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

Plasma metabolite profile of legume consumption and future risk of type 2 diabetes and cardiovascular disease

BACKGROUND

Legume consumption has been linked to a reduced risk of type 2 diabetes (T2D) and cardiovascular disease (CVD), while the potential association between plasma metabolites associated with legume consumption and the risk of cardiometabolic diseases has never been explored. Therefore, we aimed to identify a metabolite signature of legume consumption, and subsequently investigate its potential association with the incidence of T2D and CVD.

METHODS

The current cross-sectional and longitudinal analysis was conducted in 1833 PREDIMED study participants (mean age 67 years, 57.6% women) with available baseline metabolomic data. A subset of these participants with 1-year follow-up metabolomics data (n = 1522) was used for internal validation. Plasma metabolites were assessed through liquid chromatography-tandem mass spectrometry. Cross-sectional associations between 382 different known metabolites and legume consumption were performed using elastic net regression. Associations between the identified metabolite profile and incident T2D and CVD were estimated using multivariable Cox regression models.

RESULTS

Specific metabolic signatures of legume consumption were identified, these included amino acids, cortisol, and various classes of lipid metabolites including diacylglycerols, triacylglycerols, plasmalogens, sphingomyelins and other metabolites. Among these identified metabolites, 22 were negatively and 18 were positively associated with legume consumption. After adjustment for recognized risk factors and legume consumption, the identified legume metabolite profile was inversely associated with T2D incidence (hazard ratio (HR) per 1 SD: 0.75, 95% CI 0.61-0.94; p = 0.017), but not with CVD incidence risk (1.01, 95% CI 0.86-1.19; p = 0.817) over the follow-up period.

CONCLUSIONS

This study identified a set of 40 metabolites associated with legume consumption and with a reduced risk of T2D development in a Mediterranean population at high risk of cardiovascular disease.

TRIAL REGISTRATION

ISRCTN35739639.

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.

Blood metabolite profiles linking dietary patterns with health-Toward precision nutrition

Diet is one of the most important exposures that may affect health throughout life span. Investigations on dietary patterns rather than single food components are gaining in popularity because they take the complexity of the whole dietary context into account. Adherence to such dietary patterns can be measured by using metabolomics, which allows measurements of thousands of molecules simultaneously. Derived metabolite signatures of dietary patterns may reflect the consumption of specific groups of foods or their constituents originating from the dietary pattern per se, or the physiological response toward the food-derived metabolites, their interaction with endogenous metabolism, and exogenous factors such as gut microbiota. Here, we review and discuss blood metabolite fingerprints of healthy dietary patterns. The plasma concentration of several food-derived metabolites-such as betaines from whole grains and n - 3 polyunsaturated fatty acids and furan fatty acids from fish-seems to consistently reflect the intake of common foods of several healthy dietary patterns. The metabolites reflecting shared features of different healthy food indices form biomarker panels for which specific, targeted assays could be developed. The specificity of such biomarker panels would need to be validated, and proof-of-concept feeding trials are needed to evaluate to what extent the panels may mediate the effects of dietary patterns on disease risk indicators or if they are merely food intake biomarkers. Metabolites mediating health effects may represent novel targets for precision prevention strategies of clinical relevance to be verified in future studies.

Strawberry, Blueberry, and Strawberry-Blueberry Blend Beverages Prevent Hepatic Steatosis in Obese Rats by Modulating Key Genes Involved in Lipid Metabolism

There is an increasing interest in developing natural herb-infused functional beverages with health benefits; therefore, in this study, we aimed to evaluate the effect of strawberry, blueberry, and strawberry-blueberry blend decoction-based functional beverages on obesity-related metabolic alterations in high-fat and high-fructose diet-fed rats. The administration of the three berry-based beverages for eighteen weeks prevented the development of hypertriglyceridemia in obese rats (1.29-1.78-fold) and hepatic triglyceride accumulation (1.38-1.61-fold), preventing the development of hepatic steatosis. Furthermore, all beverages significantly down-regulated Fasn hepatic expression, whereas the strawberry beverage showed the greatest down-regulation of Acaca, involved in fatty acid de novo synthesis. Moreover, the strawberry beverage showed the most significant up-regulation of hepatic Cpt1 and Acadm (fatty acid β-oxidation). In contrast, the blueberry beverage showed the most significant down-regulation of hepatic Fatp5 and Cd36 (fatty acid intracellular transport). Nevertheless, no beneficial effect was observed on biometric measurements, adipose tissue composition, and insulin resistance. On the other hand, several urolithins and their derivatives, and other urinary polyphenol metabolites were identified after the strawberry-based beverages supplementation. In contrast, enterolactone was found significantly increase after the intake of blueberry-based beverages. These results demonstrate that functional beverages elaborated with berry fruits prevent diet-induced hypertriglyceridemia and hepatic steatosis by modulating critical genes involved in fatty acid hepatic metabolism.

