Alterations in visceral adipose tissue (VAT) are closely linked to cardiometabolic abnormalities. The aim of this work is to define a metabolic signature in VAT of insulin resistance (IR) dependent on, and independent of, obesity. An untargeted UPLC-Q-Exactive metabolomic approach was carried out on the VAT of obese insulin-sensitive (IS) and insulin-resistant subjects (N = 11 and N = 25, respectively) and nonobese IS and IR subjects (N = 25 and N = 10, respectively). The VAT metabolome in obesity was defined among other things by changes in the metabolism of lipids, nucleotides, carbohydrates, and amino acids, whereas when combined with high IR, it affected the metabolism of 18 carbon fatty acyl-containing phospholipid species. A multimetabolite model created by glycerophosphatidylinositol (18:0); glycerophosphatidylethanolamine (18:2); glycerophosphatidylserine (18:0); and glycerophosphatidylcholine (18:0/18:1), (18:2/18:2), and (18:2/18:3) exhibited a highly predictive performance to identify the metabotype of "insulin-sensitive obesity" among obese individuals [area under the curve (AUC) 96.7% (91.9-100)] and within the entire study population [AUC 87.6% (79.0-96.2)]. We demonstrated that IR has a unique and shared metabolic signature dependent on, and independent of, obesity. For it to be used in clinical practice, these findings need to be validated in a more accessible sample, such as blood.

16 Metabolomic studies aimed to dissect the connection between the development of type 2 diabetes and 17 obesity are still scarce. In the present study, fasting serum from sixty-four adult individuals classified 18 into four sexmatched groups by their BMI [non-obese versus morbid obese] and the increased risk of 19 developing diabetes [prediabetic insulin resistant state versus non-prediabetic non-insulin resistant] 20 was analyzed by LCand FIAESIMS/MS–driven metabolomic approaches. Altered levels of 21 [lyso]glycerophospholipids was the most specific metabolic trait associated to morbid obesity, 22 particularly lysophosphatidylcholines acylated with margaric, oleic and linoleic acids [lysoPC C17:0: 23 R = −0.56, p = 0.0003; lysoPC C18:1: R = −0.61, p = 0.0001; lysoPC C18:2 R = −0.64, p b 0.0001]. 24 Several amino acidswere biomarkers of risk of diabetes onset associated to obesity. For instance, 25 glutamate significantly associatedwith fasting insulin [R=0.5, p=0.0019] and HOMA-IR [R=0.46, 26 p=0.0072],while glycine showed negative associations [fasting insulin: R = −0.51, p = 0.0017; 27 HOMA-IR: R = −0.49, p = 0.0033], and the branched chain amino acid valine associated to 28 prediabetes and insulin resistance in a BMI-independentmanner [fasting insulin: R=0.37, 29 p=0.0479;HOMA-IR: R=0.37, p=0.0468].Minority sphingolipids including specific 30 [dihydro]ceramides and sphingomyelins also associated with the prediabetic insulin resistant state, 31 hence deserving attention as potential targets for early diagnosis or therapeutic intervention. 32

Scope The association between self-reported dietary intake and urinary metabolomic markers of habitual nut exposure with cognitive decline over a 3-year follow-up in an older Italian population is prospectively evaluated. Methods and results A total of 119 older participants are selected, based on self-referred nut intake: the non-nut consumer (n = 72) and the regular consumer (>= 2.9 g d(-1), n = 47). Nut exposure is measured at baseline either with the use of a validated food frequency questionnaire or with an HPLC-Q-ToF-MS metabolomic approach. Three years after, 28 from the nonconsumers and 10 from the consumers experienced cognitive decline. Dietary nut exposure is characterized by urinary metabolites of polyphenols and fatty acids pathways. Nut consumption estimated either by the dietary marker or by the urinary marker model is in both cases associated with less cognitive decline (OR: 0.78, 95% CI: 0.61,0.99; p = 0.043 and OR: 0.995, 95% CI: 0.991,0.999; p = 0.016, respectively) with AUCs 73.2 (95% CI: 62.9, 83.6) and 73.1 (62.5, 83.7), respectively. Conclusions A high intake of nuts may protect older adults from cognitive decline. Metabolomics provides accurate and complementary information of the nut exposure and reinforces the results obtained using dietary information.

