Nuclear Magnetic Resonance-based Metabolomics Research Articles

Changes in the urinary metabolome accompanied alterations in body mass and composition in women with overweight – impact of high versus low protein breakfast

IntroductionUnderstanding why subjects with overweight and with obesity vary in their response to dietary interventions is of major interest for developing personalized strategies for body mass regulation.ObjectivesThe aim of this study was to investigate the relationship between changes in the urine metabolome and body mass during a breakfast meal intervention. Furthermore, we aimed to elucidate if the baseline urine metabolome could predict the response to the two types of breakfast meals (high versus low protein) during the intervention.MethodsA total of 75 young, women with overweight were randomly allocated to one of two intervention groups: (1) High-protein (HP) or (2) low-protein (LP) breakfast as part of their habitual diet during a 12-week intervention. Beside the breakfast meal, participants were instructed to eat their habitual diet and maintain their habitual physical activity level. Nuclear magnetic resonance-based metabolomics was conducted on urine samples collected at baseline (wk 0), mid-intervention (wk 6), and at endpoint (wk 12). At baseline and endpoint, body mass was measured and DXA was used to measure lean body mass and fat mass.ResultsThe baseline urine metabolite profile showed a slightly higher correlation (R2 = 0.56) to body mass in comparison with lean body mass (R2 = 0.51) and fat mass (R2 = 0.53). Baseline 24-h urinary excretion of trigonelline (p = 0.04), N, N-dimethylglycine (p = 0.02), and trimethylamine (p = 0.03) were significantly higher in individuals who responded with a reduction in body mass to the HP breakfast.ConclusionsDifferences in the urine metabolome were seen for women that obtained a body weight loss in the response to the HP breakfast intervention and women who did not obtain a body weight loss, indicating that the urine metabolome contains information about the metabolic phenotype that influences the responsiveness to dietary interventions.

Fibroblast growth factor 21 enhances learning and memory performance in mice by regulating hippocampal L-lactate homeostasis

Fibroblast growth factor 21 (FGF21) is one endogenous metabolic molecule that functions as a regulator in glucose and lipid homeostasis. However, the effect of FGF21 on L-lactate homeostasis and its mechanism remains unclear until now. Forty-five Six-week-old male C57BL/6 mice were divided into three groups: control, L-lactate, and FGF21 (1.5 mg/kg) groups. At the end of the treatment, nuclear magnetic resonance-based metabolomics, and key proteins related to L-lactate homeostasis were determined respectively to evaluate the efficacy of FGF21 and its mechanisms. The results showed that, compared to the vehicle group, the L-lactate-treated mice displayed learning and memory performance impairments, as well as reduced hippocampal ATP and NADH levels, but increased oxidative stress, mitochondrial dysfunction, and apoptosis, which suggesting inhibited L-lactate-pyruvate conversion in the brain. Conversely, FGF21 treatment ameliorated the L-lactate accumulation state, accompanied by restoration of the learning and memory defects, indicating enhanced L-lactate uptake and utilization in hippocampal neurons. We demonstrated that maintaining constant L-lactate-pyruvate flux is essential for preserving neuronal bioenergetic and redox levels. FGF21 contributed to preparing the brain for situations of high availability of L-lactate, thus preventing neuronal vulnerability in metabolic reprogramming.

Metabolomic analysis reveals the biological characteristics of giant congenital melanocytic nevi

Giant congenital melanocytic nevi (GCMN) is a congenital cutaneous developmental deformity tumor that usually occurs at birth or in the first few weeks after birth, but its pathogenesis is still unclear. In this study, nuclear magnetic resonance-based metabolomics strategy was employed to evaluate the metabolic variations in serum and urine of the GCMN patients in order to understand its underlying biochemical mechanism and provide a potential intervention idea. Twenty-nine metabolites were observed to change significantly in serum and urine metabolomes, which are mainly involved in a variety of metabolic pathways including glyoxylate and dicarboxylate metabolism, TCA cycle and metabolisms of amino acids. The substantial cores of all the disturbed metabolic pathways are related to amino acid metabolism and carbohydrate metabolism and regulate the physiological state of the GCMN patients. Our results provide the physiological basis and physiological responses of GCMN and will be helpful for better understanding the molecular mechanisms of GCMN in future research.

