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ARS Home » Pacific West Area » Davis, California » Western Human Nutrition Research Center » Immunity and Disease Prevention Research » Research » Research Project #446883

Research Project: Identification of Molecular Traits of Specific Pulses that Maximize Human Health

Location: Immunity and Disease Prevention Research

Project Number: 2032-10700-002-021-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Sep 23, 2024
End Date: Dec 22, 2025

Objective:
The long-term objective of the cooperative agreement is to determine how pulse consumption improves human health at the molecular level to enable future precision nutrition and precision agriculture. Specific objectives of the current agreement are to (1) quantify consumption of specific pulses (lentils, chickpeas, pinto beans, etc.) by U.S. adults, (2) quantify the contribution of specific pulses to specific molecules (glycans, metabolites, etc.) in the diet of U.S. adults, (3) examine associations between pulse-specific molecules and markers of metabolic dysregulation; including metabolic syndrome, insulin resistance, and chronic inflammation, and (4) use a smaller cohort, which has assessed the same clinical markers in addition to high-resolution gut microbiome data, as a validation cohort, for exploratory analysis of mediation by gut microbes.

Approach:
ARS and UC Davis scientists will map multi-omic data from emerging databases in analytical food chemistry (Davis Food Glycopedia 2.0, Periodic Table of Food Initiative) to observational cohorts (NHANES, USDA Nutritional Phenotyping Study) to determine the unique contribution of pulses to the molecular composition of the U.S. diet and the association of these molecules to health outcomes. ASA24 dietary recall data from the two cohorts will be ingredientized (disaggregated) and the ingredients will then be mapped to the food composition database (DFG2 or PTFI). Health outcomes will be derived from the respective cohort's anthropometric and plasma biomarkers. We will then use machine learning (ML) models to assess the relationship between molecular diet features and clinical outcomes.