Nuclear Magnetic Resonance Metabonomics Research Articles

Screening of postoperative adjuvant chemotherapy-related serum metabolic markers in breast cancer patients based on 1H NMR metabonomics.

Breast cancer (BC) has the highest incidence rate among female malignant tumors. Adjuvant chemotherapy is commonly used to reduce micrometastasis in postoperative patients. However, monitoring the efficacy of chemotherapy in BC is a major challenge in clinical practice. In this study, 1H nuclear magnetic resonance (NMR) metabonomics was performed to explore the serum metabolic characteristics of BC patients before and after adjuvant chemotherapy. In this study, we collected serum samples from 51 healthy controls and 61 BC patients before and after chemotherapy for 1H NMR metabolomic analysis, and tested the performance of each metabolite and combination segment by the receiver operating characteristic (ROC) curves. Nine metabolites, namely glutamine, citrate, creatine, glycerophosphatidylcholine/phosphatidylcholine, glycine, 1-methylhistidine, lactate, pyruvate and formate had significant changes in BC patients before chemotherapy compared with healthy controls. Lactate, pyruvate, 1-methylhistidine and formate were found to be inversely regulated by chemotherapy. ROC analysis showed that a combination of the four metabolites had good prediction for chemotherapy efficacy with area under the curve of 0.958, sensitivity of 98.36% and specificity of 91.30%. There was no significant correlation between chemotherapy-related metabolites and clinical indicators of cancer patients, indicating that they can be used to evaluate the chemotherapy efficacy of patients with different clinical indicators. Effectively, dynamic and non-invasive metabolic markers for the evaluation of the efficacy of chemotherapy were identified in this study.

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.

Role of NMR metabonomics in Celiac Disease (CeD)

Metabonomics study provides a comprehensive metabolic profile of biological samples using techniques like mass spectroscopy and nuclear magnetic resonance (NMR) spectroscopy. The metabolites identified are later analysed using mul- tivariate statistical methods. Metabonomics has the potential to provide putative biomarker/s for disease diagnosis and for monitoring the disease progression and can be used in patient management. Recently, a few metabonomics studies have been reported on blood sera, urine and intestinal mucosal biopsies of celiac disease (CeD) patients using proton NMR. Significantly decreased levels of amino acids, methylamine, lactate, lipids, pyruvate, creatinine, choline and glycoprotein and increased levels of glucose and β-hydroxybutyrate have been reported in blood sera of CeD patients. In intestinal mucosal biopsies of CeD patients, a higher concentration of isoleucine, leucine, aspartate, succinate and pyruvate and lower concentration of glycerophosphocholine was seen as compared to controls. These studies indicates that the metabonomics study of CeD using in-vitro NMR spectroscopy helps in the determination of metabolic signature/s of the disease. It also provides an insight into the biochemistry of the disease and also helps in the identification of metabolites that could serve as putative biomarker/s for the diagnosis of CeD. This review focuses on the application of NMR based metabonomics in CeD and highlights the potential of NMR based metabonomics in the identification of biomarker/s for diagnosis and prognosis.

Urinary Metabolic Phenotyping Reveals Differences in the Metabolic Status of Healthy and Inflammatory Bowel Disease (IBD) Children in Relation to Growth and Disease Activity.

Background: Growth failure and delayed puberty are well known features of children and adolescents with inflammatory bowel disease (IBD), in addition to the chronic course of the disease. Urinary metabonomics was applied in order to better understand metabolic changes between healthy and IBD children. Methods: 21 Pediatric patients with IBD (mean age 14.8 years, 8 males) were enrolled from the Pediatric Gastroenterology Outpatient Clinic over two years. Clinical and biological data were collected at baseline, 6, and 12 months. 27 healthy children (mean age 12.9 years, 16 males) were assessed at baseline. Urine samples were collected at each visit and subjected to 1H Nuclear Magnetic Resonance (NMR) spectroscopy. Results: Using 1H NMR metabonomics, we determined that urine metabolic profiles of IBD children differ significantly from healthy controls. Metabolic differences include central energy metabolism, amino acid, and gut microbial metabolic pathways. The analysis described that combined urinary urea and phenylacetylglutamine—two readouts of nitrogen metabolism—may be relevant to monitor metabolic status in the course of disease. Conclusion: Non-invasive sampling of urine followed by metabonomic profiling can elucidate and monitor the metabolic status of children in relation to disease status. Further developments of omic-approaches in pediatric research might deliver novel nutritional and metabolic hypotheses.

