Clinical trial NCT02367287: USDA Western Human Nutrition Research Center (WHNRC) Cross-Sectional Nutritional Phenotyping Study
Official title: Assessing the Impact of Diet on Inflammation in Healthy and Obese Adults in a Cross-Sectional Phenotyping Study
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Obesity
Inflammation
Keywords: Diet
Phenotype
Immunology
Microbiota
Metabolomics
Physical activity
Neuroendocrine system
Nutritional Physiological Phenomena
Lead sponsor: USDA, Western Human Nutrition Research Center
Sponsor class: FED
First posted: 2015-02-20
Enrollment: 393
Sex: ALL
Minimum age (years): 18
Maximum age (years): 65
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: OTHER
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Healthy people in the general population

Brief summary: Although the diet of the US population meets or exceeds recommended intake levels of most essential nutrients, the quality of the diet consumed by many Americans is sub-optimal due to excessive intake of added sugars, solid fats, refined grains, and sodium. The foundations and outcomes of healthy vs. unhealthy eating habits and activity levels are complex and involve interactions between the environment and innate physiologic/genetic background. For instance, emerging research implicates chronic and acute stress responses and perturbations in the Hypothalamic-Pituitary-Adrenal axis in triggering obesity-promoting metabolic changes and poor food choices. In addition, the development of many chronic diseases, including cardiovascular disease, diabetes, cancer, asthma and autoimmune disease, results from an overactive immune response to host tissue or environmental antigens (e.g. inhaled allergens). A greater understanding is needed of the distribution of key environment-physiology interactions that drive overconsumption, create positive energy balance, and put health at risk.

Researchers from the United States Department of Agriculture (USDA) Western Human Nutrition Research Center are conducting a cross-sectional "metabolic phenotyping" study of healthy people in the general population. Observational measurements include the interactions of habitual diet with the metabolic response to food intake, production of key hormones, the conversion of food into energy: the metabolism of fats, proteins, and carbohydrates, characteristics of the immune system, stress response, gut microbiota (bacteria in the intestinal tract), and cardiovascular health. Most outcomes will be measured in response to a mixed macronutrient/high fat challenge meal.

Detailed description: Many inflammatory responses can be modulated by specific dietary components. For example, in cardiovascular disease, macrophages and T-cells react with oxidized LDL (an endogenous modified antigen) to produce arterial plaque and subsequent blockage of coronary arteries. High intake of saturated fats (or simple sugars that drive synthesis of saturated fatty acids) may promote this inflammation by affecting macrophages and T-cells. Conversely, increased intake of omega-3 fatty acids may decrease inflammation by suppression of macrophage and T-cell pro-inflammatory activity. Long-term sub-clinical inflammation caused by intestinal bacteria has been linked to the development of Irritable Bowel Disease and related disorders. Low intake of fruits, vegetables, or whole grains or high intake of saturated fats may promote sub-clinical gut inflammation by promoting dysbiosis of the gut microbiota. Allergic asthma develops in predisposed individuals as a result of an overactive allergic-type immune response to inhaled environmental allergens. Dietary factors such as vitamin D and omega-3 fatty acids may diminish pro-inflammatory responses to environmental allergens by promoting the development of T-regulatory cells and other anti-inflammatory factors.

Individual variability in chronic disease risk is well recognized. For example, why does excess adiposity lead to disease in some individuals and not others? The nature of the fat tissue rather than the abundance, may impact cross-talk with other metabolically-relevant tissues and affect disease risk. It is important to characterize healthy vs. unhealthy phenotypes across various tissues and to understand how micro- and macro-nutrients interact with molecular and metabolic pathways to support a healthy body weight. This study brings together scientists with expertise in nutritional sciences, immunology, analytical chemistry, physiology, neuroendocrinology, and behavior to understand how diet impacts metabolism and disease risk through the interplay and coordination of signals and metabolites arising from multiple organ systems.

The overall objective is to characterize the phenotypic profile of participants according to their immunologic, physiologic, neuroendocrine, and metabolic responses to a dietary challenge and a physical fitness challenge by addressing the specific aims listed below. The cross-sectional study is organized into two study visits (Visit 1 and Visit 2) separated by approximately two weeks of at-home specimen and data collection.

Specific Aim 1: To determine if diet quality is independently associated with systemic immune activation, inflammation, or oxidative stress differentiated by:

1. pro-inflammatory T-helper cells (Th1, Th2, and Th17 cells) and related cytokines
2. anti-inflammatory T-regulatory cells and related cytokines
3. dysbiosis of the gut microbiota and markers of gut inflammation (e.g. neopterin and myeloperoxidase)

   a. and to evaluate the association between dysbiosis of the gut microbiota, gut inflammation, and systemic immune activation
4. plasma metabolomic response to a mixed macronutrient challenge meal (includes diet quality and physical activity as independent variables)
5. endothelial (dys)function and vascular reactivity

Specific Aim 2: To determine if a high fat/sugar challenge meal induces differential effects over time (0-6h postprandial) according to habitual diet characteristics, physical activity levels, stress levels, age, sex, or BMI on:

1. postprandial monocyte activation
2. plasma lipid metabolomic responses including non-esterified fatty acids, phospholipids, triacylglycerols, red blood cell fatty acids, endocannabinoids, bile acids, eicosanoids and related oxylipins, ceramides, sphingoid bases, and acylcarnitines
3. plasma amino acid metabolomics
4. glucose metabolism and metabolic flexibility (i.e. the ability to switch from glucose to lipid oxidation as energy sources)
5. changes in endocrinology and self-report of hunger and satiety
6. postprandial free cortisol

Specific Aim 3: To determine the mechanisms of:

1. postprandial monocyte activation
2. suppression of challenge-meal induced monocyte activation by docosahexaenoic acid (DHA) (in an ex vivo experiment using a subset of samples)

Specific Aim 4: To evaluate the associations between eating behavior, physical activity, and/or anthropometry and the outcomes:

1. endocrinology of hunger and satiety
2. plasma metabolomic responses
3. vulnerability and resistance to stress
4. endothelial (dys)function and vascular reactivity
5. prediction of insulin sensitivity

Specific Aim 5: To determine how genetic variants affect nutrient metabolism, cardiovascular physiology, and immune function and improve understanding of how dietary factors affect these metabolic, cardiovascular and immune phenotypes.

