Location: Jean Mayer Human Nutrition Research Center On Aging2018 Annual Report
LAB NAME: Cardiovascular Nutrition 1. Determine the effect of diets differing in fat and carbohydrate type on cardiometabolic risk indicators, lipoprotein and fatty acid metabolism, response to lipid modifying therapy, and gene-nutrient interactions, using human, animal and in vitro models. 1.1 – Relative effects of palmitate (16:0), stearate (18:0) and oleate (18:1) on cardiometabolic risk factors, fatty acid kinetics and lipoprotein-mediated in vitro endothelial cell inflammatory response. 1.2 – Relative effects of simple, refined and unrefined carbohydrate on cardiometabolic risk factors, macrophage cholesterol homeostasis, subcutaneous adipose tissue macrophage infiltration/inflammatory gene expression, and intestinal microbiome. 1.3 – Synergistic effects of a ‘heart healthy’ diet and statin therapy on atherosclerosis using a porcine model. 1.4 – Common and differential effects of eicosapentaenoic acid and docosahexaenoic acid on lipid metabolism and systemic inflammation. 1.5 - Relationship of dietary fat type to HDL functionality, composition and concentration, and association with coronary heart disease. 2. Determine the relationship between food preferences, consumption patterns and dietary acculturation, and cardiovascular health using population-based datasets. 2.1 – Impact of acculturation status on dietary patterns and health outcomes in Chinese Americans. 3. Identify novel biomarkers for food and nutrient intake related to dietary patterns and cardiovascular health. 3.1 – Effect of a comprehensive 12 month approach to family weight management on biomarkers of dietary intake and cardiometabolic risk factors in child-mothers/female guardian pairs. 3.2 – Novel nutrient biomarkers to predict risk of heart failure.
LAB NAME: Cardiovascular Nutrition In the next 5 years the Cardiovascular Nutrition Laboratory (CNL) will investigate the effects of diets differing in fat type and carbohydrate type on cardiometabolic risk factors, fatty acid metabolism, response to lipid modifying therapy, and gene-nutrient interactions using human, animal and in vitro models. This will be accomplished by assessing the relative effects of palmitate, stearate and oleate on cardiometabolic risk factors, fatty acid kinetics and in vitro endothelial cell inflammatory response to lipoprotein particles; relative effects of simple-carbohydrate, refined-carbohydrate and unrefined-carbohydrate on cardiometabolic risk factors, macrophage cholesterol homeostasis, and intestinal microbiome; synergistic effects of an atherogenic or ‘ heart healthy’ diet with/without statin therapy on atherosclerosis development using a porcine model; and relative effects of eicosapentaenoic and docosahexaenoic acids on systemic inflammation and lipid metabolism. The CNL will determine the relationship between food preferences, consumption patterns and dietary acculturation, and cardiovascular health using population-based datasets by assessing the impact of acculturation status on dietary patterns and health outcomes. In addition, the CNL will identify and adjudicate novel biomarkers for food and nutrient intake and merge them with established biomarkers thereof, and assess potential relationships with family-wide CVD risk and weight management, and heart failure risk.
Sub-objective 1.1: Progress was made studying the relative effects of saturated fatty acids (SFA) – palmitic (16:0) and stearic (18:0)– and the monounsaturated fatty acid (MUFA), oleic (18:1). We tested the hypothesis that 18:0 can be converted to 18:1 but not 16:0 to 16:1 in 20 post-menopausal women (low density lipoprotein [LDL]-cholesterol[C]>2.6mmol/L) by providing them with each of 3 diets for 35 day periods using a randomized controlled cross-over (RCT) design. The diets provided 55%E carbohydrate, 15%E protein and 30%E fat, with half the fat contributed by 16:0, 18:0 or 18:1. At the end of the 18:1 and 18:0 periods participants had significantly lower LDL-C (-15%, -11%) and HDL-C (-4%, -12%) concentrations relative to the 16:0 period. T-cell proliferation in response to antibodies against CD3 (T cell receptor) and CD28 (T cell co-receptor) was significantly higher, less favorable, in response to the 16:0 relative to 18:0 and 18:1 diets (54%, 82%). There was no significant effect of the different diet on plasma triglyceride, glucose or insulin concentrations, and markers of coagulation and systemic inflammation. These data suggest that with respect to heart disease risk factors although both 16:0 and 18:0 are SFA, from a metabolic perspective 18:0 is more similar to 18:1, a MUFA, than 16:0. These findings raise the possibility that when making dietary recommendations to reduce SFA, 18:0 should not be categorized as a SFA. Using a sub-set of this cohort we conducted kinetic studies to confirm that a portion of 18:0 was converted to 18:1. At the end of the intervention period described above, following a 12 hour fast, 6 participants received their usual diet divided into 13 hourly meals. A purified fatty acid tracer (1.0 mg/kg BW) of 13C18:0 or 13C18:1 was incorporated into one meal. Plasma enrichment curves followed a similar pattern but the area under the curve of 13C18:0 was significantly higher than 13C18:1, suggesting conversion of 18:0 to 18:1. 