Distinct Metabolic Signatures Research Articles

Role of major cardiovascular surgery-induced metabolic reprogramming in acute kidney injury in critical care.

Major cardiovascular surgery imposes high physiologic stress, often causing severe organ dysfunction and poor outcomes. The underlying mechanisms remain unclear. This study investigated metabolic changes induced by major cardiovascular surgery and the potential role of identified metabolic signatures in postoperative acute kidney injury (AKI). A prospective observational study included 53 patients undergoing major cardiovascular surgery in 3 groups: cardiac surgery with cardiopulmonary bypass (CPB n = 33), without CPB (n = 10), and major vascular surgery (n = 10). For each patient, peripheral blood samples were collected pre-surgery, and at 6h and 24h post-surgery. Untargeted metabolomics using mass spectrometry quantified 8668 metabolic features in serum samples. Linear mixed-effect models (adjusted for age, sex, and body mass index) and pathway analyses were performed. In the cardiac surgery with CPB group, 772 features were significantly altered (P < 2.8E - 05) across the 3 time points. These features were enriched in five classes, all related to protein metabolism, with glycine and serine metabolism being the most represented. Cardiac surgery with CPB showed a distinct metabolic signature compared to other groups. Patients who developed postoperative AKI exhibited increased protein catabolism (including valine, leucine, and isoleucine degradation), disruptions in the citric acid cycle, and plasmatic accumulation of acylcarnitines. Major cardiovascular surgery, particularly with CPB, induces significant changes in protein metabolism. Patients developing postoperative AKI exhibited specific metabolic signatures. These findings may be critical for designing interventions to minimize organ dysfunction, including AKI, and improve outcomes in major cardiovascular surgery.

A multidimensional fecal microbial and inflammatory biomarker profiling in preterm and full-term neonates.

Preterm birth affects approximately one in every ten neonates. The clinical outcomes depend on care and management factors, including the birth delivery method and the use of antibiotics. This observational cohort study determined antimicrobial peptides, proteases, metabolomic, and microbiome profiles in fecal samples collected from 20 preterm and nine full-term neonates 48 h after birth. The results show that preterm neonates have increased levels of α-defensins, serine proteases, and matrix metalloproteinases. They also have distinct metabolic signatures characterized by decreased kynurenic acid and increased mevalonate levels. These neonates also exhibit reduced microbial diversity. This study highlights that heightened immune response and proteolytic activity, marked dysbiosis, and reduced short-chain fatty acids within the preterm gastrointestinal tract immediately after birth might predispose neonates to exacerbated gut inflammation. Some of the findings, including the elevated fecal mevalonate levels, are potential biomarkers in neonatology for early identification of metabolic disturbances linked to gut inflammation, emphasizing further studies to explore its association with inflammatory conditions in preterm infants. Inflammatory markers that can predict intestinal disorders are insufficiently characterized in preterm neonates. This study identified antimicrobial peptide responses, proteolytic activity, marked dysbiosis, and reduced short-chain fatty acid production in feces from preterm neonates. These critical differences in inflammatory, metabolomic, and microbial signatures may predispose to exacerbated gut inflammation in preterm neonates. Some inflammatory effectors in feces are potential biomarkers for the early detection of intestinal inflammatory conditions in preterm neonates. This study contributes to understanding the inflammatory conditions in the guts of preterm babies and identifies novel targets for timely diagnosis, interventions, and management practices in neonatal care.

Immunometabolic landscaping in Crohn’s disease creeping fat – Does fat matter?

Abstract Background and aims The study proposed herein aims to explore the complex immunometabolic landscape of Creeping Fat (CF) in Crohn's disease (CD) ileitis, an area that remains largely unexplored. Our hypothesis posits the existence of distinct sub-entities within mesenteric adipose tissue, characterized by unique metabolic states in immune cells, non-immune cells, and adipocytes. The primary objective is to elucidate the immunometabolic environment within ileal CF, leveraging an advanced Imaging Mass Cytometry (IMC)-based methodology. Methods Employing a 37-marker IMC panel, we will conduct comprehensive spatial and metabolic profiling of adipose and intestinal tissues from a cohort of 50 patients, including those with CD and ulcerative colitis (UC), and compare these profiles with samples from bariatric surgery patients. This approach enables single-cell level analysis with spatial resolution, uncovering the metabolic states and signatures of various cell types. Previous work in our group has already demonstrated the utility of this technique in revealing significant variations in cell metabolism across different inflammatory states and cell types in CD. Our methodology integrates the study of immune cell clusters, metabolic states, and subtypes with distinct metabolic signatures. By comparing metabolic signatures in adipose tissues with those in inflamed ileal mucosal tissue, we aim to establish an understanding of metabolic processes within CF. Anticipated impact Anticipated impact includes the identification of unique immunometabolic signatures in CF, providing new insights into the pathomechanisms of CD. This could lead to novel therapeutic targets focusing on the metabolism of specific cell types within CF. The study holds the potential to reshape our understanding of CD, paving the way for more targeted and effective treatments for this debilitating disease. Given our established expertise, robust methodology, and comprehensive cohort, this research is poised to offer significant contributions to the field of immunometabolism in IBD, enhancing our understanding of CF and its role in CD.

