Activation of NPRs and UCP1-independent pathway following CB1R antagonist treatment is associated with adipose tissue beiging in fat-fed male dogs.

CB1 receptor (CB1R) antagonism improves the deleterious effects of a high-fat diet (HFD) by reducing body fat mass and adipocyte cell size. Previous studies demonstrated that the beneficial effects of the CB1R antagonist rimonabant (RIM) in white adipose tissue (WAT) are partially due to an increase of mitochondria numbers and upregulation thermogenesis markers, suggesting an induction of WAT beiging. However, the molecular mechanism by which CB1R antagonism induces weight loss and WAT beiging is unclear. In this study, we probed for genes associated with beiging and explored longitudinal molecular mechanisms by which the beiging process occurs. HFD dogs received either RIM (HFD+RIM) or placebo (PL) (HFD+PL) for 16 wk. Several genes involved in beiging were increased in HFD+RIM compared with pre-fat, HFD, and HFD+PL. We evaluated lipolysis and its regulators including natriuretic peptide (NP) and its receptors (NPRs), ß-1 and ß-3 adrenergic receptor (ß1R, ß3R) genes. These genes were increased in WAT depots, accompanied by an increase in lipolysis in HFD+RIM. In addition, RIM decreased markers of inflammation and increased adiponectin receptors in WAT. We observed a small but significant increase in UCP1; therefore, we evaluated the newly discovered UCP1-independent thermogenesis pathway. We confirmed that SERCA2b and RYR2, the two key genes involved in this pathway, were upregulated in the WAT. Our data suggest that the upregulation of NPRs, ß-1R and ß-3R, lipolysis, and SERCA2b and RYR2 may be one of the mechanisms by which RIM promotes beiging and overall the improvement of metabolic homeostasis induced by RIM.

Variability of Directly Measured First-Pass Hepatic Insulin Extraction and Its Association With Insulin Sensitivity and Plasma Insulin.

Although the ß-cells secrete insulin, the liver, with its first-pass insulin extraction (FPE), regulates the amount of insulin allowed into circulation for action on target tissues. The metabolic clearance rate of insulin, of which FPE is the dominant component, is a major determinant of insulin sensitivity (SI). We studied the intricate relationship among FPE, SI, and fasting insulin. We used a direct method of measuring FPE, the paired portal/peripheral infusion protocol, where insulin is infused stepwise through either the portal vein or a peripheral vein in healthy young dogs (n = 12). FPE is calculated as the difference in clearance rates (slope of infusion rate vs. steady insulin plot) between the paired experiments. Significant correlations were found between FPE and clamp-assessed SI (rs = 0.74), FPE and fasting insulin (rs = -0.64), and SI and fasting insulin (rs = -0.67). We also found a wide variance in FPE (22.4-77.2%; mean ± SD 50.4 ± 19.1) that is reflected in the variability of plasma insulin (48.1 ± 30.9 pmol/L) and SI (9.4 ± 5.8 × 104 dL · kg-1 · min-1 · [pmol/L]-1). FPE could be the nexus of regulation of both plasma insulin and SI.

Assessment of hepatic insulin extraction from in vivo surrogate methods of insulin clearance measurement.

Hyperinsulinemia, accompanied by reduced first-pass hepatic insulin extraction (FPE) and increased secretion, is a primary response to insulin resistance. Different in vivo methods are used to estimate the clearance of insulin, which is assumed to reflect FPE. We compared two methodologically different but commonly used indirect estimates with directly measured FPE in healthy dogs ( n = 9). The indirect methods were 1) metabolic clearance rate of insulin (MCR) during the hyperinsulinemic-euglycemic clamp (EGC), a steady-state method, and 2) fractional clearance rate of insulin (FCR) during the frequently sampled intravenous glucose tolerance test (FSIGT), a dynamic method. MCR was calculated as the ratio of insulin infusion rate to steady-state plasma insulin. FCR was calculated as the exponential decay rate constant of the injected insulin. Directly measured FPE is based on the difference in insulin measurements during intraportal vs. peripheral vein insulin infusions. We found a strong correlation between indirect FCR (min-1) and FPE (%). In contrast, we observed a poor association between MCR (ml·min-1·kg-1) and FPE (%). Our findings in canines suggest that FCR measured during FSIGT can be used to estimate FPE. However, MCR calculated during EGC appears to be a poor surrogate for FPE.

