PubMed

Toluene inhalation in adolescent rats reduces flexible behaviour in adulthood and alters glutamatergic and GABAergic signalling. J Neurochem. 2016 Oct 1;: Authors: Furlong TM, Duncan JR, Corbit LH, Rae CD, Rowlands BD, Maher AD, Nasrallah FA, Milligan CJ, Petrou S, Lawrence AJ, Balleine BW Abstract Toluene is a commonly abused inhalant that is easily accessible to adolescents. Despite the increasing incidence of use, our understanding of its long-term impact remains limited. Here we used a range of techniques to examine the acute and chronic effects of toluene exposure on glutameteric and GABAergic function, and on indices of psychological function in adult rats after adolescent exposure. Metabolomics conducted on cortical tissue established that acute exposure to toluene produces alterations in cellular metabolism indicative of a glutamatergic and GABAergic profile. Similarly, in vitro electrophysiology in Xenopus oocytes found that acute toluene exposure reduced NMDA receptor signalling. Finally, in an adolescent rodent model of chronic intermittent exposure to toluene (10,000 ppm), we found that, while toluene exposure did not affect initial learning, it induced a deficit in updating that learning when response-outcome relationships were reversed or degraded in an instrumental conditioning paradigm. There were also group differences when more effort was required to obtain the reward; toluene exposed animals were less sensitive to progressive ratio schedules and to delayed discounting. These behavioural deficits were accompanied by changes in subunit expression of both NMDA and GABA receptors in adulthood, up to 10 weeks after the final exposure to toluene in the hippocampus, prefrontal cortex and ventromedial striatum; regions with recognised roles in behavioural flexibility and decision-making. Collectively our data suggest that exposure to toluene is sufficient to induce adaptive changes in glutamatergic and GABAergic systems and in adaptive behaviour that may underlie the deficits observed following adolescent inhalant abuse, including susceptibility to further drug-use. This article is protected by copyright. All rights reserved. PMID: 27696399 [PubMed - as supplied by publisher]

Ocean acidification influences host DNA methylation and phenotypic plasticity in environmentally susceptible corals. Evol Appl. 2016 Oct;9(9):1165-1178 Authors: Putnam HM, Davidson JM, Gates RD Abstract As climate change challenges organismal fitness by creating a phenotype-environment mismatch, phenotypic plasticity generated by epigenetic mechanisms (e.g., DNA methylation) can provide a temporal buffer for genetic adaptation. Epigenetic mechanisms may be crucial for sessile benthic marine organisms, such as reef-building corals, where ocean acidification (OA) and warming reflect in strong negative responses. We tested the potential for scleractinian corals to exhibit phenotypic plasticity associated with a change in DNA methylation in response to OA. Clonal coral fragments of the environmentally sensitive Pocillopora damicornis and more environmentally robust Montipora capitata were exposed to fluctuating ambient pH (7.9-7.65) and low pH (7.6-7.35) conditions in common garden tanks for ~6 weeks. M. capitata responded weakly, or acclimated more quickly, to OA, with no difference in calcification, minimal separation of metabolomic profiles, and no change in DNA methylation between treatments. Conversely, P. damicornis exhibited diminished calcification at low pH, stronger separation in metabolomic profiles, and responsiveness of DNA methylation to treatment. Our data suggest corals differ in their temporal dynamics and sensitivity for environmentally triggered real-time epigenetic reprogramming. The generation of potentially heritable plasticity via environmental induction of DNA methylation provides an avenue for assisted evolution applications in corals under rapid climate change. PMID: 27695524 [PubMed - in process]

Kidney Tissue Targeted Metabolic Profiling of Unilateral Ureteral Obstruction Rats by NMR. Front Pharmacol. 2016;7:307 Authors: Li Z, Li A, Gao J, Li H, Qin X Abstract Renal interstitial fibrosis is a common pathological process in the progression of kidney disease. A nuclear magnetic resonance (NMR) based metabolomic approach was used to analyze the kidney tissues of rats with renal interstitial fibrosis (RIF), induced by unilateral ureteral obstruction (UUO). The combination of a variety of statistical methods were used to screen out 14 significantly changed potential metabolites, which are related with multiple biochemical processes including amino acid metabolism, adenine metabolism, energy metabolism, osmolyte change and induced oxidative stress. The exploration of the contralateral kidneys enhanced the understanding of the disease, which was also supported by serum biochemistry and kidney histopathology results. In addition, the pathological parameters (clinical chemistry, histological and immunohistochemistry results) were correlated with the significantly changed differential metabolites related with RIF. This study showed that targeted tissue metabolomic analysis can be used as a useful tool to understand the mechanism of the disease and provide a novel insight in the pathogenesis of RIF. PMID: 27695416 [PubMed - in process]

