Perspective: Dietary Biomarkers of Intake and Exposure-Exploration with Omics Approaches

The Future of Obesity Management through Precision Nutrition: Putting the Individual at the Center

PURPOSE OF REVIEW: The prevalence of obesity continues to rise steadily. While obesity management typically relies on dietary and lifestyle modifications, individual responses to these interventions vary widely. Clinical guidelines for overweight and obesity stress the importance of personalized approaches to care. This review aims to underscore the role of precision nutrition in delivering tailored interventions for obesity management. RECENT FINDINGS: Recent technological strides have expanded our ability to detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal in analyzing intricate genomic data. Machine learning algorithms can also predict postprandial glucose, triglyceride, and insulin levels, facilitating customized dietary interventions and ultimately leading to successful weight loss. Additionally, given that adherence to dietary recommendations is one of the key predictors of weight loss success, employing more objective methods for dietary assessment and monitoring can enhance sustained long-term compliance. Biomarkers of food intake hold promise for a more objective dietary assessment. Acknowledging the multifaceted nature of obesity, precision nutrition stands poised to transform obesity management by tailoring dietary interventions to individuals' genetic backgrounds, gut microbiota, metabolic profiles, and behavioral patterns. However, there is insufficient evidence demonstrating the superiority of precision nutrition over traditional dietary recommendations. The integration of precision nutrition into routine clinical practice requires further validation through randomized controlled trials and the accumulation of a larger body of evidence to strengthen its foundation.

Metaproteomics and DNA metabarcoding as tools to assess dietary intake in humans

Objective biomarkers of food intake are a sought-after goal in nutrition research. Most biomarker development to date has focused on metabolites detected in blood, urine, skin or hair, but detection of consumed foods in stool has also been shown to be possible via DNA sequencing. An additional food macromolecule in stool that harbors sequence information is protein. However, the use of protein as an intake biomarker has only been explored to a very limited extent. Here, we evaluate and compare measurement of residual food-derived DNA and protein in stool as potential biomarkers of intake. We performed a pilot study of DNA sequencing-based metabarcoding (FoodSeq) and mass spectrometry-based metaproteomics in five individuals' stool sampled in short, longitudinal bursts accompanied by detailed diet records (n=27 total samples). Dietary data provided by stool DNA, stool protein, and written diet record independently identified a strong within-person dietary signature, identified similar food taxa, and had significantly similar global structure in two of the three pairwise comparisons between measurement techniques (DNA-to-protein and DNA-to-diet record). Metaproteomics identified proteins including myosin, ovalbumin, and beta-lactoglobulin that differentiated food tissue types like beef from dairy and chicken from egg, distinctions that were not possible by DNA alone. Overall, our results lay the groundwork for development of targeted metaproteomic assays for dietary assessment and demonstrate that diverse molecular components of food can be leveraged to study food intake using stool samples.

Towards objective measurements of habitual dietary intake patterns: comparing NMR metabolomics and food frequency questionnaire data in a population-based cohort

BACKGROUND

Low-quality, non-diverse diet is a main risk factor for premature death. Accurate measurement of habitual diet is challenging and there is a need for validated objective methods. Blood metabolite patterns reflect direct or enzymatically diet-induced metabolites. Here, we aimed to evaluate associations between blood metabolite patterns and a priori and data-driven food intake patterns.

METHODS

1, 895 participants in the Northern Sweden Health and Disease Study, a population-based prospective cohort study, were included. Fasting plasma samples were analyzed with 1H Nuclear Magnetic Resonance. Food intake data from a 64-item validated food frequency questionnaire were summarized into a priori Healthy Diet Score (HDS), relative Mediterranean Diet Score (rMDS) and a set of plant-based diet indices (PDI) as well as data driven clusters from latent class analyses (LCA). Orthogonal projections to latent structures (OPLS) were used to explore clustering patterns of metabolites and their relation to reported dietary intake patterns.

RESULTS

Age, sex, body mass index, education and year of study participation had significant influence on OPLS metabolite models. OPLS models for healthful PDI and LCA-clusters were not significant, whereas for HDS, rMDS, PDI and unhealthful PDI significant models were obtained (CV-ANOVA p < 0.001). Still, model statistics were weak and the ability of the models to correctly classify participants into highest and lowest quartiles of rMDS, PDI and unhealthful PDI was poor (50%/78%, 42%/75% and 59%/70%, respectively).

CONCLUSION

Associations between blood metabolite patterns and a priori as well as data-driven food intake patterns were poor. NMR metabolomics may not be sufficiently sensitive to small metabolites that distinguish between complex dietary intake patterns, like lipids.

Measuring diet by metabolomics: a 14-d controlled feeding study of weighed food intake

BACKGROUND

Metabolomics has the potential to enhance dietary assessment by revealing objective measures of many aspects of human food intake. Although metabolomics studies indicate that hundreds of metabolites are associated with dietary intake, correlations have been modest (e.g., r < 0.50), and few have been evaluated in controlled feeding studies.

OBJECTIVES

The aim of this study was to evaluate associations between metabolites and weighed food and beverage intake in a controlled feeding study of habitual diet.

METHODS

Healthy postmenopausal females from the Women's Health Initiative (N = 153) were provided with a customized 2-wk controlled diet designed to emulate their usual diet. Metabolites were measured by liquid chromatography tandem mass spectrometry in end-of-study 24-h urine and fasting serum samples (1293 urine metabolites; 1113 serum metabolites). We calculated partial Pearson correlations between these metabolites and intake of 65 food groups, beverages, and supplements during the feeding study. The threshold for significance was Bonferroni-adjusted to account for multiple testing (5.94 × 10-07 for urine metabolites; 6.91 × 10-07 for serum metabolites).

RESULTS

Significant diet-metabolite correlations were identified for 23 distinct foods, beverages, and supplements (171 distinct metabolites). Among foods, strong metabolite correlations (r ≥ 0.60) were evident for citrus (highest r = 0.80), dairy (r = 0.65), and broccoli (r = 0.63). Among beverages and supplements, strong correlations were evident for coffee (r = 0.86), alcohol (r = 0.69), multivitamins (r = 0.69), and vitamin E supplements (r = 0.65). Moderate correlations (r = 0.50-0.60) were also observed for avocado, fish, garlic, grains, onion, poultry, and black tea. Correlations were specific; each metabolite correlated with one food, beverage, or supplement, except for metabolites correlated with juice or multivitamins.

CONCLUSIONS

Metabolite levels had moderate to strong correlations with weighed intake of habitually consumed foods, beverages, and supplements. These findings exceed in magnitude those previously observed in population studies and exemplify the strong potential of metabolomics to contribute to nutrition research. The Women's Health Initiative is registered at clinicaltrials.gov as NCT00000611.

Unfavorable nutrient intakes in children up to school entry age: results from the nationwide German KiESEL study

Background

Nutrition in the first years of life is a cornerstone for child development and long-term health, yet there is a lack of current data on energy and nutrient intake among toddlers and preschoolers in Germany.

Objective

To analyze energy and nutrient intake in toddlers (1- to 2-year-olds) and preschoolers (3- to 5-year-olds) in Germany and compare the results with the Dietary Reference Values (DRVs) by the European Food Safety Authority.