Lipidomic Signature of Pregnant and Postpartum Females by Longitudinal and Transversal Evaluation: Putative Biomarkers Determined by UHPLC-QTOF-ESI+-MS.

Pregnancy induces significant physiological and metabolic changes in the mother to support fetal growth and prepare for childbirth. These adaptations impact various systems, including immune tolerance, metabolism, and endocrine function. While metabolomics has been utilized to study pregnancy-related metabolic changes, comprehensive comparisons between pregnant and non-pregnant states, particularly using ultra-high-performance liquid chromatography coupled with mass spectrometry (UHPLC-MS), remain limited. This study aimed to explore the dynamic, longitudinal metabolic shifts during pregnancy by profiling plasma samples from 65 pregnant women across three time points (6-14 weeks, 14-22 weeks, and >24 weeks) and 42 postpartum women. Lipidomics was prioritized, and a solvent mixture was employed to enhance lipid extraction, using UHPLC-QTOF-ESI+-MS. A total of 290 metabolites were identified and analyzed. Our results revealed significant metabolic differences between pregnant and postpartum women, with lipid molecules such as estrogen derivatives, fatty acids, and ceramides showing strong potential as biomarkers. Further biomarker analysis highlighted distinct metabolic signatures between early and late pregnancy stages, particularly in lipid metabolism (with AUC values > 0.8). These findings contribute to a deeper understanding of pregnancy-related metabolic changes and may offer insights into maternal and neonatal health outcomes.

Altered purine and pentose phosphate pathway metabolism in uteroplacental insufficiency-induced intrauterine growth restriction offspring rats impairs intestinal function

BackgroundThis study aimed to identify metabolic alterations in the small intestine of newborn rats with intrauterine growth restriction (IUGR), a condition linked to intestinal dysfunction. MethodsPregnant Sprague Dawley rats underwent bilateral uterine artery ligation on gestational day 17 to induce intrauterine growth restriction or sham surgery. Rat pups were delivered spontaneously on gestational day 22. Small intestine tissues were collected on postnatal days 0 and 7 from offspring. Liquid chromatography-mass spectrometry analysis was performed to investigate untargeted metabolomic profiles. Western blot analysis assessed protein expression of key regulators. ResultsNewborn rats with intrauterine growth restriction exhibited distinct small intestine metabolic profiles compared to controls on postnatal day 0. Notably, significant alterations were observed in purine metabolism, the pentose phosphate pathway, and related pathways. Western blot analysis revealed a decrease expression in transketolase, a key enzyme of the pentose phosphate pathway, suggesting impaired activity of the pentose phosphate pathway. Additionally, decreased expression of tight junction proteins ZO-1 and occludin indicated compromised intestinal barrier function in rats with intrauterine growth restriction. Similar metabolic disruptions persisted on postnatal day 7, with further reductions in tricarboxylic acid cycle intermediates and folate biosynthesis precursors. Interestingly, lysyl-glycine, a protein synthesis marker, was elevated in rats with intrauterine growth restriction. ConclusionsOur findings reveal a distinct metabolic signature in the small intestine of neonatal rats with intrauterine growth restriction, characterized by disruptions in the pentose phosphate pathway, purine metabolism, and energy production pathways. These novel insights suggest potential mechanisms underlying IUGR-associated intestinal dysfunction and impaired growth.

Targeting Metabolomics in Primary Hypertrophic Osteoarthropathy: Uncovering Novel Insights into Disease Pathogenesis.

