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

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.

Influence of Lactose Supplementation on Regulation of Streptococcus thermophilus on Gut Microbiota

It has been found that Streptococcus thermophilus (S. thermophilus) influenced the gut microbiota and host metabolism with strain specificity in C57BL/6J mice in the previous study, though it remains unclear whether lactose as a dietary factor associated with dairy consumption is involved as the mediator in the interaction. In the present study, integrated analysis of 16S rRNA gene sequencing and untargeted metabolomics by liquid chromatography-mass spectrometry of fecal samples in C57BL/6J mice was applied to evaluate the effect of lactose on the regulation of gut microbiota by two S. thermophilus strains (4M6 and DYNDL13-4). The results showed that the influence of lactose supplementation on gut microbiota induced by S. thermophilus ingestion was strain-specific. Although two S. thermophilus strains ingestion introduced similar perturbations in the fecal microbiota and gut microbial metabolism, the regulation of DYNDL13-4 on the gut microbiota and metabolism was more affected by lactose than 4M6. More specifically, lactose and 4M6 supplementation mainly enriched pathways of d-glutamine and d-glutamate metabolism, alanine, aspartate, and glutamate metabolism, and tryptophan and phenylalanine metabolism in the gut, whereas 4M6 only enriched tryptophan and phenylalanine metabolism. DYNDL13-4-L (DYNDL13-4 with lactose) had significant effects on sulfur, taurine, and hypotaurine metabolism in the gut and on phenylalanine, tyrosine, tryptophan biosynthesis, and linoleic acid metabolism in serum relative to the DYNDL13-4. Our study demonstrated the strain-specific effect of lactose and S. thermophilus supplementation on gut microbiota and host metabolism. However, considering the complexity of the gut microbiota, further research is necessary to provide insights to facilitate the design of personalized fermented milk products as a dietary therapeutic strategy for improving host health.

Identifying Plasma and Urinary Biomarkers of Fermented Food Intake and Their Associations with Cardiometabolic Health in a Dutch Observational Cohort

Identification of food intake biomarkers (FIBs) for fermented foods could help improve their dietary assessment and clarify their associations with cardiometabolic health. We aimed to identify novel FIBs for fermented foods in the plasma and urine metabolomes of 246 free-living Dutch adults using nontargeted LC-MS and GC-MS. Furthermore, associations between identified metabolites and several cardiometabolic risk factors were explored. In total, 37 metabolites were identified corresponding to the intakes of coffee, wine, and beer (none were identified for cocoa, bread, cheese, or yoghurt intake). While some of these metabolites appeared to originate from raw food (e.g., niacin and trigonelline for coffee), others overlapped different fermented foods (e.g., 4-hydroxybenzeneacetic acid for both wine and beer). In addition, several fermentation-dependent metabolites were identified (erythritol and citramalate). Associations between these identified metabolites with cardiometabolic parameters were weak and inconclusive. Further evaluation is warranted to confirm their relationships with cardiometabolic disease risk.

Serum and Urine Metabolites in Healthy Men after Consumption of Acidified Milk and Yogurt

The identification of molecular biomarkers that can be used to quantitatively link dietary intake to phenotypic traits in humans is a key theme in modern nutritional research. Although dairy products (with and without fermentation) represent a major food group, the identification of markers of their intake lags behind that of other food groups. Here, we report the results from an analysis of the metabolites in postprandial serum and urine samples from a randomized crossover study with 14 healthy men who ingested acidified milk, yogurt, and a non-dairy meal. Our study confirms the potential of lactose and its metabolites as markers of lactose-containing dairy foods and the dependence of their combined profiles on the fermentation status of the consumed products. Furthermore, indole-3-lactic acid and 3-phenyllactic acid are two products of fermentation whose postprandial behaviour strongly discriminates yogurt from milk intake. Our study also provides evidence of the ability of milk fermentation to increase the acute delivery of free amino acids to humans. Notably, 3,5-dimethyloctan-2-one also proves to be a specific marker for milk and yogurt consumption, as well as for cheese consumption (previously published data). These molecules deserve future characterisation in human interventional and observational studies.

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.

Innovative Application of Metabolomics on Bioactive Ingredients of Foods

Metabolomics, as a new omics technology, has been widely accepted by researchers and has shown great potential in the field of nutrition and health in recent years. This review briefly introduces the process of metabolomics analysis, including sample preparation and extraction, derivatization, separation and detection, and data processing. This paper focuses on the application of metabolomics in food-derived bioactive ingredients. For example, metabolomics techniques are used to analyze metabolites in food to find bioactive substances or new metabolites in food materials. Moreover, bioactive substances have been tested in vitro and in vivo, as well as in humans, to investigate the changes of metabolites and the underlying metabolic pathways, among which metabolomics is used to find potential biomarkers and targets. Metabolomics provides a new approach for the prevention and regulation of chronic diseases and the study of the underlying mechanisms. It also provides strong support for the development of functional food or drugs. Although metabolomics has some limitations such as low sensitivity, poor repeatability, and limited detection range, it is developing rapidly in general, and also in the field of nutrition and health. At the end of this paper, we put forward our own insights on the development prospects of metabolomics in the application of bioactive ingredients in food.