Synergistic metabolism of salivary MUC5B in oral commensal bacteria during early biofilm formation.

Bacterial metabolism in oral biofilms is comprised of complex networks of nutritional chains and biochemical regulations. These processes involve both intraspecies and interspecies networks as well as interactions with components from host saliva, gingival crevicular fluid, and dietary intake. In a previous paper, a large salivary glycoprotein, mucin MUC5B, was suggested to promote a dental health-related phenotype in the oral type strain of Streptococcus gordonii DL1, by regulating bacterial adhesion and protein expression. In this study, nuclear magnetic resonance-based metabolomics was used to examine the effects on the metabolic output of monospecies compared to dual species early biofilms of two clinical strains of oral commensal bacteria, S. gordonii and Actinomyces naeslundii, in the presence of MUC5B. The presence of S. gordonii increased colonization of A. naeslundii on salivary MUC5B, and both commensals were able to utilize MUC5B as a sole nutrient source during early biofilm formation. The metabolomes suggested that the bacteria were able to release mucin carbohydrates from oligosaccharide side chains as well as amino acids from the protein core. Synergistic effects were also seen in the dual species biofilm metabolome compared to the monospecies, indicating that A. naeslundii and S. gordonii cooperated in the degradation of salivary MUC5B. A better understanding of bacterial interactions and salivary-mediated regulation of early dental biofilm activity is meaningful for understanding oral biofilm physiology and may contribute to the development of future prevention strategies for biofilm-induced oral disease.IMPORTANCEThe study of bacterial interactions and salivary-mediated regulation of early dental biofilm activity is of interest for understanding oral microbial adaptation to environmental cues and biofilm maturation. Findings in oral commensals can prove useful from the perspectives of both oral and systemic health of the host, as well as the understanding of general microbial biofilm physiology. The knowledge may provide a basis for the development of prognostic biomarkers, or development of new treatment strategies, related to oral health and disease and possibly also to other biofilm-induced conditions. The study is also an important step toward developing the methodology for similar studies in other species and/or growth conditions.

Abstract P128: Detection Of Congenital Intrahepatic Vascular Shunt In C57BL/6 Mice

Portosystemic shunt (PSS) is an abnormal vein that leaks blood from portal vein into systemic circulation, thus bypassing the liver. We previously reported its sporadic occurrence as a congenital defect in C57BL/6 mice as well as in humans. PSS results in vascular, hepatic and metabolic anomalies. Therefore, in experimental protocols using C57BL/6 mice, ones with PSS should be identified as outliers. Accordingly, we sought methods to discern 8-weeks-old male C57BL/6 mice (n=6) as non-PSS or PSS mice. Serum total bile acids (TBA) is a bona fide biomarker of PSS in mice (non-PSS: 6.1±1.0 vs PSS: 80.6±8.2 μM; p<0.001), but utility of this biomarker is limited by its cost and invasiveness, particularly if large numbers of mice are to be screened. This led us to investigate whether use of urine might serve as a simple, inexpensive, non-invasive means of PSS diagnosis. Since urinary TBA were comparable between non-PSS (4.1±1.3 μM) and PSS mice (4.8±1.7 μM; p=0.45), we asked whether there are other urinary metabolites that could be exploited as biomarkers. Nuclear magnetic resonance-based metabolomics uncovered that Krebs cycle intermediates, i.e. , citrate (non-PSS: 1.0±0.1 v s PSS: 1.6±0.04; p<0.001), α-ketoglutarate (non-PSS: 1.0±0.1 v s PSS: 3.6±0.2; p<0.001), and fumarate (non-PSS: 1.0±0.2 v s PSS: 3.7±0.4; p<0.001) were strikingly elevated (expressed in fold change) in the urine of PSS mice. We leveraged the pH-lowering properties of such metabolites as the basis for two urine-based screening tests. Firstly, using pH test strips with a 5.5-8.0 range, we detected the differences in their urinary pH (non-PSS: 6.3±0.1 v s PSS: 5.6±0.1; p<0.001). Secondly, the difference in urinary pH was additionally quantified using the phenol red assay (non-PSS: 0.9±0.1 v s PSS: 0.2±0.03 at OD 560nm ; p<0.001). Using a larger cohort of non-PSS (n=44) and PSS (n=27) mice, we determined that the urinary phenol red assay had an accuracy of 95.8%, sensitivity of 96.3%, and specificity of 95.5% in identifying PSS mice. Taken together, these results demonstrate the feasibility of using urine as a liquid biopsy to screen for murine PSS. Application of our urinary PSS screening protocols importantly enables stratification of PSS mice, which confound cardiovascular and metabolic studies.

