USDA Western Human Nutrition Research Center (WHNRC) Cross-Sectional Nutritional Phenotyping Study

Study Overview
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Brief Summary
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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
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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: pro-inflammatory T-helper cells (Th1, Th2, and Th17 cells) and related cytokines anti-inflammatory T-regulatory cells and related cytokines 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 plasma metabolomic response to a mixed macronutrient challenge meal (includes diet quality and physical activity as independent variables) 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: postprandial monocyte activation 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 plasma amino acid metabolomics glucose metabolism and metabolic flexibility (i.e. the ability to switch from glucose to lipid oxidation as energy sources) changes in endocrinology and self-report of hunger and satiety postprandial free cortisol Specific Aim 3: To determine the mechanisms of: postprandial monocyte activation 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: endocrinology of hunger and satiety plasma metabolomic responses vulnerability and resistance to stress endothelial (dys)function and vascular reactivity 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.

Official Title
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Assessing the Impact of Diet on Inflammation in Healthy and Obese Adults in a Cross-Sectional Phenotyping Study

Conditions
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Obesity, Inflammation

Participation Criteria
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Eligibility Criteria
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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)

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 65 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Sampling strata<br>Stratified analyses of primary and secondary outcomes based on variables of interest (e.g. sex, age, or BMI) may occur prior to achieving the target for total study enrollment. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Baseline level and change in systemic immune activation following challenge meal | Number and activation level of pro-inflammatory T-helper (Th) cells (Th1, Th2 and Th17), T-regulatory (Treg) cells, and B cells will be measured in fasting blood. Monocytes and neutrophils will be measured in fasting and postprandial blood. | 0, 0.5, 3, and 6 hours postprandial | 
| Baseline level and change in plasma metabolome | Plasma fatty acid profiles of non-esterified fatty acids, phospholipids, triacylglycerols, red blood cell fatty acids, endocannabinoids, bile acids, eicosanoids and related oxylipins, ceramides, sphingoid bases, acylcarnitines, amino acids and other metabolites measured in response to a challenge meal. | 0, 0.5, 3, and 6 hours postprandial | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Baseline level and change in glucose metabolism | Glucose and insulin measured in response to a challenge meal. | 0, 0.5, 3, and 6 hours postprandial | 
| Baseline level and change in appetitive hormones | Cholecystokinin, incretins, Peptide YY 3-36, ghrelin measured in response to a challenge meal. | 0, 0.5, 3, and 6 hours postprandial | 
| Baseline level and change in mitogen activated protein (MAP) kinase activity | Mononuclear cells or B cells will be measured for MAP kinase activities in fasting and postprandial blood. | 0, 0.5, 3 and 6 hours postprandial | 
| Baseline level and change in dietary-responsive, circulating microRNA | Plasma microRNA measured in response to a challenge meal | 0, 0.5, 3, and 6 hours postprandial | 
| Baseline level and change in RNA transcriptome | Transcriptome RNA sequenced in whole blood | 0, 3, and 6 hours postprandial | 
| Genome Wide Association Study (GWAS) | DNA sequence from whole blood will be analyzed | 0 hours (fasting) | 
| General health | Clinical chemistry panel and complete blood count | 0 hours (Fasting) | 
| Anthropometrics | Height (cm), weight (kg), waist and hip circumference (cm) | single time point | 
| Vital signs | Blood pressure (mmHg), pulse rate (beats per minute) and temperature (degrees F). | single time point | 
| Body composition | Body composition (percent body fat) and bone mineral density by Dual energy X-ray Absorptiometry scan. | single time point | 
| Resting and change in metabolism | Resting and postprandial metabolic rates, including respiratory exchange ratios. | 0, 0.5, 3, and 6 hours postprandial | 
