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Polybrominated diphenyl ethers (PBDEs) are commonly used to retard the combustion of materials such as foam padding, textiles, or plastics, and numerous studies have confirmed the accumulation thereof in the environment and in fish, mammals, and humans. In this study, we used metabolomics to conduct an environmental risk assessment of the PBDE-209. We profiled the urinary metabolites of control and PBDE-treated rats (exposed to PBDE-209) using nuclear magnetic resonance (NMR) and mass spectrometry (MS). Global metabolic profiling indicated that the effects of PBDE-209 on the urinary metabolic profile were not significant. However, targeted metabolic profiling revealed progressive effects of PBDE-209 over a 7-day PBDE-209 treatment. Moreover, despite the weak PBDE-209 effects, we observed that choline, acetylcholine, 3-indoxylsulfate, creatinine, urea, and dimethyl sulfone levels were decreased, whereas that of pyruvate was significantly increased. Furthermore, we suggest that the increased pyruvate level and decreased levels of choline, acetylcholine, and uremic toxins were suggestive of endocrine disruption and neurodevelopmental toxicity caused by PBDEs. © 2016 Wiley Periodicals, Inc. Environ Toxicol 32: 1262-1272, 2017.

SummaryBackground Asthma is a chronic inflammatory disease caused by complex interactions of genetic, epigenetic, and environmental factors. For this reason, new approaches are required to clarify the pathogenesis of asthma by systemic review. Objective We applied a 1H-NMR metabolomics approach to investigate the altered metabolic pattern in sera from patients with asthma and sought to identify the mechanism underlying asthma and potential biomarkers. Method A global profile of sera from patients with asthma (n = 39) and controls (n = 26) was generated using 1H-NMR spectroscopy coupled with multivariate statistical analysis. Endogenous metabolites in serum were rapidly measured using the target-profiling procedure. Results Multivariate statistical analysis showed a clear distinction between patients with asthma and healthy subjects. Sera of asthma patients were characterized by increased levels of methionine, glutamine, and histidine and by decreased levels of formate, methanol, acetate, choline, O-phosphocholine, arginine, and glucose. The metabolites detected in the sera of patients with asthma are involved in hypermethylation, response to hypoxia, and immune reaction. Furthermore, the levels of serum metabolites from patients with asthma correlated with asthma severity; in particular, lipid metabolism was altered in patients with lower forced expiratory volume in 1 s percentage (FEV1%) predicted values. In addition, potential biomarkers showed strong predictive power in ROC analysis, and the presence of asthma in external validation models was predicted with high accuracy (90.9% for asthma and 100% for control subjects). Conclusion & Clinical Relevance These data showed that 1H-NMR-based metabolite profiling of serum may be useful for the effective diagnosis of asthma and a further understanding of its pathogenesis.

Cornus officinalis (Cornaceae) is primarily grown in Asian countries. The pericarp of C. officinalis (Corni Fructus) is a well-known traditional medicine with tonic, analgesic, and diuretic properties. We analyzed methanolic extracts of Corni Fructus (grown in Korea and China) by NMR spectroscopy. Metabolite profiling was performed to characterize the metabolic difference between different Corni Fructus origins (Korea or China). Principal components analysis revealed significant separation between Comus Fructus from different origins. The metabolites responsible for differences were identified using loading plots, coefficients plots, and variable influence on projection followed by t-tests. As a result, 16 metabolites were identified and quantified; tyrosine, acetate, sucrose, and malate differed the most between origins. These data suggest that NMR-based metabolomics can be used to identify differences between Corni Fructus samples obtained from different regions.

The goal of metabolomics is to analyze a whole metabolome under a given set of conditions, and accurate and reliable quantitation of metabolites is crucial. Absolute concentration is more valuable than relative concentration; however, the most commonly used method in NMR-based serum metabolic profiling, bin-based and full data point peak quantification, provides relative concentration levels of metabolites and are not reliable when metabolite peaks overlap in a spectrum. In this study, we present the software-assisted serum metabolite quantification (SASMeQ) method, which allows us to identify and quantify metabolites in NMR spectra using Chenomx software. This software uses the ERETIC2 utility from TopSpin to add a digitally synthesized peak to a spectrum. The SASMeQ method will advance NMR-based serum metabolic profiling by providing an accurate and reliable method for absolute quantification that is superior to bin-based quantification.

Discovery of biomarkers in peripheral blood is a crucial step toward the early diagnosis and repetitive monitoring of treatment response for Alzheimer's disease (AD). Metabolomics is a promising technology that can identify unbiased biomark- ers. To explore potential blood biomarkers for AD via metabolic profiling with high-resolution magic angle spinning nuclear magnetic resonance techniques, we identified changes in peripheral blood metabolomic profiles in response to amyloid- (A)- induced neuroinflammation and co-treatment with gallate, a phytochemical known to have anti-neuroinflammatory properties. Alzheimer's-like (AL) model mice were produced by intracerebroventricular infusion of A and compared with normal control mice with infusion of vehicle. AL mice were treated with either gallate (treated AL mice) or vehicle (untreated AL mice). Metabolomic analyses of both whole blood and plasma showed a clear separation between untreated AL mice and the other two groups, with levels of several metabolites involved in energy metabolism, including pyruvate and creatine, being signifi- cantly reduced in untreated AL mice compared with control and treated AL mice. Gallate treatment suppressed A-induced overproduction of the inflammatory cytokine tumor necrosis factor- in the hippocampus and normalized plasma levels of the affected metabolites. These results suggest that plasma levels of several metabolites could be indicative of both brain pathology and therapeutic responses, supporting the possibility of a close relationship between central neuroinflammation and systemic metabolic disturbance. These findings also suggest the potential of NMR-based metabolomics as a method to identify novel plasma biomarkers for AD, which could be confirmed by future translational research with human patients.

Marine mussels (Mytilus) are widely used as bioindicators to measure pollution in marine environments. In this study, (1)H NMR spectroscopy and multivariate statistical analyses were used to differentiate mussel groups from a heavy metal-polluted area (Onsan Bay) and a clean area (Dokdo area). Principal component analysis and orthogonal projection to latent structure-discriminant analysis revealed significant separation between extracts of mussels from Onsan Bay and from the Dokdo area. Organic osmolytes (betaine and taurine) and free amino acids (alanine, arginine, glutamine, phenylalanine, and threonine) were more highly accumulated in Onsan Bay mussels compared with Dokdo mussels. These results demonstrate that NMR-based metabolomics can be used as an efficient method for characterizing heavy metal contamination derived from polluted area compared to clean area and to identify metabolites related to environments that are contaminated with heavy metals.