Molecular effects of the consumption of margarine and butter varying in trans fat composition: a parallel human intervention study

BACKGROUND

Whereas the dietary intake of industrial trans fatty acids (iTFA) has been specifically associated with inflammation, cardiovascular disease, and type 2 diabetes, understanding the impact of dietary fats on human health remains challenging owing to their complex composition and individual effects of their lipid components on metabolism. The aim of this study is to profile the composition of blood, measured by the fatty acid (FAs) profile and untargeted metabolome of serum and the transcriptome of blood cells, in order to identify molecular signatures that discriminate dietary fat intakes.

METHODS

In a parallel study, the molecular effects of consuming dairy fat containing ruminant TFA (rTFA) or margarine containing iTFA were investigated. Healthy volunteers (n = 42; 45-69 y) were randomly assigned to diets containing margarine without TFA as major source of fat (wTFA control group with 0.4 g TFA per 100 g margarine), margarine with iTFA (iTFA group with 4.1 g TFA per 100 g margarine), or butter with rTFA (rTFA group with 6.3 g TFA per 100 g butter) for 4 weeks. The amounts of test products were individually selected so that fat intake contributed to 30-33% of energy requirements and TFA in the rTFA and iTFA groups contributed to up to 2% of energy intake. Changes in fasting blood values of lipid profiles (GC with flame-ionization detection), metabolome profiles (LC-MS, GC-MS), and gene expression (microarray) were measured.

RESULTS

Eighteen FAs, as well as 242 additional features measured by LC-MS (185) and GC-MS (54) showed significantly different responses to the diets (P_FDR-adjusted < 0.05), mainly distinguishing butter from the margarine diets while gene expression was not differentially affected. The most abundant TFA in the butter, i.e. TFA containing (E)-octadec-11-enoic acid (C18:1 t11; trans vaccenic acid), and margarines, i.e. TFA containing (E)-octadec-9-enoic acid (C18:1 t9; elaidic acid) were reflected in the significantly different serum levels of TFAs measured after the dietary interventions.

CONCLUSIONS

The untargeted serum metabolome differentiates margarine from butter intake although the identification of the discriminating features remains a bottleneck. The targeted serum FA profile provides detailed information on specific molecules differentiating not only butter from margarine intake but also diets with different content of iTFAs in margarine.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00933322.

Breath response following a nutritional challenge monitored by secondary electrospray ionization high-resolution mass spectrometry

On-line breath analysis using secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS) is a sensitive method for biomarker discovery. The strengths of this technology have already been demonstrated in the clinical environment. For the first time, this study demonstrates the application of SESI-HRMS in the field of nutritional science using a standardized nutritional intervention, consisting of a high-energy shake (950 kcal, 8% protein, 35% sugar and 57% fat). Eleven subjects underwent the intervention on three separate days and their exhaled breath was monitored up to six hours postprandially. In addition, sampling was performed during equivalent fasting conditions for selected subjects. To estimate the impact of inter- and intra-individual variability, analysis of variance simultaneous component analysis (ASCA) was conducted, revealing that the inter-individual variability accounted for 30 % of the data variation. To distinguish the effect of the intervention from fasting conditions, partial least squares discriminant analysis was performed. Candidate compound annotation was performed with pathway analysis and collision-induced dissociation (CID) experiments. Pathway analysis highlighted, among others, features associated with the metabolism of linoleate, butanoate and amino sugars. Tentative compounds annotated through CID measurements include fatty acids, amino acids, and amino acid derivatives, some of them likely derived from nutrients by the gut microbiome (e.g. propanoate, indoles), as well as organic acids from the Krebs cycle. Time-series clustering showed an overlap of observed kinetic trends with those reported previously in blood plasma.

Postprandial Responses on Serum Metabolome to Milk and Yogurt Intake in Young and Older Men

The identification and validation of biomarkers of food intake (BFIs) is a promising approach to develop more objective and complementary tools to the traditional dietary assessment methods. Concerning dairy, their evaluation in terms of intake is not simple, given the variety of existing foods, making it difficult to establish the association between specific dairy products consumption and the effects on human health, which is also dependent on the study population. Here, we aimed at identifying BFI of both milk (M) and yogurt (Y) in 14 healthy young (20–35 years) and 14 older (65–80 years). After a 3-week run-in period of dairy exclusion from the diet, the subjects acutely consumed 600 ml of M or Y. Metabolomics analyses were conducted on serum samples during the following 6 h (LC-MS and GC-MS). Several metabolites showing increased iAUC after milk or yogurt intake were considered as potential BFI, including lactose (M &gt; Y, 2-fold), galactitol (M &gt; Y, 1.5-fold), galactonate (M &gt; Y, 1.2-fold), sphingosine-1-phosphate (M &gt; Y from 2.1-fold), as well as an annotated disaccharide (Y &gt; M, 3.6-fold). Delayed serum kinetics were also observed after Y compared to M intake lysine (+22 min), phenylalanine (+45 min), tyrosine (+30min), threonine (+38 min) 3-phenyllactic acid (+30 min), lactose (+30 min), galactitol (+45min) and galactonate (+30 min). The statistical significance of certain discriminant metabolites, such as sphingosine-1-phosphate and several free fatty acids, was not maintained in the older group. This could be related to the physiological modifications induced by aging, like dysregulated lipid metabolism, including delayed appearance of dodecanoic acid (+60 min) or altered postprandial appearance of myristic acid (+70% Cmax), 3-dehydroxycarnitine (−26% Cmin), decanoylcarnitine (−51% Cmin) and dodecanoylcarnitine (−40% Cmin). In conclusion, candidate BFI of milk or yogurt could be identified based on the modified postprandial response resulting from the fermentation of milk to yogurt. Moreover, population specificities (e.g., aging) should also be considered in future studies to obtain more accurate and specific BFI.

