Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study

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.

Metabolomic Profile of Amniotic Fluid and Wheezing in the First Year of Life-A Healthy Birth Cohort Study

OBJECTIVES

To apply metabolomic analysis of amniotic fluid in a discovery cohort to see whether a specific biochemical-metabolic profile at birth is associated with the subsequent onset of wheezing over the first year of life.

STUDY DESIGN

This prospective exploratory study was conducted in a healthy term-born Dutch cohort recruited at 2 hospitals in Utrecht (UMCU, Utrecht, and Diakonessenhuis, Utrecht), The Netherlands. A metabolomic approach based on mass spectrometry was applied to analyze 142 amniotic fluid samples collected at birth. The infants were followed up during their first year of life with recording any respiratory symptoms daily, and they were classified according to the onset of wheezing.

RESULTS

Orthogonally constrained projection to latent structures discriminant analysis was used to investigate differences in the metabolic profiles of the infants with (n = 86) and without (n = 56) wheezing. A search of the available databases for amniotic fluid metabolites identified by stability selection, combined with pathway analysis, highlighted the possible metabolic perturbations involved in this condition. The model built using 16 relevant variables with plausible biological significance, showed an area under the curve of 0.82 (P < .001) and an area under the curve calculated by 7-fold full cross-validation of 0.72 (P = .003), with the steroid hormone biosynthesis and the 2-phenylalanine metabolism emerging as probably perturbed pathways.

CONCLUSIONS

Infants who will or will not experience wheezing in their first year of life have distinct amniotic fluid metabolomic profiles at birth. Changes occurring in biochemical-metabolic pathways in late intrauterine life may have a pathogenic role in early-onset wheezing.

GC-MS Based Metabolomics and NMR Spectroscopy Investigation of Food Intake Biomarkers for Milk and Cheese in Serum of Healthy Humans

The identification and validation of food intake biomarkers (FIBs) in human biofluids is a key objective for the evaluation of dietary intake. We report here the analysis of the GC-MS and 1H-NMR metabolomes of serum samples from a randomized cross-over study in 11 healthy volunteers having consumed isocaloric amounts of milk, cheese, and a soy drink as non-dairy alternative. Serum was collected at baseline, postprandially up to 6 h, and 24 h after consumption. A multivariate analysis of the untargeted serum metabolomes, combined with a targeted analysis of candidate FIBs previously reported in urine samples from the same study, identified galactitol, galactonate, and galactono-1,5-lactone (milk), 3-phenyllactic acid (cheese), and pinitol (soy drink) as candidate FIBs for these products. Serum metabolites not previously identified in the urine samples, e.g., 3-hydroxyisobutyrate after cheese intake, were detected. Finally, an analysis of the postprandial behavior of candidate FIBs, in particular the dairy fatty acids pentadecanoic acid and heptadecanoic acid, revealed specific kinetic patterns of relevance to their detection in future validation studies. Taken together, promising candidate FIBs for dairy intake appear to be lactose and metabolites thereof, for lactose-containing products, and microbial metabolites derived from amino acids, for fermented dairy products such as cheese.

Foodomics for human health: current status and perspectives

INTRODUCTION

In the post-genomic era, the opportunity to combine and integrate cutting-edge analytical platforms and data processing systems allowed the birth of foodomics, 'a discipline that studies the Food and Nutrition domains through the application of advanced omics technologies to improve consumer's well-being, health, and confidence'. Since then, this discipline has rapidly evolved and researchers are now facing the daunting tasks to meet consumers' needs in terms of food traceability, sustainability, quality, safety and integrity. Most importantly, today it is imperative to provide solid evidence of the mechanisms through which food can promote human health and well-being. Areas covered: In this review, the complex relationships connecting food, nutrition and human health will be discussed, with emphasis on the relapses for the development of functional foods and nutraceuticals, personalized nutrition approaches, and the study of the interplay among gut microbiota, diet and health/diseases. Expert commentary: Evidence has been provided supporting the role of various omic platforms in studying the health-promoting effects of food and customized dietary interventions. However, although associated to major analytical challenges, only the proper integration of multi-omics studies and the implementation of bioinformatics tools and databases will help translate findings from clinical practice into effective personalized treatment strategies.

Combining traditional dietary assessment methods with novel metabolomics techniques: present efforts by the Food Biomarker Alliance

FFQ, food diaries and 24 h recall methods represent the most commonly used dietary assessment tools in human studies on nutrition and health, but food intake biomarkers are assumed to provide a more objective reflection of intake. Unfortunately, very few of these biomarkers are sufficiently validated. This review provides an overview of food intake biomarker research and highlights present research efforts of the Joint Programming Initiative 'A Healthy Diet for a Healthy Life' (JPI-HDHL) Food Biomarkers Alliance (FoodBAll). In order to identify novel food intake biomarkers, the focus is on new food metabolomics techniques that allow the quantification of up to thousands of metabolites simultaneously, which may be applied in intervention and observational studies. As biomarkers are often influenced by various other factors than the food under investigation, FoodBAll developed a food intake biomarker quality and validity score aiming to assist the systematic evaluation of novel biomarkers. Moreover, to evaluate the applicability of nutritional biomarkers, studies are presently also focusing on associations between food intake biomarkers and diet-related disease risk. In order to be successful in these metabolomics studies, knowledge about available electronic metabolomics resources is necessary and further developments of these resources are essential. Ultimately, present efforts in this research area aim to advance quality control of traditional dietary assessment methods, advance compliance evaluation in nutritional intervention studies, and increase the significance of observational studies by investigating associations between 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.

