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Diabetic kidney disease (DKD) is the leading cause of end stage kidney failure worldwide, of which cellular insulin resistance is a major driver. Here, we study key human kidney cell types implicated in DKD (podocytes, glomerular endothelial, mesangial and proximal tubular cells) in insulin sensitive and resistant conditions, and perform simultaneous transcriptomics and proteomics for integrated analysis. Our data is further compared with bulk- and single-cell transcriptomic kidney biopsy data from early- and advanced-stage DKD patient cohorts. We identify several consistent changes (individual genes, proteins, and molecular pathways) occurring across all insulin-resistant kidney cell types, together with cell-line-specific changes occurring in response to insulin resistance, which are replicated in DKD biopsies. This study provides a rich data resource to direct future studies in elucidating underlying kidney signalling pathways and potential therapeutic targets in DKD., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

To identify the pathways that are coordinately regulated in pancreatic β cells, muscle, liver, and fat to control fasting glycemia we fed C57Bl/6, DBA/2, and Balb/c mice a regular chow or a high fat diet for 5, 13, and 33 days. Physiological, transcriptomic and lipidomic data were used in a data fusion approach to identify organ-specific pathways linked to fasting glycemia across all conditions investigated. In pancreatic islets, constant insulinemia despite higher glycemic levels was associated with reduced expression of hormone and neurotransmitter receptors, OXPHOS, cadherins, integrins, and gap junction mRNAs. Higher glycemia and insulin resistance were associated, in muscle, with decreased insulin signaling, glycolytic, Krebs' cycle, OXPHOS, and endo/exocytosis mRNAs; in hepatocytes, with reduced insulin signaling, branched chain amino acid catabolism and OXPHOS mRNAs; in adipose tissue, with increased innate immunity and lipid catabolism mRNAs. These data provide a resource for further studies of interorgan communication in glucose homeostasis., Competing Interests: M.G., C.K., and K.S. are employees of Lipotype GmbH., (© 2024 The Author(s).)

Many mechanisms responsible for COVID-19 pathogenesis are well-established, but COVID-19 includes features with unclear pathogenesis, such as autonomic dysregulation, coagulopathies, and high levels of inflammation. The receptor for the SARS-CoV-2 spike protein receptor-binding domain (RBD) is angiotensin-converting enzyme 2 (ACE2). We hypothesized that some COVID-19 patients may develop antibodies that have a negative molecular image of RBD sufficiently similar to ACE2 to yield ACE2-like catalytic activity-ACE2-like abzymes. To explore this hypothesis, we studied patients hospitalized with COVID-19 who had plasma samples available obtained about 7 days after admission. ACE2 is a metalloprotease that requires Zn 2+ for activity. However, we found that the plasma from some patients studied could specifically cleave a synthetic ACE2 peptide substrate, even though the plasma samples were collected using disodium EDTA anticoagulant. When we spiked plasma with synthetic ACE2, no ACE2 substrate cleavage activity was observed unless Zn 2+ was added or the plasma was diluted to decrease EDTA concentration. After processing samples by 100 kDa size exclusion columns and protein A/G adsorption, which depleted immunoglobulin by >99.99%, the plasma samples did not cleave the ACE2 substrate peptide. The data suggest that some patients with COVID-19 develop antibodies with abzyme-like activity capable of cleaving synthetic ACE2 substrate. Since abzymes can exhibit promiscuous substrate specificities compared to the enzyme whose active site image they resemble, and since proteolytic cascades regulate many physiologic processes, anti-RBD abzymes may contribute to some otherwise obscure COVID-19 pathogenesis., Importance: We provide what we believe to be the first description of angiotensin-converting enzyme 2 (ACE2)-like enzymatic activity associated with immunoglobulin in COVID-19 patients. COVID-19 includes many puzzling clinical features that have unclear pathogenesis, including a hyperinflammatory state, abnormalities of the clotting cascade, and blood pressure instability. We hypothesized that some patients with COVID-19 patients may produce antibodies against SARS-CoV-2 with enzymatic activity, or abzymes, that target important proteolytic regulatory cascades. The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein binds ACE2 on the surface of the future host cell. This means that the RBD has a negative molecular image of ACE2. We hypothesized that some antibodies produced against the RBD would have, in turn, a negative molecular image of the RBD sufficiently similar to ACE2 to have ACE2-like catalytic activity. In other words, some anti-RBD antibodies would be ACE2-like abzymes. Abzymes elicited by SARS-CoV-2 infection have the potential to affect host physiology., Competing Interests: The authors declare no conflict of interest.

