Background: Changes in dietary fat composition could lower the risk of developing metabolic syndrome. Adipose tissue is an interesting tissue in this

Biomarkers of food intake (BFIs) are a promising tool for limiting misclassification in nutrition research where more subjective dietary assessment instruments are used. They may also be used to assess compliance to dietary guidelines or to a dietary intervention. Biomarkers therefore hold promise for direct and objective measurement of food intake. However, the number of comprehensively validated biomarkers of food intake is limited to just a few. Many new candidate biomarkers emerge from metabolic profiling studies and from advances in food chemistry. Furthermore, candidate food intake biomarkers may also be identified based on extensive literature reviews such as described in the guidelines for Biomarker of Food Intake Reviews (BFIRev). To systematically and critically assess the validity of candidate biomarkers of food intake, it is necessary to outline and streamline an optimal and reproducible validation process. A consensus-based procedure was used to provide and evaluate a set of the most important criteria for systematic validation of BFIs. As a result, a validation procedure was developed including eight criteria, plausibility, dose-response, time-response, robustness, reliability, stability, analytical performance, and inter-laboratory reproducibility. The validation has a dual purpose: (1) to estimate the current level of validation of candidate biomarkers of food intake based on an objective and systematic approach and (2) to pinpoint which additional studies are needed to provide full validation of each candidate biomarker of food intake. This position paper on biomarker of food intake validation outlines the second step of the BFIRev procedure but may also be used as such for validation of new candidate biomarkers identified, e.g., in food metabolomic studies.

Background: Peripheral blood mononuclear cells (PBMCs) are the only readily available cells in healthy humans. Various studies showed disease-characteristic gene expression patterns in PBMCs. However, little is known of nutritional effects on PBMC gene expression patterns. Fatty acids are nutrients that regulate gene expression by activating the nuclear receptor peroxisome proliferator–activated receptor α (PPARα). PBMCs express PPARα, making these cells interesting to study FA-dependent gene expression. Objective: The aim of this study was to elucidate whether PBMC gene expression profiles also reflect nutrition-related metabolic changes. Furthermore, we focused on the specific role of PPARα in regulation of PBMC gene expression during fasting, when plasma free fatty acids are elevated. Design: Four healthy male volunteers fasted for 48 h. PBMC RNA was hybridized on Affymetrix whole genome microarrays. To elucidate the role of PPARα, PBMCs of 9 blood donors were incubated with the specific PPARα ligand Wy14643. Results: After 24 and 48 h of fasting, 1200 and 1386 genes were changed >1.4-fold, respectively. Many of those genes were involved in fatty acid β-oxidation and are known PPARα target genes. Incubation of PBMCs with Wy14643 resulted in up-regulation of genes that were also up-regulated during fasting. Conclusions: We conclude that PBMC gene expression profiles reflect nutrition-related metabolic changes such as fasting and that part of the fasting-induced changes are likely regulated by PPARα.

Biomarkers are an efficient means to examine intakes or exposures and their biological effects and to assess system susceptibility. Aided by novel profiling technologies, the biomarker research field is undergoing rapid development and new putative biomarkers are continuously emerging in the scientific literature. However, the existing concepts for classification of biomarkers in the dietary and health area may be ambiguous, leading to uncertainty about their application. In order to better understand the potential of biomarkers and to communicate their use and application, it is imperative to have a solid scheme for biomarker classification that will provide a well-defined ontology for the field. In this manuscript, we provide an improved scheme for biomarker classification based on their intended use rather than the technology or outcomes (six subclasses are suggested: food compound intake biomarkers (FCIBs), food or food component intake biomarkers (FIBs), dietary pattern biomarkers (DPBs), food compound status biomarkers (FCSBs), effect biomarkers, physiological or health state biomarkers). The application of this scheme is described in detail for the dietary and health area and is compared with previous biomarker classification for this field of research.

Identification of new biomarkers of food and nutrient intake has developed fast over the past two decades and could potentially provide important new tools for compliance monitoring and dietary intake assessment in nutrition and health science. In recent years, metabolomics has played an important role in identifying a large number of putative biomarkers of food intake (BFIs). However, the large body of scientific literature on potential BFIs outside the metabolomics area should also be taken into account. In particular, we believe that extensive literature reviews should be conducted and that the quality of all suggested biomarkers should be systematically evaluated. In order to cover the literature on BFIs in the most appropriate and consistent manner, there is a need for appropriate guidelines on this topic. These guidelines should build upon guidelines in related areas of science while targeting the special needs of biomarker methodology. This document provides a guideline for conducting an extensive literature search on BFIs, which will provide the basis to systematically validate BFIs. This procedure will help to prioritize future work on the identification of new potential biomarkers and on validating these as well as other biomarker candidates, thereby providing better tools for future studies in nutrition and health.