Isoflurane and Sevoflurane Induce Severe Hepatic Insulin Resistance in a Canine Model.

INTRODUCTION: Anesthesia induces insulin resistance, which may contribute to elevated blood glucose and adverse post-operative outcomes in critically ill patients, and impair glycemic control in surgical patients with diabetes. However, little is known about the mechanisms by which anesthesia impairs insulin sensitivity. Here we investigate the effects of anesthesia on insulin sensitivity in metabolic tissues. METHODS: Hyperinsulinemic-euglycemic clamps were performed in 32 lean (control diet; n = 16 conscious versus n = 16 anesthetized) and 24 fat-fed (6 weeks fat-feeding; n = 16 conscious versus n = 8 anesthetized) adult male mongrel dogs in conjunction with tracer methodology to differentiate hepatic versus peripheral insulin sensitivity. Propofol was administered as an intravenous bolus (3mg/kg) to initiate anesthesia, which was then maintained with inhaled sevoflurane or isoflurane (2-3%) for the duration of the procedure. RESULTS: Anesthesia reduced peripheral insulin sensitivity by approximately 50% in both lean and fat-fed animals as compared to conscious animals, and insulin action at the liver was almost completely suppressed during anesthesia such that hepatic insulin sensitivity was decreased by 75.5% and; 116.2% in lean and fat-fed groups, respectively. CONCLUSION: Inhaled anesthesia induces severe hepatic insulin resistance in a canine model. Countermeasures that preserve hepatic insulin sensitivity may represent a therapeutic target that could improve surgical outcomes in both diabetic and healthy patients.

Elevated nocturnal NEFA are an early signal for hyperinsulinaemic compensation during diet-induced insulin resistance in dogs.

AIMS/HYPOTHESIS: A normal consequence of increased energy intake and insulin resistance is compensatory hyperinsulinaemia through increased insulin secretion and/or reduced insulin clearance. Failure of compensatory mechanisms plays a central role in the pathogenesis of type 2 diabetes mellitus; consequently, it is critical to identify in vivo signal(s) involved in hyperinsulinaemic compensation. We have previously reported that high-fat feeding leads to an increase in nocturnal NEFA concentration. We therefore designed this study to test the hypothesis that elevated nocturnal NEFA are an early signal for hyperinsulinaemic compensation for insulin resistance. METHODS: Blood sampling was conducted in male dogs to determine 24 h profiles of NEFA at baseline and during high-fat feeding with and without acute nocturnal NEFA suppression using a partial A1 adenosine receptor agonist. RESULTS: High-fat feeding increased nocturnal NEFA and reduced insulin sensitivity, effects countered by an increase in acute insulin response to glucose (AIR(g)). Pharmacological NEFA inhibition after 8 weeks of high-fat feeding lowered NEFA to baseline levels and reduced AIR(g) with no effect on insulin sensitivity. A significant relationship emerged between nocturnal NEFA levels and AIR(g). This relationship indicates that the hyperinsulinaemic compensation induced in response to high-fat feeding was prevented when the nocturnal NEFA pattern was returned to baseline. CONCLUSIONS/INTERPRETATION: Elevated nocturnal NEFA are an important signal for hyperinsulinaemic compensation during diet-induced insulin resistance.

CB1R antagonist increases hepatic insulin clearance in fat-fed dogs likely via upregulation of liver adiponectin receptors.