Cardiometabolic health benefits of dairy-milk polar lipids

Low-quality dietary patterns impair cardiometabolic health by increasing the risk of obesity-related disorders. Cardiometabolic risk relative to dairy-food consumption continues to be a controversial topic, due to recommendations that endorse low-fat and nonfat dairy foods over full-fat varieties despite accumulated evidence that does not strongly support these recommendations. Controlled human studies and mechanistic preclinical investigations support that full-fat dairy foods decrease cardiometabolic risk by promoting gut health, reducing inflammation, and managing dyslipidemia. These gut- and systemic-level cardiometabolic benefits are attributed, at least in part, to milk polar lipids (MPLs) derived from the phospholipid- and sphingolipid-rich milk fat globule membrane that is of higher abundance in full-fat dairy milk. The controversy surrounding full-fat dairy food consumption is discussed in this review relative to cardiometabolic health and MPL bioactivities that alleviate dyslipidemia, shift gut microbiota composition, and reduce inflammation. This summary, therefore, is expected to advance the understanding of full-fat dairy foods through their MPLs and the need for translational research to establish evidence-based dietary recommendations.

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

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

Identification of Potential Urinary Biomarkers for Bell Pepper Intake by HPLC-HRMS-Based Metabolomics and Structure Elucidation by NMR

Dietary biomarkers show great promise for objectively assessing the food intake in humans. In this study, potential urinary biomarkers for red bell pepper intake were identified based on a dietary intervention study and a comprehensive metabolomics approach. Spot urine samples from 14 volunteers were collected in the two phases of the study (control phase: abstaining from any bell pepper/paprika products; case phase: consumption of a defined amount of fresh red bell pepper and abstaining from any further bell pepper/paprika products) and analyzed by high-performance liquid chromatography high-resolution mass spectrometry (HPLC-HRMS). Comparison of the obtained metabolomics data using statistical analysis revealed that the respective urine metabolomes differ significantly, which was attributable to the bell pepper intake. Some of the most discriminating metabolites were selected and isolated from human urine for unequivocal structure elucidation by nuclear magnetic resonance (NMR) spectroscopy. Herein, seven novel glucuronidated metabolites most likely derived from capsanthin and capsianosides were identified, implying their potential application as dietary biomarkers for the entire Capsicum genus.

Muscle and Serum Metabolomics for Different Chicken Breeds under Commercial Conditions by GC-MS

Globally, village chicken is popular and is known as a premium meat with a higher price. Food fraud can occur by selling other chicken breeds at a premium price in local markets. This study aimed to distinguish local village chicken from other chicken breeds available in the market, namely, colored broiler (Hubbard), broiler (Cobb), and spent laying hen (Dekalb) in pectoralis major and serum under commercial conditions using an untargeted metabolomics approach. Both pectoralis major and serum were analyzed using gas chromatography–mass spectrometry (GC–MS). The principal component analysis (PCA) results distinguished four different chicken breeds into three main groups for pectoralis major and serum. A total of 30 and 40 characteristic metabolites were identified for pectoralis major and serum, respectively. The four chicken breeds were characterized by the abundance of metabolites such as amino acids (L−glutamic acid, L−threonine, L−serine, L−leucine), organic acids (L−lactic acid, succinic acid, 3−hydroxybutyric acid), sugars (D−allose, D−glucose), sugar alcohols (myo−inositol), and fatty acids (linoleic acid). Our results suggest that an untargeted metabolomics approach using GC–MS and PCA could discriminate chicken breeds for pectoralis major and serum under commercial conditions. In this study, village chicken could only be distinguished from colored broiler (Hubbard) by serum samples.