Plasma, urine, and stool metabolites in response to dietary rice bran and navy bean supplementation in adults at high-risk for colorectal cancer

Introduction

Dietary intake of whole grains and legumes and adequate physical activity (PA) have been associated with reduced colorectal cancer (CRC) risk. A single-blinded, two-arm, randomized, placebo-controlled pilot trial was implemented to evaluate the impact of a 12-week dietary intervention of rice bran + navy bean supplementation and PA education on metabolite profiles and the gut microbiome among individuals at high risk of CRC.

Methods

Adults (n=20) were randomized 1:1 to dietary intervention or control. All participants received PA education at baseline. Sixteen study foods were prepared with either heat-stabilized rice bran + navy bean powder or Fibersol®-2 as a placebo. Intervention participants consumed 30 g rice bran + 30 g navy bean powder daily; those in the control group consumed 10 g placebo daily. Non-targeted metabolite profiling was performed by UPLC-MS/MS to evaluate plasma, urine, and stool at 0, 6, and 12 weeks. Stool was also analyzed for primary and secondary bile acids (BAs) and short chain fatty acids (SCFAs) by UPLC-MS/MS and microbial community structure via 16S amplicon sequencing. Two-way ANOVA was used to compare differences between groups for metabolites, and mixed models were used to compare differences between groups for BAs, SCFAs, and alpha and beta diversity measures of microbial community structure.

Results

Across biological matrices, the intervention resulted in changes to several amino acid and lipid metabolites, compared to control. There was a 2.33-fold difference in plasma (p<0.001) and a 3.33-fold difference in urine (p=0.008) for the amino acid S-methylcysteine at 12 weeks. Fold-differences to 4-methoxyphenol sulfate in plasma and urine after 6 and 12 weeks (p<0.001) was a novel result from this combined rice bran and navy bean intervention in people. A 2.98-fold difference in plasma (p=0.002) and a 17.74-fold difference in stool (p=0.026) was observed for the lipid octadecenedioylcarnitine at 12 weeks. For stool BAs, 3-oxocholic acid was increased at 12 weeks compared to control within a subset of individuals (mean difference 16.2 ug/uL, p=0.022). No significant differences were observed between groups for stool SCFAs or microbial community structure.

Discussion

Dietary intake of rice bran + navy beans demonstrates beneficial modulation of host and gut microbial metabolism and represents a practical and affordable means of increasing adherence to national guidelines for CRC control and prevention in a high-risk population.

Meeting report: plant-rich dietary patterns and health

Dietary patterns (DP) rich in plant foods are associated with improved health and reduced non-communicable disease risk. In October 2021, the Nutrition Society hosted a member-led conference, held online over 2 half days, exploring the latest research findings examining plant-rich DP and health. The aim of the present paper is to summarise the content of the conference and synopses of the individual speaker presentations are included. Topics included epidemiological analysis of plant-rich DP and health outcomes, the effects of dietary interventions which have increased fruit and vegetable (FV) intake on a range of health outcomes, how adherence to plant-rich DP is assessed, the use of biomarkers to assess FV intake and a consideration of how modifying behaviour towards increased FV intake could impact environmental outcomes, planetary health and food systems. In conclusion, although there are still considerable uncertainties which require further research, which were considered as part of the conference and are summarised in this review, adopting a plant-rich DP at a population level could have a considerable impact on diet and health outcomes, as well as planetary health.

Field-scale monitoring of green sea turtles (Chelonia mydas): Influence of site characteristics and capture technique on the blood metabolome

