Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Exhaustive Search of Dietary Intake Biomarkers as Objective Tools for Personalized Nutrimetabolomics and Precision Nutrition Implementation

OBJECTIVE

To conduct an exhaustive scoping search of existing literature, incorporating diverse bibliographic sources to elucidate the relationships between metabolite biomarkers in human fluids and dietary intake.

BACKGROUND

The search for biomarkers linked to specific dietary food intake holds immense significance for precision health and nutrition research. Using objective methods to track food consumption through metabolites offers a more accurate way to provide dietary advice and prescriptions on healthy dietary patterns by healthcare professionals. An extensive investigation was conducted on biomarkers associated with the consumption of several food groups and consumption patterns. Evidence is integrated from observational studies, systematic reviews, and meta-analyses to achieve precision nutrition and metabolism personalization.

METHODS

Tailored search strategies were applied across databases and gray literature, yielding 158 primary research articles that met strict inclusion criteria. The collected data underwent rigorous analysis using STATA and Python tools. Biomarker-food associations were categorized into 5 groups: cereals and grains, dairy products, protein-rich foods, plant-based foods, and a miscellaneous group. Specific cutoff points (≥3 or ≥4 bibliographic appearances) were established to identify reliable biomarkers indicative of dietary consumption.

RESULTS

Key metabolites in plasma, serum, and urine revealed intake from different food groups. For cereals and grains, 3-(3,5-dihydroxyphenyl) propanoic acid glucuronide and 3,5-dihydroxybenzoic acid were significant. Omega-3 fatty acids and specific amino acids showcased dairy and protein foods consumption. Nuts and seafood were linked to hypaphorine and trimethylamine N-oxide. The miscellaneous group featured compounds like theobromine, 7-methylxanthine, caffeine, quinic acid, paraxanthine, and theophylline associated with coffee intake.

CONCLUSIONS

Data collected from this research demonstrate potential for incorporating precision nutrition into clinical settings and nutritional advice based on accurate estimation of food intake. By customizing dietary recommendations based on individualized metabolic profiles, this approach could significantly improve personalized food consumption health prescriptions and support integrating multiple nutritional data.This article is part of a Nutrition Reviews special collection on Precision Nutrition.

Dietary biomarkers-an update on their validity and applicability in epidemiological studies

The aim of this literature review was to identify and provide a summary update on the validity and applicability of the most promising dietary biomarkers reflecting the intake of important foods in the Western diet for application in epidemiological studies. Many dietary biomarker candidates, reflecting intake of common foods and their specific constituents, have been discovered from intervention and observational studies in humans, but few have been validated. The literature search was targeted for biomarker candidates previously reported to reflect intakes of specific food groups or components that are of major importance in health and disease. Their validity was evaluated according to 8 predefined validation criteria and adapted to epidemiological studies; we summarized the findings and listed the most promising food intake biomarkers based on the evaluation. Biomarker candidates for alcohol, cereals, coffee, dairy, fats and oils, fruits, legumes, meat, seafood, sugar, tea, and vegetables were identified. Top candidates for all categories are specific to certain foods, have defined parent compounds, and their concentrations are unaffected by nonfood determinants. The correlations of candidate dietary biomarkers with habitual food intake were moderate to strong and their reproducibility over time ranged from low to high. For many biomarker candidates, critical information regarding dose response, correlation with habitual food intake, and reproducibility over time is yet unknown. The nutritional epidemiology field will benefit from the development of novel methods to combine single biomarkers to generate biomarker panels in combination with self-reported data. The most promising dietary biomarker candidates that reflect commonly consumed foods and food components for application in epidemiological studies were identified, and research required for their full validation was summarized.

Machine Learning in Nutrition Research

Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods of data analysis. The characteristics of machine learning (ML) make it suitable for such analysis and thus lend itself as an alternative tool to deal with data of this nature. ML has already been applied in important problem areas in nutrition, such as obesity, metabolic health, and malnutrition. Despite this, experts in nutrition are often without an understanding of ML, which limits its application and therefore potential to solve currently open questions. The current article aims to bridge this knowledge gap by supplying nutrition researchers with a resource to facilitate the use of ML in their research. ML is first explained and distinguished from existing solutions, with key examples of applications in the nutrition literature provided. Two case studies of domains in which ML is particularly applicable, precision nutrition and metabolomics, are then presented. Finally, a framework is outlined to guide interested researchers in integrating ML into their work. By acting as a resource to which researchers can refer, we hope to support the integration of ML in the field of nutrition to facilitate modern research.