Primary hypertrophic osteoarthropathy (PHO) is a rare genetic disorder characterized by skeletal and skin abnormalities. Genetic defects in prostaglandin E2 (PGE2) metabolism are known to cause PHO. However, the global impact and clinical significance of eicosanoids and oxylipins beyond PGE2 remain to be elucidated. This study aimed to investigate oxylipin networks in PHO, including the 2 subtypes, PHOAR1 and PHOAR2, and examine their associations with clinical characteristics. We conducted a targeted metabolomic study involving 16 patients with PHO and 16 age- and sex-matched healthy controls. Serum samples were collected at the time of diagnosis. Metabolites were quantified using ultra-high-performance liquid chromatography-tandem mass spectrometry. Laboratory analyses confirmed elevated levels of PGE2 in patients with PHO, consistent with the established pathogenesis. About 60 oxidized lipid metabolites were identified, with 19 differentially expressed in PHO. Besides the COX/PGE2 pathway, the lipoxygenase-mediated pathway was also involved in PHO. The metabolites 5-OxoETE, 15-OxoETE, 8S,15S-DiHETE, PGE2, 11β-PGE2, PGB2, LTB4, and LTE4 were significantly altered. Correlation analyses revealed associations between oxylipin metabolites and clinical features, including bone microarchitecture. Notably, the study highlighted differences in the oxylipin metabolite profiles between patients with PHOAR1 and patients with PHOAR2, suggesting distinct metabolic signatures for each subtype. Our study indicated a significant perturbation in oxylipin metabolism among patients with PHO, with distinct metabolic signatures observed between PHOAR1 and PHOAR2. The disruption extended beyond the metabolism of PGE2. It encompassed a broader alteration across the polyunsaturated fatty acid metabolism spectrum, including various eicosanoids and oxylipins. Our work provided a comprehensive understanding of the pathogenesis of PHO, and underscored the potential for subtype-specific therapeutic interventions.

Recent advances in applying metabolomics to uncover dietary impact on cardiometabolic health.

Cardiometabolic diseases are a major global health concern, with diet playing a crucial role in their prevention and management. Recent advancements in the identification of metabolic signatures related to dietary patterns offer a more objective assessment of individualized dietary exposure and provide deeper insights into diet-disease associations. Recent studies have shown that distinct metabolic signatures are associated with the adherence to various dietary patterns. These signatures show even stronger associations with cardiometabolic disease incidence, independent of traditional risk factors and self-reported adherence to such dietary patterns. Emerging dietary approaches, such as sustainable diets, health outcome-focused diets, and population data-driven dietary patterns, also hold promise for improving cardiometabolic health. Additionally, metabolic signatures could offer insights into diet-disease associations in underrepresented populations, addressing genetic and lifestyle differences. Application of metabolomics provides a more precise understanding of how dietary patterns influence cardiometabolic health. Although the number of studies remains limited, and current evidence is inconsistent, the approach has significant potential for improving clinical and public health strategies. Future research should prioritize prospective studies and address population- and outcome-specific dietary needs to enable targeted interventions that optimize cardiometabolic health.

Muscle Proteome Analysis of Facioscapulohumeral Dystrophy Patients Reveals a Metabolic Rewiring Promoting Oxidative/Reductive Stress Contributing to the Loss of Muscle Function.

Facioscapulohumeral muscular dystrophy (FSHD) is caused by the epigenetic de-repression of the double homeobox 4 (DUX4) gene, leading to asymmetric muscle weakness and atrophy that begins in the facial and scapular muscles and progresses to the lower limbs. This incurable condition can severely impair muscle function, ultimately resulting in a loss of ambulation. A thorough analysis of molecular factors associated with the varying degrees of muscle impairment in FSHD is still lacking. This study investigates the molecular mechanisms and biomarkers in the biceps brachii of FSHD patients, classified according to the FSHD clinical score, the A-B-C-D classification scheme, and global proteomic variation. Our findings reveal distinct metabolic signatures and compensatory responses in patients. In severe cases, we observe pronounced metabolic dysfunction, marked by dysregulated glycolysis, activation of the reductive pentose phosphate pathway (PPP), a shift toward a reductive TCA cycle, suppression of oxidative phosphorylation, and an overproduction of antioxidants that is not matched by an increase in the redox cofactors needed for their function. This imbalance culminates in reductive stress, exacerbating muscle wasting and inflammation. In contrast, mild cases show metabolic adaptations that mitigate stress by activating polyols and the oxidative PPP, preserving partial energy flow through the oxidative TCA cycle, which supports mitochondrial function and energy balance. Furthermore, activation of the hexosamine biosynthetic pathway promotes autophagy, protecting muscle cells from apoptosis. In conclusion, our proteomic data indicate that specific metabolic alterations characterize both mild and severe FSHD patients. Molecules identified in mild cases may represent potential diagnostic and therapeutic targets for FSHD.

