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Combining traditional dietary assessment methods with novel metabolomics techniques: Present efforts by the Food Biomarker Alliance
Abstract
FFQ, food diaries and 24 h recall methods represent the most commonly used dietary assessment tools in human studies on nutrition and health, but food intake biomarkers are assumed to provide a more objective reflection of intake. Unfortunately, very few of these biomarkers are sufficiently validated. This review provides an overview of food intake biomarker research and highlights present research efforts of the Joint Programming Initiative ‘A Healthy Diet for a Healthy Life’ (JPI-HDHL) Food Biomarkers Alliance (FoodBAll). In order to identify novel food intake biomarkers, the focus is on new food metabolomics techniques that allow the quantification of up to thousands of metabolites simultaneously, which may be applied in intervention and observational studies. As biomarkers are often influenced by various other factors than the food under investigation, FoodBAll developed a food intake biomarker quality and validity score aiming to assist the systematic evaluation of novel biomarkers. Moreover, to evaluate the applicability of nutritional biomarkers, studies are presently also focusing on associations between food intake biomarkers and diet-related disease risk. In order to be successful in these metabolomics studies, knowledge about available electronic metabolomics resources is necessary and further developments of these resources are essential. Ultimately, present efforts in this research area aim to advance quality control of traditional dietary assessment methods, advance compliance evaluation in nutritional intervention studies, and increase the significance of observational studies by investigating associations between nutrition and health.
... To measure adherence to both data-driven and pre-defined patterns, reliable dietary data is important. Traditional methods for dietary assessment, such as food diaries, 24-hour recalls, and food frequency questionnaires (FFQs), have been pivotal in our understanding of the relationship between diet and health (50,51). Among these, multiple-day food records, like the one used in the study Malmö Diet and Cancer (MDC), are often regarded as the gold standard in dietary investigations. ...
... Nutritional metabolomics stands at the forefront of contemporary dietary assessment, with the potential to aid in understanding the complex relationship between diet and health. By addressing the limitations of traditional methodologies like food diaries, 24-hour recalls, and food frequency questionnaires (FFQ), metabolomics introduces a new era of accuracy and reliability in nutritional research (51). ...
... Dragsted et al along with the FoodBall consortium have suggested eight groups of validity criteria for biomarkers of food intake (66). These validated biomarkers of food intake have the potential to increase the accuracy of traditional nutritional assessment methods, augmenting their reliability (51,65,(67)(68)(69). Also, as some dietary-related individual metabolites associate with future disease, they could be singled out as candidate substances for future intervention studies (70,71). ...
https://portal.research.lu.se/sv/publications/metabolite-alterations-and-cardiometabolic-disease-a-nutritional-
For copyright reasons, only the thesis summary is posted online.
Abstract:
Background:
Cardiovascular disease (CVD), type 2 diabetes (T2DM), and atrial fibrillation (AF) collectively impact millions globally, necessitating a comprehensive understanding of preceding metabolic alterations for early intervention. This thesis aims to explore metabolic shifts across populations-based cohorts and evaluate the metabolic impact of a dietary intervention.
Method:
Utilizing liquid-chromatography mass spectrometry, we quantified approximately 110 metabolites in over 6000 subjects from the Malmö Preventive Project (MPP), Malmö Diet and Cancer (MDC), Malmö Offspring Study (MOS), and the Cilento dietary intervention study (CDI). Paper I investigates associations between metabolites and future atrial fibrillation in MDC. Paper II examines associations between metabolites and a healthy dietary pattern in MDC, and their associations with future CVD, T2DM, and mortality. Paper III presents a metabolite-based model for healthy dietary intake assessed in MOS, testing its association with future T2DM and CVD in MDC and MPP. Paper IV assesses the metabolic effects of a 6-day Mediterranean diet intervention among Swedish participants in the CDI.
Results:
Paper I identifies 15 metabolites with significant associations with AF, particularly acylcarnitines (1). Paper II associates six metabolites with healthy dietary intake, with ergothioneine especially inversely related to CVD and overall mortality (2). Paper III's metabolic signature for healthy dietary intake associates with lower T2DM and CVD incidence in both MPP and MDC (3). Paper IV reports significant post-intervention metabolite changes, especially in the dietary related metabolome.
Discussion:
This thesis provides a comprehensive analysis of metabolite alterations associated with CVD, T2DM, and AF, elucidating the relationships between metabolic and dietary pattern biomarkers and disease risk. The findings emphasize the utility of plasma metabolites as potential predictors and intermediaries in the pathways leading to these major diseases. Paper 3 and 4 combined acts as a proof of concept that plasma metabolites can be used to identify subgroups with higher risk for CVD and T2DM that might be caused by poor dietary intake Similar methods could be used to develop validated metabolic analyses as biomarkers for healthy dietary intake, with potential application in personalized preventive medicine.
... Self-reported child food intake (CFI) data collected over a defined period, such as 24-hour food recall (24HFR), remain widely used in observational studies (analytical cross-sectional surveys, case-control studies, and cohort studies) and intervention studies (randomized control trials) of malnutrition (under-and overnutrition), to measure infant and young child feeding (IYCF) indicators (Brouwer-Brolsma et al., 2017;FAO, 2018;Ghosh et al., 2019;Shim, Oh, & Kim, 2014; WHO/UNICEF/IFPRI/UCDavis/FANTA/AED/USAID, 2010). The validity and reliability of these IYCF indicators and other such self-reported dietary intake metrics or indices for food intake quality, quantity, nutrient adequacy, and/or dietary diversity, however, still remain inconclusive among nutritional epidemiologists for studies across similar settings in DCs or LMICs (Archer, Lavie, & Hill, 2018;Habte & Krawinkel, 2016;Marshall, Burrows, & Collins, 2014;Miller, Webb, Micha, & Mozaffarian, 2020). ...
... These quantity and quality perspectives of protein intake have also ignited a new wave of research into the roles and underlying mechanisms of essential amino acids in early childhood growth impairment particularly stunting (Ghosh, Suri, & Uauy, 2012;Millward, 2017;Rutherfurd & Moughan, 2012;Suri, Marcus, Ghosh, Kurpad, & Rosenberg, 2013;Uauy, Suri, Ghosh, Kurpad, & Rosenberg, 2016). Several nutritional epidemiologists are also employing new approaches to possibly overcome the limitations posed by measurement errors inarguably attributed to the current conventional methods of food intake measurements (dietary exposure) through the application of advanced food metabolomics (foodomics) and nutrimetabolomics (Boeing, 2013;Brouwer-Brolsma et al., 2017;Guasch-Ferré, Bhupathiraju, & Hu, 2018;Kim, Kim, Yun, & Kim, 2016;Nalbantoglu, 2019;Ulaszewska et al., 2019). ...
... Thus, the combination of inferences drawn from foodomics laboratory data on the changes in constituent food metabolites (nutritive and non-nutritive food metabolome), serving as proxy measures of the potential external dose of exposure or surrogate dietary intake indicators of children (due to TCPM effects), together with population survey data on nutritional status (undernutrition), is viewed as a worthwhile approach to complement, supplement or compensate for some of the limitations of self-reported food intake assessment methods alone (Brouwer-Brolsma et al., 2017;Naska et al., 2017;Rollo et al., 2016). ...
... Therefore, the use of candidate biomarkers of food intake (BFIs), i.e., objective food consumption markers in biological specimens such as urine or blood, is gaining interest, even though there are still very few wellvalidated dietary intake biomarkers [21]. The intake of total fruit and vegetable consumption is frequently estimated using blood vitamin C or carotenoids (i.e., plasma αand β-carotene, β-cryptoxanthin, and lutein) [22,23]. ...
... To facilitate the identification and evaluation of new candidate BFIs, the Food Biomarker Alliance (FoodBAll) [21], a project funded by the Joint Programming Initiative a Healthy Diet for a Healthy Life, established guidelines to conduct a literature search dedicated to food intake biomarkers [25] and to evaluate their level of validation using a set of consensus criteria [26]. The guidelines were applied for all major food groups: fruit and vegetables, meats, fish, and other marine foods, dairy products, cereals and whole grains, alcoholic and non-alcoholic beverages, vegetable oils, nuts, and spices and herbs (http://foodmetabolome.org/wp3) [27][28][29][30][31][32][33][34][35][36]. ...
... These limitations can lead to incorrect or inconsistent data collection, which leads to ambiguity in identifying dietary biomarkers, thus highlighting the necessity to deploy analytical tools that can correctly measure an individual's dietary intake and facilitate corresponding BFI detection. In this regard, a major initiative was launched in 2013: the so-called Food Biomarker Alliance, also known as FoodBAll [38]. ...
... The aim of FoodBAll was to use metabolomics in BFI identification and to create an inventory of metabolite biomarkers in biological fluids produced after intaking a specific food [38]. This inventory helps to elucidate the metabolites produced in the human body as a response to dietary intake as well as overall metabolism. ...
Precision nutrition is an emerging branch of nutrition science that aims to use modern omics technologies (genomics, proteomics, and metabolomics) to assess an individual’s response to specific foods or dietary patterns and thereby determine the most effective diet or life-style interventions to prevent or treat specific diseases. Metabolomics is vital to nearly every aspect of precision nutrition. It can be targeted or untargeted, and it has many applications. Indeed, it can be used to comprehensively characterize the thousands of chemicals in foods, identify food by-products in human biofluids or tissues, characterize nutrient deficiencies or excesses, monitor biochemical responses to dietary interventions, track long- or short-term dietary habits, and guide the development of nutritional therapies. Indeed, metabolomics can be coupled with genomics and proteomics to study and advance the field of precision nutrition. Integrating omics with epidemiolog-ical and clinical data will begin to define the beneficial effects of human food metabolites. In this review, we present the metabolome and its relationship to precision nutrition. Moreover, we describe the different techniques used in metabolomics and present how metabo-lomics has been applied to advance the field of precision nutrition by providing notable examples and cases
... For this study, 11 subjects (three female, eight male) were recruited. Previous nutritional studies with similar group sizes have demonstrated the discovery of thousands of metabolites with statistical significance responding to different interventions [20,21]. The average age of the subjects was 29 ± 3 years and the average body mass index was 24.2 ± 2.8 kg m −2 . ...
... The category of hydrocarbons contains the substances 13-16, representing the trend that the majority of these compounds contain six-membered rings or even aromatic moieties. The classes of gut microbiome-related (5, 7, 17-19), and citric acid cycle molecules (20,21) show the effect of the intervention not only directly after it, but also late responses. reaching the collision cell and consequently leading to chimeric fragment spectra, a recently developed methodology improving real-time MS 2 -experiments called IQAROS was employed [30]. ...
On-line breath analysis using secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS) is a sensitive method for biomarker discovery. The strengths of this technology have already been demonstrated in the clinical environment. For the first time, this study demonstrates the application of SESI-HRMS in the field of nutritional science using a standardized nutritional intervention, consisting of a high-energy shake (950 kcal, 8% protein, 35% sugar and 57% fat). Eleven subjects underwent the intervention on three separate days and their exhaled breath was monitored up to six hours postprandially. In addition, sampling was performed during equivalent fasting conditions for selected subjects. To estimate the impact of inter- and intra-individual variability, analysis of variance simultaneous component analysis (ASCA) was conducted, revealing that the inter-individual variability accounted for 30 % of the data variation. To distinguish the effect of the intervention from fasting conditions, partial least squares discriminant analysis was performed. Candidate compound annotation was performed with pathway analysis and collision-induced dissociation (CID) experiments. Pathway analysis highlighted, among others, features associated with the metabolism of linoleate, butanoate and amino sugars. Tentative compounds annotated through CID measurements include fatty acids, amino acids, and amino acid derivatives, some of them likely derived from nutrients by the gut microbiome (e.g. propanoate, indoles), as well as organic acids from the Krebs cycle. Time-series clustering showed an overlap of observed kinetic trends with those reported previously in blood plasma.