Metabolism of phenolics in coffee and plant-based foods by canonical pathways: an assessment of the role of fatty acid β-oxidation to generate biologically-active and -inactive intermediates

ω-Phenyl-alkenoic acids are abundant in coffee, fruits, and vegetables. Along with ω-phenyl-alkanoic acids, they are produced from numerous dietary (poly)phenols and aromatic amino acids in vivo. This review addresses how phenyl-ring substitution and flux modulates their gut microbiota and endogenous β-oxidation. 3',5'-Dihydroxy-derivatives (from alkyl-resorcinols, flavanols, proanthocyanidins), and 4'-hydroxy-phenolic acids (from tyrosine, p-coumaric acid, naringenin) are β-oxidation substrates yielding benzoic acids. In contrast, 3',4',5'-tri-substituted-derivatives, 3',4'-dihydroxy-derivatives and 3'-methoxy-4'-hydroxy-derivatives (from coffee, tea, cereals, many fruits and vegetables) are poor β-oxidation substrates with metabolism diverted via gut microbiota dehydroxylation, phenylvalerolactone formation and phase-2 conjugation, possibly a strategy to conserve limited pools of coenzyme A. 4'-Methoxy-derivatives (citrus fruits) or 3',4'-dimethoxy-derivatives (coffee) are susceptible to hepatic "reverse" hydrogenation suggesting incompatibility with enoyl-CoA-hydratase. Gut microbiota-produced 3'-hydroxy-4'-methoxy-derivatives (citrus fruits) and 3'-hydroxy-derivatives (numerous (poly)phenols) are excreted as the phenyl-hydracrylic acid β-oxidation intermediate suggesting incompatibility with hydroxy-acyl-CoA dehydrogenase, albeit with considerable inter-individual variation. Further investigation is required to explain inter-individual variation, factors determining the amino acid to which C6-C3 and C6-C1 metabolites are conjugated, the precise role(s) of l-carnitine, whether glycine might be limiting, and whether phenolic acid-modulation of β-oxidation explains how phenolic acids affect key metabolic conditions, such as fatty liver, carbohydrate metabolism and insulin resistance.

Identification of Single and Combined Serum Metabolites Associated with Food Intake

Assessment of dietary intake is challenging. Traditional methods suffer from both random and systematic errors; thus objective measures are important complements in monitoring dietary exposure. The study presented here aims to identify serum metabolites associated with reported food intake and to explore whether combinations of metabolites may improve predictive models. Fasting blood samples and a 4-day weighed food diary were collected from healthy Swedish subjects (n = 119) self-defined as having habitual vegan, vegetarian, vegetarian + fish, or omnivore diets. Serum was analyzed for metabolites by 1H-nuclear magnetic resonance spectroscopy. Associations between single and combined metabolites and 39 foods and food groups were explored. Area under the curve (AUC) was calculated for prediction models. In total, 24 foods or food groups associated with serum metabolites using the criteria of rho > 0.2, p < 0.01 and AUC ≥ 0.7 were identified. For the consumption of soybeans, citrus fruits and marmalade, nuts and almonds, green tea, red meat, poultry, total fish and shellfish, dairy, fermented dairy, cheese, eggs, and beer the final models included two or more metabolites. Our results indicate that a combination of metabolites improve the possibilities to use metabolites to identify several foods included in the current diet. Combined metabolite models should be confirmed in dose−response intervention studies.

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 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.

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.

Validation of soy isoflavone intake and its health effects: a review of the development of exposure biomarkers

BACKGROUND/OBJECTIVES

It is difficult to consistently demonstrate the health effects of soy isoflavones owing to the multitude of factors contributing to their bioavailability. To accurately verify these health effects, dietary isoflavone intake should be measured using a biologically active dose rather than an intake dose. This concept has been expanded to the development of new exposure biomarkers in nutrition research. This review aims to provide an overview of the development of exposure biomarkers and suggest a novel research strategy for identifying the health effects of soy isoflavone intake.