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.

Identification of Urinary Food Intake Biomarkers for Milk, Cheese, and Soy-Based Drink by Untargeted GC-MS and NMR in Healthy Humans

The measurement of food intake biomarkers (FIBs) in biofluids represents an objective tool for dietary assessment. FIBs of milk and cheese still need more investigation due to the absence of candidate markers. Thus, an acute intervention study has been performed to sensitively and specifically identify candidate FIBs. Eleven healthy male and female volunteers participated in the randomized, controlled crossover study that tested a single intake of milk and cheese as test products, and soy-based drink as a control. Urine samples were collected at baseline and up to 24 h at distinct time intervals (0-1, 1-2, 2-4, 4-6, 6-12, and 12-24 h) and were analyzed using an untargeted multiplatform approach (GC-MS and ¹H NMR). Lactose, galactose, and galactonate were identified exclusively after milk intake while for other metabolites (allantoin, hippurate, galactitol, and galactono-1,5-lactone) a significant increase has been observed. Urinary 3-phenyllactic acid was the only compound specifically reflecting cheese intake although alanine, proline, and pyroglutamic acid were found at significantly higher levels after cheese consumption. In addition, several novel candidate markers for soy drink were identified, such as pinitol and trigonelline. Together, these candidate FIBs of dairy intake could serve as a basis for future validation studies under free-living conditions.

Nutritional metabolomics and breast cancer risk in a prospective study

Background: The epidemiologic evidence for associations between dietary factors and breast cancer is weak and etiologic mechanisms are often unclear. Exploring the role of dietary biomarkers with metabolomics can potentially facilitate objective dietary characterization, mitigate errors related to self-reported diet, agnostically test metabolic pathways, and identify mechanistic mediators.Objective: The aim of this study was to evaluate associations of diet-related metabolites with the risk of breast cancer in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.Design: We examined prediagnostic serum concentrations of diet-related metabolites in a nested case-control study in 621 postmenopausal invasive breast cancer cases and 621 matched controls in the multicenter PLCO cohort. We calculated partial Pearson correlations between 617 metabolites and 55 foods, food groups, and vitamin supplements on the basis of the 2015 Dietary Guidelines for Americans and derived from a 137-item self-administered food-frequency questionnaire. Diet-related metabolites (P-correlation < 1.47 × 10^-6) were evaluated in breast cancer analyses. ORs for the 90th compared with the 10th percentile were calculated by using conditional logistic regression, with body mass index, physical inactivity, other breast cancer risk factors, and caloric intake controlled for (false discovery rate <0.2).Results: Of 113 diet-related metabolites, 3 were associated with overall breast cancer risk (621 cases): caprate (10:0), a saturated fatty acid (OR: 1.77; 95% CI = 1.28, 2.43); γ-carboxyethyl hydrochroman (γ-CEHC), a vitamin E (γ-tocopherol) derivative (OR: 1.64; 95% CI: 1.18, 2.28); and 4-androsten-3β,17β-diol-monosulfate (1), an androgen (OR: 1.61; 95% CI: 1.20, 2.16). Nineteen metabolites were significantly associated with estrogen receptor (ER)-positive (ER⁺) breast cancer (418 cases): 12 alcohol-associated metabolites, including 7 androgens and α-hydroxyisovalerate (OR: 2.23; 95% CI: 1.50, 3.32); 3 vitamin E (tocopherol) derivatives (e.g., γ-CEHC; OR: 1.80; 95% CI: 1.20, 2.70); butter-associated caprate (10:0) (OR: 1.81; 95% CI: 1.23, 2.67); and fried food-associated 2-hydroxyoctanoate (OR: 1.46; 95% CI: 1.03, 2.07). No metabolites were significantly associated with ER-negative breast cancer (144 cases).Conclusions: Prediagnostic serum concentrations of metabolites related to alcohol, vitamin E, and animal fats were moderately strongly associated with ER⁺ breast cancer risk. Our findings show how nutritional metabolomics might identify diet-related exposures that modulate cancer risk. This trial was registered at clinicaltrials.gov as NCT00339495.