Background: Bioinformatic tools for the enrichment of 'omics' datasets facilitate interpretation and understanding of data. To date few are suitable for metabolomics datasets. The main objective of this work is to give a critical overview, for the first time, of the performance of these tools. To that aim, datasets from metabolomic repositories were selected and enriched data were created. Both types of data were analysed with these tools and outputs were thoroughly examined. Results: An exploratory multivariate analysis of the most used tools for the enrichment of metabolite sets, based on a non-metric multidimensional scaling (NMDS) of Jaccard's distances, was performed and mirrored their diversity. Codes (identifiers) of the metabolites of the datasets were searched in different metabolite databases (HMDB, KEGG, PubChem, ChEBI, BioCyc/HumanCyc, LipidMAPS, ChemSpider, METLIN and Recon2). The databases that presented more identifiers of the metabolites of the dataset were PubChem, followed by METLIN and ChEBI. However, these databases had duplicated entries and might present false positives. The performance of over-representation analysis (ORA) tools, including BioCyc/HumanCyc, ConsensusPathDB, IMPaLA, MBRole, MetaboAnalyst, Metabox, MetExplore, MPEA, PathVisio and Reactome and the mapping tool KEGGREST, was examined. Results were mostly consistent among tools and between real and enriched data despite the variability of the tools. Nevertheless, a few controversial results such as differences in the total number of metabolites were also found. Disease-based enrichment analyses were also assessed, but they were not found to be accurate probably due to the fact that metabolite disease sets are not up-to-date and the difficulty of predicting diseases from a list of metabolites. Conclusions: We have extensively reviewed the state-of-the-art of the available range of tools for metabolomic datasets, the completeness of metabolite databases, the performance of ORA methods and disease-based analyses. Despite the variability of the tools, they provided consistent results independent of their analytic approach. However, more work on the completeness of metabolite and pathway databases is required, which strongly affects the accuracy of enrichment analyses. Improvements will be translated into more accurate and global insights of the metabolome.

This study explores the metabolic profiles of concordant/discordant phenotypes of high insulin resistance (IR) and obesity. Through untargeted metabolomics (LC-ESI-QTOF-MS), we analyzed the fasting serum of subjects with high IR and/or obesity ( n = 64). An partial least-squares discriminant analysis with orthogonal signal correction followed by univariate statistics and enrichment analysis allowed exploration of these metabolic profiles. A multivariate regression method (LASSO) was used for variable selection and a predictive biomarker model to identify subjects with high IR regardless of obesity was built. Adrenic acid and a dyglyceride (DG) were shared by high IR and obesity. Uric and margaric acids, 14 DGs, ketocholesterol, and hydroxycorticosterone were unique to high IR, while arachidonic, hydroxyeicosatetraenoic (HETE), palmitoleic, triHETE, and glycocholic acids, HETE lactone, leukotriene B4, and two glutamyl-peptides to obesity. DGs and adrenic acid differed in concordant/discordant phenotypes, thereby revealing protective mechanisms against high IR also in obesity. A biomarker model formed by DGs, uric and adrenic acids presented a high predictive power to identify subjects with high IR [AUC 80.1% (68.9-91.4)]. These findings could become relevant for diabetes risk detection and unveil new potential targets in therapeutic treatments of IR, diabetes, and obesity. An independent validated cohort is needed to confirm these results.

The exact impact of bariatric surgery in metabolically "healthy" (MH) or "unhealthy" (MU) phenotypes for the study of the metabolic improvement is still unknown. We applied an untargeted LC-ESI-TripleTOF-MS-driven metabolomics approach in serum samples from 39 patients with morbid obesity (MH and MU) 1, 3, and 6 months after bariatric surgery. Multiple factor analysis, along with correlation and enrichment analyses, was carried out to distinguish those metabolites associated with metabolic improvement. Hydroxypropionic acids, medium-/long-chain hydroxy fatty acids, and bile acid glucuronides were the most discriminative biomarkers of response between MH and MU phenotypes. Hydroxypropionic (hydroxyphenyllactic-related) acids, amino acids, and glycerolipids were the most significant clusters of metabolites altered after bariatric surgery in MU ( p < 0.001). After surgery, MU and MH changed toward a common metabolic state 3 months after surgery. We observed a negative correlation with changes in waist circumference and cholesterol levels with metabolites of lipid metabolism. Glycemic variables were correlated with hexoses, which, in turn, correlated with gluconic acid and amino acid metabolism. Finally, we noted that hydroxyphenyllactic acid was associated with amino acid and lipid metabolism. Microbial metabolism of amino acid and BA glucuronidation pathways may be the key points of metabolic rearrangement after surgery.

