Discovery and validation of urinary exposure markers for different plant foods by untargeted metabolomics

The Future of Obesity Management through Precision Nutrition: Putting the Individual at the Center

PURPOSE OF REVIEW: The prevalence of obesity continues to rise steadily. While obesity management typically relies on dietary and lifestyle modifications, individual responses to these interventions vary widely. Clinical guidelines for overweight and obesity stress the importance of personalized approaches to care. This review aims to underscore the role of precision nutrition in delivering tailored interventions for obesity management. RECENT FINDINGS: Recent technological strides have expanded our ability to detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal in analyzing intricate genomic data. Machine learning algorithms can also predict postprandial glucose, triglyceride, and insulin levels, facilitating customized dietary interventions and ultimately leading to successful weight loss. Additionally, given that adherence to dietary recommendations is one of the key predictors of weight loss success, employing more objective methods for dietary assessment and monitoring can enhance sustained long-term compliance. Biomarkers of food intake hold promise for a more objective dietary assessment. Acknowledging the multifaceted nature of obesity, precision nutrition stands poised to transform obesity management by tailoring dietary interventions to individuals' genetic backgrounds, gut microbiota, metabolic profiles, and behavioral patterns. However, there is insufficient evidence demonstrating the superiority of precision nutrition over traditional dietary recommendations. The integration of precision nutrition into routine clinical practice requires further validation through randomized controlled trials and the accumulation of a larger body of evidence to strengthen its foundation.

Persistent Biofluid Small-Molecule Alterations Induced by Trypanosoma cruzi Infection Are Not Restored by Parasite Elimination

Chagas disease (CD), caused by Trypanosoma cruzi (T. cruzi) protozoa, is a complicated parasitic illness with inadequate medical measures for diagnosing infection and monitoring treatment success. To address this gap, we analyzed changes in the metabolome of T. cruzi-infected mice via liquid chromatography tandem mass spectrometry of clinically accessible biofluids: saliva, urine, and plasma. Urine was the most indicative of infection status across mouse and parasite genotypes. Metabolites perturbed by infection in urine include kynurenate, acylcarnitines, and threonylcarbamoyladenosine. Based on these results, we sought to implement urine as a tool for the assessment of CD treatment success. Strikingly, it was found that mice with parasite clearance following benznidazole antiparasitic treatment had an overall urine metabolome comparable to that of mice that failed to clear parasites. These results provide a complementary hypothesis to explain clinical trial data in which benznidazole treatment did not improve patient outcomes in late-stage disease, even in patients with successful parasite clearance. Overall, this study provides insights into new small-molecule-based CD diagnostic methods and a new approach to assess functional responses to treatment.

Metabolomic based approach to identify biomarkers of broccoli intake

It is well-established that consumption of cruciferous and brassica vegetables has a correlation with reduced rates of many negative health outcomes. There is an increased interest in identifying food intake biomarkers to address limitations related to self-reported dietary assessment. The study aims to identify biomarkers of broccoli intake using metabolomic approaches, examine the dose-response relationship, and predict the intake by multimarker panel. Eighteen volunteers consumed cooked broccoli in A-Diet Discovery study and fasting and postprandial urine samples were collected at 2, 4 and 24 hours. Subsequently the A-Diet Dose-response study was performed where volunteers consumed different portions of broccoli (49, 101 or 153 g) and urine samples were collected at the end of each intervention week. Urine samples were analysed by 1H-NMR and LC-MS. Multivariate data analysis and one-way ANOVA were performed to identify discriminating biomarkers. A panel of putative biomarkers was examined for its ability to predict intake through a multiMarker model. Multivariate analysis revealed discriminatory spectral regions between fasting and fed metabolic profiles. Subsequent time-series plots revealed multiple features increased in concentration following the consumption. Urinary S-methyl cysteine sulfoxide (SMCSO) increased as broccoli intake increased (0.17-0.24 μM per mOSM per kg, p < 0.001). Similarly from LC-MS data genipin, dihydro-β-tubaic acid and sinapic acid increased with increasing portions of intake. A panel of 8 features displayed good ability to predict intake from biomarker data only. In conclusion, urinary SMCSO and several LC-MS features appeared as potentially promising biomarkers of broccoli consumption and demonstrated dose-response relationship. Future work should focus on validating these compounds as food intake biomarkers.

Integrating (Nutri-)Metabolomics into the One Health Tendency-The Key for Personalized Medicine Advancement

Metabolomics is an advanced technology, still under development, with multiple research applications, especially in the field of health. Individual metabolic profiles, the functionality of the body, as well as its interaction with the environment, can be established using this technology. The body's response to various external factors, including the food consumed and the nutrients it contains, has increased researchers' interest in nutrimetabolomics. Establishing correlations between diet and the occurrence of various diseases, or even the development of personalized nutrition plans, could contribute to advances in precision medicine. The interdependence between humans, animals, and the environment is of particular importance today, with the dramatic emergence and spread of zoonotic diseases, food, water and soil contamination, and the degradation of resources and habitats. All these events have led to an increase in risk factors for functional diseases, burdening global health. Thus, this study aimed to highlight the importance of metabolomics, and, in particular, nutrimetabolomics, as a technical solution for a holistic, collaborative, and precise approach for the advancement of the One Health strategy.

Persistent biofluid small molecule alterations induced by Trypanosoma cruzi infection are not restored by antiparasitic treatment

Chagas Disease (CD), caused by Trypanosoma cruzi (T. cruzi) protozoa, is a complicated parasitic illness with inadequate medical measures for diagnosing infection and monitoring treatment success. To address this gap, we analyzed changes in the metabolome of T. cruzi-infected mice via liquid chromatography tandem mass spectrometry analysis of clinically-accessible biofluids: saliva, urine, and plasma. Urine was the most indicative of infection status, across mouse and parasite genotypes. Metabolites perturbed by infection in the urine include kynurenate, acylcarnitines, and threonylcarbamoyladenosine. Based on these results, we sought to implement urine as a tool for assessment of CD treatment success. Strikingly, it was found that mice with parasite clearance following benznidazole antiparasitic treatment had comparable overall urine metabolome to mice that failed to clear parasites. These results match with clinical trial data in which benznidazole treatment did not improve patient outcomes in late-stage disease. Overall, this study provides insights into new small molecule-based CD diagnostic methods and a new approach to assess functional treatment response.

Metabolic Biomarkers of Red Beetroot Juice Intake at Rest and after Physical Exercise

BACKGROUND

Red beetroot is known to be a health-promoting food. However, little attention is placed on intestinal bioactive compound absorption. The aim of the study was to assess the urinary red beetroot juice (RBJ) intake biomarkers and possible differences in RBJ's micronutrient absorption at rest or after physical exercise.

METHODS

This is a three-armed, single-blind study, involving seven healthy volunteers which were randomly divided into three groups and alternatively assigned to three experimental sessions: RBJ intake at rest, RBJ intake with physical activity, and placebo intake with physical activity. For each session, urine samples were collected before and 120, 180, and 240 min after the intake of RBJ or placebo. The same sampling times were employed for the experimental session at rest. The RBJ metabolic composition was also characterized to identify the urinary biomarkers derived from the intake.

RESULTS

4-methylpyridine-2-carboxylic acid, dopamine-3-O-sulfate, glutamine, and 3-hydroxyisobutyrate were identified as RBJ intake biomarkers. Physical activity significantly increased only the dopamine-3-O-sulfate excretion 120 min after RBJ intake.

CONCLUSIONS

Urinary dopamine-3-O-sulfate is related to RBJ dopamine content, while 4-methylpyridine-2-carboxylic acid is a betanin or betalamic acid catabolite. The different excretions of these metabolites following physical activity suggest a possible effect on the RBJ uptake depending on different transport processes through the mucosa, namely diffusion-mediated transport for dopamine and saturable transcellular transport for betalamic acid derivatives. These results open new perspectives in improving the absorption of natural bioactive molecules through physical activity.

Almond Consumption for 8 Weeks Altered Host and Microbial Metabolism in Comparison to a Control Snack in Young Adults

Almond consumption can improve cardiometabolic (CM) health. However, the mechanisms underlying those benefits are not well characterized. This study explored the effects of consuming a snack of almonds vs. crackers for 8 weeks on changes in metabolomic profiles in young adults (clinicaltrials.gov ID: NCT03084003).

