Metabolomics in the identification of biomarkers of dietary intake

Development of a point-of-care colorimetric metabolomic sensor platform

Metabolomics is the large-scale study of small molecule metabolites within a biological system. It has applications in measuring dietary intake, predicting heart disease risk, and diagnosing cancer. Metabolites are often measured using high-end analytical tools such as mass spectrometers or large spectrophotometers. However, due to their size, cost, and need for skilled operators, using such equipment at the bedside is not practical. To address this issue, we have developed a low-cost, portable, optical color sensor platform for metabolite detection. This platform includes LEDs, sensors, microcontrollers, a power source, and a Bluetooth chip enclosed within a 3D-printed light-tight case. We evaluated the color sensor's performance using both a range of dyed water samples as well as well-established colorimetric reactions for specific metabolite detection. The sensor accurately measured creatinine, L-carnitine, ascorbate, and succinate well within normal human urine levels with accuracy and sensitivity equal to or better than a standard laboratory spectrophotometer. Our color sensor offers a cost-effective, portable alternative for measuring metabolites via colorimetric assays, thereby enabling low-cost, point-of-care metabolite testing.

Evaluation of Food Intake Biomarkers for Red Bell Peppers in Human Urine Based on HPLC-MS/MS Analysis

SCOPE

The validation of dietary biomarkers is essential for the use in objective and quantitative assessment of the human dietary intake. In this study, the urinary excretion of previously identified potential biomarkers after intake of red bell peppers is analyzed.

METHODS AND RESULTS

The urine samples obtained after a two-phase dietary intervention study in which 14 volunteers participated are quantitatively analyzed by high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS/MS) after an extensive validation. In the first phase, the volunteers abstain completely from bell peppers and paprika products (control group) and in the second phase, the volunteers consume a defined amount of fresh red bell peppers (case group). After analysis, all potential biomarkers show high dispersions of their concentration, indicating interindividual differences. The glucuronidated apocarotenoid (compound 1), which probably resulted from the main carotenoids of red Capsicum fruits, shows a rapid urinary excretion. The other glucuronidated metabolites (compounds 2-8), described as potential derivatives of capsianosides from Capsicum, show a slightly delayed but longer urinary excretion.

CONCLUSIONS

A correlation between an intake of red bell pepper and the urinary excretion of recently described potential biomarkers is observed. Due to large interindividual differences, it is reasonable to assume that at least the qualitative detection of the consumption of bell peppers and possibly all Capsicum fruits is feasible.

A Vegetarian Diet Significantly Changes Plasma Kynurenine Concentrations

Tryptophan is an essential amino acid and a precursor of a number of physiologically important metabolites, including serotonin, melatonin, tryptamine, and kynurenines. We assessed tryptophan, kynurenines, and vitamin B2 and B6, as well as biomarkers of liver function and inflammation, in a group of 158 female omnivores and vegetarians aged 18-40 years. The majority of women were omnivores, and 22% were vegetarians. Vegetarians had 25% lower serum ALT, significantly higher pyridoxal concentrations, and significantly lower plasma concentrations of most kynurenines, varying from 8% lower concentrations of median plasma kynurenine to 42% lower concentrations of plasma xanthurenic acid, compared to omnivores. No significant differences were observed in vitamin B2 status or in inflammation markers, C-reactive protein and neopterin between the groups. Vegetarians had lower levels of several plasma kynurenines compared to omnivores. The reason for this is unknown; however, lower ALT concentrations, suggesting a better liver status, and a more favourable vitamin B6 status might be contributing factors.

Clinical assessment for diet prescription

Accurate nutritional assessment based on dietary intake, physical activity, genetic makeup, and metabolites is required to prevent from developing and/or to treat people suffering from malnutrition as well as other nutrition related health issues. Nutritional screening ought to be considered as an essential part of clinical assessment for every patient on admission to healthcare setups, as well as on change in clinical conditions. Therefore, a detailed nutritional assessment must be performed every time nutritional imbalances are observed or suspected. In this review we have explored different techniques used for nutritional and physical activity assessment. Dietary Intake (DI) assessment is a multidimensional and complex process. Traditionally, dietary intake is assessed through self-report techniques, but due to limitations like biases, random errors, misestimations, and nutrient databases-linked errors, questions arise about the adequacy of self-reporting dietary intake procedures. Despite the limitations in assessing dietary intake (DI) and physical activity (PA), new methods and improved technologies such as biomarkers analysis, blood tests, genetic assessments, metabolomic analysis, DEXA (Dual-energy X-ray absorptiometry), MRI (Magnetic resonance imaging), and CT (computed tomography) scanning procedures have made much progress in the improvement of these measures. Genes also plays a crucial role in dietary intake and physical activity. Similarly, metabolites are also involved in different nutritional pathways. This is why integrating knowledge about the genetic and metabolic markers along with the latest technologies for dietary intake (DI) and physical activity (PA) assessment holds the key for accurately assessing one's nutritional status and prevent malnutrition and its related complications.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Characterizing patterns of dietary exposure using metabolomic profiles of human biospecimens: a systematic review

CONTEXT

Establishing diet-disease associations requires reliable assessment of dietary intake. With the rapid advancement of metabolomics, its use in identifying objective biomarkers of dietary exposure has substantially increased.

OBJECTIVE

The aim of our review was to systematically combine all observational studies linking dietary intake patterns with metabolomic profiles of human biospecimens.

DATA SOURCES

Five databases were searched - MEDLINE, Embase, Scopus, Web of Science, and Cochrane CENTRAL - to March 2020.

DATA EXTRACTION

Of the 14 328 studies initially screened, 35 observational studies that met the specified inclusion criteria were included.

DATA ANALYSIS

All reviewed studies indicated that metabolomic measures were significantly correlated with dietary patterns, demonstrating the potential for using objective metabolomic measures to characterize individuals' dietary intake. However, similar dietary patterns did not always result in similar metabolomic profiles across different study populations.

CONCLUSION

Metabolomic profiles reflect a multitude of factors, including diet, genetic, phenotypic, and environmental influences, thereby providing a more comprehensive picture of the impact of diet on metabolism and health outcomes. Further exploration of dietary patterns and metabolomic profiles across different population groups is warranted.

