Towards nutrition with precision: unlocking biomarkers as dietary assessment tools.

Precision nutrition requires precise tools to monitor dietary habits. Yet current dietary assessment instruments are subjective, limiting our understanding of the causal relationships between diet and health. Biomarkers of food intake (BFIs) hold promise to increase the objectivity and accuracy of dietary assessment, enabling adjustment for compliance and misreporting. Here, we update current concepts and provide a comprehensive overview of BFIs measured in urine and blood. We rank BFIs based on a four-level utility scale to guide selection and identify combinations of BFIs that specifically reflect complex food intakes, making them applicable as dietary instruments. We discuss the main challenges in biomarker development and illustrate key solutions for the application of BFIs in human studies, highlighting different strategies for selecting and combining BFIs to support specific study designs. Finally, we present a roadmap for BFI development and implementation to leverage current knowledge and enable precision in nutrition research.

A Comprehensive Database for DNA Adductomics.

The exposure of human DNA to genotoxic compounds induces the formation of covalent DNA adducts, which may contribute to the initiation of carcinogenesis. Liquid chromatography (LC) coupled with high-resolution mass spectrometry (HRMS) is a powerful tool for DNA adductomics, a new research field aiming at screening known and unknown DNA adducts in biological samples. The lack of databases and bioinformatics tool in this field limits the applicability of DNA adductomics. Establishing a comprehensive database will make the identification process faster and more efficient and will provide new insight into the occurrence of DNA modification from a wide range of genotoxicants. In this paper, we present a four-step approach used to compile and curate a database for the annotation of DNA adducts in biological samples. The first step included a literature search, selecting only DNA adducts that were unequivocally identified by either comparison with reference standards or with nuclear magnetic resonance (NMR), and tentatively identified by tandem HRMS/MS. The second step consisted in harmonizing structures, molecular formulas, and names, for building a systematic database of 279 DNA adducts. The source, the study design and the technique used for DNA adduct identification were reported. The third step consisted in implementing the database with 303 new potential DNA adducts coming from different combinations of genotoxicants with nucleobases, and reporting monoisotopic masses, chemical formulas, .cdxml files, .mol files, SMILES, InChI, InChIKey and IUPAC nomenclature. In the fourth step, a preliminary spectral library was built by acquiring experimental MS/MS spectra of 15 reference standards, generating in silico MS/MS fragments for all the adducts, and reporting both experimental and predicted fragments into interactive web datatables. The database, including 582 entries, is publicly available (https://gitlab.com/nexs-metabolomics/projects/dna_adductomics_database). This database is a powerful tool for the annotation of DNA adducts measured in (HR)MS. The inclusion of metadata indicating the source of DNA adducts, the study design and technique used, allows for prioritization of the DNA adducts of interests and/or to enhance the annotation confidence. DNA adducts identification can be further improved by integrating the present database with the generation of authentic MS/MS spectra, and with user-friendly bioinformatics tools.

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

BACKGROUND: Biomarkers of meat intake hold promise in clarifying the health effects of meat consumption, yet the differentiation between red and white meat remains a challenge. We measure meat intake objectively in a free-living population by applying a newly developed, three-step strategy for biomarker-based assessment of dietary intakes aimed to indicate if (1) any meat was consumed, (2) what type it was and (3) the quantity consumed. METHODS: Twenty-four hour urine samples collected in a four-way crossover RCT and in a cross-sectional analysis of a longitudinal lifestyle intervention (the PREVIEW Study) were analyzed by untargeted LC-MS metabolomics. In the RCT, healthy volunteers consumed three test meals (beef, pork and chicken) and a control; in PREVIEW, overweight participants followed a diet with high or moderate protein levels. PLS-DA modeling of all possible combinations between six previously reported, partially validated, meat biomarkers was used to classify meat intake using samples from the RCT to predict consumption in PREVIEW. RESULTS: Anserine best separated omnivores from vegetarians (AUROC 0.94-0.97), while the anserine to carnosine ratio best distinguished the consumption of red from white meat (AUROC 0.94). Carnosine showed a trend for dose-response between non-consumers, low consumers and high consumers for all meat categories, while in combination with other biomarkers the difference was significant. CONCLUSION: It is possible to evaluate red meat intake by using combinations of existing biomarkers of white and general meat intake. Our results are novel and can be applied to assess qualitatively recent meat intake in nutritional studies. Further work to improve quantitation by biomarkers is needed.

An Untargeted Urine Metabolomics Approach for Autologous Blood Transfusion Detection.

