NMR-based metabonomic approaches for evaluating physiological influences on biofluid composition

Technological advances in current metabolomics and its application in tradition Chinese medicine

During the last few years, many metabolomics technologies have been established in biomedical research for analyzing the changes of metabolite levels.

NMR and MS Methods for Metabolomics

Metabolomics, also often referred as "metabolic profiling," is the systematic profiling of metabolites in biofluids or tissues of organisms and their temporal changes. In the last decade, metabolomics has become more and more popular in drug development, molecular medicine, and other biotechnology fields, since it profiles directly the phenotype and changes thereof in contrast to other "-omics" technologies. The increasing popularity of metabolomics has been possible only due to the enormous development in the technology and bioinformatics fields. In particular, the analytical technologies supporting metabolomics, i.e., NMR, UPLC-MS, and GC-MS, have evolved into sensitive and highly reproducible platforms allowing the determination of hundreds of metabolites in parallel. This chapter describes the best practices of metabolomics as seen today. All important steps of metabolic profiling in drug development and molecular medicine are described in great detail, starting from sample preparation to determining the measurement details of all analytical platforms, and finally to discussing the corresponding specific steps of data analysis.

What success can teach us about failure: the plasma metabolome of older adults with superior memory and lessons for Alzheimer's disease

As the world population ages, primary prevention of age-related cognitive decline and disability will become increasingly important. Prevention strategies are often developed from an understanding of disease pathobiology, but models of biological success may provide additional useful insights. Here, we studied 224 older adults, some with superior memory performance (n = 41), some with normal memory performance (n = 109), and some with mild cognitive impairment or Alzheimer's disease (AD; n = 74) to understand metabolomic differences which might inform future interventions to promote cognitive health. Plasma metabolomics revealed significant differential abundance of 12 metabolites in those with superior memory relative to controls (receiver operating characteristic area under the curve [AUC] = 0.89) and the inverse abundance pattern in the mild cognitive impairment, AD (AUC = 1.0) and even preclinical AD groups relative to controls (AUC = 0.97). The 12 metabolites are components of key metabolic pathways regulating oxidative stress, inflammation, and nitric oxide bioavailability. These findings from opposite ends of the cognitive continuum highlight the role of these pathways in superior memory abilities and whose failure may contribute to age-related memory impairment. These pathways may be targeted to promote successful cognitive aging.

Metabolomic analysis of urine with Nuclear Magnetic Resonance spectroscopy in patients with idiopathic sudden sensorineural hearing loss: A preliminary study

OBJECTIVE

Idiopathic sudden sensorineural hearing loss is a frequent emergency, with unknown aetiology and usually treated with empiric therapy. Steroids represent the only validated treatment but prognosis is unpredictable and the possibility to select the patients who will not respond to steroids could avoid unnecessary treatments. Metabolomic profiling of the biofluids target the analysis of the final product of genic expression and enzymatic activity, defining the biochemical phenotype of a whole biologic system.

METHODS

We studied the metabolomics of the urine of a cohort of patients with idiopathic sudden sensorineural hearing loss, correlating the metabolic profiles with the clinical outcomes. Metabolomic profiling of urine samples was performed by ¹H Nuclear Magnetic Resonance spectroscopy in combination with multivariate statistical approaches.

RESULTS

26 patients were included in the study: 5 healthy controls, 13 patients who did not recover after treatment at 6 months while the remaining 8 patients recovered from the hearing loss. The orthogonal partial least square-discriminant analysis score plot showed a significant separation between the two groups, responders and non-responders after steroid therapy, R²Y of 0.83, Q² of 0.38 and p value <0.05. The resulting metabolic profiles were characterized by higher levels of urinary B-Alanine, 3-hydroxybutyrate and Trimethylamine N-oxide, and lower levels of Citrate and Creatinine in patients with worst outcome.

CONCLUSION

Idiopathic sudden sensorineural hearing loss is a specific disease with unclear systemic changes, but our data suggest that there are different types of this disorder or patients predisposed to effective action of steroids allowing the recover after treatment.

Sample preparation optimization in fecal metabolic profiling

Metabolomic analysis of feces can provide useful insight on the metabolic status, the health/disease state of the human/animal and the symbiosis with the gut microbiome. As a result, recently there is increased interest on the application of holistic analysis of feces for biomarker discovery. For metabolomics applications, the sample preparation process used prior to the analysis of fecal samples is of high importance, as it greatly affects the obtained metabolic profile, especially since feces, as matrix are diversifying in their physicochemical characteristics and molecular content. However there is still little information in the literature and lack of a universal approach on sample treatment for fecal metabolic profiling. The scope of the present work was to study the conditions for sample preparation of rat feces with the ultimate goal of the acquisition of comprehensive metabolic profiles either untargeted by NMR spectroscopy and GC-MS or targeted by HILIC-MS/MS. A fecal sample pooled from male and female Wistar rats was extracted under various conditions by modifying the pH value, the nature of the organic solvent and the sample weight to solvent volume ratio. It was found that the 1/2 (w_f/v_s) ratio provided the highest number of metabolites under neutral and basic conditions in both untargeted profiling techniques. Concerning LC-MS profiles, neutral acetonitrile and propanol provided higher signals and wide metabolite coverage, though extraction efficiency is metabolite dependent.

Metabolomics as a Challenging Approach for Medicinal Chemistry and Personalized Medicine

"Omics" sciences have been developed to provide a holistic point of view of biology and to better understand the complexity of an organism as a whole. These systems biology approaches can be examined at different levels, starting from the most fundamental, i.e., the genome, and finishing with the most functional, i.e., the metabolome. Similar to how genomics is applied to the exploration of DNA, metabolomics is the qualitative and quantitative study of metabolites. This emerging field is clearly linked to genomics, transcriptomics, and proteomics. In addition, metabolomics provides a unique and direct vision of the functional outcome of an organism's activities that are required for it to survive, grow, and respond to internal and external stimuli or stress, e.g., pathologies and drugs. The links between metabolic changes, patient phenotype, physiological and/or pathological status, and treatment are now well established and have opened a new area for the application of metabolomics in the drug discovery process and in personalized medicine.