Balanced replacement of fish meal with Hermetia illucens meal allows efficient hepatic nutrient metabolism and increases fillet lipid quality in gilthead sea bream (Sparus aurata)

In the present study, gilthead sea bream (Sparus aurata) was reared using sustainable feeds containing insect meal from Hermetia illucens larvae. Proteomics and proton nuclear magnetic resonance-based metabolomics analysis were used to assess the metabolic impact of the tested feeds in sea bream liver, whereas the composition of muscle fillets was characterized by means of metabolomics and gas chromatography of fatty acid methyl esters. Including 10% of insect meal while correspondingly reducing fish meal did not substantially alter the metabolism of dietary nutrients, leading to small but significant effects solely on lauric acid content of sea bream fillets. Furthermore, a few alterations in some markers of immune response, such as leukocyte elastase inhibitor-like, granzyme B (G, H)-like, and two associated ortholog groups, serpin B and chymase, were found. In the fish group fed with insect meal, liver morphology analysis showed no structural damage or inflammation and a lower amount of hepatic lipid deposition and accumulation.

Comparative Metabolomics Analysis of Weedy Rice (Oryza spp.) across Peninsular Malaysia

Weedy rice (Oryza spp.) is a notorious weed that invades paddy fields and hampers the rice’s production and yield quality; thus, it has become a major problem for rice farmers worldwide. Weedy rice comprises a diverse morphology and phenotypic variation; however, the metabolome and chemical phenotypes of weedy rice grains have not been explored. Therefore, this study is aimed to investigate the metabolite profiles and chemical diversity of Malaysian weedy rice. Thirty-one biotypes of weedy rice grains were collected from selected rice granaries in different states of Peninsular Malaysia, including Selangor, Perak, Penang, Kedah, Perlis, Kelantan, and Terengganu. In addition to the weedy rice samples, four cultivated rice varieties (MR219, MR220, MR220 CL2, and MARDI Siraj 297) were subjected to nuclear magnetic resonance-based metabolomics. The PLS-DA and OPLS-DA models revealed a clear separation between the weedy rice and cultivated rice, which was contributed by the higher level of γ-aminobutyric acid (GABA), α-glucose, fumaric acid, and phenylalanine in the weedy rice, whilst valine, leucine, isoleucine, fatty acids, 2,3-butanediol, threonine, alanine, butyric acid, choline, γ-oryzanol, fructose, β-glucose, sucrose, ferulic acid, and formic acid were found dominant in the cultivated rice. Interestingly, the models also showed a separation between the weedy rice samples collected from the west coast and east coast regions of Peninsular Malaysia. The metabolites responsible for the separation, i.e., threonine, alanine, butyric acid, fructose, β-glucose, and formic acid, were found higher in the west coast samples, and the east coast samples were discriminated by higher levels of valine, leucine, isoleucine, fatty acids, 2,3-butanediol, choline, GABA, γ-oryzanol, α-glucose, sucrose, fumaric acid, ferulic acid, and phenylalanine. This study is the first to provide insights into the metabolite profiles and chemical phenotypes of Malaysian weedy rice that could be influenced by genotype and environmental conditions. The information on the weedy rice metabolome and omics data is important for further research on weed management and crop improvement.