Participants (n = 73, age: 18-19 years, BMI: 18-41 kg/m2) were randomly assigned to consume either almonds (2 oz/d, n = 38) or an isocaloric control snack of graham crackers (325 kcal/d, n = 35) daily for 8 weeks. Blood samples were collected at baseline prior to and at 4 and 8 weeks after the intervention. Metabolite abundances in the serum were quantified by hydrophilic interaction chromatography quadrupole (Q) time-of-flight (TOF) mass spectrometry (MS/MS), gas chromatography (GC) TOF MS, CSH-ESI (electrospray) QTOF MS/MS, and targeted analyses for free PUFAs, total fatty acids, oxylipins and endocannabinoids. Linear mixed model analyses with baseline-adjustment were conducted, and those results were used for enrichment and network analyses. Microbial community pathway predictions from 16S rRNA sequencing of fecal samples was done using PICRUST2.

Almond consumption enriched unsaturated triglycerides, unsaturated phosphatidylcholines, saturated and unsaturated lysophosphatidylcholines, tricarboxylic acids, and tocopherol clusters (p < 0.05). Targeted analyses reveal lower levels of omega-3 total fatty acids (TFAs) overall in the almond group compared to the cracker group (p < 0.05). Microbial amino acid biosynthesis, and amino sugar and nucleotide sugar metabolism pathways were also differentially enriched at the end of the intervention (p < 0.05).

The study demonstrates the differential effects of almonds on host tocopherol, lipid, and TCA cycle metabolism with potential changes in microbial metabolism, which may interact with host metabolism to facilitate the CM benefits.

Fecal Metabolites as Biomarkers for Predicting Food Intake by Healthy Adults

BACKGROUND

The fecal metabolome is affected by diet and includes metabolites generated by human and microbial metabolism. Advances in -omics technologies and analytic approaches have allowed researchers to identify metabolites and better utilize large data sets to generate usable information. One promising aspect of these advancements is the ability to determine objective biomarkers of food intake.

OBJECTIVES

We aimed to utilize a multivariate, machine learning approach to identify metabolite biomarkers that accurately predict food intake.

METHODS

Data were aggregated from 5 controlled feeding studies in adults that tested the impact of specific foods (almonds, avocados, broccoli, walnuts, barley, and oats) on the gastrointestinal microbiota. Fecal samples underwent GC-MS metabolomic analysis; 344 metabolites were detected in preintervention samples, whereas 307 metabolites were detected postintervention. After removing metabolites that were only detected in either pre- or postintervention and those undetectable in ≥80% of samples in all study groups, changes in 96 metabolites relative concentrations (treatment postintervention minus preintervention) were utilized in random forest models to 1) examine the relation between food consumption and fecal metabolome changes and 2) rank the fecal metabolites by their predictive power (i.e., feature importance score).

RESULTS

Using the change in relative concentration of 96 fecal metabolites, 6 single-food random forest models for almond, avocado, broccoli, walnuts, whole-grain barley, and whole-grain oats revealed prediction accuracies between 47% and 89%. When comparing foods with one another, almond intake was differentiated from walnut intake with 91% classification accuracy.

CONCLUSIONS

Our findings reveal promise in utilizing fecal metabolites as objective complements to certain self-reported food intake estimates. Future research on other foods at different doses and dietary patterns is needed to identify biomarkers that can be applied in feeding study compliance and clinical settings.

Metabolomics application for the design of an optimal diet

Precision nutrition is an emerging branch of nutrition science that aims to use modern omics technologies (genomics, proteomics, and metabolomics) to assess an individual's response to specific foods or dietary patterns and thereby determine the most effective diet or lifestyle interventions to prevent or treat specific diseases. Metabolomics is vital to nearly every aspect of precision nutrition. It can be targeted or untargeted, and it has many applications. Indeed, it can be used to comprehensively characterize the thousands of chemicals in foods, identify food by-products in human biofluids or tissues, characterize nutrient deficiencies or excesses, monitor biochemical responses to dietary interventions, track long- or short-term dietary habits, and guide the development of nutritional therapies. Indeed, metabolomics can be coupled with genomics and proteomics to study and advance the field of precision nutrition. Integrating omics with epidemiological and clinical data will begin to define the beneficial effects of human food metabolites. In this review, we present the metabolome and its relationship to precision nutrition. Moreover, we describe the different techniques used in metabolomics and present how metabolomics has been applied to advance the field of precision nutrition by providing notable examples and cases.

Biomarkers of Fruit Intake Using a Targeted Metabolomics Approach: an Observational Cross-Sectional Analysis of the ELSA-Brasil Study

BACKGROUND

Advances in technology have led to the identification of a greater number of metabolites related to diet. Although fruit intake biomarkers have been reported in some studies, these findings require further replication, considering the relevance of fruits for diet quality and health.

OBJECTIVES

The aim of this study was to explore the associations of a set of potential urinary biomarkers of diet, assessed using a targeted metabolomics approach, with self-reported fruit intake data in participants of a computer-assisted 24-h dietary recall (GloboDiet software) validation study.

METHODS

A total of 93 individuals aged 43-72 y, 54% female, participated in this study. The subjects were a subsample of the Longitudinal Study of Adult Health (ELSA-Brasil). A 24-h dietary recall was obtained with the aid of GloboDiet software matching a 24-h urine sample from each participant. Candidate biomarkers were selected in a literature search and identified in urine by LC coupled to high-resolution MS. Spearman correlation analyses were performed between fruit intake and each biomarker.

RESULTS

Spearman correlation analysis showed that total fruits intake was significantly correlated with citric acid (ρ = 0.213, P = 0.041), ferulic acid sulfate I (ρ = 0.240, P = 0.020), hesperetin glucuronide/homoeriodictyol glucuronide (ρ = 0.303, P = 0.003), hydroxyhippuric acid (ρ = 0.239, P = 0.021), homovanillic alcohol sulfate (ρ = 0.339, P = 0.001), methylgallic acid sulfate (ρ = 0.268, P = 0.009), naringenin glucuronide (NG; ρ = 0.278, P = 0.007), proline betaine (PB; ρ = 0.305, P = 0.003), syringic acid sulfate (ρ = 0.210, P = 0.044), and sinapic acid sulfate (ρ = 0.412, P < 0.001). Among them, 3 have been described in literature as promising biomarkers for intake of total fruit, oranges, and citrus fruit: NG, hesperetin glucuronide, and PB.

CONCLUSIONS

Associations of total fruits intake with urinary measurements indicate the potential usefulness of dietary biomarkers in the Brazilian population as a complement to self-reported dietary assessments.

Nutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review

Recent advances in metabolomics allow for more objective assessment of contemporary food exposures, which have been proposed as an alternative or complement to self-reporting of food intake. However, the quality of evidence supporting the utility of dietary biomarkers as valid measures of habitual intake of foods or complex dietary patterns in diverse populations has not been systematically evaluated. We reviewed nutritional metabolomics studies reporting metabolites associated with specific foods or food groups; evaluated the interstudy repeatability of dietary biomarker candidates; and reported study design, metabolomic approach, analytical technique(s), and type of biofluid analyzed. A comprehensive literature search of 5 databases (PubMed, EMBASE, Web of Science, BIOSIS, and CINAHL) was conducted from inception through December 2020. This review included 244 studies, 169 (69%) of which were interventional studies (9 of these were replicated in free-living participants) and 151 (62%) of which measured the metabolomic profile of serum and/or plasma. Food-based metabolites identified in ≥1 study and/or biofluid were associated with 11 food-specific categories or dietary patterns: 1) fruits; 2) vegetables; 3) high-fiber foods (grain-rich); 4) meats; 5) seafood; 6) pulses, legumes, and nuts; 7) alcohol; 8) caffeinated beverages, teas, and cocoas; 9) dairy and soya; 10) sweet and sugary foods; and 11) complex dietary patterns and other foods. We conclude that 69 metabolites represent good candidate biomarkers of food intake. Quantitative measurement of these metabolites will advance our understanding of the relation between diet and chronic disease risk and support evidence-based dietary guidelines for global health.

A synthetic consortium of 100 gut commensals modulates the composition and function in a colon model of the microbiome of elderly subjects

Administration of cultured gut isolates holds promise for modulating the altered composition and function of the microbiota in older subjects, and for promoting their health. From among 692 initial isolates, we selected 100 gut commensal strains (MCC100) based on emulating the gut microbiota of healthy subjects, and retaining strain diversity within selected species. MCC100 susceptibility to seven antibiotics was determined, and their genomes were screened for virulence factor, antimicrobial resistance and bacteriocin genes. Supplementation of healthy and frail elderly microbiota types with the MCC100 in an in vitro colon model increased alpha-diversity, raised relative abundance of taxa including Blautia luti, Bacteroides fragilis, and Sutterella wadsworthensis; and introduced taxa such as Bifidobacterium spp. Microbiota changes correlated with higher levels of branched chain amino acids, which are health-associated in elderly. The study establishes that the MCC100 consortium can modulate older subjects' microbiota composition and associated metabolome in vitro, paving the way for pre-clinical and human trials.