An Evidence-Based Review of Related Metabolites and Metabolic Network Research on Cerebral Ischemia

In recent years, metabolomics analyses have been widely applied to cerebral ischemia research. This paper introduces the latest proceedings of metabolomics research on cerebral ischemia. The main techniques, models, animals, and biomarkers of cerebral ischemia will be discussed. With analysis help from the MBRole website and the KEGG database, the altered metabolites in rat cerebral ischemia were used for metabolic pathway enrichment analyses. Our results identify the main metabolic pathways that are related to cerebral ischemia and further construct a metabolic network. These results will provide useful information for elucidating the pathogenesis of cerebral ischemia, as well as the discovery of cerebral ischemia biomarkers.

1H NMR-based metabolomics study on the physiological variations during the rat pregnancy process

In this study, NMR-based metabolomics in combination with multivariate pattern recognition technologies were employed to evaluate the physiological variations in the Wistar rats' plasma that are induced by pregnancy on the gestational days (GDs) 11, 14, 17 and 20. Untargeted metabolomics analysis revealed some possible mechanism of physiological effects for healthy pregnancies and showed a metabolic trajectory during pregnancy process. The levels of 24 metabolites were found to change significantly throughout pregnancy in maternal plasma. These metabolite changes involved in varied kinds of metabolic pathways including synthesis of biological substances, microbial metabolism in diverse environments, protein digestion and absorption, carbohydrate metabolism, digestion and absorption, mineral absorption, and ATP (Adenosine Triphosphate)-binding cassette transporters (ABC transporters). The substantial cores of all the metabolic pathways are promoting fetal growth and development and regulating maternal physiological state. This work showed relevant metabolic pathways perturbation in the maternal plasma due to normal pregnancy and provided the physical basis of time-dependent metabolic trajectory against which disease-related maternal physiological responses may be better understood in future studies.

The Healthy Core Metabolism: A New Paradigm for Primary Preventive Nutrition

Research in preventive nutrition aims at elucidating mechanism by which our diet helps us to remain in good health through optimal physiological functions. However, despite decades of accumulated data in human nutrition and regular subsequent nutritional recommendations, obesity and type 2 diabetes epidemics continue to progress worldwide each year leading to a regular decrease of the Healthy Life Years, notably in Western countries. Such a paradox may be explained by the Nutrition Transition, the extreme application of the reductionist paradigm in nutrition research, the lack of nutritional education and a too strong focus on curative nutrition in at risk/ill subjects. In this position paper, we hypothesized that researchers should focus more on healthy subjects, from birth until maturity. Rather than exploring what differentiates healthy and at risk/ill subjects, we propose to thoroughly study what characterizes a healthy state and its underlying metabolism. We define it as the Healthy Core Metabolism which remains stable whatever energy inputs (diets) and outputs (exercise), genetic background and external/internal stress, e.g., temporary illnesses. As a basis for Healthy Core Metabolism investigation, we observed that main physiological and ubiquitous functions of human organism, i.e., the neuro-vasculo-sarco-osteoporotic system, tend to follow a concave curve with common phases of growth, optimum, and decline. Finally, we hypothesized that true primary preventive nutrition should focus on the growth phase to reach the maximum capital of a given physiological function so that - whatever the further decline -, Healthy Life Years may approach or coincide with theoretical Life Expectancy.

Exploratory urinary metabolomics of type 1 leprosy reactions

BACKGROUND

Leprosy is an infectious disease caused by Mycobacterium leprae that affects the skin and nerves. Although curable with multidrug therapy, leprosy is complicated by acute inflammatory episodes called reactions, which are the major causes of irreversible neuropathy in leprosy that occur before, during, and even after treatment. Early diagnosis and prompt treatment of reactions reduces the risk of permanent disability.

METHODS

This exploratory study investigated whether urinary metabolic profiles could be identified that correlate with early signs of reversal reactions (RR). A prospective cohort of leprosy patients with and without reactions and endemic controls was recruited in Nepal. Urine-derived metabolic profiles were measured longitudinally. Thus, a conventional area of biomarker identification for leprosy was extended to non-invasive urine testing.

RESULTS

It was found that the urinary metabolome could be used to discriminate endemic controls from untreated patients with mycobacterial disease. Moreover, metabolic signatures in the urine of patients developing RR were clearly different before RR onset compared to those at RR diagnosis.

CONCLUSIONS

This study indicates that urinary metabolic profiles are promising host biomarkers for the detection of intra-individual changes during acute inflammation in leprosy and could contribute to early treatment and prevention of tissue damage.

Serum Metabolite Profiles Are Altered by Erlotinib Treatment and the Integrin α1-Null Genotype but Not by Post-Traumatic Osteoarthritis

The risk of developing post-traumatic osteoarthritis (PTOA) following joint injury is high. Furthering our understanding of the molecular mechanisms underlying PTOA and/or identifying novel biomarkers for early detection may help to improve treatment outcomes. Increased expression of integrin α1β1 and inhibition of epidermal growth factor receptor (EGFR) signaling protect the knee from spontaneous OA; however, the impact of the integrin α1β1/EGFR axis on PTOA is currently unknown. We sought to determine metabolic changes in serum samples collected from wild-type and integrin α1-null mice that underwent surgery to destabilize the medial meniscus and were treated with the EGFR inhibitor erlotinib. Following (1)H nuclear magnetic resonance spectroscopy, we generated multivariate statistical models that distinguished between the metabolic profiles of erlotinib- versus vehicle-treated mice and the integrin α1-null versus wild-type mouse genotype. Our results show the sex-dependent effects of erlotinib treatment and highlight glutamine as a metabolite that counteracts this treatment. Furthermore, we identified a set of metabolites associated with increased reactive oxygen species production, susceptibility to OA, and regulation of TRP channels in α1-null mice. Our study indicates that systemic pharmacological and genetic factors have a greater effect on serum metabolic profiles than site-specific factors such as surgery.

Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis

NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment.

Revealing Potential Biomarkers of Functional Dyspepsia by Combining 1H NMR Metabonomics Techniques and an Integrative Multi-objective Optimization Method

Metabonomics methods have gradually become important auxiliary tools for screening disease biomarkers. However, recognition of metabolites or potential biomarkers closely related to either particular clinical symptoms or prognosis has been difficult. The current study aims to identify potential biomarkers of functional dyspepsia (FD) by a new strategy that combined hydrogen nuclear magnetic resonance (¹H NMR)-based metabonomics techniques and an integrative multi-objective optimization (LPIMO) method. First, clinical symptoms of FD were evaluated using the Nepean Dyspepsia Index (NDI), and plasma metabolic profiles were measured by ¹H NMR. Correlations between the key metabolites and the NDI scores were calculated. Then, LPIMO was developed to identify a multi-biomarker panel by maximizing diagnostic ability and correlation with the NDI score. Finally, a KEGG database search elicited the metabolic pathways in which the potential biomarkers are involved. The results showed that glutamine, alanine, proline, HDL, β-glucose, α-glucose and LDL/VLDL levels were significantly altered in FD patients. Among them, phosphatidycholine (PtdCho) and leucine/isoleucine (Leu/Ile) were positively and negatively correlated with the NDI Symptom Index (NDSI) respectively. Our procedure not only significantly improved the credibility of the biomarkers, but also demonstrated the potential of further explorations and applications to diagnosis and treatment of complex disease.

Progressive Changes in the Plasma Metabolome during Malnutrition in Juvenile Pigs

Severe acute malnutrition (SAM) is one of the leading nutrition-related causes of death in children under five years of age. The clinical features of SAM are well documented, but a comprehensive understanding of the development from a normal physiological state to SAM is lacking. Characterizing the temporal metabolomic change may help to understand the disease progression and to define nutritional rehabilitation strategies. Using a piglet model we hypothesized that a progressing degree of malnutrition induces marked plasma metabolite changes. Four-week-old weaned pigs were fed a nutrient-deficient maize diet (MAL) or nutritionally optimized reference diet (REF) for 7 weeks. Plasma collected weekly was subjected to LC-MS for a nontargeted profiling of metabolites with abundance differentiation. The MAL pigs showed markedly reduced body-weight gain and lean-mass proportion relative to the REF pigs. Levels of eight essential and four nonessential amino acids showed a time-dependent deviation in the MAL pigs from that in the REF. Choline metabolites and gut microbiomic metabolites generally showed higher abundance in the MAL pigs. The results demonstrated that young malnourished pigs had a profoundly perturbed metabolism, and this provides basic knowledge about metabolic changes during malnourishment, which may be of help in designing targeted therapeutic foods for refeeding malnourished children.

Zebrafish as a Model for Systems Medicine R&D: Rethinking the Metabolic Effects of Carrier Solvents and Culture Buffers Determined by (1)H NMR Metabolomics

Zebrafish is a frequently employed model organism in systems medicine and biomarker discovery. A crosscutting fundamental question, and one that has been overlooked in the field, is the "system-wide" (omics) effects induced in zebrafish by metabolic solvents and culture buffers. Indeed, any bioactivity or toxicity test requires that the target compounds are dissolved in an appropriate nonpolar solvent or aqueous media. It is important to know whether the solvent or the buffer itself has an effect on the zebrafish model organism. We evaluated the effects of two organic carrier solvents used in research with zebrafish, as well as in drug screening: dimethyl sulfoxide (DMSO) and ethanol, and two commonly used aqueous buffers (egg water and Hank's balanced salt solution). The effects of three concentrations (0.01, 0.1, and 1%) of DMSO and ethanol were tested in the 5-day-old zebrafish embryo using proton nuclear magnetic resonance ((1)H NMR) based metabolomics. DMSO (1% and 0.1%, but not 0.01%) exposure significantly decreased the levels of adenosine triphosphate (ATP), betaine, alanine, histidine, lactate, acetate, and creatine (p < 0.05). By contrast, ethanol exposure did not alter the embryos' metabolome at any concentration tested. The two different aqueous media noted above impacted the zebrafish embryo metabolome as evidenced by changes in valine, alanine, lactate, acetate, betaine, glycine, glutamate, adenosine triphosphate, and histidine. These results show that DMSO has greater effects on the embryo metabolome than ethanol, and thus is used with caution as a carrier solvent in zebrafish biomarker research and oral medicine. Moreover, the DMSO concentration should not be higher than 0.01%. Careful attention is also warranted for the use of the buffers egg water and Hank's balanced salt solution in zebrafish. In conclusion, as zebrafish is widely used as a model organism in life sciences, metabolome changes induced by solvents and culture buffers warrant further attention for robust systems science, and precision biomarkers that will stand the test of time.

NMR-Based Metabolic Snapshot from Minibronchoalveolar Lavage Fluid: An Approach To Unfold Human Respiratory Metabolomics

The utility of mini bronchoalveolar lavage (mBAL) and its applicability in metabolomics has not been explored in the field of human respiratory disease. mBAL, "an archetype" of the local lung environment, ensures a potent technique to get the snapshot of the epithelial lining fluid afflicted to human lung disorders. Characterization of the mBAL fluid has potential to help in elucidating the composition of the alveoli and airways in the diseased state, yielding diagnostic information on clinical applicability. In this study, one of the first attempts has been made to comprehensively assign and detect metabolites in mBAL fluid, extracted from human lungs, by the composite use of 800 MHz 1D and 2D NMR, J-resolved homonuclear spectroscopy, COSY, TOCSY, and heteronuclear HSQC correlation methods. A foremost all-inclusive sketch of the 50 metabolites has been corroborated and assigned, which can be a resourceful archive to further lung-directed metabolomics, prognosis, and diagnosis. Thus, NMR-based mBALF studies, as proposed in this article, will leverage many more prospective respiratory researches for routine clinical application and prove to be a viable approach to mirror the key predisposing factors contributing to the onset of lung disease.