... Keywords: milk, yogurt, biomarkers, metabolomics, human study INTRODUCTION An accurate evaluation of the intake of specific foods and food groups is essential to establish reliable links between nutrition and health in the different human populations (1,2). Unfortunately, in most nutritional studies, data are collected based on self-reporting food frequency questionnaires or 24 hfood intake recalls, which are limited by their subjective nature (1,3). ...
... Keywords: milk, yogurt, biomarkers, metabolomics, human study INTRODUCTION An accurate evaluation of the intake of specific foods and food groups is essential to establish reliable links between nutrition and health in the different human populations (1,2). Unfortunately, in most nutritional studies, data are collected based on self-reporting food frequency questionnaires or 24 hfood intake recalls, which are limited by their subjective nature (1,3). Metabolomics has become an essential analytical strategy for nutrition studies, given its high sensitivity to detect a wide range of low-weight molecules in biological samples with a single measurement. ...
The identification and validation of biomarkers of food intake (BFIs) is a promising approach to develop more objective and complementary tools to the traditional dietary assessment methods. Concerning dairy, their evaluation in terms of intake is not simple, given the variety of existing foods, making it difficult to establish the association between specific dairy products consumption and the effects on human health, which is also dependent on the study population. Here, we aimed at identifying BFI of both milk (M) and yogurt (Y) in 14 healthy young (20–35 years) and 14 older (65–80 years). After a 3-week run-in period of dairy exclusion from the diet, the subjects acutely consumed 600 ml of M or Y. Metabolomics analyses were conducted on serum samples during the following 6 h (LC-MS and GC-MS). Several metabolites showing increased iAUC after milk or yogurt intake were considered as potential BFI, including lactose (M > Y, 2-fold), galactitol (M > Y, 1.5-fold), galactonate (M > Y, 1.2-fold), sphingosine-1-phosphate (M > Y from 2.1-fold), as well as an annotated disaccharide (Y > M, 3.6-fold). Delayed serum kinetics were also observed after Y compared to M intake lysine (+22 min), phenylalanine (+45 min), tyrosine (+30min), threonine (+38 min) 3-phenyllactic acid (+30 min), lactose (+30 min), galactitol (+45min) and galactonate (+30 min). The statistical significance of certain discriminant metabolites, such as sphingosine-1-phosphate and several free fatty acids, was not maintained in the older group. This could be related to the physiological modifications induced by aging, like dysregulated lipid metabolism, including delayed appearance of dodecanoic acid (+60 min) or altered postprandial appearance of myristic acid (+70% Cmax), 3-dehydroxycarnitine (−26% Cmin), decanoylcarnitine (−51% Cmin) and dodecanoylcarnitine (−40% Cmin). In conclusion, candidate BFI of milk or yogurt could be identified based on the modified postprandial response resulting from the fermentation of milk to yogurt. Moreover, population specificities (e.g., aging) should also be considered in future studies to obtain more accurate and specific BFI.
... We therefore analysed the plasma metabolites among 10,684 participants from the Nurses' Health Study (NHS), NHSII, and Health Professionals Follow-up Study (HPFS) and identified multi-metabolite profiles associated with plant-based diets by applying a training and testing approach. The identified metabolite profiles may serve as potential biomarkers of plant-based diets, but also markers of complex metabolic responses to the dietary exposures [12,13]. We then prospectively examined the association of obtained multimetabolite profiles with incident type 2 diabetes risk and explored the potential mediating metabolites. ...
... Second, within the metabolites selected in the metabolite profiles, it is difficult to differentiate the metabolites that directly come from the diet and the metabolites that come from the metabolic response to the dietary intake or other metabolic influences. Future studies, especially human feeding trials, can benefit from measuring both the food metabolome and the human metabolome [12,13]. Third, our findings regarding the intermediate metabolites are hypothesis-generating. ...
Aims/hypothesis
Plant-based diets, especially when rich in healthy plant foods, have been associated with a lower risk of type 2 diabetes. However, whether plasma metabolite profiles related to plant-based diets reflect this association was unknown. The aim of this study was to identify the plasma metabolite profiles related to plant-based diets, and to evaluate the associations between the identified metabolite profiles and the risk of type 2 diabetes.
Methods
Within three prospective cohorts (Nurses’ Health Study, Nurses’ Health Study II and Health Professionals Follow-up Study), we measured plasma metabolites from 10,684 participants using high-throughput LC MS. Adherence to plant-based diets was assessed by three indices derived from the food frequency questionnaire: an overall Plant-based Diet Index (PDI), a Healthy Plant-based Diet Index (hPDI), and an Unhealthy Plant-based Diet Index (uPDI). Multi-metabolite profiles related to plant-based diet were identified using elastic net regression with a training/testing approach. The prospective associations between metabolite profiles and incident type 2 diabetes were evaluated using multivariable Cox proportional hazards regression. Metabolites potentially mediating the association between plant-based diets and type 2 diabetes risk were further identified.
Results
We identified multi-metabolite profiles comprising 55 metabolites for PDI, 93 metabolites for hPDI and 75 metabolites for uPDI. Metabolite profile scores based on the identified metabolite profiles were correlated with the corresponding diet index (Pearson r = 0.33–0.35 for PDI, 0.41–0.45 for hPDI, and 0.37–0.38 for uPDI, all p<0.001). Metabolite profile scores of PDI (HR per 1 SD higher = 0.81 [95% CI 0.75, 0.88]) and hPDI (HR per 1 SD higher = 0.77 [95% CI 0.71, 0.84]) showed an inverse association with incident type 2 diabetes, whereas the metabolite profile score for uPDI was not associated with the risk. Mutual adjustment for metabolites selected in the metabolite profiles, including trigonelline, hippurate, isoleucine and a subset of triacylglycerols, attenuated the associations of diet indices PDI and hPDI with lower type 2 diabetes risk. The explainable proportion of PDI/hPDI-related diabetes risk by these metabolites ranged between 8.5% and 37.2% (all p<0.05).
Conclusions/interpretation
Plasma metabolite profiles related to plant-based diets, especially a healthy plant-based diet, were associated with a lower risk of type 2 diabetes among a generally healthy population. Our findings support the beneficial role of healthy plant-based diets in diabetes prevention and provide new insights for future investigation.
Graphical abstract
... These authors have been and continue to be pioneers in the field of PN, either through their participation in projects or through their contributions to high-impact publications. It is important to highlight the contributions of authors such as Brennan, Lorraine, Alfredo Martinez, J., Mathers, John C., and Ordovas, Jose M., who have participated and continue to participate in PN projects such as Food4Me, The Food Biomarker Alliance (FOODBALL Project), and other dietary interventions focused on PN [37,61,62]. In addition, some authors should be highlighted who, even with fewer publications, have a significant impact on the field of PN. ...
Food systems face the challenge of maintaining adequate nutrition for all populations. Inter-individual responses to the same diet have made precision or personalized nutrition (PN) an emerging and relevant topic. The aim of this study is to analyze the evolution of the PN field, identifying the principal actors and topics, and providing a comprehensive overview. Therefore, a bibliometric analysis of the scientific research available through the Web of Science (WOS) database was performed, revealing 2148 relevant papers up to June 2024. VOSviewer and the WOS platform were employed for the processing and analysis, and included an evaluation of diverse data such as country, author or most frequent keywords, among others. The analysis revealed a period of exponential growth from 2015 to 2023, with the USA, Spain, and England as the top contributors. The field of “Nutrition and Dietetics” is particularly significant, comprising nearly 33% of the total publications. The most highly cited institutions are the universities of Tufts, College Dublin, and Navarra. The relationship between nutrition, genetics, and omics sciences, along with dietary intervention studies, has been a defining factor in the evolution of PN. In conclusion, PN represents a promising field of research with significant potential for further advancement and growth.
... More than 100 different papers on food biomarkers, BFIs, software, databases, and metabolomics were published (and continue to be published) by members of the FoodBAll team. A paper describing FoodBAll's major aims was published in 2017 (Brouwer-Brolsma et al. 2017). Additionally, a website that describes the FoodBAll program, its background, objectives, and outputs (including links to various databases and papers and a social media feed) was established and is still maintained at https://www.foodmetabolome.org. ...
This report describes the knowledge mobilization and translation outcomes of the Canadian-funded portion of a large, international project called the Food Biomarker Alliance (FoodBAll), which ran from 2015 to 2019. This remarkably successful project led to a large number of important findings, outputs, and impacts. In particular, FoodBAll unequivocally demonstrated that metabolomics could be used to not only discover biomarkers of food intake (BFIs), but also to measure diet in a more objective manner. FoodBAll also created standards for assessing and validating BFIs, papers and databases describing BFIs, and kits for measuring BFIs and it laid the groundwork for many global studies exploring food composition and precision nutrition.
... For example, prominent dietary pattern scores are based exclusively on densities for food groups and nutrients. For instance, the Healthy Eating Index 2010 [30] is calculated by combining points related to the intake of total fruit, whole fruit, total vegetables, greens and beans, whole grains, dairy, total protein foods, seafood and plant proteins, polyunsaturated fatty acids, monounsaturated fatty acids, saturated fatty acids, refined grains, sodium, and 'empty calories (solid fats, alcohol, added sugars)', each relative to total calories. ...
Metabolomics profiles from blood, urine, or other body fluids have the potential to assess intakes of foods and nutrients objectively, thereby strengthening nutritional epidemiology research. Metabolomics platforms may include targeted components that estimate the relative concentrations for individual metabolites in a predetermined set, or global components, typically involving mass spectrometry, that estimate relative concentrations more broadly. While a specific metabolite concentration usually correlates with the intake of a single food or food group, multiple metabolites may be correlated with the intake of certain foods or with specific nutrient intakes, each of which may be expressed in absolute terms or relative to total energy intake. Here, I briefly review the progress over the past 20 years on the development and application intake biomarkers for foods/food groups, nutrients, and dietary patterns, primarily by drawing from several recent reviews. In doing so, I emphasize the criteria and study designs for candidate biomarker identification, biomarker validation, and intake biomarker application. The use of intake biomarkers for diet and chronic disease association studies is still infrequent in nutritional epidemiology research. My comments here will derive primarily from our research group’s recent contributions to the Women’s Health Initiative cohorts. I will complete the contribution by describing some opportunities to build on the collective 20 years of effort, including opportunities related to the metabolomics profiling of blood and urine specimens from human feeding studies that approximate habitual diets.
... Additionally, same food components are absorbed and metabolized differently in subjects with different gut microbiota or genetic backgrounds, making it difficult to accurately evaluate the correlations between the self-reported dietary fibre intake and the risk of chronic diseases (11). Under such conditions, dietary biomarkers have emerged as a complementary strategy which could complement traditional dietary assessment and a framework for their anthology and validation have been developed (12). Moreover, metabolite biomarkers may arise for the dietary fibre x microbiota x host interactions which may reflect and/or mediate differential risk of noncommunicable diseases (13,14). ...
Biomarkers associated with dietary fibre intake, as complements to traditional dietary assessment tools, may improve the understanding of its role in human health. Our aim was to discover metabolite biomarkers...
... [11][12][13] Both controlled-feeding studies and large-scale epidemiological studies that leverage metabolomics have discovered novel biomarkers for a wide diversity of foods, food groups, and dietary patterns. 14,15 Carefully controlled intervention studies are particularly useful to assess the pharmacokinetics of biomarker candidates as well as to establish dose response. Observational studies are useful to characterize biomarker variability under free-living conditions, and to estimate long-term biomarker stability. ...
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.
