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This study evaluated the validity of nutrient and food group intakes estimated by an FFQ against biomarkers. A 71-item semiquantitative FFQ was administered to 210 Brazilian children and adolescents aged 9–13 years. Intakes were correlated with biomarkers in plasma and red blood cells. Correlations between nutrients and their biomarkers were presented for animal protein, myristic acid (C14:0), EPA, DHA, β-carotene, folate, and vitamins B3, B5 and B6. Food groups and biomarkers were correlated as follows: fish products with EPA and DHA; milk and dairy with C14:0, pyridoxal 5'-phosphate and vitamin B12; total vegetables and dark green and orange vegetables with β-carotene; 5-methyltetrahydrofolate with green vegetables; and flour products with para-aminobenzoylglutamic acid. This FFQ is a valid tool for ranking Brazilian children and adolescents according to their intake of several nutrients and food groups.

Systems biology approaches have been increasingly employed in clinical studies to enhance our understanding of the role of genetics, environmental factors and their interactions on nutritional, health and disease status. Amongst the new omics technologies, metabonomics has emerged as a robust platform to capture metabolic and nutritional requirements by enabling, in a minimally invasive fashion, the monitoring of a wide range of biochemical compounds. Their variations reflect comprehensively the various molecular regulatory processes, which are tightly controlled and under the influence of genetics, diet, gut microbiota and other environmental factors. They are providing key insights into complex metabolic phenomena as well as into differences and specificities at individual and population level. The aim of this review is to evaluate promising metabolic insights towards understanding metabolism of a long and healthy life from pre-clinical and clinical metabonomics studies. We will also discuss analytical approaches to enable data integration, with an emphasis on the longitudinal component. Herein, we will illustrate current examples, challenges and perspectives in the applications of metabonomics monitoring and modelling approaches in the context of healthy ageing research.

Polyunsaturated fatty acids (PUFA) contained in fish oil (FO) are ligands for peroxisome proliferator-activated receptors (PPAR) that may induce changes in cardiometabolic markers. Variation in PPAR genes may influence the beneficial responses linked to FO supplementation in young adults. The study aimed to analyze the effect of FO supplementation on glucose metabolism, circulating lipids and inflammation according to PPARα L162V and PPARγ2 P12A genotypes in young Mexican adults. 191 young, non-smoking subjects between 18 and 40 years were included in a one-arm study. Participants were supplemented with 2.7 g/day of EPA+DHA, during six weeks. Dietary analysis, body composition measurements and indicators for glucose metabolism, circulating lipids, and markers for inflammation were analyzed before and after intervention. An overall decrease in triglycerides (TG) and an increase in HS-ω3 index were observed in all subjects [-4.1 mg/dL, (SD:±51.7), P=.02 and 2.6%, (SD:±1.2), P

Aim: There is increasing interest in the profiling and quantitation of methionine pathway metabolites for health management research. Currently, several analytical approaches are required to cover metabolites and co-factors. Results: We report the development and the validation of a method for the simultaneous detection and quantitation of 13 metabolites in red blood cells. The method, validated in a cohort of healthy human volunteers, shows a high level of accuracy and reproducibility. Conclusion: This high-throughput protocol provides a robust coverage of central metabolites and co-factors in one single analysis and in a high-throughput fashion. In large-scale clinical settings, the use of such an approach will significantly advance the field of nutritional research in health and disease.

In longitudinal clinical studies, methodologies available for the analysis of multivariate data with multivariate methods are relatively limited. Here, we present Consensus Clustering (CClust) a new computational method based on clustering of time profiles and posterior identification of correlation between clusters and predictors. Subjects are first clustered in groups according to a response variable temporal profile, using a robust consensus-based strategy. To discover which of the remaining variables are associated with the resulting groups, a non-parametric hypothesis test is performed between groups at every time point, and then the results are aggregated according to the Fisher method. Our approach is tested through its application to the EarlyBird cohort database, which contains temporal variations of clinical, metabolic, and anthropometric profiles in a population of 150 children followed-up annually from age 5 to age 16. Our results show that our consensus-based method is able to overcome the problem of the approach-dependent results produced by current clustering algorithms, producing groups defined according to Insulin Resistance (IR) and biological age (Tanner Score). Moreover, it provides meaningful biological results confirmed by hypothesis testing with most of the main clinical variables. These results position CClust as a valid alternative for the analysis of multivariate longitudinal data.

