Design and implementation of a cross-sectional nutritional phenotyping study in healthy US adults

Abstract

Background: Metabolic imbalance is a key determinant of risk of chronic diseases. Metabolic health cannot be assessed solely by body mass calculations or by static, fasted state biochemical readouts. Although previous studies have described temporal responses to dietary challenges, these studies fail to assess the environmental factors associated with certain metabolic phenotypes and therefore, provide little scientific rationale for potentially effective intervention strategies. Methods/design: In this phenotyping study of healthy US adults, we are evaluating lifestyle, biological and environmental factors in addition to metabolic parameters to determine the factors associated with variations in metabolic health. A series of practical fitness, dietary, and emotional challenges are introduced and temporal responses in various areas of specialization, including immunology, metabolomics, and endocrinology, are monitored. We expect that this study will identify key factors related to healthy or unhealthy metabolic phenotypes (metabotypes) that may be modifiable targets for the prevention of chronic diseases in an individual. Discussion: This study will provide novel insights into metabolic variability among healthy adults in balanced strata defined by sex, age and body mass index. Usual dietary intake and physical activity will be evaluated across these strata to determine how diet is associated with health status defined using many indicators including immune function, metabolism, body composition, physiology, response to exercise andmeal challenges and neuroendocrine assessment. A principal study goal is to identify dietary and other personal factors that will differentiate different levels of "health" among study participants. Trial registration: ClinicalTrials.gov NCT02367287.

Nutrient Estimation from 24-Hour Food Recalls Using Machine Learning and Database Mapping: A Case Study with Lactose

“…The objective of this study was to develop computer-assisted methods to obtain values for NCC-exclusive nutrients for food items reported in an ASA24 output for two scenarios: (1) When researchers have a license to NDSR but not NCC, and (2) when researchers have a license to NCC database files. We use lactose as a case study and estimate values from foods recorded from ASA24 recalls by a California cohort of healthy adults [25]. To address the first scenario, we trained and tested nine machine learning models on the ability to predict the amount of lactose in a given ASA24 food, Nutrients 2019, 11,3045 4 of 27 comparing the predicted lactose values to the lactose obtained by manually looking up ASA24 foods into NDSR.…”

“…The Automated Self-Administered 24-hour recall (ASA24®) system was used to collect dietary recalls from participants in the Nutritional Phenotyping Study, a cross-sectional observational study conducted by the United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center located in Davis, California, USA (clinicaltrials.gov: NCT02367287) [25]. Foods used for the training and test data sets were retrieved from the first n = 214 participants' recalls.…”

SNPs in Apolipoproteins Contribute to Sex-Dependent Differences in Blood Lipids Before and After A Dietary Challenge in Healthy U.S. Adults

“…Three hundred ninety-three healthy U.S. adults aged 18-66 years old with BMI ranges of 18.5 to 45.0 kg/m 2 were enrolled for a cross-sectional Nutritional Phenotyping Study (ClinicalTrials.gov, ID: NCT02367287). It should be acknowledged that the original sampling plan had an upper limit of BMI at 39.9 kg/m 2 [21], but the study was modified to increase the upper BMI to 45 kg/m 2 . Pregnant or lactating women were excluded from the study.…”

“…Other exclusion criteria included a known allergy to egg, recent surgeries or hospitalization (minor surgeries for the last 4 weeks or major surgeries/hospitalization for last 4 months), antibiotic treatments for last 4 weeks. Individuals who take daily medication for a diagnosed chronic disease at the time of the study were also excluded [21]. Details of recruitment and demographic characteristics of the overall population are contained within another report on this study under consideration for publication in Stress: International Journal on the Biology of Stress (personal communication, Dr. Kevin Laugero, USDA/ARS/WHNRC, Davis CA).…”

“…Multiple blood draws were then conducted postprandially at 0.5-, 3-and 6-h [21]. Heights (m) and weights (kg) were recorded in Visit 1 and Visit 2.…”