"Fuel for the Damage Induced": Untargeted Metabolomics in Elite Rugby Union Match Play

The metabolic perturbations caused by competitive rugby are not well characterized. Our aim is to utilize untargeted metabolomics to develop appropriate interventions, based on the metabolic fluctuations that occur in response to this collision-based team sport. Seven members of an English Premiership rugby squad consented to provide blood, urine, and saliva samples daily, over a competitive week including gameday (GD), with physical demands and dietary intake also recorded. Sample collection, processing and statistical analysis were performed in accordance with best practice set out by the metabolomics standards initiative employing 700 MHz NMR spectroscopy. Univariate and multivariate statistical analysis were employed to reveal the acute energy needs of this high intensity sport are met via glycolysis, the TCA cycle and gluconeogenesis. The recovery period after cessation of match play and prior to training recommencing sees a re-entry to gluconeogenesis, coupled with markers of oxidative stress, structural protein degradation, and reduced fatty acid metabolism. This novel insight leads us to propose that effective recovery from muscle damaging collisions is dependent upon the availability of glucose. An adjustment in the periodisation of carbohydrate to increase GD+1 provision may prevent the oxidation of amino acids which may also be crucial to allay markers of structural tissue degradation. Should we expand the ‘Fuel for the work required’ paradigm in collision-based team sports to include ‘Fuel for the damage induced’?

Influence of pregnancy and non-fasting conditions on the plasma metabolome in a rat prenatal toxicity study

The current parameters for determining maternal toxicity (e.g. clinical signs, food consumption, body weight development) lack specificity and may underestimate the extent of effects of test compounds on the dams. Previous reports have highlighted the use of plasma metabolomics for an improved and mechanism-based identification of maternal toxicity. To establish metabolite profiles of healthy pregnancies and evaluate the influence of food consumption as a confounding factor, metabolite profiling of rat plasma was performed by gas- and liquid-chromatography-tandem mass spectrometry techniques. Metabolite changes in response to pregnancy, food consumption prior to blood sampling (non-fasting) as well as the interaction of both conditions were studied. In dams, both conditions, non-fasting and pregnancy, had a marked influence on the plasma metabolome and resulted in distinct individual patterns of changed metabolites. Non-fasting was characterized by increased plasma concentrations of amino acids and diet related compounds and lower levels of ketone bodies. The metabolic profile of pregnant rats was characterized by lower amino acids and glucose levels and higher concentrations of plasma fatty acids, triglycerides and hormones, capturing the normal biochemical changes undergone during pregnancy. The establishment of metabolic profiles of pregnant non-fasted rats serves as a baseline to create metabolic fingerprints for prenatal and maternal toxicity studies.

Development of Personalized Nutrition: Applications in Lactose Intolerance Diagnosis and Management

Recent discoveries in the “omics” field and the growing focus on preventive health have opened new avenues for personalized nutrition (PN), which is becoming an important theme in the strategic plans of organizations that are active in healthcare, food, and nutrition research. PN holds great potential for individual health optimization, disease management, public health interventions, and product innovation. However, there are still multiple challenges to overcome before PN can be truly embraced by the public and healthcare stakeholders. The diagnosis and management of lactose intolerance (LI), a common condition with a strong inter-individual component, is explored as an interesting example for the potential role of these technologies and the challenges of PN. From the development of genetic and metabolomic LI diagnostic tests that can be carried out in the home, to advances in the understanding of LI pathology and individualized treatment optimization, PN in LI care has shown substantial progress. However, there are still many research gaps to address, including the understanding of epigenetic regulation of lactase expression and how lactose is metabolized by the gut microbiota, in order to achieve better LI detection and effective therapeutic interventions to reverse the potential health consequences of LI.

Metabolomics study of polysaccharide extracts from Polygonatum sibiricum in mice based on 1 H NMR technology

BACKGROUND

Polygonatum sibiricum Liliaceae perennial herb, as a commonly used medicine and food homologous plant, has been widely used in clinical practice of Chinese medicine since ancient times, with a history of 2000 years. As the main active ingredient, P. sibiricum polysaccharides have important pharmacological effects in blood sugar reduction and antitumor, antioxidant and liver protection.

RESULTS

Mouse models of P. sibiricum polysaccharides were used in combination with ¹ H NMR to investigate the metabolic regulation mechanism in mouse tissue and blood. The metabolite maps of the control group and the drug group in the liver had significant changes. The main differential metabolites were glucose 6-phosphate, inositol, lactose, glutamylglycine, galactose, rhamnose, cis-aconitic acid and histidine, indicating that there was definite correlation between the metabolic detection based on ¹ H NMR and the metabolic characteristics of P. sibiricum. The common differential metabolites obtained by overall metabolism analysis were 3-hydroxybutyric acid, d-ribose, adenosine phosphate, inositol, fructose 6-phosphate, histidine, aspartic acid and cis-aconitic acid.

CONCLUSIONS

This work forms the basis for identification of metabolic states combined with metabolic pathways, which could be used as diagnostic and prognostic indicators, providing therapeutic targets for new diseases. © 2020 Society of Chemical Industry.

Potential of food intake biomarkers in nutrition research

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

Assessing Urinary Metabolomics in Giant Pandas Using Chromatography/Mass Spectrometry: Pregnancy-Related Changes in the Metabolome