NMR-based metabolomic profiling identifies inflammation and muscle-related metabolites as predictors of incident type 2 diabetes mellitus beyond glucose: The Di@bet.es study

AimsThe aim of this study was to combine nuclear magnetic resonance-based metabolomics and machine learning to find a glucose-independent molecular signature associated with future type 2 diabetes mellitus development in a subgroup of individuals from the Di@bet.es study. MethodsThe study group included 145 individuals developing type 2 diabetes mellitus during the 8-year follow-up, 145 individuals matched by age, sex and BMI who did not develop diabetes during the follow-up but had equal glucose concentrations to those who did and 145 controls matched by age and sex. A metabolomic analysis of serum was performed to obtain the lipoprotein and glycoprotein profiles and 15 low molecular weight metabolites. Several machine learning-based models were trained. ResultsLogistic regression performed the best classification between individuals developing type 2 diabetes during the follow-up and glucose-matched individuals. The area under the curve was 0.628, and its 95% confidence interval was 0.510–0.746. Glycoprotein-related variables, creatinine, creatine, small HDL particles and the Johnson-Neyman intervals of the interaction of Glyc A and Glyc B were statistically significant. ConclusionsThe model highlighted a relevant contribution of inflammation (glycosylation pattern and HDL) and muscle (creatinine and creatine) in the development of type 2 diabetes as independent factors of hyperglycemia.

Quantitative plasma profiling by 1H NMR-based metabolomics: impact of sample treatment.

Introduction: There is evidence that sample treatment of blood-based biosamples may affect integral signals in nuclear magnetic resonance-based metabolomics. The presence of macromolecules in plasma/serum samples makes investigating low-molecular-weight metabolites challenging. It is particularly relevant in the targeted approach, in which absolute concentrations of selected metabolites are often quantified based on the area of integral signals. Since there are a few treatments of plasma/serum samples for quantitative analysis without a universally accepted method, this topic remains of interest for future research. Methods: In this work, targeted metabolomic profiling of 43 metabolites was performed on pooled plasma to compare four methodologies consisting of Carr-Purcell-Meiboom-Gill (CPMG) editing, ultrafiltration, protein precipitation with methanol, and glycerophospholipid solid-phase extraction (g-SPE) for phospholipid removal; prior to NMR metabolomics analysis. The effect of the sample treatments on the metabolite concentrations was evaluated using a permutation test of multiclass and pairwise Fisher scores. Results: Results showed that methanol precipitation and ultrafiltration had a higher number of metabolites with coefficient of variation (CV) values above 20%. G-SPE and CPMG editing demonstrated better precision for most of the metabolites analyzed. However, differential quantification performance between procedures were metabolite-dependent. For example, pairwise comparisons showed that methanol precipitation and CPMG editing were suitable for quantifying citrate, while g-SPE showed better results for 2-hydroxybutyrate and tryptophan. Discussion: There are alterations in the absolute concentration of various metabolites that are dependent on the procedure. Considering these alterations is essential before proceeding with the quantification of treatment-sensitive metabolites in biological samples for improving biomarker discovery and biological interpretations. The study demonstrated that g-SPE and CPMG editing are effective methods for removing proteins and phospholipids from plasma samples for quantitative NMR analysis of metabolites. However, careful consideration should be given to the specific metabolites of interest and their susceptibility to the sample treatment procedures. These findings contribute to the development of optimized sample preparation protocols for metabolomics studies using NMR spectroscopy.

Serum and urine metabolomic biomarkers for predicting prognosis in patients with immunoglobulin A nephropathy.

Immunoglobulin A nephropathy (IgAN) is the most prevalent form of glomerulonephritis worldwide. Prediction of disease progression in IgAN can help to provide individualized treatment based on accurate risk stratification. We performed proton nuclear magnetic resonance-based metabolomics analyses of serum and urine samples from healthy controls, non-progressor (NP), and progressor (P) groups to identify metabolic profiles of IgAN disease progression. Metabolites that were significantly different between the NP and P groups were selected for pathway analysis. Subsequently, we analyzed multivariate area under the receiver operating characteristic (ROC) curves to evaluate the predictive power of metabolites associated with IgAN progression. We observed several distinct metabolic fingerprints of the P group involving the following metabolic pathways: glycolipid metabolism; valine, leucine, and isoleucine biosynthesis; aminoacyl-transfer RNA biosynthesis; glycine, serine, and threonine metabolism; and glyoxylate and dicarboxylate metabolism. In multivariate ROC analyses, the combinations of serum glycerol, threonine, and proteinuria (area under the curve [AUC], 0.923; 95% confidence interval [CI], 0.667-1.000) and of urinary leucine, valine, and proteinuria (AUC, 0.912; 95% CI, 0.667-1.000) showed the highest discriminatory ability to predict IgAN disease progression. This study identified serum and urine metabolites profiles that can aid in the identification of progressive IgAN and proposed perturbed metabolic pathways associated with the identified metabolites.