The improvement of hepatic insulin sensitivity by the cannabinoid receptor 1 (CB1R) antagonist rimonabant (RIM) has been recently been reported to be due to upregulation of adiponectin. Several studies demonstrated that improvement in insulin clearance accompanies the enhancement of hepatic insulin sensitivity. However, the effects of RIM on hepatic insulin clearance (HIC) have not been fully explored. The aim of this study was to explore the molecular mechanism(s) by which RIM affects HIC, specifically to determine whether upregulation of liver adiponectin receptors (ADRs) and other key genes regulated by adiponectin mediate the effects. To induce insulin resistance in skeletal muscle and liver, dogs were fed a hypercaloric high-fat diet (HFD) for 6 wk. Thereafter, while still maintained on a HFD, animals received RIM (HFD+RIM; n = 11) or placebo (HFD+PL; n = 9) for an additional 16 wk. HIC, calculated as the metabolic clearance rate (MCR), was estimated from the euglycemic-hyperinsulinemic clamp. The HFD+PL group showed a decrease in MCR; in contrast, the HFD+RIM group increased MCR. Consistently, the expression of genes involved in HIC, CEACAM-1 and IDE, as well as gene expression of liver ADRs, were increased in the HFD+RIM group, but not in the HFD+PL group. We also found a positive correlation between CEACAM-1 and the insulin-degrading enzyme IDE with ADRs. Interestingly, expression of liver genes regulated by adiponectin and involved in lipid oxidation were increased in the HFD+RIM group. We conclude that in fat-fed dogs RIM enhances HIC, which appears to be linked to an upregulation of the adiponectin pathway.

High-fat diet-induced insulin resistance does not increase plasma anandamide levels or potentiate anandamide insulinotropic effect in isolated canine islets.

BACKGROUND: Obesity has been associated with elevated plasma anandamide levels. In addition, anandamide has been shown to stimulate insulin secretion in vitro, suggesting that anandamide might be linked to hyperinsulinemia. OBJECTIVE: To determine whether high-fat diet-induced insulin resistance increases anandamide levels and potentiates the insulinotropic effect of anandamide in isolated pancreatic islets. DESIGN AND METHODS: Dogs were fed a high-fat diet (n = 9) for 22 weeks. Abdominal fat depot was quantified by MRI. Insulin sensitivity was assessed by the euglycemic-hyperinsulinemic clamp. Fasting plasma endocannabinoid levels were analyzed by liquid chromatography-mass spectrometry. All metabolic assessments were performed before and after fat diet regimen. At the end of the study, pancreatic islets were isolated prior to euthanasia to test the in vitro effect of anandamide on islet hormones. mRNA expression of cannabinoid receptors was determined in intact islets. The findings in vitro were compared with those from animals fed a control diet (n = 7). RESULTS: Prolonged fat feeding increased abdominal fat content by 81.3±21.6% (mean±S.E.M, P<0.01). In vivo insulin sensitivity decreased by 31.3±12.1% (P<0.05), concomitant with a decrease in plasma 2-arachidonoyl glycerol (from 39.1±5.2 to 15.7±2.0 nmol/L) but not anandamide, oleoyl ethanolamide, linoleoyl ethanolamide, or palmitoyl ethanolamide. In control-diet animals (body weight: 28.8±1.0 kg), islets incubated with anandamide had a higher basal and glucose-stimulated insulin secretion as compared with no treatment. Islets from fat-fed animals (34.5±1.3 kg; P<0.05 versus control) did not exhibit further potentiation of anandamide-induced insulin secretion as compared with control-diet animals. Glucagon but not somatostatin secretion in vitro was also increased in response to anandamide, but there was no difference between groups (P = 0.705). No differences in gene expression of CB1R or CB2R between groups were found. CONCLUSIONS: In canines, high-fat diet-induced insulin resistance does not alter plasma anandamide levels or further potentiate the insulinotropic effect of anandamide in vitro.

Increase in visceral fat per se does not induce insulin resistance in the canine model.

OBJECTIVES: To determine whether a selective increase of visceral adipose tissue content will result in insulin resistance. METHODS: Sympathetic denervation of the omental fat was performed under general inhalant anesthesia by injecting 6-hydroxydopamine in the omental fat of lean mongrel dogs (n = 11). In the conscious animal, whole-body insulin sensitivity was assessed by the minimal model (SI ) and the euglycemic hyperinsulinemic clamp (SICLAMP ). Changes in abdominal fat were monitored by magnetic resonance. All assessments were determined before (Wk0) and 2 weeks (Wk2) after denervation. Data are medians (upper and lower interquartile). RESULTS: Denervation of omental fat resulted in increased percentage (and content) of visceral fat [Wk0: 10.2% (8.5-11.4); Wk2: 12.4% (10.4-13.6); P < 0.01]. Abdominal subcutaneous fat remained unchanged. However, no changes were found in SI [Wk0: 4.7 (mU/l)(-1) min(-1) (3.1-8.8); Wk2: 5.3 (mU/l)(-1) min(-1) (4.5-7.2); P = 0.59] or SICLAMP [Wk0: 42.0 × 10(-4) dl kg(-1) min(-1) (mU/l)(-1) (41.0-51.0); Wk2: 40.0 × 10(-4) dl kg(-1) min(-1) (mU/l) (-1) (34.0-52.0); P = 0.67]. CONCLUSIONS: Despite a selective increase in visceral adiposity in dogs, insulin sensitivity in vivo did not change, which argues against the concept that accumulation of visceral adipose tissue contributes to insulin resistance.

