG in this cell line. Chemical proteomics revealed DAGLβ and α,β-hydrolase domain containing protein (ABHD6) as the only targets of DH376 in Neuro-2a cells. Biochemical, genetic and lipidomic studies demonstrated that ABHD6 possesses DAGL activity in conjunction with its previously reported monoacylglycerol lipase activity. RA treatment of Neuro-2a cells increased by three-fold the amount of active ABHD6. Our study shows that ABHD6 exhibits significant DAG lipase activity in Neuro-2a cells in addition to its known MAG lipase activity and suggest it is involved in neuronal differentiation.

Summary: Parkinson’s disease (PD) exhibits systemic effects on the human metabolism, with emerging roles for the gut microbiome. Here, we integrate longitudinal metabolome data from 30 drug-naive, de novo PD patients and 30 matched controls with constraint-based modeling of gut microbial communities derived from an independent, drug-naive PD cohort, and prospective data from the general population. Our key results are (1) longitudinal trajectory of metabolites associated with the interconversion of methionine and cysteine via cystathionine differed between PD patients and controls; (2) dopaminergic medication showed strong lipidomic signatures; (3) taurine-conjugated bile acids correlated with the severity of motor symptoms, while low levels of sulfated taurolithocholate were associated with PD incidence in the general population; and (4) computational modeling predicted changes in sulfur metabolism, driven by A. muciniphila and B. wadsworthia, which is consistent with the changed metabolome. The multi-omics integration reveals PD-specific patterns in microbial-host sulfur co-metabolism that may contribute to PD severity. : Hertel et al. demonstrate complex alterations in human and microbial sulfur metabolism in Parkinson’s disease by integrating longitudinal metabolomics and computational modeling of gut microbiomes. Then, potential clinical importance is revealed as secondary taurine-conjugated bile acids are shown to be associated with disease severity and Parkinson’s disease incidence. Keywords: metabolism, Parkinson's disease, neurodegenerative disease, microbiome, transsulfuration pathway, metabolomics, metagenomics, metabolic modeling, taurine metabolism, bile acid metabolism

The endocannabinoid system (ECS) controls energy balance by regulating both energy intake and energy expenditure. Endocannabinoid levels are elevated in obesity suggesting a potential causal relationship. This study aimed to elucidate the rate of dysregulation of the ECS, and the metabolic organs involved, in diet-induced obesity. Eight groups of age-matched male C57Bl/6J mice were randomized to receive a chow diet (control) or receive a high fat diet (HFD, 45% of calories derived from fat) ranging from 1 day up to 18 weeks before euthanasia. Plasma levels of the endocannabinoids 2-arachidonoylglycerol (2-AG) and anandamide (N-arachidonoylethanolamine, AEA), and related N-acylethanolamines, were quantified by UPLC-MS/MS and gene expression of components of the ECS was determined in liver, muscle, white adipose tissue (WAT) and brown adipose tissue (BAT) during the course of diet-induced obesity development. HFD feeding gradually increased 2-AG (+132% within 4 weeks, P < 0.05), accompanied by upregulated expression of its synthesizing enzymes Daglα and β in WAT and BAT. HFD also rapidly increased AEA (+81% within 1 week, P < 0.01), accompanied by increased expression of its synthesizing enzyme Nape-pld, specifically in BAT. Interestingly, Nape-pld expression in BAT correlated with plasma AEA levels (R2 = 0.171, β = 0.276, P < 0.001). We conclude that a HFD rapidly activates adipose tissue depots to increase the synthesis pathways of endocannabinoids that may aggravate the development of HFD-induced obesity.

Gut microbiota and their metabolic products are increasingly being recognized as important modulators of human health. The fecal metabolome provides a functional readout of the interactions between human metabolism and the gut microbiota in health and disease. Due to the high complexity of the fecal matrix, sample preparation often introduces technical variation, which must be minimized to accurately detect and quantify gut bacterial metabolites. Here, we tested six different representative extraction methods (single-phase and liquid–liquid extractions) and compared differences due to fecal amount, extraction solvent type and solvent pH. Our results indicate that a minimum fecal (wet) amount of 0.50 g is needed to accurately represent the complex texture of feces. The MTBE method (MTBE/methanol/water, 3.6/2.8/3.5, v/v/v) outperformed the other extraction methods, reflected by the highest extraction efficiency for 11 different classes of compounds, the highest number of extracted features (97% of the total identified features in different extracts), repeatability (CV < 35%) and extraction recovery (≥70%). Importantly, optimization of the solvent volume of each step to the initial dried fecal material (µL/mg feces) offers a major step towards standardization, which enables confident assessment of the contributions of gut bacterial metabolites to human health.

A popular fragmentation technique for non-targeted analysis is called data-independent acquisition (DIA), because it provides fragmentation data for all analytes in a specific mass range. In this work, we demonstrated the strengths and weaknesses of DIA. Two types of chromatography (fractionation/3 min and hydrophilic interaction liquid chromatography (HILIC)/18 min) and three DIA protocols (variable sequential window acquisition of all theoretical mass spectra (SWATH), fixed SWATH and MSALL) were used to evaluate the performance of DIA. Our results show that fast chromatography and MSALL often results in product ion overlap and complex MS/MS spectra, which reduces the quantitative and qualitative power of these DIA protocols. The combination of SWATH and HILIC allowed for the correct identification of 20 metabolites using the NIST library. After SWATH window customization (i.e., variable SWATH), we were able to quantify ten structural isomers with a mean accuracy of 103% (91–113%). The robustness of the variable SWATH and HILIC method was demonstrated by the accurate quantification of these structural isomers in 10 highly diverse blood samples. Since the combination of variable SWATH and HILIC results in good quantitative and qualitative fragmentation data, it is promising for both targeted and untargeted platforms. This should decrease the number of platforms needed in metabolomics and increase the value of a single analysis.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.