Nuclear magnetic resonance-based metabolomics in goat ovarian follicular fluid

During folliculogenesis, follicular fluid (FF) supplies many of the nutrients, metabolic compounds, and signaling molecules that are essential for the accumulation of metabolic substrate stores within the oocyte. The use of metabolomics can identify metabolites produced in FF that are related to oocyte quality. Thus, this work aimed to carry out a qualitative metabolomic study using Hydrogen Nuclear Magnetic Resonance Spectroscopy (1H NMR) to characterize FF components of goats after hormonal estrus synchronization (HES) and no estrus synchronization (NES). Fluids of small (< 3 mm) and large (≥ 3 mm) follicles were collected and evaluated. 1H NMR analyses permitted to characterize seventeen metabolites, comprising sugars, amino acids, short chain organic acids, fatty acids residues, besides acetylated glycoprotein, choline phosphate and choline glycerophosphate. Qualitative differences were observed between follicles at different stages of development (small vs large). Finally, further quantitative studies will be needed to clarify the FF synthesis in goats and the effects on the quality of oocytes.

Novel biomarkers and emerging tools to identify causal molecular pathways in hypertension and associated cardiovascular diseases.

Hypertension (HT) is a modifiable risk factor for life-threatening cardiovascular diseases (CVDs) including coronary artery disease, heart failure, or stroke. Despite significant progress in understanding the pathophysiological mechanisms of the disease, the molecular pathways targeted by HT treatment remain largely unchanged. This warrants the need for finding novel biomarkers, which are causally related to persistent high blood pressure (BP) and may be pharmacologically targeted. Analytical output derived from large-scale biobanks, containing high-throughput genetic and biochemical data, such as OLINK and SomaScan-based proteomics or Nuclear Magnetic Resonance-based metabolomics, as well as novel analytical tools including the Mendelian randomization (MR) approach, enabling genetic causal inference, may create new treatment opportunities for HT and related CVDs. MR analysis may constitute additional evidence for observational studies and facilitate selection of drug targets for clinical testing and has been already used to nominate potentially causal biomarkers for HT and CVDs such as circulating glycine, branched-chain amino acids, lipoprotein(a), insulin-like growth factor 1, or fibronectin 1. Using the MR framework, genetic proxies for targets of already known drugs, such as statins, PCSK9, and ACE inhibitors, may additionally be informative about potential side effects and eventually contribute to more personalized medicine. Finally, genetic causal inference may disentangle independent direct effects of correlated traits such as lipid classes or markers of inflammation on cardiovascular clinical outcomes such as atherosclerosis and HT. While several novel HT-targeting drugs are currently under clinical investigation (e.g. brain renin-angiotensin-aldosterone system inhibitors or endothelin-1 receptor antagonists), analysis of high-throughput proteomic and metabolomic data from well-powered studies may deliver novel druggable molecular targets for HT and associated CVDs.

Nuclear Magnetic Resonance-Based Metabolomics Approach Revealed the Intervention Effect of Using Complementary and Alternative Medicine (CAM) by CKD Patients.

