Nuclear Magnetic Resonance Metabolomics Research Articles

Metabolic Changes Induced by Cerebral Ischemia, the Effect of Ischemic Preconditioning, and Hyperhomocysteinemia.

1H Nuclear Magnetic Resonance (NMR) metabolomics is one of the fundamental tools in the fast-developing metabolomics field. It identifies and quantifies the most abundant metabolites, alterations of which can describe energy metabolism, activated immune response, protein synthesis and catabolism, neurotransmission, and many other factors. This paper summarizes our results of the 1H NMR metabolomics approach to characterize the distribution of relevant metabolites and their alterations induced by cerebral ischemic injury or its combination with hyperhomocysteinemia in the affected tissue and blood plasma in rodents. A decrease in the neurotransmitter pool in the brain tissue likely follows the disordered feasibility of post-ischemic neurotransmission. This decline is balanced by the increased tissue glutamine level with the detected impact on neuronal health. The ischemic injury was also manifested in the metabolomic alterations in blood plasma with the decreased levels of glycolytic intermediates, as well as a post-ischemically induced ketosis-like state with increased plasma ketone bodies. As the 3-hydroxybutyrate can act as a likely neuroprotectant, its post-ischemic increase can suggest its supporting role in balancing ischemic metabolic dysregulation. Furthermore, the 1H NMR approach revealed post-ischemically increased 3-hydroxybutyrate in the remote organs, such as the liver and heart, as well as decreased myocardial glutamate. Ischemic preconditioning, as a proposed protective strategy, was manifested in a lower extent of metabolomic changes and/or their faster recovery in a longitudinal study. The paper also summarizes the pre- and post-ischemic metabolomic changes in the rat hyperhomocysteinemic models. Animals are challenged with hyperglycemia and ketosis-like state. A decrease in several amino acids in plasma follows the onset and progression of hippocampal neuropathology when combined with ischemic injury. The 1H NMR metabolomics approach also offers a high potential for metabolites in discriminatory analysis in the search for potential biomarkers of ischemic injury. Based on our results and the literature data, this paper presents valuable findings applicable in clinical studies and suggests the precaution of a high protein diet, especially foods which are high in Met content and low in B vitamins, in the possible risk of human cerebrovascular neuropathology.

NMR-based metabonomics reveals the dynamic effect of electro-acupuncture on central nervous system in gastric mucosal lesions (GML) rats

BackgroundGastric mucosal lesions (GML) are common in gastric diseases and seriously affect the quality of life. There are inevitable side effects in drug therapy. Acupuncture is an important part of traditional Chinese medicine. Electro-acupuncture (EA) has unique curative effect in treatment of GML. However, there are still few reports on the central mechanism of electro-acupuncture in treatment of GML. In this study, NMR metabonomics was used to explore the central metabolic change mechanism of electro-acupuncture in treatment of GML.MethodsSD rats were randomly divided into Control, GML and EA groups. According to different intervention time, each group was further divided into 3 subgroups. This study mainly established GML model rats by 75% ethanol. Dynamic expressions of metabolites in cerebral cortex and medulla were observed by 1D 1H Nuclear Magnetic Resonance (NMR) metabolomics, combined with gastric mucosal histopathological examination to evaluate the time-effect relationship of electro-acupuncture at Zusanli (ST36) and Liangmen (ST21) points for 1 day, 4 days and 7 days treatment of GML.ResultsThe results showed that the repair effect of electro-acupuncture on gastric mucosal injury was the most obvious in 4 days and stable in 7 days, and 4 days electro-acupuncture can effectively inhibit GML gastric mucosal inflammation and the expression of inflammatory cells. Meanwhile, the NMR spectrum results of medulla and cerebral cortex showed that, 21 potential metabolites were identified to participate in the mechanism of pathogenesis of GML and the regulation of electro-acupuncture, including 15 in medulla and 10 in cerebral cortex. Metabolic pathway analysis showed that the differential metabolites involved 19 metabolic pathways, which could be divided into energy, neurotransmitters, cells and cell membrane and antioxidation according to their functions. The correlation analysis of stomach, medulla and cerebral cortex shows that the stimulation signal of GML may reach the cerebral cortex from the stomach through medulla, and electro-acupuncture can treat GML by regulating the central nervous system (CNS).Conclusions4 days electro-acupuncture treatment can significantly improve gastric mucosal injury, and the curative effect tends to be stable in 7 days treatment. Meanwhile, the pathogenesis of GML and the efficacy of electro-acupuncture involve metabolic pathways such as energy, neurotransmitters, cells and antioxidation, and electro-acupuncture can treat GML by regulating CNS.

