Weight loss predictability by plasma metabolic signatures in adults with obesity and morbid obesity of the DiOGenes study.

OBJECTIVE: Aim is to predict successful weight loss by metabolic signatures at baseline and to identify which differences in metabolic status may underlie variations in weight loss success. METHODS: In DiOGenes, a randomized, controlled trial, weight loss was induced using a low-calorie diet (800 kcal) for 8 weeks. Men (N = 236) and women (N = 431) as well as groups with overweight/obesity and morbid obesity were studied separately. The relation between the metabolic status before weight loss and weight loss was assessed by stepwise regression on multiple data sets, including anthropometric parameters, NMR-based plasma metabolites, and LC-MS-based plasma lipid species. RESULTS: Maximally, 57% of the variation in weight loss success can be predicted by baseline parameters. The most powerful predictive models were obtained in subjects with morbid obesity. In these models, the metabolites most predictive for weight loss were acetoacetate, triacylglycerols, phosphatidylcholines, specific amino acids, and creatine and creatinine. This metabolic profile suggests that high energy metabolism activity results in higher amounts of weight loss. CONCLUSIONS: Possible predictive (pre-diet) markers were found for amount of weight loss for specific subgroups.

Collagen Induced Arthritis in DBA/1J Mice Associates with Oxylipin Changes in Plasma.

Oxylipins play important roles in various biological processes and are considered as mediators of inflammation for a wide range of diseases such as rheumatoid arthritis (RA). The purpose of this research was to study differences in oxylipin levels between a widely used collagen induced arthritis (CIA) mice model and healthy control (Ctrl) mice. DBA/1J male mice (age: 6-7 weeks) were selected and randomly divided into two groups, namely, a CIA and a Ctrl group. The CIA mice were injected intraperitoneally (i.p.) with the joint cartilage component collagen type II (CII) and an adjuvant injection of lipopolysaccharide (LPS). Oxylipin metabolites were extracted from plasma for each individual sample using solid phase extraction (SPE) and were detected with high performance liquid chromatography/tandem mass spectrometry (HPLC-ESI-MS/MS), using dynamic multiple reaction monitoring (dMRM). Both univariate and multivariate statistical analyses were applied. The results in univariate Student's t-test revealed 10 significantly up- or downregulated oxylipins in CIA mice, which were supplemented by another 6 additional oxylipins, contributing to group clustering upon multivariate analysis. The dysregulation of these oxylipins revealed the presence of ROS-generated oxylipins and an increase of inflammation in CIA mice. The results also suggested that the collagen induced arthritis might associate with dysregulation of apoptosis, possibly inhibited by activated NF-κB because of insufficient PPAR-γ ligands.

Oxylipid Profile of Low-Dose Aspirin Exposure: A Pharmacometabolomics Study.

BACKGROUND: While aspirin is a well-established and generally effective anti-platelet agent, considerable inter-individual variation in drug response exists, for which mechanisms are not completely understood. Metabolomics allows for extensive measurement of small molecules in biological samples, enabling detailed mapping of pathways involved in drug response. METHODS AND RESULTS: We used a mass-spectrometry-based metabolomics platform to investigate the changes in the serum oxylipid metabolome induced by an aspirin intervention (14 days, 81 mg/day) in healthy subjects (n=156). We observed a global decrease in serum oxylipids in response to aspirin (25 metabolites decreased out of 30 measured) regardless of sex. This decrease was concomitant with a significant decrease in serum linoleic acid levels (-19%, P=1.3×10(-5)), one of the main precursors for oxylipid synthesis. Interestingly, several linoleic acid-derived oxylipids were not significantly associated with arachidonic-induced ex vivo platelet aggregation, a widely accepted marker of aspirin response, but were significantly correlated with platelet reactivity in response to collagen. CONCLUSIONS: Together, these results suggest that linoleic acid-derived oxylipids may contribute to the non-COX1 mediated variability in response to aspirin. Pharmacometabolomics allowed for more comprehensive interrogation of mechanisms of action of low dose aspirin and of variation in aspirin response.

Metabolic phenotyping reveals a lipid mediator response to ionizing radiation.