Giant pandas represent one of the most endangered species worldwide, and their reproductive capacity is extremely low. They have a relatively long gestational period, mainly because embryo implantation is delayed. Giant panda cubs comprise only a small proportion of the mother's body weight, making it difficult to determine whether a giant panda is pregnant. Timely determination of pregnancy contributes to the efficient breeding and management of giant pandas. Meanwhile, metabolomics studies the metabolic composition of biological samples, which can reflect metabolic functions in cells, tissues, and organisms. This work explored the urinary metabolites of giant pandas during pregnancy. A sample of 8 female pandas was selected. Differences in metabolite levels in giant panda urine samples were analyzed via ultra-high-performance liquid chromatography/mass spectrometry comparing pregnancy to anoestrus. Pattern recognition techniques, including partial least squares-discriminant analysis and orthogonal partial least squares-discriminant analysis, were used to analyze multiple parameters of the data. Compared with the results during anoestrus, multivariate statistical analysis of results obtained from the same pandas being pregnant identified 16 differential metabolites in the positive-ion mode and 43 differential metabolites in the negative-ion mode. The levels of tryptophan, choline, kynurenic acid, uric acid, indole-3-acetaldehyde, taurine, and betaine were higher in samples during pregnancy, whereas those of xanthurenic acid and S-adenosylhomocysteine were lower. Amino acid metabolism, lipid metabolism, and organic acid production differed significantly between anoestrus and pregnancy. Our results provide new insights into metabolic changes in the urine of giant pandas during pregnancy, and the differential levels of metabolites in urine provide a basis for determining pregnancy in giant pandas. Understanding these metabolic changes could be helpful for managing pregnant pandas to provide proper nutrients to their fetuses.

Biomarkers of meat and seafood intake: an extensive literature review

Meat, including fish and shellfish, represents a valuable constituent of most balanced diets. Consumption of different types of meat and fish has been associated with both beneficial and adverse health effects. While white meats and fish are generally associated with positive health outcomes, red and especially processed meats have been associated with colorectal cancer and other diseases. The contribution of these foods to the development or prevention of chronic diseases is still not fully elucidated. One of the main problems is the difficulty in properly evaluating meat intake, as the existing self-reporting tools for dietary assessment may be imprecise and therefore affected by systematic and random errors. Dietary biomarkers measured in biological fluids have been proposed as possible objective measurements of the actual intake of specific foods and as a support for classical assessment methods. Good biomarkers for meat intake should reflect total dietary intake of meat, independent of source or processing and should be able to differentiate meat consumption from that of other protein-rich foods; alternatively, meat intake biomarkers should be specific to each of the different meat sources (e.g., red vs. white; fish, bird, or mammal) and/or cooking methods. In this paper, we present a systematic investigation of the scientific literature while providing a comprehensive overview of the possible biomarker(s) for the intake of different types of meat, including fish and shellfish, and processed and heated meats according to published guidelines for biomarker reviews (BFIrev). The most promising biomarkers are further validated for their usefulness for dietary assessment by published validation criteria.

Application of 1H-NMR Metabolomics for the Discovery of Blood Plasma Biomarkers of a Mediterranean Diet

The Mediterranean diet (MD) is a dietary pattern well-known for its benefits in disease prevention. Monitoring adherence to the MD could be improved by discovery of novel dietary biomarkers. The MEDiterranean Diet in Northern Ireland (MEDDINI) intervention study monitored the adherence of participants to the MD for up to 12 months. This investigation aimed to profile plasma metabolites, correlating each against the MD score of participants (n = 58). Based on an established 14-point scale MD score, subjects were classified into two groups (“low” and “high”). ¹H-Nuclear Magnetic Resonance (¹H-NMR) metabolomic analysis found that citric acid was the most significant metabolite (p = 5.99 × 10⁻⁴*; q = 0.03), differing between ‘low’ and ‘high’. Furthermore, five additional metabolites significantly differed (p < 0.05; q < 0.35) between the two groups. Discriminatory metabolites included: citric acid, pyruvic acid, betaine, mannose, acetic acid and myo-inositol. Additionally, the top five most influential metabolites in multivariate models were also citric acid, pyruvic acid, betaine, mannose and myo-inositol. Metabolites significantly correlated with the consumption of certain food types. For example, citric acid positively correlated fruit, fruit juice and vegetable constituents of the diet, and negatively correlated with sweet foods alone or when combined with carbonated drinks. Citric acid was the best performing biomarker and this was enhanced by paired ratio with pyruvic acid. The present study demonstrates the utility of metabolomic profiling for effectively assessing adherence to MD and the discovery of novel dietary biomarkers.

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.

Urine and fecal samples targeted metabolomics of carobs treated rats

Ceratonia siliqua, known as the carob, is considered to be of high nutritional value and of great economic significance due to its unique composition. The beneficial effects of carob against cancer, metabolic syndrome, diabetes, diarrhea, hyperlipidemia and gastro esophageal reflux disease are only a few of its therapeutic actions. Metabolomics-based analysis provides an ultimate tool, for the deciphering of nutritional intervention derived metabolic alterations. In the present study, 16 male Wistar rats were treated with carob powder for a 15-day period. Fecal and urine samples were collected at 5 time points (0, 1, 5, 10 and 15 days). By the applied HILIC-MS/MS method, 63 and 67 hydrophilic metabolites were detected in the fecal and urine samples, respectively, including amino acids, organic acids, sugars, vitamins and other endogenous compounds. A clear group separation based on fecal metabolome was observed after 1 day and 15 days treatment, while only a mild differentiation at day 1 was observed based on urine metabolome. Twenty-one fecal metabolites were responsible for the separation including amino acids and their derivatives, vitamins and organic acids. However, only 7 metabolites were altered in rat urine samples. Metabolic alterations in fecal samples could be attributed to physiological and biochemical adaptations derived from the nutritional intervention. Fecal targeted metabolomics were proven to be suitable for uplifting and highlighting such alterations.

NMR Metabolomics Protocols for Drug Discovery

Drug discovery is an extremely difficult and challenging endeavor with a very high failure rate. The task of identifying a drug that is safe, selective, and effective is a daunting proposition because disease biology is complex and highly variable across patients. Metabolomics enables the discovery of disease biomarkers, which provides insights into the molecular and metabolic basis of disease and may be used to assess treatment prognosis and outcome. In this regard, metabolomics has evolved to become an important component of the drug discovery process to resolve efficacy and toxicity issues and as a tool for precision medicine. A detailed description of an experimental protocol is presented that outlines the application of NMR metabolomics to the drug discovery pipeline. This includes (1) target identification by understanding the metabolic dysregulation in diseases, (2) predicting the mechanism of action of newly discovered or existing drug therapies, (3) and using metabolomics to screen a chemical lead to assess biological activity. Unlike other OMICS approaches, the metabolome is "fragile" and may be negatively impacted by improper sample collection, storage, and extraction procedures. Similarly, biologically irrelevant conclusions may result from incorrect data collection, preprocessing or processing procedures, or the erroneous use of univariate and multivariate statistical methods. These critical concerns are also addressed in the protocol.