Integrated and global pseudotargeted metabolomics strategy applied to screening for quality control markers of Citrus TCMs

Traditional Chinese medicine (TCM) exerts its therapeutic effect in a holistic fashion with the synergistic function of multiple characteristic constituents. The holism philosophy of TCM is coincident with global and systematic theories of metabolomics. The proposed pseudotargeted metabolomics methodologies were employed for the establishment of reliable quality control markers for use in the screening strategy of TCMs. Pseudotargeted metabolomics integrates the advantages of both targeted and untargeted methods. In the present study, targeted metabolomics equipped with the gold standard RRLC-QqQ-MS method was employed for in vivo quantitative plasma pharmacochemistry study of characteristic prototypic constituents. Meanwhile, untargeted metabolomics using UHPLC-QE Orbitrap HRMS with better specificity and selectivity was employed for identification of untargeted metabolites in the complex plasma matrix. In all, 32 prototypic metabolites were quantitatively determined, and 66 biotransformed metabolites were convincingly identified after being orally administered with standard extracts of four labeled Citrus TCMs. The global absorption and metabolism process of complex TCMs was depicted in a systematic manner.

Synephrine as a Specific Marker for Orange Consumption

To validate the suitability of synephrine, known to be a highly abundant alkaloid in oranges, as a dietary biomarker for orange consumption, a highly sensitive and robust stable isotope dilution analysis (SIDA) as well as an ECHO method, using the analyte itself as a pseudointernal standard injected into the analysis run to provide an "echo peak" of the analyte, was developed to quantitate synephrine by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in citrus juices and human urine before and after the ingestion of orange juice. A citrus juice screening revealed high synephrine concentrations of 150-420 nmol/mL in orange (n = 11) and tangerine (n = 2) juices, whereas 20-100 times lower levels were found in juice from grapefruit (n = 14), lemon (n = 5), pomelo (n = 2), and lime (n = 4). Application of the SIDA to quantitate synephrine in sulfatase/glucuronidase-treated urine samples (n = 10) after orange juice consumption showed an increase of synephrine from trace levels (0.1 ± 0.1 nmol/mL) in the 2-day washout phase to a maximum concentration of 8.9 (±5.5) nmol/mL found 4 h after ingestion of orange juice. Whereas proline betaine was recently reported as a dietary biomarker indicating the ingestion of any citrus product and Chinese artichoke, synephrine can be used a reliable additional biomarker with high specificity for orange and tangerine.

Nutrition for the ageing brain: Towards evidence for an optimal diet

As people age they become increasingly susceptible to chronic and extremely debilitating brain diseases. The precise cause of the neuronal degeneration underlying these disorders, and indeed normal brain ageing remains however elusive. Considering the limits of existing preventive methods, there is a desire to develop effective and safe strategies. Growing preclinical and clinical research in healthy individuals or at the early stage of cognitive decline has demonstrated the beneficial impact of nutrition on cognitive functions. The present review is the most recent in a series produced by the Nutrition and Mental Performance Task Force under the auspice of the International Life Sciences Institute Europe (ILSI Europe). The latest scientific advances specific to how dietary nutrients and non-nutrient may affect cognitive ageing are presented. Furthermore, several key points related to mechanisms contributing to brain ageing, pathological conditions affecting brain function, and brain biomarkers are also discussed. Overall, findings are inconsistent and fragmented and more research is warranted to determine the underlying mechanisms and to establish dose-response relationships for optimal brain maintenance in different population subgroups. Such approaches are likely to provide the necessary evidence to develop research portfolios that will inform about new dietary recommendations on how to prevent cognitive decline.

High-Throughput Quantitation of Proline Betaine in Foods and Suitability as a Valid Biomarker for Citrus Consumption

Proline betaine has been proposed as a candidate dietary biomarker for citrus intake. To validate its suitability as a dietary biomarker and to gain insight into the range of this per-methylated amino acid in foods and beverages, a quick and accurate stable isotope dilution assay was developed for quantitative high-throughput HILIC-MS/MS screening of proline betaine in foods and urine after solvent-mediated matrix precipitation. Quantitative analysis of a variety of foods confirmed substantial amounts of proline betaine in citrus juices (140-1100 mg/L) and revealed high abundance in tubers of the vegetable Stachys affinis, also known as Chinese artichocke (∼700 mg/kg). Seafood including clams, shrimp, and lobster contained limited amounts (1-95 mg/kg), whereas only traces were detected in fish, cuttlefish, fresh meat, dairy products, fresh vegetable (<3 mg/kg), coffee, tea, beer, and wine (<7 mg/L). The human excretion profiles of proline betaine in urine were comparable when common portions of orange juice or fried Stachys tubers were consumed. Neither mussels nor beer provided enough proline betaine to detect significant differences between morning urine samples collected before and after consumption. As Stachys is a rather rare vegetable and not part of peoples' daily diet, the data reported here will help to monitor the subject's compliance in future nutritional human studies on citrus products or the exclusion of citrus products in the wash-out phase of an intervention study. Moreover, proline betaine measurement can contribute to the establishment of a toolbox of valid dietary biomarkers reflecting wider aspects of diet to assess metabolic profiles as measures of dietary exposure and indicators of dietary patterns, dietary changes, or effectiveness of dietary interventions.