... Metabolomics investigates, among other things, the effect of food-derived biomarkers metabotypes variation among individuals in metabolizing the same diets in health and disease states for customized dietary interventions through metabolic patterns [34]. The identification of metabolites of food intake to serve as target of nutrition intervention makes metabolomics have potential to improve the accuracy of dietary assessment [35]. Metagenomics is vital in precision nutrition because it can be used to comprehensively analyze the diet-microbiome interaction to identify various metabotypes that characterize metabolic risk and tailor dietary intervention approaches for improved health [36]. ...
Purpose of review:
Existing dietary and lifestyle interventions and recommendations, to improve the risk factors of obesity and type 2 diabetes with the target to mitigate this double global epidemic, have produced inconsistent results due to interpersonal variabilities in response to these conventional approaches, and inaccuracies in dietary assessment methods. Precision nutrition, an emerging strategy, tailors an individual's key characteristics such as diet, phenotype, genotype, metabolic biomarkers, and gut microbiome for personalized dietary recommendations to optimize dietary response and health. Precision nutrition is suggested to be an alternative and potentially more effective strategy to improve dietary intake and prevention of obesity and chronic diseases. The purpose of this narrative review is to synthesize the current research and examine the state of the science regarding the effect of precision nutrition in improving the risk factors of obesity and type 2 diabetes.
Recent findings:
The results of the research review indicate to a large extent significant evidence supporting the effectiveness of precision nutrition in improving the risk factors of obesity and type 2 diabetes. Deeper insights and further rigorous research into the diet-phenotype-genotype and interactions of other components of precision nutrition may enable this innovative approach to be adapted in health care and public health to the special needs of individuals. Precision nutrition provides the strategy to make individualized dietary recommendations by integrating genetic, phenotypic, nutritional, lifestyle, medical, social, and other pertinent characteristics about individuals, as a means to address the challenges of generalized dietary recommendations. The evidence presented in this review shows that precision nutrition markedly improves risk factors of obesity and type 2 diabetes, particularly behavior change.
... Traditional dietary assessment methods include food diaries, 24 h dietary recalls, and food frequency questionaries (FFQs) (3). Most of these methods rely on participants' recollection and declaration (selfreport) and, thus, may suffer from underreporting, misreporting, and non-reporting of caloric intake (4). ...
Introduction
Dietary assessment is important for understanding nutritional status. Traditional methods of monitoring food intake through self-report such as diet diaries, 24-hour dietary recall, and food frequency questionnaires may be subject to errors and can be time-consuming for the user.
Methods
This paper presents a semi-automatic dietary assessment tool we developed - a desktop application called Image to Nutrients (I2N) - to process sensor-detected eating events and images captured during these eating events by a wearable sensor. I2N has the capacity to offer multiple food and nutrient databases (e.g., USDA-SR, FNDDS, USDA Global Branded Food Products Database) for annotating eating episodes and food items. I2N estimates energy intake, nutritional content, and the amount consumed. The components of I2N are three-fold: 1) sensor-guided image review, 2) annotation of food images for nutritional analysis, and 3) access to multiple food databases. Two studies were used to evaluate the feasibility and usefulness of I2N: 1) a US-based study with 30 participants and a total of 60 days of data and 2) a Ghana-based study with 41 participants and a total of 41 days of data).
Results
In both studies, a total of 314 eating episodes were annotated using at least three food databases. Using I2N’s sensor-guided image review, the number of images that needed to be reviewed was reduced by 93% and 85% for the two studies, respectively, compared to reviewing all the images.
Discussion
I2N is a unique tool that allows for simultaneous viewing of food images, sensor-guided image review, and access to multiple databases in one tool, making nutritional analysis of food images efficient. The tool is flexible, allowing for nutritional analysis of images if sensor signals aren’t available.
... Due to the different nature of BFIs, high sensitivity and wide coverage analytical methods are needed to assess the metabolic fingerprint of food intake. Liquid (LC) or gas (GC) chromatography coupled with mass spectrometry (MS) and H 1 nuclear magnetic resonance (NMR) spectroscopy are the most commonly used techniques for the analysis of BFIs [19] and targeted assays that enable the quantification of metabolites are the preferred strategy [20]. The vast majority of previously published studies about BFI fingerprinting required complex and time-consuming sample preparation, such as enzymatic hydrolysis [21,22] or solid phase extraction [23,24], resulting in incomplete hydrolysis and low recoveries, respectively. ...
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.
... A connection must be established between these data points in order to ascertain if they correctly describe the events that occur inside the gut microbiota. The fact that the data come from some in vivo testing makes this significant [193][194][195][196]. ...
Dietary and lifestyle planning decisions, dysbiosis in the composition of the microbial community and the production of bioactive metabolites by the gastrointestinal microbiota are all factors that have a significant influence on the mucosal integrity of the intestines and the progression of diseases like colon cancer.
... Metabolomics is a promising approach to objectively assess the impact of diet on chronic disease risk by quantifying small molecules in a biological system [1,15]. The majority of published literature using untargeted metabolomics in nutrition research has been biomarker discovery based on individual foods and dietary patterns [15][16][17][18][19][20]. Fewer studies have compared metabolomic profiles among dietary fats and oils [21], especially compared metabolite profiling between soybean oil and partially-hydrogenated fat [22,23] or determined the association with underlying metabolic pathways. ...
Partially-hydrogenated fat/trans fatty acid intake has been associated with adverse effects on cardiometabolic risk factors. Comparatively unexplored is the effect of unmodified oil relative to partially-hydrogenated fat on the plasma metabolite profile and lipid-related pathways. To address this gap, we conducted secondary analyses using a subset of samples randomly selected from a controlled dietary intervention trial involving moderately hypercholesterolemic individuals. Participants (N = 10, 63 ± 8 y, BMI, 26.2 ± 4.2 kg/m2, LDL-C, 3.9 ± 0.5 mmol/L) were provided with diets enriched in soybean oil (SO) and partially-hydrogenated soybean oil (PHSO). Plasma metabolite concentrations were determined using an untargeted approach and pathway analysis using LIPIDMAPS. Data were assessed using a volcano plot, receiver operating characteristics curve, partial least square-discrimination analysis and Pearson correlations. Among the known metabolites higher in plasma after the PHSO diet than the SO diet, the majority were phospholipids (53%) and di- and triglycerides (DG/TG, 34%). Pathway analysis indicated upregulation of phosphatidylcholine synthesis from DG and phosphatidylethanolamine. We identified seven metabolites (TG_56:9, TG_54:8, TG_54:7, TG_54:6, TG_48:5, DG_36:5 and benproperine) as potential biomarkers for PHSO intake. These data indicate that TG-related metabolites were the most affected lipid species, and glycerophospholipid biosynthesis was the most active pathway in response to PHSO compared to SO intake.
... Such measurement errors can reduce study power and miss detecting potential associations and may also lead to spurious findings. 3,4 Additionally, to capture the increasing diversity and complexity of modern diets, self-report methods require extensive food lists, which is burdensome for both participants and researchers. To address these limitations, food intake biomarkers (FIBs) have emerged as a more objective measure of dietary intake. ...
Identification of food intake biomarkers (FIBs) for fermented foods could help improve their dietary assessment and clarify their associations with cardiometabolic health. We aimed to identify novel FIBs for fermented foods in the plasma and urine metabolomes of 246 free-living Dutch adults using nontargeted LC-MS and GC-MS. Furthermore, associations between identified metabolites and several cardiometabolic risk factors were explored. In total, 37 metabolites were identified corresponding to the intakes of coffee, wine, and beer (none were identified for cocoa, bread, cheese, or yoghurt intake). While some of these metabolites appeared to originate from raw food (e.g., niacin and trigonelline for coffee), others overlapped different fermented foods (e.g., 4-hydroxybenzeneacetic acid for both wine and beer). In addition, several fermentation-dependent metabolites were identified (erythritol and citramalate). Associations between these identified metabolites with cardiometabolic parameters were weak and inconclusive. Further evaluation is warranted to confirm their relationships with cardiometabolic disease risk.
... Biomarkers, as objective measures of dietary intake, may help in testing the association of usual FV intake with NCD and other health outcomes, and a number of approaches have been used to develop biomarker approaches, either using more traditional or newly developed biomarkers (26)(27)(28)(29) , but also combinations of biomarkers to reflect the complexity of this food group (30,31) , or a combination of biomarker and food intake data (32)(33)(34) . Innovation in this area will help to improve the robustness of the observational epidemiological evidence supported increased FV intake and reduced NCD risk. ...
A high intake of fruit and vegetables (FV) has consistently been associated with a reduced risk of a number of non-communicable diseases. This evidence base is largely from prospective cohort studies, with meta-analyses demonstrating an association between increased FV intake and reduced risk of both CHD and stroke, although the evidence is less certain for cancer and diabetes. Controlled intervention trials examining either clinical or intermediate risk factor endpoints are more scarce. Therefore, evidence that FV consumption reduces the risk of disease is so far largely confined to observational epidemiology, which is hampered by some methodological uncertainties. Although increased FV intake is promoted across all dietary guidelines, national surveys confirm that dietary intakes are suboptimal and are not increasing over time. A range of barriers to increasing FV intake exist, including economic, physical and behavioural barriers that must be considered when exploring potential opportunities to change this, considering the feasibility of different approaches to encourage increased FV consumption. Such interventions must include consideration of context, for example, challenges and uncertainties which exist with the whole food system.
... Among these, urine analysis has gained interest in recent years as it is easy to collect, non-invasive, and familiar to the patient. Since metabolites can be found in urine, there is the possibility of gaining indirect information about the metabolism of several organs as well as any inflammatory or neoplastic processes [3,4]. ...
Although known since the first half of the twentieth century, the evolution of spectroscopic techniques has undergone a strong acceleration after the 2000s, driven by the successful development of new computer technologies suitable for analyzing the large amount of data obtained. Today’s applications are no longer limited to analytical chemistry, but are becoming useful instruments in the medical field. Their versatility, rapidity, the volume of information obtained, especially when applied to biological fluids that are easy to collect, such as urine, could provide a novel diagnostic tool with great potential in the early detection of different diseases. This review aims to summarize the existing literature regarding spectroscopy analyses of urine samples, providing insight into potential future applications.
... An example of an important aspect of validation, which is often missing in the work on BFIs is the quantity of the food ingested; the current methodology is largely qualitative and combining data across several studies could be a facile way to improve this aspect of validation. To develop and validate this type of biomarker rich standardized questionnaires on intake, as the (not-so-) gold standard, and metabolomics data (as potential source of the biomarkers) are often used, 29 but as more and more markers are identified they may also be further refined by biomarker combinations. 26,30 Work on biomarker approaches to assess whole diets have also been advanced in recent projects and could develop into another set of tools in the intake biomarker toolbox. ...
Non-communicable diseases are on the rise and are often related to food choices; nutrition affects infectious diseases too. Therefore, there is growing interest in research on public and personal health, as related to food, nutrition behaviour and well-being of consumers throughout the life cycle. These concepts and their relations are complex and only partially understood – more data is needed to improve our understanding. The required data include deep geno- and phenotyping data from human nutritional studies, covering metabolic and health, but also including behavioural and socio-economic data. The aim of this white paper is to provide a guiding framework for the future contributions of ELIXIR’s recently established Food & Nutrition (F&N) Community. This white paper is the direct result of a strategy meeting that took place in September 2019 in The Hague (NL) and involved representatives of 14 countries representing the ELIXIR Nodes. The meeting led to the definition of F&N related bioinformatics challenges, including the use of standards for data reuse and sharing, and for interoperability of data, tools and services, advocacy and training. Resolving these bioinformatics challenges makes it possible to address a wide range of F&N-related challenges, such as definition of an individual health status, individual dietary needs, and finding complex intake biomarkers (to replace questionnaires). Here, we provide suggestions on how to align these tasks within the ELIXIR Platforms, other ELIXIR Communities/Focus Groups and the European Strategy Forum on Research Infrastructures.
