NMR-based metabolomics in giant cell arteritis and polymyalgia rheumatica sequential sera differentiates active and inactive disease.

OBJECTIVES: Giant Cell Arteritis-(GCA) is an inflammatory disease following a chronic, relapsing course. The metabolic alterations related to the intense inflammatory process during the active phase and to the rapid impact of steroid treatment, remain unknown. The study aims to investigate the serum metabolome in active and inactive disease state. METHODS: 110 serum samples from 50 patients [33-GCA and 17-Polymyalgia rheumatica-(PMR)] at 3 time points, 0-(V1: active disease), 1 and 6 months-(V2 and V3: remission) of treatment with glucocorticosteroids (GCs), were subjected to Nuclear Magnetic Resonance (NMR)-based metabolomic analysis. Multi- and univariate statistical analyses were utilized to unveil metabolome alterations following treatment. RESULTS: Distinct metabolic profiles were identified between activity and remission, independently to disease type. N-acetylglycoproteins and cholines of bound phospholipids, emerged as predictive markers of disease activity. Altered levels of 4 out of the 21 small molecules were also observed, including increased levels of phenylalanine, and decreased of glutamine, alanine, and creatinine in active disease. Metabolic fingerprinting discriminated GCA from PMR in remission. GCA and PMR patients exhibited characteristic lipid alterations as a response and/or adverse effect of GCs treatment. Correlation analysis showed that several identified biomarkers were further associated with acute phase reactants, C-Reactive Protein and Erythrocyte Sedimentation Rate. CONCLUSION: The NMR profile of serum metabolome could identify and propose sensitive biomarkers of inflammation. Metabolome alterations, following GCs treatment, could provide predictors for future steroid-induced side effects.

Cardioprotection by selective SGLT-2 inhibitors in a non-diabetic mouse model of myocardial ischemia/reperfusion injury: a class or a drug effect?

Major clinical trials with sodium glucose co-transporter-2 inhibitors (SGLT-2i) exhibit protective effects against heart failure events, whereas inconsistencies regarding the cardiovascular death outcomes are observed. Therefore, we aimed to compare the selective SGLT-2i empagliflozin (EMPA), dapagliflozin (DAPA) and ertugliflozin (ERTU) in terms of infarct size (IS) reduction and to reveal the cardioprotective mechanism in healthy non-diabetic mice. C57BL/6 mice randomly received vehicle, EMPA (10 mg/kg/day) and DAPA or ERTU orally at the stoichiometrically equivalent dose (SED) for 7 days. 24 h-glucose urinary excretion was determined to verify SGLT-2 inhibition. IS of the region at risk was measured after 30 min ischemia (I), and 120 min reperfusion (R). In a second series, the ischemic myocardium was collected (10th min of R) for shotgun proteomics and evaluation of the cardioprotective signaling. In a third series, we evaluated the oxidative phosphorylation capacity (OXPHOS) and the mitochondrial fatty acid oxidation capacity by measuring the respiratory rates. Finally, Stattic, the STAT-3 inhibitor and wortmannin were administered in both EMPA and DAPA groups to establish causal relationships in the mechanism of protection. EMPA, DAPA and ERTU at the SED led to similar SGLT-2 inhibition as inferred by the significant increase in glucose excretion. EMPA and DAPA but not ERTU reduced IS. EMPA preserved mitochondrial functionality in complex I&II linked oxidative phosphorylation. EMPA and DAPA treatment led to NF-kB, RISK, STAT-3 activation and the downstream apoptosis reduction coinciding with IS reduction. Stattic and wortmannin attenuated the cardioprotection afforded by EMPA and DAPA. Among several upstream mediators, fibroblast growth factor-2 (FGF-2) and caveolin-3 were increased by EMPA and DAPA treatment. ERTU reduced IS only when given at the double dose of the SED (20 mg/kg/day). Short-term EMPA and DAPA, but not ERTU administration at the SED reduce IS in healthy non-diabetic mice. Cardioprotection is not correlated to SGLT-2 inhibition, is STAT-3 and PI3K dependent and associated with increased FGF-2 and Cav-3 expression.

Plasma Metabolomic Alterations Induced by COVID-19 Vaccination Reveal Putative Biomarkers Reflecting the Immune Response.