Obesity, insulin resistance and comorbidities? Mechanisms of association.

Overall excess of fat, usually defined by the body mass index, is associated with metabolic (e.g. glucose intolerance, type 2 diabetes mellitus (T2DM), dyslipidemia) and non-metabolic disorders (e.g. neoplasias, polycystic ovary syndrome, non-alcoholic fat liver disease, glomerulopathy, bone fragility etc.). However, more than its total amount, the distribution of adipose tissue throughout the body is a better predictor of the risk to the development of those disorders. Fat accumulation in the abdominal area and in non-adipose tissue (ectopic fat), for example, is associated with increased risk to develop metabolic and non-metabolic derangements. On the other hand, observations suggest that individuals who present peripheral adiposity, characterized by large hip and thigh circumferences, have better glucose tolerance, reduced incidence of T2DM and of metabolic syndrome. Insulin resistance (IR) is one of the main culprits in the association between obesity, particularly visceral, and metabolic as well as non-metabolic diseases. In this review we will highlight the current pathophysiological and molecular mechanisms possibly involved in the link between increased VAT, ectopic fat, IR and comorbidities. We will also provide some insights in the identification of these abnormalities.

Obesity, insulin resistance and comorbidities ? Mechanisms of association / Obesidade, resistência à insulina e comorbidades ? Mecanismos de associação

Overall excess of fat, usually defined by the body mass index, is associated with metabolic (e.g. glucose intolerance, type 2 diabetes mellitus (T2DM), dyslipidemia) and non-metabolic disorders (e.g. neoplasias, polycystic ovary syndrome, non-alcoholic fat liver disease, glomerulopathy, bone fragility etc.). However, more than its total amount, the distribution of adipose tissue throughout the body is a better predictor of the risk to the development of those disorders. Fat accumulation in the abdominal area and in non-adipose tissue (ectopic fat), for example, is associated with increased risk to develop metabolic and non-metabolic derangements. On the other hand, observations suggest that individuals who present peripheral adiposity, characterized by large hip and thigh circumferences, have better glucose tolerance, reduced incidence of T2DM and of metabolic syndrome. Insulin resistance (IR) is one of the main culprits in the association between obesity, particularly visceral, and metabolic as well as non-metabolic diseases. In this review we will highlight the current pathophysiological and molecular mechanisms possibly involved in the link between increased VAT, ectopic fat, IR and comorbidities. We will also provide some insights in the identification of these abnormalities. Arq Bras Endocrinol Metab. 2014;58(6):600-9.

Excesso de gordura, geralmente definido pelo índice de massa corporal, está associado a distúrbios metabólicos (p. ex., intolerância à glicose, diabetes melito tipo 2 (DM2), dislipidemia) e não metabólicos (p. ex., neoplasias, síndrome dos ovários policísticos, esteatose hepática não alcoólica, glomerulopatia, fragilidade óssea etc.). No entanto, mais do que sua quantidade total, a forma da distribuição corporal de tecido adiposo constitui-se em um melhor indicador de risco para o desenvolvimento de tais doenças. O acúmulo de gordura na região abdominal e em tecido não adiposo (gordura ectópica), por exemplo, está associado ao aumento de risco para distúrbios metabólicos e não metabólicos. Por outro lado, observações sugerem que os indivíduos que apresentam adiposidade periférica, caracterizada por aumento das circunferências dos quadris e da coxas, têm melhor tolerância à glicose, redução das incidências de DM2 e da síndrome metabólica. Uma das alterações subjacentes na relação entre a obesidade, particularmente a visceral, e os distúrbios citados é a resistência à insulina. Nesta revisão, enfatizaremos os mecanismos fisiopatológicos e moleculares possivelmente implicados na ligação entre o aumento das gorduras visceral e ectópica, IR e comorbidades. Também mencionaremos os métodos diagnósticos mais frequentemente usados na identificação dessas anormalidades. Arq Bras Endocrinol Metab. 2014;58(6):600-9.