Metabolomic biomarkers and novel dietary factors associated with gestational diabetes in China

INTRODUCTION

Gestational diabetes mellitus (GDM) is impaired glucose tolerance first recognised during pregnancy; its development is associated with many adverse outcomes. Mechanisms of GDM development are not fully elucidated and few studies have used Chinese participants.

OBJECTIVES

The aim of this study was to investigate the maternal metabolome associated with GDM in a Chinese population, and explore the relationship with maternal diet.

METHODS

Ninety-three participants were recruited at 26-28 weeks' gestation from Chongqing, China. Maternal urine, serum, and hair metabolomes were analysed using gas and liquid chromatography-mass spectrometry. Dietary intake was assessed using a 96-item food frequency questionnaire.

RESULTS

Of the 1064 metabolites identified, 73 were significantly different between cases and controls (P < 0.05), but only 2-aminobutyric acid had both a p- and q-value < 0.05. A "snack-based-dietary-pattern" was associated with an increased likelihood of GDM (odds ratio 2·1; 95% confidence interval 1.1-3.9). The association remained significant after adjustment for calorie intake but not food volume.

CONCLUSION

This study provides a comprehensive characterization of the maternal metabolome. The snack-based dietary pattern associated with GDM suggests that timing and frequency of consumption are important factors in the relationship between maternal diet and GDM.

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

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

Serum untargeted metabolomic profile of the Dietary Approaches to Stop Hypertension (DASH) dietary pattern

Background

The Dietary Approaches to Stop Hypertension (DASH) dietary pattern is recommended for cardiovascular disease risk reduction. Assessment of dietary intake has been limited to subjective measures and a few biomarkers from 24-h urine collections.

Objective

The aim of the study was to use metabolomics to identify serum compounds that are associated with adherence to the DASH dietary pattern.

Design

We conducted untargeted metabolomic profiling in serum specimens collected at the end of 8 wk following the DASH diet (n = 110), the fruit and vegetables diet (n = 111), or a control diet (n = 108) in a multicenter, randomized clinical feeding study (n = 329). Multivariable linear regression was used to determine the associations between the randomized diets and individual log-transformed metabolites after adjustment for age, sex, race, education, body mass index, and hypertension. Partial least-squares discriminant analysis (PLS-DA) was used to identify a panel of compounds that discriminated between the dietary patterns. The area under the curve (C statistic) was calculated as the cumulative ability to distinguish between dietary patterns. We accounted for multiple comparisons with the use of the Bonferroni method (0.05 of 818 metabolites = 6.11 × 10-5).

Results

Serum concentrations of 44 known metabolites differed significantly between participants randomly assigned to the DASH diet compared with both the control diet and the fruit and vegetables diet, which included an amino acid, 2 cofactors and vitamins (n = 2), and lipids (n = 41). With the use of PLS-DA, component 1 explained 29.4% of the variance and component 2 explained 12.6% of the variance. The 10 most influential metabolites for discriminating between the DASH and control dietary patterns were N-methylproline, stachydrine, tryptophan betaine, theobromine, 7-methylurate, chiro-inositol, 3-methylxanthine, methyl glucopyranoside, β-cryptoxanthin, and 7-methylxanthine (C statistic = 0.986).

Conclusions

An untargeted metabolomic platform identified a broad array of serum metabolites that differed between the DASH diet and 2 other dietary patterns. This newly identified metabolite panel may be used to assess adherence to the DASH dietary pattern. This trial was registered at http://www.clinicaltrials.gov as NCT03403166.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusions

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

Comparative Metabolomics Elucidates Postprandial Metabolic Modifications in Plasma of Obese Individuals with Metabolic Syndrome

Although higher intakes of dairy milk are associated with a lower risk of metabolic syndrome (MetS), the underlying protective mechanism remains unclear. This study investigated the dynamic metabolic profile shift following the ingestion of low-fat milk or an isocaloric volume of rice milk in obese individuals with metabolic syndrome (MetS). In a randomized, double-blind, crossover study, postprandial plasma samples ( n = 266) were collected from 19 MetS participants. Plasma samples were analyzed by a targeted metabolomics platform which specifically detects 117 metabolites from 25 metabolic pathways. The comprehensive time-course metabolic profiling in MetS participants indicated that the postprandial metabolic profiles distinguish low-fat milk and rice milk consumption in a time-dependent manner. Metabolic biomarkers, such as orotate, leucine/isoleucine and adenine, showed significantly different trends in the two test beverages. Bayesian statistics identified 12 metabolites associated with clinical characteristics of postprandial vascular endothelial function, such as flow-mediated dilation (FMD), postprandial plasma markers of oxidative stress and NO status. Furthermore, metabolic pathway analysis based on these metabolite data indicated the potential utility of metabolomics to provide mechanistic insights of dietary interventions to regulate postprandial metabolic excursions.

A systematic review of metabolite biomarkers of schizophrenia

Current diagnosis of schizophrenia relies exclusively on the potentially subjective interpretation of clinical symptoms and social functioning as more objective biological measurement and medical diagnostic tests are not presently available. The use of metabolomics in the discovery of disease biomarkers has grown in recent years. Metabolomic methods could aid in the discovery of diagnostic biomarkers of schizophrenia. This systematic review focuses on biofluid metabolites associated with schizophrenia. A systematic search of Web of Science and Ovid Medline databases was conducted and 63 studies investigating metabolite biomarkers of schizophrenia were included. A review of these studies revealed several potential metabolite signatures of schizophrenia including reduced levels of essential polyunsaturated fatty acids (EPUFAs), vitamin E and creatinine; and elevated levels of lipid peroxidation metabolites and glutamate. Further research is needed to validate these biomarkers and would benefit from large cohort studies and more homogeneous and well-defined subject groups.