Nuclear Magnetic Resonance (NMR) Spectroscopy For Metabolic Profiling of Medicinal Plants and Their Products

NMR spectroscopy has multidisciplinary applications, including excellent impact in metabolomics. The analytical capacity of NMR spectroscopy provides information for easy qualitative and quantitative assessment of both endogenous and exogenous metabolites present in biological samples. The complexity of a particular metabolite and its contribution in a biological system are critically important for understanding the functional state that governs the organism's phenotypes. This review covers historical aspects of developments in the NMR field, its applications in chemical profiling, metabolomics, and quality control of plants and their derived medicines, foods, and other products. The bottlenecks of NMR in metabolic profiling are also discussed, keeping in view the future scope and further technological interventions.

High-Resolution (1)H NMR Spectroscopy Discriminates Amniotic Fluid of Fetuses with Congenital Diaphragmatic Hernia from Healthy Controls

Lung hypoplasia in congenital diaphragmatic hernia (CDH) is a life-threatening birth defect. Severe cases can be offered tracheal occlusion to boost prenatal lung development, although defining those to benefit remains challenging. Metabonomics of (1)H NMR spectra collected from amniotic fluid (AF) can identify general changes in diseased versus healthy fetuses. AF embodies lung secretions and hence might contain pulmonary next to general markers of disease in CDH fetuses. AF from 81 healthy and 22 CDH fetuses was collected. NMR spectroscopy was performed at 400 MHz to compare AF from fetuses with CDH against controls. Several advanced feature extraction methods based on statistical tests that explore spectral variability, similarity, and dissimilarity were applied and compared. This resulted in the identification of 30 spectral regions, which accounted for 80% variability between CDH and controls. Combination with automated classification discriminates AF from CDH versus healthy fetuses with up to 92% accuracy. Within the identified spectral regions, isoleucine, leucine, valine, pyruvate, GABA, glutamate, glutamine, citrate, creatine, creatinine, taurine, and glucose were the most concentrated metabolites. As the metabolite pattern of AF changes with fetal development, we have excluded metabolites with a high age-related variability and repeated the analysis with 12 spectral regions, which has resulted in similar classification accuracy. From this analysis, it was possible to distinguish between AF from CDH fetuses versus healthy controls independent of gestational age.

Systems analysis of host-parasite interactions

Parasitic diseases caused by protozoan pathogens lead to hundreds of thousands of deaths per year in addition to substantial suffering and socioeconomic decline for millions of people worldwide. The lack of effective vaccines coupled with the widespread emergence of drug‐resistant parasites necessitates that the research community take an active role in understanding host–parasite infection biology in order to develop improved therapeutics. Recent advances in next‐generation sequencing and the rapid development of publicly accessible genomic databases for many human pathogens have facilitated the application of systems biology to the study of host–parasite interactions. Over the past decade, these technologies have led to the discovery of many important biological processes governing parasitic disease. The integration and interpretation of high‐throughput ‐omic data will undoubtedly generate extraordinary insight into host–parasite interaction networks essential to navigate the intricacies of these complex systems. As systems analysis continues to build the foundation for our understanding of host–parasite biology, this will provide the framework necessary to drive drug discovery research forward and accelerate the development of new antiparasitic therapies. WIREs Syst Biol Med 2015, 7:381–400. doi: 10.1002/wsbm.1311

For further resources related to this article, please visit the WIREs website.

Combined 1H-NMR and 1H-13C HSQC-NMR to improve urinary screening in autism spectrum disorders

Autism spectrum disorders (ASD) are neurodevelopmental diseases with complex genetic and environmental etiological factors. Although genetic causes play a significant part in the etiology of ASD, metabolic disturbances may also play a causal role or modulate the clinical features of ASD. The number of ASD studies involving metabolomics is increasing, and sometime with conflicting findings. We assessed the metabolomics profiling of urine samples to determine a comprehensive biochemical signature of ASD. Furthermore, to date no study has combined metabolic profiles obtained from different analytical techniques to distinguish patient with ASD from healthy individuals. We obtained (1)H-NMR spectra and 2D (1)H-(13)C HSQC NMR spectra from urine samples of patients with ASD or healthy controls. We analyzed these spectra by multivariate statistical data analysis. The OPLS-DA model obtained from (1)H NMR spectra showed a good discrimination between ASD samples and non-ASD samples (R(2)Y(cum) = 0.70 and Q(2) = 0.51). Combining the (1)H NMR spectra and the 2D (1)H-(13)C HSQC NMR spectra increased the overall quality and predictive value of the OPLS-DA model (R(2)Y(cum) = 0.84 and Q(2) = 0.71), leading to a better sensitivity and specificity. Urinary excretion of succinate, glutamate and 3-methyl-histidine differed significantly between ASD and non-ASD samples. Urinary screening of children with neurodevelopmental disorders by combining NMR spectroscopies (1D and 2D) in multivariate analysis is a better sensitive and a straightforward method that could help the diagnosis ASD.

Application of 1H NMR spectroscopy-based metabonomics to feces of cervical cancer patients with radiation-induced acute intestinal symptoms

OBJECTIVE

Radiation-induced acute intestinal symptoms (RIAISs) are a common complication of radiotherapy for cervical cancer. The aim of this study was to use (1)H nuclear magnetic resonance ((1)H NMR) combined with chemometric analysis to develop a metabolic profile of patients with RIAISs.

METHODS

Fecal samples were collected from 66 patients with cervical cancer before and after pelvic radiotherapy. After radiotherapy, RIAISs occurred in eleven patients. We selected another 11 patients from participants without RIAISs whose age, stage, histological type and treatment methods are matched with RIAIS patients as the control group. (1)H NMR spectroscopy combined with multivariate pattern recognition analysis was used to generate metabolic profile data, as well as to establish a RIAIS-specific metabolic phenotype.