... Secondly, a priori-defined food biomarkers that have reached an appropriate level of validation [124] could be measured in association with CRF to test specific diet exposure-CRF hypotheses. For example, biomarkers of coffee (quinate, 3-hydroxypyridine sulfate, 1,3-dimethylurate), alcohol (ethyl glucuronide), multivitamins (pantothenate (B 5 ), pyridoxal, alpha-tocopherol) and citrus fruits (proline betaine) have been validated in large-scale cohort studies and subsequently tested in acute dietary intervention or feeding studies [116,[125][126][127][128][129][130][131]. Leveraging nutritional metabolomics data derived from other types of biospecimens (e.g., fecal metabolites) may also provide novel insights, such as diet-microbiome interaction in relation to CRF. ...
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.
... Despite their limited availability [30,31], biomarkers are more sensitive for quantifying the magnitude and direction of potential measurement errors than traditional self-report dietary assessment methods [53]. Therefore, an important strength of this evaluation study was the collection of biological samples, which offered the opportunity to conduct established urineand blood-based nutrient biomarker assessments, including nitrogen, potassium, sodium, folate, carotenoids and EPA/DHA, as well as more innovative food metabolomics [54]. Moreover, similarly to a few of the validated apps, we used accelerometers to obtain an objective measure for TEE. ...
During recent years, the integration of technology has substantially improved self-reported dietary assessment methods, such as food frequency questionnaires (FFQ), food records, and 24-h recalls. To further reduce measurement error, additional innovations are urgently needed. Memory-related measurement error is one of the aspects that warrants attention, which is where new smartphone technologies and ecological momentary assessment (EMA) approaches provide a unique opportunity. In this article, we describe the DIASS study, which was designed to evaluate an innovative 2-h recall (2hR) smartphone-based methodology, against traditional 24-h recalls, FFQ, and biomarkers, to assess both actual and habitual dietary intake. It is hypothesized that a 2-h reporting window decreases reliance on memory and reporting burden, and increases data accuracy. We included 215 men (28%) and women (72%), with a mean ± SD age of 39 ± 19 years and a mean ± SD BMI of 23.8 ± 4.0. Most participants were highly educated (58%). Response rates for the various dietary assessment methods were >90%. Besides the evaluation of the accuracy, usability, and perceived burden of the 2hR methodology, the study set-up also allows for (further) evaluation of the other administrated dietary assessment tools.
... Enhancing technological tools is always important [76] with consequences on the governance of complex nutritional database systems (e.g., the food composition data to confer reliability to the tips provided by apps on smartphones) [100]. Another increasingly important issue is the possibility to integrate dietary assessment and other techniques belonging to metabolomics [101] in general, and biomarkers studies [102], that are proposed for "objective dietary assessment" [63]. ...
Diet and human health have a complex set of relationships, so it is crucial to identify the cause-effects paths and their management. Diet is crucial for maintaining health (prevention) and unhealthy diets or diet components can cause disease in the long term (non-communicable disease) but also in the short term (foodborne diseases). The present paper aims to provide a synthesis of current research in the field of dietary assessment in health and disease as an introduction to the special issue on “Dietary Assessment and Human Health and Disease”. Dietary assessment, continuously evolving in terms of methodology and tools, provides the core information basis for all the studies where it is necessary to disentangle the relationship between diet and human health and disease. Estimating dietary patterns allows for assessing dietary quality, adequacy, exposure, and environmental impact in nutritional surveillance so on the one hand, providing information for further clinical studies and on another hand, helping the policy to design tailored interventions considering individual and planetary health, considering that planetary health is crucial for individual health too, as the SARS-CoV-2 (COVID-19) pandemic has taught. Overall, dietary assessment should be a core component in One-Health-based initiatives to tackle public health nutrition issues.
... Several narrative reviews and position papers have highlighted the importance of metabolomic profiling for the objective assessment of dietary exposure. 22,[37][38][39][40][41][42][43] Previous reviews summarizing the available evidence for metabolomic biomarkers of dietary exposure have either (a) not been conducted in a systematic manner; 16 (b) compiled the evidence for a single biofluid, eg, urine 16 ; and/or (c) focused on a single dietary pattern, eg, the Nordic diet, 44 specific foods, nutrients, or other food components, eg, macronutrients, herbs, spices, dairy, eggs, meat, cocoa, phenolics, legumes, nuts, and vegetable oils. 2,15,[17][18][19]39,[45][46][47][48][49] The only systematic review describing metabolomic biomarkers of dietary patterns published in 2018 used a limited search of a few keywords on a single platform, ie, PubMed. ...
Context:
Establishing diet-disease associations requires reliable assessment of dietary intake. With the rapid advancement of metabolomics, its use in identifying objective biomarkers of dietary exposure has substantially increased.
Objective:
The aim of our review was to systematically combine all observational studies linking dietary intake patterns with metabolomic profiles of human biospecimens.
Data sources:
Five databases were searched - MEDLINE, Embase, Scopus, Web of Science, and Cochrane CENTRAL - to March 2020.
Data extraction:
Of the 14 328 studies initially screened, 35 observational studies that met the specified inclusion criteria were included.
Data analysis:
All reviewed studies indicated that metabolomic measures were significantly correlated with dietary patterns, demonstrating the potential for using objective metabolomic measures to characterize individuals' dietary intake. However, similar dietary patterns did not always result in similar metabolomic profiles across different study populations.
Conclusion:
Metabolomic profiles reflect a multitude of factors, including diet, genetic, phenotypic, and environmental influences, thereby providing a more comprehensive picture of the impact of diet on metabolism and health outcomes. Further exploration of dietary patterns and metabolomic profiles across different population groups is warranted.
... To address some of the concerns surrounding self-reported dietary data, the potential role of dietary biomarkers has emerged. While classical biomarkers for salt, protein and energy intake have existed for years, the emergence of metabolomics has resulted in the expansion of dietary biomarkers to include biomarkers for specific foods and dietary patterns [9][10][11]. While the potential of classical biomarkers for correcting self-reported data is well-established, there is emerging evidence that novel food and nutrient biomarkers that are discovered agnostically through metabolomic profiling can also be employed to correct self-reported data. ...
Traditionally, nutritional epidemiology is the study of the relationship between diet and health and disease in humans at the population level. Commonly, the exposure of interest is food intake. In recent years, nutritional epidemiology has moved from a “black box” approach to a systems approach where genomics, metabolomics and proteomics are providing novel insights into the interplay between diet and health. In this context, metabolomics is emerging as a key tool in nutritional epidemiology. The present review explores the use of metabolomics in nutritional epidemiology. In particular, it examines the role that food-intake biomarkers play in addressing the limitations of self-reported dietary intake data and the potential of using metabolite measurements in assessing the impact of diet on metabolic pathways and physiological processes. However, for full realisation of the potential of metabolomics in nutritional epidemiology, key challenges such as robust biomarker validation and novel methods for new metabolite identification need to be addressed. The synergy between traditional epidemiologic approaches and metabolomics will facilitate the translation of nutritional epidemiologic evidence to effective precision nutrition.
... To catalog these BFIs, members of the FoodBAll consortium systematically reviewed the literature and conducted independent metabolomic studies to identify dozens of BFIs for many classes of foods [17,[48][49][50][51][52]. The FoodBAll consortium also developed protocols and definitions for BFI identification and validation [53,54]. ...
Background:
For thousands of years, disabilities due to nutrient deficiencies have plagued humanity. Rickets, scurvy, anemia, stunted growth, blindness, and mental handicaps due to nutrient deficiencies affected up to 1/10 of the world's population prior to 1900. The discovery of essential amino acids, vitamins, and minerals, in the early 1900s, led to a fundamental change in our understanding of food and a revolution in human health. Widespread vitamin and mineral supplementation, the development of recommended dietary allowances, and the implementation of food labeling and testing along with significant improvements in food production and food quality have meant that nutrient-related disorders have almost vanished in the developed world. The success of nutritional science in preventing disease at a population-wide level is one of the great scientific triumphs of the 20th century. The challenge for nutritional science in the 21st century is to understand how to use nutrients and other food constituents to enhance human health or prevent disease at a more personal level. This is the primary goal of precision nutrition.
Summary:
Precision nutrition is an emerging branch of nutrition science that aims to use modern omics technologies (genomics, proteomics, and metabolomics) to assess an individual's response to specific foods or dietary patterns and thereby determine the most effective diet or lifestyle interventions to prevent or treat specific diseases in that individual. Metabolomics is vital to nearly every aspect of precision nutrition. It can be used to comprehensively characterize the thousands of chemicals in foods, to identify food byproducts in human biofluids or tissues, to characterize nutrient deficiencies or excesses, to monitor biochemical responses to dietary interventions, to track long-term or short-term dietary habits, and to guide the development of nutritional therapies. In this review, we will describe how metabolomics has been used to advance the field of precision nutrition by providing some notable examples or use cases. First, we will describe how metabolomics helped launch the field of precision nutrition through the diagnosis and dietary therapy of individuals with inborn errors of metabolism. Next, we will describe how metabolomics is being used to comprehensively characterize the full chemical complexity of many key foods, and how this is revealing much more about nutrients than ever imagined. Third, we will describe how metabolomics is being used to identify food consumption biomarkers and how this opens the door to a more objective and quantitative assessments of an individual's diet and their response to certain foods. Finally, we will describe how metabolomics is being coupled with other omics technologies to develop custom diets and lifestyle interventions that are leading to positive health benefits. Key Message: Metabolomics is vital to the advancement of nutritional science and in making the dream of precision nutrition a reality.
... FFQ, food diaries, and 24 h recall methods represent the most commonly used dietary assessment tools in human studies on nutrition and health, but food intake biomarkers are assumed to provide a more objective reflection of intake. Unfortunately, very few of these biomarkers are sufficiently validated [23]. ...
The growing epidemic of chronic diseases afflicting both developed and developing countries is related to diet and lifestyle. The current dietary assessment still has many constraints, particularly related to the objectivity of data gathering. Dental calculus, which is usually considered as medical waste in dental treatment, turns out to be a provider of abundant oral information. The objective of this study is to obtain the correlation between the macronutrient content of dental calculus and nutritional intake based on FFQ. This research is an analytic observational study with a case-control study design. Samples consisting of 35 obese individuals and 21 normal-weight individuals were taken using purposive sampling. The nutritional intake data were obtained using FFQ. The macronutrient content of dental calculus was checked using a colorimetric assay. The comparison between obese individuals and normal-weight individuals was tested using the Mann–Whitney test and T-test. The correlation between the macronutrient content of dental calculus and nutritional intake based on FFQ was measured using Spearman’s rank-order correlation. The results showed there was a correlation between the macronutrient content of dental calculus and macronutrient intake based on FFQ. However, strong correlation was found only between fat intake with the total lipid content of dental calculus with rs = 0.521 and between carbohydrate intake with the total carbohydrate content of dental calculus with rs = 0.519. It was concluded that carbohydrate, protein, and lipid intake can be assessed using dental calculus. Dental calculus can be an alternative source of noninvasive, inexpensive, and specific dietary biomarkers.
Food biotechnology is a scientific discipline that uses genetic engineering methods on plants, animals, or microorganisms to enhance food quality. It also involves the application of commercial packaging technology to promote food preservation, as well as the implementation of microbial fermentation processes to yield innovative food ingredients, enzymes, and additives. Food biotechnology has brought about significant advancements in food production, processing, and consumption, with a particular emphasis on using additives and preservatives. This chapter delves deeper into how biotech-based additives and preservatives can meet the needs and preferences of consumers by providing them with exceptional quality food that is guaranteed to be safe. Additionally, this chapter elucidates the multifunctional nature of these additives and preservatives, which extend beyond the scope of mere taste enhancement.
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.
Scope:
Evidence on the Mediterranean diet (MD) and age-related cognitive decline (CD) is still inconclusive partly due to self-reported dietary assessment. The aim of the current study is to develop an MD- metabolomic score (MDMS) and investigate its association with CD in community-dwelling older adults.
