Identification of Adropin as a Secreted Factor Linking Dietary Macronutrient Intake with Energy Homeostasis and Lipid Metabolism

Obesity and nutrient homeostasis are linked by mechanisms that are not fully elucidated. Here we describe a secreted protein, adropin, encoded by a gene, Energy Homeostasis Associated (Enho), expressed in liver and brain. Liver Enho expression is regulated by nutrition: lean C57BL/6J mice fed high-fat diet (HFD) exhibited a rapid increase, while fasting reduced expression compared to controls. However, liver Enho expression declines with diet-induced obesity (DIO) associated with 3 months of HFD or with genetically induced obesity, suggesting an association with metabolic disorders in the obese state. In DIO mice, transgenic overexpression or systemic adropin treatment attenuated hepatosteatosis and insulin resistance independently of effects on adiposity or food intake. Adropin regulated expression of hepatic lipogenic genes and adipose tissue peroxisome proliferator-activated receptor gamma, a major regulator of lipogenesis. Adropin may therefore be a factor governing glucose and lipid homeostasis, which protects against hepatosteatosis and hyperinsulinemia associated with obesity. © 2008 Elsevier Inc. All rights reserved

Lower energy expenditure predicts long-term increases in weight and fat mass

Context: The relevance of the contribution of energy expenditure (EE) and substrate oxidation to weight change has not been fully confirmed. Objective: The objective of the study was to determine whether metabolic parameters measured in a whole room indirect calorimeter are predictive of long-term body weight change. Setting: The study was conducted at a clinical research unit in Phoenix, Arizona, from 1985 to 2005. Participants: A total of 612 healthy subjects (384 males and 228 females; aged 29.5 ± 8.1 years; body mass index 33.0 ± 8.7 kg/m2; percent body fat 30.9 ± 9.6%), including 422 Native Americans and 190 whites. Follow-up data were available for 292 Native Americans with a median follow-up time of 6.7 years (interquartile range 3.9-10.5). Main Outcome Measures: Twenty-four-hour EE, sleeping metabolic rate, daily (fed) and sleeping (fasting) respiratory quotient, and carbohydrate and fat oxidation rates were measured during a 24-hour respiratory chamber. Body composition was assessed by underwater weighing or dual-energy x-ray absorptiometry. Results: After accounting for demographic and body composition measures, the remaining variance of 24-hour EE was inversely related to the rate of weight change (ρ = -0.158, P = .007) and fat mass change (ρ = -0.179, P = .012), such that 100 kcal belowthe expected 24-hour EE corresponded to 0.2 kg/y weight gain, of which 0.1 kg/y was fat mass. Deviations from the predicted values of the sleeping metabolic rate (ρ= -0.121, P= .039) and fed respiratory quotient (ρ = 0.119, P = .042) were also associated with future weight change, whereas the fat oxidation rate was inversely associated with weight change in men (ρ= -0.174, P= .024) but not in women (ρ = 0.018, P = .853). Conclusions: Measures of energy expenditure and substrate oxidation are predictors of long-term weight change, indicating a small but significant role for reduced metabolic rate in weight gain. Copyright © 2013 by The Endocrine Society

Core body temperature, energy expenditure, and epinephrine during fasting, eucaloric feeding, and overfeeding in healthy adult men: evidence for a ceiling effect for human thermogenic response to diet