Given their threatened status, there is considerable interest in establishing monitoring techniques that can be used to evaluate the health of sea turtles in the wild. The present study represents a methodological contribution towards field-scale metabolomic assessment of sea turtles, by exploring differences in blood biochemistry associated with site characteristics and capture technique. We compared the metabolome of blood from animals at three locations (two coastal and one reefal), collected from turtles that were either resting or active, and sampled across multiple seasons at one location. Our results show clear differences in the metabolome of turtles from the three locations, some of which are likely attributable to differences in diet or forage quality and others which may reflect differences in other factors (e.g., occurrence of land-based contaminants or other biotic and/or abiotic stressors) between coastal and reefal sites. Our analysis also revealed the influence of capture technique on metabolite profiles, with numerous markers of physical exertion in animals captured while active that were absent in turtles sampled while resting. We observed a modest potential for temporal differences in the metabolome, but controlling for sampling time did not change the overall conclusions of our study. This suggests that temporal differences in the metabolome warrant consideration when designing studies to evaluate the status of sea turtles in the wild, but that site characteristics and capture technique are bigger drivers. However, sample size for this comparison was relatively small and further investigation of seasonal differences in the metabolome are warranted. Research exploring each of these factors more closely will further contribute towards achieving robust metabolomics analysis of sea turtles across large spatial and temporal scales.

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.

Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health

Urinary metabolic profiling is a promising powerful tool to reflect dietary intake and can help understand metabolic alterations in response to diet quality. Here, we used 1H NMR spectroscopy in a multicountry study in European children (1147 children from 6 different cohorts) and identified a common panel of 4 urinary metabolites (hippurate, N-methylnicotinic acid, urea, and sucrose) that was predictive of Mediterranean diet adherence (KIDMED) and ultra-processed food consumption and also had higher capacity in discriminating children's diet quality than that of established sociodemographic determinants. Further, we showed that the identified metabolite panel also reflected the associations of these diet quality indicators with C-peptide, a stable and accurate marker of insulin resistance and future risk of metabolic disease. This methodology enables objective assessment of dietary patterns in European child populations, complementary to traditional questionary methods, and can be used in future studies to evaluate diet quality. Moreover, this knowledge can provide mechanistic evidence of common biological pathways that characterize healthy and unhealthy dietary patterns, and diet-related molecular alterations that could associate to metabolic disease.

Applications of Metabolomics to Precision Nutrition

BACKGROUND

For thousands of years, disabilities due to nutrient deficiencies have plagued humanity. Rickets, scurvy, anemia, stunted growth, blindness, and mental handicaps due to nutrient deficiencies affected up to 1/10 of the world's population prior to 1900. The discovery of essential amino acids, vitamins, and minerals, in the early 1900s, led to a fundamental change in our understanding of food and a revolution in human health. Widespread vitamin and mineral supplementation, the development of recommended dietary allowances, and the implementation of food labeling and testing along with significant improvements in food production and food quality have meant that nutrient-related disorders have almost vanished in the developed world. The success of nutritional science in preventing disease at a population-wide level is one of the great scientific triumphs of the 20th century. The challenge for nutritional science in the 21st century is to understand how to use nutrients and other food constituents to enhance human health or prevent disease at a more personal level. This is the primary goal of precision nutrition.

SUMMARY

Precision nutrition is an emerging branch of nutrition science that aims to use modern omics technologies (genomics, proteomics, and metabolomics) to assess an individual's response to specific foods or dietary patterns and thereby determine the most effective diet or lifestyle interventions to prevent or treat specific diseases in that individual. Metabolomics is vital to nearly every aspect of precision nutrition. It can be used to comprehensively characterize the thousands of chemicals in foods, to identify food byproducts in human biofluids or tissues, to characterize nutrient deficiencies or excesses, to monitor biochemical responses to dietary interventions, to track long-term or short-term dietary habits, and to guide the development of nutritional therapies. In this review, we will describe how metabolomics has been used to advance the field of precision nutrition by providing some notable examples or use cases. First, we will describe how metabolomics helped launch the field of precision nutrition through the diagnosis and dietary therapy of individuals with inborn errors of metabolism. Next, we will describe how metabolomics is being used to comprehensively characterize the full chemical complexity of many key foods, and how this is revealing much more about nutrients than ever imagined. Third, we will describe how metabolomics is being used to identify food consumption biomarkers and how this opens the door to a more objective and quantitative assessments of an individual's diet and their response to certain foods. Finally, we will describe how metabolomics is being coupled with other omics technologies to develop custom diets and lifestyle interventions that are leading to positive health benefits. Key Message: Metabolomics is vital to the advancement of nutritional science and in making the dream of precision nutrition a reality.

