GLP-1 receptor (GLP-1R) is widely located throughout the brain, but the precise molecular mechanisms mediating the actions of GLP-1 and its long-acting analogs on adipose tissue as well as the brain areas responsible for these interactions remain largely unknown. We found that central injection of a clinically used GLP-1R agonist, liraglutide, in mice stimulates brown adipose tissue (BAT) thermogenesis and adipocyte browning independent of nutrient intake. The mechanism controlling these actions is located in the hypothalamic ventromedial nucleus (VMH), and the activation of AMPK in this area is sufficient to blunt both central liraglutide-induced thermogenesis and adipocyte browning. The decreased body weight caused by the central injection of liraglutide in other hypothalamic sites was sufficiently explained by the suppression of food intake. In a longitudinal study involving obese type 2 diabetic patients treated for 1 year with GLP-1R agonists, both exenatide and liraglutide increased energy expenditure. Although the results do not exclude the possibility that extrahypothalamic areas are also modulating the effects of GLP-1R agonists, the data indicate that long-acting GLP-1R agonists influence body weight by regulating either food intake or energy expenditure through various hypothalamic sites and that these mechanisms might be clinically relevant.

OBJECTIVE To assess the predictive capacity of a recently described equation that we have termed CUN-BAE (Clínica Universidad de Navarra-Body Adiposity Estimator) based on BMI, sex, and age for estimating body fat percentage (BF%) and to study its clinical usefulness. RESEARCH DESIGN AND METHODS We conducted a comparison study of the developed equation with many other anthropometric indices regarding its correlation with actual BF% in a large cohort of 6,510 white subjects from both sexes (67% female) representing a wide range of ages (18–80 years) and adiposity. Additionally, a validation study in a separate cohort (n = 1,149) and a further analysis of the clinical usefulness of this prediction equation regarding its association with cardiometabolic risk factors (n = 634) was carried out. RESULTS The mean BF% in the cohort of 6,510 subjects determined by air displacement plethysmography was 39.9 ± 10.1%, and the mean BF% estimated by the CUN-BAE was 39.3 ± 8.9% (SE of the estimate, 4.66%). In this group, BF% calculated with the CUN-BAE showed the highest correlation with actual BF% (r = 0.89, P < 0.000001) compared with other anthropometric measures or BF% estimators. Similar agreement was found in the validation sample. Moreover, BF% estimated by the CUN-BAE exhibits, in general, better correlations with cardiometabolic risk factors than BMI as well as waist circumference in the subset of 634 subjects. CONCLUSIONS CUN-BAE is an easy-to-apply predictive equation that may be used as a first screening tool in clinical practice. Furthermore, our equation may be a good tool for identifying patients at cardiovascular and type 2 diabetes risk.

Obesity is the major risk factor for the development of prediabetes and type 2 diabetes. BMI is widely used as a surrogate measure of obesity, but underestimates the prevalence of obesity, defined as an excess of body fat. We assessed the presence of impaired glucose tolerance or impaired fasting glucose (both considered together as prediabetes) or type 2 diabetes in relation to the criteria used for the diagnosis of obesity using BMI as compared to body fat percentage (BF%). We performed a cross‐sectional study including 4,828 (587 lean, 1,320 overweight, and 2,921 obese classified according to BMI) white subjects (66% females), aged 18–80 years. BMI, BF% determined by air‐displacement plethysmography (ADP) and conventional blood markers of glucose metabolism and lipid profile were measured. We found a higher than expected number of subjects with prediabetes or type 2 diabetes in the obese category according to BF% when the sample was globally analyzed (P < 0.0001) and in the lean BMI‐classified subjects (P < 0.0001), but not in the overweight or obese‐classified individuals. Importantly, BF% was significantly higher in lean (by BMI) women with prediabetes or type 2 diabetes as compared to those with normoglycemia (NG) (35.5 ± 7.0 vs. 30.3 ± 7.7%, P < 0.0001), whereas no differences were observed for BMI. Similarly, increased BF% was found in lean BMI‐classified men with prediabetes or type 2 diabetes (25.2 ± 9.0 vs. 19.9 ± 8.0%, P = 0.008), exhibiting no differences in BMI or waist circumference. In conclusion, assessing BF% may help to diagnose disturbed glucose tolerance beyond information provided by BMI and waist circumference in particular in male subjects with BMI <25 kg/m² and over the age of 40.

Non-alcoholic fatty liver disease (NAFLD) is a major global health threat due to its growing incidence and prevalence. It is becoming the leading cause of liver disease in addition to its strong association with cardio-metabolic disease. Therefore, its prevention and treatment are of strong public interest. Therapeutic approaches emphasize lifestyle modifications including physical activity and the adoption of healthy eating habits that intend to mainly control body weight and cardio-metabolic risk factors associated with the metabolic syndrome. Lifestyle interventions may be reinforced by pharmacological treatment in advanced stages, though there is still no registered drug for the specific treatment of NAFLD. The purpose of this review is to assess the evidence available regarding the impact of dietary recommendations against NAFLD, highlighting the effect of macronutrient diet composition and dietary patterns in the management of NAFLD.