EXTH-64. MECHANISMS OF MITOCHONDRIAL COMPLEX-I SENSITIVITY IN GBM

Abstract The biguanide metformin that is widely used for the management of Type 2 diabetes is being evaluated as an anti-neoplastic agent in cancer trials including GBM (NCT02780024, NCT03243851). The mechanisms of action of metformin as an anti-neoplastic agent is still being investigated, but recent studies have unequivocally demonstrated that its therapeutic effects in tumor cell growth and signaling are dependent on inhibition of mitochondrial complex I. Based on the success of metformin in combination therapy in some cancers, new generation of mitochondrial complex I inhibitors (MCI-i) such as IM156, IACS-010759, are currently under investigation. Diffusion of metformin across the plasma membrane occurs slowly. Its entry is facilitated by two transporters OCT1 and OCT2 that are not well expressed outside the liver and kidney. This presents a problem due to its lack of accumulation in other tissues at therapeutic concentrations. Therefore, identification of tumor subtypes that respond better to lower concentrations of metformin may be leveraged for targeted metformin therapy. Metformin GBM trials may be unsatisfactory since there are no molecular markers to distinguish metformin responders from non-responders. Identification of molecular markers may greatly improve metformin and other MCI-i-based therapy in GBM. By examining TCGA data and experimental analysis, we have identified that PDHA, that catalyzes pyruvate to acetyl Co-A, is a predictive molecular marker for MCI-i sensitivity in GBM and potentially beyond GBM. PDHA expression varies widely in patient tumors, potentially due to differential methylation. We are performing joint pathway analysis by examining differentially expressed genes and stable isotope tracing studies to determine distinct metabolic signatures in the two subsets of GBM. We are also performing Classification And Regression Tree (CART) analysis on a cohort of sixty primary GBM lines and tissues to predict if PDHA expression provides a binary outcome for MCI-i sensitivity.

Integrated omics profiling reveals systemic dysregulation and potential biomarkers in the blood of patients with neuromyelitis optica spectrum disorders

BackgroundNeuromyelitis optica spectrum disorders (NMOSD) are autoimmune conditions that affect the central nervous system. The contribution of peripheral abnormalities to the disease's pathogenesis is not well understood.MethodsTo investigate this, we employed a multi-omics approach analyzing blood samples from 52 NMOSD patients and 46 healthy controls (HC). This included mass cytometry, cytokine arrays, and targeted metabolomics. We then analyzed the peripheral changes of NMOSD, and features related to NMOSD's disease severity. Furthermore, an integrative analysis was conducted to identify the distinguishing characteristics of NMOSD from HC. Additionally, we unveiled the variations in peripheral features among different clinical subgroups within NMOSD. An independent cohort of 40 individuals with NMOSD was utilized to assess the serum levels of fibroblast activation protein alpha (FAP).ResultsOur analysis revealed a distinct peripheral immune and metabolic signature in NMOSD patients. This signature is characterized by an increase in monocytes and a decrease in regulatory T cells, dendritic cells, natural killer cells, and various T cell subsets. Additionally, we found elevated levels of inflammatory cytokines and reduced levels of tissue-repair cytokines. Metabolic changes were also evident, with higher levels of bile acids, lactates, triglycerides, and lower levels of dehydroepiandrosterone sulfate, homoarginine, octadecadienoic acid (FA[18:2]), and sphingolipids. We identified distinctive biomarkers differentiating NMOSD from HC and found blood factors correlating with disease severity. Among these, fibroblast activation protein alpha (FAP) was a notable marker of disease progression.ConclusionsOur comprehensive blood profile analysis offers new insights into NMOSD pathophysiology, revealing significant peripheral immune and metabolic alterations. This work lays the groundwork for future biomarker identification and mechanistic studies in NMOSD, highlighting the potential of FAP as a marker of disease progression.