Exposure to ionizing radiation has dramatically increased in modern society, raising serious health concerns. The molecular response to ionizing radiation, however, is still not completely understood. Here, we screened mouse serum for metabolic alterations following an acute exposure to γ radiation using a multiplatform mass-spectrometry-based strategy. A global, molecular profiling revealed that mouse serum undergoes a series of significant molecular alterations following radiation exposure. We identified and quantified bioactive metabolites belonging to key biochemical pathways and low-abundance, oxygenated, polyunsaturated fatty acids (PUFAs) in the two groups of animals. Exposure to γ radiation induced a significant increase in the serum levels of ether phosphatidylcholines (PCs) while decreasing the levels of diacyl PCs carrying PUFAs. In exposed mice, levels of pro-inflammatory, oxygenated metabolites of arachidonic acid increased, whereas levels of anti-inflammatory metabolites of omega-3 PUFAs decreased. Our results indicate a specific serum lipidomic biosignature that could be utilized as an indicator of radiation exposure and as novel target for therapeutic intervention. Monitoring such a molecular response to radiation exposure might have implications not only for radiation pathology but also for countermeasures and personalized medicine.

A protective lipidomic biosignature associated with a balanced omega-6/omega-3 ratio in fat-1 transgenic mice.

A balanced omega-6/omega-3 polyunsaturated fatty acid (PUFA) ratio has been linked to health benefits and the prevention of many chronic diseases. Current dietary intervention studies with different sources of omega-3 fatty acids (omega-3) lack appropriate control diets and carry many other confounding factors derived from genetic and environmental variability. In our study, we used the fat-1 transgenic mouse model as a proxy for long-term omega-3 supplementation to determine, in a well-controlled manner, the molecular phenotype associated with a balanced omega-6/omega-3 ratio. The fat-1 mouse can convert omega-6 to omega-3 PUFAs, which protect against a wide variety of diseases including chronic inflammatory diseases and cancer. Both wild-type (WT) and fat-1 mice were subjected to an identical diet containing 10% corn oil, which has a high omega-6 content similar to that of the Western diet, for a six-month duration. We used a multi-platform lipidomic approach to compare the plasma lipidome between fat-1 and WT mice. In fat-1 mice, an unbiased profiling showed a significant increase in the levels of unesterified eicosapentaenoic acid (EPA), EPA-containing cholesteryl ester, and omega-3 lysophosphospholipids. The increase in omega-3 lipids is accompanied by a significant reduction in omega-6 unesterified docosapentaenoic acid (omega-6 DPA) and DPA-containing cholesteryl ester as well as omega-6 phospholipids and triacylglycerides. Targeted lipidomics profiling highlighted a remarkable increase in EPA-derived diols and epoxides formed via the cytochrome P450 (CYP450) pathway in the plasma of fat-1 mice compared with WT mice. Integration of the results of untargeted and targeted analyses has identified a lipidomic biosignature that may underlie the healthful phenotype associated with a balanced omega-6/omega-3 ratio, and can potentially be used as a circulating biomarker for monitoring the health status and the efficacy of omega-3 intervention in humans.

Postprandial fatty acid specific changes in circulating oxylipins in lean and obese men after high-fat challenge tests.

SCOPE: Circulating oxylipins may affect peripheral tissues and are assumed to play an important role in endothelial function. They are esterified in triglyceride-rich lipoproteins that are increased after a high-fat (HF) meal, depending on BMI and fatty acid (FA) type. Yet, it is unclear which oxylipins appear in circulation after HF meals differing in FA composition. METHODS AND RESULTS: In a double-blind randomized crossover challenge study, we characterized the postprandial oxylipin response after different HF challenges in lean and obese men receiving HF milkshakes, either high in saturated FAs (SFA), monounsaturated FAs (MUFA), or omega 3 (n-3) polyunsaturated FAs (PUFA). Plasma oxylipin profiles were significantly altered at 2 and 4 h after shake consumption when compared to baseline. Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) derived oxylipins increased after n-3 PUFA shake consumption. MUFA shake consumption increased levels of cytochrome P450 mediated oxylipins. SFA shake consumption led to strong increases in linoleic acid (LA) derived HODEs. No differences were observed between lean and obese individuals at baseline and after any shake consumption. CONCLUSION: We are the first demonstrating acute effects on circulating oxylipins after HF meal challenges. These changes were strongly influenced by different dietary FAs and may affect endothelial function.

Plasma oxylipin profiling identifies polyunsaturated vicinal diols as responsive to arachidonic acid and docosahexaenoic acid intake in growing piglets.