Methods and results:
This study includes participants from the Three-City Study from the Bordeaux (n = 418) and Dijon (n = 422) cohorts who are free of dementia at baseline. Repeated measures of cognition over 12 years are collected. An MDMS is designed based on serum biomarkers related to MD key food groups and using a targeted metabolomics platform. Associations with CD are investigated through conditional logistic regression (matched on age, sex, and education level) in both sample sets. The MDMS is found to be inversely associated with CD (odds ratio [OR] [95% confidence interval (CI)] = 0.90 [0.80-1.00]; p = 0.048) in the Bordeaux (discovery) cohort. Results are comparable in the Dijon (validation) cohort, with a trend toward significance (OR [95% CI] = 0.91 [0.83-1.01]; p = 0.084).
Conclusions:
A greater adherence to the MD, here assessed by a serum MDMS, is associated with lower odds of CD in older adults.
Precision nutrition aims to deliver personalised dietary advice to individuals based on their personal genetics, metabolism and dietary/environmental exposures. Recent advances have demonstrated promise for the use of omic technologies for furthering the field of precision nutrition. Metabolomics in particular is highly attractive as measurement of metabolites can capture information on food intake, levels of bioactive compounds and the impact of diets on endogenous metabolism. These aspects contain useful information for precision nutrition. Furthermore using metabolomic profiles to identify subgroups or metabotypes is attractive for the delivery of personalised dietary advice. Combining metabolomic derived metabolites with other parameters in prediction models is also an exciting avenue for understanding and predicting response to dietary interventions. Examples include but not limited to role of one carbon metabolism and associated co-factors in blood pressure response. Overall, while evidence exists for potential in this field there are also many unanswered questions. Addressing these and clearly demonstrating that precision nutrition approaches enable adherence to healthier diets and improvements in health will be key in the near future.
Breast cancer is one of the most common types of cancer in women worldwide, and its incidence is increasing. Diet has been identified as a modifiable risk factor for breast cancer, but the complex interplay between diet, metabolism, and cancer development is not fully understood. Nutritional metabolomics is a rapidly evolving field that can provide insights into the metabolic changes associated with dietary factors and their impact on breast cancer risk. The review’s objective is to provide a comprehensive overview of the current research on the application of nutritional metabolomics in understanding the relationship between diet and breast cancer. The search strategy involved querying several electronic databases, including PubMed, Scopus, Web of Science, and Google Scholar. The search terms included combinations of relevant keywords such as “nutritional metabolomics”, “diet”, “breast cancer”, “metabolites”, and “biomarkers”. In this review, both in vivo and in vitro studies were included, and we summarize the current state of knowledge on the role of nutritional metabolomics in understanding the diet–breast cancer relationship, including identifying specific metabolites and metabolic pathways associated with breast cancer risk. We also discuss the challenges associated with nutritional metabolomics research, including standardization of analytical methods, interpretation of complex data, and integration of multiple-omics approaches. Finally, we highlight future directions for nutritional metabolomics research in studying diet–breast cancer relations, including investigating the role of gut microbiota and integrating multiple-omics approaches. The application of nutritional metabolomics in the study of diet–breast cancer relations, including 2-amino-4-cyano butanoic acid, piperine, caprate, rosten-3β,17β-diol-monosulfate, and γ-carboxyethyl hydrochroman, among others, holds great promise for advancing our understanding of the role of diet in breast cancer development and identifying personalized dietary recommendations for breast cancer prevention, control, and treatment.
The importance of a healthy diet for humans is known for decades. The elucidation of key molecules responsible for the beneficial and adverse dietary effects is slowly developing as the tools are missing. Carbonyl-containing metabolites are a common bioproducts through conversion of diet by the microbiome. In here, we have utilized our recently developed mass spectrometric methodology based on chemoselective conjugation of carbonyl-metabolites. The method has been applied for urine sample analysis from a dietary (poly)phenol intervention study (N = 78 individuals) for the first time. We have identified a series of carbonyl-metabolites of dietary origin and the chemical structure was validated for 30 metabolites. Our sensitive analysis led to the discovery of four unknown dietary markers with high sensitivity and selectivity (AUC > 0.91). Our chemical metabolomics method has been successfully applied for large-scale analysis and provides the basis for targeted metabolomics to identify unknown nutritional and disease-related biomarkers.
Nutritional biomarkers of dairy intake can be affected by both food transformation and the metabolic status of the consumer. To assess these effects, this study investigated the serum volatilome of 14 young (YA) and 14 older (OA) adult men undergoing a 3 week restriction of dairy and fermented foods followed by a randomized crossover acute intake of milk and yogurt. 3,5-Dimethyl-octan-2-one was identified as a potential marker of dairy product intake as its response after both milk and yogurt intake was significantly increased during the postprandial phase but significantly decreased in fasting serum samples of the OA group after the restriction phase. The postprandial response of two metabolites was significantly different for the two dairy products while 19 metabolites were modulated by age. Remarkably, the response of all age-dependent metabolites was higher in the OA than in the YA group after milk or yogurt intake, whereas at the end of the restriction phase, their fasting concentrations were lower in the OA than in the YA group. Among these, p-cresol, a specific marker of colonic protein fermentation, had a significant response in the OA but not the YA group, which may suggest impaired intestinal processing of dietary proteins in the OA group.
Purpose:
In people with epilepsy achieving optimal dietary intake may be hampered by psychological and physical comorbidities associated with seizures, medication use, socioeconomic disadvantage and the use of therapeutic diets. This systematic review aimed to evaluate the reported dietary intake and nutritional status of children and adults with epilepsy.
Methods:
A systematic literature search was completed across Ovid MEDLINE, EMBASE and CINAHL (all from inception to 4 November 2021). We included studies that reported dietary intake in adults and children diagnosed with epilepsy compared with local reference ranges, control groups or general populations. Studies using interventions and therapeutic diets were excluded. Risk of bias was assessed using the Study Quality Assessment Tools by the National Heart, Lung and Blood Institute. A descriptive analysis was performed due to the heterogenous nature of the data.
Results:
The initial search returned 1214 articles. Full-text screening was completed for 98 studies and 19 studies met eligibility criteria and were included for extraction. These comprised of seven paediatric studies, eight adult studies and four studies that included both adult and paediatric cohorts. Sample size of cases in each study ranged from 17 to 3,220. Vitamin A, C, D and folate were the most frequently reported vitamins. Calcium, iron and zinc were the most commonly reported minerals. Most studies showed that people with epilepsy had poorer dietary intake and nutritional status compared with control groups or reference standards.
Conclusion:
There were limited studies on dietary intake and nutritional status in people with epilepsy. Most available studies suggested poorer status compared to non-epilepsy controls. The development of a validated dietary assessment tool specifically for epilepsy cohorts would enable comparison of findings across studies, and aid with appropriately tailoring nutrition advice to individuals with epilepsy.
Nutrition influences health throughout the life course. Good nutrition increases the probability of good pregnancy outcomes, proper childhood development, and healthy aging, and it lowers the probability of developing common diet-related chronic diseases, including obesity, cardiovascular disease, cancer, and type 2 diabetes. Despite the importance of diet and health, studying these exposures is among the most challenging in population sciences research. US and global food supplies are complex; eating patterns have shifted such that half of meals are eaten away from home, and there are thousands of food ingredients with myriad combinations. These complexities make dietary assessment and links to health challenging for both population sciences research and for public health policy and practice. Furthermore, most studies evaluating nutrition and health usually rely on self-report instruments prone to random and systematic measurement error. Scientific advances involve developing nutritional biomarkers and then applying these biomarkers as stand-alone nutritional exposures or for calibrating self-reports using specialized statistics.
Expected final online publication date for the Annual Review of Public Health, Volume 44 is April 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Purpose
Milk-derived free fatty acids (FFAs) may act as both biomarkers of intake and metabolic effect. In this study we explored associations between different types of dairy consumption, a selection of milk-derived free fatty acids, and cardiometabolic disease (CMD) risk factors.
Methods
Sixty-seven FFAs were quantified in the plasma of 131 free-living Dutch adults (median 60 years) using gas chromatography-flame ionization detector. Intakes of different dairy foods and groups were assessed using a food frequency questionnaire. Twelve different CMD risk factors were analyzed. Multiple linear regressions were used to evaluate the associations under study.
Results
Based on the fully adjusted models, 5 long-chain unsaturated FFAs (C18:1 t13 + c6 + c7 + u, C18:2 c9t11 + u, C20:1 c11, C20:3 c8c11c14, and C20:4 c5c8c11c14), 2 medium-chain saturated FFAs (C15, C15 iso ), and a trans FFA (C16:1 t9) were positively associated with at least one variable of dairy intake, as well as plasma total and LDL cholesterol, blood pressure, and SCORE ( p ≤ 0.05). A long-chain PUFA associated with high-fat fermented dairy intake (C18:2 t9t12), was negatively associated with serum triglyceride levels, and a long-chain saturated FFA associated with cheese intake (C18:1 u1) was negatively associated with plasma LDL cholesterol and serum triglyceride levels. No clear associations were observed between dairy intake and CMD risk factors.
Conclusion
Milk-derived FFAs could act as sensitive biomarkers for dairy intake and metabolism, allowing the association between dairy and CMD risk to be more precisely evaluated.
Diet and nutrition have an essential connection to human health. Dietary data provide valuable information about specific associations between exposure to dietary components and health, disease, or mortality. Due to the high daily variability of diet, the accurate assessment of dietary intake in the free-living human population is more challenging than the measurement of other environmental exposures. For most epidemiological studies, exposure to a long-term diet is more relevant than intake on a specific day or a reduced number of days. It is essential to choose a suitable method for assessing diet and interpreting data collected. Dietary intake can be assessed using subjective or objective methods. Subjective methods are based on people’s memory, who must answer a self-reporting form, or can be carried out by a trained interviewer, recalling food and food preparations consumed at the previous mealtime, the day before, or for a specified period. Subjective dietary assessment methods include the food frequency questionnaire, 24-hour dietary recall, food record, and weight food record. In recent years, technological innovations have improved data collection methods and subsequent analysis, but the problem of misreporting dietary intake, whether voluntary or involuntary, persists and contributes to data inaccuracy and misinterpretation. Objective dietary assessment methods appeal to nutritional biomarkers to estimate dietary exposures. These markers highly correlated with dietary intake, regardless of the subject’s memory and ability to describe the type and quantity of food consumed. These methods are usually expensive and invasive, so their use in large epidemiological studies can be difficult to implement. Some biomarkers have been used to validate dietary questionnaires, which are frequently used in large epidemiological studies; for example, the case of doubly labeled water as a marker of dietary energy. The human validation of this technique included different ages and conditions. Most of the studies show lower values for reported energy intake compared with measured total energy expenditure. This underreporting is usually higher in people with obesity. Biomarkers are also used to measure intake or exposure to a food component; for example, urinary sodium excretion is used as an objective marker of sodium intake or urinary nitrogen, which provides an objective measurement of dietary protein intake. Biomarkers can also be used to assess nutritional status by measuring body fluids like urine, blood, saliva, or tissues or even provide accurate information of dietary intake and new insights into the biological effect of dietary patterns and lifestyle and their impact on health/disease risk. In recent years, omics technologies have been integrated into nutritional epidemiological research to identify novel biomarkers. These scientific advances will help researchers obtain more accurate data and will allow for a better calibration of traditional methods when assessing dietary intake.Key wordsDietary intake assessment methodsFood frequency questionnaire24-hour dietary recallFood recordsDoubly labeled waterBiomarkersValidity
All living creatures need to eat. Eating a variety of different healthy foods in moderate amounts is important. How do we know which foods are healthy? Researchers can compare the foods consumed by healthy and unhealthy people by asking what and how much they eat. Unfortunately, people cannot always remember what and how much they eat, which makes it difficult to figure out which foods are healthy. Recently, researchers discovered that a group of research tools called omics could help. When people eat, the building blocks of food are broken down into small compounds called metabolites. With laboratory equipment, researchers can measures these metabolites in food and in the body, to help them get a better idea of which foods are healthy or unhealthy. Researchers can also use omics tools to find the best foods for each unique person so that we can all stay healthy and happy.