NMR metabonomics of cerebrospinal fluid distinguishes between Parkinson’s disease and controls

This study assesses if nuclear magnetic resonance (NMR) metabonomics can discriminate between Parkinson’s disease (PD) patients and control subjects, and consequently identify metabolic markers for the disease. One-dimensional 1H NMR spectroscopy was used for quantitative analysis of metabolites in the cerebrospinal fluid (CSF) from 10 PD patients and 10 control individuals, together with uni- and multivariate statistical analysis to discriminate between the groups and to identify significantly altered metabolite concentrations. In total 60 metabolites were identified and of those 38 were quantified in all CSF samples. An overall lowering of metabolite content was observed in PD patients compared to control subjects (fold change of 0.85±0.30). Multivariate statistics reveal significant changes (ǀw*ǀ>0.2) among nine metabolites (alanine, creatinine, dimethylamine, glucose, lactate, mannose, phenylalanine, 3-hydroxyisobutyric acid and 3-hydroxyisovaleric acid). Three of these (alanine, creatinine and mannose) are identified as significantly changed also by univariate statistics (p<0.00132, Bonferroni corrected). Panels with all or a selected set of these metabolites were successfully used for discriminating between the two groups. In conclusion, NMR metabonomics can readily determine metabolite concentrations in CSF, identify putative biomarkers that distinguish between the PD patients and control subjects, and thus potentially become a tool for diagnostic purposes.

Following Healthy Pregnancy by Nuclear Magnetic Resonance (NMR) Metabolic Profiling of Human Urine

In this work, untargeted NMR metabonomics was employed to evaluate the effects of pregnancy on the metabolite composition of maternal urine, thus establishing a control excretory trajectory for healthy pregnancies. Urine was collected for independent groups of healthy nonpregnant and pregnant women (in first, second, third trimesters) and multivariate analysis performed on the corresponding NMR spectra. Models were validated through Monte Carlo Cross Validation and permutation tests and metabolite correlations measured through Statistical Total Correlation Spectroscopy. The levels of 21 metabolites were found to change significantly throughout pregnancy, with variations observed for the first time to our knowledge for choline, creatinine, 4-deoxyerythronic acid, 4-deoxythreonic acid, furoylglycine, guanidoacetate, 3-hydroxybutyrate, and lactate. Results confirmed increased aminoaciduria across pregnancy and suggested (a) a particular involvement of isoleucine and threonine in lipid oxidation/ketone body synthesis, (b) a relation of excreted choline, taurine, and guanidoacetate to methionine metabolism and urea cycle regulation, and (c) a possible relationship of furoylglycine and creatinine to pregnancy, based on a tandem study of nonfasting confounding effects. Results demonstrate the usefulness of untargeted metabonomics in finding biomarker metabolic signatures for healthy pregnancies, against which disease-related deviations may be confronted in future studies, as a base for improved diagnostics and prediction.

The Cardiovascular Risk of Healthy Individuals Studied by NMR Metabonomics of Plasma Samples

The identification and the present wide acceptance of cardiovascular risk factors such as age, sex, hypertension, hyperlipidemia, smoking, obesity, diabetes, and physical inactivity have led to dramatic reductions in cardiovascular morbidity and mortality. However, novel risk predictors present opportunities to identify more patients at risk and to more accurately define the biochemical signature of that risk. In this paper, we present a comprehensive metabonomic analysis of 864 plasma samples from healthy volunteers, through Nuclear Magnetic Resonance (NMR) and multivariate statistical analysis (regression and classification). We have found that subjects that are classified as at high or at low risk using the common clinical markers can also be discriminated using NMR metabonomics. This discrimination is not only due to common markers (such as total cholesterol, triglycerides, LDL, HDL), but also to (p < 0.05 after Bonferroni correction) other metabolites (e.g., 3-hydroxybutyrate, α-ketoglutarate, threonine, dimethylglycine) previously not associated with cardiovascular diseases.