MATERIALS/METHODS

We cover recent studies on the health effects of soy isoflavones focusing on isoflavone metabolites as exposure biomarkers.

RESULTS

Compared to non-fermented soy foods, fermented soy foods cause an increased concentration of isoflavones in the biofluid immediately following ingestion. The correlation between exposure biomarkers in blood and urine and the food frequency questionnaire was slightly lower than that of corresponding 24-h dietary recalls. Urinary and blood isoflavone levels did not show a consistent association with chronic disease and cancer risk.

CONCLUSION

It is crucial to understand the variable bioavailabilities of soy isoflavones, which may affect evaluations of soy isoflavone intake in health and disease. Further studies on the development of valid exposure biomarkers are needed to thoroughly investigate the health effects of isoflavone.

Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations-A Perspective

Improvement of diet at the population level is a cornerstone of national and international strategies for reducing chronic disease burden. A critical challenge in generating robust data on habitual dietary intake is accurate exposure assessment. Self-reporting instruments (e.g., food frequency questionnaires, dietary recall) are subject to reporting bias and serving size perceptions, while weighed dietary assessments are unfeasible in large-scale studies. However, secondary metabolites derived from individual foods/food groups and present in urine provide an opportunity to develop potential biomarkers of food intake (BFIs). Habitual dietary intake assessment in population surveys using biomarkers presents several challenges, including the need to develop affordable biofluid collection methods, acceptable to participants that allow collection of informative samples. Monitoring diet comprehensively using biomarkers requires analytical methods to quantify the structurally diverse mixture of target biomarkers, at a range of concentrations within urine. The present article provides a perspective on the challenges associated with the development of urine biomarker technology for monitoring diet exposure in free-living individuals with a view to its future deployment in "real world" situations. An observational study (n = 95), as part of a national survey on eating habits, provided an opportunity to explore biomarker measurement in a free-living population. In a second food intervention study (n = 15), individuals consumed a wide range of foods as a series of menus designed specifically to achieve exposure reflecting a diversity of foods commonly consumed in the UK, emulating normal eating patterns. First Morning Void urines were shown to be suitable samples for biomarker measurement. Triple quadrupole mass spectrometry, coupled with liquid chromatography, was used to assess simultaneously the behavior of a panel of 54 potential BFIs. This panel of chemically diverse biomarkers, reporting intake of a wide range of commonly-consumed foods, can be extended successfully as new biomarker leads are discovered. Towards validation, we demonstrate excellent discrimination of eating patterns and quantitative relationships between biomarker concentrations in urine and the intake of several foods. In conclusion, we believe that the integration of information from BFI technology and dietary self-reporting tools will expedite research on the complex interactions between dietary choices and health.

A Novel LC-MS Based Targeted Metabolomic Approach to Study the Biomarkers of Food Intake

SCOPE

In this work, an integrated strategy is developed for rapid discovery, precise identification, and automated quantification for the biomarkers of food intake (BFIs) for specific food exposure using an ultra-high-pressure liquid chromatography-high-resolution mass spectrometry (MS) based targeted metabolomics approach.

METHODS AND RESULTS

Using whole grain (WG) wheat intake as an example, the combination of paired mass distance networking and parallel reaction monitoring analysis is applied to selectively extract and identify WG metabolites in human urine samples. As a result, a total of 76 wheat phytochemical-derived metabolites, including 17 alkylresorcinol metabolites, 20 benzoxazinoid derivatives, and 39 phenolic acid metabolites are identified. Subsequently, a MS spectral database consisting of the identified metabolites is created by mzVault. The characteristics of identified metabolites from the database are incorporated into the TraceFinder software to establish a quantification platform. Using a standardized urine sample, the authors are able to simultaneously quantify both free and conjugated (sulfate and glucuronide) WG wheat metabolites in real samples without further enzymatic hydrolysis, which is validated by using authentic standards to quantify these metabolites.