OBJECTIVE:Bariatric surgery is considered the most efficient treatment for morbid obesity and its related diseases. However, its role as a metabolic modifier is not well understood. We aimed to determine biosignatures of response to bariatric surgery and elucidate short-term metabolic adaptations.METHODS:We used a LC- and FIA-ESI-MS/MS approach to quantify acylcarnitines, (lyso)phosphatidylcholines, sphingomyelins, amino acids, biogenic amines and hexoses in serum samples of subjects with morbid obesity (n = 39) before and 1, 3 and 6 months after bariatric surgery. K-means cluster analysis allowed to distinguish metabotypes of response to bariatric surgery.RESULTS:For the first time, global metabolic changes following bariatric surgery independent of the baseline health status of the subjects have been revealed. We identify two metabolic phenotypes (metabotypes) at the interval 6 months-baseline after surgery, which presented differences in the levels of compounds of urea metabolism, gluconeogenic precursors and (lyso)phospholipid particles. Clinically, metabotypes were different in terms of the degree of improvement in insulin resistance, cholesterol, low-density lipoproteins and uric acid independent of the magnitude of weight loss.CONCLUSIONS:This study opens new perspectives and new hypotheses on the metabolic benefits of bariatric surgery and understanding of the biology of obesity and its associated diseases.

Dietary polyphenols have been recently proposed as activators of the AMP-activated protein kinase (AMPK) signaling pathway and this fact might explain the relationship between the consumption of polyphenol-rich foods and the slowdown of the progression of aging. In the present work, the effects of strawberry consumption were evaluated on biomarkers of oxidative damage and on aging-associated reductions in mitochondrial function and biogenesis for 8weeks in old rats. Strawberry supplementation increased antioxidant enzyme activities, mitochondrial biomass and functionality, and decreased intracellular ROS levels and biomarkers of protein, lipid and DNA damage (P<0.05). Furthermore, a significant (P<0.05) increase in the expression of the AMPK cascade genes, involved in mitochondrial biogenesis and antioxidant defences, was also detected after strawberry intake. These in vivo results were then verified in vitro on HepG2 cells, confirming the involvement of AMPK in the beneficial effects exerted by strawberry against aging progression.

Polyphenols play an important role in human health. To address their accessibility to a breastfed infant, we planned to evaluate whether breast milk (BM) (colostrum, transitional, and mature) epicatechin metabolites could be related to the dietary habits of mothers. The polyphenol consumption of breastfeeding mothers was estimated using a food frequency questionnaire and 24 h recalls. Solid-phase extraction-ultra performance liquid chromatography-tandem mass spectrometry (SPE-UPLC-MS/MS) was applied for direct epicatechin metabolite analysis. Their bioavailability in BM as a result of dietary ingestion was confirmed in a preliminary experiment with a single dose of dark chocolate. Several host and microbial phase II metabolites of epicatechin were detected in BM among free-living lactating mothers. Interestingly, a modest correlation between dihydroxyvalerolactone sulfate and the intake of cocoa products was observed. Although a very low percentage of dietary polyphenols is excreted in BM, they are definitely in the diet of breastfed infants. Therefore, evaluation of their role in infant health could be further promoted.