Clinical and Epidemiological Metabonomics

Metabonomics is an omics approach to identify and monitor metabolic characteristics, changes, and phenotypes with respect to various synergetic factors such as environment, life style, diet, and potential pathophysiological processes. Recently, metabonomics has also opened up a possibility for functional genomics in large genome-wide studies. Mass spectrometry (MS) and proton nuclear magnetic resonance (NMR) spectroscopy are the two key experimental technologies in the field. Recent advancements are numerous, and methodologies currently exist that allow for automated high-throughput experimentation in a very cost-effective manner. Technical developments have evoked an increasing number of metabonomics applications in clinical and epidemiological disciplines to understand the complex molecular foundations of various diseases. Techniques with the aim of assessing large numbers of metabolites that are substrates, intermediates, or products in various metabolic pathways are particularly relevant in the risk assessment of metabolic conditions like diabetes and vascular diseases. It has also been envisioned that metabonomics approaches may overtake standard analytical measurements of individual metabolites and eventually lead to holistic multimetabolic risk phenotyping in the early detection of high-risk individuals for various metabolic diseases. Thus, metabonomics offers potential means to move away from single biomarkers and thresholds in clinical medicine. And, furthermore, even though the current medical biomarkers and thresholds are necessary benchmarks for clinical practice, it will be crucial to let the future diagnostics to follow from new science. Good predictions are necessary for effective prevention; an important step towards this is expected to happen when complex traits will not anymore be limited by clinical diagnoses and definitions but will be handled as multivariate continuous dimensions. Consequently, clinical and epidemiological metabonomics is likely to be one of the key new omics areas to assist translational research in the near future. Here, the Journal of Biomedicine and Biotechnology presents this special issue, 2011. Although only representing a small fraction of the contribution of metabonomics to various biomedical disciplines, the papers presented here show the increasing potential of metabonomics approaches to complement clinical and epidemiological research. To start the special issue, we have five contributions that review several aspects of metabonomics research. M. G. Barderas et al. discuss the concepts of metabolic profiling, fingerprinting, and footprinting focusing on the area of cardiovascular diseases. E. Silvestri and coworkers discuss the timely and relevant issue of integrative analyses of related omics data sets in order to furnish new insights not accessible through one-dimensional data. Further, I. Kouskoumvekaki and G. Panagiotou give an extensive up-to-date overview on the database resources on metabolic pathways and metabolomes and also summarize the statistical tools often used for the analysis of metabonomics data. Y. Kim and S. Milner deal with the challenges related to bioactive food components in cancer research and prevention. Moreover, M. Sofia and coauthors review the potential use of exhaled breath condensate as a suitable matrix for NMR-based metabonomics of airway diseases. This special issue contains two methodology reports. G. Kastenmuller and coworkers have developed a freely accessible methodology to facilitate automated and standardized analysis for quantitative metabolic data, covering the steps from data acquisition to biological interpretation. M. C. Martinez-Bisbal and colleagues, using magnetic resonance microscopy, present a critical and valuable interpretation on the high-resolution magic angle spinning data of human tumor tissues. The six original research papers in this special issue start with the paper by J. Willmann et al. who demonstrate the advantage of combining high-pressure liquid chromatography, MS, and NMR spectroscopy in analyzing three different types of extracts of a common membrane component phosphatidylcholine. Then, D. F. Brougham et al. focus on the use of artificial neural networks in classifying proton NMR spectroscopic data recorded on whole-cell culture samples of four different lung carcinoma cell lines, displaying different drug-resistance patterns. In a mouse study, D. Otter et al. apply MS-based nontargeted urinary metabolite profiling to identify biomarkers of colon inflammation. In another mouse study, J. Zhou et al. provide evidence that NMR metabonomics may be sensitive enough to detect small differences in the composition of maternal plasma and thus be helpful for identifying biomarkers of birth defects. Additionally, in low-birth weight and high-birth weight piglets P. M. Nissen and coworkers combine NMR and MS to reveal a relationship between birth weight and plasma inositols, suggesting their potential role in fetal programming of type 2 diabetes. L. Guo et al. end this special issue in providing the latest epidemiologic information on the etiology distribution of neurodevelopmental disabilities in Chinese, and by demonstrating, on the basis of 8-year clinical experience, that MS-based pediatric metabonomics is clinically helpful. Overall, we hope that this special issue hints at the rising potential of metabonomics approaches in clinical and epidemiological research and translational medicine. Mika Ala-Korpela Veikko Salomaa Olav M. Kvalheim

