Nutrition for Precision Health, Powered by the All of Us

Summary

The goal of this Nutrition for Precision Health (NPH) powered by All of Us research study is to develop Artificial Intelligence/Machine Learning (AI/ML) algorithms that predict individual responses to diet patterns using rich multimodal data streams collected across multiple domains (e.g., behavior, social, environmental, clinical and molecular biomarkers). NPH includes a large phenotyping cohort (Module 1, N=8000) and two separate follow-up groups drawn from a subset of Module 1participants. One group (Module 2, N=1200) receives three distinct diets in a 14-day crossover sequence, with at least a 14-day washout period between diets, while living in their own homes. A second group (Module 3, N=150) receives the same three diets under full-time supervision in a residential research setting. We will train and test AI/ML models to predict 0-4 hour postprandial response curves for glucose, insulin, triglycerides, and GLP-1, to the standardized diet-specific meal test (DSMT) collected after each of the three different diets delivered in Module 2. Each diet functions as a controlled stimulus to reveal biological features (such as individual variables, patterns, or clusters of measurements) that best predict a person's response.

The Module 2 DSMT response curves are the primary outcomes (dependent variables) for AI/ML algorithms that predict individual responses to diet patterns.

As a secondary objective, NPH will evaluate the validity and acceptability of technology-based dietary assessment tools. The Automated Self-Administered 24-hour recall (ASA24), Automatic Ingestion Monitor-2 (AIM-2), and the mobile food record (mFR) will be evaluated in Modules 2 and 3, and the ASA24 food record and the image-assisted ASA24 recall will be evaluated only in Module 3. Total energy intake, macronutrient and dietary fiber intake data are the main outcomes for validity testing compared against measures of actual intake. Acceptability will be determined from feedback surveys.

Conditions

• Nutrition
• Health
• Dietary Habits

Interventions

OTHER

Diet A

This diet has high amounts of fruits/vegetables, whole grains, and beans, moderate amounts of dairy, meat/poultry/eggs, nuts/seeds, and olive oil, and very low amounts of sugar sweetened drinks and desserts.

OTHER

Diet B

This diet has high amounts of refined grains, meat/poultry/egg, sugar sweetened drinks, snacks, desserts, and processed foods. It has a moderate amount of dairy and low amounts of fruits/vegetables, whole grains, and fish.

OTHER

Diet C

This diet has moderate-high amounts of vegetables, meat/poultry/egg, nuts/seeds, dairy and fats/oils, low amounts of fruits, and very low amounts of grains and sugars.

Sponsors & Collaborators

• National Institutes of Health (NIH)

  collaborator NIH

• University of North Carolina, Chapel Hill

  collaborator OTHER

• Northwestern University

  collaborator OTHER

• Illinois Institute of Technology

  collaborator OTHER

• University of Chicago

  collaborator OTHER

• Pennington Biomedical Research Center

  collaborator OTHER

• Louisiana State University Health Sciences Center in New Orleans

  collaborator OTHER

• University of California, Davis

  collaborator OTHER

• University of California, Los Angeles

  collaborator OTHER

• Cedars-Sinai Medical Center

  collaborator OTHER

• University of Alabama at Birmingham

  collaborator OTHER

• Tufts University

  collaborator OTHER

• Massachusetts General Hospital

  collaborator OTHER

• Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)

  collaborator NIH

• National Center for Advancing Translational Sciences (NCATS)

  collaborator NIH

• National Cancer Institute (NCI)

  collaborator NIH

• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

  collaborator NIH

• City University of New York, School of Public Health

  collaborator OTHER

• Mayo Clinic

  collaborator OTHER

• University of California, San Diego

  collaborator OTHER

• University of Hawaii

  collaborator OTHER

• Vanderbilt University Medical Center

  collaborator OTHER

• National Heart, Lung, and Blood Institute (NHLBI)

  collaborator NIH

• National Center for Complementary and Integrative Health (NCCIH)

  collaborator NIH

• National Institute of Drug Abuse

  collaborator FED

• Public Health Informatics Computational and Operations Research

  collaborator UNKNOWN

• University of Southern California

  collaborator OTHER

• Cornell University

  collaborator OTHER

• University of Alabama, Tuscaloosa

  collaborator OTHER

• North Carolina State University

  collaborator OTHER

• University of North Carolina, Charlotte

  collaborator OTHER

• Duke University

  collaborator OTHER

• Stevens Institute of Technology

  collaborator OTHER

• Purdue University

  collaborator OTHER

• United States Military Academy West Point

  collaborator FED

• USDA, Western Human Nutrition Research Center

  collaborator FED

• North Carolina Central University

  collaborator OTHER

• Wake Forest University Health Sciences

  collaborator OTHER

• Boston University

  collaborator OTHER

• Children's Hospital of Richmond

  collaborator UNKNOWN

• Virginia Commonwealth University

  collaborator OTHER

• Verily Life Sciences LLC

  collaborator INDUSTRY

• Indiana University

  collaborator OTHER

• Fred Hutchinson Cancer Center

  collaborator OTHER

• Columbia University

  collaborator OTHER

• University of Pennsylvania

  collaborator OTHER

• RTI International

  lead OTHER

Principal Investigators

• Marie G Gantz, PhD · RTI International

Study Design

Allocation

NON_RANDOMIZED

Purpose

OTHER

Masking

SINGLE

Model

CROSSOVER

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2023-04-14

Primary Completion

2026-12-31

Completion

2027-01-31

Countries

• United States

Study Locations