Evaluating the Robustness of Biomarkers of Dairy Food Intake in a Free-Living Population Using Single- and Multi-Marker Approaches

Studies examining associations between self-reported dairy intake and health are inconclusive, but biomarkers hold promise for elucidating such relationships by offering objective measures of dietary intake. Previous human intervention studies identified several biomarkers for dairy foods in blood and urine using non-targeted metabolomics. We evaluated the robustness of these biomarkers in a free-living cohort in the Netherlands using both single- and multi-marker approaches. Plasma and urine from 246 participants (54 ± 13 years) who completed a food frequency questionnaire were analyzed using liquid and gas chromatography-mass spectrometry. The targeted metabolite panel included 37 previously-identified candidate biomarkers of milk, cheese, and/or yoghurt consumption. Associations between biomarkers and energy-adjusted dairy food intakes were assessed by a ‘single-marker’ generalized linear model, and stepwise regression was used to select the best ‘multi-marker’ panel. Multi-marker models that also accounted for common covariates better captured the subtle differences for milk (urinary galactose, galactitol; sex, body mass index, age) and cheese (plasma pentadecanoic acid, isoleucine, glutamic acid) over single-marker models. No significant associations were observed for yogurt. Further examination of other facets of validity of these biomarkers may improve estimates of dairy food intake in conjunction with self-reported methods, and help reach a clearer consensus on their health impacts.

Microbiota and Metabolite Modifications after Dietary Exclusion of Dairy Products and Reduced Consumption of Fermented Food in Young and Older Men

The gut microbiota adapts to age-related changes in host physiology but is also affected by environmental stimuli, like diet. As a source of both pre- and probiotics, dairy and fermented foods modulate the gut microbiota composition, which makes them interesting food groups to use for the investigation of interactions between diet and ageing. Here we present the effects of excluding dairy products and limiting fermented food consumption for 19 days on gut microbiota composition and circulating metabolites of 28 healthy, young (YA) and older (OA) adult men. The intervention affected gut microbial composition in both groups, with significant increases in Akkermansia muciniphila and decreases in bacteria of the Clostridiales order. Lower fasting levels of glucose and insulin, as well as dairy-associated metabolites like lactose and pentadecanoic acid, were observed after the intervention, with no effect of age. The intervention also decreased HDL and LDL cholesterol levels. Dairy fat intake was positively associated with the HDL cholesterol changes but not with the LDL/HDL ratio. In conclusion, restricting the intake of dairy and fermented foods in men modified their gut microbiota and blood metabolites, while the impact of the dietary restrictions on these outcomes was more marked than the effect of age.

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.

A rapid GC method coupled with quadrupole or time of flight mass spectrometry for metabolomics analysis

Gas chromatography-mass spectrometry (GC-MS) is an ideal tool for analyzing the intermediates of tricarboxylic acid cycle and glycolysis, sugars, organic acids and amino acids, etc. High-throughput metabolomics methods are required by large-scale clinical researches, and time of flight mass spectrometry (TOF MS) having fast scanning rate is preferable for rapid GC. Quadrupole MS (qMS) instruments have 95% market share, and their potential in rapid metabolomics is worth being studied. In this work, a within 15-min GC program was established and matched by qMS scanning for plasma metabolome analysis after N-methyl-N-(trimethylsilyl)-trifluoroacetamide derivatization. Compared to the longer-time program GC-qMS method, the rapid GC-qMS method had nearly no metabolome information loss, and it had excellent profile performance in repeatability, intra-day and inter-day precision, sampling range, linearity and extraction recovery. Compared to TOF MS, qMS achieved similar results in investigating lung cancer serum metabolic disruptions. Partial least squares-discriminant analysis revealed that the two datasets acquired by qMS and TOF MS had very similar model parameters, and most of top ranked differential metabolites were the same. This study provides a rapid and economical GC-qMS metabolomics method for researchers. Still, MS having faster scanning rate and higher sensitivity are recommended, if possible, to detect more small peaks and some co-eluted peaks.

Intake of Fermented Dairy Products Induces a Less Pro-Inflammatory Postprandial Peripheral Blood Mononuclear Cell Gene Expression Response than Non-Fermented Dairy Products: A Randomized Controlled Cross-Over Trial

SCOPE

It is aimed to investigate how intake of high-fat meals composed of different dairy products with a similar fat content affects postprandial peripheral blood mononuclear cell (PBMC) expression of inflammation-related genes, as well as circulating inflammatory markers and metabolites.

METHODS AND RESULTS

Healthy subjects (n = 47) consume four different high-fat meals composed of either butter, cheese, whipped cream, or sour cream in a randomized controlled cross-over study. Fasting and postprandial PBMC gene expression, plasma metabolites, and circulating inflammatory markers are measured. Using a linear mixed model, it is found that expression of genes related to lymphocyte activation, cytokine signaling, chemokine signaling, and cell adhesion is differentially altered between the four meals. In general, intake of the fermented products cheese and sour cream reduces, while intake of the non-fermented products butter and whipped cream increases, expression of these genes. Plasma amino acid concentrations increase after intake of cheese compared to the other meals, and the amino acid changes correlate with several of the differentially altered genes.

CONCLUSION

Intake of fermented dairy products, especially cheese, induces a less inflammatory postprandial PBMC gene expression response than non-fermented dairy products. These findings may partly explain inconsistent findings in studies on health effects of dairy products.