13C18:0 was first converted to 13C16:0, desaturated to 13C16:1 and elongated to 13C18:1, the latter being the major metabolite. No fatty acid metabolites of 13C18:1 was detected during the 3 day monitoring period. A higher proportion of 18:0 and its metabolites were incorporated into the plasma triglyceride than 18:1. Breath 13CO2 kinetic curves indicated a lower cumulative oxidation rate of 13C18:0 than 13C18:1. These data indicate higher plasma 13C18:0 reflects lower oxidation rates, multi-stage conversion to 18:1, and preferential incorporation along with its metabolites into plasma triglycerides. Sub-objective 1.2: We compared the effect of different carbohydrate-types (simple, refined and unrefined) on cardiometabolic risk (CMR) indicators. Participants (postmenopausal women and men [N=11], 65 ± 8y, BMI 29.8 ± 3.2kg/m2, LDL-C =2.6mmol/L) were provided with each of 3 diets (60% E total carbohydrate, 15% E protein, 25% E fat) for 4.5 weeks using a RCT design. The diets differed due to the isocaloric exchange of the 3 carbohydrate-types. The intervention resulted in similar serum CMR indicators and ex vivo cholesterol efflux with the exception of significantly higher serum LDL- and nonHDL-C concentrations after the refined- compared to simple- or unrefined-carbohydrate diets. Mean adipocyte area and percent large adipocytes was significantly higher at the end of the refined- compared to the simple- or unrefined-carbohydrate diets. Adipose tissue gene expression and ex vivo cytokine secretion was similar among diets. These findings raise the possibility that refined-carbohydrate may have unique adverse effects on CRM indicators distinct from simple- and unrefined-carbohydrate. Sub-objective 1.3: In collaboration with ARS-Beltsville, we used the Ossabaw pig model to determine the effect of a heart healthy diet (HHD) and Western diet (WD) +/- atorvastatin (S) therapy on epicardial adipose tissue (EAT). EAT is an adipose tissue depot adjacent to the coronary arteries, displays a dysfunctional phenotype characterized by the production of pro-inflammatory adipokines and cytokines and is thought to act locally on underlying coronary arteries to promote lesion formations. Pigs (N=30) were allocated to four groups, HHD, HHD+S, WD, WD+S. Diets were matched for macronutrient composition but differed in types of fat (unsaturated vs saturated) and carbohydrate (whole vs refined). The HHD was supplemented with fish oil 3-times/week. After 6 months, relative to the HHD, pigs fed the WD had significantly higher proportions of total SFA and trans fatty acids, lower proportions of n-6 and n-3 PUFA, and higher estimated stearoyl-CoA-desaturase 1 and delta-6-desaturase and lower stearoyl-CoA-desaturase 2 activities. SFA were positively associated with interferon regulatory factor 7, interferon induced protein with tetratricopeptide repeats 1, and prostaglandin-endoperoxide synthase 2 expression, and negatively associated with interleukin 6 expression. Total n-6 and n-3 PUFAs were positively associated with free fatty acid receptor 4, peroxisome proliferator activated receptor gamma and arachidonate 5-lipoxygenase expression. These data suggest dietary fat type influences EAT fatty acid profiles which in turn alter pro-inflammatory and anti-inflammatory gene expression, supporting current recommendations to replace saturated fat with unsaturated fat.
1. Ossabaw pig proves to be a reliable experimental model to study heart disease. Due to difficulties in studying the coronary artery disease in humans, little is known about how altering a person’s diet can affect the use of statins in the treatment of heart disease. ARS and ARS-funded researchers in Boston, Massachusetts and Beltsville, Maryland successfully replicated coronary disease in Ossabaw pigs by feeding them the equivalent of a Western diet that lead to build up of cholesterol in the coronary arteries and produced other risk factors for heart disease in humans. The use of this pig model to study heart disease can be the cornerstone of coronary artery disease prevention and treatment for almost half of American adults older than 40 years of age who take medications such as statins to treat heart disease.
2. Glycemic Index of food can be influenced by prior meal. It has become common practice to recommend people select foods with lower values on the glycemic index (GI), a ranking system based on the effect a specific food has on blood sugar levels. However, this does not take into consideration how the fat, protein and carbohydrate content consumed in a prior meal may influence the glucose level of a food with a low GI ranking. ARS-funded researchers in Boston, Massachusetts conducted a 12-week study, in which 20 healthy participants received each of three breakfast meals with similar calorie values (either high carbohydrate, high fat or high protein) on separate days in random order, followed by a standard set of food challenges used to determine GI values. Consuming the high protein breakfast lowered the glucose response compared to the high carbohydrate and high fat breakfasts, but the serum lipid tests that measure cholesterol and other fats (triglyceride) showed participants had similar levels regardless of the breakfast composition. This data suggest that composition of the prior meal continues to influence blood sugar levels and it is unwise to make dietary recommendations based on the glycemic index of an individual food, especially if the intent is to reduce the risk of chronic disease.
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