Validation of the Brazilian Healthy Eating Index-Revised Using Biomarkers in Children and Adolescents

The Brazilian Healthy Eating Index-Revised (BHEI-R) can be used to determine overall dietary patterns. We assessed the BHEI-R scores in children and adolescents, aged from 9 to 13 years old, and associated its component scores with biomarkers of health and dietary exposure. Three 24-h recalls were used to generate BHEI-R. Biomarkers were analyzed in plasma and red blood cells. Correlation tests, agreement, and covariance analyses were used to associate BHEI-R components with biomarkers. Data from 167 subjects were used. The strongest correlations were between fruits, vegetables and legumes with omega-6 and omega-3 fatty acids, and β-carotene intakes. Milk and dairy correlated with plasma retinol and pyridoxine. All components rich in vegetable and animal protein sources correlated with plasma creatine. Total BHEI-R scores were positively associated with intakes of omega-6, omega-3, fiber and vitamin C, and inversely associated with energy and saturated fat intakes of individuals. Plasma β-carotene and riboflavin biomarkers were positively associated with total BHEI-R. An inadequate food consumption pattern was captured by both biomarkers of health and dietary exposure. BHEI-R was validated for the above dietary components and can be associated with metabolomics and nutritional epidemiological data in future pediatric studies.

School-based primary NCD risk reduction: education and public health perspectives

The rising global burden of noncommunicable diseases (NCDs) has heightened awareness of the necessity for primary risk prevention programmes. These aim to facilitate long-term behaviour changes in children and adolescents that can reduce NCD risk factors and disease onset in later-life. School-based programmes designed to improve childhood and adolescent health behaviours and wellbeing contribute to this; however, design and impact assessment of these is complex. These programmes should be multidisciplinary, utilizing both educational and health expertise. Health outcomes may not be evident in the short term, but may occur with learning-related behaviour modifications, highly effective when sustained over a lifetime. Thus assessment must analyse short-term learning and behaviour impacts as well as long-term capability, behaviour and health outcomes.The focus of assessment measures in the health and education sectors differs and often lacks depth in one or other area. Educators generally focus on identifying evidence of learning related to capability, attitude and/or behaviour changes, while public health practitioners typically focus on health measures (e.g. body mass index (BMI), mental health, or risk behaviours).We argue that multidisciplinary approaches incorporating education and health viewpoints clarify issues relating to the potential value of schools as a setting to facilitate primary NCD risk reduction. To demonstrate this, we need to: 1) build stronger understandings of the features of effective learning for behavioural change and the best way to evaluate these, and 2) convincingly correlate these measures with long-term metabolic health indicators by tracking learner behaviour and health over time.

Estimation of Chicken Intake by Adults Using Metabolomics-Derived Markers

BACKGROUND

Improved assessment of meat intake with the use of metabolomics-derived markers can provide objective data and could be helpful in clarifying proposed associations between meat intake and health.

OBJECTIVE

The objective of this study was to identify novel markers of chicken intake using a metabolomics approach and use markers to determine intake in an independent cohort.

METHODS

Ten participants [age: 62 y; body mass index (in kg/m2): 28.25] in the NutriTech food intake study consumed increasing amounts of chicken, from 88 to 290 g/d, in a 3-wk span. Urine and blood samples were analyzed by nuclear magnetic resonance and mass spectrometry, respectively. A multivariate data analysis was performed to identify markers associated with chicken intake. A calibration curve was built based on dose-response association using NutriTech data. A Bland-Altman analysis evaluated the agreement between reported and calculated chicken intake in a National Adult Nutrition Survey cohort.

RESULTS

Multivariate data analysis of postprandial and fasting urine samples collected in participants in the NutriTech study revealed good discrimination between high (290 g/d) and low (88 g/d) chicken intakes. Urinary metabolite profiles showed differences in metabolite levels between low and high chicken intakes. Examining metabolite profiles revealed that guanidoacetate increased from 1.47 to 3.66 mmol/L following increasing chicken intakes from 88 to 290 g/d (P < 0.01). Using a calibration curve developed from the NutriTech study, chicken intake was calculated through the use of data from the National Adult Nutrition Survey, in which consumers of chicken had a higher guanidoacetate excretion (0.70 mmol/L) than did nonconsumers (0.47 mmol/L; P < 0.01). A Bland-Altman analysis revealed good agreement between reported and calculated intakes, with a bias of -30.2 g/d. Plasma metabolite analysis demonstrated that 3-methylhistidine was a more suitable indicator of chicken intake than 1-methylhistidine.

CONCLUSIONS

Guanidoacetate was successfully identified and confirmed as a marker of chicken intake, and its measurement in fasting urine samples could be used to determine chicken intake in a free-living population. This trial was registered at clinicaltrials.gov as NCT01684917.

Identification of Urinary Polyphenol Metabolite Patterns Associated with Polyphenol-Rich Food Intake in Adults from Four European Countries

We identified urinary polyphenol metabolite patterns by a novel algorithm that combines dimension reduction and variable selection methods to explain polyphenol-rich food intake, and compared their respective performance with that of single biomarkers in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. The study included 475 adults from four European countries (Germany, France, Italy, and Greece). Dietary intakes were assessed with 24-h dietary recalls (24-HDR) and dietary questionnaires (DQ). Thirty-four polyphenols were measured by ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS-MS) in 24-h urine. Reduced rank regression-based variable importance in projection (RRR-VIP) and least absolute shrinkage and selection operator (LASSO) methods were used to select polyphenol metabolites. Reduced rank regression (RRR) was then used to identify patterns in these metabolites, maximizing the explained variability in intake of pre-selected polyphenol-rich foods. The performance of RRR models was evaluated using internal cross-validation to control for over-optimistic findings from over-fitting. High performance was observed for explaining recent intake (24-HDR) of red wine (r = 0.65; AUC = 89.1%), coffee (r = 0.51; AUC = 89.1%), and olives (r = 0.35; AUC = 82.2%). These metabolite patterns performed better or equally well compared to single polyphenol biomarkers. Neither metabolite patterns nor single biomarkers performed well in explaining habitual intake (as reported in the DQ) of polyphenol-rich foods. This proposed strategy of biomarker pattern identification has the potential of expanding the currently still limited list of available dietary intake biomarkers.