Analyses of serum and urinary metabolites in individuals with peripheral artery disease (PAD) consuming a bean-rich diet: Relationships with drug metabolites

Peripheral artery disease (PAD) has high morbidity and mortality rates. A metabolomics approach was employed to determine whether consumption of bean-rich diets for 8 weeks would impact the metabolomic profile of PAD individuals. Serum and urine, collected from 54 participants with clinical PAD at baseline and after 8 weeks on 0.3 cups beans/d (n=19), 0.6 cups beans/d (n= 20), or control (n=23) diet, and the beans were extracted and analyzed using LC-QTOF-MS. As a result, PGE2 p-acetamidophenyl ester, PGF2α diethyl amide and 5-L-glutamyl-L-alanine were significantly changed in the serum or urine of bean groups compared to control. Significant changes (P<0.05) in the profile and/or levels of 22 flavonoids present in bean extracts showed the potential importance of the mixture of beans used in this study. In a subset of participants taking metoprolol, after 8 weeks the bean-rich diets significantly elevated metoprolol in the serum while reducing it in urine compared to baseline. In addition, the diets significantly enhanced the urinary excretion of metformin. In conclusion, several biochemical pathways including prostaglandins and glutathione were affected by bean consumption. Significant changes in the metabolism of metoprolol and metformin with bean consumption suggested the presence of diet-drug interactions that may require adjustment of the prescribed dose. ClinicalTrials.gov Identifier: NCT01382056 Novelty: • Bean consumption by people with PAD alters the levels of certain metabolites in serum and urine • Different bean types (black, red kidney, pinto, navy) have unique flavonoid profiles • Metabolomics revealed potential diet-dug interactions as serum and/or urinary levels of metoprolol and metformin are modified by bean consumption.

Odd Chain Fatty Acids Are Not Robust Biomarkers for Dietary Intake of Fiber

SCOPE

Prior investigation has suggested a positive association between increased colonic propionate production and circulating odd-chain fatty acids (OCFAs; pentadecanoic acid [C15:0], heptadecanoic acid [C17:0]). As the major source of propionate in humans is the microbial fermentation of dietary fiber, OCFAs have been proposed as candidate biomarkers of dietary fiber. The objective of this study is to critically assess the plausibility, robustness, reliability, dose-response, time-response aspects of OCFAs as potential biomarkers of fermentable fibers in two independent studies using a validated analytical method.

METHODS AND RESULTS

OCFAs are first assessed in a fiber supplementation study, where 21 participants received 10 g dietary fiber supplementation for 7 days. OCFAs are then assessed in a highly controlled inpatient setting, which 19 participants consumed a high fiber (45.1 g per day) and a low fiber diet (13.6 g per day) for 4 days. Collectively in both studies, dietary intakes of fiber as fiber supplementations or having consumed a high fiber diet do not increase circulating levels of OCFAs. The dose and temporal relations are not observed.

CONCLUSION

Current study has generated new insight on the utility of OCFAs as fiber biomarkers and highlighted the importance of critical assessment of candidate biomarkers before application.

New-onset vegetarian diet shows differences in fatty acid metabolites in European American and African American women

BACKGROUND AND AIMS

The type of fat consumed in animal-based western diets, typically rich in the saturated fat palmitate, has been implicated in cardiometabolic disease risk. In contrast, the most abundant mono- and polyunsaturated fats, more typical in a vegetarian or plant-based diet, potentiate less deleterious effects. This study determined differences in plasma and urine metabolites when switching from omnivorous to vegetarian diet, including metabolites involved in fatty acid utilization.

METHODS AND RESULTS

A prospective cohort of 38 European (EA) and African American (AA) omnivorous females were matched by age (25.7 ± 5.3y) and BMI (22.4 ± 1.9 kg/m²). Pre-intervention samples were collected while subjects consumed habitual animal-based diet. Changes in metabolites were assessed by ultra-high-performance liquid chromatography-tandem mass spectroscopy (Metabolon, Inc.) upon completing four days of novel vegetarian diet provided by the Vanderbilt Metabolic Kitchen. Changes in several diet-derived metabolites were observed, including increases in compounds derived from soy food metabolism along with decreases in metabolites of xanthine and histidine. Significant changes occurred in metabolites of saturated, monounsaturated and polyunsaturated fatty acids along with significant differences between EA and AA women in changes in plasma concentrations of acylcarnitines, which reflect the completeness of fatty acid oxidation (versus storage).

CONCLUSION

These data suggest improvements in fatty acid metabolism (oxidation vs storage), a key factor in energy homeostasis, may be promoted rapidly by adoption of a vegetarian (plant-based) diet. Mechanistic differences in response to diet interventions must be understood to effectively provide protection against the widespread development of obesity and cardiometabolic disease in population subgroups, such as AA women.

A systematic review to identify biomarkers of intake for fermented food products

Background

Fermented foods are ubiquitous in human diets and often lauded for their sensory, nutritious, and health-promoting qualities. However, precise associations between the intake of fermented foods and health have not been well-established. This is in part due to the limitations of current dietary assessment tools that rely on subjective reporting, making them prone to memory-related errors and reporting bias. The identification of food intake biomarkers (FIBs) bypasses this challenge by providing an objective measure of intake. Despite numerous studies reporting on FIBs for various types of fermented foods and drinks, unique biomarkers associated with the fermentation process (“fermentation-dependent” biomarkers) have not been well documented. We therefore conducted a comprehensive, systematic review of the literature to identify biomarkers of fermented foods commonly consumed in diets across the world.

Results

After title, abstract, and full-text screening, extraction of data from 301 articles resulted in an extensive list of compounds that were detected in human biofluids following the consumption of various fermented foods, with the majority of articles focusing on coffee (69), wine (69 articles), cocoa (62), beer (34), and bread (29). The identified compounds from all included papers were consolidated and sorted into FIBs proposed for a specific food, for a food group, or for the fermentation process. Alongside food-specific markers (e.g., trigonelline for coffee), and food-group markers (e.g., pentadecanoic acid for dairy intake), several fermentation-dependent markers were revealed. These comprised compounds related to the fermentation process of a particular food, such as mannitol (wine), 2-ethylmalate (beer), methionine (sourdough bread, cheese), theabrownins (tea), and gallic acid (tea, wine), while others were indicative of more general fermentation processes (e.g., ethanol from alcoholic fermentation, 3-phenyllactic acid from lactic fermentation).

Conclusions

Fermented foods comprise a heterogeneous group of foods. While many of the candidate FIBs identified were found to be non-specific, greater specificity may be observed when considering a combination of compounds identified for individual fermented foods, food groups, and from fermentation processes. Future studies that focus on how fermentation impacts the composition and nutritional quality of food substrates could help to identify novel biomarkers of fermented food intake.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12263-021-00686-4.

Identification and Reproducibility of Urinary Metabolomic Biomarkers of Habitual Food Intake in a Cross-Sectional Analysis of the Cancer Prevention Study-3 Diet Assessment Sub-Study

Previous cross-sectional metabolomics studies have identified many potential dietary biomarkers, mostly in blood. Few studies examined urine samples although urine is preferred for dietary biomarker discovery. Furthermore, little is known regarding the reproducibility of urinary metabolomic biomarkers over time. We aimed to identify urinary metabolomic biomarkers of diet and assess their reproducibility over time. We conducted a metabolomics analysis among 648 racially/ethnically diverse men and women in the Diet Assessment Sub-study of the Cancer Prevention Study-3 cohort to examine the correlation between >100 food groups/items [101 by a food frequency questionnaire (FFQ), and 105 by repeated 24 h diet recalls (24HRs)] and 1391 metabolites measured in 24 h urine sample replicates, six months apart. Diet-metabolite associations were examined by Pearson's partial correlation analysis. Biomarkers were evaluated for prediction accuracy assessed using area under the curve (AUC) calculated from the receiver operating characteristic curve and for reproducibility assessed using intraclass correlation coefficients (ICCs). A total of 1708 diet-metabolite associations were identified after Bonferroni correction for multiple comparisons and restricting correlation coefficients to >0.2 or <-0.2 (1570 associations using the FFQ and 933 using 24HRs), 513 unique metabolites correlated with 79 food groups/items. The median ICCs of the 513 putative biomarkers was 0.53 (interquartile range 0.42-0.62). In this study, with comprehensive dietary data and repeated 24 h urinary metabolic profiles, we identified a large number of diet-metabolite correlations and replicated many found in previous studies. Our findings revealed the promise of urine samples for dietary biomarker discovery in a large cohort study and provide important information on biomarker reproducibility, which could facilitate their utilization in future clinical and epidemiological studies.