Introduction: Type 2 diabetes (T2D) onset, progression and outcomes differ substantially between individuals. Multi-omics analyses may allow a deeper understanding of these differences and ultimately facilitate personalised treatments. Here, in an unsupervised "bottom-up" approach, we attempt to group T2D patients based solely on -omics data generated from plasma., Methods: Circulating plasma lipidomic and proteomic data from two independent clinical cohorts, Hoorn Diabetes Care System (DCS) and Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS), were analysed using Similarity Network Fusion. The resulting patient network was analysed with Logistic and Cox regression modelling to explore relationships between plasma -omic profiles and clinical characteristics., Results: From a total of 1,134 subjects in the two cohorts, levels of 180 circulating plasma lipids and 1195 proteins were used to separate patients into two subgroups. These differed in terms of glycaemic deterioration (Hazard Ratio=0.56;0.73), insulin sensitivity and secretion (C-peptide, p =3.7e-11;2.5e-06, DCS and GoDARTS, respectively; Homeostatic model assessment 2 (HOMA2)-B; -IR; -S, p=0.0008;4.2e-11;1.1e-09, only in DCS). The main molecular signatures separating the two groups included triacylglycerols, sphingomyelin, testican-1 and interleukin 18 receptor., Conclusions: Using an unsupervised network-based fusion method on plasma lipidomics and proteomics data from two independent cohorts, we were able to identify two subgroups of T2D patients differing in terms of disease severity. The molecular signatures identified within these subgroups provide insights into disease mechanisms and possibly new prognostic markers for T2D., Competing Interests: GR has received grant funding from, and is a consultant for, Sun Pharmaceuticals Inc. KS is CEO of Lipotype. KS and CK are shareholders of Lipotype. MG is an employee of Lipotype. MH is an employee of Janssen Research & Development. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Li, Dragan, Tran, Fung, Kuznetsov, Hansen, Beulens, Hart, Slieker, Donnelly, Gerl, Klose, Mehl, Simons, Elders, Pearson, Rutter and Ibberson.)

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.

Vaccines are essential tools to prevent infection and control transmission of infectious diseases that threaten public health. Most infectious agents enter their hosts across mucosal surfaces, which make up key first lines of host defense against pathogens. Mucosal immune responses play critical roles in host immune defense to provide durable and better recall responses. Substantial attention has been focused on developing effective mucosal vaccines to elicit robust localized and systemic immune responses by administration via mucosal routes. Mucosal vaccines that elicit effective immune responses yield protection superior to parenterally delivered vaccines. Beyond their valuable immunogenicity, mucosal vaccines can be less expensive and easier to administer without a need for injection materials and more highly trained personnel. However, developing effective mucosal vaccines faces many challenges, and much effort has been directed at their development. In this article, we review the history of mucosal vaccine development and present an overview of mucosal compartment biology and the roles that mucosal immunity plays in defending against infection, knowledge that has helped inform mucosal vaccine development. We explore new progress in mucosal vaccine design and optimization and novel approaches created to improve the efficacy and safety of mucosal vaccines.

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression., (© 2023. The Author(s).)