Systems analysis and the prediction and prevention of Type 2 diabetes mellitus.

Prevalence of Type 2 diabetes has increased at an alarming rate, highlighting the need to correctly predict the development of this disease in order to allow intervention and thus, slow progression of the disease and resulting metabolic derangement. There have been many recent 'advances' geared toward the detection of pre-diabetes, including genome wide association studies and metabolomics. Although these approaches generate a large amount of data with a single blood sample, studies have indicated limited success using genetic and metabolomics information alone for identification of disease risk. Clinical assessment of the disposition index (DI), based on the hyperbolic law of glucose tolerance, is a powerful predictor of Type 2 diabetes, but is not easily assessed in the clinical setting. Thus, it is evident that combining genetic or metabolomic approaches for a more simple assessment of DI may provide a useful tool to identify those at highest risk for Type 2 diabetes, allowing for intervention and prevention.

Hepatic insulin clearance is the primary determinant of insulin sensitivity in the normal dog.

OBJECTIVE: Insulin resistance is a powerful risk factor for Type 2 diabetes and a constellation of chronic diseases, and is most commonly associated with obesity. We examined if factors other than obesity are more substantial predictors of insulin sensitivity under baseline, nonstimulated conditions. METHODS: Metabolic assessment was performed in healthy dogs (n = 90). Whole-body sensitivity from euglycemic clamps (SICLAMP ) was the primary outcome variable, and was measured independently by IVGTT (n = 36). Adiposity was measured by MRI (n = 90), and glucose-stimulated insulin response was measured from hyperglycemic clamp or IVGTT (n = 86 and 36, respectively). RESULTS: SICLAMP was highly variable (5.9-75.9 dl/min per kg per µU/ml). Despite narrow range of body weight (mean, 28.7 ± 0.3 kg), adiposity varied approximately eight-fold and was inversely correlated with SICLAMP (P < 0.025). SICLAMP was negatively associated with fasting insulin, but most strongly associated with insulin clearance. Clearance was the dominant factor associated with sensitivity (r = 0.53, P < 0.00001), whether calculated from clamp or IVGTT. CONCLUSIONS: These data suggest that insulin clearance contributes substantially to insulin sensitivity, and may be pivotal in understanding the pathogenesis of insulin resistance. We propose the hyperinsulinemia due to reduction in insulin clearance is responsible for insulin resistance secondary to changes in body weight.

Failure of homeostatic model assessment of insulin resistance to detect marked diet-induced insulin resistance in dogs.

Accurate quantification of insulin resistance is essential for determining efficacy of treatments to reduce diabetes risk. Gold-standard methods to assess resistance are available (e.g., hyperinsulinemic clamp or minimal model), but surrogate indices based solely on fasting values have attractive simplicity. One such surrogate, the homeostatic model assessment of insulin resistance (HOMA-IR), is widely applied despite known inaccuracies in characterizing resistance across groups. Of greater significance is whether HOMA-IR can detect changes in insulin sensitivity induced by an intervention. We tested the ability of HOMA-IR to detect high-fat diet-induced insulin resistance in 36 healthy canines using clamp and minimal model analysis of the intravenous glucose tolerance test (IVGTT) to document progression of resistance. The influence of pancreatic function on HOMA-IR accuracy was assessed using the acute insulin response during the IVGTT (AIRG). Diet-induced resistance was confirmed by both clamp and minimal model (P < 0.0001), and measures were correlated with each other (P = 0.001). In striking contrast, HOMA-IR ([fasting insulin (µU/mL) × fasting glucose (mmol)]/22.5) did not detect reduced sensitivity induced by fat feeding (P = 0.22). In fact, 13 of 36 animals showed an artifactual decrease in HOMA-IR (i.e., increased sensitivity). The ability of HOMA-IR to detect diet-induced resistance was particularly limited under conditions when insulin secretory function (AIRG) is less than robust. In conclusion, HOMA-IR is of limited utility for detecting diet-induced deterioration of insulin sensitivity quantified by glucose clamp or minimal model. Caution should be exercised when using HOMA-IR to detect insulin resistance when pancreatic function is compromised. It is necessary to use other accurate indices to detect longitudinal changes in insulin resistance with any confidence.