Metabolomics, Nutrition, and Potential Biomarkers of Food Quality, Intake, and Health Status

Diet, dietary patterns, and other environmental factors such as exposure to toxins are playing an important role in the prevention/development of many diseases, like obesity, type 2 diabetes, and consequently on the health status of individuals. A major challenge nowadays is to identify novel biomarkers to detect as early as possible metabolic dysfunction and to predict evolution of health status in order to refine nutritional advices to specific population groups. Omics technologies such as genomics, transcriptomics, proteomics, and metabolomics coupled with statistical and bioinformatics tools have already shown great potential in this research field even if so far only few biomarkers have been validated. For the past two decades, important analytical techniques have been developed to detect as many metabolites as possible in human biofluids such as urine, blood, and saliva. In the field of food science and nutrition, many studies have been carried out for food authenticity, quality, and safety, as well as for food processing. Furthermore, metabolomic investigations have been carried out to discover new early biomarkers of metabolic dysfunction and predictive biomarkers of developing pathologies (obesity, metabolic syndrome, type-2 diabetes, etc.). Great emphasis is also placed in the development of methodologies to identify and validate biomarkers of nutrients exposure.

Identifying biomarkers of dietary patterns by using metabolomics

BACKGROUND

Healthy dietary patterns that conform to national dietary guidelines are related to lower chronic disease incidence and longer life span. However, the precise mechanisms involved are unclear. Identifying biomarkers of dietary patterns may provide tools to validate diet quality measurement and determine underlying metabolic pathways influenced by diet quality.

OBJECTIVE

The objective of this study was to examine the correlation of 4 diet quality indexes [the Healthy Eating Index (HEI) 2010, the Alternate Mediterranean Diet Score (aMED), the WHO Healthy Diet Indicator (HDI), and the Baltic Sea Diet (BSD)] with serum metabolites.

DESIGN

We evaluated dietary patterns and metabolites in male Finnish smokers (n = 1336) from 5 nested case-control studies within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study cohort. Participants completed a validated food-frequency questionnaire and provided a fasting serum sample before study randomization (1985-1988). Metabolites were measured with the use of mass spectrometry. We analyzed cross-sectional partial correlations of 1316 metabolites with 4 diet quality indexes, adjusting for age, body mass index, smoking, energy intake, education, and physical activity. We pooled estimates across studies with the use of fixed-effects meta-analysis with Bonferroni correction for multiple comparisons, and conducted metabolic pathway analyses.

RESULTS

The HEI-2010, aMED, HDI, and BSD were associated with 23, 46, 23, and 33 metabolites, respectively (17, 21, 11, and 10 metabolites, respectively, were chemically identified; r-range: -0.30 to 0.20; P = 6 × 10-15 to 8 × 10-6). Food-based diet indexes (HEI-2010, aMED, and BSD) were associated with metabolites correlated with most components used to score adherence (e.g., fruit, vegetables, whole grains, fish, and unsaturated fat). HDI correlated with metabolites related to polyunsaturated fat and fiber components, but not other macro- or micronutrients (e.g., percentages of protein and cholesterol). The lysolipid and food and plant xenobiotic pathways were most strongly associated with diet quality.

CONCLUSIONS

Diet quality, measured by healthy diet indexes, is associated with serum metabolites, with the specific metabolite profile of each diet index related to the diet components used to score adherence. This trial was registered at clinicaltrials.gov as NCT00342992.

Metabolic Phenotyping of Diet and Dietary Intake

Nutrition provides the building blocks for growth, repair, and maintenance of the body and is key to maintaining health. Exposure to fast foods, mass production of dietary components, and wider importation of goods have challenged the balance between diet and health in recent decades, and both scientists and clinicians struggle to characterize the relationship between this changing dietary landscape and human metabolism with its consequent impact on health. Metabolic phenotyping of foods, using high-density data-generating technologies to profile the biochemical composition of foods, meals, and human samples (pre- and postfood intake), can be used to map the complex interaction between the diet and human metabolism and also to assess food quality and safety. Here, we outline some of the techniques currently used for metabolic phenotyping and describe key applications in the food sciences, ending with a broad outlook at some of the newer technologies in the field with a view to exploring their potential to address some of the critical challenges in nutritional science.

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.

Spaceflight induced changes in the human proteome

INTRODUCTION

Spaceflight is one of the most extreme conditions encountered by humans: Individuals are exposed to radiation, microgravity, hypodynamia, and will experience isolation. A better understanding of the molecular processes induced by these factors may allow us to develop personalized countermeasures to minimize risks to astronauts. Areas covered: This review is a summary of literature searches from PubMed, NASA, Roskosmos and the authors' research experiences and opinions. The review covers the available proteomic data on the effects of spaceflight factors on the human body, including both real space missions and ground-based model experiments. Expert commentary: Overall, the authors believe that the present background, methodology and equipment improvements will enhance spaceflight safety and support accumulation of new knowledge on how organisms adapt to extreme conditions.

