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Over the past decade, the analysis of metabolic data with advanced chemometric techniques has offered the potential to explore functional relationships among biological compartments in relation to the structure and function of the intestine. However, the employed methodologies, generally based on regression modeling techniques, have given emphasis to region-specific metabolic patterns, while providing only limited insights into the spatiotemporal metabolic features of the complex gastrointestinal system. Hence, novel approaches are needed to analyze metabolic data to reconstruct the metabolic biological space associated with the evolving structures and func6ons of an organ such as the gastrointestinal tract. Here, we report the application of multivariate curve resolution (MCR) methodology to model metabolic relationships along the gastrointestinal compartments in relation to its structure and function using data from our previous metabonomic analysis. The method simultaneously summarizes metabolite occurrence and contribution to continuous metabolic signatures of the different biological compartments of the gut tract. This methodology sheds new light onto the complex web of metabolic interac6ons with gut symbionts that modulate host cell metabolism in surrounding gut tissues. In the future, such an approach will be key to provide new insights into the dynamic onset of metabolic deregulations involved in region-specific gastrointestinal disorders, such as Crohn's disease or ulcerative colitis. 10.1021/ac102015n

In this article we highlight a novel variation on dynamic time warping (DTW) for aligning chromatogram signals. We are interested in sets of signals that can be aligned well locally, but not globally, by shifting individual signals in time. This kind of alignment is often sufficient for aligning gas chromatography data. Regular DTW often 'over-warps' signals and introduces artificial features into the aligned data. To overcome this we introduce a variable penalty into the DTW process. The penalty is added to the distance metric whenever a nondiagonal step is taken. We select our penalty based on a morphological dilation of the two signals. We showcase our method by aligning GC/MS datafiles from 712 blood plasma samples processed in 23 batches over the course of 6 months. The use of variable penalty DTW significantly reduces the number of nondiagonal moves. In the examples presented here, this reduction is by a factor of 30, with no cost to visual quality of the alignment.

The rapid development of nutrition science is embracing digital transformation to generate large amounts of data. Precision nutrition and "Big Data" place increasing demand for data repositories and visualization, which enhances the digital transformation. We defined the need for an integrated nutrition data platform as a web-based platform that can collect, store, track, analyze, monitor, and visually display key metrics in nutrition and health while allowing users to interact with visuals and download data provided in the platform. Interactive dashboards create new opportunities for scholars and practitioners to generate and test hypotheses. We present the development and implementation of the Global Nutrition and Health Atlas (GNHA; https://sites.tufts.edu/gnha/), an open-access online platform covering nutrition and health data with 26 themes and 500+ indicators from 190+ countries up to 30 y. We view GNHA as an interactive tool aiming to share information and perspectives and foster collaborations and innovations. [ABSTRACT FROM AUTHOR]

Abstract 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.

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. [ABSTRACT FROM AUTHOR]

Aging is a dynamic process depending on intrinsic and extrinsic factors and its evolution is a continuum of transitions, involving multifaceted processes at multiple levels. It is recognized that frailty and sarcopenia are shared by the major age-related diseases thus contributing to elderly morbidity and mortality. Pre-frailty is still not well understood but it has been associated with global imbalance in several physiological systems, including inflammation, and in nutrition. Due to the complex phenotypes and underlying pathophysiology, the need for robust and multidimensional biomarkers is essential to move toward more personalized care. The objective of the present study was to better characterize the complexity of pre-frailty phenotype using untargeted metabolomics, in order to identify specific biomarkers, and study their stability over time. The approach was based on the NU-AGE project (clinicaltrials.gov, NCT01754012) that regrouped 1,250 free-living elderly people (65–79 y.o., men and women), free of major diseases, recruited within five European centers. Half of the volunteers were randomly assigned to an intervention group (1-year Mediterranean type diet). Presence of frailty was assessed by the criteria proposed by Fried et al. (2001). In this study, a sub-cohort consisting in 212 subjects (pre-frail and non-frail) from the Italian and Polish centers were selected for untargeted serum metabolomics at T0 (baseline) and T1 (follow-up). Univariate statistical analyses were performed to identify discriminant metabolites regarding pre-frailty status. Predictive models were then built using linear logistic regression and ROC curve analyses were used to evaluate multivariate models. Metabolomics enabled to discriminate sub-phenotypes of pre-frailty both at the gender level and depending on the pre-frailty progression and reversibility. The best resulting models included four different metabolites for each gender. They showed very good prediction capacity with AUCs of 0.93 (95% CI = 0.87–1) and 0.94 (95% CI = 0.87–1) for men and women, respectively. Additionally, early and/or predictive markers of pre-frailty were identified for both genders and the gender specific models showed also good performance (three metabolites; AUC = 0.82; 95% CI = 0.72–0.93) for men and very good for women (three metabolites; AUC = 0.92; 95% CI = 0.86–0.99). These results open the door, through multivariate strategies, to a possibility of monitoring the disease progression over time at a very early stage. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. 1H 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. [ABSTRACT FROM AUTHOR]