Derivation and Validation of a Total Fruit and Vegetable Intake Prediction Model to Identify Targets for Biomarker Discovery Using the UK National Diet and Nutrition Survey

BACKGROUND

Dietary assessments in research and clinical settings are largely reliant on self-reported questionnaires. It is acknowledged that these are subject to measurement error and biases and that objective approaches would be beneficial. Dietary biomarkers have been purported as a complementary approach to improve the accuracy of dietary assessments. Tentative biomarkers have been identified for many individual fruits and vegetables (FVs), but an objective total FV intake assessment tool has not been established.

OBJECTIVES

To derive and validate a prediction model of total FV intake (TFVpred) to inform future biomarker studies.

METHODS

Data from the National Diet and Nutrition Survey (NDNS) were used for this analysis. A modeling group (MG) consisting of participants aged >11 years from the NDNS years 5-6 was created (n = 1746). Intake data for 96 FVs were analyzed by stepwise regression to derive a model that satisfied 3 selection criteria: SEE ≤80, R2 >0.7, and ≤10 predictors. The TFVpred model was validated using comparative data from a validation group (VG) created from the NDNS years 7-8 (n = 1865). Pearson's correlation coefficients were assessed between observed and predicted values in the MG and VG. Bland-Altman plots were used to assess agreement between TFVpred estimates and total FV intake.

RESULTS

A TFVpred model, comprised of tomatoes, apples, carrots, bananas, pears, strawberries, and onions, satisfied the selection criteria (R2 = 0.761; SEE = 78.81). Observed and predicted total FV intake values were positively correlated in the MG (r = 0.872; P < 0.001; R2 = 0.761) and the VG (r = 0.838; P < 0.001; R2 = 0.702). In the MG and VG, 95.0% and 94.9%, respectively, of TFVpred model residuals were within the limits of agreement.

CONCLUSIONS

Intakes of a concise FV list can be used to predict total FV intakes in a UK population. The individual FVs included in the TFVpred model present targets for biomarker discovery aimed at objectively assessing total FV intake.

Novel Urinary Biomarkers of Orange Juice Consumption, Interindividual Variability, and Differences with Processing Methods

Untargeted metabolomics identified urinary biomarkers able to discriminate between the intake of fresh hand-squeezed and industrially processed orange juices. Processing led to an upregulation in the excretion of hydroxy-polymethoxyflavone sulfates, abscisic acid, and sinapic acid 4'-glucuronide. The demethylated polymethoxyflavone metabolites were produced with a significant interindividual variability suggesting that they could originate from gut microbiota metabolism. No correlation between the excretion levels of flavanone and polymethoxyflavone metabolites was observed, showing that gut microbiota metabolism differences could be behind the interindividual variability. Subjects with a high excretion level of hesperetin conjugates could be low or high polymethoxyflavone excretors. Flavanone phase II metabolites were primarily glucuronides, while those of demethylated polymethoxyflavones were mainly sulfates. A comparative study with the available demethylated polymethoxyflavone standards suggested that the metabolites produced in humans could be tentatively 4'-hydroxy- and/or 3'-hydroxy-polymethoxyflavone sulfates. This study is the first to describe the bioavailability and metabolism of citrus juice polymethoxyflavones in humans.

New Advanced Glycation End Products Observed in Rat Urine by Untargeted Metabolomics after Feeding with Heat-Treated Skimmed Milk Powder

SCOPE

Milk powder is commonly consumed throughout the world. However, advanced glycation end products (AGEs) will form in milk powder during thermal processing and long-term storage. This study aimed to identify such compounds with potential as new urinary biomarkers of intake of heat-treated skimmed milk powder (HSMP).

METHODS AND RESULTS

A parallel study is performed with different dosages of HSMP as well as hydrolyzed HSMP and untreated skimmed milk powder (SMP) in 36 rats. The 24-h urine samples on day 7 or 8 are collected and profiled by untargeted UPLC-Qtof-MS metabolomics. Statistical analysis revealed 25 metabolites differentiating SMP and HSMP; nineteen of these structures are proposed as lysine- and arginine-derived AGEs, and heterocyclic compounds.

CONCLUSION

These metabolites may potentially serve as biomarkers of food intake pending further validation to assess intakes of heat-processed dairy foods and thus help to elucidate the effects of HSMP consumption or dietary AGEs on human health.

Charged metabolite biomarkers of food intake assessed via plasma metabolomics in a population-based observational study in Japan

Food intake biomarkers can be critical tools that can be used to objectively assess dietary exposure for both epidemiological and clinical nutrition studies. While an accurate estimation of food intake is essential to unravel associations between the intake and specific health conditions, random and systematic errors affect self-reported assessments. This study aimed to clarify how habitual food intake influences the circulating plasma metabolome in a free-living Japanese regional population and to identify potential food intake biomarkers. To achieve this aim, we conducted a cross-sectional analysis as part of a large cohort study. From a baseline survey of the Tsuruoka Metabolome Cohort Study, 7,012 eligible male and female participants aged 40-69 years were chosen for this study. All data on patients' health status and dietary intake were assessed via a food frequency questionnaire, and plasma samples were obtained during an annual physical examination. Ninety-four charged plasma metabolites were measured using capillary electrophoresis mass spectrometry, by a non-targeted approach. Statistical analysis was performed using partial-least-square regression. A total of 21 plasma metabolites were likely to be associated with long-term food intake of nine food groups. In particular, the influential compounds in each food group were hydroxyproline for meat, trimethylamine-N-oxide for fish, choline for eggs, galactarate for dairy, cystine and betaine for soy products, threonate and galactarate for carotenoid-rich vegetables, proline betaine for fruits, quinate and trigonelline for coffee, and pipecolate for alcohol, and these were considered as prominent food intake markers in Japanese eating habits. A set of circulating plasma metabolites was identified as potential food intake biomarkers in the Japanese community-dwelling population. These results will open the way for the application of new reliable dietary assessment tools not by self-reported measurements but through objective quantification of biofluids.

Application of UPLC-QTOF-MS Based Untargeted Metabolomics in Identification of Metabolites Induced in Pathogen-Infected Rice

Metabolomics is a useful tool for comparing metabolite changes in plants. Because of its high sensitivity, metabolomics combined with high-resolution mass spectrometry (HR-MS) is the most widely accepted metabolomics tools. In this study, we compared the metabolites of pathogen-infected rice (Oryza sativa) with control rice using an untargeted metabolomics approach. We profiled the mass features of two rice groups using a liquid chromatography quadrupole time-of-flight mass spectrometry (QTOF-MS) system. Twelve of the most differentially induced metabolites in infected rice were selected through multivariate data analysis and identified through a mass spectral database search. The role of these compounds in metabolic pathways was finally investigated using pathway analysis. Our study showed that the most frequently induced secondary metabolites are prostanoids, a subclass of eicosanoids, which are associated with plant defense metabolism against pathogen infection. Herein, we propose a new untargeted metabolomics approach for understanding plant defense system at the metabolic level.

The Potential of Multi-Biomarker Panels in Nutrition Research: Total Fruit Intake as an Example

Dietary and food intake biomarkers offer the potential of improving the accuracy of dietary assessment. An extensive range of putative intake biomarkers of commonly consumed foods have been identified to date. As the field of food intake biomarkers progresses toward solving the complexities of dietary habits, combining biomarkers associated with single foods or food groups may be required. The objective of this work was to examine the ability of a multi-biomarker panel to classify individuals into categories of fruit intake. Biomarker data was measured using ¹H NMR spectroscopy in two studies: (1) An intervention study where varying amounts of fruit was consumed and (2) the National Adult Nutrition Survey (NANS). Using data from an intervention study a biomarker panel (Proline betaine, Hippurate, and Xylose) was constructed from three urinary biomarker concentrations. Biomarker cut-off values for three categories of fruit intake were developed. The biomarker sum cut-offs were ≤ 4.766, 4.766–5.976, >5.976 μM/mOsm/kg for <100, 101–160, and >160 g fruit intake. The ability of the biomarker sum to classify individuals into categories of fruit intake was examined in the cross-sectional study (NANS) (N = 565). Examination of results in the cross-sectional study revealed excellent agreement with self-reported intake: a similar number of participants were ranked into each category of fruit intake. The work illustrates the potential of multi-biomarker panels and paves the way forward for further development in the field. The use of such panels may be key to distinguishing foods and adding specificity to the predictions of food intake.