The aim of our study was to test the hypothesis that administration of Regenerating islet-derived protein 3α (Reg3α), a protein described as having protective effects against oxidative stress and anti-inflammatory activity, could participate in the control of glucose homeostasis and potentially be a new target of interest in the treatment of type 2 diabetes. To that end the recombinant human Reg3α protein was administered for one month in insulin-resistant mice fed high fat diet. We performed glucose and insulin tolerance tests, assayed circulating chemokines in plasma and measured glucose uptake in insulin sensitive tissues. We evidenced an increase in insulin sensitivity during an oral glucose tolerance test in ALF-5755 treated mice vs controls and decreased the pro-inflammatory cytokine C-X-C Motif Chemokine Ligand 5 (CXCL5). We also demonstrated an increase in glucose uptake in skeletal muscle. Finally, correlation studies using human and mouse muscle biopsies showed negative correlation between intramuscular Reg3α mRNA expression (or its murine isoform Reg3γ) and insulin resistance. Thus, we have established the proof of concept that Reg3α could be a novel molecule of interest in the treatment of T2D by increasing insulin sensitivity via a skeletal muscle effect., Competing Interests: The authors declare the following conflict of interests: Lyse Santoro is CEO of The Healthy Aging Company (THAC). Laure Jamot and Fanny Roth are employees of THAC. Gilles Amouyal, Paul Amouyal, Christian Bréchot and Christophe Magnan are co-founders of THAC., (© 2022 Published by Elsevier Ltd.)

Objectives: To find plasma biomarkers prognostic of type 2 diabetes, which could also inform on pancreatic β-cell deregulations or defects in the function of insulin target tissues., Methods: We conducted a systems biology approach to characterize the plasma lipidomes of C57Bl/6J, DBA/2J, and BALB/cJ mice under different nutritional conditions, as well as their pancreatic islet and liver transcriptomes. We searched for correlations between plasma lipids and tissue gene expression modules., Results: We identified strong correlation between plasma triacylglycerols (TAGs) and islet gene modules that comprise key regulators of glucose- and lipid-regulated insulin secretion and of the insulin signaling pathway, the two top hits were Gck and Abhd6 for negative and positive correlations, respectively. Correlations were also found between sphingomyelins and islet gene modules that overlapped in part with the gene modules correlated with TAGs. In the liver, the gene module most strongly correlated with plasma TAGs was enriched in mRNAs encoding fatty acid and carnitine transporters as well as multiple enzymes of the β-oxidation pathway. In humans, plasma TAGs also correlated with the expression of several of the same key regulators of insulin secretion and the insulin signaling pathway identified in mice. This cross-species comparative analysis further led to the identification of PITPNC1 as a candidate regulator of glucose-stimulated insulin secretion., Conclusion: TAGs emerge as biomarkers of a liver-to-β-cell axis that links hepatic β-oxidation to β-cell functional mass and insulin secretion., (Copyright © 2021 The Authors. Published by Elsevier GmbH.. All rights reserved.)

Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic ( N = 12,828), metabolomic ( N = 2,945), lipidomic ( N = 2,593), and proteomic ( N = 1,170) data were obtained in plasma. For each data type, each cluster was compared with the other four clusters as the reference. The insulin-resistant cluster showed the most distinct molecular signature, with higher branched-chain amino acid, diacylglycerol, and triacylglycerol levels and aberrant protein levels in plasma were enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher levels of cytokines. The mild diabetes cluster with high HDL showed the most beneficial molecular profile with effects opposite of those seen in the insulin-resistant cluster. This study shows that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease., (© 2021 by the American Diabetes Association.)