Serum nonesterified fatty acids have utility as dietary biomarkers of fat intake from fish, fish oil, and dairy in women

Nutritional studies rely on various biological specimens for FA determination, yet it is unclear how levels of serum NEFAs correlate with other circulating lipid pools. Here, we used a high-throughput method (<4 min/sample) based on multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry (MSI-NACE-MS) to investigate whether specific serum NEFAs have utility as biomarkers of dietary fat intake in women. We first identified circulating NEFAs correlated with long-term/habitual food intake among pregnant women with contrasting dietary patterns (n = 50). Acute changes in serum NEFA trajectories were also studied in nonpregnant women (n = 18) following high-dose (5 g/day) fish oil (FO) supplementation or isoenergetic sunflower oil placebo over 56 days. In the cross-sectional study, serum ω-3 FAs correlated with self-reported total ω-3 daily intake, notably EPA as its NEFA (r = 0.46; P = 0.001), whereas pentadecanoic acid was associated with full-fat dairy intake (r = 0.43; P = 0.002), outcomes consistent with results from total FA serum hydrolysates. In the intervention cohort, serum ω-3 NEFAs increased 2.5-fold from baseline within 28 days following FO supplementation, and this increase was most pronounced for EPA (P = 0.0004). Unlike for DHA, circulating EPA as its NEFA also strongly correlated to EPA concentrations measured from erythrocyte phospholipid hydrolysates (r = 0.66; P = 4.6 × 10-10) and was better suited to detect dietary nonadherence. We conclude that MSI-NACE-MS offers a rapid method to quantify serum NEFAs and objectively monitor dietary fat intake in women that is complementary to food-frequency questionnaires.

Human urine 1H NMR metabolomics reveals alterations of protein and carbohydrate metabolism when comparing habitual Average Danish diet vs. healthy New Nordic diet

OBJECTIVES

The aim of this study was to investigate the alteration of the human urine metabolome by means of diet and to compare the metabolic effects of the nutritionally healthy New Nordic Diet (NND) with an Average Danish Diet (ADD). The NND was designed a decade ago by scientists and chefs, based on local and sustainable foods, including fish, shellfish, vegetables, roots, fruit, and berries. The NND has been proven to lower blood pressure, reduce glycemia, and lead to weight loss.

METHODS

The human urine metabolome was measured by untargeted proton nuclear magnetic resonance spectroscopy in samples from 142 centrally obese Danes (20-66 years old), randomized to consume the ADD or the NND. The resulting metabolomics data was processed and analyzed using advanced multivariate data analysis methods to reveal effects related to the design factors, including diet, season, sex, and changes in body weight.

RESULTS

Exploration of the nuclear magnetic resonance profiles revealed unique metabolite markers reflecting changes in protein and carbohydrate metabolism between the two diets. Glycine betaine, glucose, trimethylamine N-oxide and creatinine were increased in urine of the individuals following the NND compared with the ADD population, whereas relative concentrations of tartrate, dimethyl sulfone, and propylene glycol were decreased. Propylene glycol had a strong association with the homeostatic model assessment for insulin resistance in the NND group. The food intake biomarkers found in this study confirm the importance of these as tools for nutritional research.

CONCLUSIONS

Findings from this study provided new insights into the effects of a healthy diet on glycemia, reduction of inflammation, and weight loss among obese individuals, and alteration of the gut microbiota metabolism.

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

SCOPE

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

METHODS AND RESULTS

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

CONCLUSIONS

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

Consumption of a diet high in dairy leads to higher 15:0 in cholesteryl esters of healthy people when compared to diets high in meat and grain

BACKGROUND AND AIMS

A higher dairy product intake has been associated to higher blood concentrations of 15:0 (pentadecanoic acid), 17:0 (margaric acid), and 14:0 (myristic acid). This study investigates whether a diet high in dairy products influences cholesteryl ester fatty acid concentrations of these specific fatty acids (FA).

METHODS AND RESULTS

In a randomized multiple cross-over study, 13 men and 17 women aged 22 ± 4 years with a BMI of 21.6 ± 2.2 kg/m² received 3 isocaloric intervention diets (dairy, meat or grain) in random order. For this post-hoc analysis, FA in plasma cholesteryl esters were measured using gas chromatography. We performed a linear mixed model per centered log-ratio transformed FA, adjusting for period, and the interaction between diet and period. Consumed total fat intake per controlled intervention diet was 31.0 ± 0.9 en%/day (dairy), 31.5 ± 0.6 en%/day (meat), and 28.4 ± 1.2 en%/day (grain), respectively. The dairy diet led to higher relative concentrations of 15:0 when compared to diets high in meat and grain, (β; 0.27, 95%CI: 0.18,0.37; p = 1.2 × 10^-5, and β: 0.15; 95%CI: 0.06,0.24; p = 1.2 × 10^-2, respectively). The dairy diet also led to higher 14:0 when compared to the meat diet (β: 0.34; 95%CI: 0.21,0.46; p = 6.0 × 10^-5), but not when compared to the grain diet. 17:0 did not differ between diets.