Food is a complex matter, literally. From production to functionalization, from nutritional quality engineering to predicting effects on health, the interest in finding an efficient physicochemical characterization of food has boomed in recent years. The sheer complexity of characterizing food and its interaction with the human organism has however made the use of data driven approaches in modelling a necessity. High‐throughput techniques, such as Nuclear Magnetic Resonance (NMR) spectroscopy, are well suited for omics data production and, coupled with machine learning, are paving a promising way of modelling food‐human interaction. The foodomics approach sets the framework for omic data integration in food studies, in which NMR experiments play a key role. NMR data can be used to assess nutritional qualities of food, helping the design of functional and sustainable sources of nutrients, detect biomarkers of intake and study how they impact the metabolism of different individuals, study the kinetics of compounds in foods or their by‐products to detect pathological conditions and improve the efficiency of in‐silico models of the metabolic network.
The Eetscore FFQ was developed to score the Dutch Healthy Diet index 2015 (DHD2015-index) representing the Dutch food-based dietary guidelines of 2015. This paper describes the development of the Eetscore FFQ, a short screener assessing diet quality, examines associations between diet quality and participants’ characteristics, and evaluates the relative validity and reproducibility of the Eetscore FFQ in a cross-sectional study with Dutch adults. The study sample consisted of 751 participants, aged 19-91 y, recruited from the EetMeetWeet research panel. The mean DHD2015-index score based on the Eetscore FFQ of the total sample was 111 (SD 17.5) out of a maximum score of 160 points and was significantly higher in women than in men, positively associated with age and education level, and inversely associated with BMI. The Kendall’s tau-b coefficient of the DHD2015- index between the Eetscore FFQ and the full-length FFQ (on average 1.7-month interval, n=565) was 0.51 (95% CI 0.47, 0.55), indicating an acceptable ranking ability. The intraclass correlation coefficient (ICC) between DHD2015-index scores derived from two repeated Eetscore FFQs (on average 3.8-month interval, n=343) was 0.91 (95% CI: 0.89, 0.93) suggesting a very good reproducibility. In conclusion, the Eetscore FFQ was considered acceptable in ranking participants according to their diet quality compared with the full-length FFQ and showed good to excellent reproducibility.
The traditional Mediterranean diet (MedDiet), rich in minimally processed plant foods and fish, has been widely recognized to be one of the healthiest diets. Data from multiple randomized clinical trials have demonstrated its powerful effect against oxidative stress, inflammation and the development and progression of cardiovascular disease, type 2 diabetes, and other metabolic conditions that play a crucial role in the pathogenesis of neurodegenerative diseases.
The protecting effects of the MedDiet against cognitive decline have been investigated in several observational and experimental studies. Data from observational studies suggest that the MedDiet may represent an effective dietary strategy for the early prevention of dementia, although these findings require further substantiation in clinical trials which have so far produced inconclusive results. Moreover, as we discuss in this review, accumulating data emphasizes the importance of: 1) maintaining an optimal nutritional and metabolic status for the promotion of healthy cognitive aging, and 2) implementing cognition-sparing dietary and lifestyle interventions during early time-sensitive windows before the pathological cascades turn into an irreversible state.
In summary, components of the MedDiet pattern, such as essential fatty acids, polyphenols and vitamins, have been associated with reduced oxidative stress and the current evidence from observational studies seems to assign to the MedDiet a beneficial role in promoting brain health; however, results from clinical trials have been inconsistent. While we advocate for longitudinal analyses and for larger and longer clinical trials to be conducted, we assert our interim support to the use of the MedDiet as a protective dietary intervention for cognitive function based on its proven cardiovascular and metabolic benefits.
The authors evaluated the validity of a 152-item semiquantitative food frequency questionnaire (SFFQ) by comparing it with two 7-day dietary records (7DDRs) or up to 4 automated self-administered 24-hour recalls (ASA24s) over a 1-year period in the women's Lifestyle Validation Study (2010-2012), conducted among subgroups of the Nurses' Health Studies. Intakes of energy and 44 nutrients were assessed using the 3 methods among 632 US women. Compared with the 7DDRs, SFFQ responses tended to underestimate sodium intake but overestimate intakes of energy, macronutrients, and several nutrients in fruits and vegetables, such as carotenoids. Spearman correlation coefficients between energy-adjusted intakes from 7DDRs and the SFFQ completed at the end of the data-collection period ranged from 0.36 for lauric acid to 0.77 for alcohol (mean r = 0.53). Correlations of the end-period SFFQ were weaker when ASA24s were used as the comparison method (mean r = 0.43). After adjustment for within-person variation in the comparison method, the correlations of the final SFFQ were similar with 7DDRs (mean r = 0.63) and ASA24s (mean r = 0.62). These data indicate that this SFFQ provided reasonably valid estimates for intakes of a wide variety of dietary variables and that use of multiple 24-hour recalls or 7DDRs as a comparison method provided similar conclusions if day-to-day variation was taken into account.
Exposome-Explorer (http://exposome-explorer.iarc.fr) is the first database dedicated to biomarkers of exposure to environmental risk factors. It contains detailed information on the nature of biomarkers, their concentrations in various human biospecimens, the study population where measured and the analytical techniques used for measurement. It also contains correlations with external exposure measurements and data on biological reproducibility over time. The data in Exposome-Explorer was manually collected from peer-reviewed publications and organized to make it easily accessible through a web interface for in-depth analyses. The database and the web interface were developed using the Ruby on Rails framework. A total of 480 publications were analyzed and 10 510 concentration values in blood, urine and other biospecimens for 692 dietary and pollutant biomarkers were collected. Over 8000 correlation values between dietary biomarker levels and food intake as well as 536 values of biological reproducibility over time were also compiled. Exposome-Explorer makes it easy to compare the performance between biomarkers and their fields of application. It should be particularly useful for epidemiologists and clinicians wishing to select panels of biomarkers that can be used in biomonitoring studies or in exposome-wide association studies, thereby allowing them to better understand the etiology of chronic diseases.
Background:
The human metabolome is influenced by various intrinsic and extrinsic factors. A precondition to identify such biomarkers is the comprehensive understanding of the composition and variability of the metabolome of healthy humans. Sample handling aspects have an important impact on the composition of the metabolome; therefore, it is crucial for any metabolomics study to standardize protocols on sample collection, preanalytical sample handling, storage, and analytics to keep the nonbiological variability as low as possible.
Objective:
The main objective of the KarMeN study is to analyze the human metabolome in blood and urine by targeted and untargeted metabolite profiling (gas chromatography-mass spectrometry [GC-MS], GC×GC-MS, liquid chromatography-mass spectrometry [LC-MS/MS], and(1)H nuclear magnetic resonance [NMR] spectroscopy) and to determine the impact of sex, age, body composition, diet, and physical activity on metabolite profiles of healthy women and men. Here, we report the outline of the study protocol with special regard to all aspects that should be considered in studies applying metabolomics.
Methods:
Healthy men and women, aged 18 years or older, were recruited. In addition to a number of anthropometric (height, weight, body mass index, waist circumference, body composition), clinical (blood pressure, electrocardiogram, blood and urine clinical chemistry) and functional parameters (lung function, arterial stiffness), resting metabolic rate, physical activity, fitness, and dietary intake were assessed, and 24-hour urine, fasting spot urine, and plasma samples were collected. Standard operating procedures were established for all steps of the study design. Using different analytical techniques (LC-MS, GC×GC-MS,(1)H NMR spectroscopy), metabolite profiles of urine and plasma were determined. Data will be analyzed using univariate and multivariate as well as predictive modeling methods.
Results:
The project was funded in 2011 and enrollment was carried out between March 2012 and July 2013. A total of 301 volunteers were eligible to participate in the study. Metabolite profiling of plasma and urine samples has been completed and data analysis is currently underway.
Conclusions:
We established the KarMeN study applying a broad set of clinical and physiological examinations with a high degree of standardization. Our experimental approach of combining scheduled timing of examinations and sampling with the multiplatform approach (GC×GC-MS, GC-MS, LC-MS/MS, and(1)H NMR spectroscopy) will enable us to differentiate between current and long-term effects of diet and physical activity on metabolite profiles, while enabling us at the same time to consider confounders such as age and sex in the KarMeN study.
Trial registration:
German Clinical Trials Register DRKS00004890; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00004890 (Archived by WebCite at http://www.webcitation.org/6iyM8dMtx).
Biomarkers of nutrient intake or nutrient status are important objective measures of foods/nutrients as one of the most important environmental factors people are exposed to. It is very difficult to obtain accurate data on individual food intake, and there is a large variation of nutrient composition of foods consumed in a population. Thus, it is difficult to obtain precise measures of exposure to different nutrients and thereby be able to understand the relationship between diet, health, and disease. This is the background for investing considerable resources in studying biomarkers of nutrients believed to be important in our foods. Modern technology with high sensitivity and specificity concerning many nutrient biomarkers has allowed an interesting development with analyses of very small amounts of blood or tissue material. In combination with non-professional collection of blood by finger-pricking and collection on filters or sticks, this may make collection of samples and analyses of biomarkers much more available for scientists as well as health professionals and even lay people in particular in relation to the marked trend of self-monitoring of body functions linked to mobile phone technology. Assuming standard operating procedures are used for collection, drying, transport, extraction, and analysis of samples, it turns out that many analytes of nutritional interest can be measured like metabolites, drugs, lipids, vitamins, minerals, and many types of peptides and proteins. The advantage of this alternative sampling technology is that non-professionals can collect, dry, and mail the samples; the samples can often be stored under room temperature in a dry atmosphere, requiring small amounts of blood. Another promising area is the potential relation between the microbiome and biomarkers that may bemeasured in feces as well as in blood.
Saliva is a clear, watery biofluid produced by the salivary glands to protect and lubricate the oral cavity. While mostly composed of water (99 %), the chemical composition of saliva is known to change quite dramatically in response to a variety of different physiological states, stimuli, insults and stressors. Unfortunately, among the human biofluids typically used in medical testing (such as blood and urine), saliva is rarely used. Given that saliva is the most easily accessible and readily obtained biofluid, this is rather unfortunate. Part of the reluctance to use saliva in medical testing likely has to do with the fact that its chemical composition is not well known. Here, a comprehensive characterization of the human saliva metabolome is presented. Multiple analytical platforms including nuclear magnetic resonance spectroscopy, gas chromatography mass spectrometry, direct flow injection/ liquid chromatography mass spectrometry, inductively coupled plasma mass spectrometry, and high performance liquid chromatography were employed to quantify the metabolites that can be commonly detected in human saliva. Using this multiplatform approach, we were able to quantify and/or identify 308 salivary metabolites or metabolite species in human saliva. This experimental work was complemented with computer-aided literature mining that led to the identification and annotation of another 708 salivary metabolites. The combined collection of 853 non-redundant salivary metabolites or metabolite species together with their concentrations, related literature references, and links to their known disease associations are freely available at http://www.hmdb.ca/.
Habitual red meat consumption was consistently related to a higher risk of type 2 diabetes in observational studies. Potentially underlying mechanisms are unclear.
This study aimed to identify blood metabolites that possibly relate red meat consumption to the occurrence of type 2 diabetes.
