In recent years, the use of metabolomics (the “–omics” science that measures the set of small molecules present in biospecimens) has allowed the identification of new and robust biomarkers of food or nutrient intake, which give a more objective measure of exposure than self-reported methods1. Accurate measurement of food consumption is crucial to understanding the link between diet and optimal health status or risk of development of diet-related diseases2.
The development of a platform for the analysis of food intake biomarkers that allows an actual assessment of European consumers’ diet within PREVENTOMICS has been carried out in three main steps:
- preparation of a list of candidate biomarkers of food intake and development of an analytical method to measure them in urine samples;
- development of a database able to link biomarkers of food intake and food products consumed by the European population;
- analysis of urine samples, to match the analytical data on the biomarkers of food intake with data from the dietary records associated with urine samples.
Figure 1: The excel-based database developed, able to associate food intake biomarkers with individual foodstuffs and food groups.
Biomarkers identification
Firstly, the identification of biomarkers of intake of food groups and specific foodstuffs has been carried out through systematic and comprehensive literature searches. To reduce the list of identified biomarkers to a reasonable number, several criteria were taken into consideration.
First of all, food intake biomarkers had to be identified in humans and had to be specific for a foodstuff or a food group (specificity). Then, they had to be urinary biomarkers (owing to the reliability of this biological fluid for the assessment of biomarkers of food intake), identified through a LC-MS technique, and feasible to be analysed (analytical feasibility, i.e. present in urine at detectable concentrations). In this way, the biomarkers of interest or feasible to be measured and, thus, suitable to be included in the final list of candidate biomarkers of food intake were decided. Once the list was set, a search of the reference compounds for the selected biomarkers was carried out and a targeted LC-MS method for their analysis was developed.
Database development to link biomarkers with food products
In parallel, a comprehensive excel-based database able to associate food intake biomarkers with individual foodstuffs and food groups has been created. Briefly, it links the entries (food items and their respective food categories) of a validated nutritional database, which is the Food Composition Database for Epidemiological Studies in Italy (BDA)3, to a database containing the main food categories for food intake biomarkers and their respective biomarkers specifically created for this purpose (Figure 1).
Afterwards, dietary information collected in food diaries of the three days immediately before urine collection during the PREVENTOMICS trials have been decoded and added to the newly developed database. In practice, each food consumed by volunteers has been linked to a food item in the nutritional database and then to its respective biomarker(s) of food intake.
Matching biomarkers’ data from food intake with dietary records
Lastly, they have been analysed and quantified in urine samples with the newly developed LC-MS method. Following this, the levels of biomarkers in urine have been linked almost automatically to the database and compared and correlated with the data from the food diaries. Actually, comparing the information collected through self-reported methods with that provided by targeted metabolomics represents the best strategy to validate the developed methodological approach. This will guarantee that the outcomes derived from the metabolomics analysis of food intake biomarkers will represent a real subject’s dietary pattern.
Thanks to these developments, a simple urine sample could become an amazingly detailed descriptor of dietary intake and of diet quality, making compliance to a dietary intervention and detection of potential deficiencies or of dangerous overconsumption easy to unravel.
References
- Garcia-Aloy M, Rabassa M, Casas-Agustench P, Hidalgo-Liberona N, Llorach R, Andres-Lacueva C. Novel strategies for improving dietary exposure assessment: Multiple-data fusion is a more accurate measure than the traditional single-biomarker approach. Trends Food Sci. Technol. 2017; 69: 220–229
- Brennan L. Moving toward Objective Biomarkers of Dietary Intake. J. Nutr. 2018; 148 (6): 821–822
- Banca Dati di Composizione degli Alimenti per Studi Epidemiologici in Italia (BDA) – Food Composition Database for Epidemiological Studies in Italy (BDA), at <http://www.bda-ieo.it>
About the authors
Claudia Favari
Post-doctoral research fellow at the Human Nutrition Unit, Department of Food and Drug, University of Parma. PhD in Food Science under the supervision of Prof. Del Rio, Claudia’s main research interests are (poly)phenols bioavailability and metabolism and associated inter-individual variability, objective dietary intake assessment through food intake biomarkers and personalized nutrition. For her research purposes, she adopts both targeted and untargeted metabolomics approaches.
Daniele Del Rio
Daniele is the Head of the School of Advanced Studies on Food and Nutrition at the University of Parma, in Italy. He also acts as Scientific Director of the Need For Nutrition Education/Innovation Programme Global Centre for Nutrition & Health, in Cambridge, UK. He serves as Editor in Chief of the International Journal of Food Sciences and Nutrition (Taylor & Francis). He is a proud Commendatore (Knight Commander) of the Order of Merit of the Italian Republic, and he is proudly growing a team of brilliant scientists.