Vaccination is currently the most effective strategy for the mitigation of the COVID-19 pandemic. mRNA vaccines trigger the immune system to produce neutralizing antibodies (NAbs) against SARS-CoV-2 spike proteins. However, the underlying molecular processes affecting immune response after vaccination remain poorly understood, while there is significant heterogeneity in the immune response among individuals. Metabolomics have often been used to provide a deeper understanding of immune cell responses, but in the context of COVID-19 vaccination such data are scarce. Mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR)-based metabolomics were used to provide insights based on the baseline metabolic profile and metabolic alterations induced after mRNA vaccination in paired blood plasma samples collected and analysed before the first and second vaccination and at 3 months post first dose. Based on the level of NAbs just before the second dose, two groups, "low" and "high" responders, were defined. Distinct plasma metabolic profiles were observed in relation to the level of immune response, highlighting the role of amino acid metabolism and the lipid profile as predictive markers of response to vaccination. Furthermore, levels of plasma ceramides along with certain amino acids could emerge as predictive biomarkers of response and severity of inflammation.

Chemometrically Assisted Optimization of Pregabalin Fluorescent Derivatization Reaction with a Novel Xanthone Analogue and Validation of the Method for the Determination of Pregabalin in Bulk via a Plate Reader.

Quantitation of chromophore-free analytes is always a challenge. To this purpose, derivatization of the analyte constitutes a common strategy, leading to a product with a strong signal. In the current study, a novel xanthone analogue was utilized for the first time for the derivatization of pregabalin, a model analyte with a primary amine moiety that lacks a chromophore. The fact that only the xanthene-based derivative, formed after the derivatization reaction fluoresces, enables avoiding its chromatographic separation from the reagent and thus reducing the analysis time of a series of samples in 1-2 min via a plate reader. The reaction conditions were optimized via a central composite design (CCD), with fluorescence signal as the measure of the yield. The following factors that affect the derivatization reaction were chosen: (a) temperature, (b) reaction time, and (c) triethylamine solution volume used to drive the reaction to completion. After the identification of the optimal conditions, the method was validated according to ICH guidelines, using a fluorescence plate reader for signal measurement (λex = 540, λem = 615 nm). Finally, the newly developed high-throughput method was applied to the determination of drug content in pregabalin bulk.

Exploring the metabolomic profile of cerebellum after exposure to acute stress.

Psychological stress and stress-related disorders constitute a major health problem in modern societies. Although the brain circuits involved in emotional processing are intensively studied, little is known about the implication of cerebellum in stress responses whereas the molecular changes induced by stress exposure in cerebellum remain largely unexplored. Here, we investigated the effects of acute stress exposure on mouse cerebellum. We used a forced swim test (FST) paradigm as an acute stressor. We then analyzed the cerebellar metabolomic profiles of stressed (n = 11) versus control (n = 11) male CD1 mice by a Nuclear Magnetic Resonance (NMR)-based, untargeted metabolomics approach. Our results showed altered levels of 19 out of the 47 annotated metabolites, which are implicated in neurotransmission and N-acetylaspartic acid (NAA) turnover, as well as in energy and purine/pyrimidine metabolism. We also correlated individual metabolite levels with FST behavioral parameters, and reported associations between FST readouts and levels of 4 metabolites. This work indicates an altered metabolomic signature after acute stress in the cerebellum and highlights a previously unexplored involvement of cerebellum in stress responses.

Metabolic phenotyping and cardiovascular disease: an overview of evidence from epidemiological settings.

Metabolomics, the comprehensive measurement of low-molecular-weight molecules in biological fluids used for metabolic phenotyping, has emerged as a promising tool to better understand pathways underlying cardiovascular disease (CVD) and to improve cardiovascular risk stratification. Here, we present the main methodologies for metabolic phenotyping, the methodological steps to analyse these data in epidemiological settings and the associated challenges. We discuss evidence from epidemiological studies linking metabolites to coronary heart disease and stroke. These studies indicate the systemic nature of CVD and identify associated metabolic pathways such as gut microbial cometabolism, branched-chain amino acids, glycerophospholipid and cholesterol metabolism, as well as activation of inflammatory processes. Integration of metabolomic with genomic data can provide new evidence for involved biochemical pathways and potential for causality using Mendelian randomisation. The clinical utility of metabolic biomarkers for cardiovascular risk stratification in healthy individuals has not yet been established. As sample sizes with high-dimensional molecular data increase in epidemiological settings, integration of metabolomic data across studies and platforms with other molecular data will lead to new understanding of the metabolic processes underlying CVD and contribute to identification of potentially novel preventive and pharmacological targets. Metabolic phenotyping offers a powerful tool in the characterisation of the molecular signatures of CVD, paving the way to new mechanistic understanding and therapies, as well as improving risk prediction of CVD patients. However, there are still challenges to face in order to contribute to clinically important improvements in CVD.