Design

Dietary intake was assessed by weighed food record data (3 + 1 day) of 890 children from the representative cross-sectional Children's Nutrition Survey to Record Food Consumption (KiESEL), carried out in 2014-2017 as a module of the German Health Interview and Examination Survey for Children and Adolescents Wave 2. For the calculation of energy and nutrient intake, the German Nutrient Database BLS 3.02, LEBTAB, and a supplement database were used.

Results

Median intakes of energy and most nutrients met or exceeded the DRVs in both toddlers and preschoolers. However, low intakes relative to DRVs were found for vitamin D (6-9% of DRV, including supplements) and iodine (57-65% of DRV). Age specific downward deviations were observed for iron intake in toddlers (75% of DRV) and for calcium intake in preschoolers (67-77% of DRV). In contrast, intakes were high for saturated fatty acids (SFA) (14-16 E%), mono-/disaccharides (60-87 g/day), and protein [2.1-2.6 g/(kg body weight*day)].

Conclusion

Nutrient imbalances in toddlers and preschoolers in Germany, which are partly age-related, give rise to concern. Research is needed to determine if routine vitamin D supplementation should be extended beyond infancy. Public health efforts to increase the rate of use of iodized salt and to reduce the intake of SFA and mono-/disaccharides in children's diets are to be strengthened.

Salmon Food-Specific Compounds and Their Metabolites Increase in Human Plasma and Are Associated with Cardiometabolic Health Indicators Following a Mediterranean-Style Diet Intervention

BACKGROUND

Nutrimetabolomics allows for the comprehensive analysis of foods and human biospecimens to identify biomarkers of intake and begin to probe their associations with health. Salmon contains hundreds of compounds that may provide cardiometabolic benefits.

OBJECTIVES

We used untargeted metabolomics to identify salmon food-specific compounds (FSCs) and their predicted metabolites that were found in plasma after a salmon-containing Mediterranean-style (MED) diet intervention. Associations between changes in salmon FSCs and changes in cardiometabolic health indicators (CHIs) were also explored.

METHODS

For this secondary analysis of a randomized, crossover, controlled feeding trial, 41 participants consumed MED diets with 2 servings of salmon per week for 2 5-wk periods. CHIs were assessed, and fasting plasma was collected pre- and postintervention. Plasma, salmon, and 99 MED foods were analyzed using liquid chromatography-mass spectrometry-based metabolomics. Compounds were characterized as salmon FSCs if detected in all salmon replicates but none of the other foods. Metabolites of salmon FSCs were predicted using machine learning. For salmon FSCs and metabolites found in plasma, linear mixed-effect models were used to assess change from pre- to postintervention and associations with changes in CHIs.

RESULTS

Relative to the other 99 MED foods, there were 508 salmon FSCs with 237 unique metabolites. A total of 143 salmon FSCs and 106 metabolites were detected in plasma. Forty-eight salmon FSCs and 30 metabolites increased after the intervention (false discovery rate <0.05). Increases in 2 annotated salmon FSCs and 2 metabolites were associated with improvements in CHIs, including total cholesterol, low-density lipoprotein cholesterol, triglycerides, and apolipoprotein B.

CONCLUSIONS

A data-driven nutrimetabolomics strategy identified salmon FSCs and their predicted metabolites that were detectable in plasma and changed after consumption of a salmon-containing MED diet. Findings support this approach for the discovery of compounds in foods that may serve, upon further validation, as biomarkers or act as bioactive components influential to health. The trials supporting this work were registered at NCT02573129 (Mediterranean-style diet intervention) and NCT05500976 (ongoing clinical trial).

Fecal Metagenomics to Identify Biomarkers of Food Intake in Healthy Adults: Findings from Randomized, Controlled, Nutrition Trials

BACKGROUND

Undigested components of the human diet affect the composition and function of the microorganisms present in the gastrointestinal tract. Techniques like metagenomic analyses allow researchers to study functional capacity, thus revealing the potential of using metagenomic data for developing objective biomarkers of food intake.

OBJECTIVES

As a continuation of our previous work using 16S and metabolomic datasets, we aimed to utilize a computationally intensive, multivariate, machine-learning approach to identify fecal KEGG (Kyoto encyclopedia of genes and genomes) Orthology (KO) categories as biomarkers that accurately classify food intake.

METHODS

Data were aggregated from 5 controlled feeding studies that studied the individual impact of almonds, avocados, broccoli, walnuts, barley, and oats on the adult gastrointestinal microbiota. Deoxyribonucleic acid from preintervention and postintervention fecal samples underwent shotgun genomic sequencing. After preprocessing, sequences were aligned and functionally annotated with Double Index AlignMent Of Next-generation sequencing Data v2.0.11.149 and MEtaGenome ANalyzer v6.12.2, respectively. After the count normalization, the log of the fold change ratio for resulting KOs between pre- and postintervention of the treatment group against its corresponding control was utilized to conduct differential abundance analysis. Differentially abundant KOs were used to train machine-learning models examining potential biomarkers in both single-food and multi-food models.

RESULTS

We identified differentially abundant KOs in the almond (n = 54), broccoli (n = 2474), and walnut (n = 732) groups (q < 0.20), which demonstrated classification accuracies of 80%, 87%, and 86% for the almond, broccoli, and walnut groups using a random forest model to classify food intake into each food group's respective treatment and control arms, respectively. The mixed-food random forest achieved 81% accuracy.

CONCLUSIONS

Our findings reveal promise in utilizing fecal metagenomics to objectively complement self-reported measures of food intake. Future research on various foods and dietary patterns will expand these exploratory analyses for eventual use in feeding study compliance and clinical settings.

Dietary biomarkers-an update on their validity and applicability in epidemiological studies

The aim of this literature review was to identify and provide a summary update on the validity and applicability of the most promising dietary biomarkers reflecting the intake of important foods in the Western diet for application in epidemiological studies. Many dietary biomarker candidates, reflecting intake of common foods and their specific constituents, have been discovered from intervention and observational studies in humans, but few have been validated. The literature search was targeted for biomarker candidates previously reported to reflect intakes of specific food groups or components that are of major importance in health and disease. Their validity was evaluated according to 8 predefined validation criteria and adapted to epidemiological studies; we summarized the findings and listed the most promising food intake biomarkers based on the evaluation. Biomarker candidates for alcohol, cereals, coffee, dairy, fats and oils, fruits, legumes, meat, seafood, sugar, tea, and vegetables were identified. Top candidates for all categories are specific to certain foods, have defined parent compounds, and their concentrations are unaffected by nonfood determinants. The correlations of candidate dietary biomarkers with habitual food intake were moderate to strong and their reproducibility over time ranged from low to high. For many biomarker candidates, critical information regarding dose response, correlation with habitual food intake, and reproducibility over time is yet unknown. The nutritional epidemiology field will benefit from the development of novel methods to combine single biomarkers to generate biomarker panels in combination with self-reported data. The most promising dietary biomarker candidates that reflect commonly consumed foods and food components for application in epidemiological studies were identified, and research required for their full validation was summarized.