The dose-responsiveness of plasma oxylipins to incremental dietary intake of arachidonic acid (20:4n-6; ARA) and docosahexaenoic acid (22:6n-3; DHA) was determined in piglets. Piglets randomly received one of six formulas (n = 8 per group) from days 3 to 27 postnatally. Diets contained incremental ARA or incremental DHA levels as follows (% fatty acid, ARA/DHA): (A1) 0.1/1.0; (A2) 0.53/1.0; (A3-D3) 0.69/1.0; (A4) 1.1/1.0; (D1) 0.66/0.33; and (D2) 0.67/0.62, resulting in incremental intake (g/kg BW/day) of ARA: 0.07 ± 0.01, 0.43 ± 0.03, 0.55 ± 0.03, and 0.82 ± 0.05 at constant DHA intake (0.82 ± 0.05), or incremental intake of DHA: 0.27 ± 0.02, 0.49 ± 0.03, and 0.81 ± 0.05 at constant ARA intake (0.54 ± 0.04). Plasma oxylipin concentrations and free plasma PUFA levels were determined at day 28 using LC-MS/MS. Incremental dietary ARA intake dose-dependently increased plasma ARA levels. In parallel, ARA intake dose-dependently increased ARA-derived diols 5,6- and 14,15-dihydroxyeicosatrienoic acid (DiHETrE) and linoleic acid-derived 12,13-dihydroxyoctadecenoic acid (DiHOME), downstream metabolites of cytochrome P450 expoxygenase (CYP). The ARA epoxide products from CYP are important in vascular homeostatic maintenance. Incremental DHA intake increased plasma DHA and most markedly raised the eicosapentaenoic acid (EPA) metabolite 17,18-dihydroxyeicosatetraenoic acid (DiHETE) and the DHA metabolite 19,20-dihydroxydocosapentaenoic acid (DiHDPE). In conclusion, increasing ARA and DHA intake dose-dependently influenced endogenous n-6 and n-3 oxylipin plasma concentrations in growing piglets, although the biological relevance of these findings remains to be determined.

Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: towards metabolomics diagnostics.

Obesity is a risk factor for cardiovascular diseases and type 2 diabetes especially when the fat is accumulated to central depots. Novel biomarkers are crucial to develop diagnostics for obesity and related metabolic disorders. We evaluated the associations between metabolite profiles (136 lipid components, 12 lipoprotein subclasses, 17 low-molecular-weight metabolites, 12 clinical markers) and 28 phenotype parameters (including different body fat distribution parameters such as android (A), gynoid (G), abdominal visceral (VAT), subcutaneous (SAT) fat) in 215 plasma/serum samples from healthy overweight men (n=32) and women (n=83) with central obesity. (Partial) correlation analysis and partial least squares (PLS) regression analysis showed that only specific metabolites were associated to A:G ratio, VAT, and SAT, respectively. These association patterns were gender dependent. For example, insulin, cholesterol, VLDL, and certain triacylglycerols (TG 54:1-3) correlated to VAT in women, while in men VAT was associated with TG 50:1-5, TG 55:1, phosphatidylcholine (PC 32:0), and VLDL ((X)L). Moreover, multiple regression analysis revealed that waist circumference and total fat were sufficient to predict VAT and SAT in women. In contrast, only VAT but not SAT could be predicted in men and only when plasma metabolites were included, with PC 32:0 being most strongly associated with VAT. These findings collectively highlight the potential of metabolomics in obesity and that gender differences need to be taken into account for novel biomarker and diagnostic discovery for obesity and metabolic disorders.

Quantitative profiling of oxylipins through comprehensive LC-MS/MS analysis: application in cardiac surgery.

Oxylipins, including eicosanoids, affect a broad range of biological processes, such as the initiation and resolution of inflammation. These compounds, also referred to as lipid mediators, are (non-) enzymatically generated by oxidation of polyunsaturated fatty acids such as arachidonic acid (AA). A plethora of lipid mediators exist which makes the development of generic analytical methods challenging. Here we developed a robust and sensitive targeted analysis platform for oxylipins and applied it in a biological setting, using high performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS) operated in dynamic multiple reaction monitoring (dMRM). Besides the well-described AA metabolites, oxylipins derived from linoleic acid, dihomo-γ-linolenic acid, α-linolenic acid, eicosapentaenoic acid and docosahexaenoic acid were included. Our comprehensive platform allows the quantitative evaluation of approximately 100 oxylipins down to low nanomolar levels. Applicability of the analytical platform was demonstrated by analyzing plasma samples of patients undergoing cardiac surgery. Altered levels of some of the oxylipins, especially in certain monohydroxy fatty acids such as 12-HETE and 12-HEPE, were observed in samples collected before and 24 h after cardiac surgery. These findings indicate that this generic oxylipin profiling platform can be applied broadly to study these highly bioactive compounds in relation to human disease.

Between Metabolite Relationships: an essential aspect of metabolic change.