Evaluating Concordance of Bodies of Evidence from Randomized Controlled Trials, Dietary Intake, and Biomarkers of Intake in Cohort Studies: A Meta-Epidemiological Study

We aimed to identify and compare empirical data to determine the concordance of diet-disease effect estimates of bodies of evidence (BoE) from randomized controlled trials (RCTs), dietary intake, and biomarkers of dietary intake in cohort studies (CSs). The Cochrane Database of Systematic Reviews and MEDLINE were searched for systematic reviews (SRs) of RCTs and SRs of CSs that investigated both dietary intake and biomarkers of intake published between 1 January 2010 and 31 December 2019. For matched diet-disease associations, the concordance between results from the 3 different BoE was analyzed using 2 definitions: qualitative (e.g., 95% CI within a predefined range) and quantitative (test hypothesis on the z score). Moreover, the differences in the results coming from BoERCTs, BoECSs dietary intake, and BoECSs biomarkers were synthesized to get a pooled ratio of risk ratio (RRR) across all eligible diet-disease associations, so as to compare the 3 BoE. Overall, 49 diet-disease associations derived from 41 SRs were identified and included in the analysis. Twenty-four percent, 10%, and 39% of the diet-disease associations were qualitatively concordant comparing BoERCTs with BoECSs dietary intake, BoERCTs with BoECSs biomarkers, and comparing both BoE from CSs, respectively; 88%, 69%, and 90% of the diet-disease associations were quantitatively concordant comparing BoERCTs with BoECSs dietary intake, BoERCTs with BoECSs biomarkers, and comparing both BoE from CSs, respectively. The pooled RRRs comparing effects from BoERCTs with effects from BoECSs dietary intake were 1.09 (95% CI: 1.06, 1.13) and 1.18 (95% CI: 1.10, 1.25) compared with BoECSs biomarkers. Comparing both BoE from CSs, the difference in the results was also small (RRR: 0.92; 95% CI: 0.88, 0.96). Our findings suggest that BoE from RCTs and CSs are often quantitatively concordant. Prospective SRs in nutrition research should include, whenever possible, BoE from RCTs and CSs on dietary intake and biomarkers of intake to provide the whole picture for an investigated diet-disease association.

Whole grains and legumes consumption in association with neuromyelitis optica spectrum disorder odds

Background: The environmental risk factors of neuromyelitis optica spectrum disorder (NMOSD) are not fully specified. Regarding the evidence on the possible protective effects of whole grains and legumes against inflammatory disorders, we examined the association between the mentioned dietary components and NMOSD. Methods: 70 patients with NMOSD with definite diagnosis and 164 hospital-based controls were included in this case-control investigation. Data on demographic, clinical, and anthropometric characteristics were collected. Dietary habits of participants were assessed using a previously validated food frequency questionnaire (FFQ) containing 168 food items. Daily intakes of whole grains and legumes were calculated and classified in quartiles. The odds of suffering from NMOSD according to the quartiles of whole grains and legumes were measured in the form of logistic regression models. Results: The mean amount of whole grains (115.29 vs. 44.14 g) and legumes (59.43 vs. 34.50 g) consumption was significantly higher in the control group versus the case group. There was a reverse association between whole grains or legumes and NMOSD odds in both models [P < 0.05, odds ratio (OR) < 1]. In the fully-adjusted model, 90% [95% confidence interval (CI): 0.02-0.39] and 92% (95% CI: 0.01-0.52) reduction in NMOSD odds was observed in the third and fourth quartiles of whole grains intake, respectively. Higher intake of legumes in the third and fourth quartiles led to 81% (95% CI: 0.05-0.71) and 95% (95% CI: 0.01-0.27) reduction in the odds of NMOSD, respectively. Conclusion: Aligned with the results of other investigations on inflammatory disorders, our results suggested a negative association between whole grains and legumes and NMOSD odds.

UK Nutrition Research Partnership (NRP) workshop: Forum on advancing dietary intake assessment

The development of better and more robust measures of dietary intake in free living situations was identified as a priority for advancing nutrition research by the Office of Strategic Coordination for Health Research (OSCHR) Review of Nutrition and Human Health Research in 2017. The UK Nutrition Research Partnership (NRP) sponsored a workshop on Dietary Intake Assessment methodology alongside its series of ‘Hot Topic’ workshops designed to accelerate progress in nutrition research by bringing together people from a range of different disciplines. The workshop on Dietary Intake Assessment methodology took place via Zoom over two half‐days in January 2021 and included 50 scientists from a wide range of disciplines. The problems with current methods of dietary assessment and how emerging technologies might address them were set out in pre‐recorded presentations and explored in panel discussions. Participants then worked in breakout groups to discuss and prioritise the research questions that should be addressed to best further the field and lead to improvements in dietary assessment methodology. Five priority research questions were selected. Participants were asked to brainstorm potential approaches for addressing them and were then asked to focus on one approach and develop it further. At the end of these sessions, participants presented their project ideas to the rest of the workshop and these will be reported back to the Medical Research Council. It is hoped that potential collaborative projects arising from these discussions will be taken forward in response to future funding calls.