Chronic kidney disease (CKD) is the end point of a number of systemic chronic diseases. The prevalence of CKD is increasing worldwide and recent epidemiological studies are showing the high prevalence of renal failure in CKD patients using complementary and alternative medicines (CAMs). Clinicians believe that biochemical profiles of CKD patients using CAM (referred here to as CAM-CKD) may be different compared to those on standard clinical treatment and should be managed differently. The present study aims to explore the potential of the NMR-based metabolomics approach to reveal the serum metabolic disparity between CKD and CAM-CKD patients with respect to normal control (NC) subjects and if the differential metabolic patterns can provide rationale for the efficacy and safety of standard and/or alternative therapies. Serum samples were obtained from 30 CKD patients, 43 CAM-CKD patients, and 47 NC subjects. The quantitative serum metabolic profiles were measured using 1D 1H CPMG NMR experiments performed at 800 MHz NMR spectrometer. The serum metabolic profiles were compared using various multivariate statistical analysis tools available on MetaboAnalyst (freely available web-based software) such as partial least-squares discriminant analysis (PLS-DA) and random forest (a machine learning) classification method. The discriminatory metabolites were identified based on variable importance in projection (VIP) statistics and further evaluated for statistical significance (i.e., p < 0.05) using either Student t-test or ANOVA statistics. PLS-DA models were capable of clustering CKD and CAM-CKD with considerably high values of Q 2 and R 2. Compared to CAM-CKD patients, the sera of CKD patients were characterized by (a) elevated levels of urea, creatinine, citrate, glucose, glycerol, and phenylalanine and phenylalanine-to-tyrosine ratio (PTR) and (b) decreased levels of various amino acids (such leucine, isoleucine, valine, and alanine), high-density lipoproteins, lactate, and acetate. These changes suggested that CKD patients manifest severe oxidative stress, hyperglycemia (with dampened glycolysis), increased protein energy wasting, and reduced lipid/membrane metabolism. Statistically significant and strong positive correlation of PTR with serum creatinine levels suggested the role of oxidative stress in the progression of kidney disease. Significant differences in metabolic patterns between CKD and CAM-CKD patients were observed. With respect to NC subjects, the serum metabolic changes were more aberrant in CKD patients compared to CAM-CKD patients. The aberrant metabolic changes in CKD patients with manifestations of higher oxidative stress compared to CAM-CKD patients could explain clinical discrepancies between CKD and CAM-CKD patients and further advocate the use of different treatment strategies for CKD and CAM-CKD patients.

Nuclear Magnetic Resonance-Based Metabolomics to Predict Early and Late Adverse Outcomes in Ischemic Stroke Treated with Intravenous Thrombolysis.

Metabolic perturbations and inflammatory mediators play a fundamental role in both early and late adverse post-acute ischemic stroke outcomes. Using data from the observational MAGIC (MArker bioloGici nell'Ictus Cerebrale) study, we evaluated the effect of 130 serum metabolic features, using a nuclear magnetic spectroscopy approach, on the following outcomes: hemorrhagic transformation at 24 h after stroke, non-response to intravenous thrombolytic treatment with the recombinant tissue plasminogen activator (rt-PA), and the 3 month functional outcome. Blood circulating metabolites, lipoproteins, and inflammatory markers were assessed at the baseline and 24 h after rt-PA treatment. Adjusting for the major determinants for unfavorable outcomes (i.e., age, sex, time onset-to-treatment, etc.), we found that acetone and 3-hydroxybutyrate were associated with symptomatic hemorrhagic transformation and with non-response to rt-PA; while 24 h after rt-PA, levels of triglycerides high-density lipoprotein (HDL) and triglycerides low-density lipoprotein (LDL) were associated with 3 month mortality. Cholesterol and phospholipids levels, mainly related to smaller and denser very low-density lipoprotein (VLDL) and LDL subfractions were associated with 3 month poor functional outcomes. We also reported associations between baseline 24 h relative variation (Δ) in VLDL subfractions and ΔC-reactive protein, Δinterleukin-10 levels with hemorrhagic transformation. All observed metabolic changes reflect a general condition of energy failure, oxidative stress, and systemic inflammation that characterize the development of adverse outcomes.

MliR, a novel MerR-like regulator of iron homeostasis, impacts metabolism, membrane remodeling, and cell adhesion in the marine Bacteroidetes Bizionia argentinensis.