The metabolome 18 years on: a concept comes of age. Metabolomics. 2016;12(9):148 Authors: Kell DB, Oliver SG Abstract BACKGROUND: The term 'metabolome' was introduced to the scientific literature in September 1998. AIM AND KEY SCIENTIFIC CONCEPTS OF THE REVIEW: To mark its 18-year-old 'coming of age', two of the co-authors of that paper review the genesis of metabolomics, whence it has come and where it may be going. PMID: 27695392 [PubMed - in process]

Solid-phase microextraction technology for in vitro and in vivo metabolite analysis. Trends Analyt Chem. 2016 Jun;80:57-65 Authors: Zhang Q, Zhou L, Chen H, Wang CZ, Xia Z, Yuan CS Abstract Analysis of endogenous metabolites in biological samples may lead to the identification of biomarkers in metabolomics studies. To achieve accurate sample analysis, a combined method of continuous quick sampling and extraction is required for online compound detection. Solid-phase microextraction (SPME) integrates sampling, extraction and concentration into a single solvent-free step for chemical analysis. SPME has a number of advantages, including simplicity, high sensitivity and a relatively non-invasive nature. In this article, we reviewed SPME technology in in vitro and in vivo analyses of metabolites after the ingestion of herbal medicines, foods and pharmaceutical agents. The metabolites of microorganisms in dietary supplements and in the gastrointestinal tract will also be examined. As a promising technology in biomedical and pharmaceutical research, SPME and its future applications will depend on advances in analytical technologies and material science. PMID: 27695152 [PubMed - in process]

Time-resolved metabolomics analysis of individual differences during the early stage of lipopolysaccharide-treated rats. Sci Rep. 2016 Oct 03;6:34136 Authors: Dai D, Gao Y, Chen J, Huang Y, Zhang Z, Xu F Abstract Lipopolysaccharide (LPS) can lead to uncontrollable cytokine production and eventually cause fatal sepsis syndrome. Individual toxicity difference of LPS has been widely reported. In our study we observed that two thirds of the rats (24/36) died at a given dose of LPS, while the rest (12/36) survived. Tracking the dynamic metabolic change in survival and non-survival rats in the early stage may reveal new system information to understand the inter-individual variation in response to LPS. As the time-resolved datasets are very complex and no single method can elucidate the problem clearly and comprehensively, the static and dynamic metabolomics methods were employed in combination as cross-validation. Intriguingly, some common results have been observed. Lipids were the main different metabolites between survival and non-survival rats in pre-dose serum and in the early stage of infection with LPS. The LPS treatment led to S-adenosly-methionine and total cysteine individual difference in early stage, and subsequent significant perturbations in energy metabolism and oxidative stress. Furthermore, cytokine profiles were analyzed to identify potential biological associations between cytokines and specific metabolites. Our collective findings may provide some heuristic guidance for elucidating the underlying mechanism of individual difference in LPS-mediated disease. PMID: 27695004 [PubMed - in process]

Plasma metabolomics identified novel metabolites associated with risk of type 2 diabetes in two prospective cohorts of Chinese adults. Int J Epidemiol. 2016 Sep 30;: Authors: Qiu G, Zheng Y, Wang H, Sun J, Ma H, Xiao Y, Li Y, Yuan Y, Yang H, Li X, Min X, Zhang C, Xu C, Jiang Y, Zhang X, He M, Yang M, Hu Z, Tang H, Shen H, Hu FB, Pan A, Wu T Abstract BACKGROUND: Metabolomics studies in Caucasians have identified a number of novel metabolites in association with the risk of type 2 diabetes (T2D). However, few prospective metabolomic studies are available in Chinese populations. In the present study, we sought to identify novel metabolites consistently associated with incident T2D in two independent cohorts of Chinese adults. METHODS: We performed targeted metabolomics (52 metabolites) of fasting plasma samples by liquid chromatography-mass spectrometry in two prospective case-control studies nested within the Dongfeng-Tongji (DFTJ) cohort and Jiangsu Non-communicable Disease (JSNCD) cohort. After following for 4.61 ± 0.15 and 7.57 ± 1.13 years, respectively, 1039 and 520 eligible participants developed incident T2D in these two cohorts, and controls were 1:1 matched with cases by age (± 5 years) and sex. Multivariate conditional logistic regression models were constructed to identify metabolites associated with future T2D risk in both cohorts. RESULTS: We identified four metabolites consistently associated with an increased risk of developing T2D in the two cohorts, including alanine, phenylalanine, tyrosine and palmitoylcarnitine. In the meta-analysis of two cohorts, the odds ratios (95% confidence intervals, CIs) comparing extreme quartiles were 1.79 (1.32-2.42) for alanine, 1.91 (1.41-2.60) for phenylalanine, 1.85 (1.37-2.48) for tyrosine and 1.63 (1.21-2.20) for palmitoylcarnitine (all Ptrend ≤ 0.01). CONCLUSIONS: We confirmed the association of alanine, phenylalanine and tyrosine with future T2D risk and further identified palmitoylcarnitine as a novel metabolic marker of incident T2D in two prospective cohorts of Chinese adults. Our findings might provide new aetiological insight into the development of T2D. PMID: 27694567 [PubMed - as supplied by publisher]