Hyperbaric Exposure of Scuba Divers Affects the Urinary Excretion of Nucleic Acid Oxidation Products and Hypoxanthine.

In recent studies, oxidative stress after scuba diving has been explored by measuring urinary biomarkers in volunteers under controlled conditions. Dive depth and duration, water temperature, and workload are all variables that can elicit metabolic responses. A controlled diving experiment was performed in an indoor pool at 20, 30, and 40 m depths at a water temperature of 32 °C, on three different days. Samples of urine from five male scuba divers were taken before diving and at four time points after diving, and then tested for their concentration of five different oxidative stress biomarkers by means of liquid chromatography tandem mass spectrometry and by 1H nuclear magnetic resonance metabolomics analysis. The results showed no variation in the five biomarkers after diving, but a decreasing trend was observed over the three days, with no differences among the three depths. The lack of effect on oxidative stress biomarkers has been attributed to the comfortable water temperature and to the absence of exercise in the divers during the experiment. Instead, an increase in hypoxanthine excretion, which can be considered a biomarker sensitive to hyperbaric exposure, was found after diving. Finally, the results suggest a physiological mechanism of metabolic adaptation to a new condition.

A Real-Life Reproducibility Assessment for NMR Metabolomics.

Nuclear magnetic resonance (NMR) metabolomics is currently popular enough to attract both specialized and non-specialized NMR groups involving both analytical trained personnel and newcomers, including undergraduate students. Recent interlaboratory studies performed by established NMR metabolomics groups demonstrated high reproducibility of the state-of-the-art NMR equipment and SOPs. There is, however, no assessment of NMR reproducibility when mixing both analytical experts and newcomers. An interlaboratory assessment of NMR quantitation reproducibility was performed using two NMR instruments belonging to different laboratories and involving several operators with different backgrounds and metabolomics expertise for the purpose of assessing the limiting factors for data reproducibility in a multipurpose NMR environment. The variability induced by the operator, automatic pipettes, NMR tubes and NMR instruments was evaluated in order to assess the limiting factors for quantitation reproducibility. The results estimated the expected reproducibility data in a real-life multipurpose NMR laboratory to a maximum 4% variability, demonstrating that the current NMR equipment and SOPs may compensate some of the operator-induced variability.

Towards a semi-automated analysis of fish plasma by 1H NMR metabolomics - applications to aquaculture

Aquafeed is one of the main costs in aquaculture and major efforts are being made to find sustainable ingredients that could improve production sustainability and efficiency. Our research focused on the inclusion of glycerol in the feed of European seabass (Dicentrarchus labrax), as it is a cheap carbon substrate expected to enter metabolism through the glycolytic pathway. The Nuclear Magnetic Resonance (NMR) spectroscopy provides accurate and high-throughput metabolic profiles, allowing quantification and evaluation of the effects of experimental diets in the context of fish nutrition. The aim of the present study was to assess the applicability of the automated online profiling routine Bayesil to fish blood plasma and compare with the manual targeted metabolite profiling approach.After a 60-day feeding trial (0%, 2.5%, 5.0% glycerol supplemented diets), fish were sacrificed at 6 h and 24 h after last meal and blood was sampled. Filtered plasma samples were analysed by NMR, followed by two metabolite-profiling approaches: i) an automated spectral profiling provided by the Bayesil platform, and ii) a manual metabolite profiling.Spectra were analysed with the automated Bayesil routine, identifying and quantifying 51 metabolites, in a reproducible, fast and user-independent method. On the other hand, the manual approach only managed to quantify 20 metabolites. However, under supraphysiological concentrations of glycerol, namely in the 5.0% diet, the Bayesil algorithm was not able to properly integrate the glycerol and glycine signals. The Bland-Altman and PLS-DA analysis revealed differences; nonetheless, with the exception of acetic acid, creatinine, formate, glutamine and threonine, all other metabolites presented a low bias and/or a strong correlation coefficient. Overall, it is expected a reasonable tradeoff between the accuracy in metabolite quantification and the increase of variables.The automated Bayesil database may be applied as a useful tool for systematic monitoring of fish plasma profile in aquaculture research and industrial quality control analysis, to generate robust variance-based multivariate statistical models. To our knowledge, this is the first time a NMR-based high-throughput automated routine is evaluated for aquaculture research.