Aims/hypothesis: Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes. In the current study we replicate and cross-validate these type 2 diabetes clusters in three large cohorts using variables readily measured in the clinic., Methods: In three independent cohorts, in total 15,940 individuals were clustered based on age, BMI, HbA 1c , random or fasting C-peptide, and HDL-cholesterol. Clusters were cross-validated against the original clusters based on HOMA measures. In addition, between cohorts, clusters were cross-validated by re-assigning people based on each cohort's cluster centres. Finally, we compared the time to insulin requirement for each cluster., Results: Five distinct type 2 diabetes clusters were identified and mapped back to the original four All New Diabetics in Scania (ANDIS) clusters. Using C-peptide and HDL-cholesterol instead of HOMA2-B and HOMA2-IR, three of the clusters mapped with high sensitivity (80.6-90.7%) to the previously identified severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD) and mild obesity-related diabetes (MOD) clusters. The previously described ANDIS mild age-related diabetes (MARD) cluster could be mapped to the two milder groups in our study: one characterised by high HDL-cholesterol (mild diabetes with high HDL-cholesterol [MDH] cluster), and the other not having any extreme characteristic (mild diabetes [MD]). When these two milder groups were combined, they mapped well to the previously labelled MARD cluster (sensitivity 79.1%). In the cross-validation between cohorts, particularly the SIDD and MDH clusters cross-validated well, with sensitivities ranging from 73.3% to 97.1%. SIRD and MD showed a lower sensitivity, ranging from 36.1% to 92.3%, where individuals shifted from SIRD to MD and vice versa. People belonging to the SIDD cluster showed the fastest progression towards insulin requirement, while the MDH cluster showed the slowest progression., Conclusions/interpretation: Clusters based on C-peptide instead of HOMA2 measures resemble those based on HOMA2 measures, especially for SIDD, SIRD and MOD. By adding HDL-cholesterol, the MARD cluster based upon HOMA2 measures resulted in the current clustering into two clusters, with one cluster having high HDL levels. Cross-validation between cohorts showed generally a good resemblance between cohorts. Together, our results show that the clustering based on clinical variables readily measured in the clinic (age, HbA 1c , HDL-cholesterol, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts. Adding HDL-cholesterol to the clustering resulted in the identification of a cluster with very slow glycaemic deterioration., (© 2021. The Author(s).)

Most research on human pancreatic islets is conducted on samples obtained from normoglycaemic or diseased brain-dead donors and thus cannot accurately describe the molecular changes of pancreatic islet beta cells as they progress towards a state of deficient insulin secretion in type 2 diabetes (T2D). Here, we conduct a comprehensive multi-omics analysis of pancreatic islets obtained from metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum, from normoglycemia to T2D. We find that islet pools isolated from surgical samples by laser-capture microdissection display remarkably more heterogeneous transcriptomic and proteomic profiles in patients with diabetes than in non-diabetic controls. The differential regulation of islet gene expression is already observed in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive, but disharmonic, remodelling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or transdifferentiation stages in T2D. Furthermore, through integration of islet transcriptomics with preoperative blood plasma lipidomics, we define the relative importance of gene coexpression modules and lipids that are positively or negatively associated with HbA1c levels, pointing to potential prognostic markers., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