Functional Metabolomics Describes the Yeast Biosynthetic Regulome. Cell. 2016 Sep 28;: Authors: Mülleder M, Calvani E, Alam MT, Wang RK, Eckerstorfer F, Zelezniak A, Ralser M Abstract Genome-metabolism interactions enable cell growth. To probe the extent of these interactions and delineate their functional contributions, we quantified the Saccharomyces amino acid metabolome and its response to systematic gene deletion. Over one-third of coding genes, in particular those important for chromatin dynamics, translation, and transport, contribute to biosynthetic metabolism. Specific amino acid signatures characterize genes of similar function. This enabled us to exploit functional metabolomics to connect metabolic regulators to their effectors, as exemplified by TORC1, whose inhibition in exponentially growing cells is shown to match an interruption in endomembrane transport. Providing orthogonal information compared to physical and genetic interaction networks, metabolomic signatures cluster more than half of the so far uncharacterized yeast genes and provide functional annotation for them. A major part of coding genes is therefore participating in gene-metabolism interactions that expose the metabolism regulatory network and enable access to an underexplored space in gene function. PMID: 27693354 [PubMed - as supplied by publisher]

Association of blood lipids with Alzheimer's disease: A comprehensive lipidomics analysis. Alzheimers Dement. 2016 Sep 28;: Authors: Proitsi P, Kim M, Whiley L, Simmons A, Sattlecker M, Velayudhan L, Lupton MK, Soininen H, Kloszewska I, Mecocci P, Tsolaki M, Vellas B, Lovestone S, Powell JF, Dobson RJ, Legido-Quigley C Abstract INTRODUCTION: The aim of this study was to (1) replicate previous associations between six blood lipids and Alzheimer's disease (AD) (Proitsi et al 2015) and (2) identify novel associations between lipids, clinical AD diagnosis, disease progression and brain atrophy (left/right hippocampus/entorhinal cortex). METHODS: We performed untargeted lipidomic analysis on 148 AD and 152 elderly control plasma samples and used univariate and multivariate analysis methods. RESULTS: We replicated our previous lipids associations and reported novel associations between lipids molecules and all phenotypes. A combination of 24 molecules classified AD patients with >70% accuracy in a test and a validation data set, and we identified lipid signatures that predicted disease progression (R(2) = 0.10, test data set) and brain atrophy (R(2) ≥ 0.14, all test data sets except left entorhinal cortex). We putatively identified a number of metabolic features including cholesteryl esters/triglycerides and phosphatidylcholines. DISCUSSION: Blood lipids are promising AD biomarkers that may lead to new treatment strategies. PMID: 27693183 [PubMed - as supplied by publisher]

