scholarly journals Regulation of Energy Balance and Body Weight by the Brain: A Distributed System Prone to Disruption

2011 ◽  
Vol 34 (4) ◽  
pp. 733-745 ◽  
Author(s):  
Lucy F. Faulconbridge ◽  
Matthew R. Hayes
Keyword(s):  
Body Weight ◽  
Energy Balance ◽  
Distributed System ◽  
The Brain

scholarly journals Effect of selective expression of dominant-negative PPARγ in pro-opiomelanocortin neurons on the control of energy balance

2016 ◽  
Vol 48 (7) ◽  
pp. 491-501 ◽  
Author(s):  
Madeliene Stump ◽  
Deng-Fu Guo ◽  
Ko-Ting Lu ◽  
Masashi Mukohda ◽  
Xuebo Liu ◽  
...  
Keyword(s):  
Body Weight ◽  
Weight Gain ◽  
Energy Balance ◽  
High Fat Diet ◽  
Control Diet ◽  
Cre Recombinase ◽  
Dominant Negative ◽  
High Fat ◽  
Pparγ Agonist ◽  
The Brain

Peroxisome proliferator-activated receptor-γ (PPARγ), a master regulator of adipogenesis, was recently shown to affect energy homeostasis through its actions in the brain. Deletion of PPARγ in mouse brain, and specifically in the pro-opiomelanocortin (POMC) neurons, results in resistance to diet-induced obesity. To study the mechanisms by which PPARγ in POMC neurons controls energy balance, we constructed a Cre-recombinase-dependent conditionally activatable transgene expressing either wild-type (WT) or dominant-negative (P467L) PPARγ and the tdTomato reporter. Inducible expression of both forms of PPARγ was validated in cells in culture, in liver of mice infected with an adenovirus expressing Cre-recombinase (AdCre), and in the brain of mice expressing Cre-recombinase either in all neurons (NESCre/PPARγ-P467L) or selectively in POMC neurons (POMCCre/PPARγ-P467L). Whereas POMCCre/PPARγ-P467L mice exhibited a normal pattern of weight gain when fed 60% high-fat diet, they exhibited increased weight gain and fat mass accumulation in response to a 10% fat isocaloric-matched control diet. POMCCre/PPARγ-P467L mice were leptin sensitive on control diet but became leptin resistant when fed 60% high-fat diet. There was no difference in body weight between POMCCre/PPARγ-WT mice and controls in response to 60% high-fat diet. However, POMCCre/PPARγ-WT, but not POMCCre/PPARγ-P467L, mice increased body weight in response to rosiglitazone, a PPARγ agonist. These observations support the concept that alterations in PPARγ-driven mechanisms in POMC neurons can play a role in the regulation of metabolic homeostasis under certain dietary conditions.

scholarly journals Kisspeptin and energy balance in reproduction

Reproduction ◽  
2014 ◽  
Vol 147 (3) ◽  
pp. R53-R63 ◽  
Author(s):  
Julie-Ann P De Bond ◽  
Jeremy T Smith
Keyword(s):  
Body Weight ◽  
Energy Balance ◽  
Arcuate Nucleus ◽  
Reproductive Function ◽  
Neuroendocrine Regulation ◽  
Direct Role ◽  
Gnrh Neurons ◽  
The Brain ◽  
Direct Regulator

Kisspeptin is vital for the neuroendocrine regulation of GNRH secretion. Kisspeptin neurons are now recognized as a central pathway responsible for conveying key homeostatic information to GNRH neurons. This pathway is likely to mediate the well-established link between energy balance and reproductive function. Thus, in states of severely altered energy balance (either negative or positive), fertility is compromised, as isKiss1expression in the arcuate nucleus. A number of metabolic modulators have been proposed as regulators of kisspeptin neurons including leptin, ghrelin, pro-opiomelanocortin (POMC), and neuropeptide Y (NPY). Whether these regulate kisspeptin neurons directly or indirectly will be discussed. Moreover, whether the stimulatory role of leptin on reproduction is mediated by kisspeptin directly will be questioned. Furthermore, in addition to being expressed in GNRH neurons, the kisspeptin receptor (Kiss1r) is also expressed in other areas of the brain, as well as in the periphery, suggesting alternative roles for kisspeptin signaling outside of reproduction. Interestingly, kisspeptin neurons are anatomically linked to, and can directly excite, anorexigenic POMC neurons and indirectly inhibit orexigenic NPY neurons. Thus, kisspeptin may have a direct role in regulating energy balance. Although data fromKiss1rknockout and WT mice found no differences in body weight, recent data indicate that kisspeptin may still play a role in food intake and glucose homeostasis. Thus, in addition to regulating reproduction, and mediating the effect of energy balance on reproductive function, kisspeptin signaling may also be a direct regulator of metabolism.