Analyses were conducted in the prospective European Prospective Investigation into Cancer and Nutrition-Potsdam cohort (n = 27,548), applying a nested case-cohort design (n = 2681, including 688 incident diabetes cases). Habitual diet was assessed with validated semiquantitative food-frequency questionnaires. Total red meat consumption was defined as energy-standardized summed intake of unprocessed and processed red meats. Concentrations of 14 amino acids, 17 acylcarnitines, 81 glycerophospholipids, 14 sphingomyelins, and ferritin were determined in serum samples from baseline. These biomarkers were considered potential mediators of the relation between total red meat consumption and diabetes risk in Cox models. The proportion of diabetes risk explainable by biomarker adjustment was estimated in a bootstrapping procedure with 1000 replicates.
After adjustment for age, sex, lifestyle, diet, and body mass index, total red meat consumption was directly related to diabetes risk [HR for 2 SD (11 g/MJ): 1.26; 95% CI: 1.01, 1.57]. Six biomarkers (ferritin, glycine, diacyl phosphatidylcholines 36:4 and 38:4, lysophosphatidylcholine 17:0, and hydroxy-sphingomyelin 14:1) were associated with red meat consumption and diabetes risk. The red meat-associated diabetes risk was significantly (P < 0.001) attenuated after simultaneous adjustment for these biomarkers [biomarker-adjusted HR for 2 SD (11 g/MJ): 1.09; 95% CI: 0.86, 1.38]. The proportion of diabetes risk explainable by respective biomarkers was 69% (IQR: 49%, 106%).
In our study, high ferritin, low glycine, and altered hepatic-derived lipid concentrations in the circulation were associated with total red meat consumption and, independent of red meat, with diabetes risk. The red meat-associated diabetes risk was largely attenuated after adjustment for selected biomarkers, which is consistent with the presumed mediation hypothesis.
© 2015 American Society for Nutrition.
Fruit and vegetable consumption produces changes in several biomarkers in blood. The present study aimed to examine the dose-response curve between fruit and vegetable consumption and carotenoid (α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein and zeaxanthin), folate and vitamin C concentrations. Furthermore, a prediction model of fruit and vegetable intake based on these biomarkers and subject characteristics (i.e. age, sex, BMI and smoking status) was established. Data from twelve diet-controlled intervention studies were obtained to develop a prediction model for fruit and vegetable intake (including and excluding fruit and vegetable juices). The study population in the present individual participant data meta-analysis consisted of 526 men and women. Carotenoid, folate and vitamin C concentrations showed a positive relationship with fruit and vegetable intake. Measures of performance for the prediction model were calculated using cross-validation. For the prediction model of fruit, vegetable and juice intake, the root mean squared error (RMSE) was 258·0 g, the correlation between observed and predicted intake was 0·78 and the mean difference between observed and predicted intake was - 1·7 g (limits of agreement: - 466·3, 462·8 g). For the prediction of fruit and vegetable intake (excluding juices), the RMSE was 201·1 g, the correlation was 0·65 and the mean bias was 2·4 g (limits of agreement: - 368·2, 373·0 g). The prediction models which include the biomarkers and subject characteristics may be used to estimate average intake at the group level and to investigate the ranking of individuals with regard to their intake of fruit and vegetables when validating questionnaires that measure intake.
Vitamin D plays a major role in Ca and bone metabolism, and its extraskeletal functions are being appraised. Although inadequate vitamin D concentrations have been reported in populations worldwide, too little is known about vitamin D status and its determinants among children in developing countries. We aimed to determine vitamin D status and its determinants in Nepalese children of pre-school age.
A community-based, cross-sectional study.
Rural Nepal at latitude 27·39°N.
Healthy children (n 280) aged 12-60 months, selected randomly from the records of a vitamin A supplementation programme. Blood samples were collected using the dried blood spot technique and analysed for serum 25-hydroxyvitamin D (s-25(OH)D) concentration using liquid chromatography-tandem mass spectrometry. Ca intake and background variables were assessed with a structured questionnaire.
Hypovitaminosis D, defined as s-25(OH)D concentration less than 50 nmol/l, was found in 91·1 % of the children. S-25(OH)D concentration was not related to gender, socio-economic indicators, sun exposure or nutritional status. Currently breast-fed children had higher s-25(OH)D concentrations (36·4 (sd 13·2) nmol/l) than those who were not (28·6 (sd 9·8) nmol/l, P<0·001). Adjustment for sociodemographic factors did not alter the results.
There is widespread vitamin D deficiency among pre-school children in a rural area of Nepal. In our sample, sociodemographic factors did not affect the vitamin D status of children, but prolonged breast-feeding was associated with higher s-25(OH)D concentrations. Further research is required to investigate the health consequences of poor vitamin D status for this population.
Older adults represent a substantial number of the world population, which is set to grow considerably in the coming years. The health challenges faced by the older adults are unique. Several age-related changes in them make phlebotomy difficult. Application of dried blood has been demonstrated to be useful in the other similarly vulnerable population, the neonates. Similar approach of standardization and demonstration of use of dried blood spots (DBS) for analytes of interest in older adult population would be highly appreciated. There are very few reports of use of DBS in older adults. There are several potential areas of interest for older adults in which DBS assays are available but have not been applied for screening in them. This review describes a brief general overview of DBS, its advantages and disadvantages and potential use in disease diagnosis in older adults.
Analysis of the human metabolome has yielded valuable insights into health, disease and toxicity. However, the metabolic profile of complex biological fluids such as blood is highly dynamic and this has limited the discovery of robust biomarkers. Hair grows relatively slowly, and both endogenous compounds and environmental exposures are incorporated from blood into hair during growth, which reflects the average chemical composition over several months.
We used hair samples to study the metabolite profiles of women with pregnancies complicated by fetal growth restriction (FGR) and healthy matched controls. We report the use of GC-MS metabolite profiling of hair samples for biomarker discovery. Unsupervised statistical analysis showed complete discrimination of FGR from controls based on hair composition alone. A predictive model combining 5 metabolites produced an area under the receiver-operating curve of 0.998.
This is the first study of the metabolome of human hair and demonstrates that this biological material contains robust biomarkers, which may lead to the development of a sensitive diagnostic tool for FGR, and perhaps more importantly, to stable biomarkers for a range of other diseases.
The food metabolome is defined as the part of the human metabolome directly derived from the digestion and biotransformation of foods and their constituents. With >25,000 compounds known in various foods, the food metabolome is extremely complex, with a composition varying widely according to the diet. By its very nature it represents a considerable and still largely unexploited source of novel dietary biomarkers that could be used to measure dietary exposures with a high level of detail and precision. Most dietary biomarkers currently have been identified on the basis of our knowledge of food compositions by using hypothesis-driven approaches. However, the rapid development of metabolomics resulting from the development of highly sensitive modern analytic instruments, the availability of metabolite databases, and progress in (bio)informatics has made agnostic approaches more attractive as shown by the recent identification of novel biomarkers of intakes for fruit, vegetables, beverages, meats, or complex diets. Moreover, examples also show how the scrutiny of the food metabolome can lead to the discovery of bioactive molecules and dietary factors associated with diseases. However, researchers still face hurdles, which slow progress and need to be resolved to bring this emerging field of research to maturity. These limits were discussed during the First International Workshop on the Food Metabolome held in Glasgow. Key recommendations made during the workshop included more coordination of efforts; development of new databases, software tools, and chemical libraries for the food metabolome; and shared repositories of metabolomic data. Once achieved, major progress can be expected toward a better understanding of the complex interactions between diet and human health.
The risk of adverse drug reactions (ADRs) rises with increasing age. In the field of ADRs, drug-nutrient interactions (DNIs) are a relatively unexplored area. More knowledge will contribute to the simple prevention of this type of ADR. As the prevalence of vitamin D deficiency in the elderly is high, the primary objective of this review is to evaluate the literature on the relationship between drug use and vitamin D status, focusing on medicines commonly used by the elderly. PubMed was searched for human epidemiological and clinical studies published until early 2013, investigating the relationship between vitamin D blood levels and use of drugs from one of the following groups: proton pump inhibitors (PPIs), biguanides, vitamin K antagonists, platelet aggregation inhibitors, thiazide diuretics, loop diuretics, beta-blocking agents, calcium channel blockers, angiotensin-converting enzyme (ACE) inhibitors, angiotensin-II antagonists, statins, benzodiazepines, and antidepressants. A total of 63 publications were identified. Thiazide diuretics, statins, and calcium channel blocking agents were the most frequently studied drug groups. Associations between thiazides and vitamin D were mixed (n = 22), statins had no or positive associations (n = 16) and calcium blockers were not associated or were negatively associated with vitamin D (n = 10). In conclusion, several knowledge gaps exist on the relationship between drug use and vitamin D blood levels. Available data are scarce (particularly for the aged), study characteristics are highly variable, and found associations may be confounded by, amongst other things, the underlying disease. Nonetheless, this review provides a basis for future research on ADRs that contribute to nutrient deficiencies.
The application of metabolomics in multi-centre studies is increasing. The aim of the present study was to assess the effects of geographical location on the metabolic profiles of individuals with the metabolic syndrome. Blood and urine samples were collected from 219 adults from seven European centres participating in the LIPGENE project (Diet, genomics and the metabolic syndrome: an integrated nutrition, agro-food, social and economic analysis). Nutrient intakes, BMI, waist:hip ratio, blood pressure, and plasma glucose, insulin and blood lipid levels were assessed. Plasma fatty acid levels and urine were assessed using a metabolomic technique. The separation of three European geographical groups (NW, northwest; NE, northeast; SW, southwest) was identified using partial least-squares discriminant analysis models for urine (R 2 X: 0·33, Q 2: 0·39) and plasma fatty acid (R 2 X: 0·32, Q 2: 0·60) data. The NW group was characterised by higher levels of urinary hippurate and N-methylnicotinate. The NE group was characterised by higher levels of urinary creatine and citrate and plasma EPA (20 : 5 n-3). The SW group was characterised by higher levels of urinary trimethylamine oxide and lower levels of plasma EPA. The indicators of metabolic health appeared to be consistent across the groups. The SW group had higher intakes of total fat and MUFA compared with both the NW and NE groups (P≤ 0·001). The NE group had higher intakes of fibre and n-3 and n-6 fatty acids compared with both the NW and SW groups (all P< 0·001). It is likely that differences in dietary intakes contributed to the separation of the three groups. Evaluation of geographical factors including diet should be considered in the interpretation of metabolomic data from multi-centre studies.
In order to assess mercury (Hg), selenium (Se) and arsenic (As) exposure in the Mediterranean area, total mercury (THg), monomethylmercury (MeHg), Se and As levels were measured in umbilical cord blood and breast milk from Italian (n=900), Slovenian (n=584), Croatian (n=234) and Greek (n=484) women. THg, MeHg, As, and Se levels were also determined in blood samples of the same mothers from Italy and Croatia. In addition, THg and MeHg were determined in the same women's hair from all the countries involved in this study and As and Se levels were determined in the mother's urine samples from Italy, Croatia and Greece. Besides recording the consumption of other food items, the frequencies of fish consumption were assessed by detailed food frequency questionnaires, since fish represents an important source of Hg, Se and As in humans. The highest levels of THg and As were found in cord blood (Med(THg)=5.8 ng/g; Med(As)=3.3 ng/g) and breast milk (Med(THg)=0.6 ng/g; Med(As)=0.8 ng/g) from Greek women, while the highest Se levels were found in cord blood (Med=113 ng/g) from Italy. Significant linear correlations were found between Hg, Se and As in blood, cord blood and breast milk. In addition, significant relations were found between the frequencies of total fish consumption and biomarkers of As, MeHg and Se exposure, with the strongest Spearman rank coefficients between frequencies of total fish consumption and THg levels in cord blood (rs=0.442, p<0.001) or THg levels in hair (rs=0.421, p<0.001), and between frequencies of total fish consumption and As levels in cord blood (rs=0.350, p<0.001). The differences in Hg and As exposure between countries were probably due to different amounts of fish consumption and the consumption of different species of fish of different origin, while the highest Se levels in women from Italy were probably the consequence of the more frequent consumption of different non specific food items. Moreover, fish consumption, the possible common source of As, Hg and Se intake, could explain the correlations between the elements determined in cord blood, mother's blood or breast milk.
