Siran He1, Ngoc-Anh Le2, Manuel Ramírez-Zea3, Reynaldo Martorell4, K M Venkat Narayan4, Aryeh D Stein5. 1. Nutrition and Health Sciences Program, Laney Graduate School, Emory University, Atlanta, GA, USA. 2. Biomarker Core Laboratory, Foundation for Atlanta Veterans Education and Research (FAVER), Atlanta Veterans Affairs Health Care System (AVAHCS), Atlanta, GA, USA. 3. INCAP Research Center for the Prevention of Chronic Diseases (CIIPEC), Institute of Nutrition of Central America and Panama, Guatemala City, Guatemala. 4. Rollins School of Public Health, Emory University, Atlanta, GA, USA. 5. Rollins School of Public Health, Emory University, Atlanta, GA, USA. Electronic address: Aryeh.stein@emory.edu.
Abstract
BACKGROUND & AIMS: With the rise of global cardiometabolic diseases, it is important to investigate risk factors such as obesity. Metabolic flexibility, the ability to maintain metabolic homeostasis following an acute challenge, can reflect cardiometabolic health. We investigated the association between body composition and the metabolic flexibility following meal consumption in an adult population. METHODS: In this study of 1027 participants (mean age 44.0 y ± SD 4.2 y), we administered a mixed-macronutrient meal challenge. Fasting and 2-h postprandial plasma were assayed for lipids, glycemic, and inflammation biomarkers. We characterized metabolic flexibility through meal-induced biomarker responses (%Δ, the difference between postprandial and fasting concentrations, divided by fasting concentration). We then compared the responses by sex-specific tertiles of body mass index (BMI) and percent body fat. RESULTS: With every unit (kg/m2) increase in BMI, %Δ (95% confidence interval) increased by 0.17% (0.09, 0.26%) for total cholesterol, 0.31% (0.07, 0.54%) for triglycerides, and 0.11% (0.01, 0.20%) for apoA-I, whereas insulin elevation was reduced (-6.30%; -8.41, -4.20%), and the reduction in leptin was attenuated (0.64%; 0.25, 1.05%). With each unit (percent) increase in body fat, we observed similar changes in the %Δ of total cholesterol and leptin but not in triglycerides, apoA-I, or insulin. Glucose response increased by 0.29% (0.06, 0.51%) as body fat increases by one unit. CONCLUSION: Metabolic flexibility, as assessed by biomarker responses to an acute physiological meal challenge, differed by body composition. These findings may help elucidate the pathways through which obesity contributes to cardiometabolic diseases.
BACKGROUND & AIMS: With the rise of global cardiometabolic diseases, it is important to investigate risk factors such as obesity. Metabolic flexibility, the ability to maintain metabolic homeostasis following an acute challenge, can reflect cardiometabolic health. We investigated the association between body composition and the metabolic flexibility following meal consumption in an adult population. METHODS: In this study of 1027 participants (mean age 44.0 y ± SD 4.2 y), we administered a mixed-macronutrient meal challenge. Fasting and 2-h postprandial plasma were assayed for lipids, glycemic, and inflammation biomarkers. We characterized metabolic flexibility through meal-induced biomarker responses (%Δ, the difference between postprandial and fasting concentrations, divided by fasting concentration). We then compared the responses by sex-specific tertiles of body mass index (BMI) and percent body fat. RESULTS: With every unit (kg/m2) increase in BMI, %Δ (95% confidence interval) increased by 0.17% (0.09, 0.26%) for total cholesterol, 0.31% (0.07, 0.54%) for triglycerides, and 0.11% (0.01, 0.20%) for apoA-I, whereas insulin elevation was reduced (-6.30%; -8.41, -4.20%), and the reduction in leptin was attenuated (0.64%; 0.25, 1.05%). With each unit (percent) increase in body fat, we observed similar changes in the %Δ of total cholesterol and leptin but not in triglycerides, apoA-I, or insulin. Glucose response increased by 0.29% (0.06, 0.51%) as body fat increases by one unit. CONCLUSION: Metabolic flexibility, as assessed by biomarker responses to an acute physiological meal challenge, differed by body composition. These findings may help elucidate the pathways through which obesity contributes to cardiometabolic diseases.
Authors: Suziy de M Bandeira; Lucas José S da Fonseca; Glaucevane da S Guedes; Luíza A Rabelo; Marília O F Goulart; Sandra Mary L Vasconcelos Journal: Int J Mol Sci Date: 2013-02-05 Impact factor: 5.923