Effects of acylated and nonacylated anthocyanins extracts on gut metabolites and microbiota in diabetic Zucker rats: A metabolomic and metagenomic study

Anthocyanins have been shown to have prebiotic properties. This study investigated the impact of nonacylated anthocyanins and acylated anthocyanins on fecal and cecal metabolites and colonic gut microbiota in diabetic state using 1H nuclear magnetic resonance (NMR) metabolomics and metagenomic sequencing. Zucker diabetic fatty rats fed with high-fat diet were gavaged with nonacylated anthocyanins extracted from bilberries (NAAB) or acylated anthocyanins extracted from purple potatoes (AAPP) at daily doses of 25 and 50 mg/kg body weight for 8 weeks. Lean Zucker rats fed with normal diet (ND) and high-fat diet (Con) were used as healthy controls groups. Binned NMR spectra and sequenced gene abundance were used for data analysis. Dysbiosis of colonic microbiota and gut metabolites in the diabetic rats were observed compared to the lean Zucker rats. Both anthocyanin extracts increased cecal sugar levels and the abundance of Peptostreptococcaceae sp. and decreased the abundance of Parabacteroides spp. in colon. In addition to the increased fecal short-chain fatty acids, AAPP decreased colonic Ruminococcus torques and Lachnospiraceae bacterium 4_1_37FAA abundances and increased oxidative phosphorylation. The anthocyanin extracts modulated the gut metabolism and microbiota in diabetes, with AAPP showing more regulatory and beneficial effects on diabetes.

Metabolic Impact of Anticancer Drugs Pd2Spermine and Cisplatin on the Brain of Healthy Mice.

The new palladium agent Pd2Spermine (Spm) has been reported to exhibit promising cytotoxic properties, while potentially circumventing the known disadvantages associated to cisplatin therapeutics, namely acquired resistance and high toxicity. This work presents a nuclear magnetic resonance (NMR) metabolomics study of brain extracts obtained from healthy mice, to assess the metabolic impacts of the new Pd2Spm complex in comparison to that of cisplatin. The proton NMR spectra of both polar and nonpolar brain extracts were analyzed by multivariate and univariate statistics, unveiling several metabolite variations during the time course of exposition to each drug (1–48 h). The distinct time-course dependence of such changes revealed useful information on the drug-induced dynamics of metabolic disturbances and recovery periods, namely regarding amino acids, nucleotides, fatty acids, and membrane precursors and phospholipids. Putative biochemical explanations were proposed, based on existing pharmacokinetics data and previously reported metabolic responses elicited by the same metal complexes in the liver of the same animals. Generally, results suggest a more effective response of brain metabolism towards the possible detrimental effects of Pd2Spm, with more rapid recovery back to metabolites’ control levels and, thus, indicating that the palladium drug may exert a more beneficial role than cDDP in relation to brain toxicity.

NMR Metabolomics Assessment of Osteogenic Differentiation of Adipose-Tissue-Derived Mesenchymal Stem Cells.