MetaNetX/MNXref is a reconciliation of metabolites and biochemical reactions providing cross-links between major public biochemistry and Genome-Scale Metabolic Network (GSMN) databases. The new release brings several improvements with respect to the quality of the reconciliation, with particular attention dedicated to preserving the intrinsic properties of GSMN models. The MetaNetX website (https://www.metanetx.org/) provides access to the full database and online services. A major improvement is for mapping of user-provided GSMNs to MXNref, which now provides diagnostic messages about model content. In addition to the website and flat files, the resource can now be accessed through a SPARQL endpoint (https://rdf.metanetx.org)., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The standard treatment for neovascular age-related macular degeneration (nAMD) consists of intravitreal anti-vascular endothelial growth factors (VEGF). However, for some patients, even maximal anti-VEGF treatment does not entirely suppress exudative activity. The goal of this study was to identify molecular biomarkers in nAMD with incomplete response to anti-VEGF treatment. Aqueous humor (AH) samples were collected from three groups of patients: 17 patients with nAMD responding incompletely to anti-VEGF (18 eyes), 17 patients affected by nAMD with normal treatment response (21 eyes), and 16 control patients without any retinopathy (16 eyes). Proteomic and multiplex analyses were performed on these samples. Proteomic analyses showed that nAMD patients with incomplete anti-VEGF response displayed an increased inflammatory response, complement activation, cytolysis, protein-lipid complex, and vasculature development pathways. Multiplex analyses revealed a significant increase of soluble vascular cell adhesion molecule-1 (sVCAM-1) [  p = 0.001], interleukin-6 (IL-6) [  p = 0.009], bioactive interleukin-12 (IL-12p40) [  p = 0.03], plasminogen activator inhibitor type 1 (PAI-1) [  p = 0.004], and hepatocyte growth factor (HGF) [  p = 0.004] levels in incomplete responders in comparison to normal responders. Interestingly, the same biomarkers showed a high intercorrelation with r2 values between 0.58 and 0.94. In addition, we confirmed by AlphaLISA the increase of sVCAM-1 [  p < 0.0001] and IL-6 [  p = 0.043] in the incomplete responder group. Incomplete responders in nAMD are associated with activated angiogenic and inflammatory pathways. The residual exudative activity of nAMD despite maximal anti-VEGF treatment may be related to both angiogenic and inflammatory responses requiring specific adjuvant therapy. Data are available via ProteomeXchange with identifier PXD02247., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Mantel, Borgo, Guidotti, Forestier, Kirsch, Derradji, Waridel, Burdet, Mehl, Schweizer and Roduit.)

Understanding the adaptive responses of individual bacterial strains is crucial for microbiome engineering approaches that introduce new functionalities into complex microbiomes, such as xenobiotic compound metabolism for soil bioremediation. Adaptation requires metabolic reprogramming of the cell, which can be captured by multi-omics, but this data remains formidably challenging to interpret and predict. Here we present a new approach that combines genome-scale metabolic modeling with transcriptomics and exometabolomics, both of which are common tools for studying dynamic population behavior. As a realistic demonstration, we developed a genome-scale model of Pseudomonas veronii 1YdBTEX2, a candidate bioaugmentation agent for accelerated metabolism of mono-aromatic compounds in soil microbiomes, while simultaneously collecting experimental data of P. veronii metabolism during growth phase transitions. Predictions of the P. veronii growth rates and specific metabolic processes from the integrated model closely matched experimental observations. We conclude that integrative and network-based analysis can help build predictive models that accurately capture bacterial adaptation responses. Further development and testing of such models may considerably improve the successful establishment of bacterial inoculants in more complex systems.

Background: Metabolic alterations, related to cerebral glucose metabolism, brain insulin resistance, and age-induced mitochondrial dysfunction, play an important role in Alzheimer's disease (AD) on both the systemic and central nervous system level. To study the extent and significance of these alterations in AD, quantitative metabolomics was applied to plasma and cerebrospinal fluid (CSF) from clinically well-characterized AD patients and cognitively healthy control subjects. The observed metabolic alterations were associated with core pathological processes of AD to investigate their relation with amyloid pathology and tau-related neurodegeneration., Methods: In a case-control study of clinical and biomarker-confirmed AD patients (n = 40) and cognitively healthy controls without cerebral AD pathology (n = 34) with paired plasma and CSF samples, we performed metabolic profiling, i.e., untargeted metabolomics and targeted quantification. Targeted quantification focused on identified deregulated pathways highlighted in the untargeted assay, i.e. the TCA cycle, and its anaplerotic pathways, as well as the neuroactive tryptophan and kynurenine pathway., Results: Concentrations of several TCA cycle and beta-oxidation intermediates were higher in plasma of AD patients, whilst amino acid concentrations were significantly lower. Similar alterations in these energy metabolism intermediates were observed in CSF, together with higher concentrations of creatinine, which were strongly correlated with blood-brain barrier permeability. Alterations of several amino acids were associated with CSF Amyloidβ1-42. The tryptophan catabolites, kynurenic acid and quinolinic acid, showed significantly higher concentrations in CSF of AD patients, which, together with other tryptophan pathway intermediates, were correlated with either CSF Amyloidβ1-42, or tau and phosphorylated Tau-181., Conclusions: This study revealed AD-associated systemic dysregulation of nutrient sensing and oxidation and CNS-specific alterations in the neuroactive tryptophan pathway and (phospho)creatine degradation. The specific association of amino acids and tryptophan catabolites with AD CSF biomarkers suggests a close relationship with core AD pathology. Our findings warrant validation in independent, larger cohort studies as well as further investigation of factors such as gender and APOE genotype, as well as of other groups, such as preclinical AD, to identify metabolic alterations as potential intervention targets.