The MerR family is a group of transcriptional activators with conserved N-terminal helix-turn-helix DNA binding domains and variable C-terminal effector binding regions. In most MerR proteins the effector binding domain (EBD) contains a cysteine center suited for metal binding and mediates the response to environmental stimuli, such as oxidative stress, heavy metals or antibiotics. We here present a novel transcriptional regulator classified in the MerR superfamily that lacks an EBD domain and has neither conserved metal binding sites nor cysteine residues. This regulator from the psychrotolerant bacteria Bizionia argentinensis JUB59 is involved in iron homeostasis and was named MliR (MerR-like iron responsive Regulator). In silico analysis revealed that homologs of the MliR protein are widely distributed among different bacterial species. Deletion of the mliR gene led to decreased cell growth, increased cell adhesion and filamentation. Genome-wide transcriptomic analysis showed that genes associated with iron homeostasis were downregulated in mliR-deletion mutant. Through nuclear magnetic resonance-based metabolomics, ICP-MS, fluorescence microscopy and biochemical analysis we evaluated metabolic and phenotypic changes associated with mliR deletion. This work provides the first evidence of a MerR-family regulator involved in iron homeostasis and contributes to expanding our current knowledge on relevant metabolic pathways and cell remodeling mechanisms underlying in the adaptive response to iron availability in bacteria.

Accelerometer-Based Sedentary Time, Physical Activity, and Serum Metabolome in Young Men.

Physical activity (PA) has been shown to associate with many health benefits but studies with metabolome-wide associations with PA are still lacking. Metabolome studies may deepen the mechanistic understanding of PA on the metabolic pathways related to health outcomes. The aim of the present study was to study the association of accelerometer based sedentary time (SB) and PA with metabolome measures. SB and PA were measured by a hip-worn accelerometer in 314 young adult men (age: mean 28, standard deviation 7 years). Metabolome was analyzed from fasting serum samples consisting of 66 metabolome measures (nuclear magnetic resonance-based metabolomics). The associations were analyzed using a single and compositional approach with regression analysis. The compositional analysis revealed that 4 metabolome variables were significantly (γ: 0.32–0.44, p ≤ 0.002), and 13 variables with a trend towards significance (p < 0.05), associated with SB with varying metabolic pathways. Trends towards significant associations (p < 0.05) were observed with 5 variables with moderate-to-vigorous and 1 variable with light intensity PA with varying metabolic pathways. The present study revealed possible mechanistic pathways relevant for the interaction between especially SB but also PA of moderate-to-vigorous intensity with ketone bodies and amino acid concentration related to exercised-induced energy production and lipid metabolism.

Metabolomics profile in acute respiratory distress syndrome by nuclear magnetic resonance spectroscopy in patients with community-acquired pneumonia

BackgroundAcute respiratory distress syndrome (ARDS) is a challenging clinical problem. Discovering the potential metabolic alterations underlying the ARDS is important to identify novel therapeutic target and improve the prognosis. Serum and urine metabolites can reflect systemic and local changes and could help understanding metabolic characterization of community-acquired pneumonia (CAP) with ARDS.MethodsClinical data of patients with suspected CAP at the First Affiliated Hospital of Wenzhou Medical University were collected from May 2020 to February 2021. Consecutive patients with CAP were enrolled and divided into two groups: CAP with and without ARDS groups. 1H nuclear magnetic resonance-based metabolomics analyses of serum and urine samples were performed before and after treatment in CAP with ARDS (n = 43) and CAP without ARDS (n = 45) groups. Differences metabolites were identifed in CAP with ARDS. Furthermore, the receiver operating characteristic (ROC) curve was utilized to identify panels of significant metabolites for evaluating therapeutic effects on CAP with ARDS. The correlation heatmap was analyzed to further display the relationship between metabolites and clinical characteristics.ResultsA total of 20 and 42 metabolites were identified in the serum and urine samples, respectively. Serum metabolic changes were mainly involved in energy, lipid, and amino acid metabolisms, while urine metabolic changes were mainly involved in energy metabolism. Elevated levels of serum 3-hydroxybutyrate, lactate, acetone, acetoacetate, and decreased levels of serum leucine, choline, and urine creatine and creatinine were detected in CAP with ARDS relative to CAP without ARDS. Serum metabolites 3-hydroxybutyrate, acetone, acetoacetate, citrate, choline and urine metabolite 1-methylnicotinamide were identified as a potential biomarkers for assessing therapeutic effects on CAP with ARDS, and with AUCs of 0.866 and 0.795, respectively. Moreover, the ROC curve analysis revealed that combined characteristic serum and urine metabolites exhibited a better classification system for assessing therapeutic effects on CAP with ARDS, with a AUC value of 0.952. In addition, differential metabolites strongly correlated with clinical parameters in patients with CAP with ARDS.ConclusionsSerum- and urine-based metabolomics analyses identified characteristic metabolic alterations in CAP with ARDS and might provide promising circulatory markers for evaluating therapeutic effects on CAP with ARDS.