CONCLUSION

The plasma cholesteryl ester fraction after a diet high in dairy was characterized by higher 15:0 levels. Concentrations of 14:0 were only higher when comparing the FA profile after a diet high in dairy when compared to a diet high in meat.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, NCT01314040.

Identification of Milk and Cheese Intake Biomarkers in Healthy Adults Reveals High Interindividual Variability of Lewis System-Related Oligosaccharides

BACKGROUND

The use of biomarkers of food intake (BFIs) in blood and urine has shown great promise for assessing dietary intake and complementing traditional dietary assessment tools whose use is prone to misreporting.

OBJECTIVE

Untargeted LC-MS metabolomics was applied to identify candidate BFIs for assessing the intake of milk and cheese and to explore the metabolic response to the ingestion of these foods.

METHODS

A randomized controlled crossover study was conducted in healthy adults [5 women, 6 men; age: 23.6 ± 5.0 y; BMI (kg/m2): 22.1 ± 1.7].  After a single isocaloric intake of milk (600 mL), cheese (100 g), or soy-based drink (600 mL), serum and urine samples were collected postprandially up to 6 h and after fasting after 24 h. Untargeted metabolomics was conducted using LC-MS. Discriminant metabolites were selected in serum by multivariate statistical analysis, and their mass distribution and postprandial kinetics were compared.

RESULTS

Serum metabolites discriminant for cheese intake had a significantly lower mass distribution than metabolites characterizing milk intake (P = 4.1 × 10-4). Candidate BFIs for milk or cheese included saccharides, a hydroxy acid, amino acids, amino acid derivatives, and dipeptides. Two serum oligosaccharides, blood group H disaccharide (BGH) and Lewis A trisaccharide (LeA), specifically reflected milk intake but with high interindividual variability. The 2 oligosaccharides showed related but opposing trends: subjects showing an increase in either oligosaccharide did not show any increase in the other oligosaccharide. This result was confirmed in urine.

CONCLUSIONS

New candidate BFIs for milk or cheese could be identified in healthy adults, most of which were related to protein metabolism. The increase in serum of LeA and BGH after cow-milk intake in adults calls for further investigations considering the beneficial health effects on newborns of such oligosaccharides in maternal milk. The trial is registered at clinicaltrials.gov as NCT02705560.

Dairy Intake in 2 American Adult Cohorts Associates with Novel and Known Targeted and Nontargeted Circulating Metabolites

BACKGROUND

The role of dairy in health can be elucidated by investigating circulating metabolites associated with intake.

OBJECTIVES

We sought to identify metabolites associated with quantity and type of dairy intake in the Framingham Heart Study Offspring and Third Generation (Gen3) cohorts.

METHODS

Dairy intake (total dairy, milk, cheese, yogurt, and cream/butter) was analyzed in relation to targeted (Offspring, n = 2205, 55.1 ± 9.8 y, 52% female, 217 signals; Gen3, n = 866, 40.5 ± 8.8 y, 54.9% female, 79 signals) and nontargeted metabolites (Gen3, ∼7031 signals) in a 2-step analysis including orthogonal projections to latent structures with discriminant analysis (OPLS-DA) in discovery subsets to identify metabolites distinguishing between high and low intake; and linear regression in confirmation subsets to assess putative associations, subsequently tested in the total samples. Previously reported associations were also investigated.

RESULTS

OPLS-DA in the Offspring targeted discovery subset resulted in a variable importance in projection (VIP) >1 of 65, 60, 58, 66, and 60 metabolites for total dairy, milk, cream/butter, cheese, and yogurt, respectively, of which 5, 3, 1, 6, and 4 metabolites, respectively, remained after confirmation. In the Gen3 targeted discovery subset, OPLS-DA resulted in a VIP >1 of 17, 15, 13, 7, and 6 metabolites for total dairy, milk, cream/butter, cheese, and yogurt, respectively. In the Gen3 nontargeted discovery subset, OPLS-DA resulted in a VIP >2 of 203, 503, 78, 186, and 206 metabolites, respectively. Combining targeted and nontargeted results in Gen3, significant associations of 7 (6 unannotated), 2, 12 (11 unannotated), 0, and 61 (all unannotated) metabolites, respectively, remained. Candidate identities of unannotated signals included fatty acids and food flavorings. Results supported relations previously reported for C14:0 sphingomyelin, and marginal associations for deoxycholates.

CONCLUSIONS

Dairy in 2 American adult cohorts associated with numerous circulating metabolites. Reports about diet-metabolite relations and confirmation of previous findings might be limited by specificity of dietary intake and breadth of measured metabolites.