Scope: Quinic acid in its free form is broadly abundant in plants, and can accumulate in copious amounts in coffee, tea, and certain fruits. However, it has been mostly studied as chlorogenic acid, an ester of caffeic and quinic acids. When chlorogenic acid reaches the colon, it is hydrolyzed by microbial esterases releasing caffeic and quinic acids. While biotransformation of chlorogenic and caffeic acids have been elucidated by in vitro and in vivo studies, the gut metabolism of quinic acid has been so far overlooked. Methods and Results: [U-13C]-Quinic acid is submitted to a colonic model using human fecal microbiota for assessing its metabolic fate. The metabolite profiles formed along microbial biotransformation are monitored by a combined metabolomics approach, using both 2D GC– and ultra-HPLC–MS. Six metabolic intermediates are identified by incorporation of isotopic label. Conclusion: Two parallel degradation pathways could be proposed: (1) an oxidative route, leading to aromatization and accumulation of protocatechuic acid, and a (2) reductive route, including dehydroxylation to cyclohexane carboxylic acid. Elucidating the biotransformation of food bioactives by the gut microbiota is of relevance for understanding nutrition, interindividual variability and potential effects on human metabolism.

Background Hyperhomocysteinemia is a risk factor for cognitive decline and dementia, including Alzheimer disease (AD). Homocysteine (Hcy) is a sulfur-containing amino acid and metabolite of the methionine pathway. The interrelated methionine, purine, and thymidylate cycles constitute the one-carbon metabolism that plays a critical role in the synthesis of DNA, neurotransmitters, phospholipids, and myelin. In this study, we tested the hypothesis that one-carbon metabolites beyond Hcy are relevant to cognitive function and cerebrospinal fluid (CSF) measures of AD pathology in older adults. Methods Cross-sectional analysis was performed on matched CSF and plasma collected from 120 older community-dwelling adults with (n = 72) or without (n = 48) cognitive impairment. Liquid chromatography-mass spectrometry was performed to quantify one-carbon metabolites and their cofactors. Least absolute shrinkage and selection operator (LASSO) regression was initially applied to clinical and biomarker measures that generate the highest diagnostic accuracy of a priori-defined cognitive impairment (Clinical Dementia Rating-based) and AD pathology (i.e., CSF tau phosphorylated at threonine 181 [p-tau181]/β-Amyloid 1–42 peptide chain [Aβ1–42] >0.0779) to establish a reference benchmark. Two other LASSO-determined models were generated that included the one-carbon metabolites in CSF and then plasma. Correlations of CSF and plasma one-carbon metabolites with CSF amyloid and tau were explored. LASSO-determined models were stratified by apolipoprotein E (APOE) ε4 carrier status. Results The diagnostic accuracy of cognitive impairment for the reference model was 80.8% and included age, years of education, Aβ1–42, tau, and p-tau181. A model including CSF cystathionine, methionine, S-adenosyl-L-homocysteine (SAH), S-adenosylmethionine (SAM), serine, cysteine, and 5-methyltetrahydrofolate (5-MTHF) improved the diagnostic accuracy to 87.4%. A second model derived from plasma included cystathionine, glycine, methionine, SAH, SAM, serine, cysteine, and Hcy and reached a diagnostic accuracy of 87.5%. CSF SAH and 5-MTHF were associated with CSF tau and p-tau181. Plasma one-carbon metabolites were able to diagnose subjects with a positive CSF profile of AD pathology in APOE ε4 carriers. Conclusions We observed significant improvements in the prediction of cognitive impairment by adding one-carbon metabolites. This is partially explained by associations with CSF tau and p-tau181, suggesting a role for one-carbon metabolism in the aggregation of tau and neuronal injury. These metabolites may be particularly critical in APOE ε4 carriers. Electronic supplementary material The online version of this article (doi:10.1186/s13195-017-0270-x) contains supplementary material, which is available to authorized users.