Utilising the precision nutrition toolkit in the path towards precision medicine

The overall aim of precision nutrition is to replace the 'one size fits all' approach to dietary advice with recommendations that are more specific to the individual in order to improve the prevention or management of chronic disease. Interest in precision nutrition has grown with advancements in technologies such as genomics, proteomics, metabolomics and measurement of the gut microbiome. Precision nutrition initiatives have three major applications in precision medicine. First, they aim to provide more 'precision' dietary assessments through artificial intelligence, wearable devices or by employing omic technologies to characterise diet more precisely. Secondly, precision nutrition allows us to understand the underlying mechanisms of how diet influences disease risk and identify individuals who are more susceptible to disease due to gene-diet or microbiota-diet interactions. Third, precision nutrition can be used for 'personalised nutrition' advice where machine-learning algorithms can integrate data from omic profiles with other personal and clinical measures to improve disease risk. Proteomics and metabolomics especially provide the ability to discover new biomarkers of food or nutrient intake, proteomic or metabolomic signatures of diet and disease, and discover potential mechanisms of diet-disease interactions. Although there are several challenges that must be overcome to improve the reproducibility, cost-effectiveness and efficacy of these approaches, precision nutrition methodologies have great potential for nutrition research and clinical application.

A Scoping Review of Nutritional Biomarkers Associated with Food Security

Food insecurity affects more than 40 million individuals in the United States and is linked to negative health outcomes due, in part, to poor dietary quality. Despite the emergence of metabolomics as a modality to objectively characterize nutritional biomarkers, it is unclear whether food security is associated with any biomarkers of dietary quality. This scoping review aims to summarize studies that examined associations between nutritional biomarkers and food security, as well as studies that investigated metabolomic differences between people with and without food insecurity. PubMed, Embase, Scopus, and AGRICOLA were searched through August 2022 for studies describing food insecurity and metabolic markers in blood, urine, plasma, hair, or nails. The 78 studies included consisted of targeted assays quantifying lipids, dietary nutrients, heavy metals, and environmental xenobiotics as biochemical features associated with food insecurity. Among those biomarkers which were quantified in at least five studies, none showed a consistent association with food insecurity. Although three biomarkers of dietary quality have been assessed between food-insecure versus food-secure populations, no studies have utilized untargeted metabolomics to characterize patterns of small molecules that distinguish between these two populations. Further studies are needed to characterize the dietary quality profiles of individuals with and without food insecurity.

Urine Metabolites and Bioactive Compounds from Functional Food: Applications of Liquid Chromatography Mass Spectrometry

Bioactive compounds in functional foods, medicinal plants and others are considered attractive value-added molecules based on their wide range of bioactivity. It is clear that an important role is occupied by polyphenol, phenolic compounds and others. Urine is an effective biofluid to evaluate and monitor alterations in homeostasis and other processes related to metabolism. The current review provides a detailed description of the formation of urine in human body, various aspects relevant to sampling and analysis of urinary metabolites before presenting recent developments leveraging on metabolite profiling of urine. For the profiling of small molecules in urine, advancement of liquid chromatography mass tandem spectrometry (LC/MS/MS), establishment of standardized chemical fragmentation libraries, computational resources, data-analysis approaches with pattern recognition tools have made it an attractive option. The profiling of urinary metabolites gives an overview of the biomarkers associated with the diet and evaluates its biological effects. Metabolic pathways such as glycolysis, tricarboxylic acid cycle, amino acid metabolism, energy metabolism, purine metabolism and others can be evaluated. Finally, a combination of metabolite profiling with chemical standardization and bioassay in functional food and medicinal plants will likely lead to the identification of new biomarkers and novel biochemical insights.

Identification of Dietary Supplements Associated with Blood Metabolites in the Hispanic Community Health Study/Study of Latinos Cohort Study

BACKGROUND

Metabolomics approaches have been widely used to define the consumption of foods but have less often been used to study exposure to dietary supplements.

OBJECTIVES

This study aimed to identify dietary supplements associated with metabolite levels and to examine whether these metabolites predicted incident diabetes risk.

METHODS

We studied 3972 participants from a prospective cohort study of 18-74-y-old Hispanic/Latino adults. At a baseline examination, we ascertained use of dietary supplements using recall methods and concurrently, a serum metabolomic panel. After adjustment for potential confounders, we identified dietary supplements associated with metabolites. We then examined the association of these metabolites with incident diabetes at the 6-y study examination.

RESULTS

We observed a total of 110 dietary supplement-metabolite associations that met the criteria for statistical significance adjusted for age, sex, field center, Hispanic/Latino background, body mass index, diet, smoking, physical activity, and number of medications (adjusted P < 0.05). This included 13 metabolites uniquely associated with only one dietary supplement ingredient. Vitamin C had the most associated metabolites (n = 15), including positive associations with oxalate, tartronate, threonate, and isocitrate, which were each in turn protective for the risk of incident diabetes. Vitamin C was also associated with higher N-acetylvaline level, which was an unfavorable diabetes risk factor. Other findings related to branched chain amino acid related compounds including α-hydroxyisovalerate and 2-hydroxy-3-methylvalerate, which were inversely associated with thiamine or riboflavin intake and also predicted higher diabetes risk. Vitamin B12 had an inverse association with γ-glutamylvaline, levels of which were positively associated with the risk of diabetes.

CONCLUSIONS

Our data point to potential metabolite changes associated with vitamin C and B vitamins, which may have favorable metabolic effects. Knowledge of blood metabolites that can be modified by dietary supplement intake may aid understanding the health effects of dietary supplements and identify potential biological mediators.

Biomarkers of moderate alcohol intake and alcoholic beverages: a systematic literature review

The predominant source of alcohol in the diet is alcoholic beverages, including beer, wine, spirits and liquors, sweet wine, and ciders. Self-reported alcohol intakes are likely to be influenced by measurement error, thus affecting the accuracy and precision of currently established epidemiological associations between alcohol itself, alcoholic beverage consumption, and health or disease. Therefore, a more objective assessment of alcohol intake would be very valuable, which may be established through biomarkers of food intake (BFIs). Several direct and indirect alcohol intake biomarkers have been proposed in forensic and clinical contexts to assess recent or longer-term intakes. 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. The aim of this systematic review is to list and validate biomarkers of ethanol intake per se excluding markers of abuse, but including biomarkers related to common categories of alcoholic beverages. Validation of the proposed candidate biomarker(s) for alcohol itself and for each alcoholic beverage was done according to the published guideline for biomarker reviews. In conclusion, common biomarkers of alcohol intake, e.g., as ethyl glucuronide, ethyl sulfate, fatty acid ethyl esters, and phosphatidyl ethanol, show considerable inter-individual response, especially at low to moderate intakes, and need further development and improved validation, while BFIs for beer and wine are highly promising and may help in more accurate intake assessments for these specific beverages.