Lipidomic profiling of triple-negative breast cancer cells reveals distinct metabolic signatures associated with EpCAM expression

Lipid metabolism is essential at all stages of cancer progression, particularly for triple-negative breast cancer (TNBC) the deadliest cancer subtype for women patients. TNBC cells exhibit significant metabolic heterogeneity, which contributes to their aggressive behavior. Epithelial-to-mesenchymal transition (EMT), a key step in metastasis, is associated with distinct lipid profiles, where the epithelial cell adhesion molecule (EpCAM) was found to be decreased along the transition. To understand this link, we employed lipidomic profiling of the TNBC cell line SUM149PT, which exhibits high variability in EpCAM, an epithelial marker. Using EpCAM levels to categorize cells with high and low EpCAM expression using fluorescence-activated cell sorter, we performed targeted mass spectrometry analysis of various lipid classes (glycerophospholipids, glycerolipids, lysophospholipids, and sphingolipids) by a hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS)-based screening method. After correcting for cell size, we identified a unique lipid profile associated with each EpCAM expression level. Notably, cells with higher EpCAM expression displayed lower levels of lysophosphatidylethanolamine (LPE). This finding suggests a potential role for LPE in the regulation of EMT in TNBC.

Simultaneous metabolomics and lipidomics analysis based on 4in1 online analysis system reveal metabolic signatures in atherosclerotic mice

Developing efficient and comprehensive analysis methods for metabolomics and lipidomics in the biological tissues and body fluids is essential for understanding the disease mechanisms. Although various two-dimensional liquid chromatography-mass spectrometry (2D-LC-MS) methods have been proposed to expand metabolite coverage, achieving higher efficiency in integrated metabolomics and lipidomics studies remains a technical challenge. In this work, a novel 4in1 online analysis system with excellent reproducibility and mass accuracy was constructed for metabolomics and lipidomics study in various biological samples from atherosclerotic mice. This system enabled the simultaneous detection in both positive and negative ion modes with extensive polarity separation in a single analytical run. Using the 4in1 online analysis system, we identified distinct but complementary metabolic signatures associated with atherosclerosis in different biological samples. Specifically, a total of 230 and 170 differential metabolites or lipids were detected in mice plasma samples and aortic tissue samples, respectively, including glycerophospholipids, sphingolipids, fatty acyls, glycerolipids, carboxylic acids, and pyrimidine nucleosides. Additionally, atherosclerosis-related metabolic pathways involved in biosynthesis of unsaturated fatty acids, sphingolipid metabolism, cholesterol metabolism, glycerophospholipid metabolism, and choline metabolism further revealed. These findings demonstrate that the novel 4in1 online analysis system is a faithful, stable and powerful tool for comprehensive metabolomics and lipidomics studies in complex biological matrices.

Metabolic Effects of the SGLT2 Inhibitor Dapagliflozin in Heart Failure Across the Spectrum of Ejection Fraction.

Mechanisms of benefit with SGLT2is (sodium-glucose cotransporter-2 inhibitors) in heart failure (HF) remain incompletely characterized. Dapagliflozin alters ketone and fatty acid metabolism in HF with reduced ejection fraction though similar effects have not been observed in HF with preserved ejection fraction. We explore whether metabolic effects of SGLT2is vary across the left ventricular ejection fraction spectrum and their relationship with cardiometabolic end points in 2 randomized trials of dapagliflozin in HF. Metabolomic profiling of 61 metabolites was performed in 527 participants from DEFINE-HF (Dapagliflozin Effects on Biomarkers, Symptoms and Functional Status in Patients With HF With Reduced Ejection Fraction) and PRESERVED-HF (Dapagliflozin in PRESERVED Ejection Fraction HF; 12-week, placebo-controlled trials of dapagliflozin in HF with reduced ejection fraction and HF with preserved ejection fraction, respectively). Linear regression was used to assess changes in principal components analysis-defined metabolite factors with treatment from baseline to 12 weeks, as well as the relationship between changes in metabolite clusters and HF-related end points. The mean age was 66±11 years, 43% were female, and 33% were self-identified as Black. Two principal components analysis-derived metabolite factors (which were comprised of ketone and short-/medium-chain acylcarnitines) increased with dapagliflozin compared with placebo. Ketosis (defined as 3-hydroxybutyrate >500 μM) was achieved in 4.5% with dapagliflozin versus 1.2% with placebo (P=0.03). There were no appreciable treatment effects on amino acids, including branched-chain amino acids. Increases in several acylcarnitines were consistent across LVEF (Pinteraction>0.10), whereas the ketogenic effect diminished at higher LVEF (Pinteraction=0.01 for 3-hydroxybutyrate). Increases in metabolites reflecting mitochondrial dysfunction (particularly long-chain acylcarnitines) and aromatic amino acids and decreases in branched-chain amino acids were associated with worse HF-related outcomes in the overall cohort, with consistency across treatment and LVEF. SGLT2is demonstrate common (fatty acid) and distinct (ketogenic) metabolic signatures across the LVEF spectrum. Changes in key pathways related to fatty acid and amino acid metabolism are associated with HF-related end points and may serve as therapeutic targets across HF subtypes. URL: https://www.clinicaltrials.gov; Unique Identifiers: NCT03030235 and NCT02653482.