Longitudinal studies aim typically at following populations of subjects over time and are important to understand the global evolution of biological processes. When it comes to longitudinal omics data, it will often depend on the overall objective of the study, and constraints imposed by the data, to define the appropriate modeling tools. Here, we report the use of multilevel simultaneous component analysis (MSCA), orthogonal projection on latent structures (OPLS), and regularized canonical correlation analysis (rCCA) to study associations between specific longitudinal urine metabonomics data and microbiome data in a diet-induced obesity model using C57BL/6 mice. (1)H NMR urine metabolic profiling was performed on samples collected weekly over a period of 13 weeks, and stool microbial composition was assessed using 16S rRNA gene sequencing at three specific time periods (baseline, first week response, end of study). MSCA and OPLS allowed us to explore longitudinal urine metabonomics data in relation to the dietary groups, as well as dietary effects on body weight. In addition, we report a data integration strategy based on regularized CCA and correlation analyses of urine metabonomics data and 16S rRNA gene sequencing data to investigate the functional relationships between metabolites and gut microbial composition. Thanks to this workflow enabling the breakdown of this data set complexity, the most relevant patterns could be extracted to further explore physiological processes at an anthropometric, cellular, and molecular level.

Objectives: Exclusive enteral nutrition (EEN) is one of the first-line therapeutic options for pediatric patients with active Crohn’s disease (CD). However, only sparse data exist on plasma metabolic changes from patients on EEN therapy. Thus to gain mechanistic insights, we have characterized selected markers in pediatric CD patients treated with EEN for induction of disease remission. Methods: Plasma levels of 18 cytokines and chemokines and 163 metabolites in 10 pediatric CD patients receiving 8 weeks of EEN therapy were measured. Measurements were performed at three time points: a) at baseline (V0); b) during EEN intervention at week 4 (V4) and; c) at 4 weeks after completion of EEN therapy at week 12 (V12). Results: Comparisons between V0 and V4 levels identified changes in 20 different molecules, including increases in 7 metabolites of the diacyl phosphatidylcholine (PC) class and 6 metabolites of the alkylacyl PC class. However, most of these changes were not sustained after returning to a normal diet, i.e. only 7 out of the 20 molecules with significant changes between V0 and V4 still retained significance upon comparing V0 and V12. Conclusions: The changes in the plasma levels of various phospholipids at different time-points reflect the nutritional intervention and improved health status of pediatric CD patients.

The Brazilian Healthy Eating Index-Revised (BHEI-R) can be used to determine overall dietary patterns. We assessed the BHEI-R scores in children and adolescents, aged from 9 to 13 years old, and associated its component scores with biomarkers of health and dietary exposure. Three 24-h recalls were used to generate BHEI-R. Biomarkers were analyzed in plasma and red blood cells. Correlation tests, agreement, and covariance analyses were used to associate BHEI-R components with biomarkers. Data from 167 subjects were used. The strongest correlations were between fruits, vegetables and legumes with omega-6 and omega-3 fatty acids, and β-carotene intakes. Milk and dairy correlated with plasma retinol and pyridoxine. All components rich in vegetable and animal protein sources correlated with plasma creatine. Total BHEI-R scores were positively associated with intakes of omega-6, omega-3, fiber and vitamin C, and inversely associated with energy and saturated fat intakes of individuals. Plasma β-carotene and riboflavin biomarkers were positively associated with total BHEI-R. An inadequate food consumption pattern was captured by both biomarkers of health and dietary exposure. BHEI-R was validated for the above dietary components and can be associated with metabolomics and nutritional epidemiological data in future pediatric studies.