Joint Microbiota Activity and Dietary Assessment through Urinary Biomarkers by LC-MS/MS

Accurate dietary assessment in nutritional research is a huge challenge, but essential. Due to the subjective nature of self-reporting methods, the development of analytical methods for food intake and microbiota biomarkers determination is needed. This work presents an ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) method for the quantification and semi quantification of 20 and 201 food intake biomarkers (BFIs), respectively, as well as 7 microbiota biomarkers applied to 208 urine samples from lactating mothers (M) (N = 59). Dietary intake was assessed through a 24 h dietary recall (R24h). BFI analysis identified three distinct clusters among samples: samples from clusters 1 and 3 presented higher concentrations of most biomarkers than those from cluster 2, with dairy products and milk biomarkers being more concentrated in cluster 1, and seeds, garlic and onion in cluster 3. Significant correlations were observed between three BFIs (fruits, meat, and fish) and R24h data (r > 0.2, p-values < 0.01, Spearman correlation). Microbiota activity biomarkers were simultaneously evaluated and the subgroup patterns detected were compared to clusters from dietary assessment. These results evidence the feasibility, usefulness, and complementary nature of the determination of BFIs, R24h, and microbiota activity biomarkers in observational nutrition cohort studies.

Furan fatty acid metabolite in newborns predicts risk of asthma

BACKGROUND

Intake of fish-oil and fatty fish during pregnancy has been shown to reduce the risk of childhood asthma but biomarkers of such intake are lacking.

OBJECTIVE

To establish biomarkers of prenatal fish-oil exposure from newborn dry blood spot metabolomics profiles and assess their relevance for childhood asthma risk stratification.

METHODS

The Danish COPSAC₂₀₁₀ mother-child cohort was utilized to investigate the effect of a double-blinded randomized controlled trial of fish-oil supplementation during pregnancy on dry blood spot liquid-chromatography mass spectrometry-based metabolomics profiles of 677 newborns. We thereafter investigated the association between fish-oil associated biomarkers in the newborn and development of asthma-related outcomes. Replication was sought in the independent observational COPSAC₂₀₀₀ cohort with 387 newborn metabolomics profiles.

RESULTS

The newborn metabolomics profiles differed between children in the fish-oil vs. placebo group in COPSAC₂₀₁₀ (area under the receiver operator curve = 0.94 ± 0.03, p < .001). The fish-oil metabolomics profile and the top biomarker, 3-carboxy-4-methyl-5-propyl-2-furan propanoic acid (CMPF) were both associated with a decreased risk of asthma by age 6 years (HR = 0.89, p = .002 and HR = 0.67, p = .005, respectively). In COPSAC₂₀₀₀ , newborn CMPF level was also inversely associated with asthma risk by age 6 years (HR = 0.69, p = .01). Troublesome lung symptoms and common infections in the first 3 years were also inversely associated with newborn CMPF levels in both cohorts.

CONCLUSIONS

Newborn children's blood levels of the furan fatty acid metabolite CMPF reflect fish-oil and fatty fish intake during pregnancy and are associated with a lower risk of asthma across two cohorts, which could aid newborn screening for childhood asthma.

Contribution of natural food environments to nutritional intake and biomarker status: insights from the women of indigenous santhal communities of Jharkhand, India

BACKGROUND

Many indigenous communities reside in biodiverse environments replete with natural food sources but show ​poor access and utilization.

METHODS

To understand the links between indigenous food access, dietary intakes, and biomarkers, we conducted a cross-sectional study among women of the Santhal Community (n = 211) from 17 villages in the Godda district of Jharkhand, India. Survey methods included household surveys, dietary intake assessment (24 HDR) and micronutrient and inflammatory biomarkers' estimation.

RESULTS

The diversity in access to foods from different natural sources expressed as Food access diversity index was low. This led to poor consumption and thus a low Minimum Dietary Diversity. The mean nutrient intake was less than the estimated average requirement for all nutrients. Women with higher dietary diversity scores had higher nutrient intakes. Thiamine and calcium intakes were significantly higher in women consuming indigenous foods than non-consumers. One-fourth of the women had elevated levels of inflammatory biomarkers. The prevalence of iron deficiency was approximately 70%. Vitamin A insufficiency (measured as retinol-binding protein) was observed in around 33.6% women, while 28.4% were deficient. Household access to natural food sources was associated with specific biomarkers. The access to kitchen garden (baari) was positively associated with retinol-binding protein levels and negatively with inflammatory biomarkers, while access to ponds was positively associated with ferritin levels.

CONCLUSION

The findings highlight the role of access to diverse natural foods resources, including indigenous foods, for improving nutrition security in indigenous communities. Nutrition and health programs promoting indigenous food sources should include the assessment of biomarkers for effective monitoring and surveillance.

Discovery of Food Intake Biomarkers Using Metabolomics

Due to the high impact of diet exposure on health, it is crucial the generation of robust data of regular dietary intake, hence improving the accuracy of dietary assessment. The metabolites derived from individual food or group of food have great potential to become biomarkers of food intake (BFIs) and provide more objective food consumption measurements.Herein, it is presented an untargeted metabolomic workflow for the discovery BFIs in blood and urine samples, from the study design to the biomarker identification. Samples are analyzed by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). A wide variety of compounds are covered by separate analyses of medium to nonpolar molecules and polar metabolites based on two LC separations as well as both positive and negative electrospray ionization. The main steps of data treatment of the comprehensive data sets and statistical analysis are described, as well as the principal considerations for the BFI identification.

Research gaps and opportunities in precision nutrition: an NIH workshop report

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.

Enhancing untargeted metabolomics using metadata-based source annotation

Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.

Assessing Adherence to Healthy Dietary Habits Through the Urinary Food Metabolome: Results From a European Two-Center Study

Background

Diet is one of the most important modifiable lifestyle factors in human health and in chronic disease prevention. Thus, accurate dietary assessment is essential for reliably evaluating adherence to healthy habits.

Objectives

The aim of this study was to identify urinary metabolites that could serve as robust biomarkers of diet quality, as assessed through the Alternative Healthy Eating Index (AHEI-2010).

Design

We set up two-center samples of 160 healthy volunteers, aged between 25 and 50, living as a couple or family, with repeated urine sampling and dietary assessment at baseline, and 6 and 12 months over a year. Urine samples were subjected to large-scale metabolomics analysis for comprehensive quantitative characterization of the food-related metabolome. Then, lasso regularized regression analysis and limma univariate analysis were applied to identify those metabolites associated with the AHEI-2010, and to investigate the reproducibility of these associations over time.

Results

Several polyphenol microbial metabolites were found to be positively associated with the AHEI-2010 score; urinary enterolactone glucuronide showed a reproducible association at the three study time points [false discovery rate (FDR): 0.016, 0.014, 0.016]. Furthermore, other associations were found between the AHEI-2010 and various metabolites related to the intake of coffee, red meat and fish, whereas other polyphenol phase II metabolites were associated with higher AHEI-2010 scores at one of the three time points investigated (FDR < 0.05 or β ≠ 0).

Conclusion

We have demonstrated that urinary metabolites, and particularly microbiota-derived metabolites, could serve as reliable indicators of adherence to healthy dietary habits.

Clinical Trail Registration

www.ClinicalTrials.gov, Identifier: NCT03169088.