Acylcarnitines and amino acids are key players in energy metabolism; however, analytical methods for comprehensive and straightforward quantitative profiling of these metabolites, without derivatization or use of ion-pairing agents, are lacking. We therefore developed a hydrophilic interaction chromatography (HILIC)-based high-resolution mass spectrometry (HRMS) method for the simultaneous quantification of acylcarnitines and amino acids in a single run, while taking advantage of HRMS data acquired in full-scan mode to screen for additional derivatives and other polar metabolites. A single-step metabolite extraction with internal standard mixture (in methanol) warranted high-throughput sample preparation whose applicability was demonstrated on a panel of human biofluids (i.e., blood plasma, CSF, and urine) and brain tissue. Method accuracy was within 90-106% of validated NIST reference plasma concentrations for the panel of measured amino acids. Amino acid and acylcarnitine extraction recoveries were 87-100% on average, depending on the concentration range spiked. The coefficient of variation (CV) was 1-10% and 1-25% for intra- and interday measurements, respectively, with the highest CVs for the metabolites at the limit of quantification, depending on the biofluid. Acylcarnitine and amino acid signatures or chemical composition barcodes of the different biofluids and human brain tissue were acquired and biofluid- and tissue-associated differences were discussed in the context of their respective physiological roles. Significant differences were observed in the amino acid profiles, whereas acylcarnitine composition did not show biofluid-characteristic or brain region-specific pattern. The retrospective exploration of full-scan all-ion-fragmentation data allowed us to extract the information on unsaturated and hydroxylated acylcarnitine species, amines, and purine and pyrimidine metabolites. This merged targeted and untargeted approach provides an innovative strategy for simultaneous and comprehensive assessment of acylcarnitine and amino acid metabolism in clinical research studies using relevant biofluids and tissue extracts.

Cerebrospinal fluid (CSF) is a key body fluid that maintains the homeostasis in central nervous system (CNS). As a biofluid whose content reflects the brain metabolic activity, the CSF has been profiled in the context of neurological diseases to provide novel insights into the disease mechanisms. However, a global high-throughput approach to measure a broad diversity of polar metabolites present in CSF is lacking. Although still perceived as challenging and less reproducible, hydrophilic interaction liquid chromatography (HILIC) has recently evolved to offer the unprecedented coverage capacity of water-soluble metabolome. Here, we present a global HILIC high-resolution mass spectrometry-based (HRMS) approach that combines the profiling in acidic pH ESI (+) and basic pH ESI (-) mode to extend the coverage of CSF polar metabolome. This approach allowed us to annotate and measure a broad range of central carbon metabolites (implicated in glycolysis, TCA cycle, nucleotide, amino acid and fatty acid metabolism) in CSF collected from cognitively healthy elderly volunteers (n = 32), using a single extraction method. Metabolite annotation was achieved using the accurate mass, RT and MS/MS criteria, allowing for the characterization of 146 measurable metabolites. Exploration of characterized individual CSF profiles allowed for a discovery of intriguing gender-associated differences, with significantly higher acylcarnitine levels in men and higher taurine levels women. With this case study, we demonstrate the value of combined HILIC ESI ± HRMS profiling to assess CSF metabolome in clinical research studies., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Cerebrospinal fluid (CSF) is a key body fluid that maintains the homeostasis in central nervous system (CNS). As a biofluid whose content reflects the brain metabolic activity, the CSF is analyzed in the context of neurological diseases and is rarely collected from healthy subjects. For this reason, the metabolite variation associated with general phenotypic characteristics such as gender and age have hardly ever been studied. Here we present the hydrophilic interaction liquid chromatography-high resolution mass spectrometry (HILIC-HRMS) data as a result of untargeted metabolomics analysis of a cohort of elderly cognitively healthy volunteers ( n  = 32). 146 unambiguously identified water soluble metabolites (using accurate mass, retention time and MS/MS matching against spectral libraries) were measured and their abundances across all the subjects depending on their gender are provided in this article. Data tables are available at https://data.mendeley.com/datasets/c73xtsd4s5/1. it's published on mendeley, the DOI is DOI:10.17632/c73xtsd4s5.1. The data presented in this article are related to the research article entitled "A global HILIC-MS approach to measure polar human cerebrospinal fluid metabolome: Exploring gender-associated variation in a cohort of elderly cognitively healthy subjects" (Gallart-Ayala et al., 2018, In press).