Objectives A lipidomic approach was employed in a clinically well-defined cohort of healthy obese women to explore blood lipidome phenotype ascribed to body fat deposition, with emphasis on epicardial adipose tissue (EAT). Methods The present investigation delivered a lipidomics signature of epicardial adiposity under healthy clinical conditions using a cohort of 40 obese females (age: 25-45 years, BMI: 28-40 kg/m2) not showing any metabolic disease traits. Lipidomics analysis of blood plasma was employed in combination with in vivo quantitation of mediastinal fat depots by computerized tomography. Results All cardiac fat depots correlated to indicators of hepatic dysfunctions (ALAT and ASAT), which describe physiological connections between hepatic and cardiac steatosis. Plasma lipidomics encompassed overall levels of lipid classes, fatty acid profiles, and individual lipid species. EAT and visceral fat associated with diacylglycerols (DAG), triglycerides, and distinct phospholipid and sphingolipid species. A pattern of DAG and phosphoglycerols was specific to EAT. Conclusions Human blood plasma lipidomics appears to be a promising clinical and potentially diagnostic readout for patient stratification and monitoring. Association of blood lipidomics signature to regio-specific mediastinal and visceral adiposity under healthy clinical conditions may help provide more biological insights into obese patient stratification for cardiovascular disease risks. [ABSTRACT FROM AUTHOR]

Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on 1H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10−8) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10−44) and lysine (rs8101881, P = 1.2×10−33), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn's disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers. [ABSTRACT FROM AUTHOR]

Visceral adiposity is increasingly recognized as a key condition for the development of obesity related disorders, with the ratio between visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) reported as the best correlate of cardiometabolic risk. In this study, using a cohort of 40 obese females (age: 25–45 y, BMI: 28–40 kg/m2) under healthy clinical conditions and monitored over a 2 weeks period we examined the relationships between different body composition parameters, estimates of visceral adiposity and blood/urine metabolic profiles. Metabonomics and lipidomics analysis of blood plasma and urine were employed in combination with in vivo quantitation of body composition and abdominal fat distribution using iDXA and computerized tomography. Of the various visceral fat estimates, VAT/SAT and VAT/total abdominal fat ratios exhibited significant associations with regio-specific body lean and fat composition. The integration of these visceral fat estimates with metabolic profiles of blood and urine described a distinct amino acid, diacyl and ether phospholipid phenotype in women with higher visceral fat. Metabolites important in predicting visceral fat adiposity as assessed by Random forest analysis highlighted 7 most robust markers, including tyrosine, glutamine, PC-O 44∶6, PC-O 44∶4, PC-O 42∶4, PC-O 40∶4, and PC-O 40∶3 lipid species. Unexpectedly, the visceral fat associated inflammatory profiles were shown to be highly influenced by inter-days and between-subject variations. Nevertheless, the visceral fat associated amino acid and lipid signature is proposed to be further validated for future patient stratification and cardiometabolic health diagnostics. [ABSTRACT FROM AUTHOR]

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 centenarians, elderly, and young individuals. With 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 characteristic of their extreme aging phenotype. Our data in centenarians support promotion of 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 result 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. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWASs) have become a very important tool to address the genetic origin of phenotypic variability, in particular associated with diseases. Nevertheless, these types of studies provide limited information about disease etiology and the molecular mechanisms involved. Recently, the incorporation of metabolomics into the analysis has offered novel opportunities for a better understanding of disease-related metabolic deregulation. The pattern emerging from this work is that gene-driven changes in metabolism are prevalent and that common genetic variations can have a profound impact on the homeostatic concentrations of specific metabolites. A particularly interesting aspect of this work takes into account interactions of environment and lifestyle with the genome and how this interaction translates into changes in the metabolome. For instance, the role of PYROXD2 in trimethylamine metabolism points to an interaction between host and microbiome genomes (host/microbiota). Often, these findings reveal metabolic deregulations, which could eventually be tuned with a nutritional intervention. Here we review the development of gene-metabolism association studies from a single-gene/single-metabolite to a genome-wide/metabolome-wide approach and highlight the conceptual changes associated with this ongoing transition. Moreover, we report some of our recent GWAS results on a cohort of 265 individuals from an ethnically diverse population that validate and refine previous findings on gene-urine metabolism interactions. Specifically, our results confirm the effect of PYROXD2 polymorphisms on trimethylamine metabolism and suggest that a previously reported association of N-acetylated compounds with the ALMS1/NAT8 locus is driven by SNPs in the ALMS1 gene. [ABSTRACT FROM AUTHOR]