Urine has long been a "favored" biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca.
Elucidation of the relationships between genotype, diet, and health requires accurate dietary assessment. In intervention and epidemiological studies, dietary assessment usually relies on questionnaires, which are susceptible to recall bias. An alternative approach is to quantify biomarkers of intake in biofluids, but few such markers have been validated so far. Here we describe the use of metabolomics for the discovery of nutritional biomarkers, using citrus fruits as a case study. Three study designs were compared. Urinary metabolomes were profiled for volunteers that had (a) consumed an acute dose of orange or grapefruit juice, (b) consumed orange juice regularly for one month, and (c) reported high or low consumption of citrus products for a large cohort study. Some signals were found to reflect citrus consumption in all three studies. Proline betaine and flavanone glucuronides were identified as known biomarkers, but various other biomarkers were revealed. Further, many signals that increased after citrus intake in the acute study were not sensitive enough to discriminate high and low citrus consumers in the cohort study. We propose that urine profiling of cohort subjects stratified by consumption is an effective strategy for discovery of sensitive biomarkers of consumption for a wide range of foods.
In spite of amazing progress in food supply and nutritional science, and a striking increase in life expectancy of approximately 2.5 months per year in many countries during the previous 150 years, modern nutritional research has a great potential of still contributing to improved health for future generations, granted that the revolutions in molecular and systems technologies are applied to nutritional questions. Descriptive and mechanistic studies using state of the art epidemiology, food intake registration, genomics with single nucleotide polymorphisms (SNPs) and epigenomics, transcriptomics, proteomics, metabolomics, advanced biostatistics, imaging, calorimetry, cell biology, challenge tests (meals, exercise, etc.), and integration of all data by systems biology, will provide insight on a much higher level than today in a field we may name molecular nutrition research. To take advantage of all the new technologies scientists should develop international collaboration and gather data in large open access databases like the suggested Nutritional Phenotype database (dbNP). This collaboration will promote standardization of procedures (SOP), and provide a possibility to use collected data in future research projects. The ultimate goals of future nutritional research are to understand the detailed mechanisms of action for how nutrients/foods interact with the body and thereby enhance health and treat diet-related diseases.
The Human Metabolome Database (HMDB) (www.hmdb.ca) is a resource dedicated to providing scientists with the most current and comprehensive coverage of the human metabolome. Since its first release in 2007, the HMDB has been used to facilitate research for nearly 1000 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 3.0) has been significantly expanded and enhanced over the 2009 release (version 2.0). In particular, the number of annotated metabolite entries has grown from 6500 to more than 40 000 (a 600% increase). This enormous expansion is a result of the inclusion of both 'detected' metabolites (those with measured concentrations or experimental confirmation of their existence) and 'expected' metabolites (those for which biochemical pathways are known or human intake/exposure is frequent but the compound has yet to be detected in the body). The latest release also has greatly increased the number of metabolites with biofluid or tissue concentration data, the number of compounds with reference spectra and the number of data fields per entry. In addition to this expansion in data quantity, new database visualization tools and new data content have been added or enhanced. These include better spectral viewing tools, more powerful chemical substructure searches, an improved chemical taxonomy and better, more interactive pathway maps. This article describes these enhancements to the HMDB, which was previously featured in the 2009 NAR Database Issue. (Note to referees, HMDB 3.0 will go live on 18 September 2012.).
Dietary measurement error creates serious challenges to reliably discovering new diet-disease associations in nutritional cohort studies. Such error causes substantial underestimation of relative risks and reduction of statistical power for detecting associations. On the basis of data from the Observing Protein and Energy Nutrition Study, we recommend the following approaches to deal with these problems. Regarding data analysis of cohort studies using food-frequency questionnaires, we recommend 1) using energy adjustment for relative risk estimation; 2) reporting estimates adjusted for measurement error along with the usual relative risk estimates, whenever possible (this requires data from a relevant, preferably internal, validation study in which participants report intakes using both the main instrument and a more detailed reference instrument such as a 24-hour recall or multiple-day food record); 3) performing statistical adjustment of relative risks, based on such validation data, if they exist, using univariate (only for energy-adjusted intakes such as densities or residuals) or multivariate regression calibration. We note that whereas unadjusted relative risk estimates are biased toward the null value, statistical significance tests of unadjusted relative risk estimates are approximately valid. Regarding study design, we recommend increasing the sample size to remedy loss of power; however, it is important to understand that this will often be an incomplete solution because the attenuated signal may be too small to distinguish from unmeasured confounding in the model relating disease to reported intake. Future work should be devoted to alleviating the problem of signal attenuation, possibly through the use of improved self-report instruments or by combining dietary biomarkers with self-report instruments.
Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca.
This study examined the association between self-reported diabetes, fish consumption and serum levels of organochlorines in a First Nation community. One quarter of the 101 participants reported diabetes. Serum PCBs, but not p,p'-DDE, were positively correlated to consumption frequency of total fish, walleye and pike, but not trout. Reported diabetes was positively associated to p,p'-DDE and some PCB congeners. Odds Ratios (OR) for reported diabetes for those in the upper 75th percentile for serum p,p'-DDE compared to the others were 3.5 (95% CI 1-13.8) and 6.1 (95% CI 1.4-27.3) (weight wet and lipid-standardized values, respectively) and for total sum of PCBs: 4.91 (95% CI 1.4-19.0) and 5.51 (95% CI 1.3-24.1). For participants who were in the upper 50th percentile for trout and white fish intake, reported diabetes was respectively 6 and 4 times lower compared to the others. These findings support the hypothesis that environmental exposure to elevated p,p'-DDE and PCBs is associated with increased risk of diabetes. Consumption of trout and white fish may be beneficial to reduce risk.
Mass spectrometry (MS) techniques, because of their sensitivity and selectivity, have become methods of choice to characterize the human metabolome and MS-based metabolomics is increasingly used to characterize the complex metabolic effects of nutrients or foods. However progress is still hampered by many unsolved problems and most notably the lack of well established and standardized methods or procedures, and the difficulties still met in the identification of the metabolites influenced by a given nutritional intervention. The purpose of this paper is to review the main obstacles limiting progress and to make recommendations to overcome them. Propositions are made to improve the mode of collection and preparation of biological samples, the coverage and quality of mass spectrometry analyses, the extraction and exploitation of the raw data, the identification of the metabolites and the biological interpretation of the results.
There is a need for objective biomarkers of dietary intake, because self-reporting is often subject to bias. We tested the validity of a biomarker for the fraction of dietary carbohydrate (CHO) from cane sugar and high fructose corn syrup (C(4) sugars) using natural (13)C abundance of plasma glucose. In a randomized, single-blinded, crossover design, 5 participants consumed 3 weight-maintaining diets for 7 d, with a 2-wk washout between diet periods. Diets differed in the fraction of total CHO energy from C(4) sugars (5, 16, or 32%). During each diet period, blood samples were drawn at hours 0800 and 1600 on d 1, 3, and 5 and at 0800, 1000, 1200, 1400, and 1600 on d 7. The delta(13)C abundance of plasma glucose was analyzed via GC- isotope ratio MS. Within each diet period, delta(13)C abundance of the 0800 fasting glucose did not change from baseline with increasing time during a diet period; however, there was a strong positive correlation (R(2) = 0.89) between delta(13)C abundance of the glucose concentration at 1000 on d 7 and the percent of breakfast CHO from C(4) sugars. Also, delta(13)C abundance of the combined plasma glucose samples on d 7 demonstrated a strong positive correlation (R(2) = 0.90) with the percent of total daily CHO from C(4) sugars. The natural delta(13)C abundance of postprandial plasma glucose relative to dietary C(4) CHO content was a valid biomarker for contributions of C(4) caloric sweeteners from the previous meal.
Plasma phospholipid fatty acids have been correlated with food intakes in populations with homogeneous dietary patterns. However, few data are available on populations with heterogeneous dietary patterns.
The objective was to investigate whether plasma phospholipid fatty acids are suitable biomarkers of dietary intakes across populations involved in a large European multicenter study.
A cross-sectional study design nested to the European Prospective Investigation into Cancer and Nutrition (EPIC) was conducted to determine plasma fatty acid profiles in >3,000 subjects from 16 centers, who had also completed 24-h dietary recalls and dietary questionnaires. Plasma fatty acids were assessed by capillary gas chromatography. Ecological and individual correlations were calculated between fatty acids and select food groups.
The most important determinant of plasma fatty acids was region, which suggests that the variations across regions are largely due to different food intakes. Strong ecological correlations were observed between fish intake and long-chain n-3 polyunsaturated fatty acids (r = 0.78, P < 0.01), olive oil and oleic acid (r = 0.73, P < 0.01), and margarine and elaidic acid (r = 0.76, P < 0.01). Individual correlations varied across the regions, particularly between olive oil and oleic acid and between alcohol and the saturation index, as an indicator of stearoyl CoA desaturase activity.
These findings indicate that specific plasma phospholipid fatty acids are suitable biomarkers of some food intakes in the EPIC Study. Moreover, these findings suggest complex interactions between alcohol intake and fatty acid metabolism, which warrants further attention in epidemiologic studies relating dietary fatty acids to alcohol-related cancers and other chronic diseases.
The measurement of food intake biomarkers (FIBs) in biofluids represents an objective tool for dietary assessment. FIBs of milk and cheese still need more investigation due to the absence of candidate markers. Thus, an acute intervention study has been performed to sensitively and specifically identify candidate FIBs. Eleven healthy male and female volunteers participated in the randomised, controlled crossover study that tested a single intake of milk and cheese as test products, and soy based drink as a control. Urine samples were collected at baseline and up to 24h at distinct time intervals (0-1, 1-2, 2-4, 4-6, 6-12 and 12-24h) and were analysed using an untargeted multi-platform approach (GC-MS and 1H-NMR). Lactose, galactose and galactonate were identified exclusively after milk intake while for other metabolites (allantoin, hippurate, galactitol and galactono-1,5-lactone) a significant increase has been observed. Urinary 3-phenyllactic acid was the only compound specifically reflecting cheese intake although alanine, proline and pyroglutamic acid were found at significantly higher levels after cheese consumption. In addition, several novel candidate markers for soy drink were identified such as pinitol and trigonelline. Together, these candidate FIBs of dairy intake could serve as a basis for future validation studies under free-living conditions.
Scope:
There is a dearth of studies demonstrating the use of dietary biomarkers for determination of food intake. The objective of this study was to develop calibration curves for use in quantifying citrus intakes in an independent cohort.
Methods and results:
Participants (n = 50) from the NutriTech food-intake study consumed standardized breakfasts for three consecutive days over three consecutive weeks. Orange juice intake decreased over the weeks. Urine samples were analyzed by NMR-spectroscopy and proline betaine was quantified and normalized to osmolality. Calibration curves were developed and used to predict citrus intake in an independent cohort; the Irish National Adult Nutrition Survey (NANS) (n = 565). Proline betaine displayed a dose-response relationship to orange juice intake in 24h and fasting samples (p<0.001). In a test set, predicted orange juice intakes displayed excellent agreement with true intake. There were significant associations between predicted intake measured in 24h and fasting samples and true intake(r = 0.710-0.919). Citrus intakes predicted for the NANS cohort demonstrated good agreement with self-reported intake and this agreement improved following normalization to osmolality.
Conclusion:
The developed calibration curves successfully predicted citrus intakes in an independent cohort. Expansion of this approach to other foods will be important for the development of objective intake measurements. This article is protected by copyright. All rights reserved.