Foodomics Application: Analysis of Dietary Components of the DASH Diet Pre and Post Consumption

Background/Objective While the benefit of improving the diet through the intake of different food groups such as fruits and vegetables is well established, many nutrient specific intervention studies have failed to demonstrate the effectiveness of specific foods in preventing or altering disease progression. This may be due to exposome and microbiome variations between individuals, and the lack of dependable biomarkers relating non‐nutritive dietary compounds to health benefits. Additionally, robust analysis techniques have not been implemented to identify the vast multitude of compounds in foods and to elucidate their health‐related fate. Foodomics attempts to fill these research challenges through the analysis of individual foods and their resulting metabolic signatures following intake. We hypothesized that individual foods will produce unique identifiable molecular compounds in biofluids, which will provide signatures of intake and lead to the identification of bioactive compounds that may impact health. Methods In a clinical cross‐over feeding study using the Dietary Approaches to Stop Hypertension (DASH) diet, participants were randomized to consume a 7‐day rotational controlled diet in which the primary source of protein was either pork or white meat (chicken and fish) for six weeks, followed by a washout for four weeks, and then consumption of the alternate meat source diet for six weeks. To interrogate diet samples for foodomics analysis, lypholization and methanol extraction were conducted on 14 composite daily diets and 12 selected individual foods. Untargeted metabolomic analysis was conducted on the extracted food samples and archived urine samples of 10 study participants, pre‐ and post‐diet intervention, using liquid chromatography mass spectrometry (LC/MS) with a SB‐AQ column in positive ion mode. Results A total of 10948 unique metabolites were detected in the individual foods, ranging from 833 compounds detected in tilapia and 1998 compounds detected in cucumbers, with over 4000 compounds detected in the composite diets. Each food produced unique metabolites; for example, caffeic acid, a cardioprotectant, was found only in blueberries, and specific acylcarnitines were protein source dependent. Metabolite signatures of each individual food and the composite diets were also detectable in the urine. Comparison of pre‐ and post‐diet urine metabolites revealed changes in the abundance of 74 and 183 metabolites from the white meat and pork diets, respectively, with 13 metabolites that correlated with observed reductions in blood pressure in the study participants. Conclusion This novel foodomics analysis demonstrated that LC/MS analysis of individual foods and composite diets produced unique metabolite signatures detectable in urine. Those metabolites may lead to biomarkers that not only indicate consumption, but may also help elucidate the role of individual foods in the exposome and health outcomes, including changes in blood pressure. Support or Funding Information Funding provided by discretionary funding from the Krebs & Reisdorph Labs, NIH/NCATS Colorado CTSA Grant UL1 TR001082, & Pork Checkoff Funds