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-g-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. [ABSTRACT FROM AUTHOR]

Previous studies have shown that the dietary diversity of young Filipino children to be limited and that the prevalence of nutrient inadequacies is high. This study extends the current knowledge to examine the relationship between diet diversity and the probability of adequacy of micronutrients among Filipino schoolchildren (aged 6 to 12 years), by the wealth status and dwelling location. The dietary intake data were collected using a single 24-h recall from 6460 children in the Filipino National Nutrition Survey 2013. The diet diversity score (DDS) and the probability of adequacies (PA) of 11 micronutrients were calculated, and further stratified by socio-economic status (SES) and dwelling location. The diet diversity was generally low (mean DDS = 4 out of 9). Children from the lowest SES, and living in rural areas, tended to have a lower DDS. Children with a DDS of 1 were likely to be inadequate in all 11 micronutrients. The higher DDS (≥6) was associated with higher PAs for the B vitamins but not for calcium, folate, iron, vitamin A and to large extent, vitamin C. This suggests that it was difficult for this population to achieve adequacy in these 5 micronutrients. More rigorous research on the topic is needed. Better access to nutrient-rich or fortified staple foods, in tandem with increased education on the importance of dietary diversity, are potential strategies to support children in achieving adequate micronutrient intakes. [ABSTRACT FROM AUTHOR]

Background:‘You are what you eat’ is an accurate summary for humans and animals when it comes to carbon isotope abundance. In biological material, natural13C/12C ratio is subject to minute variations due to diet composition (mainly from ingestion of C3 and C4 metabolism plants) and to the discrimination between ‘light’ and ‘heavy’ isotopes during biochemical reactions (isotope effects and isotopic fractionation). Methodology/Principal Findings:Carbon isotopic abundance was measured in ZDF (fa/+) and ZDF (fa/fa), (lean and obese-diabetic rats respectively) fed the same diet. By analysing plasma metabolites (glucose and non-esterified fatty acids), breath and liver tissue by high-precision isotope ratio mass spectrometry, we demonstrate for the first time statistically distinguishable metabolic carbon isotope abundance between ZDF (fa/+) and ZDF (fa/fa) rats based on plasma glucose, palmitic, oleic, linoleic, arachidonic acids and bulk analysis of liver tissue (P<0.005) resulting into clear isotopic fingerprints using principal component analysis. We studied the variation of isotopic abundance between both groups for each metabolite and through the metabolic pathways using the precursor/product approach. We confirmed that lipids were depleted in 13C compared to glucose in both genotypes. We found that isotopic abundance of linoleic acid (C18: 2n-6), even though both groups had the same feed, differed significantly between both groups. The likely reason for these changes between ZDF (fa/+) and ZDF (fa/fa) are metabolic dysregulation associated with various routing and fluxes of metabolites. Conclusion/Significance:This work provides evidence that measurement of natural abundance isotope ratio of both bulk tissue and individual metabolites can provide meaningful information about metabolic changes either associated to phenotype or to genetic effects; irrespective of concentration. In the future measuring the natural abundance δ13C of key metabolites could be used as endpoints for studying in vivo metabolism, especially with regards to metabolic dysregulation, and development and progression of metabolic diseases. [ABSTRACT FROM AUTHOR]

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<.001 respectively]. Mean fasting insulin and glycated hemoglobin (HbA1c%) were significantly decreased in all subjects [-0.547mlU/L, (SD:±10.29), P=.034 and-0.07%, (SD:±0.3), P<.001 respectively], whereas there was no change in body composition, fasting glucose, adiponectin and inflammatory markers. Subjects carrying the minor alleles of PPARα L162V and PPARγ2 P12A had higher responses in reduction of TG and fasting insulin respectively. Interestingly, doses below 2.7 g/day (1.8 g/day) were sufficient to induce a significant reduction in fasting insulin and HbA1c% from baseline (P=.019 and P<.001). The observed responses in triglycerides and fasting insulin in the Mexican population give further evidence of the importance of FO supplementation in young people as an early step towards the prevention of cardiometabolic disease. [ABSTRACT FROM AUTHOR]