LC-HRMS-based global metabolomics profiling unravels the distinct metabolic signature of lapatinib-resistant and trastuzumab-resistant HER2+ breast cancer cells

The effectiveness of lapatinib (LAP) and trastuzumab (TRZ), the first-line therapies for HER2+ breast cancer, has been limited owing to the development of acquired resistance in patients with HER2+. This study aimed to investigate the alterations in metabolic signatures in LAP-resistant HCC1954 and TRZ-resistant HCC1954 and pathways in human HER2+ breast cancer cells using liquid chromatography–high-resolution mass spectrometry (LC-HRMS) and enrichment analysis. The HCC1954 parental cells were sequentially treated 13 rounds with LAP or TRZ to develop resistant cells and then tested for their cytotoxicity using the MTT assay. Metabolites were prepared from HCC1954 parental (MBXWT), HCC1954-LAP (MBXLAP), and HCC1954-TRZ (MBXTRZ) cells prior to LC-HRMS, chemometric, enrichment, and joint pathway analyses. LAP- and TRZ-resistant cells were successfully developed from HCC1954, and 29 and 17 differentially expressed metabolites (DEMs) were identified between MBXWT-MBXLAP and MBXWT-MBXTRZ, respectively. The analysis of DEMs between MBXWT and MBXLAP revealed significant enrichment in D-amino acid metabolism, while MBXWT and MBXTRZ identified valine, leucine, isoleucine biosynthesis, ascorbate, and aldarate metabolism. Joint pathway enrichment analysis of LAP-resistant DEMs and differentially expressed genes (DEGs) showed enrichment in glutathione metabolism, while that of TRZ-resistance and DEGs showed enrichment in carbohydrate metabolism, namely pentose and glucuronate interconversions, starch and sucrose metabolism, and galactose metabolism. The findings from this study indicate considerable metabolic changes in LAP- and TRZ-resistant HCC1954 cells, which are crucial for understanding the resistance mechanisms and developing strategies to overcome these problems.

CHARACTERISATION OF THE RESPONSE OF PRE-CLINICAL MODELS OF GLIOMA TO METABOLIC THERAPIES USING IN VIVO MAGNETIC RESONANCE SPECTROSCOPY

Abstract AIMS Magnetic resonance imaging (MRI) is routinely used to diagnose and monitor brain tumours. Magnetic resonance spectroscopy (MRS) allows us to record the metabolic profile of tumours in situ. This provides a non-invasive method to monitor the response of tumours to metabolic therapies. We aimed to characterise the response of pre-clinical models of glioma to metabolic therapies such as arginine deprivation and the ketogenic diet (KD) by MRS, to better understand what metabolic changes are occurring in the tumour. METHOD We performed orthotopic injection of three different cell lines, including the syngeneic models GL261 and CT2A, as well as a primary GBM cell line, into the striatum of C57BL/6 and athymic nude mice respectively. Mice were randomised to either arginine deprivation treatment using pegylated arginine deiminase (ADI), or KD, plus controls. In each animal, we collected single voxel MRS data using STEAM on both the tumour itself, and healthy brain. MRS data was exported in jMRUI format and analysed in R using the spant package, followed by PCA and OPLS-DA. RESULTS PCA showed that there is clear distinction between healthy and tumour spectra across all models. OPLS-DA indicated that the lipid and choline spectral regions were significantly associated with tumour, whereas the NAA and glutamine/glutamate regions were significantly associated with healthy brain. Integration of specific peaks associated with these metabolites confirmed these results. Subset analysis indicated distinct metabolic signatures between the syngeneic models and the primary GBM model. Furthermore, there is evidence to suggest that tumours in animals treated with arginine deprivation have a unique metabolic signature. CONCLUSION This data indicates that the tumour specific response to metabolic therapies can be measured by routine MRS screening. This would allow a non-invasive method by which clinicians could monitor the effectiveness of metabolic therapies in patients with gliomas.