Background In homeothermic animals, approximately 50% of daily energy expenditure (EE) is spent to maintain a consistent core body temperature (CBT). In humans, little is known about CBT responses to feeding and overfeeding and their relationship to diet-related changes in EE. Objective To study the effects of feeding and overfeeding on CBT and its association with diet-induced thermogenesis (DIT). Design Fifty-three healthy men with normal glucose regulation and a wide range of body composition (mean ± SD, body fat: 25 ± 8%, range: 7–43%) had 24-h EE assessed during fasting in a whole-room indirect calorimeter with concomitant CBT measurement by ingestible capsules and 24-h urinary collection for catecholamine measurements. Changes in 24-h EE (DIT) and CBT compared to fasting were assessed during three normal-protein (20%) diets using a cross-over design: one eucaloric diet (EBL, 50% carbohydrate, n = 37) and two overfeeding diets with 200% energy requirements: a high-fat (FNP, 60% fat, n = 25) and a high-carbohydrate (CNP; 75% carbohydrate, n = 24) diet. Results The average 24-h CBT (avgCBT) during fasting was 36.81 ± 0.14 °C (inter-individual CV = 0.4%) and positively correlated with 24-h urinary epinephrine (r = 0.61, p < 0.001), but not with body composition measures (p > 0.05). AvgCBT increased during EBL (Δ = 0.06 ± 0.11 °C, p = 0.002), FNP (Δ = 0.13 ± 0.14 °C, p < 0.001), and CNP (Δ = 0.19 ± 0.13 °C, p < 0.001) and associated with increased DIT during EBL (r = 0.43, p = 0.01, β = 31 kcal/day/0.1 °C) and FNP (r = 0.60, p = 0.002, β = 43 kcal/day/0.1 °C), but not CNP (p = 0.47). A ceiling effect for the increase in CBT, but not in DIT, was observed during feeding and, particularly, overfeeding. Conclusions CBT increases with feeding and is moderately associated with DIT to a different degree depending on the macronutrient composition of the overfeeding diet. There is a ceiling effect such that individuals with a higher CBT during fasting have limited capacity to increase CBT with feeding. Because of body thermoregulatory mechanisms that maintain a constant CBT, these results indicate that CBT has a limited role in the inter-individual variability in DIT

Cycling Efficiency During Incremental Cycle Ergometry After 24 Hours of Overfeeding or Fasting

Objective: The objective of this study was to determine whether net cycling efficiency (NET) is altered by 24-hour fasting or overfeeding and whether it correlates with dietary-related energy expenditure (EE) and future weight change. Methods: In a crossover design, healthy subjects fasted or were overfed for 24 hours while in a whole-room calorimeter using five diets with doubled energy needs: standard, high-carbohydrate (75%), high-fat (60%), high-protein (30%), and low-protein (3%) diets. Graded cycling exercise at low power outputs (10-25-50 W) was performed the day before and after each dietary intervention. Results: NET did not change following any dietary intervention (all P > 0.05 vs. 0). Individual changes in NET did not correlate with EE responses to dietary interventions. However, the change in NET after low-protein overfeeding was inversely correlated with baseline body fat (r = −0.60, P = 0.01); that is, NET increased in lean but decreased in overweight subjects (Δ = 0.010 ± 0.010 vs. −0.013 ± 0.009, P = 0.0003). Increased NET following the low-protein diet was associated with weight gain after 6 months (r = 0.60, P = 0.05). Conclusions: Despite no substantial effect of acute overfeeding or fasting on NET, the change in NET following low-protein overfeeding depends on adiposity and may influence weight change, suggesting that increased efficiency in a setting of protein scarcity is an adaptive response that may ultimately lead to weight gain

Increased 24-hour ad libitum food intake is associated with lower plasma irisin concentrations the following morning in adult humans

BACKGROUND The relationship between food intake and irisin concentrations in humans is unclear. OBJECTIVES To determine whether the previous day's intake impacts fasting plasma irisin concentrations, or whether fasting irisin concentrations associate with subsequent ad libitum food intake. METHODS Sixty-six nondiabetic adults (42 men) were admitted for a study of the determinants of energy intake. After 6 days of a weight maintaining diet, ad libitum energy intake over 3 days was assessed using a vending machine paradigm. Fasting plasma irisin concentrations were measured on the morning of the second day of the vending period. RESULTS There were no correlations between irisin and demographic or anthropometric parameters. On day 1, subjects consumed 144 ± 52% of weight maintaining energy needs. Every additional 500 kcal consumed on day 1 associated with a 3.4% lower irisin concentration the following morning (95% CI -6.2, -0.4%, p = 0.01; adjusted for age, sex and race). If energy intake was expressed as a percentage of weight maintaining energy needs, every 10% increase associated with a 1.9% lower irisin concentration (95% CI -3.7, -0.1%; adjusted p = 0.02). A 100 kcal increase in carbohydrate or fat consumption associated with a 1.3% (95% CI -2.5, -0.1%, p = 0.01) and a 0.6% (95% CI -1.1, -0.0%, p = 0.02) lower irisin concentration, respectively. There was no association between fasting irisin concentrations and subsequent energy intake on day 2 (r = 0.19, p = 0.1). CONCLUSIONS Higher ad libitum 24 h energy intake was associated with lower fasting irisin concentrations the following morning, but fasting irisin concentrations did not predict subsequent energy intake. The decrease in irisin concentrations with increased energy intake is consistent with the detrimental metabolic effects of overeating