Metabolomics in nutrition research-a powerful window into nutritional metabolism

Metabolomics is the study of small molecules present in biological samples. In recent years it has become evident that such small molecules, called metabolites, play a key role in the development of disease states. Furthermore, metabolomic applications can reveal information about alterations in certain metabolic pathways under different conditions. Data acquisition in metabolomics is usually performed using nuclear magnetic resonance (NMR)-based approaches or mass spectrometry (MS)-based approaches with a more recent trend including the application of multiple platforms in order to maximise the coverage in terms of metabolites measured. The application of metabolomics is rapidly increasing and the present review will highlight applications in nutrition research.

Use of biomarkers to assess fruit and vegetable intake

A high intake of fruit and vegetables (FV) has been associated with reduced risk of a number of chronic diseases, including CVD. The aim of this review is to describe the potential use of biomarkers to assess FV intake. Traditional methods of assessing FV intake have limitations, and this is likely to impact on observed associations with disease outcomes and markers of disease risk. Nutritional biomarkers may offer a more objective and reliable method of assessing dietary FV intake. Some single blood biomarkers, such as plasma vitamin C and serum carotenoids, are well established as indicators of FV intake. Combining potential biomarkers of intake may more accurately predict overall FV intake within intervention studies than the use of any single biomarker. Another promising approach is metabolomic analysis of biological fluids using untargeted approaches to identify potential new biomarkers of FV intake. Using biomarkers to measure FV intake may improve the accuracy of dietary assessment.

A systematic review of food composition tools used for determining dietary polyphenol intake in estimated intake studies

Translating food intake data into phytochemical outcomes is a crucial step in investigating potential health benefits. The aim of this review was to examine the tools for determining dietary-derived polyphenol intakes for estimated intake studies. Published studies from 2004 to 2014 reporting polyphenol food composition information were sourced with 157 studies included. Six polyphenol subclasses were identified. One quarter of studies (n=39) reported total flavonoids intake with 27% reporting individual flavonoid compounds. Assessing multiple compounds was common with approximately 10% of studies assessing seven (n=13), six (n=12) and five (n=14) subclasses of polyphenol. There was no pattern between reported flavonoids compounds and subclass studied. Approximately 60% of studies relied on publicly accessible food composition data to estimate dietary polyphenols intake with 33% using two or more tools. This review highlights the importance of publicly accessible composition databases for estimating polyphenol intake and provides a reference for tools available globally.

Nontargeted LC-MSn Profiling of Compounds in Ileal Fluids That Decrease after Raspberry Intake Identifies Consistent Alterations in Bile Acid Composition

Ileostomy studies provide a unique insight into the digestion of foods, allowing identification of physiologically relevant dietary phytochemicals and their metabolites that are important to gut health. We previously reported an increase of components, including novel triterpenoids, in ileal fluids of 11 ileostomates following consumption of raspberries using nontargeted LC-MSⁿ techniques in combination with data deconvolution software. The current study focused on components that consistently decreased postsupplementation. After data deconvolution, 32 components were identified that met exclusion parameters of m/z signals and which decreased significantly in ileal fluids from eight of 11 participants post-raspberry supplementation. Two-thirds of these components were identified putatively from their MS properties. Consistent decreases were observed in components that possibly reflected "washing out" of presupplementation intake of common foods/drinks including (poly)phenol metabolites. Metabolites associated with fat metabolism such as hydroxylated fatty acids and cholate-type bile acids were specifically reduced. However, more directed re-examination of the data revealed that although some cholates were consistently reduced, the more polar glyco- and tauro-linked bile acid derivatives increased consistently, by as much as 100-fold over presupplementation levels. The possible reasons for these substantial alterations in bile acid composition in ileal fluids in response to raspberry intake are discussed.

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.

Assessment of dietary exposure and effect in humans: The role of NMR

In human nutritional science progress has always depended strongly on analytical measurements for establishing relationships between diet and health. This field has undergone significant changes as a result of the development of NMR and mass spectrometry methods for large scale detection, identification and quantification of metabolites in body fluids. This has allowed systematic studies of the metabolic fingerprints that biological processes leave behind, and has become the research field of metabolomics. As a metabolic profiling technique, NMR is at its best when its unbiased nature, linearity and reproducibility are exploited in well-controlled nutritional intervention and cross-sectional population screening studies. Although its sensitivity is less good than that of mass spectrometry, NMR has maintained a strong position in metabolomics through implementation of standardisation protocols, hyphenation with mass spectrometry and chromatographic techniques, accurate quantification and spectral deconvolution approaches, and high-throughput automation. Thus, NMR-based metabolomics has contributed uniquely to new insights into dietary exposure, in particular by unravelling the metabolic fates of phytochemicals and the discovery of dietary intake markers. NMR profiling has also contributed to the understanding of the subtle effects of diet on central metabolism and lipoprotein metabolism. In order to hold its ground in nutritional metabolomics, NMR will need to step up its performance in sensitivity and resolution; the most promising routes forward are the analytical use of dynamic nuclear polarisation and developments in microcoil construction and automated fractionation.

Nutrition recommendations and science: next parallel steps

This article examines nutrition recommendations in relation to developments in nutrition science. Combining data on the genome, metabolome and microbiota is likely to open possibilities for personalized nutrition planning, but we are still far from practical applications. However, even these new steps are unlikely to challenge the role and importance of population-based nutrition recommendations as a tool to promote dietary patterns, policies and public health. Developments in science could help in deriving more benefits from nutrition recommendations. For instance, improved accuracy of dietary intake assessment is needed both for surveillance and for understanding the quantitative interplay between diet and health. Applying metabolomics together with food diaries or questionnaires, and also modern technologies such as digital photography, are potentially interesting methods in this respect. Research on consumer behaviour, attitudes and policy interventions, such as taxation of unhealthy foods and nutrition labelling, are needed to gain more insight into how to change eating behaviour for better health at the population level.

