ISNN

Nutrition is at the epicenter of human health and disease. However, our current “one size fits all” approach to clinical nutrition is failing a large segment of the population. Individual factors including genetics, metabolism, physiology, microbiome, behavior, the built and contextual environment all underlie the inherent variability in response to diets. Exciting new research shows that machine learning algorithms can integrate this complex information and predict how someone responds to a given diet. If validated, this innovative approach will provide a radical change in the delivery of personalized nutrition prescriptions to promote health and treat chronic diseases in all people. The goal of the Nutrition for Precision Health (NPH) research study is to study a large and diverse group of American adults and to use machine learning and artificial intelligence models to understand the individual responses to foods and dietary patterns. NPH is the first ancillary study of the All of Us Research Program. The consortium was formed January 2022 and plans to enroll approximately 10,000 participants into the NPH study. Using a discovery science approach study participants will enroll in either one or two modules; Module 1: a cross-sectional study to characterize daily dietary intake and accompanying nutritional status, biological and other measures over 10 days, as well as physiological responses following a liquid mixed meal tolerance test; Module 2 a crossover randomized study of three 14-day dietary interventions implemented in a community dwelling setting; Module 3 a crossover randomized study of the same three dietary interventions as in Module 2, implemented in a domiciled setting. Participants in these three Modules will contribute simultaneous, multimodal measurements (e.g., dietary assessment, anthropometric, physiological, behavioral, social, and contextual measurements) carefully selected for their relevance to understanding responses to foods, including nutrients, food components, and dietary patterns. The rich set of data and biospecimens will be used to inform paradigm shifting approaches that enable large-scale delivery of personalized dietary prescriptions to promote general health, delay cardiometabolic diseases, and importantly address health disparities.

Nutrition for Precision Health (NPH) is the first ancillary study of the All of Us Research Program. We plan to enroll approximately 10,000 participants into the NPH study. NPH is discovery science research involving modular components, including:

■ Module 1 is a cross-sectional study of approximately 10,000 individuals enrolled in the All of Us Research Program to characterize their daily dietary intake and accompanying nutritional status, biological and other measures measured over approximately 8 to 14 days, as well as physiological responses following a liquid mixed meal tolerance test.

■ Module 2 is a crossover design randomized study of three dietary interventions implemented in a community dwelling setting. This module will enroll approximately 1,500 individuals who have completed Module 1. Participants will undergo three controlled dietary interventions provided for 14-days each, in a sequence determined by cohort randomization, and separated by washout periods. Physiological responses following a diet-specific mixed meal tolerance test will be measured.

■ Module 3 is a crossover design randomized study of the same three dietary interventions as in Module 2, implemented in a domiciled setting. This module will enroll approximately 500 individuals who have completed Module 1. Participation in Modules 2 and 3 will be mutually exclusive. Module 3 participants will be studied in residence and will undergo the three 14-day dietary interventions (as in Module 2), in a sequence determined by cohort randomization, with washout periods of at least 14 days. Physiological responses following a liquid mixed meal tolerance test and a diet-specific mixed meal tolerance test (on separate days) will be measured.

Within these modules, NPH will evaluate the use of novel dietary assessment measures to improve dietary assessments and to prescribe assessments to people in future research with increased precision.