308 Isoenergetic reduction of dietary macronutrients reveals distinct fecal metabolomic signatures in lean and obese cats fed at maintenance

Abstract Obesity has become a concerning problem in cats. Increasing evidence demonstrates the utility of metabolomics in identifying disease biomarkers and assessing the effects of nutritional interventions, although limited information exists regarding alterations in fecal metabolites in lean and obese domestic cats in response to different macronutrient content. In the current study, three extruded diets were formulated based on adult maintenance using an isoenergentic approach. These diets were created by adjusting the levels of identical ingredients to achieve a low-protein [LP; protein 28% metabolizable energy (ME), fat 40%ME, NFE 32% ME), a low-fat (LF; protein 42% ME, fat 30% ME, NFE 30% ME), and a low-carbohydrate (LC; protein 36% ME, fat 41% ME, NFE 23% ME] diet. Healthy neutered male adult cats [n = 18; body condition scores (BCS) 4 or 5 (lean, n = 9) and 8 or 9 (obese, n = 9)] were fed each diet for a period of 4 wk in a 3 x 3 Latin square design. Fecal samples from each cat were collected between d 22 and 28 of each treatment period. A total of 67 fecal metabolites in six groups (35 amino acids, 11 fatty acids, 10 sugars and sugar metabolites, 5 alcohols, 3 nitrogenous bases, and 3 others) were analyzed using 1H NMR spectroscopy. To evaluate the impact of body condition, diet and their interaction on each metabolite, proc GLIMMIX covariance structure was selected by the smallest Akaike information criterion value in SAS. The Shapiro-Wilk test was used to check normality and lognormal or beta distribution were applied when appropriate. Bonferroni correction post-hoc test was followed to correct Type I error. Statistical significance was considered at P &amp;lt; 0.05. In lean cats, significantly greater concentrations of fecal proteinogenic and branched-chain amino acids, such as methionine, valine, and L-lysine, as well as pyruvic acid and sugars (P &amp;lt; 0.05) were observed. This suggests that these metabolites may either be more actively fermented by bacteria or not utilized as extensively as in obese cats, potentially contributing to a reduction in obesity status. Regardless of body condition, there is a possibility of an enhanced activity in the tryptophan degradation pathway, leading to the greatest concentrations of fecal tryptophan (P = 0.04) in the LF diet, while the greatest fecal D-galactose (P = 0.04) in the LP diet was likely due to the greater dietary carbohydrate content. These observed results suggested that fecal metabolites were influenced by both body condition and diet; however, body condition had a more substantial impact on metabolite changes in cats, whereas no body condition and diet interaction were noted. Overall, the study indicated distinct fecal metabolic signatures in lean and obese cats subjected to different macronutrient diets and further research is warranted to validate the observed findings. Funding was provided by Champion Petfoods, Natural Sciences and Engineering Council of Canada and Mitacs Accelerate.

Metabolomic profiles differentiate between porto-sinusoidal vascular disorder, cirrhosis, and healthy individuals

Background & AimsPorto-sinusoidal vascular disorder (PSVD) is a rare and diagnostically challenging vascular liver disease. This study aimed to identify distinct metabolomic signatures in patients with PSVD, cirrhosis, and healthy volunteers (HV) to facilitate non-invasive diagnosis and elucidate perturbed metabolic pathways. MethodsSerum samples from 20 HV and patients with histologically confirmed PSVD or cirrhosis were analyzed. Metabolites were measured using liquid chromatography-mass spectrometry (LC-MS). Differential abundance was evaluated with Limma’s moderated t-statistics. Artificial neural network (ANN) and support vector machine (SVM) models were developed to classify PSVD against cirrhosis or HV metabolomic profiles. An independent cohort was used for validation. ResultsA total of 283 metabolites were included for downstream analysis. Clustering effectively separated PSVD metabolomes from HV, although a subset of PSVD patients (n=5, 25%) overlapped with cirrhosis. Differential testing revealed significant PSVD-linked metabolic perturbations, including taurocholic and adipic acids, distinguishing PSVD from both HV and cirrhosis. Alterations in pyrimidine, glycine, serine, and threonine pathways were exclusively associated with PSVD. Machine learning models utilizing selected metabolic signatures reliably differentiated PSVD from HV or cirrhosis using only 4 to 6 metabolites. Validation in an independent cohort demonstrated the high discriminative ability of taurocholic acid (AUROC 0.899) for PSVD vs HV and the taurocholic acid/aspartic acid ratio (AUROC 0.720) for PSVD vs cirrhosis. ConclusionsHigh-throughput metabolomics enabled the identification of distinct metabolic profiles for differentiating PSVD, cirrhosis, and healthy individuals. Unique alterations in the glycine, serine, and threonine pathways suggest their potential involvement in PSVD pathogenesis. Impact And ImplicationsPorto-sinusoidal vascular disorder (PSVD) is a vascular liver disease that can lead to pre-sinusoidal portal hypertension in the absence of cirrhosis, with poorly understood pathophysiology and no established treatment. Our study demonstrates that analyzing the serum metabolome could reveal distinct metabolic signatures in PSVD patients, including alterations in the pyrimidine, glycine, serine and threonine pathways and potentially shedding light on the disease's underlying pathways. These findings hold potential for earlier and non-invasive diagnosis of PSVD, potentially reducing reliance on invasive procedures like liver biopsy and guiding diagnostic pathways.