Not only the levels of individual metabolites, but also the relations between the levels of different metabolites may indicate (experimentally induced) changes in a biological system. Component analysis methods in current 'standard' use for metabolomics, such as Principal Component Analysis (PCA), do not focus on changes in these relations. We therefore propose the concept of 'Between Metabolite Relationships' (BMRs): common changes in the covariance (or correlation) between all metabolites in an organism. Such structural changes may indicate metabolic change brought about by experimental manipulation but which are lost with standard data analysis methods. These BMRs can be analysed by the INdividual Differences SCALing (INDSCAL) method. First the BMR quantification is described and subsequently the INDSCAL method. Finally, two studies illustrate the power and the applicability of BMRs in metabolomics. The first study is about the induced plant response of cabbage to herbivory, of which BMRs are a considerable part. In the second study-a human nutritional intervention study of green tea extract-standard data analysis tools did not reveal any metabolic change, although the BMRs were considerably affected. The presented results show that BMRs can be easily implemented in a wide variety of metabolomic studies. They provide a new source of information to describe biological systems in a way that fits flawlessly into the next generation of systems biology questions, dealing with personalized responses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0316-1) contains supplementary material, which is available to authorized users.

Dynamic transcriptional and metabolic responses in yeast adapting to temperature stress.

Understanding the response processes in cellular systems to external perturbations is a central goal of large-scale molecular profiling experiments. We investigated the molecular response of yeast to increased and lowered temperatures relative to optimal reference conditions across two levels of molecular organization: the transcriptome using a whole yeast genome microarray and the metabolome applying the gas chromatography/mass spectrometry (GC/MS) technology with in vivo stable-isotope labeling for accurate relative quantification of a total of 50 different metabolites. The molecular adaptation of yeast to increased or lowered temperatures relative control conditions at both the metabolic and transcriptional level is dominated by temperature-inverted differential regulation patterns of transcriptional and metabolite responses and the temporal response observed to be biphasic. The set of previously described general environmental stress response (ESR) genes showed particularly strong temperature-inverted response patterns. Among the metabolites measured, trehalose was detected to respond strongest to the temperature stress and with temperature-inverted up- and downregulation relative to control, midtemperature conditions. Although associated with the same principal environmental parameter, the two different temperature regimes caused very distinct molecular response patterns at both the metabolite and the transcript level. While pairwise correlations between different transcripts and between different metabolites were found generally preserved under the various conditions, substantial differences were also observed indicative of changed underlying network architectures or modified regulatory relationships. Gene and associated gene functions were identified that are differentially regulated specifically under the gradual stress induction applied here compared to abrupt stress exposure investigated in previous studies, including genes of as of yet unidentified function and genes involved in protein synthesis and energy metabolism.

Metabolic pathway relationships revealed by an integrative analysis of the transcriptional and metabolic temperature stress-response dynamics in yeast.

The integrated analysis of omics datasets covering different levels of molecular organization has become a central task of systems biology. We investigated the transcriptional and metabolic response of yeast exposed to increased (37 degrees C) and lowered (10 degrees C) temperatures relative to optimal reference conditions (28 degrees C) in the context of known metabolic pathways. Pairwise metabolite correlation levels were found to carry more pathway-related information and to extend to farther distances within the metabolic pathway network than associated transcript level correlations. Metabolites were detected to correlate stronger to their cognate transcripts (metabolite is reactant of the enzyme encoded by the transcript) than to more remote or randomly chosen transcripts reflecting their close metabolic relationship. We observed a pronounced temporal hierarchy between metabolic and transcriptional molecular responses under heat and cold stress. Changes of metabolites were most significantly correlated to transcripts encoding metabolic enzymes, when metabolites were considered leading in time-lagged correlation analyses. By applying the concept of Granger causality, we detected directed relationships between metabolites and their cognate transcripts. When interpreted as substrate-to-product directions, most of these directed Granger causality pairs agreed with the KEGG-annotated preferred reaction direction. Thus, the introduced Granger causality approach may prove useful for determining the preferred direction of metabolic reactions in cellular systems. The metabolites glutamic acid and serine were identified as central causative metabolites influencing transcript levels at later time points. Selected examples are presented illustrating the intertwined relationships between metabolites and transcripts in the yeast temperature stress adaptation process.

Retention index thresholds for compound matching in GC-MS metabolite profiling.