Food-Based Interventions to Modify Diet Quality and Diversity to Address Multiple Micronutrient Deficiency

Global data indicate a high prevalence of hidden hunger among population. Deficiencies of certain micronutrients such as folic acid, iodine, iron, and vitamin A have long lasting effects on growth and development and therefore have been a National priority from many decades. The strategy implemented so far limits to the use of supplemental sources or fortified foods in alleviating the burden of deficiencies. These approaches however undermine the food-based strategies involving dietary diversification as the long-term sustainable strategy. There is lack of understanding on the level of evidence needed to implement such strategies and the level of monitoring required for impact evaluation. Dietary diversity concerns how to ensure access for each individual to a quality and safe diet with adequate macro- and micronutrients. The key to success in using dietary diversity as a strategy to tackle hidden hunger is in integrating it with the principles of bioavailability, translated to efficient food synergies with due emphasis on food accessibility, affordability, and outdoor physical activity/life style modifications. Promoting enabling environment and sustainable agriculture is crucial for practicing dietary diversification with behavior change communication as an integral segment. It can be concluded that food-based strategies require careful understanding of the factors associated with it and moderate it to form an effective strategy for controlling multiple micronutrient deficiencies.

1H-NMR based metabolomics study for the detection of the human urine metabolic profile effects of Origanum dictamnus tea ingestion

NMR based metabolomics clarify theOriganum dictamnustea effect upon the human urine metabolome.

New findings on the in vivo antioxidant activity of Curcuma longa extract by an integrated (1)H NMR and HPLC-MS metabolomic approach

Curcuminoids possess powerful antioxidant activity as demonstrated in many chemical in vitro tests and in several in vivo trials. Nevertheless, the mechanism of this activity is not completely elucidated and studies on the in vivo antioxidant effects are still needed. Metabolomics may be used as an attractive approach for such studies and in this paper, we describe the effects of oral administration of a Curcuma longa L. extract (150 mg/kg of total curcuminoids) to 12 healthy rats with particular attention to urinary markers of oxidative stress. The experiment was carried out over 33 days and changes in the 24-h urine samples metabolome were evaluated by (1)H NMR and HPLC-MS. Both techniques produced similar representations for the collected samples confirming our previous study. Modifications of the urinary metabolome lead to the observation of different variables proving the complementarity of (1)H NMR and HPLC-MS for metabolomic purposes. The urinary levels of allantoin, m-tyrosine, 8-hydroxy-2'-deoxyguanosine, and nitrotyrosine were decreased in the treated group thus supporting an in vivo antioxidant effect of the oral administration of Curcuma extract to healthy rats. On the other hand, urinary TMAO levels were higher in the treated compared to the control group suggesting a role of curcumin supplementation on microbiota or on TMAO urinary excretion. Furthermore, the urinary levels of the sulphur containing compounds taurine and cystine were also changed suggesting a role for such constituents in the biochemical pathways involved in Curcuma extract bioactivity and indicating the need for further investigation on the complex role of antioxidant curcumin effects.

Postprandial metabolomics: A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal

The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms - gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) - to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1-86% for GC-MS and 0.9-42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2-97% for the positive and 4-69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a multi-platform metabolomics approach followed by multivariate and univariate data analysis for a broad-scale screen of the individual metabolome, particularly for studies using repeated measures to determine dietary response phenotype.

Herring and Beef Meals Lead to Differences in Plasma 2-Aminoadipic Acid, β-Alanine, 4-Hydroxyproline, Cetoleic Acid, and Docosahexaenoic Acid Concentrations in Overweight Men

BACKGROUND

Dietary guidelines generally recommend increasing fish intake and reducing red meat intake for better long-term health. Few studies have compared the metabolic differences between eating meat and fish.

OBJECTIVE

The objective of this study was to determine whether there are differences in the postprandial plasma metabolic response to meals containing baked beef, baked herring, and pickled herring.

METHODS

Seventeen overweight men (BMI 25-30 kg/m(2), 41-67 y of age) were included in a randomized crossover intervention study. Subjects ate baked herring-, pickled herring-, and baked beef-based meals in a randomized order and postprandial blood plasma samples were taken over 7 h. Plasma metabolomics were measured with the use of gas chromatography-mass spectrometry and areas under the curve for detected metabolites were compared between meals.

RESULTS

The plasma postprandial response of 2-aminoadipic acid, a suggested marker of diabetes risk, was 1.6 times higher after the beef meal than after the baked herring meal (P < 0.001). Plasma β-alanine and 4-hydroxyproline both were markedly greater after beef intake than after herring intake (16 and 3.4 times the response of baked herring, respectively; P < 0.001). Herring intake led to a greater plasma postprandial response from docosahexaenoic acid (DHA) and cetoleic acid compared with beef (17.6 and 150 times greater, respectively; P < 0.001), whereas hippuric acid and benzoic acid were elevated after pickled herring compared with baked herring (5.4 and 43 times higher; P < 0.001).

CONCLUSIONS

These results in overweight men confirm that DHA and cetoleic acid reflect herring intake, whereas β-alanine and 4-hydroxyproline are potential biomarkers for beef intake. The greater postprandial rise in 2-aminoadipic acid after the beef meal, coupled to its proposed role in stimulating insulin secretion, may have importance in the context of red meat intake and increased diabetes risk. This trial was registered at clinicaltrials.gov as NCT02381613.

Metabolomics to Explore Impact of Dairy Intake

Dairy products are an important component in the Western diet and represent a valuable source of nutrients for humans. However, a reliable dairy intake assessment in nutrition research is crucial to correctly elucidate the link between dairy intake and human health. Metabolomics is considered a potential tool for assessment of dietary intake instead of traditional methods, such as food frequency questionnaires, food records, and 24-h recalls. Metabolomics has been successfully applied to discriminate between consumption of different dairy products under different experimental conditions. Moreover, potential metabolites related to dairy intake were identified, although these metabolites need to be further validated in other intervention studies before they can be used as valid biomarkers of dairy consumption. Therefore, this review provides an overview of metabolomics for assessment of dairy intake in order to better clarify the role of dairy products in human nutrition and health.

Identification and monitoring of metabolite markers of dry bean consumption in parallel human and mouse studies

SCOPE

Aim of the study was to identify and monitor metabolite markers of dry bean consumption in parallel human and mouse studies that each had shown chemopreventive effects of dry bean consumption on colorectal neoplasia risk.

