High-fat Environment Research Articles

Examining Pancreatic Islet Lipotoxicity Using Two-Photon NAD(P)H Imaging

Pancreatic islet β-cells maintain blood glucose through the regulated secretion of insulin. A rise in blood glucose stimulates production of NAD(P)H resulting in a cascade of increased ATP/ADP ratio, closure of ATP-sensitive potassium channels, membrane depolarization, Ca2+-influx, and insulin secretion. During the course of Type II diabetes, the glucose-stimulated insulin response is dampened by glucose and lipid toxicity. It has recently been shown that the novel endocrine factor, FGF21, protects metabolically active tissues such as liver and white adipose tissue (WAT) by regulating fatty acid metabolism. To test the effects of FGF21 on islet β-cells, we measured the levels of Acetyl-CoA carboxylase (ACC) in response to FGF21. ACC is an enzyme involved in the synthesis of malonyl-CoA, a substrate used in fatty acid synthesis and a regulator of fatty acid oxidation. Reducing ACC expression is critical to the normal compensation of beta-cells to lipid toxicity. We show that FGF21 decreases ACC protein levels in mouse pancreatic islets. To determine whether decreased ACC protein level acts as a protective mechanism in maintaining β-cell sensitivity to glucose, we examined changes in NAD(P)H by two photon microscopy of living islets held in a microfluidic device as a direct measure of changes in the metabolism. Our data reveals that compared to control islets, FGF21-treated islets retain the glucose-stimulated NAD(P)H response in a high fat environment. We will further examine the kinetics of the islet glucose response using time-lapse NAD(P)H imaging of islets. Overall, these studies will determine the metabolic changes that occur during the β-cell response to FGF21, and enhance understanding of how this effect can protect beta-cells from high fatty acid stress.

Adaptation and Maladaptation of the Heart in Obesity

Obesity affects the cardiovascular system at many different levels, including the heart muscle itself. Clinical and experimental studies have shown an accumulation of triglycerides and other lipid species in cardiomyocytes. Analogous to hepatic steatosis, investigators have introduced the term “cardiac steatosis”. The present review addresses the complex relationships between cardiac fuel homeostasis, insulin resistance, and proposed mechanisms of damage to cardiomyocytes in different models of obesity, insulin resistance, and lipotoxicity. Specifically, the review weighs the evidence whether there is a heart muscle disorder in human obesity. It discusses how adipokines can modulate cardiac metabolism, and it focuses on the metabolic remodeling accompanying increased fatty acid supply in the heart of rodent models of lipotoxicity, with special attention to the role played by mitochondrial uncoupling and futile cycling. We stress the notion that, in spite of the many proposed mechanisms, cardiac lipotoxicity is still a hypothesis rather than an established pathophysiologic principle. Although the concept of a “lipotoxic cardiomyopathy” seems attractive, we propose instead a series of steps on a path from adaptation to maladaptation of the heart in obesity. A case in point is insulin resistance of the heart which may be both adaptive (protecting the heart from excess fuel) or maladaptive (associated with reactive oxygen species formation and activation of signaling pathways of programmed cell death). The present literature reflects an extraordinary complexity of the heart’s metabolic, functional and structural changes in obesity.

Rhythm of the β-cell oscillator is not governed by a single regulator: multiple systems contribute to oscillatory behavior

Pulsatile insulin output, paralleled by oscillations in intracellular Ca(2+), reflect oscillating metabolism within beta-cells in response to secretory fuels. Here we question whether oscillatory periodicity is conserved or varied from stimulation to stimulation, whether glycolysis is essential for the manifestation of an oscillatory response, and if an environment of nutrient oversupply affects oscillatory regularity. We have determined that a beta-cell oscillatory Ca(2+) pattern is independent of the type of applied secretory fuel (glucose, methyl-pyruvate, or alpha-ketoisocaproate). In addition, single cells respond with the same pattern when repeatedly stimulated, regardless of the type of stimulatory fuel. Presence of substimulatory glucose is not necessary to obtain an oscillatory responses to methyl-pyruvate or alpha-ketoisocaproate. Glucose-6-phosphate, as a measure of glycolytic flux, is not detectable under these conditions. These data suggest that multiple systems, rather than a single enzyme component, can contribute to the beta-cell oscillatory behavior. Prolonged exposure to high levels of palmitate impaired oscillatory regularity in the individual beta-cells. This supports the hypothesis that a high-fat environment might contribute to loss of regular oscillatory pattern in diabetic subjects, acting, at least in part, at the level of the single beta-cell.

Evidence that multiple genes influence baseline concentrations and diet response of Lp(a) in baboons.

We investigated the response of lipoprotein(a) [Lp(a)] levels to dietary fat and cholesterol in 633 baboons fed a series of 3 diets: a basal diet low in cholesterol and fat, a high-fat diet, and a diet high in fat and cholesterol. Measurement of serum concentrations in samples taken while the baboons were sequentially fed the 3 diets allowed us to analyze 3 Lp(a) variables: Lp(a)(Basal), Lp(a)(RF) (response to increased dietary fat), and Lp(a)(RC) (response to increased dietary cholesterol in the high-fat environment). On average, Lp(a) concentrations significantly increased 6% and 28%, respectively, when dietary fat and cholesterol were increased (P<0.001). As expected, most of the variation in Lp(a)(Basal) was influenced by genes (h(2)=0.881). However, less than half of the variation in Lp(a)(RC) was influenced by genes (h(2)=0.347, P<0. 0001), whereas the increase due to dietary fat alone was not significantly heritable (h(2)=0.043, P=0.28). To determine whether Lp(a) phenotypic variation was due to variation in LPA, the locus encoding the apolipoprotein(a) [apo(a)] protein, we conducted linkage analyses by using LPA genotypes inferred from the apo(a) isoform phenotypes. All of the genetic variance in Lp(a)(Basal) concentration was linked to the LPA locus (log of the odds [LOD] score was 30.5). In contrast, linkage analyses revealed that genetic variance in Lp(a)(RC) was not linked to the LPA locus (LOD score was 0.036, P>0.5). To begin identifying the non-LPA genes that influence the Lp(a) response to dietary cholesterol, we tested, in bivariate quantitative genetic analyses, for correlation with low density lipoprotein cholesterol [LDLC; ie, non-high density lipoprotein cholesterol less the cholesterol contribution from Lp(a)]. LDLC(Basal) was weakly correlated with Lp(a)(Basal) (rho(P)=0.018). However, LDLC(RC) and Lp(a)(RC) were strongly correlated (rho(P)=0. 382), and partitioning the correlations revealed significant genetic and environmental correlations (rho(G)=0.587 and rho(E)=0.251, respectively). The results suggest that increasing both dietary fat and dietary cholesterol caused significant increases in Lp(a) concentrations and that the response to dietary cholesterol was mediated by a gene or suite of genes that appears to exert pleiotropic effects on LDLC levels as well. The gene(s) influencing Lp(a) response to dietary cholesterol is not linked to the LPA locus.