Sample preparation procedures utilized in microbial metabolomics: An overview. J Chromatogr B Analyt Technol Biomed Life Sci. 2016 Sep 22;: Authors: Patejko M, Jacyna J, Markuszewski MJ Abstract Bacteria are remarkably diverse in terms of their size, structure and biochemical properties. Due to this fact, it is hard to develop a universal method for handling bacteria cultures during metabolomic analysis. The choice of suitable processing methods constitutes a key element in any analysis, because only appropriate selection of procedures may provide accurate results, leading to reliable conclusions. Because of that, every analytical experiment concerning bacteria requires individually and very carefully planned research methodology. Although every study varies in terms of sample preparation, there are few general steps to follow while planning experiment, like sampling, separation of cells from growth medium, stopping their metabolism and extraction. As a result of extraction, all intracellular metabolites should be washed out from cell environment. What is more, extraction method utilized cannot cause any chemical decomposition or degradation of the metabolome. Furthermore, chosen extraction method should correlate with analytical technique, so it will not disturb or prolong following sample preparation steps. For those reasons, we observe a need to summarize sample preparation procedures currently utilized in microbial metabolomic studies. In the presented overview, papers concerning analysis of extra- and intracellular metabolites, published over the last decade, have been discussed. Presented work gives some basic guidelines that might be useful while planning experiments in microbial metabolomics. PMID: 27693061 [PubMed - as supplied by publisher]

Medium-chain Fatty Acids as Biomarkers of Mitochondrial Dysfunction in Traumatic Brain Injury. EBioMedicine. 2016 Sep 28;: Authors: González-Domínguez R PMID: 27692983 [PubMed - as supplied by publisher]

An overview of renal metabolomics. Kidney Int. 2016 Sep 28;: Authors: Kalim S, Rhee EP Abstract The high-throughput, high-resolution phenotyping enabled by metabolomics has been applied increasingly to a variety of questions in nephrology research. This article provides an overview of current metabolomics methodologies and nomenclature, citing specific considerations in sample preparation, metabolite measurement, and data analysis that investigators should understand when examining the literature or designing a study. Furthermore, we review several notable findings that have emerged in the literature that both highlight some of the limitations of current profiling approaches, as well as outline specific strengths unique to metabolomics. More specifically, we review data on the following: (i) tryptophan metabolites and chronic kidney disease onset, illustrating the interpretation of metabolite data in the context of established biochemical pathways; (ii) trimethylamine-N-oxide and cardiovascular disease in chronic kidney disease, illustrating the integration of exogenous and endogenous inputs to the blood metabolome; and (iii) renal mitochondrial function in diabetic kidney disease and acute kidney injury, illustrating the potential for rapid translation of metabolite data for diagnostic or therapeutic aims. Finally, we review future directions, including the need to better characterize interperson and intraperson variation in the metabolome, pool existing data sets to identify the most robust signals, and capitalize on the discovery potential of emerging nontargeted methods. PMID: 27692817 [PubMed - as supplied by publisher]

Chemical Isotope Labeling LC-MS for High Coverage and Quantitative Profiling of the Hydroxyl Submetabolome in Metabolomics. Anal Chem. 2016 Oct 3;: Authors: Zhao S, Luo X, Li L Abstract A key step in metabolomics is to perform accurate relative quantification of the metabolomes in comparative samples with high coverage. Hydroxyl-containing metabolites are an important class of the metabolome with diverse structures and physical/chemical properties. However, many of them are difficult to detect with high sensitivity. We present a high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) technique for in-depth profiling of the hydroxyl submetabolome. It involves the use of acidic liquid-liquid extraction (LLE) to enrich hydroxyl metabolites into ethyl acetate from an aqueous sample. After drying and then re-dissolving in acetonitrile, the metabolite extract is labeled by using base-activated (12)C- or (13)C-dansylation reaction. A fast step-gradient LC-UV method is used to determine the total concentration of labeled metabolites. Based on the concentration information, an equal amount of (12)C-labeled individual sample is taken for mixing with a (13)C-labeled pool or control for relative metabolite quantification. The (12)C-/(13)C-labeled mixtures are individually analyzed by LC-MS and the resultant peak pairs of labeled metabolites in MS are measured for relative quantification and metabolite identification. A standard library of 85 hydroxyl compounds containing MS, retention time and MS/MS information has been constructed for positive metabolite identification based on matches of two or all of the triple parameters with those of an unknown. Using human urine as an example, we analyzed samples of 1:1 (12)C-/(13)C-labeled urine in triplicate with triplicate runs per sample and detected an average of 3759±45 peak pairs or metabolites per run and 3538±71 pairs per sample with 3093 pairs in common (n=9). Out of the 3093 peak pairs, 2304 pairs (75%) could be positively or putatively identified based on metabolome database searches including 20 pairs positively identified using the dansylated hydroxyl standards library. Majority of detected metabolites are those containing hydroxyl groups. This technique opens a new venue for detailed characterization of the hydroxyl submetabolome in metabolomics research. PMID: 27690392 [PubMed - as supplied by publisher]