Mechanisms underlying restoration of hepatic insulin sensitivity with CB1 antagonism in the obese dog model.

Visceral fat has long been associated with the development of insulin resistance. Although the mechanism is not well understood, it has been suggested that an increase in this fat depot results in an elevation in portal vein levels of free fatty acids and/or adipokines, adversely affecting hepatic glucose production. Overactivity of the endocannabinoid system is closely related to abdominal obesity and type 2 diabetes, suggesting CB1 receptor antagonism may exert its beneficial effects by decreasing visceral fat mass. A recent study published from our laboratory explores the role of chronic CB1 receptor antagonism and the longitudinal changes in insulin sensitivity and fat deposition in the canine model.

CB(1) antagonism restores hepatic insulin sensitivity without normalization of adiposity in diet-induced obese dogs.

The endocannabinoid system is highly implicated in the development of insulin resistance associated with obesity. It has been shown that antagonism of the CB(1) receptor improves insulin sensitivity (S(I)). However, it is unknown whether this improvement is due to the direct effect of CB(1) blockade on peripheral tissues or secondary to decreased fat mass. Here, we examine in the canine dog model the longitudinal changes in S(I) and fat deposition when obesity was induced with a high-fat diet (HFD) and animals were treated with the CB(1) antagonist rimonabant. S(I) was assessed (n = 20) in animals fed a HFD for 6 wk to establish obesity. Thereafter, while HFD was continued for 16 additional weeks, animals were divided into two groups: rimonabant (1.25 mg·kg(-1)·day(-1) RIM; n = 11) and placebo (n = 9). Euglycemic hyperinsulinemic clamps were performed to evaluate changes in insulin resistance and glucose turnover before HFD (week -6) after HFD but before treatment (week 0) and at weeks 2, 6, 12, and 16 of treatment (or placebo) + HFD. Magnetic resonance imaging was performed to determine adiposity- related changes in S(I). Animals developed significant insulin resistance and increased visceral and subcutaneous adiposity after 6 wk of HFD. Treatment with RIM resulted in a modest decrease in total trunk fat with relatively little change in peripheral glucose uptake. However, there was significant improvement in hepatic insulin resistance after only 2 wk of RIM treatment with a concomitant increase in plasma adiponectin levels; both were maintained for the duration of the RIM treatment. CB(1) receptor antagonism appears to have a direct effect on hepatic insulin sensitivity that may be mediated by adiponectin and independent of pronounced reductions in body fat. However, the relatively modest effect on peripheral insulin sensitivity suggests that significant improvements may be secondary to reduced fat mass.

Simplified method to isolate highly pure canine pancreatic islets.

OBJECTIVES: The canine model has been used extensively to improve the human pancreatic islet isolation technique. At the functional level, dog islets show high similarity to human islets and thus can be a helpful tool for islet research. We describe and compare 2 manual isolation methods, M1 (initial) and M2 (modified), and analyze the variables associated with the outcomes, including islet yield, purity, and glucose-stimulated insulin secretion (GSIS). METHODS: Male mongrel dogs were used in the study. M2 (n = 7) included higher collagenase concentration, shorter digestion time, faster shaking speed, colder purification temperature, and higher differential density gradient than M1 (n = 7). RESULTS: Islet yield was similar between methods (3111.0 ± 309.1 and 3155.8 ± 644.5 islets/g, M1 and M2, respectively; P = 0.951). Pancreas weight and purity together were directly associated with the yield (adjusted R(2) = 0.61; P = 0.002). Purity was considerably improved with M2 (96.7% ± 1.2% vs 75.0% ± 6.3%; P = 0.006). M2 improved GSIS (P = 0.021). Independently, digestion time was inversely associated with GSIS. CONCLUSIONS: We describe an isolation method (M2) to obtain a highly pure yield of dog islets with adequate ß-cell glucose responsiveness. The isolation variables associated with the outcomes in our canine model confirm previous reports in other species, including humans.

Large size cells in the visceral adipose depot predict insulin resistance in the canine model.