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.

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.

The Relationship between Dietary Polyphenol Intakes and Urinary Polyphenol Concentrations in Adults Prescribed a High Vegetable and Fruit Diet

Urinary polyphenol metabolites are potential biomarkers of dietary polyphenol intake. The current study aims to evaluate associations between total diet, vegetable and fruit polyphenol intakes with urinary polyphenol metabolite concentrations in a sample of adults prescribed a diet rich in vegetables and fruit. Thirty-four participants completed a 10-week pre-post study. Participants were asked to consume Australian recommended daily vegetable and fruit serves and attend measurement sessions at baseline and at weeks 2 and 10. Two 24-h diet recalls were collected at each time-point and polyphenol intakes were calculated using the Phenol-Explorer database. Spot urine samples, collected at each time-point, were analyzed for 15 polyphenol metabolites using liquid chromatography-mass spectroscopy. Spearman’s correlation analyzes assessed the strength of relationships between urinary and dietary polyphenols. Linear mixed models were used to investigate relationships between polyphenol excretion and intake. Total urinary polyphenols were significantly correlated with total polyphenol intakes at week 10 (r_s = 0.47) and fruit polyphenols at week 2 (r_s = 0.38). Hippuric acid was significantly correlated with vegetable polyphenols at baseline (r_s = 0.39). Relationships were identified between individual polyphenol metabolites and vegetable and fruit polyphenols. Linear mixed model analyzes identified that for every 1 mg increase in polyphenol intakes, urinary polyphenol excretion increased by 16.3 nmol/g creatinine. Although the majority of relationships were not sufficiently strong or consistent at different time-points, promising relationships were observed between total urinary polyphenols and total polyphenol intakes, and hippuric acid and vegetable polyphenols.

Design and Characterisation of a Randomized Food Intervention That Mimics Exposure to a Typical UK Diet to Provide Urine Samples for Identification and Validation of Metabolite Biomarkers of Food Intake

Poor dietary choices are major risk factors for obesity and non-communicable diseases, which places an increasing burden on healthcare systems worldwide. To monitor the effectiveness of healthy eating guidelines and strategies, there is a need for objective measures of dietary intake in community settings. Metabolites derived from specific foods present in urine samples can provide objective biomarkers of food intake (BFIs). Whilst the majority of biomarker discovery/validation studies have investigated potential biomarkers for single foods only, this study considered the whole diet by using menus that delivered a wide range of foods in meals that emulated conventional UK eating patterns. Fifty-one healthy participants (range 19-77 years; 57% female) followed a uniquely designed, randomized controlled dietary intervention, and provided spot urine samples suitable for discovery of BFIs within a real-world context. Free-living participants prepared and consumed all foods and drinks in their own homes and were asked to follow the protocols for meal consumption and home urine sample collection. This study also assessed the robustness, and impact on data quality, of a minimally invasive urine collection protocol. Overall the study design was well-accepted by participants and concluded successfully without any drop outs. Compliance for urine collection, adherence to menu plans, and observance of recommended meal timings, was shown to be very high. Metabolome analysis using mass spectrometry coupled with data mining demonstrated that the study protocol was well-suited for BFI discovery and validation. Novel, putative biomarkers for an extended range of foods were identified including legumes, curry, strongly-heated products, and artificially sweetened, low calorie beverages. In conclusion, aspects of this study design would help to overcome several current challenges in the development of BFI technology. One specific attribute was the examination of BFI generalizability across related food groups and across different preparations and cooking methods of foods. Furthermore, the collection of urine samples at multiple time points helped to determine which spot sample was optimal for identification and validation of BFIs in free-living individuals. A further valuable design feature centered on the comprehensiveness of the menu design which allowed the testing of biomarker specificity within a biobank of urine samples.

Biomarker-based validity of a food frequency questionnaire estimating intake in Brazilian children and adolescents

This study evaluated the validity of nutrient and food group intakes estimated by an FFQ against biomarkers. A 71-item semiquantitative FFQ was administered to 210 Brazilian children and adolescents aged 9-13 years. Intakes were correlated with biomarkers in plasma and red blood cells. Correlations between nutrients and their biomarkers were presented for animal protein, myristic acid (C14:0), EPA, DHA, β-carotene, folate, and vitamins B3, B5 and B6. Food groups and biomarkers were correlated as follows: fish products with EPA and DHA; milk and dairy with C14:0, pyridoxal 5'-phosphate and vitamin B12; total vegetables and dark green and orange vegetables with β-carotene; 5-methyltetrahydrofolate with green vegetables; and flour products with para-aminobenzoylglutamic acid. This FFQ is a valid tool for ranking Brazilian children and adolescents according to their intake of several nutrients and food groups.