Urinary Biomarkers for Orange Juice Consumption

SCOPE

As orange juice belongs to one of the most consumed juices worldwide, a human study is performed to identify urinary biomarkers for the consumption of orange juice in order to differentiate between low, medium, and high intake.

METHODS AND RESULTS

The 32 study participants abstained from citrus fruits, juices and products thereof, except for one portion of orange juice, for eight days. Throughout the study, spot urine samples are collected and quantitatively analyzed by high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) regarding their content of several potential biomarkers for orange juice intake after enzymatic treatment with β-glucuronidase. Proline betaine is determined as a long-term biomarker: based on its urinary excretion, orange juice consumption is traceable for at least 72 h after intake. Naringenin and hesperetin are identified as qualitative short-term biomarkers. Synephrine sulfate also showed a fast increase and decrease in a semi-quantitative approach. In the case of phloretin, no correlation between orange juice consumption and the urinary concentration is observed.

CONCLUSION

Proline betaine is the most promising biomarker for orange juice consumption and allows to differentiate between low, medium, and high intake. Hesperetin and naringenin (as well as synephrine) are applicable as supporting biomarkers, whereas phloretin does not represent a reliable biomarker for orange juice consumption.

Identification and Reproducibility of Plasma Metabolomic Biomarkers of Habitual Food Intake in a US Diet Validation Study

Previous metabolomic studies have identified putative blood biomarkers of dietary intake. These biomarkers need to be replicated in other populations and tested for reproducibility over time for the potential use in future epidemiological studies. We conducted a metabolomics analysis among 671 racially/ethnically diverse men and women included in a diet validation study to examine the correlation between >100 food groups/items (101 by a food frequency questionnaire (FFQ), 105 by 24-h diet recalls (24HRs)) with 1141 metabolites measured in fasting plasma sample replicates, six months apart. Diet–metabolite associations were examined by Pearson’s partial correlation analysis. Biomarker reproducibility was assessed using intraclass correlation coefficients (ICCs). A total of 677 diet–metabolite associations were identified after Bonferroni adjustment for multiple comparisons and restricting absolute correlation coefficients to greater than 0.2 (601 associations using the FFQ and 395 using 24HRs). The median ICCs of the 238 putative biomarkers was 0.56 (interquartile range 0.46–0.68). In this study, with repeated FFQs, 24HRs and plasma metabolic profiles, we identified several potentially novel food biomarkers and replicated others found in our previous study. Our findings contribute to the growing literature on food-based biomarkers and provide important information on biomarker reproducibility which could facilitate their utilization in future nutritional epidemiological studies.

Urinary biomarkers of dietary intake: a review

Dietary intakes are commonly assessed by established methods including food frequency questionnaires, food records, or recalls. These self-report methods have limitations impacting validity and reliability. Dietary biomarkers provide objective verification of self-reported food intakes, and represent a rapidly evolving area. This review aims to summarize the urinary biomarkers of individual foods, food groups, dietary patterns, or nutritional supplements that have been evaluated to date. Six electronic databases were searched. Included studies involved healthy populations, were published from 2000, and compared measured dietary intake with urinary markers. The initial search identified 9985 studies; of these, 616 full texts were retrieved and 109 full texts were included. Of the included studies, 67 foods and food components were studied, and 347 unique urinary biomarkers were identified. The most reliable biomarkers identified were whole grains (alkylresorcinols), soy (isoflavones), and sugar (sucrose and fructose). While numerous novel urinary biomarkers have been identified, further validation studies are warranted to verify the accuracy of self-reported intakes and utility within practice.

Mediterranean diet intervention in overweight and obese subjects lowers plasma cholesterol and causes changes in the gut microbiome and metabolome independently of energy intake

OBJECTIVES

This study aimed to explore the effects of an isocaloric Mediterranean diet (MD) intervention on metabolic health, gut microbiome and systemic metabolome in subjects with lifestyle risk factors for metabolic disease.

DESIGN

Eighty-two healthy overweight and obese subjects with a habitually low intake of fruit and vegetables and a sedentary lifestyle participated in a parallel 8-week randomised controlled trial. Forty-three participants consumed an MD tailored to their habitual energy intakes (MedD), and 39 maintained their regular diets (ConD). Dietary adherence, metabolic parameters, gut microbiome and systemic metabolome were monitored over the study period.

RESULTS

Increased MD adherence in the MedD group successfully reprogrammed subjects' intake of fibre and animal proteins. Compliance was confirmed by lowered levels of carnitine in plasma and urine. Significant reductions in plasma cholesterol (primary outcome) and faecal bile acids occurred in the MedD compared with the ConD group. Shotgun metagenomics showed gut microbiome changes that reflected individual MD adherence and increase in gene richness in participants who reduced systemic inflammation over the intervention. The MD intervention led to increased levels of the fibre-degrading Faecalibacterium prausnitzii and of genes for microbial carbohydrate degradation linked to butyrate metabolism. The dietary changes in the MedD group led to increased urinary urolithins, faecal bile acid degradation and insulin sensitivity that co-varied with specific microbial taxa.

CONCLUSION

Switching subjects to an MD while maintaining their energy intake reduced their blood cholesterol and caused multiple changes in their microbiome and metabolome that are relevant in future strategies for the improvement of metabolic health.

Specific adaptations are selected in opposite sun exposed Antarctic cryptoendolithic communities as revealed by untargeted metabolomics

Antarctic cryptoendolithic communities are self-supporting borderline ecosystems spreading across the extreme conditions of the Antarctic desert and represent the predominant life-form in the ice-free areas of McMurdo Dry Valleys, accounted as the closest terrestrial Martian analogue. Components of these communities are highly adapted extremophiles and extreme-tolerant microorganisms, among the most resistant known to date. Recently, studies investigated biodiversity and community composition in these ecosystems but the metabolic activity of the metacommunity has never been investigated. Using an untargeted metabolomics, we explored stress-response of communities spreading in two sites of the same location, subjected to increasing environmental pressure due to opposite sun exposure, accounted as main factor influencing the diversity and composition of these ecosystems. Overall, 331 altered metabolites (206 and 125 unique for north and south, respectively), distinguished the two differently exposed communities. We also selected 10 metabolites and performed two-stage Receiver Operating Characteristic (ROC) analysis to test them as potential biomarkers. We further focused on melanin and allantoin as protective substances; their concentration was highly different in the community in the shadow or in the sun. These results clearly indicate that opposite insolation selected organisms in the communities with different adaptation strategies in terms of key metabolites produced.

Potential of food intake biomarkers in nutrition research

The influence of dietary habits on health/disease is well-established. Accurate dietary assessment is essential to understand metabolic pathways/processes involved in this relationship. In recent years, biomarker discovery has become a major area of interest for improving dietary assessment. Well-established nutrient intake biomarkers exist; however, there is growing interest in identifying and using biomarkers for more accurate and objective measurements of food intake. Metabolomics has emerged as a key tool used for biomarker discovery, employing techniques such as NMR spectroscopy, or MS. To date, a number of putatively identified biomarkers were discovered for foods including meat, cruciferous vegetables and legumes. However, many of the results are associations only and lack the desired validation including dose-response studies. Food intake biomarkers can be employed to classify individuals into consumers/non-consumers of specific foods, or into dietary patterns. Food intake biomarkers can also play a role in correcting self-reported measurement error, thus improving dietary intake estimates. Quantification of food intake was previously performed for citrus (proline betaine), chicken (guanidoacetate) and grape (tartaric acid) intake. However, this area still requires more investigation and expansion to a range of foods. The present review will assess the current literature of identified specific food intake biomarkers, their validation and the variety of biomarker uses. Addressing the utility of biomarkers and highlighting gaps in this area is important to advance the field in the context of nutrition research.