This Article presents, for the first time to our knowledge, an untargeted nuclear magnetic resonance (NMR) metabolomic characterization of the polar intracellular metabolic adaptations of human adipose-derived mesenchymal stem cells during osteogenic differentiation. The use of mesenchymal stem cells (MSCs) for bone regeneration is a promising alternative to conventional bone grafts, and untargeted metabolomics may unveil novel metabolic information on the osteogenic differentiation of MSCs, allowing their behavior to be understood and monitored/guided toward effective therapies. Our results unveiled statistically relevant changes in the levels of just over 30 identified metabolites, illustrating a highly dynamic process with significant variations throughout the whole 21-day period of osteogenic differentiation, mainly involving amino acid metabolism and protein synthesis; energy metabolism and the roles of glycolysis, the tricarboxylic acid cycle, and oxidative phosphorylation; cell membrane metabolism; nucleotide metabolism (including the specific involvement of O-glycosylation intermediates and NAD+); and metabolic players in protective antioxidative mechanisms (such as glutathione and specific amino acids). Different metabolic stages are proposed and are supported by putative biochemical explanations for the metabolite changes observed. This work lays the groundwork for the use of untargeted NMR metabolomics to find potential metabolic markers of osteogenic differentiation efficacy.

1H-NMR-based metabolomics reveals the biomarker panel and molecular mechanism of hepatocellular carcinoma progression.

Hepatocellular carcinoma (HCC) is one of the most extensive and most deadly cancers in the world. Biomarkers for early diagnosis of HCC are still lacking, and noninvasive and effective biomarkers are urgently needed. Metabolomics is committed to studying the changes of metabolites under stimulation, and provides a new approach for discovery of potential biomarkers. In the current work, 1H nuclear magnetic resonance (NMR) metabolomics approach was utilized to explore the potential biomarkers in HCC progression, and the biomarker panel was evaluated by receiver operating characteristic (ROC) curve analyses. Our results revealed that a biomarker panel consisting of hippurate, creatinine, putrescine, choline, and taurine might be involved in HCC progression. Functional pathway analysis showed that taurine and hypotaurine metabolism is markedly involved in the occurrence and development of HCC. Furthermore, our results indicated that the TPA activity and the level and expression of PKM2 were gradually increased in HCC progression. This research provides a scientific basis for screening potential biomarkers of HCC.

Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms.

Early diagnosis of cancer is critical for improving patient outcomes, but cancers may be hard to diagnose if patients present with nonspecific signs and symptoms. We have previously shown that nuclear magnetic resonance (NMR) metabolomics analysis can detect cancer in animal models and distinguish between differing metastatic disease burdens. Here, we hypothesized that biomarkers within the blood metabolome could identify cancers within a mixed population of patients referred from primary care with nonspecific symptoms, the so-called "low-risk, but not no-risk" patient group, as well as distinguishing between those with and without metastatic disease. Patients (n = 304 comprising modeling, n = 192, and test, n = 92) were recruited from 2017 to 2018 from the Oxfordshire Suspected CANcer (SCAN) pathway, a multidisciplinary diagnostic center (MDC) referral pathway for patients with nonspecific signs and symptoms. Blood was collected and analyzed by NMR metabolomics. Orthogonal partial least squares discriminatory analysis (OPLS-DA) models separated patients, based upon diagnoses received from the MDC assessment, within 62 days of initial appointment. Area under the ROC curve for identifying patients with solid tumors in the independent test set was 0.83 [95% confidence interval (CI): 0.72-0.95]. Maximum sensitivity and specificity were 94% (95% CI: 73-99) and 82% (95% CI: 75-87), respectively. We could also identify patients with metastatic disease in the cohort of patients with cancer with sensitivity and specificity of 94% (95% CI: 72-99) and 88% (95% CI: 53-98), respectively. For a mixed group of patients referred from primary care with nonspecific signs and symptoms, NMR-based metabolomics can assist their diagnosis, and may differentiate both those with malignancies and those with and without metastatic disease. See related commentary by Van Tine and Lyssiotis, p. 1477.

Potential of nuclear magnetic resonance metabolomics in the study of prostate cancer.

Nuclear magnetic resonance (NMR) metabolomics is a powerful analytical technique and a tool which has unique characteristics and capabilities for the evaluation of a number of biochemicals/metabolites of cancer and other disease processes that are present in biofluids (urine and blood) and tissues. The potential of NMR metabolomics in prostate cancer (PCa) has been explored by researchers and its usefulness has been documented. A large number of metabolites such as citrate, choline, and sarcosine were detected by NMR metabolomics from biofluids and tissues related to PCa and their levels were compared with controls and benign prostatic hyperplasia. The changes in the levels of these metabolites aid in the diagnosis and help to understand the dysregulated metabolic pathways in PCa. We review recent studies on in vitro and ex vivo NMR spectroscopy-based PCa metabolomics and its possible role as a diagnostic tool.