RESULTS

Orthogonal partial least-squares discriminant analysis was used to distinguish samples between the pre- and post-radiotherapy RIAIS patients and between RIAIS patients and controls. Fecal samples from RIAIS patients after pelvic radiotherapy were characterized by increased concentrations of α-ketobutyrate, valine, uracil, tyrosine, trimethylamine N-oxide, phenylalanine, lysine, isoleucine, glutamine, creatinine, creatine, bile acids, aminohippurate, and alanine, accompanied by reduced concentrations of α-glucose, n-butyrate, methylamine, and ethanol relative to samples from RIAIS patients before pelvic radiotherapy, while in RIAIS patients relative to controls, trimethylamine, n-butyrate, fumarate and acetate were down-regulated and valine, TMAO, taurine, phenylalanine, lactate, isoleucine and creatinine were up-regulated.

CONCLUSIONS

We obtained the metabolic profile of RIAIS patients from fecal samples using NMR-based metabonomics. This profile has the potential to be developed into a novel clinical tool for RIAIS diagnosis or therapeutic monitoring, and could contribute to an improved understanding of the disease mechanism. However, because of the limitations of methods, technique, bacterial contamination of feces and small sample size, further research and verification are needed.

Analysis of the Human Adult Urinary Metabolome Variations with Age, Body Mass Index, and Gender by Implementing a Comprehensive Workflow for Univariate and OPLS Statistical Analyses

Urine metabolomics is widely used for biomarker research in the fields of medicine and toxicology. As a consequence, characterization of the variations of the urine metabolome under basal conditions becomes critical in order to avoid confounding effects in cohort studies. Such physiological information is however very scarce in the literature and in metabolomics databases so far. Here we studied the influence of age, body mass index (BMI), and gender on metabolite concentrations in a large cohort of 183 adults by using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). We implemented a comprehensive statistical workflow for univariate hypothesis testing and modeling by orthogonal partial least-squares (OPLS), which we made available to the metabolomics community within the online Workflow4Metabolomics.org resource. We found 108 urine metabolites displaying concentration variations with either age, BMI, or gender, by integrating the results from univariate p-values and multivariate variable importance in projection (VIP). Several metabolite clusters were further evidenced by correlation analysis, and they allowed stratification of the cohort. In conclusion, our study highlights the impact of gender and age on the urinary metabolome, and thus it indicates that these factors should be taken into account for the design of metabolomics studies.

A Metabolomic Approach to Understanding the Metabolic Link between Obesity and Diabetes

Obesity and diabetes arise from an intricate interplay between both genetic and environmental factors. It is well recognized that obesity plays an important role in the development of insulin resistance and diabetes. Yet, the exact mechanism of the connection between obesity and diabetes is still not completely understood. Metabolomics is an analytical approach that aims to detect and quantify small metabolites. Recently, there has been an increased interest in the application of metabolomics to the identification of disease biomarkers, with a number of well-known biomarkers identified. Metabolomics is a potent approach to unravel the intricate relationships between metabolism, obesity and progression to diabetes and, at the same time, has potential as a clinical tool for risk evaluation and monitoring of disease. Moreover, metabolomics applications have revealed alterations in the levels of metabolites related to obesity-associated diabetes. This review focuses on the part that metabolomics has played in elucidating the roles of metabolites in the regulation of systemic metabolism relevant to obesity and diabetes. It also explains the possible metabolic relation and association between the two diseases. The metabolites with altered profiles in individual disorders and those that are specifically and similarly altered in both disorders are classified, categorized and summarized.

Metabolite Signatures in Hydrophilic Extracts of Mouse Lungs Exposed to Cigarette Smoke Revealed by 1H NMR Metabolomics Investigation

¹H-NMR metabolomics was used to investigate the changes of metabolites in the lungs of mice with and without being exposed to a controlled amount of cigarette smoke. It was found that the concentrations of adenosine derivatives (i.e. ATP, ADP and AMP), inosine and uridine were significantly changed in the lungs of mice exposed to cigarette smoke when compared with controls regardless the mice were obese or of regular weight. The decreased ATP, ADP, AMP and elevated inosine suggested that the deaminases in charge of adenosine derivatives to inosine derivatives conversion would be significantly changed in the lungs of mice exposed to cigarette smoke. Indeed, transcriptional study confirmed that the concentrations of adenosine monophosphate deaminase 2 and adenosine deaminase 2 were significantly changed in the lungs of mice exposed to cigarette smoke. We also found that the ratio of glycerophosphocholine (GPC) to phosphocholine (PC) was significantly increased in the lungs of obese mice compared with those of the regular weight mice. The GPC/PC ratio was further elevated in the lungs of obese group exposed to cigarette smoke.

Perinatal asphyxia: a review from a metabolomics perspective

Perinatal asphyxia is defined as an oxygen deprivation that occurs around the time of birth, and may be caused by several perinatal events. This medical condition affects some four million neonates worldwide per year, causing the death of one million subjects. In most cases, infants successfully recover from hypoxia episodes; however, some patients may develop HIE, leading to permanent neurological conditions or impairment of different organs and systems. Given its multifactor dependency, the timing, severity and outcome of this disease, mainly assessed through Sarnat staging, are of difficult evaluation. Moreover, although the latest newborn resuscitation guideline suggests the use of a 21% oxygen concentration or room air, such an approach is still under debate. Therefore, the pathological mechanism is still not clear and a golden standard treatment has yet to be defined. In this context, metabolomics, a new discipline that has described important perinatal issues over the last years, proved to be a useful tool for the monitoring, the assessment, and the identification of potential biomarkers associated with asphyxia events. This review covers metabolomics research on perinatal asphyxia condition, examining in detail the studies reported both on animal and human models.