CONCLUSION

This novel strategy opens the window to study the biomarkers of specific food intake and make it feasible to validate the BFIs in large-scale human studies.

Food intake biomarkers for berries and grapes

Grapes and berries are two types of widely consumed fruits characterized by a high content in different phytochemicals. However, their accurate dietary assessment is particularly arduous, because of the already wide recognized bias associated with self-reporting methods, combined with the large range of species and cultivars and the fact that these fruits are popularly consumed not only in fresh and frozen forms but also as processed and derived products, including dried and canned fruits, beverages, jams, and jellies. Reporting precise type and/or quantity of grape and berries in FFQ or diaries can obviously be affected by errors. Recently, biomarkers of food intake (BFIs) rose as a promising tool to provide accurate information indicating consumption of certain food items. Protocols for performing systematic reviews in this field, as well as for assessing the validity of candidate BFIs have been developed within the Food Biomarker Alliance (FoodBAll) Project. This paper aims to evaluate the putative BIFs for blueberries, strawberries, raspberries, blackberries, cranberries, blackcurrant, and grapes. Candidate BFIs for grapes were resveratrol metabolites and tartaric acid. The metabolites considered as putative BFI for berries consumption were mostly anthocyanins derivatives together with several metabolites of ellagitannins and some aroma compounds. However, identification of BFIs for single berry types encountered more difficulties. In the absence of highly specific metabolites reported to date, we suggested some multi-metabolite panels that may be further investigated as putative biomarkers for some berry fruits.

Urine Metabolome Profiling Reveals Imprints of Food Heating Processes after Dietary Intervention with Differently Cooked Potatoes

Heat treatment is a widely used method for food processing, and the compounds formed by heat processes may serve as biomarkers of heated food intake in nutrition studies. Therefore, we aimed to characterize the differential metabolic signatures resulting from intake of different potato products and identify potential intake biomarkers. In a randomized, controlled, crossover meal study, healthy volunteers consumed boiled rice, boiled potatoes, and two deep-fried potato products, potato chips and French fries. The urine metabolome was acquired by LC-MS-based untargeted metabolomics. Twenty-two selected metabolites were found for deep-fried potatoes, two for potato intake in general, and one for boiled rice. Fourteen of the 22 selected metabolites were tentatively identified as furan-, pyrrole- and pyrazine-derived compounds indicative of Maillard reactions. With further validation, these candidate biomarkers will be important tools to investigate the influence of heated foods on human health.

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.

Biomarkers of Whole-Grain and Cereal-Fiber Intake in Human Studies: A Systematic Review of the Available Evidence and Perspectives

High whole-grain consumption is related to better health outcomes. The specific physiological effect of these compounds is still unrevealed, partly because the accurate estimation of the intake of whole grains from dietary assessments is difficult and prone to bias, due to the complexity of the estimation of the intake by the consumer. A biomarker of whole-grain intake and type of whole-grain intake would be useful for quantifying the exposure to whole-grain intake. In this review, we aim to review the evidence on the potential biomarkers for whole-grain intake in the literature. We conducted a systematic search in Medline, Embase, Web of Science, and the Cochrane database. In total, 39 papers met the inclusion criteria following the PRISMA guidelines and were included. The relative validity, responsiveness, and reproducibility of these markers were assessed for short-, medium-, and long-term exposure as important criteria for the potential use of these biomarkers from a clinical and research perspective. We found three major groups of biomarkers: (1) alkylresorcinol, as well as its homologs and metabolites, assessed in plasma, adipose tissue biopsies, erythrocyte membranes, and urine; (2) avenacosides, assessed in urine samples; and (3) benzoxazinoid-derived phenylacetamide sulfates, assessed in blood and urine samples. The reviewed biomarkers may be used for improved assessment of associations between whole-grain intake and health outcomes.