The aging phenotype in humans has been thoroughly studied but a detailed metabolic profiling capable of shading light on the underpinning biological processes of longevity is still missing. Here using a combined metabonomics approach compromising holistic 1H-NMR profiling and targeted MS approaches, we report for the first time the metabolic phenotype of longevity in a well characterized human aging cohort compromising mostly female’s centenarian, elderly, and young individuals. Within increasing age targeted MS profiling of blood serum displayed a marked decrease in tryptophan concentration, while an unique alteration of specific glycerophospholipids and sphingolipids are seen in the longevity phenotype.We hypothesized that the overall lipidome changes specific to longevity putatively reflect centenarians’ unique capacity to adapt/respond to the accumulating oxidative and chronic inflammatory conditions characteristics of their extreme aging phenotype. Our data in centenarians support promotion of a cellular detoxification mechanisms through specific modulation of the arachidonic acid metabolic cascade as we underpinned increased concentration of 8,9-EpETrE, suggesting enhanced cytochrome P450 (CYP) enzyme activity. Such effective mechanism might results in the activation of an anti-oxidative response, as displayed by decreased circulating levels of 9-HODE, and 9-oxoODE, markers of lipid peroxidation and oxidative products of linoleic acid. Lastly, we also revealed that the longevity process deeply affects the structure and composition of the human gut microbiota as shown by the increased extrection of phenylacetylglutamine (PAG) and p-cresol sulfate (PCS) in urine of centenarians. Together, our novel approach in this representative Italian longevity cohort support the hypothesis that a complex remodeling of lipid, amino acid metabolism, and of gut microbiota functionality are key regulatory processes marking exceptional longevity in humans.

A global metabolic profiling methodology based on gas chromatography coupled to time of flight mass spectrometry (GC TOFMS) for human plasma was applied to a human exercise study focused on the effects of beverages containing glucose galactose or fructose taken after exercise and throughout a recovery period of 6. h and 45. min. One group of 10 well trained male cyclists performed 3 experimental sessions on separate days (randomized single center). After performing a standardized depletion protocol on a bicycle subjects consumed one of three different beverages: maltodextrin (MD). +. glucose (2:1 ratio) MD. +. galactose (2:1) and MD. +. fructose (2:1) consumed at an average of 1.25. g of carbohydrate (CHO) ingested per minute. Blood was taken straight after exercise and every 45. min within the recovery phase. With the resulting blood plasma insulin free fatty acid (FFA) profile glucose and GC TOFMS global metabolic profiling measurements were performed. The resulting profiling data was able to match the results obtained from the other clinical measurements with the addition of being able to follow many different metabolites throughout the recovery period. The data quality was assessed with all the labelled internal standards yielding values of

Background Dietary long-chain polyunsaturated fatty acids (LC-PUFA) are of crucial importance for the development of neural tissues. The aim of this study was to evaluate the impact of a dietary supplementation in n-3 fatty acids in female rats during gestation and lactation on fatty acid pattern in brain glial cells phosphatidylethanolamine (PE) and phosphatidylserine (PS) in the neonates. Methods Sprague-Dawley rats were fed during the whole gestation and lactation period with a diet containing either docosahexaenoic acid (DHA, 0.55%) and eicosapentaenoic acid (EPA, 0.75% of total fatty acids) or α-linolenic acid (ALA, 2.90%). At two weeks of age, gastric content and brain glial cell PE and PS of rat neonates were analyzed for their fatty acid and dimethylacetal (DMA) profile. Data were analyzed by bivariate and multivariate statistics. Results In the neonates from the group fed with n-3 LC-PUFA, the DHA level in gastric content (+65%, P < 0.0001) and brain glial cell PE (+18%, P = 0.0001) and PS (+15%, P = 0.0009) were significantly increased compared to the ALA group. The filtered correlation analysis (P < 0.05) underlined that levels of dihomo-γ-linolenic acid (DGLA), DHA and n-3 docosapentaenoic acid (DPA) were negatively correlated with arachidonic acid (ARA) and n-6 DPA in PE of brain glial cells. No significant correlation between n-3 and n-6 LC-PUFA were found in the PS dataset. DMA level in PE was negatively correlated with n-6 DPA. DMA were found to occur in brain glial cell PS fraction; in this class DMA level was correlated negatively with DHA and positively with ARA. Conclusion The present study confirms that early supplementation of maternal diet with n-3 fatty acids supplied as LC-PUFA is more efficient in increasing n-3 in brain glial cell PE and PS in the neonate than ALA. Negative correlation between n-6 DPA, a conventional marker of DHA deficiency, and DMA in PE suggests n-6 DPA that potentially be considered as a marker of tissue ethanolamine plasmalogen status. The combination of multivariate and bivariate statistics allowed to underline that the accretion pattern of n-3 LC-PUFA in PE and PS differ.