Human Melanoma-Cell Metabolic Profiling: Identification of Novel Biomarkers Indicating Metastasis.

Melanoma is the most aggressive type of skin cancer, leading to metabolic rewiring and enhancement of metastatic transformation. Efforts to improve its early and accurate diagnosis are largely based on preclinical models and especially cell lines. Hence, we herein present a combinational Nuclear Magnetic Resonance (NMR)- and Ultra High Performance Liquid Chromatography-High-Resolution Tandem Mass Spectrometry (UHPLC-HRMS/MS)-mediated untargeted metabolomic profiling of melanoma cells, to landscape metabolic alterations likely controlling metastasis. The cell lines WM115 and WM2664, which belong to the same patient, were examined, with WM115 being derived from a primary, pre-metastatic, tumor and WM2664 clonally expanded from lymph-node metastases. Metabolite samples were analyzed using NMR and UHPLC-HRMS. Multivariate statistical analysis of high resolution NMR and MS (positive and negative ionization) results was performed by Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA) and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA), while metastasis-related biomarkers were determined on the basis of VIP lists, S-plots and Student's t-tests. Receiver Operating Characteristic (ROC) curves of NMR and MS data revealed significantly differentiated metabolite profiles for each cell line, with WM115 being mainly characterized by upregulated levels of phosphocholine, choline, guanosine and inosine. Interestingly, WM2664 showed notably increased contents of hypoxanthine, myo-inositol, glutamic acid, organic acids, purines, pyrimidines, AMP, ADP, ATP and UDP(s), thus indicating the critical roles of purine, pyrimidine and amino acid metabolism during human melanoma metastasis.

Malignancy Grade-Dependent Mapping of Metabolic Landscapes in Human Urothelial Bladder Cancer: Identification of Novel, Diagnostic, and Druggable Biomarkers.

BACKGROUND: Urothelial bladder cancer (UBC) is one of the cancers with the highest mortality rate and prevalence worldwide; however, the clinical management of the disease remains challenging. Metabolomics has emerged as a powerful tool with beneficial applications in cancer biology and thus can provide new insights on the underlying mechanisms of UBC progression and/or reveal novel diagnostic and therapeutic schemes. METHODS: A collection of four human UBC cell lines that critically reflect the different malignancy grades of UBC was employed; RT4 (grade I), RT112 (grade II), T24 (grade III), and TCCSUP (grade IV). They were examined using Nuclear Magnetic Resonance, Mass Spectrometry, and advanced statistical approaches, with the goal of creating new metabolic profiles that are mechanistically associated with UBC progression toward metastasis. RESULTS: Distinct metabolic profiles were observed for each cell line group, with T24 (grade III) cells exhibiting the most abundant metabolite contents. AMP and creatine phosphate were highly increased in the T24 cell line compared to the RT4 (grade I) cell line, indicating the major energetic transformation to which UBC cells are being subjected during metastasis. Thymosin ß4 and ß10 were also profiled with grade-specific patterns of expression, strongly suggesting the importance of actin-cytoskeleton dynamics for UBC advancement to metastatic and drug-tolerant forms. CONCLUSIONS: The present study unveils a novel and putatively druggable metabolic signature that holds strong promise for early diagnosis and the successful chemotherapy of UBC disease.

An Overview of Metabolic Phenotyping in Blood Pressure Research.

PURPOSE OF THE REVIEW: This review presents the analytical techniques, processing and analytical steps used in metabolomics phenotyping studies, as well as the main results from epidemiological studies on the associations between metabolites and high blood pressure. RECENT FINDINGS: A variety of metabolomic approaches have been applied to a range of epidemiological studies to uncover the pathophysiology of high blood pressure. Several pathways have been suggested in relation to blood pressure including the possible role of the gut microflora, inflammatory, oxidative stress, and lipid pathways. Metabolic changes have also been identified associated with blood pressure lowering effects of diets high in fruits and vegetables and low in meat intake. However, the current body of literature on metabolic profiling and blood pressure is still in its infancy, not fully consistent and requires careful interpretation. Metabolic phenotyping is a promising approach to uncover metabolic pathways associated with high blood pressure and throw light into the complex pathophysiology of hypertension.