Food intake biomarkers for green leafy vegetables, bulb vegetables, and stem vegetables: a review

BACKGROUND

Numerous studies acknowledged the importance of an adequate vegetable consumption for human health. However, current methods to estimate vegetable intake are often prone to measurement errors due to self-reporting and/or insufficient detail. More objective intake biomarkers for vegetables, using biological specimens, are preferred. The only concentration biomarkers currently available are blood carotenoids and vitamin C, covering total fruit and vegetable intake. Identification of biomarkers for specific vegetables is needed for a better understanding of their relative importance for human health. Within the FoodBAll Project under the Joint Programming Initiative "A Healthy Diet for a Healthy Life", an ambitious action was undertaken to identify candidate intake biomarkers for all major food groups consumed in Europe by systematically reviewing the existent literature. This study describes the review on candidate biomarkers of food intake (BFIs) for leafy, bulb, and stem vegetables, which was conducted within PubMed, Scopus and Web of Science for studies published through March 2019.

RESULTS

In total, 65 full-text articles were assessed for eligibility for leafy vegetables, and 6 full-text articles were screened for bulb and stem vegetables. Putative BFIs were identified for spinach, lettuce, endive, asparagus, artichoke, and celery, but not for rocket salad. However, after critical evaluation through a validation scheme developed by the FoodBAll consortium, none of the putative biomarkers appeared to be a promising BFI. The food chemistry data indicate that some candidate BFIs may be revealed by further studies.

CONCLUSION

Future randomized controlled feeding studies combined with observational studies, applying a non-targeted metabolomics approach, are needed in order to identify valuable BFIs for the intake of leafy, bulb, and stem vegetables.

The anserine to carnosine ratio: an excellent discriminator between white and red meats consumed by free-living overweight participants of the PREVIEW study

BACKGROUND

Biomarkers of meat intake hold promise in clarifying the health effects of meat consumption, yet the differentiation between red and white meat remains a challenge. We measure meat intake objectively in a free-living population by applying a newly developed, three-step strategy for biomarker-based assessment of dietary intakes aimed to indicate if (1) any meat was consumed, (2) what type it was and (3) the quantity consumed.

METHODS

Twenty-four hour urine samples collected in a four-way crossover RCT and in a cross-sectional analysis of a longitudinal lifestyle intervention (the PREVIEW Study) were analyzed by untargeted LC-MS metabolomics. In the RCT, healthy volunteers consumed three test meals (beef, pork and chicken) and a control; in PREVIEW, overweight participants followed a diet with high or moderate protein levels. PLS-DA modeling of all possible combinations between six previously reported, partially validated, meat biomarkers was used to classify meat intake using samples from the RCT to predict consumption in PREVIEW.

RESULTS

Anserine best separated omnivores from vegetarians (AUROC 0.94-0.97), while the anserine to carnosine ratio best distinguished the consumption of red from white meat (AUROC 0.94). Carnosine showed a trend for dose-response between non-consumers, low consumers and high consumers for all meat categories, while in combination with other biomarkers the difference was significant.

CONCLUSION

It is possible to evaluate red meat intake by using combinations of existing biomarkers of white and general meat intake. Our results are novel and can be applied to assess qualitatively recent meat intake in nutritional studies. Further work to improve quantitation by biomarkers is needed.

FOBI: an ontology to represent food intake data and associate it with metabolomic data

Nutrition research can be conducted by using two complementary approaches: (i) traditional self-reporting methods or (ii) via metabolomics techniques to analyze food intake biomarkers in biofluids. However, the complexity and heterogeneity of these two very different types of data often hinder their analysis and integration. To manage this challenge, we have developed a novel ontology that describes food and their associated metabolite entities in a hierarchical way. This ontology uses a formal naming system, category definitions, properties and relations between both types of data. The ontology presented is called FOBI (Food-Biomarker Ontology) and it is composed of two interconnected sub-ontologies. One is a 'Food Ontology' consisting of raw foods and 'multi-component foods' while the second is a 'Biomarker Ontology' containing food intake biomarkers classified by their chemical classes. These two sub-ontologies are conceptually independent but interconnected by different properties. This allows data and information regarding foods and food biomarkers to be visualized in a bidirectional way, going from metabolomics to nutritional data or vice versa. Potential applications of this ontology include the annotation of foods and biomarkers using a well-defined and consistent nomenclature, the standardized reporting of metabolomics workflows (e.g. metabolite identification, experimental design) or the application of different enrichment analysis approaches to analyze nutrimetabolomic data. Availability: FOBI is freely available in both OWL (Web Ontology Language) and OBO (Open Biomedical Ontologies) formats at the project's Github repository (https://github.com/pcastellanoescuder/FoodBiomarkerOntology) and FOBI visualization tool is available in https://polcastellano.shinyapps.io/FOBI_Visualization_Tool/.