Eligibility criteria: Inclusion Criteria:

* 18-65 y
* Male or female
* Body Mass Index 18.5-45.0 kg/m2 (Normal to obese)

Exclusion Criteria:

* Pregnant or lactating women
* Known allergy to egg-white protein
* Systolic blood pressure greater than 140 mm Hg or diastolic blood pressure greater than 90 mm Hg measured on three separate occasions
* Diagnosed active chronic diseases for which the individual is currently taking daily medication, including but not limited to:

  * Diabetes mellitus
  * Cardiovascular disease
  * Cancer
  * Gastrointestinal disorders
  * Kidney disease
  * Liver disease
  * Bleeding disorders
  * Asthma
  * Autoimmune disorders
  * Hypertension
  * Osteoporosis
* Recent minor surgery (within 4 wk) or major surgery (within 16 wk)
* Recent antibiotic therapy (within 4 wk)
* Recent hospitalization (within 4 wk)
* Use of prescription medications at the time of the study that directly affect endpoints of interest (e.g. hyperlipidemia, glycemic control, steroids, statins, anti-inflammatory agents, and over-the-counter weight loss aids)

Primary outcomes:
measure: Baseline level and change in systemic immune activation following challenge meal
timeFrame: 0, 0.5, 3, and 6 hours postprandial
measure: Baseline level and change in plasma metabolome
timeFrame: 0, 0.5, 3, and 6 hours postprandial
Secondary outcomes:
measure: Baseline level and change in glucose metabolism
timeFrame: 0, 0.5, 3, and 6 hours postprandial
measure: Baseline level and change in appetitive hormones
timeFrame: 0, 0.5, 3, and 6 hours postprandial
measure: Baseline level and change in mitogen activated protein (MAP) kinase activity
timeFrame: 0, 0.5, 3 and 6 hours postprandial
measure: Baseline level and change in dietary-responsive, circulating microRNA
timeFrame: 0, 0.5, 3, and 6 hours postprandial
measure: Baseline level and change in RNA transcriptome
timeFrame: 0, 3, and 6 hours postprandial
measure: Genome Wide Association Study (GWAS)
timeFrame: 0 hours (fasting)
measure: General health
timeFrame: 0 hours (Fasting)
measure: Anthropometrics
timeFrame: single time point
measure: Vital signs
timeFrame: single time point
measure: Body composition
timeFrame: single time point
measure: Resting and change in metabolism
timeFrame: 0, 0.5, 3, and 6 hours postprandial
measure: Gut microbiota
timeFrame: single time point
measure: Gut microbiota fermentation capacity
timeFrame: single time point
measure: Gut microbiota pathogen resistance capacity
timeFrame: single time point
measure: Gut inflammation
timeFrame: single time point
measure: Stool metabolites
timeFrame: single time point
measure: Stool RNA markers
timeFrame: single time point
measure: Baseline and change in hunger and appetite
timeFrame: 0, 1, 2, 3, 4, 5, and 6 hours postprandial
measure: Baseline and change in gut fermentation profile
timeFrame: 0, 1, 2, 3, 4, 5, and 6 hours postprandial
measure: Recent dietary intake
timeFrame: Three 24-hour dietary recalls collected at home
measure: Dietary intake
timeFrame: single time point
measure: Behavior assessment
timeFrame: single time point
measure: Taste thresholds
timeFrame: single time point
measure: Skin reflectance
timeFrame: single time point
measure: Peripheral arterial tone
timeFrame: single time point
measure: Pulmonary function
timeFrame: single time point
measure: Pulmonary inflammation
timeFrame: single time point
measure: Executive function
timeFrame: single time point
measure: Cognitive function
timeFrame: single time point
measure: Aerobic fitness assessment
timeFrame: single time point
measure: Submaximal oxygen consumption
timeFrame: single time point
measure: Physical activity
timeFrame: daily, for 7 days
measure: Usual physical activity
timeFrame: single time point
measure: Heart rate variability and autonomic nerve conductivity
timeFrame: single time point
measure: Allostatic Load
timeFrame: single time point
measure: Baseline and change in salivary cortisol in response to test meal
timeFrame: 0, immediately post-prandial, 30, 60, and 90 minutes post-prandial
measure: Baseline and change in salivary cortisol in response to exercise
timeFrame: 0, immediately post-exercise, 30, 60, and 90 minutes post-exercise
measure: Baseline and change in salivary cortisol in response to emotional recall task
timeFrame: 0, immediately post-task, 30, 60, and 90 minutes post-task
measure: Baseline and change in breath aldehydes
timeFrame: 0, 1, 4 and 6 hours postprandial
Other outcomes:
Locations:
city: Davis
country: United States
facility: USDA, Western Human Nutrition Research Center
state: California
Study officials:
affiliation: USDA, Western Human Nutrition Research Center
name: Charles B Stephensen, Ph.D.
role: PRINCIPAL_INVESTIGATOR
affiliation: USDA, Western Human Nutrition Research Center
name: Brian J Bennett, Ph.D.
role: PRINCIPAL_INVESTIGATOR
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