Mass Spectrometry-Based Analysis of Urinary Biomarkers for Dietary Tomato Intake

SCOPE

In this study, the applicability of several β-carboline, imidazole, and steroidal alkaloids as biomarkers for tomato juice intake is evaluated.

METHODS AND RESULTS

Over the course of a 2-week crossover dietary intervention study, 14 volunteers were given low and high doses of tomato juice after 3 days of avoiding tomato-based products. On the day of consumption and the following days, volunteers provided urine samples that were quantitatively analyzed by high-performance liquid chromatography-tandem mass spectrometry. Herein, glucose-derived β-carboline alkaloids are determined as supporting, yet non-specific dietary biomarkers for tomato juice intake. Several imidazole alkaloids represent further biomarkers, which are shown to specifically indicate consumption of tomato juice for 24 h and partly >24 h. Additionally, steroidal alkaloids derived from esculeogenin B are determined to be specific biomarkers for tomato juice detectable for at least 48 h after consumption. The intake of low and high amounts of tomato juice is significantly distinguishable based on the urinary excretion of all determined biomarkers as well.

CONCLUSIONS

The dietary intake of tomato juice is conclusively traceable based on urinary excretion of multiple β-carboline, imidazole, and steroidal alkaloids, and can be determined for up to 48 h after consumption. Furthermore, different intake doses can clearly be distinguished based on their urinary excretion.

Circulating Pro- and Anti-Inflammatory Metabolites and Its Potential Role in Rheumatoid Arthritis Pathogenesis

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease that affects synovial joints, leading to inflammation, joint destruction, loss of function, and disability. Although recent pharmaceutical advances have improved the treatment of RA, patients often inquire about dietary interventions to improve RA symptoms, as they perceive pain and/or swelling after the consumption or avoidance of certain foods. There is evidence that some foods have pro- or anti-inflammatory effects mediated by diet-related metabolites. In addition, recent literature has shown a link between diet-related metabolites and microbiome changes, since the gut microbiome is involved in the metabolism of some dietary ingredients. But diet and the gut microbiome are not the only factors linked to circulating pro- and anti-inflammatory metabolites. Other factors including smoking, associated comorbidities, and therapeutic drugs might also modify the circulating metabolomic profile and play a role in RA pathogenesis. This article summarizes what is known about circulating pro- and anti-inflammatory metabolites in RA. It also emphasizes factors that might be involved in their circulating concentrations and diet-related metabolites with a beneficial effect in RA.

Biomarkers of appetite: is there a potential role for metabolomics?

Knowing the biological signals associated with appetite control is crucial for understanding the regulation of food intake. Biomarkers of appetite have been defined as physiological measures that relate to subjective appetite ratings, measured food intake, or both. Several metabolites including amino acids, lipids and glucose were proposed as key molecules associated with appetite control over 60 years ago, and along with bile acids are all among possible appetite biomarker candidates. Additional metabolites that have been associated with appetite include endocannabinoids, lactate, cortisol and β-hydroxybutyrate. However, although appetite is a complex integrative process, studies often investigated a limited number of markers in isolation. Metabolomics involves the study of small molecules or metabolites present in biological samples such as urine or blood, and may present a powerful approach to further the understanding of appetite control. Using multiple analytical techniques allows the characterisation of molecules, such as carbohydrates, lipids, amino acids, bile acids and fatty acids. Metabolomics has proven successful in identifying markers of consumption of certain foods and biomarkers implicated in several diseases. However, it has been underexploited in appetite control or obesity. The aim of the present narrative review is to: (1) provide an overview of existing metabolites that have been identified in human biofluids and associated with appetite control; and (2) discuss the potential of metabolomics to deepen understanding of appetite control in humans.

Benefits of the Mediterranean diet: Epidemiological and molecular aspects

More than 50 years after the Seven Countries Study, a large number of epidemiological studies have explored the relationship between the Mediterranean diet (MD) and health, through observational, case-control, some longitudinal and a few experimental studies. The overall results show strong evidence suggesting a protective effect of the MD mainly on the risk of cardiovascular disease (CVD) and certain types of cancer. The beneficial effects have been attributed to the types of food consumed, total dietary pattern, components in the food, cooking techniques, eating behaviors and lifestyle behaviors, among others. The aim of this article is to review and summarize the knowledge derived from the literature focusing on the benefits of the MD on health, including those that have been extensively investigated (CVD, cancer) along with more recent issues such as mental health, immunity, quality of life, etc. The review begins with a brief description of the MD and its components. Then we present a review of studies evaluating metabolic biomarkers and genotypes in relation to the MD. Other sections are dedicated to observation and intervention studies for various pathologies. Finally, some insights into the relationship between the MD and sustainability are explored. In conclusion, the research undertaken on metabolomics approaches has identified potential markers for certain MD components and patterns, but more investigation is needed to obtain valid measures. Further evaluation of gene-MD interactions are also required to better understand the mechanisms by which the MD diet exerts its beneficial effects on health. Observation and intervention studies, particularly PREDIMED, have provided invaluable data on the benefits of the MD for a wide range of chronic diseases. However further research is needed to explore the effects of other lifestyle components associated with Mediterranean populations, its environmental impact, as well as the MD extrapolation to non-Mediterranean contexts.

Identification of Plasma Lipid Metabolites Associated with Nut Consumption in US Men and Women

BACKGROUND

Intake of nuts has been inversely associated with risk of type 2 diabetes and cardiovascular disease, partly through inducing a healthy lipid profile. How nut intake may affect lipid metabolites remains unclear.

OBJECTIVE

The aim of this study was to identify the plasma lipid metabolites associated with habitual nut consumption in US men and women.

METHODS

We analyzed cross-sectional data from 1099 participants in the Nurses' Health Study (NHS), NHS II, and Health Professionals Follow-up Study. Metabolic profiling was conducted on plasma by LC-mass spectrometry. Nut intake was estimated from food-frequency questionnaires. We included 144 known lipid metabolites that had CVs ≤25%. Multivariate linear regression was used to assess the associations of nut consumption with individual plasma lipid metabolites.

RESULTS

We identified 17 lipid metabolites that were significantly associated with nut intake, based on a 1 serving (28 g)/d increment in multivariate models [false discovery rate (FDR) P value <0.05]. Among these species, 8 were positively associated with nut intake [C24:0 sphingomyelin (SM), C36:3 phosphatidylcholine (PC) plasmalogen-A, C36:2 PC plasmalogen, C24:0 ceramide, C36:1 PC plasmalogen, C22:0 SM, C34:1 PC plasmalogen, and C36:2 phosphatidylethanolamine plasmalogen], with changes in relative metabolite level (expressed in number of SDs on the log scale) ranging from 0.36 to 0.46 for 1 serving/d of nuts. The other 9 metabolites were inversely associated with nut intake with changes in relative metabolite level ranging from -0.34 to -0.44. In stratified analysis, 3 metabolites were positively associated with both peanuts and peanut butter (C24:0 SM, C24:0 ceramide, and C22:0 SM), whereas 6 metabolites were inversely associated with other nuts (FDR P value <0.05).

CONCLUSIONS

A panel of lipid metabolites was associated with intake of nuts, which may provide insight into biological mechanisms underlying associations between nuts and cardiometabolic health. Metabolites that were positively associated with intake of nuts may be helpful in identifying potential biomarkers of nut intake.

Paving the Way to Precision Nutrition Through Metabolomics

Nutrition is an interdisciplinary science that studies the interactions of nutrients with the body in relation to maintenance of health and well-being. Nutrition is highly complex due to the underlying various internal and external factors that could model it. Thus, hacking this complexity requires more holistic and network-based strategies that could unveil these dynamic system interactions at both time and space scales. The ongoing omics era with its high-throughput molecular data generation is paving the way to embrace this complexity and is deeply reshaping the whole field of nutrition. Understanding the future paths of nutrition science is of importance from both translational and clinical perspectives. Basic nutrients which might include metabolites are important in nutrition science. Moreover, metabolites are key biological communication channels and represent an appealing functional readout at the interface of different major influential factors that define health and disease. Metabolomics is the technology that enables holistic and systematic analyses of metabolites in a biological system. Hence, given its intrinsic functionality, its tight connection to metabolism and its high clinical actionability potential, metabolomics is a very appealing technology for nutrition science. The ultimate goal is to deliver a tailored and clinically relevant nutritional recommendations and interventions to achieve precision nutrition. This work intends to present an update on the applications of metabolomics to personalize nutrition in translational and clinical settings. It also discusses the current conceptual shifts that are remodeling clinical nutrition practices in this Precision Medicine era. Finally, perspectives of clinical nutrition in the ever-growing, data-driven healthcare landscape are presented.