Principal Component Analysis (PCA) Loading and Statistical Tests for Nuclear Magnetic Resonance (NMR) Metabolomics Involving Multiple Study Groups

Metabolomics is an interdisciplinary area that integrates knowledge of instrumentation, data science, and biochemistry. Metabolomics studies the changes in a large number of metabolites after various treatments using analytical platforms. However, the interpretation approaches have not been completely investigated. Principal component analysis (PCA) is an unsupervised method that describes high throughput metabolite data, which is different from supervised approaches such as partial least-squares discriminant analysis (PLS-DA) which frequently has overfitting problems. The interpretation of PCA loadings, especially for studies with multiple study groups, is not well developed for metabolomics. In this study, a new method was reported that integrates PCA loading values with the commonly used statistical t-test analysis to significantly improve the convenience and efficiency of interpretation. The method was demonstrated using practical studies of NMR metabolomics on the extracts from sea anemone that were treated with six atrazine concentrations. The results indicated that the approach is suitable for multiple groups of metabolomics for early-stage discoveries, such as low concentrations and potentially longitudinal studies. In summary, this methodology may be critical in studies such as environmental metabolomics with various stimuli factors where the data interpretation was previously incompletely developed.

NMR Hydrophilic Metabolomic Analysis of Bacterial Resistance Pathways Using Multivalent Antimicrobials with Challenged and Unchallenged Wild Type and Mutated Gram-Positive Bacteria.

Multivalent membrane disruptors are a relatively new antimicrobial scaffold that are difficult for bacteria to develop resistance to and can act on both Gram-positive and Gram-negative bacteria. Proton Nuclear Magnetic Resonance (1H NMR) metabolomics is an important method for studying resistance development in bacteria, since this is both a quantitative and qualitative method to study and identify phenotypes by changes in metabolic pathways. In this project, the metabolic differences between wild type Bacillus cereus (B. cereus) samples and B. cereus that was mutated through 33 growth cycles in a nonlethal dose of a multivalent antimicrobial agent were identified. For additional comparison, samples for analysis of the wild type and mutated strains of B. cereus were prepared in both challenged and unchallenged conditions. A C16-DABCO (1,4-diazabicyclo-2,2,2-octane) and mannose functionalized poly(amidoamine) dendrimer (DABCOMD) were used as the multivalent quaternary ammonium antimicrobial for this hydrophilic metabolic analysis. Overall, the study reported here indicates that B. cereus likely change their peptidoglycan layer to protect themselves from the highly positively charged DABCOMD. This membrane fortification most likely leads to the slow growth curve of the mutated, and especially the challenged mutant samples. The association of these sample types with metabolites associated with energy expenditure is attributed to the increased energy required for the membrane fortifications to occur as well as to the decreased diffusion of nutrients across the mutated membrane.

Exosome-Enriched Plasma Analysis as a Tool for the Early Detection of Hypertensive Gestations.

Hypertensive disorders of pregnancy are closely associated with prematurity, stillbirth, and maternal morbidity and mortality. The onset of hypertensive disorders of pregnancy (HDP) is generally noticed after the 20th week of gestation, limiting earlier intervention. The placenta is directly responsible for modulating local and systemic physiology by communicating using mechanisms such as the release of extracellular vesicles, especially exosomes. In this study, we postulated that an analysis of exosome-enriched maternal plasma could provide a more focused and applicable approach for diagnosing HDP earlier in pregnancy. Therefore, the peripheral blood plasma of 24 pregnant women (11 controls, 13 HDP) was collected between 20th and 24th gestational weeks and centrifuged for exosome enrichment. Exosome-enriched plasma samples were analyzed by Raman spectroscopy and by proton nuclear magnetic resonance metabolomics (1H NMR). Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to analyze the Raman data, from the spectral region of 600–1,800 cm–1, to determine its potential to discriminate between groups. Using principal component analysis, we were able to differentiate the two groups, with 89% of all variances found in the first three principal components. In patients with HDP, most significant differences in Raman bands intensity were found for sphingomyelin, acetyl CoA, methionine, DNA, RNA, phenylalanine, tryptophan, carotenoids, tyrosine, arginine, leucine, amide I and III, and phospholipids. The 1H NMR analysis showed reduced levels of D-glucose, L-proline, L-tyrosine, glycine, and anserine in HDP, while levels of 2-hydroxyvalerate, polyunsaturated fatty acids, and very-low-density lipoprotein (VLDL) were increased. 1H NMR results were able to assign an unknown sample to either the control or HDP groups at a precision of 88.3% using orthogonal partial least squares discriminant analysis and 87% using logistic regression analysis. Our results suggested that an analysis of exosome-enriched plasma could provide an initial assessment of placental function at the maternal-fetal interface and aid HDP diagnosis, prognosis, and treatment, as well as to detect novel, early biomarkers for HDP.