PURPOSE: Autologous blood transfusion is performance enhancing and prohibited in sport but remains difficult to detect. This study explored the hypothesis that an untargeted urine metabolomics analysis can reveal one or more novel metabolites with high sensitivity and specificity for detection of autologous blood transfusion. METHODS: In a randomized, double-blinded, placebo-controlled, crossover design, exercise-trained men (n = 12) donated 900 mL blood or were sham phlebotomized. After 4 wk, red blood cells or saline were reinfused. Urine samples were collected before phlebotomy and 2 h and 1, 2, 3, 5, and 10 d after reinfusion and analyzed by ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. Models of unique metabolites reflecting autologous blood transfusion were attained by partial least-squares discriminant analysis. RESULTS: The strongest model was obtained 2 h after reinfusion with a misclassification error of 6.3% and 98.8% specificity. However, combining only a few of the strongest metabolites selected by this model provided a sensitivity of 100% at days 1 and 2 and 66% at day 3 with 100% specificity. Metabolite identification revealed the presence of secondary di-2-ethylhexyl phtalate metabolites and putatively identified the presence of (iso)caproic acid glucuronide as the strongest candidate biomarker. CONCLUSIONS: Untargeted urine metabolomics revealed several plasticizers as the strongest metabolic pattern for detection of autologous blood transfusion for up to 3 d. Importantly, no other metabolites in urine seem of value for antidoping purposes.

Urine Metabolome Profiling Reveals Imprints of Food Heating Processes after Dietary Intervention with Differently Cooked Potatoes.

Heat treatment is a widely used method for food processing, and the compounds formed by heat processes may serve as biomarkers of heated food intake in nutrition studies. Therefore, we aimed to characterize the differential metabolic signatures resulting from intake of different potato products and identify potential intake biomarkers. In a randomized, controlled, crossover meal study, healthy volunteers consumed boiled rice, boiled potatoes, and two deep-fried potato products, potato chips and French fries. The urine metabolome was acquired by LC-MS-based untargeted metabolomics. Twenty-two selected metabolites were found for deep-fried potatoes, two for potato intake in general, and one for boiled rice. Fourteen of the 22 selected metabolites were tentatively identified as furan-, pyrrole- and pyrazine-derived compounds indicative of Maillard reactions. With further validation, these candidate biomarkers will be important tools to investigate the influence of heated foods on human health.

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

SCOPE: Biomarkers of red meat may clarify the relationship between meat intake and health. This paper explores the discovery of biomarkers of intake for three types of meat with varying heme iron content. Candidate biomarkers for red and general meat are further evaluated based on defined validation criteria. METHODS AND RESULTS: In a randomized cross-over meal study, healthy volunteers consume a randomized sequence of four test meals: chicken, pork, beef, and a control made of egg white and pea. Fasting and postprandial urine samples are collected to cover 48 h and profiled by untargeted LC-ESI-qTOF-MS metabolomics. The profiles following the meal challenges are explored by univariate and multivariate analyses. Nine red, four white, and eight general meat biomarkers are selected as putative biomarkers, originating from collagen degradation, flavour compounds, and amino acid metabolism. Heme-related metabolites are masked by the chlorophyll content of the control meal. The candidate biomarkers are confirmed in an independent meal study and validated for plausibility, robustness, time-response, and prediction performance. Combinations of biomarkers are more efficient than single markers in predicting meat intake. CONCLUSION: New combinations of partially validated biomarkers are proposed to assess terrestrial meat intake and thus help disentangle the effects of meat consumption on human health.

Biomarkers of meat and seafood intake: an extensive literature review.

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

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

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

Sea buckthorn decreases and delays insulin response and improves glycaemic profile following a sucrose-containing berry meal: a randomised, controlled, crossover study of Danish sea buckthorn and strawberries in overweight and obese male subjects.

PURPOSE: Berries and mixed berry products exert acute effects on postprandial glycaemia and insulinemia, but very few berries have been studied, and primarily in normal weight subjects. Sea buckthorn and strawberry are compositionally widely different berries and may likely produce different responses. The effects of strawberry and sea buckthorn on postprandial glycaemia and insulinemia were examined in overweight or obese male subjects. Subjective appetite sensations and ad libitum intake were also examined. METHODS: The study was conducted as a randomised, controlled, single-blinded, three-way crossover study. Eighteen subjects were studied in three 2-h meal tests followed by a subsequent ad libitum meal. Test meals contained added sucrose and either sea buckthorn, strawberry or no berries with added fructose (control). Blood samples were collected at t = 0, 30, 45, 60, 90 and 120 min. Subjective appetite sensations were recorded at t = 0, 15, 30, 45, 60, 90, 120, and 140 min and subsequent ad libitum intake was recorded. Statistical differences in all continuous measures were evaluated based on the existence of a meal or a time-meal interaction by repeated measures linear model analyses or by differences in AUC by linear mixed models. RESULTS: None of the berries affected postprandial glucose. However, sea buckthorn improved glycaemic profile (44.7%, p < 0.01) compared to control. Sea buckthorn also resulted in a decrease in plasma insulin concentration at 30 min (39.6%, p < 0.01) and at 45 min (16.5%, p < 0.05) compared to control and the maximal increase in plasma insulin was lower following sea buckthorn compared with control (23.6%, p < 0.01). Strawberry did not affect postprandial insulin concentrations compared to control. No differences between control and each of the two berries were observed for any of the appetite parameters, except for desire for something sweet, which was increased following the sea buckthorn meal compared to control. CONCLUSIONS: There was no effect on postprandial glucose response to a sugar challenge given together with purees of strawberry or sea buckthorn. Sea buckthorn decreased and delayed the insulin response and improved glycaemic profile compared with control. Strawberry had no such effects. No important differences were seen for the appetite measures. Sea buckthorn might be useful as a culinary tool for lowering meal insulin response.