Food Intake Biomarkers for Increasing the Efficiency of Dietary Pattern Assessment through the Use of Metabolomics: Unforeseen Research Requirements for Addressing Current Gaps

Postprandial Dried Blood Spot-Based Nutritional Metabolomic Analysis Discriminates a High-Fat, High-Protein Meat-Based Diet from a High Carbohydrate Vegan Diet: A Randomized Controlled Crossover Trial

BACKGROUND

Due to the challenges associated with accurate monitoring of dietary intake in humans, nutritional metabolomics (including food intake biomarkers) analysis as a complementary tool to traditional dietary assessment methods has been explored. Food intake biomarker assessment using postprandial dried blood spot (DBS) collection can be a convenient and accurate means of monitoring dietary intake vs 24-hour urine collection.

OBJECTIVE

The objective of this study was to use nutritional metabolomics analysis to differentiate a high-fat, high-protein meat (HFPM) diet from a high-carbohydrate vegan (HCV) diet in postprandial DBS and 24-hour urine.

DESIGN

This was a randomized controlled crossover feeding trial.

PARTICIPANTS/SETTING

Participants were healthy young adult volunteers (n = 8) in California. The study was completed in August 2019.

INTERVENTION

The standardized isocaloric diet interventions included an HFPM and an HCV diet. Participants attended 2 intervention days, separated by a 2-week washout.

MAIN OUTCOME MEASURES

During each intervention day, a finger-prick blood sample was collected in the fasting state, 3 hours post breakfast, and 3 hours post lunch. Participants also collected their urine for 24 hours. DBS and urine samples were analyzed by ultra-performance liquid chromatography mass spectrometry to identify potential food intake biomarkers.

STATISTICAL ANALYSES PERFORMED

Principal component analysis for discriminatory analysis and univariate analysis using paired t tests were performed.

RESULTS

Principal component analysis found no discrimination of baseline DBS samples. In both the postprandial DBS and 24-hour urine, post-HFPM consumption had higher (P < 0.05) levels of acylcarnitines, creatine, and cis-trans hydroxyproline, and the HCV diet was associated with elevated sorbitol (P < 0.05). The HFPM diet had higher concentrations of triacylglycerols with fewer than 54 total carbons in DBS, and 24-hour urine had higher nucleoside mono- and di-phosphates (P < 0.05).

CONCLUSIONS

Nutritional metabolomics profiles of postprandial DBS and 24-hour urine collections were capable of differentiating the HFPM and HCV diets. The potential use of postprandial DBS-based metabolomic analysis deserves further investigation for dietary intake monitoring.

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

SCOPE

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

METHODS AND RESULTS

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

CONCLUSION

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

Food intake biomarkers for berries and grapes

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

Discovery of Intake Biomarkers of Lentils, Chickpeas, and White Beans by Untargeted LC-MS Metabolomics in Serum and Urine

SCOPE

To identify reliable biomarkers of food intake (BFIs) of pulses.

METHODS AND RESULTS

A randomized crossover postprandial intervention study is conducted on 11 volunteers who consumed lentils, chickpeas, and white beans. Urine and serum samples are collected at distinct postprandial time points up to 48 h, and analyzed by LC-HR-MS untargeted metabolomics. Hypaphorine, trigonelline, several small peptides, and polyphenol-derived metabolites prove to be the most discriminating urinary metabolites. Two arginine-related compounds, dopamine sulfate and epicatechin metabolites, with their microbial derivatives, are identified only after intake of lentils, whereas protocatechuic acid is identified only after consumption of chickpeas. Urinary hydroxyjasmonic and hydroxydihydrojasmonic acids, as well as serum pipecolic acid and methylcysteine, are found after white bean consumption. Most of the metabolites identified in the postprandial study are replicated as discriminants in 24 h urine samples, demonstrating that in this case the use of a single, noninvasive sample is suitable for revealing the consumption of pulses.

CONCLUSIONS

The results of the present untargeted metabolomics work reveals a broad list of metabolites that are candidates for use as biomarkers of pulse intake. Further studies are needed to validate these BFIs and to find the best combinations of them to boost their specificity.

Quantifying the human diet in the crosstalk between nutrition and health by multi-targeted metabolomics of food and microbiota-derived metabolites

BACKGROUND

Metabolomics is a powerful tool for investigating the association between nutrition and health status. Although urine is commonly employed for studying the metabolism and transformation of food components, the use of blood samples could be preferable to gain new insights into the bioavailability of diet-derived compounds and their involvement in health. However, the chemical complexity of blood samples hinders the analysis of this biological fluid considerably, which makes the development of novel and comprehensive analytical methods mandatory.