Adipocyte size plays a key role in the development of insulin resistance. We examined longitudinal changes in adipocyte size and distribution in visceral (VIS) and subcutaneous (SQ) fat during obesity-induced insulin resistance and after treatment with CB-1 receptor antagonist, rimonabant (RIM) in canines. We also examined whether adipocyte size and/or distribution is predictive of insulin resistance. Adipocyte morphology was assessed by direct microscopy and analysis of digital images in previously studied animals 6 weeks after high-fat diet (HFD) and 16 weeks of HFD + placebo (PL; n = 8) or HFD + RIM (1.25 mg/kg/day; n = 11). At 6 weeks, mean adipocyte diameter increased in both depots with a bimodal pattern only in VIS. Sixteen weeks of HFD+PL resulted in four normally distributed cell populations in VIS and a bimodal pattern in SQ. Multilevel mixed-effects linear regression with random-effects model of repeated measures showed that size combined with share of adipocytes >75 µm in VIS only was related to hepatic insulin resistance. VIS adipocytes >75 µm were predictive of whole body and hepatic insulin resistance. In contrast, there was no predictive power of SQ adipocytes >75 µm regarding insulin resistance. RIM prevented the formation of large cells, normalizing to pre-fat status in both depots. The appearance of hypertrophic adipocytes in VIS is a critical predictor of insulin resistance, supporting the deleterious effects of increased VIS adiposity in the pathogenesis of insulin resistance.

Consistency of the disposition index in the face of diet induced insulin resistance: potential role of FFA.

OBJECTIVE: Insulin resistance induces hyperinsulinemic compensation, which in turn maintains almost a constant disposition index. However, the signal that gives rise to the hyperinsulinemic compensation for insulin resistance remains unknown. METHODS: In a dog model of obesity we examined the possibility that potential early-week changes in plasma FFA, glucose, or both could be part of a cascade of signals that lead to compensatory hyperinsulinemia induced by insulin resistance. RESULTS: Hypercaloric high fat feeding in dogs resulted in modest weight gain, and an increase in adipose tissue with no change in the non-adipose tissue size. To compensate for the drop in insulin sensitivity, there was a significant rise in plasma insulin, which can be attributed in part to a decrease in the metabolic clearance rate of insulin and increased insulin secretion. In this study we observed complete compensation for high fat diet induced insulin resistance as measured by the disposition index. The compensatory hyperinsulinemia was coupled with significant changes in plasma FFAs and no change in plasma glucose. CONCLUSIONS: We postulate that early in the development of diet induced insulin resistance, a change in plasma FFAs may directly, through signaling at the level of ß-cell, or indirectly, by decreasing hepatic insulin clearance, result in the observed hyperinsulinemic compensation.

Rimonabant prevents additional accumulation of visceral and subcutaneous fat during high-fat feeding in dogs.

We investigated whether rimonabant, a type 1 cannabinoid receptor antagonist, reduces visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in dogs maintained on a hypercaloric high-fat diet (HHFD). To determine whether energy expenditure contributed to body weight changes, we also calculated resting metabolic rate. Twenty male dogs received either rimonabant (1.25 mg.kg(-1).day(-1), orally; n = 11) or placebo (n = 9) for 16 wk, concomitant with a HHFD. VAT, SAT, and nonfat tissue were measured by magnetic resonance imaging. Resting metabolic rate was assessed by indirect calorimetry. By week 16 of treatment, rimonabant dogs lost 2.5% of their body weight (P = 0.029), whereas in placebo dogs body weight increased by 6.2% (P < 0.001). Rimonabant reduced food intake (P = 0.027), concomitant with a reduction of SAT by 19.5% (P < 0.001). In contrast with the VAT increase with placebo (P < 0.01), VAT did not change with rimonabant. Nonfat tissue remained unchanged in both groups. Body weight loss was not associated with either resting metabolic rate (r(2) = 0.24; P = 0.154) or food intake (r(2) = 0.24; P = 0.166). In conclusion, rimonabant reduced body weight together with a reduction in abdominal fat, mainly because of SAT loss. Body weight changes were not associated with either resting metabolic rate or food intake. The findings provide evidence of a peripheral effect of rimonabant to reduce adiposity and body weight, possibly through a direct effect on adipose tissue.