Metabolic and Lipidomic Markers Differentiate COVID-19 From Non-Hospitalized and Other Intensive Care Patients.

Coronavirus disease 2019 (COVID-19) is a viral infection affecting multiple organ systems of great significance for metabolic processes. Thus, there is increasing interest in metabolic and lipoprotein signatures of the disease, and early analyses have demonstrated a metabolic pattern typical for atherosclerotic and hepatic damage in COVID-19 patients. However, it remains unclear whether this is specific for COVID-19 and whether the observed signature is caused by the disease or rather represents an underlying risk factor. To answer this question, we have analyzed 482 serum samples using nuclear magnetic resonance metabolomics, including longitudinally collected samples from 12 COVID-19 and 20 cardiogenic shock intensive care patients, samples from 18 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody-positive individuals, and single time point samples from 58 healthy controls. COVID-19 patients showed a distinct metabolic serum profile, including changes typical for severe dyslipidemia and a deeply altered metabolic status compared with healthy controls. Specifically, very-low-density lipoprotein and intermediate-density lipoprotein particles and associated apolipoprotein B and intermediate-density lipoprotein cholesterol were significantly increased, whereas cholesterol and apolipoprotein A2 were decreased. Moreover, a similarly perturbed profile was apparent when compared with other patients with cardiogenic shock who are in the intensive care unit when looking at a 1-week time course, highlighting close links between COVID-19 and lipid metabolism. The metabolic profile of COVID-19 patients distinguishes those from healthy controls and also from patients with cardiogenic shock. In contrast, anti-SARS-CoV-2 antibody-positive individuals without acute COVID-19 did not show a significantly perturbed metabolic profile compared with age- and sex-matched healthy controls, but SARS-CoV-2 antibody-titers correlated significantly with metabolic parameters, including levels of glycine, ApoA2, and small-sized low- and high-density lipoprotein subfractions. Our data suggest that COVID-19 is associated with dyslipidemia, which is not observed in anti-SARS-CoV-2 antibody-positive individuals who have not developed severe courses of the disease. This suggests that lipoprotein profiles may represent a confounding risk factor for COVID-19 with potential for patient stratification.

Molecular Discrimination between Organic and Conventional Liquid Milk Products in Thailand Using 1H-NMR Metabolomics Approach

The aims of this study were to characterize and compare non-volatile polar metabolite profiles of organic and conventional liquid milk products using a non-targeted proton nuclear magnetic resonance ( 1 H-NMR) metabolomics approach. Pasteurized plain-liquid milk products from 10 different brands available in Thai marketplace were analyzed for their major chemical compositions and 1 H-NMR derived metabolome data. Results demonstrated no specific trend for differentiation between organic and conventional milk samples based on their pH, fat, protein, lactose, and milk solid-not-fat compositions. A total of 45 non-volatile polar metabolites in milk samples were identified by 1 H-NMR technique. The chemometric analysis allowed discrimination between organic and conventional milk samples based on their 1 H-NMR metabolite profiles. Changes in the relative concentration of formate, betaine, dimethyl sulfone, 2-oxoglutarate, creatine, pyruvate, butyrate, proline, acetoacetate, alanine, glycerophosphocholine, carnitine, and hippurate were statistically identified as potential biomarkers accountable for the discrimination between organic and conventional milk samples in this study. Variations of these compounds might be the reflections of animal diets, rumen fermentation, and physiological adaptation of the cows raised in organic dairy farming systems. Our findings provide new insights and support the effectiveness of using a non-targeted 1 H-NMR combined with chemometrics to investigate the molecular authenticity of organic food products.