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

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

Trimethylamine-N-Oxide Postprandial Response in Plasma and Urine Is Lower After Fermented Compared to Non-Fermented Dairy Consumption in Healthy Adults

Trimethylamine-N-oxide (TMAO) can be produced by the gut microbiota from dietary substrates and is associated with cardiovascular disease. While dairy products contain TMAO precursors, the effect of fermented dairy on TMAO metabolism remains unclear. We used plasma and urine samples collected for two randomised cross-over studies to evaluate the effects of fermented dairy consumption on TMAO metabolism. In Study 1, thirteen healthy young men tested a yogurt and an acidified milk during postprandial tests and a two-week daily intervention. In Study 2, ten healthy adults tested milk and cheese during postprandial tests. TMAO and five related metabolites were measured in plasma and urine by LC-MS/MS and NMR. Faecal microbiota composition was assessed in Study 1 (16S rRNA metagenomics sequencing). Fermented milk products were associated with lower postprandial TMAO responses than non-fermented milks in urine (Study 1, p = 0.01; Study 2, p = 0.02) and in plasma, comparing yogurt and acidified milk (Study 1, p = 0.04). Daily consumption of dairy products did not differentially affect fasting TMAO metabolites. Significant correlations were observed between microbiota taxa and circulating or urinary TMAO concentrations. Fermentation of dairy products appear, at least transiently, to affect associations between dairy products and circulating TMAO levels.

DHA-Induced Perturbation of Human Serum Metabolome. Role of the Food Matrix and Co-Administration of Oat β-glucan and Anthocyanins

Docosahexaenoic acid (DHA) has been reported to have a positive impact on many diet-related disease risks, including metabolic syndrome. Although many DHA-enriched foods have been marketed, the impact of different food matrices on the effect of DHA is unknown. As well, the possibility to enhance DHA effectiveness through the co-administration of other bioactives has seldom been considered. We evaluated DHA effects on the serum metabolome administered to volunteers at risk of metabolic syndrome as an ingredient of three different foods. Foods were enriched with DHA alone or in combination with oat beta-glucan or anthocyanins and were administered to volunteers for 4 weeks. Serum samples collected at the beginning and end of the trial were analysed by NMR-based metabolomics. Multivariate and univariate statistical analyses were used to characterize modifications in the serum metabolome and to evaluate bioactive-bioactive and bioactive-food matrix interactions. DHA administration induces metabolome perturbation that is influenced by the food matrix and the co-presence of other bioactives. In particular, when co-administered with oat beta-glucan, DHA induces a strong rearrangement in the lipoprotein profile of the subjects. The observed modifications are consistent with clinical results and indicate that metabolomics represents a possible strategy to choose the most appropriate food matrices for bioactive enrichment.

Metabolomics reveals plausible interactive effects between dairy product consumption and metabolic syndrome in humans

BACKGROUND & AIMS

Metabolic syndrome (MetS) induces major disturbances in plasma metabolome, reflecting abnormalities of several metabolic pathways. Recent evidences have demonstrated that the consumption of dairy products may protect from MetS, but the mechanisms remains unknown. The present study aimed at identify how the consumption of different types of dairy products could modify the changes in plasma metabolome during MetS.

METHODS

In this observational study, we analyzed how the consumption of dairy products could modify the perturbations in the plasma metabolome induced by MetS in a sample of 298 participants (61 with MetS) from the French MONA LISA survey. Metabolomic profiling was analyzed with UPLC-MS/MS.

RESULTS

Subjects with MetS exhibited major changes in plasma metabolome. Significant differences in plasma levels of branched chain amino acids, gamma-glutamyl amino acids, and metabolites from arginine and proline metabolism were observed between healthy control and Mets subjects. Plasma levels of many lipid species were increased with MetS (mono- and diacylglycerols, eicosanoids, lysophospholipids and lysoplasmalogens), with corresponding decreases in short chain fatty acids and plasmalogens. The consumption of dairy products, notably with a low fat content (milk and fresh dairy products), altered metabolite profiles in plasma from MetS subjects. Specifically, increasing consumption of dairy products promoted accumulation of plasma C15:0 fatty acid and was inversely associated to some circulating lysophospholipids, sphingolipids, gamma-glutamyl amino acids, leukotriene B4 and lysoplasmalogens.

CONCLUSIONS

the consumption of low fat dairy products could mitigate some of the variations induced by MetS.

1H NMR-based fingerprinting of eleven Mexican Capsicum annuum cultivars

Approximately 90% of the chili peppers consumed in the world are harvested in Mexico. The present article describes the untargeted ¹H NMR-based metabolomic profiling of 11 cultivars of Capsicum annuum species which are routinely consumed worldwide. The metabolomic fingerprinting detected via ¹H NMR contained 44 metabolites including sugars, amino acids, organic acids, polyphenolic acids and alcohols which were identified by comparison with the literature data, with Chenomx database and by 2D NMR. Statistical approaches based on principal component analysis (PCA) and linear discriminant analysis (LDA) were used to classify the Capsicum annuum cultivars according to their metabolite profile. LDA revealed metabolomic differences and similarities among Capsicum annuum cultivars, whereas hierarchical cluster analysis (HCA) significantly separated the cultivars according to the phylogenetic trees obtained. Substantial endogenous levels of free amino acids and carbohydrates were detected in all the studied cultivars but interestingly, Capsicum annuum cv. mirasol and C. annuum cv. chilaca contained almost three-fold more endogenous levels of vitamin C than the other cultivars. Considering that this antioxidant was found in crude aqueous extracts, its abundance could be directly proportional to its bioavailability for human nutrition. The results suggest that ¹H NMR is an effective method to determine differences among cultivars of the Capsicum annuum species.