METHODS

In this work, we optimized a multi-targeted metabolomics platform for the quantitative and simultaneous analysis of 450 food-derived metabolites by ultra-high performance liquid chromatography coupled to tandem mass spectrometry. To handle the chemical complexity of blood samples, three complementary extraction methods were assayed and compared in terms of recovery, sensitivity, precision and matrix effects with the aim of maximizing metabolomics coverage: protein precipitation, reversed solid-phase extraction, and hybrid protein precipitation with solid-phase extraction-mediated phospholipid removal.

RESULTS

After careful optimization of the extraction conditions, protein precipitation enabled the most efficient and high-throughput extraction of the food metabolome in plasma, although solid-phase extraction-based protocols provided complementary performance for the analysis of specific polyphenol classes. The developed method yielded accurate recovery rates with negligible matrix effects, and good linearity, as well as high sensitivity and precision for most of the analyzed metabolites.

CONCLUSIONS

The multi-targeted metabolomics platform optimized in this work enables the simultaneous detection and quantitation of 450 dietary metabolites in short-run times using small volumes of biological sample, which facilitates its application to epidemiological studies.

Two apples a day modulate human:microbiome co-metabolic processing of polyphenols, tyrosine and tryptophan

PURPOSE

Validated biomarkers of food intake (BFIs) have recently been suggested as a useful tool to assess adherence to dietary guidelines or compliance in human dietary interventions. Although many new candidate biomarkers have emerged in the last decades for different foods from metabolic profiling studies, the number of comprehensively validated biomarkers of food intake is limited. Apples are among the most frequently consumed fruits and a rich source of polyphenols and fibers, an important mediator for their health-protective properties.

METHODS

Using an untargeted metabolomics approach, we aimed to identify biomarkers of long-term apple intake and explore how apples impact on the human plasma and urine metabolite profiles. Forty mildly hypercholesterolemic volunteers consumed two whole apples or a sugar and energy-matched control beverage, daily for 8 weeks in a randomized, controlled, crossover intervention study. The metabolome in plasma and urine samples was analyzed via untargeted metabolomics.

RESULTS

We found 61 urine and 9 plasma metabolites being statistically significant after the whole apple intake compared to the control beverage, including several polyphenol metabolites that could be used as BFIs. Furthermore, we identified several endogenous indole and phenylacetyl-glutamine microbial metabolites significantly increasing in urine after apple consumption. The multiomic dataset allowed exploration of the correlations between metabolites modulated significantly by the dietary intervention and fecal microbiota species at genus level, showing interesting interactions between Granulicatella genus and phenyl-acetic acid metabolites. Phloretin glucuronide and phloretin glucuronide sulfate appeared promising biomarkers of apple intake; however, robustness, reliability and stability data are needed for full BFI validation.

CONCLUSION

The identified apple BFIs can be used in future studies to assess compliance and to explore their health effects after apple intake. Moreover, the identification of polyphenol microbial metabolites suggests that apple consumption mediates significant gut microbial metabolic activity which should be further explored.

Improving the reporting quality of intervention trials addressing the inter-individual variability in response to the consumption of plant bioactives: quality index and recommendations

PURPOSE

The quality of the study design and data reporting in human trials dealing with the inter-individual variability in response to the consumption of plant bioactives is, in general, low. There is a lack of recommendations supporting the scientific community on this topic. This study aimed at developing a quality index to assist the assessment of the reporting quality of intervention trials addressing the inter-individual variability in response to plant bioactive consumption. Recommendations for better designing and reporting studies were discussed.

METHODS

The selection of the parameters used for the development of the quality index was carried out in agreement with the scientific community through a survey. Parameters were defined, grouped into categories, and scored for different quality levels. The applicability of the scoring system was tested in terms of consistency and effort, and its validity was assessed by comparison with a simultaneous evaluation by experts' criteria.

RESULTS

The "POSITIVe quality index" included 11 reporting criteria grouped into four categories (Statistics, Reporting, Data presentation, and Individual data availability). It was supported by detailed definitions and guidance for their scoring. The quality index score was tested, and the index demonstrated to be valid, reliable, and responsive.

CONCLUSIONS

The evaluation of the reporting quality of studies addressing inter-individual variability in response to plant bioactives highlighted the aspects requiring major improvements. Specific tools and recommendations favoring a complete and transparent reporting on inter-individual variability have been provided to support the scientific community on this field.