Understanding subfertility at a molecular level in the female through the application of nuclear magnetic resonance (NMR) spectroscopy

Understanding the aetiology of subfertility and female reproductive tract disorders at a molecular level may improve success rates in fertility treatment. Such understanding may be gained by the application of metabonomics technologies to tissues or biofluids. Metabonomics is concerned with the quantification of molecules in the metabolome and uses nuclear magnetic resonance (NMR) spectroscopy as one of the main technological platforms. This review concentrates on NMR studies of the female reproductive tract and discusses further possible applications. While full metabolic profiling is relatively recent, targeted NMR studies of biofluid and tissue has a longer history. Searches were carried out on MEDLINE(®), PubMed, SciFinder(®) Scholar 2007 and ISI Web of Knowledge(SM) for papers about NMR spectroscopy or metabonomics of the female reproductive tract and subfertility. NMR spectroscopy has been employed for the compositional analysis of various elements of the female reproductive tract, including cervical mucus, follicular fluid (FF), ovarian tissue, fallopian tubes and uterine matter. NMR was used to document for the first time a change in FF lipoprotein concentration during follicular development. NMR analysis of granulosa cells from rats has revealed that follicle-stimulating hormone increases the activity of the pentose pathway, having crucial implications for ovarian stimulation regimens. In the uterine matter work, it has been shown by NMR that glycolysis is rapidly stimulated by estrogen, and in another study, citrate in uterine fluid was found as a potential biomarker for adenomyosis. NMR has also been used to show that chlamydiae are able to achieve higher energy reserves by stimulating glucose transport in host cells. A range of NMR spectroscopic techniques have been applied to the analysis of the female reproductive tract, however great potential remains for further studies. Incorporation of metabonomics techniques into female fertility research may be valuable for understanding subfertility and predicting outcomes of assisted conception treatments.

BAS/BSCR47 Quantitative metabolic profiling of subclinical atherosclerosis by serum NMR metabonomics

ObjectiveTo determine associations of systemic metabolites with subclinical atherosclerosis.Methods4407 serum samples were measured by nuclear magnetic resonance (NMR) spectroscopy from the Cardiovascular Risk in Young Finns Study, and carotid intima-media...

High-throughput serum NMR metabonomics for cost-effective holistic studies on systemic metabolism

A high-throughput proton (1H) nuclear magnetic resonance (NMR) metabonomics approach is introduced to characterise systemic metabolic phenotypes. The methodology combines two molecular windows that contain the majority of the metabolic information available by 1H NMR from native serum, e.g. serum lipids, lipoprotein subclasses as well as various low-molecular-weight metabolites. The experimentation is robotics-controlled and fully automated with a capacity of about 150-180 samples in 24 h. To the best of our knowledge, the presented set-up is unique in the sense of experimental high-throughput, cost-effectiveness, and automated multi-metabolic data analyses. As an example, we demonstrate that the NMR data as such reveal associations between systemic metabolic phenotypes and the metabolic syndrome (n = 4407). The high-throughput of up to 50,000 serum samples per year is also paving the way for this technology in large-scale clinical and epidemiological studies. In contradiction to single 'biomarkers', the application of this holistic NMR approach and the integrated computational methods provides a data-driven systems biology approach to biomedical research.