The detection of testosterone abuse in sports is routinely achieved through the 'steroidal module' of the Athlete Biological Passport by GC-MS(/MS) quantification of selected endogenous anabolic androgenic steroids (EAAS) from athletes' urines. To overcome some limitations of the "urinary steroid profile" such as the presence of confounding factors (ethnicity, enzyme polymorphism, bacterial contamination, and ethanol), ultrahigh performance liquid chromatography (UHPLC) measurements of blood concentrations of testosterone, its major metabolites, and precursors could represent an interesting and complementary strategy. In this work, two UHPLC-MS/MS methods were developed for the quantification of testosterone and related compounds in human serum, including major progestogens, corticoids, and estrogens. The validated methods were then used for the analyses of serum samples collected from 19 healthy male volunteers after oral and transdermal testosterone administration. Results from unsupervised multiway analysis allowed variations of target analytes to be assessed simultaneously over a 96-h time period. Except for alteration of concentration values due to the circadian rhythm, which concerns mainly corticosteroids, DHEA, and progesterone, significant variations linked to the oral and transdermal testosterone administration were observed for testosterone, DHT, and androstenedione. As a second step of analysis, the longitudinal monitoring of these biomarkers using intra-individual thresholds showed, in comparison to urine, significant improvements in the detection of testosterone administration, especially for volunteers with del/del genotype for phase II UGT2B17 enzyme, not sensitive to the main urinary marker, T/E ratio. A substantial extension of the detection window after transdermal testosterone administration was also observed in serum matrix. The longitudinal follow-up proposed in this study represents a first example of 'blood steroid profile' in doping control analysis, which can be proposed in the future as a complement to the 'urinary module' for improving steroid abuse detection capabilities.