METHODS AND RESULTS

Using LC/mass spectroscopy ± ESI and GC/mass spectroscopy, serum metabolites of dry beans were measured in 46 men before and after a 4-week dry bean enriched diet (250 g/day) and 12 mice that received a standardized diet containing either 0 or 10% navy bean ethanol extract for 6 weeks; we also investigated fecal metabolites in the mice. The serum metabolites identified in these controlled feeding studies were then investigated in 212 polyp-free participants from the Polyp Prevention Trial who self-reported either increased (≥+31 g/day from baseline), high dry bean intake of ≥42 g/day in year 3 or low, unchanged dry bean consumption of <8 g/day; serum was analyzed from baseline and year 3. Serum pipecolic acid and S-methyl cysteine were elevated after dry bean consumption in human and mouse studies and reflected dry bean consumption in the Polyp Prevention Trial.

CONCLUSION

Serum levels of pipecolic acid and S-methyl cysteine are useful biomarkers of dry bean consumption.

Systems-based approaches to unravel multi-species microbial community functioning

Some of the most transformative discoveries promising to enable the resolution of this century's grand societal challenges will most likely arise from environmental science and particularly environmental microbiology and biotechnology. Understanding how microbes interact in situ, and how microbial communities respond to environmental changes remains an enormous challenge for science. Systems biology offers a powerful experimental strategy to tackle the exciting task of deciphering microbial interactions. In this framework, entire microbial communities are considered as metaorganisms and each level of biological information (DNA, RNA, proteins and metabolites) is investigated along with in situ environmental characteristics. In this way, systems biology can help unravel the interactions between the different parts of an ecosystem ultimately responsible for its emergent properties. Indeed each level of biological information provides a different level of characterisation of the microbial communities. Metagenomics, metatranscriptomics, metaproteomics, metabolomics and SIP-omics can be employed to investigate collectively microbial community structure, potential, function, activity and interactions. Omics approaches are enabled by high-throughput 21st century technologies and this review will discuss how their implementation has revolutionised our understanding of microbial communities.

The same microbiota and a potentially discriminant metabolome in the saliva of omnivore, ovo-lacto-vegetarian and Vegan individuals

The salivary microbiota has been linked to both oral and non-oral diseases. Scant knowledge is available on the effect of environmental factors such as long-term dietary choices on the salivary microbiota and metabolome. This study analyzed the microbial diversity and metabolomic profiles of the saliva of 161 healthy individuals who followed an omnivore or ovo-lacto-vegetarian or vegan diet. A large core microbiota was identified, including 12 bacterial genera, found in >98% of the individuals. The subjects could be stratified into three “salivary types” that differed on the basis of the relative abundance of the core genera Prevotella, Streptococcus/Gemella and Fusobacterium/Neisseria. Statistical analysis indicated no effect of dietary habit on the salivary microbiota. Phylogenetic beta-diversity analysis consistently showed no differences between omnivore, ovo-lacto-vegetarian and vegan individuals. Metabolomic profiling of saliva using ¹H-NMR and GC-MS/SPME identified diet-related biomarkers that enabled a significant discrimination between the 3 groups of individuals on the basis of their diet. Formate, urea, uridine and 5-methyl-3-hexanone could discriminate samples from omnivores, whereas 1-propanol, hexanoic acid and proline were characteristic of non-omnivore diets. Although the salivary metabolome can be discriminating for diet, the microbiota has a remarkable inter-individual stability and did not vary with dietary habits. Microbial homeostasis might be perturbed with sub-standard oral hygiene or other environmental factors, but there is no current indication that a choice of an omnivore, ovo-lacto-vegetarian or vegan diet can lead to a specific composition of the oral microbiota with consequences on the oral homeostasis.

NMR-based metabolomics: from sample preparation to applications in nutrition research

Metabolomics is the study of metabolites present in biological samples such as biofluids, tissue/cellular extracts and culture media. Measurement of these metabolites is achieved through use of analytical techniques such as NMR and mass spectrometry coupled to liquid chromatography. Combining metabolomic data with multivariate data analysis tools allows the elucidation of alterations in metabolic pathways under different physiological conditions. Applications of NMR-based metabolomics have grown in recent years and it is now widely used across a number of disciplines. The present review gives an overview of the developments in the key steps involved in an NMR-based metabolomics study. Furthermore, there will be a particular emphasis on the use of NMR-based metabolomics in nutrition research.

Habitual dietary intake impacts on the lipidomic profile

Reliable dietary assessments are essential when attempting to understand the complex links between diet and health. Traditional methods for collecting dietary exposure can be unreliable, therefore there is an increasing interest in identifying biomarkers to provide a more accurate measurement. Metabolomics is a technology that offers great promise in this area. The aim of this study was to use a multivariate statistical strategy to link lipidomic patterns with dietary data in an attempt to identify dietary biomarkers. We assessed the relationship between lipidomic profiles and dietary data in volunteers (n=34) from the Metabolic Challenge Study (MECHE). Principal component analysis (PCA), linear regression and receiver operating characteristic (ROC) analysis were used to (1) reduce the lipidomic data into lipid patterns (LPs), (2) investigate relationships between these patterns and dietary data and (3) identify biomarkers of dietary intake. Our study identified a total of 6 novel LPs. LP1 was highly predictive of dietary fat intake (area under the curve AUC=0.82). A random forest (RF) classification model used to discriminate between low and high consumers resulted with an error rate of >10%, with a panel of six metabolites identified as the most predictive. LP4 was highly predictive of alcohol intake (AUC=0.81) with lysophosphatidylcholine alkyl C18:0 (LPCeC18:0) identified as a potential biomarker of alcohol consumption. LP6 had a reasonably good ability to predict dietary fish intake (AUC=0.76), with lysophosphatidylethanolamine acyl C18:2 (LPEaC18:2) phoshatidylethanolamine diaclyl C38:4 (PEaaC38:4) identified as potential biomarkers. The identification of these LPs and specific biomarkers will help in better classifying a persons dietary intake and in turn will improve the assessment of the relationship between diet and disease. Linking these LPs and specific biomarkers with health parameters will be an important future step.