Recent Advances in the Application of Metabolomics for Nutrition and Health

Metabolomics is the study of small molecules called metabolites in biological samples. Application of metabolomics to nutrition research has expanded in recent years, with emerging literature supporting multiple applications. Key examples include applications of metabolomics in the identification and development of objective biomarkers of dietary intake, in developing personalized nutrition strategies, and in large-scale epidemiology studies to understand the link between diet and health. In this review, we provide an overview of the current applications and identify key challenges that need to be addressed for the further development of the field. Successful development of metabolomics for nutrition research has the potential to improve dietary assessment, help deliver personalized nutrition, and enhance our understanding of the link between diet and health.

Biomarkers of food intake for nuts and vegetable oils: an extensive literature search

Nuts and vegetable oils are important sources of fat and of a wide variety of micronutrients and phytochemicals. Following their intake, several of their constituents, as well as their derived metabolites, are found in blood circulation and in urine. As a consequence, these could be used to assess the compliance to a dietary intervention or to determine habitual intake of nuts and vegetable oils. However, before these metabolites can be widely used as biomarkers of food intake (BFIs), several characteristics have to be considered, including specificity, dose response, time response, stability, and analytical performance. We have, therefore, conducted an extensive literature search to evaluate current knowledge about potential BFIs of nuts and vegetable oils. Once identified, the strengths and weaknesses of the most promising candidate BFIs have been summarized. Results from selected studies have provided a variety of compounds mainly derived from the fatty fraction of these foods, but also other components and derived metabolites related to their nutritional composition. In particular, α-linolenic acid, urolithins, and 5-hydroxyindole-3-acetic acid seem to be the most plausible candidate BFIs for walnuts, whereas for almonds they could be α-tocopherol and some catechin-derived metabolites. Similarly, several studies have reported a strong association between selenium levels and consumption of Brazil nuts. Intake of vegetable oils has been mainly assessed through the measurement of specific fatty acids in different blood fractions, such as oleic acid for olive oil, α-linolenic acid for flaxseed (linseed) and rapeseed (canola) oils, and linoleic acid for sunflower oil. Additionally, hydroxytyrosol and its metabolites were the most promising distinctive BFIs for (extra) virgin olive oil. However, most of these components lack sufficient specificity to serve as BFIs. Therefore, additional studies are necessary to discover new candidate BFIs, as well as to further evaluate the specificity, sensitivity, dose-response relationships, and reproducibility of these candidate biomarkers and to eventually validate them in other populations. For the discovery of new candidate BFIs, an untargeted metabolomics approach may be the most effective strategy, whereas for increasing the specificity of the evaluation of food consumption, this could be a combination of different metabolites.

A Metabolomics Approach to the Identification of Urinary Biomarkers of Pea Intake

A significant body of evidence demonstrates that isoflavone metabolites are good markers of soy intake, while research is lacking on specific markers of other leguminous sources such as peas. In this context, the objective of our current study was to identify biomarkers of pea intake using an untargeted metabolomics approach. A randomized cross-over acute intervention study was conducted on eleven participants who consumed peas and couscous (control food) in random order. The urine samples were collected in fasting state and postprandially at regular intervals and were further analysed by ultra-performance liquid chromatography coupled to quadrupole time of flight mass spectrometry (UPLC-QTOF-MS). Multivariate statistical analysis resulted in robust Partial least squares Discriminant Analysis (PLS-DA) models obtained for comparison of fasting against the postprandial time points (0 h vs. 4 h, (R²X = 0.41, Q² = 0.4); 0 h vs. 6 h, ((R²X = 0.517, Q² = 0.495)). Variables with variable importance of projection (VIP) scores ≥1.5 obtained from the PLS-DA plot were considered discriminant between the two time points. Repeated measures analysis of variance (ANOVA) was performed to identify features with a significant time effect. Assessment of the time course profile revealed that ten features displayed a differential time course following peas consumption compared to the control food. The interesting features were tentatively identified using accurate mass data and confirmed by tandem mass spectrometry (MS using commercial spectral databases and authentic standards. 2-Isopropylmalic acid, asparaginyl valine and N-carbamoyl-2-amino-2-(4-hydroxyphenyl) acetic acid were identified as markers reflecting pea intake. The three markers also increased in a dose-dependent manner in a randomized intervention study and were further confirmed in an independent intervention study. Overall, key validation criteria were met for the successfully identified pea biomarkers. Future work will examine their use in nutritional epidemiology studies.

Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies

The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state-of-the-art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful "tips and tricks" along the analytical workflow.

Biomarkers of legume intake in human intervention and observational studies: a systematic review

There is a growing interest in assessing dietary intake more accurately across different population groups, and biomarkers have emerged as a complementary tool to replace traditional dietary assessment methods. The purpose of this study was to conduct a systematic review of the literature available and evaluate the applicability and validity of biomarkers of legume intake reported across various observational and intervention studies. A systematic search in PubMed, Scopus, and ISI Web of Knowledge identified 44 studies which met the inclusion criteria for the review. Results from observational studies focused on soy or soy-based foods and demonstrated positive correlations between soy intake and urinary, plasma or serum isoflavonoid levels in different population groups. Similarly, intervention studies demonstrated increased genistein and daidzein levels in urine and plasma following soy intake. Both genistein and daidzein exhibited dose-response relationships. Other isoflavonoid levels such as O-desmethylangolensin (O-DMA) and equol were also reported to increase following soy consumption. Using a developed scoring system, genistein and daidzein can be considered as promising candidate markers for soy consumption. Furthermore, genistein and daidzein also served as good estimates of soy intake as evidenced from long-term exposure studies marking their status as validated biomarkers. On the contrary, only few studies indicated proposed biomarkers for pulses intake, with pipecolic acid and S-methylcysteine reported as markers reflecting dry bean consumption, unsaturated aliphatic, hydroxyl-dicarboxylic acid related to green beans intake and trigonelline reported as marker of peas consumption. However, data regarding criteria such as specificity, dose-response and time-response relationship, reliability, and feasibility to evaluate the validity of these markers is lacking. In conclusion, despite many studies suggesting proposed biomarkers for soy, there is a lack of information on markers of other different subtypes of legumes. Further discovery and validation studies are needed in order to identify reliable biomarkers of legume intake.

Biomarkers of food intake for cocoa and liquorice (products): a systematic review

Background

To unravel true links between diet and health, it is important that dietary exposure is accurately measured. Currently, mainly self-reporting methods (e.g. food frequency questionnaires and 24-h recalls) are used to assess food intake in epidemiological studies. However, these traditional instruments are subjective measures and contain well-known biases. Especially, estimating the intake of the group of confectionary products, such as products containing cocoa and liquorice, remains a challenge. The use biomarkers of food intake (BFIs) may provide a more objective measurement. However, an overview of current candidate biomarkers and their validity is missing for both cocoa- and liquorice-containing foods.

Objective

The purpose of the current study was to (1) identify currently described candidate BFIs for cocoa (products) and liquorice, (2) to evaluate the validity of these identified candidate BFIs and (3) to address further validation and/or identification work to be done.

Methods

This systematic review was based on a comprehensive literature search of three databases (PubMed, Scopus and ISI web of Science), to identify candidate BFIs. Via a second search step in the Human Metabolome Database (HMDB), the Food Database (FooDB) and Phenol-Explorer, the specificity of the candidate BFIs was evaluated, followed by an evaluation of the validity of the specific candidate BFIs, via pre-defined criteria.

Results

In total, 37 papers were included for cocoa and 8 papers for liquorice. For cocoa, 164 unique candidate BFIs were obtained, and for liquorice, four were identified in total. Despite the high number of identified BFIs for cocoa, none of the metabolites was specific. Therefore, the validity of these compounds was not further examined. For liquorice intake, 18-glycyrrhetinic acid (18-GA) was found to have the highest assumed validity.

Conclusions

For cocoa, specific BFIs were missing, mainly because the individual BFIs were also found in foods having a similar composition, such as tea (polyphenols) or coffee (caffeine). However, a combination of individual BFIs might lead to discriminating profiles between cocoa (products) and foods with a similar composition. Therefore, studies directly comparing the consumption of cocoa to these similar products are needed, enabling efforts to find a unique profile per product. For liquorice, we identified 18-GA as a promising BFI; however, important information on its validity is missing; thus, more research is necessary. Our findings indicate a need for more studies to determine acceptable BFIs for both cocoa and liquorice.