The goal of this study was to evaluate the combination of powerful chromatographic methods and compact single quadrupole MS device for simple in vitro cytochrome P450 (CYP) inhibition assay, instead of more expensive triple quadrupole MS/MS detectors. For this purpose, two modern chromatographic approaches (ultra-high pressure liquid chromatography (UHPLC) and ultra-high performance supercritical fluid chromatography (UHPSFC)) were tested in combination with simple MS detector. To show the applicability for an in vitro CYP-mediated metabolism assay using the cocktail approach, a method was first developed in UHPLC-MS to separate a mixture of 8 probe substrates and 8 CYP-specific metabolites. A screening procedure was initially applied to determine the best combination of a column, an organic modifier and a mobile-phase pH, followed by fine tuning of the conditions (i.e., gradient profile, temperature and pH) using HPLC modelling software. A similar sequential method development procedure was also evaluated for UHPSFC-MS. For method development, where peak tracking is necessary, the use of single quadrupole MS was found to be extremely valuable for following the investigated analytes. Ultimately, a baseline separation of the 16 compounds was achieved in both UHPLC-MS and UHPSFC-MS with an analysis time of less than 7 min. In a second series of experiments, sensitivity was evaluated, and LOQ values were between 2 and 100 ng/mL in UHPLC-MS, while they ranged from 2 to 200 ng/mL in UHPSFC-MS. Based on the concentrations employed for the current in vitro phase I metabolism assay, these LOQ values were appropriate for this type of application. Finally, the two analytical methods were applied to in vitro CYP-dependent metabolism testing. Two well-known phytochemical inhibitors, yohimbine and resveratrol, were investigated, and reliable conclusions were drawn from these experiments with both UHPLC-MS and UHPSFC-MS. At the end, the proposed strategy of optimized chromatography combined with simple MS device has been shown to potentially compete with the widely used combination of generic chromatography and highly selective MS/MS device for simple in vitro CYP inhibition assays. In addition, our analytical method may be easier to use in a routine environment; the instrument cost is significantly reduced and the two developed methods fit for purpose., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The detailed characterization of cold-pressed lemon oils (CPLOs) is of great importance for the flavor and fragrance (F&F) industry. Since a control of authenticity by standard analytical techniques can be bypassed using elaborated adulterated oils to pretend a higher quality, a combination of advanced orthogonal methods has been developed. The present study describes a combined metabolomic approach based on UHPLC-TOF-MS profiling and (1)H NMR fingerprinting to highlight metabolite differences on a set of representative samples used in the F&F industry. A new protocol was set up and adapted to the use of CPLO residues. Multivariate analysis based on both fingerprinting methods showed significant chemical variations between Argentinian and Italian samples. Discriminating markers identified in mixtures belong to furocoumarins, flavonoids, terpenoids and fatty acids. Quantitative NMR revealed low citropten and high bergamottin content in Italian samples. The developed metabolomic approach applied to CPLO residues gives some new perspectives for authenticity assessment., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Due to the importance of citrus lemon oil for the industry, fast and reliable analytical methods that allow the authentication and/or classification of such oil, using the origin of production or extraction process, are necessary. To evaluate the potential of volatile and non-volatile fractions for classification purposes, volatile compounds of cold-pressed lemon oils were analyzed, using GC-FID/MS and FT-MIR, while the non-volatile residues were studied, using FT-MIR, (1)H-NMR and UHPLC-TOF-MS. 64 Lemon oil samples from Argentina, Spain and Italy were considered. Unsupervised and supervised multivariate analyses were sequentially performed on various data blocks obtained by the above techniques. Successful data treatments led to statistically significant models that discriminated and classified cold-pressed lemon oils according to their geographic origin, as well as their production processes. Studying the loadings allowed highlighting of important classes of discriminant variables that corresponded to putative or identified chemical functions and compounds., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

A series of twelve analogs carrying fluoro, chloro, bromo and iodo halogens on the ortho, meta and para positions of a benzoyloxytropane skeleton were synthesized by a simple acylation of 8-methyl-8-aza-bicyclo[3.2.1]octan- 3α-ol by halogenobenzoyl chlorides. The compounds were evaluated in vitro against Plasmodium falciparum (P. f.), Trypanosoma brucei brucei (T. b. b.), Trypanosoma cruzi (T. c.) and Leishmania infantum (L. i.). This study shows that the presence of a halogenated atom and its position on the aromatic ring are important for in vitro activity. Compounds 4 (IC50 = 3.6 µM), 8 (IC50 = 6.7 µM), 5 (IC50 = 8.1 µM) and 7 (IC50 = 9.5 µM) were found the most active against P. f., whereas compounds 12 (IC50 = 5.1 µM), 11 (IC50 = 5.6 µM) and 9 (IC50 = 5.8 µM) exhibited the most pronounced activity against T. b. b. This series of compounds can be considered as non-toxic to the human cell line MRC-5.