Location: Food Components and Health Laboratory
Project Number: 8040-10700-007-000-D
Project Type: In-House Appropriated
Start Date: Apr 30, 2024
End Date: Apr 29, 2029
Objective:
Objective 1: Elucidate the impact of differential bioavailability of dietary bioactive components, such as isothiocyanates and polyphenols, in predicting inter-individual response to dietary intake.
Sub-objective 1.A: Determine the role of differential bioavailability of berry flavonoids (proportion absorbed via the small intestine vs. proportion reaching the colon) in influencing glycemic response and gut microbiota metabolism.
Sub-objective 1.B: Determine the role of differential bioavailability (proportion absorbed via the small intestine vs. proportion reaching the colon) of phenolic compounds from a mix of polyphenol-rich foods in influencing glycemic response and gut microbiota metabolism.
Sub-objective 1.C: Determine the importance of isothiocyanate bioavailability on influencing xenobiotic metabolism via glutathione-S-transferase concentration and activity.
Objective 2: Elucidate the impact of differential digestibility of dietary macronutrients, such as fat and carbohydrate, in predicting inter-individual response to dietary intake.
Sub-objective 2.A: Determine the role of differential digestibility of fat from tree nuts in determining blood lipid response and gut microbiota metabolism.
Sub-objective 2.B: Determine the role of differential digestibility of carbohydrate from pulses (chickpeas and lentils) in determining blood lipid response and gut microbiota metabolism.
Approach:
The nutrition community increasingly recognizes that a single set of dietary guidelines does not provide optimal health benefits to all individuals. Factors such as genotype, phenotype, efficiency in digestion and nutrient absorption, rates of metabolic pathways, gut microbiota, and other characteristics affect an individual’s response to diet. However, data to create predictive algorithms to prescribe targeted dietary recommendations are not yet sufficient. By combining data from our previous human feeding studies with new analyses utilizing novel analytical approaches, we will strengthen the evidence for predicting how certain individual characteristics may influence response to dietary interventions.