Sources of Variation in Food-Related Metabolites during Pregnancy

The extent to which variation in food-related metabolites are attributable to non-dietary factors remains unclear, which may explain inconsistent food-metabolite associations observed in population studies. This study examined the association between non-dietary factors and the serum concentrations of food-related biomarkers and quantified the amount of variability in metabolite concentrations explained by non-dietary factors. Pregnant women (n = 600) from two Canadian birth cohorts completed a validated semi-quantitative food frequency questionnaire, and serum metabolites were measured by multisegment injection-capillary electrophoresis-mass spectrometry. Hierarchical linear modelling and principal component partial R-square (PC-PR2) were used for data analysis. For proline betaine and DHA (mainly exogenous), citrus foods and fish/fish oil intake, respectively, explained the highest proportion of variability relative to non-dietary factors. The unique contribution of dietary factors was similar (15:0, 17:0, hippuric acid, TMAO) or lower (14:0, tryptophan betaine, 3-methylhistidine, carnitine) compared to non-dietary factors (i.e., ethnicity, maternal age, gestational age, pre-pregnancy BMI, physical activity, and smoking) for metabolites that can either be produced endogenously, biotransformed by gut microbiota, and/or derived from multiple food sources. The results emphasize the importance of adjusting for non-dietary factors in future analyses to improve the accuracy and precision of the measures of food intake and their associations with health and disease.

A New Approach to Understanding Cancer-Related Fatigue: Leveraging the 3P Model to Facilitate Risk Prediction and Clinical Care

Simple Summary

For the growing number of cancer survivors worldwide, fatigue presents a major hurdle to function and quality of life. Treatment options for cancer-related fatigue are still emerging, and our current understanding of its etiology is limited. In this paper, we describe a new application of a comprehensive model for cancer-related fatigue: the predisposing, precipitating, and perpetuating (3P) factors model. We propose that the 3P model may be leveraged—particularly using metabolomics, the microbiome, and inflammation in conjunction with behavioral science—to better understand the pathophysiology of cancer-related fatigue.

Abstract

A major gap impeding development of new treatments for cancer-related fatigue is an inadequate understanding of the complex biological, clinical, demographic, and lifestyle mechanisms underlying fatigue. In this paper, we describe a new application of a comprehensive model for cancer-related fatigue: the predisposing, precipitating, and perpetuating (3P) factors model. This model framework outlined herein, which incorporates the emerging field of metabolomics, may help to frame a more in-depth analysis of the etiology of cancer-related fatigue as well as a broader and more personalized set of approaches to the clinical treatment of fatigue in oncology care. Included within this review paper is an in-depth description of the proposed biological mechanisms of cancer-related fatigue, as well as a presentation of the 3P model’s application to this phenomenon. We conclude that a clinical focus on organization risk stratification and treatment around the 3P model may be warranted, and future research may benefit from expanding the 3P model to understand fatigue not only in oncology, but also across a variety of chronic conditions.

A Molecular Approach to Understanding the Role of Diet in Cancer-Related Fatigue: Challenges and Future Opportunities

Cancer-related fatigue (CRF) is considered one of the most frequent and distressing symptoms for cancer survivors. Despite its high prevalence, factors that predispose, precipitate, and perpetuate CRF are poorly understood. Emerging research focuses on cancer and treatment-related nutritional complications, changes in body composition, and nutritional deficiencies that can compound CRF. Nutritional metabolomics, the novel study of diet-related metabolites in cells, tissues, and biofluids, offers a promising tool to further address these research gaps. In this position paper, we examine CRF risk factors, summarize metabolomics studies of CRF, outline dietary recommendations for the prevention and management of CRF in cancer survivorship, and identify knowledge gaps and challenges in applying nutritional metabolomics to understand dietary contributions to CRF over the cancer survivorship trajectory.

Metabolomics and the Multi-Omics View of Cancer

Cancer is widely regarded to be a genetic disease. Indeed, over the past five decades, the genomic perspective on cancer has come to almost completely dominate the field. However, this genome-only view is incomplete and tends to portray cancer as a disease that is highly heritable, driven by hundreds of complex genetic interactions and, consequently, difficult to prevent or treat. New evidence suggests that cancer is not as heritable or purely genetic as once thought and that it really is a multi-omics disease. As highlighted in this review, the genome, the exposome, and the metabolome all play roles in cancer’s development and manifestation. The data presented here show that >90% of cancers are initiated by environmental exposures (the exposome) which lead to cancer-inducing genetic changes. The resulting genetic changes are, then, propagated through the altered DNA of the proliferating cancer cells (the genome). Finally, the dividing cancer cells are nourished and sustained by genetically reprogrammed, cancer-specific metabolism (the metabolome). As shown in this review, all three “omes” play roles in initiating cancer. Likewise, all three “omes” interact closely, often providing feedback to each other to sustain or enhance tumor development. Thanks to metabolomics, these multi-omics feedback loops are now much more evident and their roles in explaining the hallmarks of cancer are much better understood. Importantly, this more holistic, multi-omics view portrays cancer as a disease that is much more preventable, easier to understand, and potentially, far more treatable.

An evaluation of the serum carbon isotope ratio as a candidate predictive biomarker of the dietary animal protein ratio (animal protein/total protein) in a 15-day controlled feeding study of US adults

BACKGROUND

The serum natural abundance carbon isotope ratio (CIR) was recently identified as a candidate biomarker of animal protein intake in postmenopausal women. Such a biomarker would help clarify the relation between dietary protein source (plant or animal) and chronic disease risk.

OBJECTIVES

We aimed to evaluate the performance of the serum CIR as a biomarker of dietary protein source in a controlled feeding study of men and women of diverse age and BMI.

METHODS

We conducted a 15-d feeding study of 100 adults (age: 18-70 y, 55% women) in Phoenix, AZ. Participants were provided individualized diets that approximated habitual food intakes. Serum was collected at the end of the feeding period for biomarker measurements.

RESULTS

Median [IQR] animal protein intake was 67 g/d [55-88 g/d], which was 64% of total protein. The serum CIR was positively correlated with animal protein and inversely correlated with plant protein intake, leading to a strong correlation (r2 = 0.76) with the dietary animal protein ratio (APR; animal/total protein). Regressing serum CIR on the APR, serum nitrogen isotope ratio (NIR), gender, age, and body weight generated an R2 of 0.78. Following the measurement error model for predictive biomarkers, the resulting regression equation was then inverted to develop a calibrated biomarker equation for APR. Added sugars ratio (added/total sugars intake) and corn intakes also influenced the serum CIR but to a much lesser degree than the APR; variations in these intakes had only small effects on biomarker-estimated APR.

CONCLUSIONS

Based on our findings in this US cohort of mixed sex and age, we propose the serum CIR alongside NIR as a predictive dietary biomarker of the APR. We anticipate using this biomarker to generate calibrated estimates based on self-reported intake and ultimately to obtain more precise disease risk estimates according to dietary protein source.

Dietary Management of Heart Failure: DASH Diet and Precision Nutrition Perspectives

Heart failure (HF) is a major health care burden increasing in prevalence over time. Effective, evidence-based interventions for HF prevention and management are needed to improve patient longevity, symptom control, and quality of life. Dietary Approaches to Stop Hypertension (DASH) diet interventions can have a positive impact for HF patients. However, the absence of a consensus for comprehensive dietary guidelines and for pragmatic evidence limits the ability of health care providers to implement clinical recommendations. The refinement of medical nutrition therapy through precision nutrition approaches has the potential to reduce the burden of HF, improve clinical care, and meet the needs of diverse patients. The aim of this review is to summarize current evidence related to HF dietary recommendations including DASH diet nutritional interventions and to develop initial recommendations for DASH diet implementation in outpatient HF management. Articles involving human studies were obtained using the following search terms: Dietary Approaches to Stop Hypertension (DASH diet), diet pattern, diet, metabolism, and heart failure. Only full-text articles written in English were included in this review. As DASH nutritional interventions have been proposed, limitations of these studies are the small sample size and non-randomization of interventions, leading to less reliable evidence. Randomized controlled interventions are needed to offer definitive evidence related to the use of the DASH diet in HF management.