ScopeTomato contains a variety of phenolics associated with health-promoting properties. However, the effects of processing and the addition of oil during tomato sauce preparation on microbial metabolism of phenolics in the small intestine are still unclear.Methods and resultsAn open, controlled, randomized, and crossover feeding trial with 40 healthy volunteers was carried out to analyze the metabolites in plasma and urine after the consumption of tomato and tomato sauces, with tomato sauce enriched with refined olive oil (ROOE) and without refined olive oil (oil-free: OF). Ten phenolics in plasma and 93 metabolites in urine were quantified. Processing tomatoes into sauce enhanced the bioavailability of flavanones, flavanols, and some hydroxycinnamic acids, as reflected by the increase in the area under the plasma concentration versus time curve. An increase in their plasma half-life was also observed, particularly after ingestion of ROOE, possibly favored by enterohepatic circulation. A wide variety of gut microbial metabolites was also detected, namely flavanones, hydroxycinnamic acids, flavonols, hydroxyphenylpropanoic acids, hydroxyphenylacetic acids, and hydroxybenzoic acids.ConclusionsFlavanones and flavonols in ROOE presented higher bioavailability, suggesting that the processing undergone by the raw tomato improved their absorption.

Metabolomic studies aimed to dissect the connection between the development of type 2 diabetes and obesity are still scarce. In the present study, fasting serum from sixty-four adult individuals classified into four sex-matched groups by their BMI [non-obese versus morbid obese] and the increased risk of developing diabetes [prediabetic insulin resistant state versus non-prediabetic non-insulin resistant] was analyzed by LC- and FIA-ESI-MS/MS-driven metabolomic approaches. Altered levels of [lyso]glycerophospholipids was the most specific metabolic trait associated to morbid obesity, particularly lysophosphatidylcholines acylated with margaric, oleic and linoleic acids [lysoPC C17:0: R=-0.56, p=0.0003; lysoPC C18:1: R=-0.61, p=0.0001; lysoPC C18:2 R=-0.64, p<0.0001]. Several amino acids were biomarkers of risk of diabetes onset associated to obesity. For instance, glutamate significantly associated with fasting insulin [R=0.5, p=0.0019] and HOMA-IR [R=0.46, p=0.0072], while glycine showed negative associations [fasting insulin: R=-0.51, p=0.0017; HOMA-IR: R=-0.49, p=0.0033], and the branched chain amino acid valine associated to prediabetes and insulin resistance in a BMI-independent manner [fasting insulin: R=0.37, p=0.0479; HOMA-IR: R=0.37, p=0.0468]. Minority sphingolipids including specific [dihydro]ceramides and sphingomyelins also associated with the prediabetic insulin resistant state, hence deserving attention as potential targets for early diagnosis or therapeutic intervention.

Objective: To review the metabolomic studies carried out so far to identify metabolic markers associated with surgical and dietary treatments for weight loss in subjects with obesity.Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed.Results: Thirty-two studies successfully met the eligibility criteria. The metabolic adaptations shared by surgical and dietary interventions mirrored a state of starvation ketoacidosis (increase of circulating ketone bodies), an increase of acylcarnitines and fatty acid beta-oxidation, a decrease of specific amino acids including branched-chain amino acids (BCAA) and (lyso)glycerophospholipids previously associated with obesity, and adipose tissue expansion. The metabolic footprint of bariatric procedures was specifically characterized by an increase of bile acid circulating pools and a decrease of ceramide levels, a greater perioperative decline in BCAA, and the rise of circulating serine and glycine, mirroring glycemic control and inflammation improvement. In one study, 3-hydroxybutyrate was particularly identified as an early metabolic marker of long-term prognosis after surgery and proposed to increase current prognostic modalities and contribute to personalized treatment.Conclusions: Metabolomics helped in deciphering the metabolic response to weight loss treatments. Moving from association to causation is the next challenge to move to a further level of clinical application.

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC–q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread ( n = 56), white-bread consumers ( n = 48) and whole-grain bread consumers ( n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N -α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1–86.4 %) to 93.7 % (89.4–98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6–69.7 %) to 78.4 % (69.8–87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Tomato sauce is the most commonly consumed processed tomato product worldwide, but very little is known about how the manufacturing process may affect the phenolic composition and bioavailability after consumption. In a prospective randomised, cross-over intervention study, we analysed the plasma and urinary levels of tomato phenolic compounds and their metabolites after acute consumption of raw tomatoes and tomato sauce, enriched or not with refined olive oil during production. Respectively, eleven and four phenolic metabolites were found in urine and plasma samples. The plasma concentration and urinary excretion of naringenin glucuronide were both significantly higher after the consumption of tomato sauce than raw tomatoes. The results suggest that the mechanical and thermal treatments during tomato sauce manufacture may help to deliver these potentially bioactive phenolics from the food matrix more effectively than the addition of an oil component, thus increasing their bioavailability.