Urinary metabolomic signatures as indicators of injury severity following traumatic brain injury: A pilot study.

BackgroundAnalysis of fluid metabolites has the potential to provide insight into the neuropathophysiology of injury in patients with traumatic brain injury (TBI).ObjectiveUsing a 1H nuclear magnetic resonance (NMR)-based quantitative metabolic profiling approach, this study determined (1) if urinary metabolites change during recovery in patients with mild to severe TBI; (2) whether changes in urinary metabolites correlate to injury severity; (3) whether biological pathway analysis reflects mechanisms that mediate neural damage/repair throughout TBI recovery.MethodsUrine samples were collected within 7 days and at 6-months post-injury in male participants (n = 8) with mild-severe TBI. Samples were analyzed with NMR-based quantitative spectroscopy for metabolomic profiles and analyzed with multivariate statistical and machine learning-based analyses.ResultsLower levels of homovanillate (R = −0.74, p ≤ 0.001), L-methionine (R = −0.78, p < 0.001), and thymine (R = −0.85, p < 0.001) negatively correlated to injury severity. Pathway analysis revealed purine metabolism to be a primary pathway (p < 0.01) impacted by TBI.ConclusionThis study provides pilot data to support the use of urinary metabolites in clinical practice to better interpret biochemical changes underlying TBI severity and recovery. The discovery of urinary metabolites as biomarkers may assist in objective and rapid identification of TBI severity and prognosis. Thus, 1H NMR metabolomics has the potential to facilitate the adaptation of treatment programs that are personalized to the patient’s needs.

Impact of the Pd2Spm (Spermine) Complex on the Metabolism of Triple-Negative Breast Cancer Tumors of a Xenograft Mouse Model.

The interest in palladium(II) compounds as potential new anticancer drugs has increased in recent years, due to their high toxicity and acquired resistance to platinum(II)-derived agents, namely cisplatin. In fact, palladium complexes with biogenic polyamines (e.g., spermine, Pd2Spm) have been known to display favorable antineoplastic properties against distinct human breast cancer cell lines. This study describes the in vivo response of triple-negative breast cancer (TNBC) tumors to the Pd2Spm complex or to cisplatin (reference drug), compared to tumors in vehicle-treated mice. Both polar and lipophilic extracts of tumors, excised from a MDA-MB-231 cell-derived xenograft mouse model, were characterized through nuclear magnetic resonance (NMR) metabolomics. Interestingly, the results show that polar and lipophilic metabolomes clearly exhibit distinct responses for each drug, with polar metabolites showing a stronger impact of the Pd(II)-complex compared to cisplatin, whereas neither drug was observed to significantly affect tumor lipophilic metabolism. Compared to cisplatin, exposure to Pd2Spm triggered a higher number of, and more marked, variations in some amino acids, nucleotides and derivatives, membrane precursors (choline and phosphoethanolamine), dimethylamine, fumarate and guanidine acetate, a signature that may be relatable to the cytotoxicity and/or mechanism of action of the palladium complex. Putative explanatory biochemical hypotheses are advanced on the role of the new Pd2Spm complex in TNBC metabolism.

Objective biomarkers for clinical relapse in multiple sclerosis: a metabolomics approach