Untargeted Metabolomics Identifies Novel Potential Biomarkers of Habitual Food Intake in a Cross-Sectional Study of Postmenopausal Women

Background

Recent studies suggest that untargeted metabolomics is a promising tool to identify novel biomarkers of individual foods. However, few large cross-sectional studies with comprehensive data on habitual diet and circulating metabolites have been conducted.

Objective

We aimed to identify potential food biomarkers and evaluate their predictive accuracy.

Methods

We conducted a cross-sectional analysis of consumption of 91 food groups or items, assessed by a 152-item food-frequency questionnaire, in relation to 1186 serum metabolites measured by mass spectrometry-based platforms from 1369 nonsmoking postmenopausal women (mean age = 68.3 y). Diet-metabolite associations were selected by Pearson's partial correlation analysis (P < 4.63 × 10-7, |r| > 0.2). The predictive accuracy of the selected food metabolites was evaluated from the area under the curve (AUC) calculated from receiver operating characteristic analysis conducted among women in the top and bottom quintiles of dietary intake.

Results

We identified 379 diet-metabolite associations. Forty-two food groups or items were correlated with 199 serum metabolites. We replicated 63 metabolites as biomarkers of habitual food intake reported in previous cross-sectional studies. Among those not previously shown to be associated with habitual diet, several are biologically plausible and were reported in acute feeding studies including: banana and dopamine 3-O-sulfate (r = 0.34, AUC = 76%) and dopamine 4-O-sulfate (r = 0.33, AUC = 74%), garlic and alliin (r = 0.24, AUC = 69%), N-acetylalliin (r = 0.27, AUC = 70%), and S-allylcysteine (r = 0.23, AUC = 69). Two unannotated metabolites were the strongest predictors for dark fish (X-02269, r = 0.51, AUC = 94%) and coffee intake (X-21442, r = 0.62, AUC = 98%).

Conclusion

In this comprehensive, cross-sectional analysis of habitual food intake and serum metabolites among postmenopausal women, we identified several potentially novel food biomarkers and replicated others. Our findings contribute to the limited literature on food-based biomarkers and highlight the significant and promising role that large cohort studies with archived blood samples could play in this field. This study was registered at clinicaltrials.gov as NCT03282812.

Validation of biomarkers of food intake-critical assessment of candidate biomarkers

Biomarkers of food intake (BFIs) are a promising tool for limiting misclassification in nutrition research where more subjective dietary assessment instruments are used. They may also be used to assess compliance to dietary guidelines or to a dietary intervention. Biomarkers therefore hold promise for direct and objective measurement of food intake. However, the number of comprehensively validated biomarkers of food intake is limited to just a few. Many new candidate biomarkers emerge from metabolic profiling studies and from advances in food chemistry. Furthermore, candidate food intake biomarkers may also be identified based on extensive literature reviews such as described in the guidelines for Biomarker of Food Intake Reviews (BFIRev). To systematically and critically assess the validity of candidate biomarkers of food intake, it is necessary to outline and streamline an optimal and reproducible validation process. A consensus-based procedure was used to provide and evaluate a set of the most important criteria for systematic validation of BFIs. As a result, a validation procedure was developed including eight criteria, plausibility, dose-response, time-response, robustness, reliability, stability, analytical performance, and inter-laboratory reproducibility. The validation has a dual purpose: (1) to estimate the current level of validation of candidate biomarkers of food intake based on an objective and systematic approach and (2) to pinpoint which additional studies are needed to provide full validation of each candidate biomarker of food intake. This position paper on biomarker of food intake validation outlines the second step of the BFIRev procedure but may also be used as such for validation of new candidate biomarkers identified, e.g., in food metabolomic studies.

Guidelines for Biomarker of Food Intake Reviews (BFIRev): how to conduct an extensive literature search for biomarker of food intake discovery

Identification of new biomarkers of food and nutrient intake has developed fast over the past two decades and could potentially provide important new tools for compliance monitoring and dietary intake assessment in nutrition and health science. In recent years, metabolomics has played an important role in identifying a large number of putative biomarkers of food intake (BFIs). However, the large body of scientific literature on potential BFIs outside the metabolomics area should also be taken into account. In particular, we believe that extensive literature reviews should be conducted and that the quality of all suggested biomarkers should be systematically evaluated. In order to cover the literature on BFIs in the most appropriate and consistent manner, there is a need for appropriate guidelines on this topic. These guidelines should build upon guidelines in related areas of science while targeting the special needs of biomarker methodology. This document provides a guideline for conducting an extensive literature search on BFIs, which will provide the basis to systematically validate BFIs. This procedure will help to prioritize future work on the identification of new potential biomarkers and on validating these as well as other biomarker candidates, thereby providing better tools for future studies in nutrition and health.

Use of Metabolomics in Improving Assessment of Dietary Intake

BACKGROUND

Nutritional metabolomics is rapidly evolving to integrate nutrition with complex metabolomics data to discover new biomarkers of nutritional exposure and status.

CONTENT

The purpose of this review is to provide a broad overview of the measurement techniques, study designs, and statistical approaches used in nutrition metabolomics, as well as to describe the current knowledge from epidemiologic studies identifying metabolite profiles associated with the intake of individual nutrients, foods, and dietary patterns.

SUMMARY

A wide range of technologies, databases, and computational tools are available to integrate nutritional metabolomics with dietary and phenotypic information. Biomarkers identified with the use of high-throughput metabolomics techniques include amino acids, acylcarnitines, carbohydrates, bile acids, purine and pyrimidine metabolites, and lipid classes. The most extensively studied food groups include fruits, vegetables, meat, fish, bread, whole grain cereals, nuts, wine, coffee, tea, cocoa, and chocolate. We identified 16 studies that evaluated metabolite signatures associated with dietary patterns. Dietary patterns examined included vegetarian and lactovegetarian diets, omnivorous diet, Western dietary patterns, prudent dietary patterns, Nordic diet, and Mediterranean diet. Although many metabolite biomarkers of individual foods and dietary patterns have been identified, those biomarkers may not be sensitive or specific to dietary intakes. Some biomarkers represent short-term intakes rather than long-term dietary habits. Nonetheless, nutritional metabolomics holds promise for the development of a robust and unbiased strategy for measuring diet. Still, this technology is intended to be complementary, rather than a replacement, to traditional well-validated dietary assessment methods such as food frequency questionnaires that can measure usual diet, the most relevant exposure in nutritional epidemiologic studies.

Multi-omics analysis reveals that ornithine decarboxylase contributes to erlotinib resistance in pancreatic cancer cells

Molecular and metabolic alterations in cancer cells are one of the leading causes of acquired resistance to chemotherapeutics. In this study, we explored an experimental strategy to identify which of these alterations can induce erlotinib resistance in human pancreatic cancer. Using genetically matched erlotinib-sensitive (BxPC-3) and erlotinib-resistant (BxPC-3ER) pancreatic cancer cells, we conducted a multi-omics analysis of metabolomes and transcriptomes in these cells. Untargeted and targeted metabolomic analyses revealed significant changes in metabolic pathways involved in the regulation of polyamines, amino acids, and fatty acids. Further transcriptomic analysis identified that ornithine decarboxylase (ODC) and its major metabolite, putrescine, contribute to the acquisition of erlotinib resistance in BxPC-3ER cells. Notably, either pharmacological or genetic blockage of ODC was able to restore erlotinib sensitivity, and this could be rescued by treatment with exogenous putrescine in erlotinib-resistant BxPC-3ER cells. Moreover, using a panel of cancer cells we demonstrated that ODC expression levels in cancer cells are inversely correlated with sensitivity to chemotherapeutics. Taken together, our findings will begin to uncover mechanisms of acquired drug resistance and ultimately help to identify potential therapeutic markers in cancer.

Lipidomics Insights in Health and Nutritional Intervention Studies

Lipids are among the major components of food and constitute the principal structural biomolecules of human body together with proteins and carbohydrates. Lipidomics encompasses the investigation of the lipidome, defined as the entire spectrum of lipids in a biological system at a given time. Among metabolomics technologies, lipidomics has evolved due to the relevance of lipids in nutrition and their well-recognized roles in health. Mass spectrometry advances have greatly facilitated lipidomics, but owing to the complexity and diversity of the lipids, lipidome purification and analysis are still challenging. This review focuses on lipidomics strategies, applications, and achievements of studies related to nutrition and health research.