Biomarkers of cereal food intake

Background/objectives

Cereal foods are major contributors to the daily energy, protein, and dietary fiber intake all over the world. The role of cereals in human health is dependent on whether they are consumed as refined or whole grain and on cereal species. To unravel the underlying mechanisms of health effects attributed to specific cereal foods and to provide more precise dietary advice, there is a need for improved dietary assessment of whole-grain intake. Dietary biomarkers of specific cereals, different fractions or cereal-containing foods could offer such a possibility. The aim of this review was to summarize the current status on biomarkers of different cereals, fractions, and specific cereal foods.

Subjects and methods

A literature review was conducted and putative biomarkers of different cereals and pseudo-cereals (wheat, oats, rye, barley, rice, and quinoa) as well as for different grain fractions (whole grain, refined grain, bran) and foods were summarized and discussed.

Results

Several putative biomarkers have been suggested for different cereals, due to their unique presence in these grains. Among the biomarkers, odd-numbered alkylresorcinols are the most well-studied and -evaluated biomarkers and reflect whole-grain wheat and rye intake. Even-numbered alkylresorcinols have been suggested to reflect quinoa intake. Recent studies have also highlighted the potential of avenanthramides and avenacosides as specific biomarkers of oat intake, and a set of biomarkers have been suggested to reflect rice bran intake. However, there are yet no specific biomarkers of refined grains. Most biomarker candidates remain to be evaluated in controlled interventions and free-living populations before applied as biomarkers of intake in food and health studies.

Conclusion

Several putative biomarkers of different cereals have been suggested and should be validated in human studies using recently developed food intake biomarker validation criteria.

Addressing the pitfalls when designing intervention studies to discover and validate biomarkers of habitual dietary intake

INTRODUCTION

Dietary exposure monitoring within populations is reliant on self-reported measures such as Food Frequency Questionnaires and diet diaries. These methods often contain inaccurate information due to participant misreporting, non-compliance and bias. Urinary metabolites derived from individual foods could provide additional objective indicators of dietary exposure. For biomarker approaches to have utility it is essential that they cover a wide-range of commonly consumed foods and the methodology works in a real-world environment.

OBJECTIVES

To test that the methodology works in a real-world environment and to consider the impact of the major sources of likely variance; particularly complex meals, different food formulations, processing and cooking methods, as well as the dynamics of biomarker duration in the body.

METHODS

We designed and tested a dietary exposure biomarker discovery and validation strategy based on a food intervention study involving free-living individuals preparing meals and collecting urine samples at home. Two experimental periods were built around three consecutive day menu plans where all foods and drinks were provided (n = 15 and n = 36).

RESULTS

The experimental design was validated by confirming known consumption biomarkers in urinary samples after the first menu plan. We tested biomarker performance with different food formulations and processing methods involving meat, wholegrain, fruits and vegetables.

CONCLUSION

It was demonstrated that spot urine samples, together with robust dietary biomarkers, despite major sources of variance, could be used successfully for dietary exposure monitoring in large epidemiological studies.

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.

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.

Alterations of the Benzoxazinoid Profiles of Uninjured Maize Seedlings During Freezing, Storage, and Lyophilization

Benzoxazinoids are highly studied compounds due to their biological activity and presence in several cereals. They include compound classes such as hydroxamic acids and lactams and usually occur as inactive glucosides in unstressed plants. Injury to the plant causes enzymatic hydrolysis of the inactive glucosides to the biologically active hydroxamic acid and lactam aglucones. The hydroxamic acids further undergo spontaneous hydrolysis to benzoxazolinones in aqueous solution. Extraction methods that do not cause immediate inactivation of enzymes result in accumulation of aglucones in samples. Using HPLC-MS to profile benzoxazinoids in maize seedlings subjected to several sample preparation techniques, we have found that hydroxamic acid aglucones and benzoxazolinones are present in uninjured maize seedlings, but that the benxozazinoid profile varies depending on sample treatment, potentially underrepresenting the glucoside content and overrepresenting the aglucone and benzoxazolinone content.