Dominant components of the Thoroughbred metabolome characterised by (1) H-nuclear magnetic resonance spectroscopy: A metabolite atlas of common biofluids

REASONS FOR PERFORMING STUDY

Metabonomics is emerging as a powerful tool for disease screening and investigating mammalian metabolism. This study aims to create a metabolic framework by producing a preliminary reference guide for the normal equine metabolic milieu.

OBJECTIVES

To metabolically profile plasma, urine and faecal water from healthy racehorses using high resolution (1) H-nuclear magnetic resonance (NMR) spectroscopy and to provide a list of dominant metabolites present in each biofluid for the benefit of future research in this area.

STUDY DESIGN

This study was performed using 7 Thoroughbreds in race training at a single time point. Urine and faecal samples were collected noninvasively and plasma was obtained from samples taken for routine clinical chemistry purposes.

METHODS

Biofluids were analysed using (1) H-NMR spectroscopy. Metabolite assignment was achieved via a range of one- and 2-dimensional experiments.

RESULTS

A total of 102 metabolites were assigned across the 3 biological matrices. A core metabonome of 14 metabolites was ubiquitous across all biofluids. All biological matrices provided a unique window on different aspects of systematic metabolism. Urine was the most populated metabolite matrix with 65 identified metabolites, 39 of which were unique to this biological compartment. A number of these were related to gut microbial host cometabolism. Faecal samples were the most metabolically variable between animals; acetate was responsible for the majority (28%) of this variation. Short-chain fatty acids were the predominant features identified within this biofluid by (1) H-NMR spectroscopy.

CONCLUSIONS

Metabonomics provides a platform for investigating complex and dynamic interactions between the host and its consortium of gut microbes and has the potential to uncover markers for health and disease in a variety of biofluids. Inherent variation in faecal extracts along with the relative abundance of microbial-mammalian metabolites in urine and invasive nature of plasma sampling, infers that urine is the most appropriate biofluid for the purposes of metabonomic analysis.

Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes

This paper highlights the metabolomic roles in systems biology towards the elucidation of metabolic mechanisms in obesity and type 2 diabetes.

Application of NMR-based metabolomics for environmental assessment in the Great Lakes using zebra mussel (Dreissena polymorpha)

Zebra mussel, Dreissena polymorpha, in the Great Lakes is being monitored as a bio-indicator organism for environmental health effects by the National Oceanic and Atmospheric Administration's Mussel Watch program. In order to monitor the environmental effects of industrial pollution on the ecosystem, invasive zebra mussels were collected from four stations-three inner harbor sites (LMMB4, LMMB1, and LMMB) in Milwaukee Estuary, and one reference site (LMMB5) in Lake Michigan, Wisconsin. Nuclear magnetic resonance (NMR)-based metabolomics was used to evaluate the metabolic profiles of the mussels from these four sites. The objective was to observe whether there were differences in metabolite profiles between impacted sites and the reference site; and if there were metabolic profile differences among the impacted sites. Principal component analyses indicated there was no significant difference between two impacted sites: north Milwaukee harbor (LMMB and LMMB4) and the LMMB5 reference site. However, significant metabolic differences were observed between the impacted site on the south Milwaukee harbor (LMMB1) and the LMMB5 reference site, a finding that correlates with preliminary sediment toxicity results. A total of 26 altered metabolites (including two unidentified peaks) were successfully identified in a comparison of zebra mussels from the LMMB1 site and LMMB5 reference site. The application of both uni- and multivariate analysis not only confirmed the variability of altered metabolites but also ensured that these metabolites were identified via unbiased analysis. This study has demonstrated the feasibility of the NMR-based metabolomics approach to assess whole-body metabolomics of zebra mussels to study the physiological impact of toxicant exposure at field sites.

Distinguishing the serum metabolite profiles differences in breast cancer by gas chromatography mass spectrometry and random forest method

In this study, we proposed a metabolomics strategy to distinguish different metabolic characters of healthy controls, breast benign (BE) patients, and breast malignant (BC) patients by using the GC-MS and random forest method (RF).

Acclimatisation-induced stress influenced host metabolic and gut microbial composition change

An integrated metabonomics and metagenomics approach utilised here showed that acclimatisation-induced stress leads to host metabolic and gut microbiotal changes.

Molecular effects of supraphysiological doses of doping agents on health

Supraphysiological doses of doping agents, such as T/DHT and GH/IGF-1, affect cellular pathways associated with apoptosis and inflammation.

The metabolomics of airway diseases, including COPD, asthma and cystic fibrosis

Chronic obstructive pulmonary disease (COPD), asthma and cystic fibrosis (CF) are characterized by airway obstruction and an inflammatory process. Reaching early diagnosis and discrimination of subtypes of these respiratory diseases are quite a challenging task than other chronic illnesses. Metabolomics is the study of metabolic pathways and the measurement of unique biochemical molecules generated in a living system. In the last decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. In this article, we review the current state of the metabolomics of COPD, asthma and CF with a focus on the different methods and instrumentation being used for the discovery of biomarkers in research and translation into clinic as diagnostic aids for the choice of patient-specific therapies.

1H-NMR analysis of the human urinary metabolome in response to an 18-month multi-component exercise program and calcium–vitamin-D3supplementation in older men

The musculoskeletal benefits of calcium and vitamin-D3supplementation and exercise have been extensively studied, but the effect on metabolism remains contentious. Urine samples were analyzed by1H-NMR spectroscopy from participants recruited for an 18-month, randomized controlled trial of a multi-component exercise program and calcium and vitamin-D3fortified milk consumption. It was shown previously that no increase in musculoskeletal composition was observed for participants assigned to the calcium and vitamin-D3intervention, but exercise resulted in increased bone mineral density, total lean body mass, and muscle strength. Retrospective metabolomics analysis of urine samples from patients involved in this study revealed no distinct changes in the urinary metabolome in response to the calcium and vitamin-D3intervention, but significant changes followed the exercise intervention, notably a reduction in creatinine and an increase in choline, guanidinoacetate, and hypoxanthine (p < 0.001, fold change > 1.5). These metabolites are intrinsically involved in anaerobic ATP synthesis, intracellular buffering, and methyl-balance regulation. The exercise intervention had a marked effect on the urine metabolome and markers of muscle turnover but none of these metabolites were obvious markers of bone turnover. Measurement of specific urinary exercise biomarkers may provide a basis for monitoring performance and metabolic response to exercise regimes.