Using Pulses in Baked Products: Lights, Shadows, and Potential Solutions

Nowadays, consumers are more conscious of the environmental and nutritional benefits of foods. Pulses-thanks to both nutritional and health-promoting features, together with their low environmental impact-satisfy the demand for high-protein/high-fiber products. However, their consumption is still somewhat limited in Western countries, due to the presence of antinutrient compounds including phytic acid, trypsin inhibitors, and some undigested oligosaccharides, which are responsible for digestive discomfort. Another limitation of eating pulses regularly is their relatively long preparation time. One way to increase the consumption of pulses is to use them as an ingredient in food formulations, such as bread and other baked products. However, some sensory and technological issues limit the use of pulses on an industrial scale; consequently, they require special attention when combined with cereal-based products. Developing formulations and/or processes to improve pulse quality is necessary to enhance their incorporation into baked products. In this context, this study provides an overview of strengths and weaknesses of pulse-enriched baked products focusing on the various strategies-such as the choice of suitable ingredients or (bio)-technological approaches-that counteract the negative effects of including pulses in baked goods.

Distribution and possible biosynthetic pathway of non-protein sulfur amino acids in legumes

Some grain legumes store sulfur in the form of non-protein amino acids in seed. γ-Glutamyl-S-methylcysteine is found in Phaseolus and several Vigna species. γ-Glutamyl-S-ethenylcysteine, an antinutritional compound, is present in Vicia narbonensis. In P. vulgaris, free S-methylcysteine levels are higher at early stages of seed development followed by a decline. γ-Glutamyl-S-methylcysteine accumulates later, in two phases, with a lag during reserve accumulation. The concentration of total S-methylcysteine, quantified after acid hydrolysis, is positively regulated by sulfate nutrition. The levels of both γ-glutamyl-S-methylcysteine and γ-glutamyl-S-ethenylcysteine are modulated in response to changes in seed protein composition. A model is proposed whereby the majority of γ-glutamyl-S-methylcysteine in P. vulgaris is synthesized via the intermediate S-methylhomoglutathione. Knowledge of the biosynthesis of non-protein sulfur amino acids is required for metabolic engineering approaches, in conjunction with manipulation of the protein sink, to increase the concentration of nutritionally essential methionine and cysteine. This would improve protein quality of some important legume crops.

Effect of Genistein on Cholesterol Metabolism-Related Genes in HepG2 Cell

It has been reported that genistein could improve metabolic syndromes. Our study aimed to investigate the effects and potential mechanisms of genistein on improving cholesterol metabolism in HepG2 cell. HepG2 cells were cultured with 0, 0.01, 1.00, 10.00, and 50.00 µM genistein for 24 hr. The current results showed a dose-dependent manner between genistein and intracellular contents of total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), and cellular apolipoprotein A1 (Apo-A1) secretion. TC was increased by 25.69%, meanwhile HDL-C and Apo-A1 were decreased by 56.00% and 25.93%, respectively, when the dosage of genistein was 1.00 µM. Genistein dose-dependently upregulated the protein and mRNA levels of sterol regulatory element binding proteins-2 (SREBP-2), as well as the mRNA levels of low-density lipoprotein receptor (LDLR) and 3-hydroxy-3-methyl glutaryl coenzyme A reductase (HMGCR), by 145.91%, 72.29%, 310.23%, and 123.08%, respectively, when we gave 1.00 µM genistein, indicating that intracellular cholesterol synthesis and absorption of exogenous cholesterol were increased. In addition, the mRNA levels of peroxisome proliferator-activated receptor-γ (PPARγ) and liver X receptor (LXRα), lowered by 58.23% and 34.86% at 0.01 µM genistein, were reduced in a dose-dependent manner. LXRα and ATP-binding cassette transporter A1 (ABCA1) protein levels were significantly (P < 0.05) decreased by 50.35% and 11.60% at 1.00 µM genistein, which indicated that cellular cholesterol efflux was inhibited. Taken together, our results suggested that genistein at dosage of more than 1.00 µM was able to increase the intracellular cholesterol levels by up regulating SREBP-2/LDLR/HMGCR pathway and suppressing PPARγ/LXRα/ABCA1 pathway. PRACTICAL APPLICATION: In this study, genistein appeared to be effective in reducing plasma cholesterol levels due to increase the intracellular cholesterol levels by upregulating cholesterol absorption through SREBP-2/LDLR/HMGCR pathway, and also downregulating cholesterol efflux via PPARγ/LXRα/ABCA1 pathway in vitro. In addition, plasma cholesterol is regarded as the key indicator of atherosclerosis; therefore, we believe that our findings could be used for further exploration on a possible therapeutic application of genistein for atherosclerosis.