The methionine cycle is a key pathway contributing to the regulation of human health, with well-established involvement in cardiovascular diseases and cognitive function. Changes in one-carbon cycle metabolites have also been associated with mild cognitive decline, vascular dementia, and Alzheimer’s disease. Today, there is no single analytical method to monitor both metabolites and co-factors of the methionine cycle. To address this limitation, we here report for the first time a new method for the simultaneous quantitation of 17 metabolites in the methionine cycle, which are homocysteic acid, taurine, serine, cysteine, glycine, homocysteine, riboflavin, methionine, pyridoxine, cystathionine, pyridoxamine, S-adenosylhomocysteine, S-adenosylmethionine, betaine, choline, dimethylglycine, and 5-methyltetrahydrofolic acid. This multianalyte method, developed using ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS), provides a highly accurate and precise quantitation of these 17 metabolites for both plasma and cerebrospinal fluid metabolite monitoring. The method requires a simple sample preparation, which, combined with a short chromatographic run time, ensures a high sample throughput. This analytical strategy will thus provide a novel metabolomics approach to be employed in large-scale observational and intervention studies. We expect such a robust method to be particularly relevant for broad and deep molecular phenotyping of individuals in relation to their nutritional requirements, health monitoring, and disease risk management. Electronic supplementary material The online version of this article (doi:10.1007/s00216-016-0003-1) contains supplementary material, which is available to authorized users.

Summary Lysine acetylation is involved in various biological processes and is considered a key reversible post-translational modification in the regulation of gene expression, enzyme activity, and subcellular localization. This post-translational modification is therefore highly relevant in the context of circadian biology, but its characterization on the proteome-wide scale and its circadian clock dependence are still poorly described. Here, we provide a comprehensive and rhythmic acetylome map of the mouse liver. Rhythmic acetylated proteins showed subcellular localization-specific phases that correlated with the related metabolites in the regulated pathways. Mitochondrial proteins were over-represented among the rhythmically acetylated proteins and were highly correlated with SIRT3-dependent deacetylation. SIRT3 activity being nicotinamide adenine dinucleotide (NAD)+ level-dependent, we show that NAD+ is orchestrated by both feeding rhythms and the circadian clock through the NAD+ salvage pathway but also via the nicotinamide riboside pathway. Hence, the diurnal acetylome relies on a functional circadian clock and affects important diurnal metabolic pathways in the mouse liver., Graphical Abstract, Highlights • Phase of daily acetylated proteins is subcellular localization-dependent • Mitochondrial proteins are over-represented among the rhythmically acetylated proteins • Acetylated mitochondrial protein are enriched in SIRT3 targets • Circadian clock regulates the NAD+-dependent SIRT3 activity through the NR pathway, Mauvoisin et al. provide a rhythmic acetylome map of the mouse liver. Rhythmic acetylated proteins showed subcellular localization-specific phases with an over-representation of SIRT3 targets. Feeding rhythms and the circadian clock regulate NAD+ synthesis through the salvage and nicotinamide riboside pathways, affecting metabolite accumulation.

Summary Nuclear magnetic resonance (NMR)-based metabolomics is widely used to obtain metabolic fingerprints of biological systems. While targeted workflows require previous knowledge of metabolites, prior to statistical analysis, untargeted approaches remain a challenge. Computational tools dealing with fully untargeted NMR-based metabolomics are still scarce or not user-friendly. Therefore, we developed AlpsNMR (Automated spectraL Processing System for NMR), an R package that provides automated and efficient signal processing for untargeted NMR metabolomics. AlpsNMR includes spectra loading, metadata handling, automated outlier detection, spectra alignment and peak-picking, integration and normalization. The resulting output can be used for further statistical analysis. AlpsNMR proved effective in detecting metabolite changes in a test case. The tool allows less experienced users to easily implement this workflow from spectra to a ready-to-use dataset in their routines. Availability and implementation The AlpsNMR R package and tutorial is freely available to download from http://github.com/sipss/AlpsNMR under the MIT license. Supplementary information Supplementary data are available at Bioinformatics online.