Precision high-throughput proton NMR spectroscopy of human urine, serum, and plasma for large-scale metabolic phenotyping

Proton nuclear magnetic resonance (NMR)-based metabolic phenotyping of urine and blood plasma/serum samples provides important prognostic and diagnostic information and permits monitoring of disease progression in an objective manner. Much effort has been made in recent years to develop NMR instrumentation and technology to allow the acquisition of data in an effective, reproducible, and high-throughput approach that allows the study of general population samples from epidemiological collections for biomarkers of disease risk. The challenge remains to develop highly reproducible methods and standardized protocols that minimize technical or experimental bias, allowing realistic interlaboratory comparisons of subtle biomarker information. Here we present a detailed set of updated protocols that carefully consider major experimental conditions, including sample preparation, spectrometer parameters, NMR pulse sequences, throughput, reproducibility, quality control, and resolution. These results provide an experimental platform that facilitates NMR spectroscopy usage across different large cohorts of biofluid samples, enabling integration of global metabolic profiling that is a prerequisite for personalized healthcare.

The metabolite profiles of the obese population are gender-dependent

Studies have identified that several amino acids, in particular, branched-chain amino acids (BCAAs), have increased significantly in obese individuals when compared to lean individuals. Additionally, these metabolites were strongly associated with future diabetes, which rendered them prognostic markers suitable for obese populations. Here we report a metabonomic study that reveals new findings on the role of these amino acid markers, particularly BCAAs, in a Chinese cohort including 106 healthy obese and 105 healthy lean participants. We found that the BCAAs were correlated with insulin resistance and differentially expressed in obese men, but not in obese women. The results were verified with two independent groups of participants (Chinese, n = 105 and American, n = 72) and demonstrate that the serum metabolite profiles of the obese population are gender-dependent. The study supports the previous findings of a panel of several key metabolites as prognostic markers of the obese population and highlights the need to take into account gender differences when using these markers for risk assessment.

Maternal and fetal metabonomic alterations in prenatal nicotine exposure-induced rat intrauterine growth retardation

Prenatal nicotine exposure causes adverse birth outcome. However, the corresponding metabonomic alterations and underlying mechanisms of nicotine-induced developmental toxicity remain unclear. The aims of this study were to characterize the metabolic alterations in biofluids in nicotine-induced intrauterine growth retardation (IUGR) rat model. In the present study, pregnant Wistar rats were intragastrically administered with different doses of nicotine (0.5, 1.0 and 2.0 mg/kg d) from gestational day (GD) 11-20. The metabolic profiles of the biofluids, including maternal plasma, fetal plasma and amniotic fluid, were analyzed using (1)H nuclear magnetic resonance (NMR)-based metabonomic techniques. Prenatal nicotine exposure caused noticeably lower body weights, higher IUGR rates of fetal rats, and elevated maternal and fetal corticosterone (CORT) levels compared to the controls. The correlation analysis among maternal, fetal serum CORT levels and fetal bodyweight suggested that the levels of maternal and fetal serum CORT presented a positive correlation (r=0.356, n=32, P<0.05), while there was a negative correlation between fetal (r=-0.639, n=32, P<0.01) and maternal (r=-0.530, n=32, P<0.01) serum CORT level and fetal bodyweight. The fetal metabonome alterations included the stimulation of lipogenesis and the decreased levels of glucose and amino acids. The maternal metabonome alterations involved the enhanced blood glucose levels, fatty acid oxygenolysis, proteolysis and amino acid accumulation. These results suggested that prenatal nicotine exposure is associated with an altered maternal and fetal metabonome, which may be related to maternal increased glucocorticoid level induced by nicotine.

Serum metabolomic profiles evaluated after surgery may identify patients with oestrogen receptor negative early breast cancer at increased risk of disease recurrence. Results from a retrospective study

PURPOSE

Metabolomics is a global study of metabolites in biological samples. In this study we explored whether serum metabolomic spectra could distinguish between early and metastatic breast cancer patients and predict disease relapse.

METHODS

Serum samples were analysed from women with metastatic (n = 95) and predominantly oestrogen receptor (ER) negative early stage (n = 80) breast cancer using high resolution nuclear magnetic resonance spectroscopy. Multivariate statistics and a Random Forest classifier were used to create a prognostic model for disease relapse in early patients.

RESULTS

In the early breast cancer training set (n = 40), metabolomics correctly distinguished between early and metastatic disease in 83.7% of cases. A prognostic risk model predicted relapse with 90% sensitivity (95% CI 74.9-94.8%), 67% specificity (95% CI 63.0-73.4%) and 73% predictive accuracy (95% CI 70.6-74.8%). These results were reproduced in an independent early breast cancer set (n = 40), with 82% sensitivity, 72% specificity and 75% predictive accuracy. Disease relapse was associated with significantly lower levels of histidine (p = 0.0003) and higher levels of glucose (p = 0.01), and lipids (p = 0.0003), compared with patients with no relapse.

CONCLUSIONS

The performance of a serum metabolomic prognostic model for disease relapse in individuals with ER-negative early stage breast cancer is promising. A confirmation study is ongoing to better define the potential of metabolomics as a host and tumour-derived prognostic tool.