26 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2016/10/01PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

18 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2016/09/30PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

A Web Server for Peak Detection, Baseline Correction and Alignment in Two-dimensional Gas Chromatography Mass Spectrometry-based Metabolomics Data. Anal Chem. 2016 Sep 27; Authors: Tian TF, Wang SY, Kuo TC, Tan CE, Chen GY, Kuo CH, Chen CH, Chan CC, Lin OA, Tseng YJ Abstract Two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC/TOF-MS) is superior for chromatographic separation and provides great sensitivity for complex biological fluid analysis in metabolomics. However, GCxGC/TOF-MS data processing is currently limited to vendor software and typically requires several preprocessing steps. In this work, we implement a web-based platform, which we call GC(2)MS, to facilitate the application of recent advances in GCxGC/TOF-MS, especially for metabolomics studies. The core processing workflow of GC(2)MS consists of blob/peak detection, baseline correction, and blob alignment. GC(2)MS treats GCxGC/TOF-MS data as pictures and clusters the pixels as blobs according to the brightness of each pixel to generate a blob table. GC(2)MS then aligns the blobs of two GCxGC/TOF-MS datasets according to their distance and similarity. The blob distance and similarity are the Euclidean distance of the first and second retention times of two blobs and the Pearson's correlation coefficient of the two mass spectra, respectively. GC(2)MS also directly corrects the raw data baseline. The analytical performance of GC(2)MS was evaluated using GCxGC/TOF-MS datasets of Angelica sinensis compounds acquired under different experimental conditions and of human plasma samples. The results show that GC(2)MS is an easy-to-use tool for detecting peaks and correcting baselines, and GC(2)MS is able to align GCxGC/TOF-MS datasets acquired under different experimental conditions. GC(2)MS is freely accessible at http://gc2ms.web.cmdm.tw. PMID: 27673369 [PubMed - as supplied by publisher]

The diagnostic and prognostic value of systems biology research in major traumatic and thermal injury: a review. Burns Trauma. 2016;4:33 Authors: Hazeldine J, Hampson P, Lord JM Abstract As secondary complications remain a significant cause of morbidity and mortality amongst hospitalised trauma patients, the need to develop novel approaches by which to identify patients at risk of adverse outcome is becoming increasingly important. Centred on the idea that patients who experience "poor" outcome post trauma elicit a response to injury that is distinct from those who experience "good" outcome, tailored therapeutics is an emerging concept aimed at improving current treatment regimens by promoting patient-specific therapies. Making use of recent advancements in the fields of genomics, proteomics and metabolomics, numerous groups have undertaken a systems-based approach to analysing the acute immune and inflammatory response to major traumatic and thermal injury in an attempt to uncover a single or combination of biomarkers that can identify patients at risk of adverse outcome. Early results are encouraging, with all three approaches capable of discriminating patients with "good" outcome from those who develop nosocomial infections, sepsis and multiple organ failure, with differences apparent in blood samples acquired as early as 2 h post injury. In particular, genomic data is proving to be highly informative, identifying patients at risk of "poor" outcome with a higher degree of sensitivity and specificity than statistical models built upon data obtained from existing anatomical and physiological scoring systems. Here, focussing predominantly upon human-based research, we provide an overview of the findings of studies that have investigated the immune and inflammatory response to major traumatic and thermal injury at the genomic, protein and metabolite level, and consider both the diagnostic and prognostic potential of these approaches. PMID: 27672669 [PubMed]