A Scoping Review of the Application of Metabolomics in Nutrition Research: The Literature Survey 2000-2019

Nutrimetabolomics is an emerging field in nutrition research, and it is expected to play a significant role in deciphering the interaction between diet and health. Through the development of omics technology over the last two decades, the definition of food and nutrition has changed from sources of energy and major/micro-nutrients to an essential exposure factor that determines health risks. Furthermore, this new approach has enabled nutrition research to identify dietary biomarkers and to deepen the understanding of metabolic dynamics and the impacts on health risks. However, so far, candidate markers identified by metabolomics have not been clinically applied and more efforts should be made to validate those. To help nutrition researchers better understand the potential of its application, this scoping review outlined the historical transition, recent focuses, and future prospects of the new realm, based on trends in the number of human research articles from the early stage of 2000 to the present of 2019 by searching the Medical Literature Analysis and Retrieval System Online (MEDLINE). Among them, objective dietary assessment, metabolic profiling, and health risk prediction were positioned as three of the principal applications. The continued growth will enable nutrimetabolomics research to contribute to personalized nutrition in the future.

The Impact of Cultivation Management and Weed Control Systems of Very Early Potato on Weed Infestation, Biodiversity, and Health Safety of Tubers

The aim of the research was to determine the impact of potato cultivation management and weeding systems on weed infestation and to evaluate the possibility of using biomarkers to assess consumer exposure to herbicide residues in potato tubers. The experiment was carried out in 2016–2018 in Central-Eastern Poland. The subject of research was the very early variety Lord. The experiment was established using the randomized block method in a split-plot design. The first order factor was cultivation management: (A) traditional and (B) under polyethylene sheeting (PE-sheeting) put “on flat”. The second-order factors were weed control systems: (a) mechanical (b) to (d)-chemical. The study determined the degree of damage to crops and weeds, fresh and dry weight of weeds, their number and floristic composition, and herbicide residues in tubers and in the soil. The fresh and dry mass of weeds was most effectively limited by mechanical and chemical treatment with the use of a preparation containing linuron. Managing potato cultivation with PE-sheeting and soil herbicides has proven to be safe for very early potato production. Used for pre-emergence care, the preparation containing linuron did not leave even trace amounts of this active substance in the tubers. The determined amount of the active substance fluorochloridon and clomazone was lower than the Maximum Residue Level (MRL) norm in the EU (European Union). As a result, the adopted, innovative management and weeding control systems in the cultivation of early potato varieties can be considered safe for the consumer.

Nutrition and Frailty: Opportunities for Prevention and Treatment

Frailty is a syndrome of growing importance given the global ageing population. While frailty is a multifactorial process, poor nutritional status is considered a key contributor to its pathophysiology. As nutrition is a modifiable risk factor for frailty, strategies to prevent and treat frailty should consider dietary change. Observational evidence linking nutrition with frailty appears most robust for dietary quality: for example, dietary patterns such as the Mediterranean diet appear to be protective. In addition, research on specific foods, such as a higher consumption of fruit and vegetables and lower consumption of ultra-processed foods are consistent, with healthier profiles linked to lower frailty risk. Few dietary intervention studies have been conducted to date, although a growing number of trials that combine supplementation with exercise training suggest a multi-domain approach may be more effective. This review is based on an interdisciplinary workshop, held in November 2020, and synthesises current understanding of dietary influences on frailty, focusing on opportunities for prevention and treatment. Longer term prospective studies and well-designed trials are needed to determine the causal effects of nutrition on frailty risk and progression and how dietary change can be used to prevent and/or treat frailty in the future.

Wearable and Mobile Sensors for Personalized Nutrition

While wearable and mobile chemical sensors have experienced tremendous growth over the past decade, their potential for tracking and guiding nutrition has emerged only over the past three years. Currently, guidelines from doctors and dietitians represent the most common approach for maintaining optimal nutrition status. However, such recommendations rely on population averages and do not take into account individual variability in responding to nutrients. Precision nutrition has recently emerged to address the large heterogeneity in individuals' responses to diet, by tailoring nutrition based on the specific requirements of each person. It aims at preventing and managing diseases by formulating personalized dietary interventions to individuals on the basis of their metabolic profile, background, and environmental exposure. Recent advances in digital nutrition technology, including calories-counting mobile apps and wearable motion tracking devices, lack the ability of monitoring nutrition at the molecular level. The realization of effective precision nutrition requires synergy from different sensor modalities in order to make timely reliable predictions and efficient feedback. This work reviews key opportunities and challenges toward the successful realization of effective wearable and mobile nutrition monitoring platforms. Non-invasive wearable and mobile electrochemical sensors, capable of monitoring temporal chemical variations upon the intake of food and supplements, are excellent candidates to bridge the gap between digital and biochemical analyses for a successful personalized nutrition approach. By providing timely (previously unavailable) dietary information, such wearable and mobile sensors offer the guidance necessary for supporting dietary behavior change toward a managed nutritional balance. Coupling of the rapidly emerging wearable chemical sensing devices-generating enormous dynamic analytical data-with efficient data-fusion and data-mining methods that identify patterns and make predictions is expected to revolutionize dietary decision-making toward effective precision nutrition.

Nutritional Quality and Safety of Complementary Foods Developed from Blends of Staple Grains and Honey Bee Larvae (Apis mellifera)

Complementary foods must be adequate to satisfy the nutritional needs of the growing child together with breastfeeding. This study was aimed at evaluating the nutritional composition, microbial safety, and sensory quality of extruded complementary foods developed from blends of staple grains and insect bee larva (Apis mellifera). Teff, maize, soybean, and bee larva samples were milled to flour and blended before extrusion as follows: ComF01 (57% maize, 29% teff, and 14% soybean) and ComF02 (58% maize, 29% teff, and 13% bee larvae) using NutriSurvey software (version, 2007). Nutrient composition, microbial, and sensory analyses of developed flour blends were conducted using standard methods. The proximate composition of moisture, fat, fiber, carbohydrate, and energy was significantly different between the developed and commercial wean-mix foods. ComF02 recorded the highest fat content (14.3 g/100 g), energy (427.18 kcal/100 g), and vitamins A (706 μg/100 g), B3 (8.2 mg/100 g), and B9 (86.7 mg/100 g) while ComF01 had the highest protein content (12.56 g/100 g). Iron (40.94 mg/100 g) and calcium (68.20 mg/100 g) were the minerals with the highest content in ComF02. Both ComF01 and ComF02 met the recommended dietary allowance of nutrients for infants aged 6-12 months. Overall, the present study showed that bee larvae can be used to develop complementary foods that are nutritionally adequate, microbiologically safe, and sensory acceptable meeting the dietary allowance of infants at an acceptable level compared to conventional cereal-based foods.