Multi-step preparation technique to recover multiple metabolite compound classes for in-depth and informative metabolomic analysis

Metabolomics is an emerging field which enables profiling of samples from living organisms in order to obtain insight into biological processes. A vital aspect of metabolomics is sample preparation whereby inconsistent techniques generate unreliable results. This technique encompasses protein precipitation, liquid-liquid extraction, and solid-phase extraction as a means of fractionating metabolites into four distinct classes. Improved enrichment of low abundance molecules with a resulting increase in sensitivity is obtained, and ultimately results in more confident identification of molecules. This technique has been applied to plasma, bronchoalveolar lavage fluid, and cerebrospinal fluid samples with volumes as low as 50 µl.  Samples can be used for multiple downstream applications; for example, the pellet resulting from protein precipitation can be stored for later analysis. The supernatant from that step undergoes liquid-liquid extraction using water and strong organic solvent to separate the hydrophilic and hydrophobic compounds. Once fractionated, the hydrophilic layer can be processed for later analysis or discarded if not needed. The hydrophobic fraction is further treated with a series of solvents during three solid-phase extraction steps to separate it into fatty acids, neutral lipids, and phospholipids. This allows the technician the flexibility to choose which class of compounds is preferred for analysis. It also aids in more reliable metabolite identification since some knowledge of chemical class exists.

1HNMR-based metabolomic profile of rats with experimental acute pancreatitis

Background

Acute pancreatitis (AP) is a common inflammatory disease of the pancreas accompanied by serious metabolic disturbances. Nevertheless, the specific metabolic process of this disease is still unclear. Characterization of the metabolome may help identify biomarkers for AP. To identify potential biomarkers, this study therefore investigated the 1H-nuclear magnetic resonance (NMR)-based metabolomic profile of AP.

Methods

Fourteen male adult Sprague–Dawley rats were randomized into two groups: the AP group, in which AP was induced by retrograde ductal infusion of 3.5% sodium taurocholate; and the sham operation group (SO), in which rats were infused with 0.9% saline. Blood samples were obtained 12 hours later and a 600 MHz superconducting NMR spectrometer was used to detect plasma metabolites. Principal components analysis (PCA) and partial least squares-discriminant analysis after orthogonal signal correction (OSC-PLS-DA) were used to analyze both longitudinal Eddy-delay (LED) and Carr–Purcell–Meiboom–Gill (CPMG) spectra.

Results

Differences in plasma metabolites between the two groups were detected by PCA and PLS-DA of 1HNMR spectra. Compared with the SO group, plasma levels of lactate (δ 1.3, 1.34, 4.1), valine (δ 0.98, 1.02), succinic acid (δ 2.38), 3-hydroxybutyric acid (3-HB, δ 1.18), high density lipoprotein (HDL, δ 0.8), and unsaturated fatty acid (UFA, δ 2.78, 5.3) were elevated in the AP group, while levels of glycerol (δ 3.58, 3.66), choline (δ 3.22), trimethylamine oxide (TMAO, δ 3.26), glucose (δ 3–4), glycine (δ 3.54), very low density lipoprotein (VLDL, δ 1.34) and phosphatidylcholine (Ptd, δ 2.78) were decreased.

Conclusions

AP has a characteristic metabolic profile. Lactate, valine, succinic acid, 3-HB, HDL, UFA, glycerol, choline, TMAO, glucose, glycine, VLDL, and Ptd may be potential biomarkers of early stage AP.

An magnetic resonance-based plasma metabonomic investigation on abnormal Savda in different complicated diseases

OBJECTIVE

To provide potential evidence for the existence of abnormal Savda, we assessed host metabonomic responses and dynamic changes occurring in various diseases using 1H nuclear magnetic resonance (NMR)-based metabonomics.

METHODS

Plasma samples taken from patients with complicated diseases with abnormal Savda (n = 140, including 35 cases each of diabetes, asthma, breast cancer, and cervical carcinoma) and from healthy controls (n = 35) were analyzed by 1H NMR (600 MHz), and the spectral profiles were analyzed by multivariate analysis using orthogonal projection to latent structure with discriminant analysis.

RESULTS

Supervised modeling of the data provided very good discrimination between patients and healthy controls. Compared with the healthy controls, the patient groups with different disease conditions displayed similar metabolic changes, characterized by lower creatine, creatinine, lactate, and amino acid levels (including isoleucine, leucine, valine, alanine, and 1-methylhistidine) and higher lipid levels (very low-density lipoproteins and unsaturated lipids). Additionally, cancer patients (breast and cervical) showed decreased myo-inositol, a-glucose, and beta-glucose, and increased pyruvate and carnitine in plasma.

CONCLUSION

The data indicate that decreased oxidative defense, liver function abnormalities, amino acid deficiencies, and energy metabolism disorders are common characteristics of complicated diseases, which may be related to the formation of abnormal Savda.

A metabolomic approach to animal vitreous humor topographical composition: a pilot study

The purpose of this study was to evaluate the feasibility of a (1)H-NMR-based metabolomic approach to explore the metabolomic signature of different topographical areas of vitreous humor (VH) in an animal model. Five ocular globes were enucleated from five goats and immediately frozen at -80 °C. Once frozen, three of them were sectioned, and four samples corresponding to four different VH areas were collected: the cortical, core, and basal, which was further divided into a superior and an inferior fraction. An additional two samples were collected that were representative of the whole vitreous body. (1)H-NMR spectra were acquired for twenty-three goat vitreous samples with the aim of characterizing the metabolomic signature of this biofluid and identifying whether any site-specific patterns were present. Multivariate statistical analysis (MVA) of the spectral data were carried out, including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Partial Least Squares Discriminant Analysis (PLS-DA). A unique metabolomic signature belonging to each area was observed. The cortical area was characterized by lactate, glutamine, choline, and its derivatives, N-acetyl groups, creatine, and glycerol; the core area was characterized by glucose, acetate, and scyllo-inositol; and the basal area was characterized by branched-chain amino acids (BCAA), betaine, alanine, ascorbate, lysine, and myo-inositol. We propose a speculative approach on the topographic role of these molecules that are mainly responsible for metabolic differences among the as-identified areas. (1)H-NMR-based metabolomic analysis has shown to be an important tool for investigating the VH. In particular, this approach was able to assess in the samples here analyzed the presence of different functional areas on the basis of a different metabolite distribution.