Accurate determination of relapses in multiple sclerosis is important for diagnosis, classification of clinical course and therapeutic decision making. The identification of biofluid markers for multiple sclerosis relapses would add to our current diagnostic armamentarium and increase our understanding of the biology underlying the clinical expression of inflammation in multiple sclerosis. However, there is presently no biofluid marker capable of objectively determining multiple sclerosis relapses although some, in particular neurofilament-light chain, have shown promise. In this study, we sought to determine if metabolic perturbations are present during multiple sclerosis relapses, and, if so, identify candidate metabolite biomarkers and evaluate their discriminatory abilities at both group and individual levels, in comparison with neurofilament-light chain. High-resolution global and targeted 1H nuclear magnetic resonance metabolomics as well as neurofilament-light chain measurements were performed on the serum in four groups of relapsing-remitting multiple sclerosis patients, stratified by time since relapse onset: (i) in relapse (R); (ii) last relapse (LR) ≥ 1 month (M) to < 6 M ago; (iii) LR ≥ 6 M to < 24 M ago; and (iv) LR ≥ 24 M ago. Two hundred and one relapsing-remitting multiple sclerosis patients were recruited: R (n = 38), LR 1–6 M (n = 28), LR 6–24 M (n = 34), LR ≥ 24 M (n = 101). Using supervised multivariate analysis, we found that the global metabolomics profile of R patients was significantly perturbed compared to LR ≥ 24 M patients. Identified discriminatory metabolites were then quantified using targeted metabolomics. Lysine and asparagine (higher in R), as well as, isoleucine and leucine (lower in R), were shortlisted as potential metabolite biomarkers. ANOVA of these metabolites revealed significant differences across the four patient groups, with a clear trend with time since relapse onset. Multivariable receiver operating characteristics analysis of these four metabolites in discriminating R versus LR ≥ 24 M showed an area under the curve of 0.758, while the area under the curve for serum neurofilament-light chain was 0.575. Within individual patients with paired relapse–remission samples, all four metabolites were significantly different in relapse versus remission, with the direction of change consistent with that observed at group level, while neurofilament-light chain was not discriminatory. The perturbations in the identified metabolites point towards energy deficiency and immune activation in multiple sclerosis relapses, and the measurement of these metabolites, either singly or in combination, are useful as biomarkers to differentiate relapse from remission at both group and individual levels.

High-Density Lipoprotein 3 Cholesterol and Primary Open-Angle Glaucoma: Metabolomics and Mendelian Randomization Analyses

We hypothesized that the effect of blood lipid-related metabolites on primary open-angle glaucoma (POAG) would differ according to specific lipoprotein particles and lipid sub-fractions. We investigated the associations of blood levels of lipoprotein particles and lipid sub-fractions with POAG. Cross-sectional study. Individuals recruited for the baseline visit of the population-based Singapore Epidemiology of Eye Disease study (n= 8503). All participants underwent detailed standardized ocular and systemic examinations. A total of 130 blood lipid-related metabolites were quantified using a nuclear magnetic resonance metabolomics platform. The analyses were conducted in 2 stages. First, we investigated whether and which lipid-related metabolites were directly associated with POAG using regression analyses followed by Bayesian network modeling. Second, we investigated if any causal relationship exists between the identified lipid-related metabolites, if any, and POAG using 2-sample Mendelian randomization (MR) analysis. We performed genome-wide association studies (GWAS) on high-density lipoprotein (HDL) 3 cholesterol (after inverse normal transformation) and used the top variants associated with HLD3 cholesterol as instrumental variables (IVs) in the MR analysis. Primary open-angle glaucoma. Of the participants, 175 (2.1%) had POAG. First, a logistic regression model showed that total HDL3 cholesterol (negatively) and phospholipids in very large HDL (positively) were associated with POAG. Further analyses using a Bayesian network analysis showed that only total HDL3 cholesterol was directly associated with POAG (odds ratio [OR], 0.72 per 1 standard deviation increase in HDL3 cholesterol; 95% confidence interval [CI], 0.61-0.84), independently of age, gender, intraocular pressure (IOP), body mass index (BMI), education level, systolic blood pressure, axial length, and statin medication. Using 5 IVs identified from the GWAS and with the inverse variance weighted MR method, we found that higher levels of HDL3 cholesterol were associated with a decreased odds of POAG (OR, 0.91; 95% CI, 0.84-0.99, P= 0.021). Other MR methods, including weighted median, mode-based estimator, and contamination mixture methods, derived consistent OR estimates. None of the routine lipids (blood total, HDL, or low-density lipoprotein [LDL] cholesterol) were associated with POAG. Overall, these results suggest that the relationship between HDL3 cholesterol and POAG might be causal and specific, and that dysregulation of cholesterol transport may play a role in the pathogenesis of POAG.