Identification and Reproducibility of Urinary Metabolomic Biomarkers of Habitual Food Intake in a Cross-Sectional Analysis of the Cancer Prevention Study-3 Diet Assessment Sub-Study

Previous cross-sectional metabolomics studies have identified many potential dietary biomarkers, mostly in blood. Few studies examined urine samples although urine is preferred for dietary biomarker discovery. Furthermore, little is known regarding the reproducibility of urinary metabolomic biomarkers over time. We aimed to identify urinary metabolomic biomarkers of diet and assess their reproducibility over time. We conducted a metabolomics analysis among 648 racially/ethnically diverse men and women in the Diet Assessment Sub-study of the Cancer Prevention Study-3 cohort to examine the correlation between >100 food groups/items [101 by a food frequency questionnaire (FFQ), and 105 by repeated 24 h diet recalls (24HRs)] and 1391 metabolites measured in 24 h urine sample replicates, six months apart. Diet-metabolite associations were examined by Pearson's partial correlation analysis. Biomarkers were evaluated for prediction accuracy assessed using area under the curve (AUC) calculated from the receiver operating characteristic curve and for reproducibility assessed using intraclass correlation coefficients (ICCs). A total of 1708 diet-metabolite associations were identified after Bonferroni correction for multiple comparisons and restricting correlation coefficients to >0.2 or <-0.2 (1570 associations using the FFQ and 933 using 24HRs), 513 unique metabolites correlated with 79 food groups/items. The median ICCs of the 513 putative biomarkers was 0.53 (interquartile range 0.42-0.62). In this study, with comprehensive dietary data and repeated 24 h urinary metabolic profiles, we identified a large number of diet-metabolite correlations and replicated many found in previous studies. Our findings revealed the promise of urine samples for dietary biomarker discovery in a large cohort study and provide important information on biomarker reproducibility, which could facilitate their utilization in future clinical and epidemiological studies.

Lipidomics-Based Comparison of Molecular Compositions of Green, Yellow, and Red Bell Peppers

Identifying and annotating the molecular composition of individual foods will improve scientific understanding of how foods impact human health and how much variation exists in the molecular composition of foods of the same species. The complexity of this task includes distinct varieties and variations in natural occurring pigments of foods. Lipidomics, a sub-field of metabolomics, has emerged as an effective tool to help decipher the molecular composition of foods. For this proof-of-principle research, we determined the lipidomic profiles of green, yellow and red bell peppers (Capsicum annuum) using liquid chromatography mass spectrometry and a novel tool for automated annotation of compounds following database searches. Among 23 samples analyzed from 6 peppers (2 green, 1 yellow, and 3 red), over 8000 lipid compounds were detected with 315 compounds (106 annotated) found in all three colors. Assessments of relationships between these compounds and pepper color, using linear mixed effects regression and false discovery rate (<0.05) statistical adjustment, revealed 11 compounds differing by color. The compound most strongly associated with color was the carotenoid, β-cryptoxanthin (p-value = 7.4 × 10⁻⁵; FDR adjusted p-value = 0.0080). These results support lipidomics as a viable analytical technique to identify molecular compounds that can be used for unique characterization of foods.

Measuring Dietary Botanical Diversity as a Proxy for Phytochemical Exposure

The study of natural plant molecules and their medicinal properties, pharmacognosy, provides a taxonomy for botanical families that represent diverse chemical groupings with potentially distinct functions in relation to human health. Yet, this reservoir of knowledge has not been systematically applied to elucidating the role of patterns of plant food consumption on gut microbial ecology and function. All chemical classes of dietary phytochemicals can affect the composition of the microbes that colonize the gut and their function. In turn, the gut microbiome affects the host via multiple mechanisms including gut barrier function, immune function, satiety and taste regulation and the activity of biological signaling pathways that influence health and disease. Herein, we report the development of a botanical diversity index (BDI) to evaluate plant food consumption as a novel metric for identifying and quantifying phytochemicals to which an individual is exposed. A rationale is advanced for using the BDI to investigate how plant food diversity impacts gut microbial ecology and functionality.

Validation of soy isoflavone intake and its health effects: a review of the development of exposure biomarkers

BACKGROUND/OBJECTIVES

It is difficult to consistently demonstrate the health effects of soy isoflavones owing to the multitude of factors contributing to their bioavailability. To accurately verify these health effects, dietary isoflavone intake should be measured using a biologically active dose rather than an intake dose. This concept has been expanded to the development of new exposure biomarkers in nutrition research. This review aims to provide an overview of the development of exposure biomarkers and suggest a novel research strategy for identifying the health effects of soy isoflavone intake.

MATERIALS/METHODS

We cover recent studies on the health effects of soy isoflavones focusing on isoflavone metabolites as exposure biomarkers.

RESULTS

Compared to non-fermented soy foods, fermented soy foods cause an increased concentration of isoflavones in the biofluid immediately following ingestion. The correlation between exposure biomarkers in blood and urine and the food frequency questionnaire was slightly lower than that of corresponding 24-h dietary recalls. Urinary and blood isoflavone levels did not show a consistent association with chronic disease and cancer risk.

CONCLUSION

It is crucial to understand the variable bioavailabilities of soy isoflavones, which may affect evaluations of soy isoflavone intake in health and disease. Further studies on the development of valid exposure biomarkers are needed to thoroughly investigate the health effects of isoflavone.

The Breath Carbon Isotope Ratio Reflects Short-term Added-Sugar Intake in a Dose-Response, Crossover Feeding Study of 12 Healthy Adults

BACKGROUND

Objective dietary biomarkers are urgently needed for a wider range of foods and nutrients. The breath carbon isotope ratio (CIR; measured as δ13C values) has potential as a noninvasive measure of short-term added sugar (AS) intake but has not been evaluated in a controlled-feeding study.

OBJECTIVE

The aim was to evaluate the effect of short-term AS intake on breath CIR in a dose-response, randomized, crossover feeding study.

METHODS

Six men and 6 women, aged 25 to 60 y, were randomly assigned to a balanced sequence of 5 dietary treatments. Three treatments delivered low (0 g/d), medium (75 g/d), or high (150 g/d) amounts of AS over the course of a single day's breakfast and lunch and 2 switched high and low intake amounts between breakfast and lunch. Experimental meals delivered 60% of daily energy and added-sugar targets. There was a washout period of 1-2 wk between treatments. Breath was collected at 2-h intervals from 08:00 (fasting) to 16:00 h. Breath CIR was measured using cavity ring-down spectroscopy, and the effects of dietary treatments and baseline were evaluated using multivariate linear regression.

RESULTS

Breath CIR showed a significant response to increasing AS intake at all sampling time points (all P < 0.0001), with a dose-response of 0.030 (95% CI: 0.024, 0.037) ‰/g. Fasting breath CIR (baseline) influenced postfeeding breath CIR at all sampling time points (P < 0.0001); however, effect sizes were largest in the morning. For afternoon-collected samples (14:00 and 16:00), the effect of recent AS intake (lunch) was 4-fold greater than the effect of previous added-sugar intake (breakfast).