The generation of retention index (RI) libraries is an expensive and time-consuming effort. Procedures for the transfer of RI properties between chromatography variants are, therefore, highly relevant for a shared use. The precision of RI determination and accuracy of RI transfer between 8 method variants employing 5%-phenyl-95%-dimethylpolysiloxane capillary columns was investigated using a series of 9 n-alkanes (C(10)-C(36)). The precision of the RI determination of 13 exemplary fatty acid methyl esters (C(8) ME-C(30) ME) was 0.22-0.33 standard deviation (S.D.) expressed in RI units in low complexity samples. In the presence of complex biological matrices this precision may deteriorate to 0.75-1.11. Application of the previously proposed Kováts, van den Dool or 3rd-5th order polynomial regression algorithms resulted in similar precision of RI calculation. For transfer of empirical van den Dool-RI properties between the chromatography variants 3rd order regression was found to represent the minimal necessary assumption. The range of typical regression coefficients was r(2)=0.9988-0.9998 and accuracy of RI prediction between chromatography variants varied between 5.1 and 19.8 (0.29-0.69%) S.D. of residual RI error, RI(predicted)-RI(determined) (n>64). Accuracy of prediction was enhanced when subsets of chemically similar compound classes were used for regression, for example organic acids and sugars exhibited 0.78 (n=29) and 3.74 (n=37) S.D. of residual RI error, respectively. In conclusion, we suggest use of percent RI error rather than absolute RI units for the definition of matching thresholds. Thresholds of 0.5-1.0% may apply to most transfers between chromatography variants. These thresholds will not solve all matching ambiguities in complex samples. Therefore, we recommend co-analysis of reference substances with each GC-MS profiling experiment. Composition of these defined reference mixtures may best approximate or mimic the quantitative and qualitative composition of the biological matrix under investigation.

TagFinder for the quantitative analysis of gas chromatography--mass spectrometry (GC-MS)-based metabolite profiling experiments.

MOTIVATION: Typical GC-MS-based metabolite profiling experiments may comprise hundreds of chromatogram files, which each contain up to 1000 mass spectral tags (MSTs). MSTs are the characteristic patterns of approximately 25-250 fragment ions and respective isotopomers, which are generated after gas chromatography (GC) by electron impact ionization (EI) of the separated chemical molecules. These fragment ions are subsequently detected by time-of-flight (TOF) mass spectrometry (MS). MSTs of profiling experiments are typically reported as a list of ions, which are characterized by mass, chromatographic retention index (RI) or retention time (RT), and arbitrary abundance. The first two parameters allow the identification, the later the quantification of the represented chemical compounds. Many software tools have been reported for the pre-processing, the so-called curve resolution and deconvolution, of GC-(EI-TOF)-MS files. Pre-processing tools generate numerical data matrices, which contain all aligned MSTs and samples of an experiment. This process, however, is error prone mainly due to (i) the imprecise RI or RT alignment of MSTs and (ii) the high complexity of biological samples. This complexity causes co-elution of compounds and as a consequence non-selective, in other words impure MSTs. The selection and validation of optimal fragment ions for the specific and selective quantification of simultaneously eluting compounds is, therefore, mandatory. Currently validation is performed in most laboratories under human supervision. So far no software tool supports the non-targeted and user-independent quality assessment of the data matrices prior to statistical analysis. TagFinder may fill this gap. STRATEGY: TagFinder facilitates the analysis of all fragment ions, which are observed in GC-(EI-TOF)-MS profiling experiments. The non-targeted approach allows the discovery of novel and unexpected compounds. In addition, mass isotopomer resolution is maintained by TagFinder processing. This feature is essential for metabolic flux analyses and highly useful, but not required for metabolite profiling. Whenever possible, TagFinder gives precedence to chemical means of standardization, for example, the use of internal reference compounds for retention time calibration or quantitative standardization. In addition, external standardization is supported for both compound identification and calibration. The workflow of TagFinder comprises, (i) the import of fragment ion data, namely mass, time and arbitrary abundance (intensity), from a chromatography file interchange format or from peak lists provided by other chromatogram pre-processing software, (ii) the annotation of sample information and grouping of samples into classes, (iii) the RI calculation, (iv) the binning of observed fragment ions of equal mass from different chromatograms into RI windows, (v) the combination of these bins, so-called mass tags, into time groups of co-eluting fragment ions, (vi) the test of time groups for intensity correlated mass tags, (vii) the data matrix generation and (viii) the extraction of selective mass tags supported by compound identification. Thus, TagFinder supports both non-targeted fingerprinting analyses and metabolite targeted profiling. AVAILABILITY: Exemplary TagFinder workspaces and test data sets are made available upon request to the contact authors. TagFinder is made freely available for academic use from http://www-en.mpimp-golm.mpg.de/03-research/researchGroups/01-dept1/Root_Metabolism/smp/TagFinder/index.html.