Assessment of lactase activity in humans by measurement of galactitol and galactonate in serum and urine after milk intake

Background

Lactase is an enzyme that hydrolyzes lactose into glucose and galactose in the small intestine, where they are absorbed. Hypolactasia is a common condition, primarily caused by genetic programming, that leads to lactose maldigestion and, in certain cases, lactose intolerance. Galactitol and galactonate are 2 products of hepatic galactose metabolism that are candidate markers for the intake of lactose-containing foods.

Objectives

The primary objective of the study was to explore the changes in serum and urine metabolomes during postprandial dairy product tests through the association between lactase persistence genotype and the postprandial dynamics of lactose-derived metabolites.

Methods

We characterized the 6-h postprandial serum kinetics and urinary excretion of lactose, galactose, galactitol, and galactonate in 14 healthy men who had consumed a single dose of acidified milk (800 g) which contained 38.8 g lactose. Genotyping of LCT-13910 C/T (rs4988235) was performed to assess primary lactase persistence.

Results

There were 2 distinct postprandial responses, classified as high and low metabolite responses, observed for galactose, and its metabolites galactitol and galactonate, in serum and urine. In all but 1 subject, there was a concordance between the high metabolite responses and genetic lactase persistence and between the low metabolite responses and genetic lactase nonpersistence (accuracy 0.92), galactitol and galactonate being more discriminative than galactose.

Conclusions

Postprandial galactitol and galactonate after lactose overload appear to be good proxies for genetically determined lactase activity. The development of a noninvasive lactose digestion test based on the measurement of these metabolites in urine could be clinically useful. This trial was registered at clinicaltrials.gov as NCT02230345.

Automated supervised learning pipeline for non-targeted GC-MS data analysis

Non-targeted analysis is nowadays applied in many different domains of analytical chemistry such as metabolomics, environmental and food analysis. Conventional processing strategies for GC-MS data include baseline correction, feature detection, and retention time alignment before multivariate modeling. These techniques can be prone to errors and therefore time-consuming manual corrections are generally necessary. We introduce here a novel fully automated approach to non-targeted GC-MS data processing. This new approach avoids feature extraction and retention time alignment. Supervised machine learning on decomposed tensors of segmented chromatographic raw data signal is used to rank regions in the chromatograms contributing to differentiation between sample classes. The performance of this novel data analysis approach is demonstrated on three published datasets.

Combining Mass Spectrometry and NMR Improves Metabolite Detection and Annotation

Despite inherent complementarity, nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are routinely separately employed to characterize metabolomics samples. More troubling is the erroneous view that metabolomics is better served by exclusively utilizing MS. Instead, we demonstrate the importance of combining NMR and MS for metabolomics by using small chemical compound treatments of Chlamydomonas reinhardtii as an illustrative example. A total of 102 metabolites were detected (82 by gas chromatography-MS, 20 by NMR, and 22 by both techniques). Out of these, 47 metabolites of interest were identified: 14 metabolites were uniquely identified by NMR, and 16 metabolites were uniquely identified by GC-MS. A total of 17 metabolites were identified by both NMR and GC-MS. In general, metabolites identified by both techniques exhibited similar changes upon compound treatment. In effect, NMR identified key metabolites that were missed by MS and enhanced the overall coverage of the oxidative pentose phosphate pathway, Calvin cycle, tricarboxylic acid cycle, and amino acid biosynthetic pathways that informed on pathway activity in central carbon metabolism, leading to fatty-acid and complex-lipid synthesis. Our study emphasizes a prime advantage of combining multiple analytical techniques: the improved detection and annotation of metabolites.

Biomarker of food intake for assessing the consumption of dairy and egg products

Dairy and egg products constitute an important part of Western diets as they represent an excellent source of high-quality proteins, vitamins, minerals and fats. Dairy and egg products are highly diverse and their associations with a range of nutritional and health outcomes are therefore heterogeneous. Such associations are also often weak or debated due to the difficulty in establishing correct assessments of dietary intake. Therefore, in order to better characterize associations between the consumption of these foods and health outcomes, it is important to identify reliable biomarkers of their intake. Biomarkers of food intake (BFIs) provide an accurate measure of intake, which is independent of the memory and sincerity of the subjects as well as of their knowledge about the consumed foods. We have, therefore, conducted a systematic search of the scientific literature to evaluate the current status of potential BFIs for dairy products and BFIs for egg products commonly consumed in Europe. Strikingly, only a limited number of compounds have been reported as markers for the intake of these products and none of them have been sufficiently validated. A series of challenges hinders the identification and validation of BFI for dairy and egg products, in particular, the heterogeneous composition of these foods and the lack of specificity of the markers identified so far. Further studies are, therefore, necessary to validate these compounds and to discover new candidate BFIs. Untargeted metabolomic strategies may allow the identification of novel biomarkers, which, when taken separately or in combination, could be used to assess the intake of dairy and egg products.