CONCLUSIONS

These findings support the potential of the breath CIR as a biomarker of short-term AS intake in healthy US adults. More work is needed to evaluate other potential dietary effects and whether multiple breath collections could capture daily AS intake.

Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations-A Perspective

Improvement of diet at the population level is a cornerstone of national and international strategies for reducing chronic disease burden. A critical challenge in generating robust data on habitual dietary intake is accurate exposure assessment. Self-reporting instruments (e.g., food frequency questionnaires, dietary recall) are subject to reporting bias and serving size perceptions, while weighed dietary assessments are unfeasible in large-scale studies. However, secondary metabolites derived from individual foods/food groups and present in urine provide an opportunity to develop potential biomarkers of food intake (BFIs). Habitual dietary intake assessment in population surveys using biomarkers presents several challenges, including the need to develop affordable biofluid collection methods, acceptable to participants that allow collection of informative samples. Monitoring diet comprehensively using biomarkers requires analytical methods to quantify the structurally diverse mixture of target biomarkers, at a range of concentrations within urine. The present article provides a perspective on the challenges associated with the development of urine biomarker technology for monitoring diet exposure in free-living individuals with a view to its future deployment in "real world" situations. An observational study (n = 95), as part of a national survey on eating habits, provided an opportunity to explore biomarker measurement in a free-living population. In a second food intervention study (n = 15), individuals consumed a wide range of foods as a series of menus designed specifically to achieve exposure reflecting a diversity of foods commonly consumed in the UK, emulating normal eating patterns. First Morning Void urines were shown to be suitable samples for biomarker measurement. Triple quadrupole mass spectrometry, coupled with liquid chromatography, was used to assess simultaneously the behavior of a panel of 54 potential BFIs. This panel of chemically diverse biomarkers, reporting intake of a wide range of commonly-consumed foods, can be extended successfully as new biomarker leads are discovered. Towards validation, we demonstrate excellent discrimination of eating patterns and quantitative relationships between biomarker concentrations in urine and the intake of several foods. In conclusion, we believe that the integration of information from BFI technology and dietary self-reporting tools will expedite research on the complex interactions between dietary choices and health.

Maternal Diet and the Serum Metabolome in Pregnancy: Robust Dietary Biomarkers Generalizable to a Multiethnic Birth Cohort

BACKGROUND

Advances in metabolomics are anticipated to decipher associations between dietary exposures and health. Replication biomarker studies in different populations are critical to demonstrate generalizability.

OBJECTIVES

To identify and validate robust serum metabolites associated with diet quality and specific foods in a multiethnic cohort of pregnant women.

DESIGN

In this cross-sectional analysis of 3 multiethnic Canadian birth cohorts, we collected semiquantitative FFQ and serum data from 900 women at the second trimester of pregnancy. We calculated a diet quality score (DQS), defined as daily servings of "healthy" minus "unhealthy" foods. Serum metabolomics was performed by multisegment injection-capillary electrophoresis-mass spectrometry, and specific serum metabolites associated with maternal DQSs were identified. We combined the results across all 3 cohorts using meta-analysis to classify robust dietary biomarkers (r > ± 0.1; P < 0.05).

RESULTS

Diet quality was higher in the South Asian birth cohort (mean DQS = 7.1) than the 2 white Caucasian birth cohorts (mean DQS <3.2). Sixty-six metabolites were detected with high frequency (>75%) and adequate precision (CV <30%), and 47 were common to all cohorts. Hippuric acid was positively associated with healthy diet score in all cohorts, and with the overall DQS only in the primarily white Caucasian cohorts. We observed robust correlations between: 1) proline betaine-citrus foods; 2) 3-methylhistidine-red meat, chicken, and eggs; 3) hippuric acid-fruits and vegetables; 4) trimethylamine N-oxide (TMAO)-seafood, meat, and eggs; and 5) tryptophan betaine-nuts/legumes.

CONCLUSIONS

Specific serum metabolites reflect intake of citrus fruit/juice, vegetables, animal foods, and nuts/legumes in pregnant women independent of ethnicity, fasting status, and delays to storage across multiple collection centers. Robust biomarkers of overall diet quality varied by cohort. Proline betaine, 3-methylhistidine, hippuric acid, TMAO, and tryptophan betaine were robust dietary biomarkers for investigations of maternal nutrition in diverse populations.

Recommendations for standardizing nomenclature for dietary (poly)phenol catabolites

There is a lack of focus on the protective health effects of phytochemicals in dietary guidelines. Although a number of chemical libraries and databases contain dietary phytochemicals belonging to the plant metabolome, they are not entirely relevant to human health because many constituents are extensively metabolized within the body following ingestion. This is especially apparent for the highly abundant dietary (poly)phenols, for which the situation is compounded by confusion regarding their bioavailability and metabolism, partially because of the variety of nomenclatures and trivial names used to describe compounds arising from microbial catabolism in the gastrointestinal tract. This confusion, which is perpetuated in online chemical/metabolite databases, will hinder future discovery of bioactivities and affect the establishment of future dietary guidelines if steps are not taken to overcome these issues. In order to resolve this situation, a nomenclature system for phenolic catabolites and their human phase II metabolites is proposed in this article and the basis of its format outlined. Previous names used in the literature are cited along with the recommended nomenclature, International Union of Pure and Applied Chemistry terminology, and, where appropriate, Chemical Abstracts Service numbers, InChIKey, and accurate mass.

Ultra-Performance Liquid Chromatography-Ion Mobility Separation-Quadruple Time-of-Flight MS (UHPLC-IMS-QTOF MS) Metabolomics for Short-Term Biomarker Discovery of Orange Intake: A Randomized, Controlled Crossover Study

A major problem with dietary assessments is their subjective nature. Untargeted metabolomics and new technologies can shed light on this issue and provide a more complete picture of dietary intake by measuring the profile of metabolites in biological samples. Oranges are one of the most consumed fruits in the world, and therefore one of the most studied for their properties. The aim of this work was the application of untargeted metabolomics approach with the novel combination of ion mobility separation coupled to high resolution mass spectrometry (IMS-HRMS) and study the advantages that this technique can bring to the area of dietary biomarker discovery, with the specific case of biomarkers associated with orange consumption (Citrus reticulata) in plasma samples taken during an acute intervention study (consisting of a randomized, controlled crossover trial in healthy individuals). A total of six markers of acute orange consumption, including betonicines and conjugated flavonoids, were identified with the experimental data and previous literature, demonstrating the advantages of ion mobility in the identification of dietary biomarkers and the benefits that an additional structural descriptor, as the collision cross section value (CCS), can provide in this area.

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.

An Integrative Approach to Assessing Diet-Cancer Relationships

The relationship between diet and cancer is often viewed with skepticism by the public and health professionals, despite a considerable body of evidence and general consistency in recommendations over the past decades. A systems biology approach which integrates 'omics' data including metabolomics, genetics, metagenomics, transcriptomics and proteomics holds promise for developing a better understanding of how diet affects cancer and for improving the assessment of diet through biomarker discovery thereby renewing confidence in diet-cancer links. This review discusses the application of multi-omics approaches to studies of diet and cancer. Considerations and challenges that need to be addressed to facilitate the investigation of diet-cancer relationships with multi-omic approaches are also discussed.