Analysis of energy metabolism in humans: A review of methodologies

Background

Obesity is a consequence of chronic energy imbalance. We need accurate and precise measurements of energy intake and expenditure, as well as the related behaviors, to fully understand how energy homeostasis is regulated in order to develop interventions and evaluate their effectiveness to combat the global obesity epidemic.

Scope of review

We provide an in-depth review of the methodologies currently used to measure energy intake and expenditure in humans, including their principles, advantages, and limitations in the clinical research setting. The aim is to provide researchers with a comprehensive guide to conduct obesity research of the highest possible quality.

Major conclusions

An array of methodologies is available to measure various aspects of energy metabolism and none is perfect under all circumstances. The choice of methods should be specific to particular research questions with practicality and quality of data the priorities for consideration. A combination of complementary measurements may be preferable. There is an imperative need to develop new methodologies to improve the accuracy and precision of energy intake assessments.

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Image-based technology is a significant step to improve energy intake measurement.

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Physical activity informs patterns but not absolute energy expenditure.

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Combining complementary measurements overcomes shortfalls of individual methods.

Comparing metabolite profiles of habitual diet in serum and urine

BACKGROUND

Diet plays an important role in chronic disease etiology, but some diet-disease associations remain inconclusive because of methodologic limitations in dietary assessment. Metabolomics is a novel method for identifying objective dietary biomarkers, although it is unclear what dietary information is captured from metabolites found in serum compared with urine.

OBJECTIVE

We compared metabolite profiles of habitual diet measured from serum with those measured from urine.

DESIGN

We first estimated correlations between consumption of 56 foods, beverages, and supplements assessed by a food-frequency questionnaire, with 676 serum and 848 urine metabolites identified by untargeted liquid chromatography mass spectrometry, ultra-high performance liquid chromatography tandem mass spectrometry, and gas chromatography mass spectrometry in a colon adenoma case-control study (n = 125 cases and 128 controls) while adjusting for age, sex, smoking, fasting, case-control status, body mass index, physical activity, education, and caloric intake. We controlled for multiple comparisons with the use of a false discovery rate of <0.1. Next, we created serum and urine multiple-metabolite models to predict food intake with the use of 10-fold crossvalidation least absolute shrinkage and selection operator regression for 80% of the data; predicted values were created in the remaining 20%. Finally, we compared predicted values with estimates obtained from self-reported intake for metabolites measured in serum and urine.

RESULTS

We identified metabolites associated with 46 of 56 dietary items; 417 urine and 105 serum metabolites were correlated with ≥1 food, beverage, or supplement. More metabolites in urine (n = 154) than in serum (n = 39) were associated uniquely with one food. We found previously unreported metabolite associations with leafy green vegetables, sugar-sweetened beverages, citrus, added sugar, red meat, shellfish, desserts, and wine. Prediction of dietary intake from multiple-metabolite profiles was similar between biofluids.

CONCLUSIONS

Candidate metabolite biomarkers of habitual diet are identifiable in both serum and urine. Urine samples offer a valid alternative or complement to serum for metabolite biomarkers of diet in large-scale clinical or epidemiologic studies.

Nutritional Cognitive Neuroscience: Innovations for Healthy Brain Aging

Nutritional cognitive neuroscience is an emerging interdisciplinary field of research that seeks to understand nutrition's impact on cognition and brain health across the life span. Research in this burgeoning field demonstrates that many aspects of nutrition—from entire diets to specific nutrients—affect brain structure and function, and therefore have profound implications for understanding the nature of healthy brain aging. The aim of this Focused Review is to examine recent advances in nutritional cognitive neuroscience, with an emphasis on methods that enable discovery of nutrient biomarkers that predict healthy brain aging. We propose an integrative framework that calls for the synthesis of research in nutritional epidemiology and cognitive neuroscience, incorporating: (i) methods for the precise characterization of nutritional health based on the analysis of nutrient biomarker patterns (NBPs), along with (ii) modern indices of brain health derived from high-resolution magnetic resonance imaging (MRI). By integrating cutting-edge techniques from nutritional epidemiology and cognitive neuroscience, nutritional cognitive neuroscience will continue to advance our understanding of the beneficial effects of nutrition on the aging brain and establish effective nutritional interventions to promote healthy brain aging.

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.

Diet, nutrition, and cancer: past, present and future

Despite the potentially important roles of diet and nutrition in cancer prevention, the evidence to support these roles is widely perceived by the public and health professionals as being inconsistent. In this Review, we present the issues and challenges in conducting and interpreting diet-cancer research, including those relating to the design of epidemiological studies, dietary data collection methods, and factors that affect the outcome of intervention trials. Approaches to improve effect estimates, such as the use of biomarkers to improve the accuracy of characterizing dietary exposures, are also discussed. Nutritional and dietary patterns are complex; therefore, the use of a reductionist approach to investigations, by focusing on specific nutrients, can produce misleading information. The effects of tumour heterogeneity and the failure to appreciate the nonlinear, U-shaped relationship between micronutrients and cancer in both observational studies and clinical trials are discussed. New technologies and investigational approaches are enabling the exploration of complex interactions between genetic, epigenetic, metabolic, and gut-microbial processes that will inform our knowledge of the diet-cancer relationship. Communicating the status of the evolving science in the context of the overall scientific evidence base, and evidence-based dietary recommendations for cancer prevention, should be emphasized in guidance for the public and for individual patients.