1H NMR-based metabolomics of skin squamous cell carcinoma and peri-tumoral region tissues

Squamous cell carcinomas (SCC) are the most frequent forms of skin malignancy. Knowledge of the metabolic changes occur in SCC and peri-tumoral region tissues is still limited. To investigate the metabolic changes in skin SCC and peri-tumoral regions, twenty-four patients with histopathology diagnosis of SCC were included in the study. Tissue samples were obtained from the SCCs, peri-tumoral regions (within 5 mm adjacent to the tumor margin) and distance normal tissues for control (> 5 mm adjacent to the tumor margin) from each patient. The metabolic changes of the three regions were investigated using 1H nuclear magnetic resonance-based metabolomics. Key metabolites in SCC were identified and validated by comparing with the other two regions. Eight metabolites were identified and validated between the SCCs and the controls, the concentrations of lactate, alanine, valine, creatine, aspartate, tyrosine, and glutamine significantly increased in SCC, while that of glucose decreased. The metabolomics analysis showed that lactate and valine were the key metabolites in SCCs and prei-tumoral regions. Pathways analysis showed that valine, leucine, and isoleucine biosynthesis, and pyruvate metabolism were the key abnormal metabolic pathways in SCC. Metabolomics analysis of key metabolites and pathways revealed that glycolysis, tricarboxylic acid (TCA) cycle, and amino acids metabolism played a central role in the metabolic of SCCs and peri-tumoral regions.

HPTLC-based metabolomics for the investigation of metabolic changes during plant development: The case study of Artemisia annua

The application of high performance thin layer chromatography (HPTLC)-based non-targeted metabolomics as a holistic approach to compare fingerprints of metabolite changes during Artemisia annua development is described. Images of HPTLC chromatograms obtained after derivatization with anisaldehyde-sulphuric acid reagent were used as a dataset for multivariate analysis. Principal component analysis and orthogonal partial least squares discriminant analysis confirmed the differentiation of samples belonging to vegetative phase, flowering stage, and seed formation stage of the plant development. The obtained results showed that the HPTLC-based metabolomics approach can be a very reliable technique for the investigation of metabolic changes during plant development, complementary to gas chromatography?mass spectrometry and nuclear magnetic resonance-based metabolomics.

Maternal inflammatory and omega-3 fatty acid pathways mediate the association between socioeconomic disadvantage and childhood cognition

Poor cognitive outcomes in early childhood predict poor educational outcomes and diminished health over the life course. We sought to investigate (i) whether maternal metabolites predict child cognition, and (ii) if maternal metabolomic profile mediates the relationship between environmental exposures and child cognition. Metabolites were measured using nuclear magnetic resonance-based metabolomics in pregnant women from a population-derived birth cohort. Child cognition was measured at age 2 years. In 662 mother–child pairs, elevated inflammatory markers (β = −2.62; 95% CI −4.10, −1.15; P = 0.0005) and lower omega-3 fatty acid-related metabolites (β = 0.49; 95% CI 0.09, 0.88; P = 0.02) in the mother were associated with lower child cognition and partially mediated the association between lower child cognition and multiple risk factors common to socioeconomic disadvantage. Modifying maternal prenatal metabolic pathways related to inflammation and omega-3 fatty acids may offset the adverse associations between prenatal risk factors related to socioeconomic disadvantage and low child cognition.