| Gut microbiota | Gut microbiota composition and gene content will be assessed in stool using polymerase chain reaction (PCR) and sequencing | single time point | 
| Gut microbiota fermentation capacity | The fermentation capacity of microbiota will be measured from a single stool sample | single time point | 
| Gut microbiota pathogen resistance capacity | The pathogen resistance capability of microbiota will be measured from a single stool sample | single time point | 
| Gut inflammation | Gut inflammation will be assessed by measuring molecules in stool and/or the response of intestinal epithelial cell cultures to fecal waters from a single stool sample. | single time point | 
| Stool metabolites | Volatile and short chain fatty acids and bile acids will be measured in a single stool sample. | single time point | 
| Stool RNA markers | RNA markers will provide a measure of genes expressed by cells of the colon naturally present in a single stool sample | single time point | 
| Baseline and change in hunger and appetite | Perceived hunger and fullness will be measured using a visual analog scale. Responses will be a marked on an unsegmented line from 0 or not at all to 5 or extremely. | 0, 1, 2, 3, 4, 5, and 6 hours postprandial | 
| Baseline and change in gut fermentation profile | Breath hydrogen and methane measured in response to a challenge meal. | 0, 1, 2, 3, 4, 5, and 6 hours postprandial | 
| Recent dietary intake | Random selection of 2 week days and 1 weekend day for 24-hour recall using an automated multi-pass method | Three 24-hour dietary recalls collected at home | 
| Dietary intake | Food frequency questionnaire (FFQ) | single time point | 
| Behavior assessment | Chronic stress questionnaire, food choice questionnaires, and a food preference activity. | single time point | 
| Taste thresholds | Sampling tastes of sweet, salty, and bitter solutions in comparison to water to determine threshold of taste detection. | single time point | 
| Skin reflectance | Spectrophotometric measure of skin pigmentation for assessment of vitamin D status. | single time point | 
| Peripheral arterial tone | Use of the EndoPAT system to measure blood vessel tone. | single time point | 
| Pulmonary function | Forced expiratory lung volume test | single time point | 
| Pulmonary inflammation | Pulmonary inflammation measured as exhaled nitric oxide (NO) | single time point | 
| Executive function | Executive function will be assessed using Cambridge Neuropsychological Test Automated Battery (CANTAB) and Iowa Gambling Task | single time point | 
| Cognitive function | Measured by Wechsler Abbreviated Standard Intelligence test. | single time point | 
| Aerobic fitness assessment | Pulse rate (bpm) and recovery after a 3 min YMCA Step Test | single time point | 
| Submaximal oxygen consumption | The submaximal volume of oxygen consumed during a 4 minute treadmill walking protocol (VO2max) (ml/kg*min) | single time point | 
| Physical activity | Use of an accelerometer worn on the hip for 7 days | daily, for 7 days | 
| Usual physical activity | Activity recall using a questionnaire | single time point | 
| Heart rate variability and autonomic nerve conductivity | Monitoring of autonomic balance, cardiac performance, and respiratory measurements and activity using MindWare Mobile Impedance Cardiograph. | single time point | 
| Allostatic Load | An aggregate score derived from measures of urinary cortisol, norepinephrine, epinephrine, blood cholesterol, high sensitivity c-reactive protein, and hemoglobin A1C. | single time point | 
| Baseline and change in salivary cortisol in response to test meal | Salivary cortisol measured by enzyme-linked immunosorbent assay (ELISA) | 0, immediately post-prandial, 30, 60, and 90 minutes post-prandial | 
| Baseline and change in salivary cortisol in response to exercise | Salivary cortisol measured by enzyme-linked immunosorbent assay (ELISA) | 0, immediately post-exercise, 30, 60, and 90 minutes post-exercise | 
| Baseline and change in salivary cortisol in response to emotional recall task | Salivary cortisol measured by enzyme-linked immunosorbent assay (ELISA) | 0, immediately post-task, 30, 60, and 90 minutes post-task | 
| Baseline and change in breath aldehydes | The concentration of aldehydes present in human breath before and after a high-fat meal will be measured by mass spectrometry | 0, 1, 4 and 6 hours postprandial | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Phenotype, Immunology, Microbiota, Metabolomics, Physical activity, Neuroendocrine system, Nutritional Physiological Phenomena, Diet