The acute impact of polyphenols from Hibiscus sabdariffa in metabolic homeostasis: an approach combining metabolomics and gene-expression analyses

We explored the acute multifunctional effects of polyphenols from Hibiscus sabdariffa in humans to assess possible consequences on the host's health. The expected dynamic response was studied using a combination of transcriptomics and metabolomics to integrate specific functional pathways through network-based methods and to generate hypotheses established by acute metabolic effects and/or modifications in the expression of relevant genes. Data were obtained from healthy male volunteers after 3 hours of ingestion of an aqueous Hibiscus sabdariffa extract. The data were compared with data obtained prior to the ingestion, and the overall findings suggest that these particular polyphenols had a simultaneous role in mitochondrial function, energy homeostasis and protection of the cardiovascular system. These findings suggest beneficial actions in inflammation, endothelial dysfunction, and oxidation, which are interrelated mechanisms. Among other effects, the activation of the heme oxygenase-biliverdin reductase axis, the systemic inhibition of the renin-angiotensin system, the inhibition of the angiotensin-converting enzyme, and several actions mirroring those of the peroxisome proliferator-activated receptor agonists further support this notion. We also found concordant findings in the serum of the participants, which include a decrease in cortisol levels and a significant increase in the active vasodilator metabolite of bradykinin (des-Arg(9)-bradykinin). Therefore, our data support the view that polyphenols from Hibiscus sabdariffa play a regulatory role in metabolic health and in the maintenance of blood pressure, thus implying a multi-faceted impact in metabolic and cardiovascular diseases.

Systematic analysis of the polyphenol metabolome using the Phenol-Explorer database

SCOPE

The Phenol-Explorer web database details 383 polyphenol metabolites identified in human and animal biofluids from 221 publications. Here, we exploit these data to characterize and visualize the polyphenol metabolome, the set of all metabolites derived from phenolic food components.

METHODS AND RESULTS

Qualitative and quantitative data on 383 polyphenol metabolites as described in 424 human and animal intervention studies were systematically analyzed. Of these metabolites, 301 were identified without prior enzymatic hydrolysis of biofluids, and included glucuronide and sulfate esters, glycosides, aglycones, and O-methyl ethers. Around one-third of these compounds are also known as food constituents and corresponded to polyphenols absorbed without further metabolism. Many ring-cleavage metabolites formed by gut microbiota were noted, mostly derived from hydroxycinnamates, flavanols, and flavonols. Median maximum plasma concentrations (C(max)) of all human metabolites were 0.09 and 0.32 μM when consumed from foods or dietary supplements, respectively. Median time to reach maximum plasma concentration in humans (T(max)) was 2.18 h.

CONCLUSION

These data show the complexity of the polyphenol metabolome and the need to take into account biotransformations to understand in vivo bioactivities and the role of dietary polyphenols in health and disease.

A mass spectrometric insight into the origins of benign gynecological disorders

Applications of mass spectrometry (MS) are rapidly expanding and encompass molecular and cellular biology. MS aids in the analysis of in vivo global molecular alterations, identifying potential biomarkers which may improve diagnosis and treatment of various pathologies. MS has added new dimensionality to medical research. Pioneering gynecologists now study molecular mechanisms underlying female reproductive pathology with MS-based tools. Although benign gynecologic disorders including endometriosis, adenomyosis, leiomyoma, and polycystic ovarian syndrome (PCOS) carry low mortality rates, they cause significant physical, mental, and social detriments. Additionally, some benign disorders are unfortunately associated with malignancies. MS-based technology can detect malignant changes in formerly benign proteomes and metabolomes with distinct advantages of speed, sensitivity, and specificity. We present the use of MS in proteomics and metabolomics, and summarize the current understanding of the molecular pathways concerning female reproductive anatomy. Highlight discoveries of novel protein and metabolite biomarkers via MS-based technology, we underscore the clinical application of these techniques in the diagnosis and management of benign gynecological disorders. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:450-470, 2017.

Physiological conditions can be reflected in human urine proteome and metabolome

Biomarkers are the measurable changes associated with physiological or pathophysiological processes. Urine, unlike blood, lacks mechanisms for maintaining homeostasis: it is therefore an ideal source of biomarkers that can reflect systemic changes. Urinary proteome and metabolome have been studied for their diagnostic capabilities, ability to monitor disease and prognostic utility. In this review, the effects of common physiological conditions such as gender, age, diet, daily rhythms, exercise, hormone status, lifestyle and extreme environments on human urine are discussed. These effects should be considered when biomarker studies of diseases are conducted. More importantly, if physiological changes can be reflected in urine, we have reason to expect that urine will become widely used to detect small and early changes in pathological and/or pharmacological conditions.