The role of metabolomics in determination of new dietary biomarkers

Traditional methods for the assessment of dietary intake are prone to error; in order to improve and enhance these methods increasing interest in the identification of dietary biomarkers has materialised. Metabolomics has emerged as a key tool in the area of dietary biomarker discovery and to date the use of metabolomics has identified a number of putative biomarkers. Applications to identify novel biomarkers of intake have in general taken three approaches: (1) specific acute intervention studies to identify specific biomarkers of intake; (2) searching for biomarkers in cohort studies by correlating to self-reported intake of a specific food/food group(s); (3) analysing dietary patterns in conjunction with metabolomic profiles to identify biomarkers and nutritypes. A number of analytical technologies are employed in metabolomics as currently there is no single technique capable of measuring the entire metabolome. These approaches each have their own advantages and disadvantages. The present review will provide an overview of current technologies and applications of metabolomics in the determination of new dietary biomarkers. In addition, it will address some of the current challenges in the field and future outlooks.

Urinary Biomarkers of Whole Grain Wheat Intake Identified by Non-targeted and Targeted Metabolomics Approaches

Mounting evidence suggests that whole grain (WG) intake plays an important role in chronic disease prevention. However, numerous human studies have failed to produce clear-cut conclusions on this topic. Here, a combination of non-targeted and targeted metabolomics approaches, together with kinetic studies, was used to investigate biomarkers of WG wheat intake and further explore the diet-disease associations. Via these integrated approaches, forty-one compounds were identified as the most discriminating endogenous metabolites after WG versus refined grain (RG) wheat bread consumption. The corresponding biological assessment of these endogenous changes suggests that, in contrast to RG consumption, WG wheat consumption may facilitate antioxidant defense systems and moderate the risk factors of cancer, cardiovascular diseases, and other chronic diseases. A panel of urinary markers consisting of seven alkylresorcinol metabolites and five benzoxazinoid derivatives as specific biomarkers, as well as five phenolic acid derivatives, was also established to cover multiple time points and longer time periods for correctly and objectively monitoring WG wheat intake. Through these findings, we have established a comprehensive biomarker pool to better assess WG wheat consumption, and to monitor the endogenous changes that are linked to health effects of WG wheat consumption.

Benzoxazinoids in Prostate Cancer Patients after a Rye-Intensive Diet: Methods and Initial Results

Rye bread contains high amounts of benzoxazinoids, and in vitro studies have shown suppressive effects of selected benzoxazinoids on prostate cancer cells. Thus, research into benzoxazinoids as possible suppressors of prostate cancer is demanded. A pilot study was performed in which ten prostate cancer patients received a rye-enriched diet 1 week prior to prostatectomy. Plasma and urine samples were collected pre- and postintervention. Ten prostate biopsies were obtained from each patient and histologically evaluated. The biopsies exhibited concentrations above the detection limit of seven benzoxazinoids ranging from 0.15 to 10.59 ng/g tissue. An OPLS-DA analysis on histological and plasma concentrations of benzoxazinoids classified the subjects into two clusters. A tendency of higher benzoxazinoid concentrations toward the benign group encourages further investigations. Benzoxazinoids were quantified by an optimized LC-MS/MS method, and matrix effects were evaluated. At low concentrations in biopsy and plasma matrices the matrix effect was concentration-dependent and nonlinear. For the urine samples the general matrix effects were small but patient-dependent.

Metabolomics as a tool in the identification of dietary biomarkers

Current dietary assessment methods including FFQ, 24-h recalls and weighed food diaries are associated with many measurement errors. In an attempt to overcome some of these errors, dietary biomarkers have emerged as a complementary approach to these traditional methods. Metabolomics has developed as a key technology for the identification of new dietary biomarkers and to date, metabolomic-based approaches have led to the identification of a number of putative biomarkers. The three approaches generally employed when using metabolomics in dietary biomarker discovery are: (i) acute interventions where participants consume specific amounts of a test food, (ii) cohort studies where metabolic profiles are compared between consumers and non-consumers of a specific food and (iii) the analysis of dietary patterns and metabolic profiles to identify nutritypes and biomarkers. The present review critiques the current literature in terms of the approaches used for dietary biomarker discovery and gives a detailed overview of the currently proposed biomarkers, highlighting steps needed for their full validation. Furthermore, the present review also evaluates areas such as current databases and software tools, which are needed to advance the interpretation of results and therefore enhance the utility of dietary biomarkers in nutrition research.