Metabolic characterization of type 2 diabetes mellitus (T2DM) is crucial for the identification of individuals at risk for developing diabetes and T2DM-related vascular complications as well as for monitoring disease progression. The application of metabolomics to diabetes research may lead to the identification and discovery of diagnostic and prognostic T2DM biomarkers, in addition to elucidating disease pathways. In the present review, we summarize the distinct classes of metabolites that have been proposed as potential biomarkers for progressing stages of T2DM by metabolomic approaches. Several studies have demonstrated that the metabolism of carbohydrates, lipids, and amino acids is considerably altered in prediabetes and continue to vary over the course of T2DM progression. The identification of intermediate metabolites involved in glycolysis, gluconeogenesis, the tricarboxylic acid cycle, lipolysis, and proteolysis have provided evidence of these metabolic dysfunctions. Finally, given the increasing worldwide incidence of T2DM and its related complications, research should focus on the impact of lifestyle factors, particularly diet, at the metabolomic level for better understanding and improved healthcare strategies.

An UHPLC-MS/MS method for the quantification of tomato phenolic metabolites in human fluids was optimized and validated, and then applied in a pilot dietary intervention study with healthy volunteers. A 5-fold gain in speed (3.5 min of total run); 7-fold increase in MS sensitivity and 2-fold greater efficiency (50% peak width reduction) were observed when comparing the proposed method with the reference-quality HPLC-MS/MS system, whose assay performance has been previously documented. The UHPLC-MS/MS method led to an overall improvement in the limits of detection (LOD) and quantification (LOQ) for all the phenolic compounds studied. The recoveries ranged between 68% and 100% in urine and 61% and 100% in plasma. The accuracy; intra- and interday precision; and stability met with the acceptance criteria of the AOAC International norms. Due to the improvements in the analytical method; the total phenolic metabolites detected in plasma and urine in the pilot intervention study were 3 times higher than those detected by HPLC-MS/MS. Comparing with traditional methods; which require longer time of analysis; the methodology described is suitable for the analysis of phenolic compounds in a large number of plasma and urine samples in a reduced time frame.

Although LC-MS untargeted metabolomics continues to expand into exiting research domains, methodological issues have not been solved yet by the definition of unbiased, standardized and globally accepted analytical protocols. In the present study, the response of the plasma metabolome coverage to specific methodological choices of the sample preparation (two SPE technologies, three sample-to-solvent dilution ratios) and the LC-ESI-MS data acquisition steps of the metabolomics workflow (four RP columns, four elution solvent combinations, two solvent quality grades, postcolumn modification of the mobile phase) was investigated in a pragmatic and decision tree-like performance evaluation strategy. Quality control samples, reference plasma and human plasma from a real nutrimetabolomic study were used for intermethod comparisons. Uni- and multivariate data analysis approaches were independently applied. The highest method performance was obtained by combining the plasma hybrid extraction with the highest solvent proportion during sample preparation, the use of a RP column compatible with 100% aqueous polar phase (Atlantis T3), and the ESI enhancement by using UHPLC-MS purity grade methanol as both organic phase and postcolumn modifier. Results led to the following considerations: submit plasma samples to hybrid extraction for removal of interfering components to minimize the major sample-dependent matrix effects; avoid solvent evaporation following sample extraction if loss in detection and peak shape distortion of early eluting metabolites are not noticed; opt for a RP column for superior retention of highly polar species when analysis fractionation is not feasible; use ultrahigh quality grade solvents and "vintage" analytical tricks such as postcolumn organic enrichment of the mobile phase to enhance ESI efficiency. The final proposed protocol offers an example of how novel and old-fashioned analytical solutions may fruitfully cohabit in untargeted metabolomics protocols.