Polyphenol metabolome in human urine and its association with intake of polyphenol-rich foods across European countries

BACKGROUND

An improved understanding of the contribution of the diet to health and disease risks requires accurate assessments of dietary exposure in nutritional epidemiologic studies. The use of dietary biomarkers may improve the accuracy of estimates.

OBJECTIVE

We applied a metabolomic approach in a large cohort study to identify novel biomarkers of intake for a selection of polyphenol-containing foods. The large chemical diversity of polyphenols and their wide distribution over many foods make them ideal biomarker candidates for such foods.

DESIGN

Metabolic profiles were measured with the use of high-resolution mass spectrometry in 24-h urine samples from 481 subjects from the large European Prospective Investigation on Cancer and Nutrition cohort. Peak intensities were correlated to acute and habitual dietary intakes of 6 polyphenol-rich foods (coffee, tea, red wine, citrus fruit, apples and pears, and chocolate products) measured with the use of 24-h dietary recalls and food-frequency questionnaires, respectively.

RESULTS

Correlation (r > 0.3, P < 0.01 after correction for multiple testing) and discriminant [pcorr (1) > 0.3, VIP > 1.5] analyses showed that >2000 mass spectral features from urine metabolic profiles were significantly associated with the consumption of the 6 selected foods. More than 80 polyphenol metabolites associated with the consumption of the selected foods could be identified, and large differences in their concentrations reflecting individual food intakes were observed within and between 4 European countries. Receiver operating characteristic curves showed that 5 polyphenol metabolites, which are characteristic of 5 of the 6 selected foods, had a high predicting ability of food intake.

CONCLUSION

Highly diverse food-derived metabolites (the so-called food metabolome) can be characterized in human biospecimens through this powerful metabolomic approach and screened to identify novel biomarkers for dietary exposures, which are ultimately essential to better understand the role of the diet in the cause of chronic diseases.

Food metabolomics: from farm to human

Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans.

The genomics of micronutrient requirements

Healthy nutrition is accepted as a cornerstone of public health strategies for reducing the risk of noncommunicable conditions such as obesity, cardiovascular disease, and related morbidities. However, many research studies continue to focus on single or at most a few factors that may elicit a metabolic effect. These reductionist approaches resulted in: (1) exaggerated claims for nutrition as a cure or prevention of disease; (2) the wide use of empirically based dietary regimens, as if one fits all; and (3) frequent disappointment of consumers, patients, and healthcare providers about the real impact nutrition can make on medicine and health. Multiple factors including environment, host and microbiome genetics, social context, the chemical form of the nutrient, its (bio)availability, and chemical and metabolic interactions among nutrients all interact to result in nutrient requirement and in health outcomes. Advances in laboratory methodologies, especially in analytical and separation techniques, are making the chemical dissection of foods and their availability in physiological tissues possible in an unprecedented manner. These omics technologies have opened opportunities for extending knowledge of micronutrients and of their metabolic and endocrine roles. While these technologies are crucial, more holistic approaches to the analysis of physiology and environment, novel experimental designs, and more sophisticated computational methods are needed to advance our understanding of how nutrition influences health of individuals.

Optimized Analytical Procedures for the Untargeted Metabolomic Profiling of Human Urine and Plasma by Combining Hydrophilic Interaction (HILIC) and Reverse-Phase Liquid Chromatography (RPLC)-Mass Spectrometry

Profiling of body fluids is crucial for monitoring and discovering metabolic markers of health and disease and for providing insights into human physiology. Since human urine and plasma each contain an extreme diversity of metabolites, a single liquid chromatographic system when coupled to mass spectrometry (MS) is not sufficient to achieve reasonable metabolome coverage. Hydrophilic interaction liquid chromatography (HILIC) offers complementary information to reverse-phase liquid chromatography (RPLC) by retaining polar metabolites. With the objective of finding the optimal combined chromatographic solution to profile urine and plasma, we systematically investigated the performance of five HILIC columns with different chemistries operated at three different pH (acidic, neutral, basic) and five C18-silica RPLC columns. The zwitterionic column ZIC-HILIC operated at neutral pH provided optimal performance on a large set of hydrophilic metabolites. The RPLC columns Hypersil GOLD and Zorbax SB aq were proven to be best suited for the metabolic profiling of urine and plasma, respectively. Importantly, the optimized HILIC-MS method showed excellent intrabatch peak area reproducibility (CV < 12%) and good long-term interbatch (40 days) peak area reproducibility (CV < 22%) that were similar to those of RPLC-MS procedures. Finally, combining the optimal HILIC- and RPLC-MS approaches greatly expanded metabolome coverage with 44% and 108% new metabolic features detected compared with RPLC-MS alone for urine and plasma, respectively. The proposed combined LC-MS approaches improve the comprehensiveness of global metabolic profiling of body fluids and thus are valuable for monitoring and discovering metabolic changes associated with health and disease in clinical research studies.