Canopy position has a profound effect on soybean seed composition. PeerJ. 2016;4:e2452 Authors: Huber SC, Li K, Nelson R, Ulanov A, DeMuro CM, Baxter I Abstract Although soybean seeds appear homogeneous, their composition (protein, oil and mineral concentrations) can vary significantly with the canopy position where they were produced. In studies with 10 cultivars grown over a 3-yr period, we found that seeds produced at the top of the canopy have higher concentrations of protein but less oil and lower concentrations of minerals such as Mg, Fe, and Cu compared to seeds produced at the bottom of the canopy. Among cultivars, mean protein concentration (average of different positions) correlated positively with mean concentrations of S, Zn and Fe, but not other minerals. Therefore, on a whole plant basis, the uptake and allocation of S, Zn and Fe to seeds correlated with the production and allocation of reduced N to seed protein; however, the reduced N and correlated minerals (S, Zn and Fe) showed different patterns of allocation among node positions. For example, while mean concentrations of protein and Fe correlated positively, the two parameters correlated negatively in terms of variation with canopy position. Altering the microenvironment within the soybean canopy by removing neighboring plants at flowering increased protein concentration in particular at lower node positions and thus altered the node-position gradient in protein (and oil) without altering the distribution of Mg, Fe and Cu, suggesting different underlying control mechanisms. Metabolomic analysis of developing seeds at different positions in the canopy suggests that availability of free asparagine may be a positive determinant of storage protein accumulation in seeds and may explain the increased protein accumulation in seeds produced at the top of the canopy. Our results establish node-position variation in seed constituents and provide a new experimental system to identify genes controlling key aspects of seed composition. In addition, our results provide an unexpected and simple approach to link agronomic practices to improve human nutrition and health in developing countries because food products produced from seeds at the bottom of the canopy contained higher Fe concentrations than products from the top of the canopy. Therefore, using seeds produced in the lower canopy for production of iron-rich soy foods for human consumption could be important when plants are the major source of protein and human diets can be chronically deficient in Fe and other minerals. PMID: 27672507 [PubMed]

Microgravity induces proteomics changes involved in endoplasmic reticulum stress and mitochondrial protection. Sci Rep. 2016;6:34091 Authors: Feger BJ, Thompson JW, Dubois LG, Kommaddi RP, Foster MW, Mishra R, Shenoy SK, Shibata Y, Kidane YH, Moseley MA, Carnell LS, Bowles DE Abstract On Earth, biological systems have evolved in response to environmental stressors, interactions dictated by physical forces that include gravity. The absence of gravity is an extreme stressor and the impact of its absence on biological systems is ill-defined. Astronauts who have spent extended time under conditions of minimal gravity (microgravity) experience an array of biological alterations, including perturbations in cardiovascular function. We hypothesized that physiological perturbations in cardiac function in microgravity may be a consequence of alterations in molecular and organellar dynamics within the cellular milieu of cardiomyocytes. We used a combination of mass spectrometry-based approaches to compare the relative abundance and turnover rates of 848 and 196 proteins, respectively, in rat neonatal cardiomyocytes exposed to simulated microgravity or normal gravity. Gene functional enrichment analysis of these data suggested that the protein content and function of the mitochondria, ribosomes, and endoplasmic reticulum were differentially modulated in microgravity. We confirmed experimentally that in microgravity protein synthesis was decreased while apoptosis, cell viability, and protein degradation were largely unaffected. These data support our conclusion that in microgravity cardiomyocytes attempt to maintain mitochondrial homeostasis at the expense of protein synthesis. The overall response to this stress may culminate in cardiac muscle atrophy. PMID: 27670941 [PubMed - as supplied by publisher]

Reduction in cardiometabolic risk factors by a multifunctional diet is mediated via several branches of metabolism as evidenced by non-targeted metabolite profiling approach. Mol Nutr Food Res. 2016 Sep 27; Authors: Tovar J, de Mello VD, Nilsson A, Johansson M, Paananen J, Lehtonen M, Hanhineva K, Björck I Abstract SCOPE: MFD, a diet based on multiple functional concepts and ingredients with antiinflammatory activity, was previously shown to improve different cardiometabolic risk-associated markers in healthy subjects. Here, we assessed the impact of MFD on plasma metabolome and explored associations of the differential metabolites with clinical parameters, searching for metabolic determinants related to the effects of MFD. METHODS AND RESULTS: Forty-four overweight healthy volunteers completed a randomized crossover intervention comparing MFD with a control diet devoid of the active components of MFD. Fasting plasma samples were analyzed with non-targeted metabolite profiling at baseline and at the end (4 wk) of each diet period by liquid chromatography coupled to quadrupole-time of flight-MS system, revealing a vast impact of MFD on metabolic homeostasis. Main metabolite classes affected included acylcarnitines, furan fatty acids, phospholipids (plasmalogens, phosphatidylcholines, phosphatidylethanolamines), and various low-molecular weight products from the bioactivity of gut microbiota. Circulating levels of several of these metabolites correlated with changes in clinical blood lipid biomarkers. CONCLUSIONS: The metabolomics approach revealed that consumption of MFD affected different areas of metabolism, highlighting the impact of a healthy diet on plasma metabolome. This seems linked to reduced cardiometabolic risk and provides mechanistic insight into the effects of MFD. This article is protected by copyright. All rights reserved. PMID: 27670644 [PubMed - as supplied by publisher]