Metabotropic Glutamate Receptors Type 3 and 5 Feature the "NeuroTransmitter-type" of Glioblastoma: A Bioinformatic Approach.

Glioblastoma (GBM) represents an aggressive and common tumor of the central nervous system. The prognosis of GBM is poor, and despite a refined genetic and molecular characterization, pharmacological treatment is largely suboptimal. Contribute to defining a therapeutic line in GBM targeting the mGlu3 receptor in line with the principles of precision medicine. Here, we performed a computational analysis focused on the expression of type 3 and 5 metabotropic glutamate receptor subtypes (mGlu3 and mGlu5, respectively) in high- and low-grade gliomas. The analysis allowed the identification of a particular high-grade glioma type, characterized by a high expression level of both receptor subtypes and by other markers of excitatory and inhibitory neurotransmission. This so-called neurotransmitter-GBM (NT-GBM) also shows a distinct immunological, metabolic, and vascularization gene signature. Our findings might lay the groundwork for a targeted therapy to be specifically applied to this putative novel type of GBM.

Endometriotic lesions exhibit distinct metabolic signature compared to paired eutopic endometrium at the single-cell level

Current therapeutics of endometriosis focus on hormonal disruption of endometriotic lesions (ectopic endometrium, EcE). Recent findings show higher glycolysis utilization in EcE, suggesting non-hormonal strategy for disease treatment that addresses cellular metabolism. Identifying metabolically altered cell types in EcE is important for targeted metabolic drug therapy without affecting eutopic endometrium (EuE). Here, using single-cell RNA-sequencing, we examine twelve metabolic pathways in paired samples of EuE and EcE from women with confirmed endometriosis. We detect nine major cell types in both EuE and EcE. Metabolic pathways are most differentially regulated in perivascular, stromal, and endothelial cells, with the highest changes in AMPK signaling, HIF-1 signaling, glutathione metabolism, oxidative phosphorylation, and glycolysis. We identify transcriptomic co-activation of glycolytic and oxidative metabolism in perivascular and stromal cells of EcE, indicating a critical role of metabolic reprogramming in maintaining endometriotic lesion growth. Perivascular cells, involved in endometrial stroma repair and angiogenesis, may be potential targets for non-hormonal treatment of endometriosis.

Alterations in Choline Metabolism in Non-Obese Individuals with Insulin Resistance and Type 2 Diabetes Mellitus.

The prevalence of non-obese individuals with insulin resistance (IR) and type 2 diabetes (T2D) is increasing worldwide. This study investigates the metabolic signature of phospholipid-associated metabolites in non-obese individuals with IR and T2D, aiming to identify potential biomarkers for these metabolic disorders. The study cohort included non-obese individuals from the Qatar Biobank categorized into three groups: insulin sensitive, insulin resistant, and patients with T2D. Each group comprised 236 participants, totaling 708 individuals. Metabolomic profiling was conducted using high-resolution mass spectrometry, and statistical analyses were performed to identify metabolites associated with the progression from IS to IR and T2D. The study observed significant alterations in specific phospholipid metabolites across the IS, IR, and T2D groups. Choline phosphate, glycerophosphoethanolamine, choline, glycerophosphorylcholine (GPC), and trimethylamine N-oxide showed significant changes correlated with disease progression. A distinct metabolic signature in non-obese individuals with IR and T2D was characterized by shifts in choline metabolism, including decreased levels of choline and trimethylamine N-oxide and increased levels of phosphatidylcholines, phosphatidylethanolamines, and their degradation products. These findings suggest that alterations in choline metabolism may play a critical role in the development of glucose intolerance and insulin resistance. Targeting choline metabolism could offer potential therapeutic strategies for treating T2D. Further research is needed to validate these biomarkers and understand their functional significance in the pathogenesis of IR and T2D in non-obese populations.