A metabolomics approach to the identification of biomarkers of sugar-sweetened beverage intake

BACKGROUND

The association between sugar-sweetened beverages (SSBs) and health risks remains controversial. To clarify proposed links, reliable and accurate dietary assessment methods of food intakes are essential.

OBJECTIVE

The aim of this present work was to use a metabolomics approach to identify a panel of urinary biomarkers indicative of SSB consumption from a national food consumption survey and subsequently validate this panel in an acute intervention study.

DESIGN

Heat map analysis was performed to identify correlations between ¹H nuclear magnetic resonance (NMR) spectral regions and SSB intakes in participants of the National Adult Nutrition Survey (n = 565). Metabolites were identified and receiver operating characteristic (ROC) analysis was performed to assess sensitivity and specificity of biomarkers. The panel of biomarkers was validated in an acute study (n = 10). A fasting first-void urine sample and postprandial samples (2, 4, 6 h) were collected after SSB consumption. After NMR spectroscopic profiling of the urine samples, multivariate data analysis was applied.

RESULTS

A panel of 4 biomarkers-formate, citrulline, taurine, and isocitrate-were identified as markers of SSB intake. This panel of biomarkers had an area under the curve of 0.8 for ROC analysis and a sensitivity and specificity of 0.7 and 0.8, respectively. All 4 biomarkers were identified in the SSB sample. After acute consumption of an SSB drink, all 4 metabolites increased in the urine.

CONCLUSIONS

The present metabolomics-based strategy proved to be successful in the identification of SSB biomarkers. Future work will ascertain how to translate this panel of markers for use in nutrition epidemiology.

Metabolomics as a tool in nutritional research

PURPOSE OF REVIEW

Metabolomics is emerging as a powerful tool for studying metabolic processes and in recent years, the applications in the area of nutrition have risen rapidly. The present review gives an overview of the current applications in the field of nutrition and identifies areas in need of advancement.

RECENT FINDINGS

Applications in nutrition research can in general be divided into three main areas: identification of dietary biomarkers, study of diet-related diseases and identification of biomarkers of disease and application to dietary intervention studies as a tool to identify molecular mechanisms.

SUMMARY

Metabolomics has made a significant impact on all the areas identified above and is set to have a major impact on the study of diet-health relationships.

A short review of applications of liquid chromatography mass spectrometry based metabolomics techniques to the analysis of human urine

Mass spectrometry based metabolomics profiling.

Towards the fecal metabolome derived from moderate red wine intake

Dietary polyphenols, including red wine phenolic compounds, are extensively metabolized during their passage through the gastrointestinal tract; and their biological effects at the gut level (i.e., anti-inflammatory activity, microbiota modulation, interaction with cells, among others) seem to be due more to their microbial-derived metabolites rather than to the original forms found in food. In an effort to improve our understanding of the biological effects that phenolic compounds exert at the gut level, this paper summarizes the changes observed in the human fecal metabolome after an intervention study consisting of a daily consumption of 250 mL of wine during four weeks by healthy volunteers (n = 33). It assembles data from two analytical approaches: (1) UPLC-ESI-MS/MS analysis of phenolic metabolites in fecal solutions (targeted analysis); and (2) UHPLC-TOF MS analysis of the fecal solutions (non-targeted analysis). Both approaches revealed statistically-significant changes in the concentration of several metabolites as a consequence of the wine intake. Similarity and complementarity between targeted and non-targeted approaches in the analysis of the fecal metabolome are discussed. Both strategies allowed the definition of a complex metabolic profile derived from wine intake. Likewise, the identification of endogenous markers could lead to new hypotheses to unravel the relationship between moderate wine consumption and the metabolic functionality of gut microbiota.

A metabolomics-driven approach to predict cocoa product consumption by designing a multimetabolite biomarker model in free-living subjects from the PREDIMED study

SCOPE

The aim of the current study was to apply an untargeted metabolomics strategy to characterize a model of cocoa intake biomarkers in a free-living population.

METHODS AND RESULTS

An untargeted HPLC-q-ToF-MS based metabolomics approach was applied to human urine from 32 consumers of cocoa or derived products (CC) and 32 matched control subjects with no consumption of cocoa products (NC). The multivariate statistical analysis (OSC-PLS-DA) showed clear differences between CC and NC groups. The discriminant biomarkers identified were mainly related to the metabolic pathways of theobromine and polyphenols, as well as to cocoa processing. Consumption of cocoa products was also associated with reduced urinary excretions of methylglutarylcarnitine, which could be related to effects of cocoa exposure on insulin resistance. To improve the prediction of cocoa consumption, a combined urinary metabolite model was constructed. ROC curves were performed to evaluate the model and individual metabolites. The AUC values (95% CI) for the model were 95.7% (89.8-100%) and 92.6% (81.9-100%) in training and validation sets, respectively, whereas the AUCs for individual metabolites were <90%.

CONCLUSIONS

The metabolic signature of cocoa consumption in free-living subjects reveals that combining different metabolites as biomarker models improves prediction of dietary exposure to cocoa.