Combined Markers to Assess Meat Intake-Human Metabolomic Studies of Discovery and Validation

SCOPE

Biomarkers of red meat may clarify the relationship between meat intake and health. This paper explores the discovery of biomarkers of intake for three types of meat with varying heme iron content. Candidate biomarkers for red and general meat are further evaluated based on defined validation criteria.

METHODS AND RESULTS

In a randomized cross-over meal study, healthy volunteers consume a randomized sequence of four test meals: chicken, pork, beef, and a control made of egg white and pea. Fasting and postprandial urine samples are collected to cover 48 h and profiled by untargeted LC-ESI-qTOF-MS metabolomics. The profiles following the meal challenges are explored by univariate and multivariate analyses. Nine red, four white, and eight general meat biomarkers are selected as putative biomarkers, originating from collagen degradation, flavour compounds, and amino acid metabolism. Heme-related metabolites are masked by the chlorophyll content of the control meal. The candidate biomarkers are confirmed in an independent meal study and validated for plausibility, robustness, time-response, and prediction performance. Combinations of biomarkers are more efficient than single markers in predicting meat intake.

CONCLUSION

New combinations of partially validated biomarkers are proposed to assess terrestrial meat intake and thus help disentangle the effects of meat consumption on human health.

Biomarkers of Nutrition and Health: New Tools for New Approaches

A main challenge in nutritional studies is the valid and reliable assessment of food intake, as well as its effects on the body. Generally, food intake measurement is based on self-reported dietary intake questionnaires, which have inherent limitations. They can be overcome by the use of biomarkers, capable of objectively assessing food consumption without the bias of self-reported dietary assessment. Another major goal is to determine the biological effects of foods and their impact on health. Systems analysis of dynamic responses may help to identify biomarkers indicative of intake and effects on the body at the same time, possibly in relation to individuals' health/disease states. Such biomarkers could be used to quantify intake and validate intake questionnaires, analyse physiological or pathological responses to certain food components or diets, identify persons with specific dietary deficiency, provide information on inter-individual variations or help to formulate personalized dietary recommendations to achieve optimal health for particular phenotypes, currently referred as "precision nutrition." In this regard, holistic approaches using global analysis methods (omics approaches), capable of gathering high amounts of data, appear to be very useful to identify new biomarkers and to enhance our understanding of the role of food in health and disease.

Role of metabolomics in identification of biomarkers related to food intake

Dietary assessment methods including FFQ and food diaries are associated with many measurement errors including energy under-reporting and incorrect estimation of portion sizes. Such errors can lead to inconsistent results especially when investigating the relationship between food intake and disease causation. To improve the classification of a person's dietary intake and therefore clarify proposed links between diet and disease, reliable and accurate dietary assessment methods are essential. Dietary biomarkers have emerged as a complementary approach to the traditional methods, and in recent years, metabolomics has developed as a key technology for the identification of new dietary biomarkers. The objective of this review is to give an overview of the approaches used for the identification of biomarkers and potential use of the biomarkers. Over the years, a number of strategies have emerged for the discovery of dietary biomarkers including acute and medium term interventions and cross-sectional/cohort study approaches. Examples of the different approaches will be presented. Concomitant with the focus on single biomarkers of specific foods, there is an interest in the development of biomarker signatures for the identification of dietary patterns. In the present review, we present an overview of the techniques used in food intake biomarker discover, including the experimental approaches used and challenges faced in the field. While significant progress has been achieved in the field of dietary biomarkers in recent years, a number of challenges remain. Addressing these challenges will be key to ensure success in implementing use of dietary biomarkers.

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

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