Targeting the delivery of dietary plant bioactives to those who would benefit most: from science to practical applications

Background

A healthy diet and optimal lifestyle choices are amongst the most important actions for the prevention of cardiometabolic diseases. Despite this, it appears difficult to convince consumers to select more nutritious foods. Furthermore, the development and production of healthier foods do not always lead to economic profits for the agro-food sector. Most dietary recommendations for the general population represent a “one-size-fits-all approach” which does not necessarily ensure that everyone has adequate exposure to health-promoting constituents of foods. Indeed, we now know that individuals show a high variability in responses when exposed to specific nutrients, foods, or diets.

Purpose

This review aims to highlight our current understanding of inter-individual variability in response to dietary bioactives, based on the integration of findings of the COST Action POSITIVe. We also evaluate opportunities for translation of scientific knowledge on inter-individual variability in response to dietary bioactives, once it becomes available, into practical applications for stakeholders, such as the agro-food industry. The potential impact from such applications will form an important impetus for the food industry to develop and market new high quality and healthy foods for specific groups of consumers in the future. This may contribute to a decrease in the burden of diet-related chronic diseases.

Individual differences in ADME (Absorption, Digestion, Metabolism and Excretion) is believed to underpin much of the inter-individual variation in responses.

Recent developments in the area of food metabolome databases and fast improvements in innovative metabotyping technologies hold great promise for improved profiling of dietary intake, exposure to individual ingredients, foods and dietary patterns, as well as our ability to identify individual responsiveness.

The food industry needs well-defined population clusters or targets in order to be able to design “personalized products”.

There are indeed excellent industrial opportunities for foods that modulate gut microbiota, and thereby enable the delivery of food bioactive metabolites.

It is currently not clear whether knowledge on individual nutrient needs, based on genetic or metagenomic data, would affect long-term dietary and health behaviours.

Data to support the development of dietary recommendations may need to be generated by new n-of-1-based study designs in the future.

Biomarkers of food intake for nuts and vegetable oils: an extensive literature search

Nuts and vegetable oils are important sources of fat and of a wide variety of micronutrients and phytochemicals. Following their intake, several of their constituents, as well as their derived metabolites, are found in blood circulation and in urine. As a consequence, these could be used to assess the compliance to a dietary intervention or to determine habitual intake of nuts and vegetable oils. However, before these metabolites can be widely used as biomarkers of food intake (BFIs), several characteristics have to be considered, including specificity, dose response, time response, stability, and analytical performance. We have, therefore, conducted an extensive literature search to evaluate current knowledge about potential BFIs of nuts and vegetable oils. Once identified, the strengths and weaknesses of the most promising candidate BFIs have been summarized. Results from selected studies have provided a variety of compounds mainly derived from the fatty fraction of these foods, but also other components and derived metabolites related to their nutritional composition. In particular, α-linolenic acid, urolithins, and 5-hydroxyindole-3-acetic acid seem to be the most plausible candidate BFIs for walnuts, whereas for almonds they could be α-tocopherol and some catechin-derived metabolites. Similarly, several studies have reported a strong association between selenium levels and consumption of Brazil nuts. Intake of vegetable oils has been mainly assessed through the measurement of specific fatty acids in different blood fractions, such as oleic acid for olive oil, α-linolenic acid for flaxseed (linseed) and rapeseed (canola) oils, and linoleic acid for sunflower oil. Additionally, hydroxytyrosol and its metabolites were the most promising distinctive BFIs for (extra) virgin olive oil. However, most of these components lack sufficient specificity to serve as BFIs. Therefore, additional studies are necessary to discover new candidate BFIs, as well as to further evaluate the specificity, sensitivity, dose-response relationships, and reproducibility of these candidate biomarkers and to eventually validate them in other populations. For the discovery of new candidate BFIs, an untargeted metabolomics approach may be the most effective strategy, whereas for increasing the specificity of the evaluation of food consumption, this could be a combination of different metabolites.

Breakthroughs in the Health Effects of Plant Food Bioactives: A Perspective on Microbiomics, Nutri(epi)genomics, and Metabolomics

Plant bioactive compounds consumed as part of our diet are able to influence human health. They include secondary metabolites like (poly)phenols, carotenoids, glucosinolates, alkaloids, and terpenes. Although much knowledge has been gained, there is still need for studies unravelling the effects of plant bioactives on cardiometabolic health at the individual level, using cutting-edge high-resolution and data-rich holistic approaches. The aim of this Perspective is to review the prospects of microbiomics, nutrigenomics and nutriepigenomics, and metabolomics to assess the response to plant bioactive consumption while considering interindividual variability. Insights for future research in the field toward personalized nutrition are discussed.