scholarly journals The Role of Hypothalamic Tri-Iodothyronine Availability in Seasonal Regulation of Energy Balance and Body Weight

2011 ◽  
Vol 2011 ◽  
pp. 1-7 ◽  
Author(s):  
Michelle Murphy ◽  
Francis J. P. Ebling
Keyword(s):  
Body Weight ◽  
Thyroid Hormone ◽  
Energy Balance ◽  
Third Ventricle ◽  
Peripheral Circulation ◽  
Brain Cell ◽  
Monocarboxylate Transporter ◽  
Type Iii ◽  
Seasonal Regulation ◽  
The Brain

Seasonal cycles of body weight provide a natural model system to understand the central control of energy balance. Studies of such cycles in Siberian hamsters suggest that a change in the hypothalamic availability of thyroid hormone is the key determinant of annual weight regulation. Uptake of thyroid hormone into the hypothalamus from the peripheral circulation occurs largely through a specific monocarboxylate transporter expressed by tanycyte cells lining the third ventricle. Tanycytes are the principal brain cell type expressing type II and type III deiodinases, so they control the local concentrations of T4, T3, and inactive metabolites. Type III deiodinase mRNA in tanycytes is photoperiodically upregulated in short photoperiod. This would be expected to reduce the availability of T3 in the hypothalamus by promoting the production of inactive metabolites such as rT3. Experimental microimplantation of T3 directly into the hypothalamus during short-days promotes a long-day phenotype by increasing food intake and body weight without affecting the peripheral thyroid axis. Thus, thyroid hormone exerts anabolic actions within the brain that play a key role in the seasonal regulation of body weight. Understanding the precise actions of thyroid hormone in the brain may identify novel targets for long-term pharmacological manipulation of body weight.

Role of the brain in energy balance and obesity

1996 ◽  
Vol 271 (3) ◽  
pp. R491-R500 ◽  
Author(s):  
B. E. Levin ◽  
V. H. Routh
Keyword(s):  
Nervous System ◽  
Body Weight ◽  
Energy Balance ◽  
The Body ◽  
Metabolic Efficiency ◽  
Recidivism Rate ◽  
Consistent Finding ◽  
Set Point ◽  
And Storage ◽  
The Brain

Energy balance and body weight are regulated in short, intermediate, and long cycles that are superimposed on each other. We propose that the brain is the primary center of this regulation. The brain has evolved mechanisms for sensing the energy status of the body using neural and metabolic signals such as glucose, insulin, and leptin. It has central processing and storage capacity for handling this afferent information and can change both structurally and functionally in response to its internal and external milieu. The brain regulates energy balance through its control of energy intake on the one hand and expenditure and storage on the other using neurohumoral mechanisms that include the autonomic nervous system. Work in animal models suggests that the brain of obese individuals largely ignores signals of excess adiposity from the periphery, keeping the body weight set point at pathologically high levels. Disordered regulation of neuropeptide Y and monoamine metabolism within the ventromedial hypothalamus is a consistent finding in the brains of obesity-prone and obese rodents. Such dysregulation causes inappropriate neurohumoral control of metabolism and autonomic output to organs such as the pancreas, resulting in increased metabolic efficiency and persistent adiposity. The high recidivism rate in the treatment of obesity suggests that central dysfunction may be due to long-term reorganization of the nervous system in such a way as to perpetuate the abnormally high set point of body weight.

scholarly journals A multi-component screen for feeding behaviour and nutritional status in Drosophila to interrogate mammalian appetite-related genes

2020 ◽  
Author(s):  
J Chalmers ◽  
YCL Tung ◽  
CH Liu ◽  
CJ O’Kane ◽  
S O’Rahilly ◽  
...  
Keyword(s):  
Body Weight ◽  
Energy Balance ◽  
Food Intake ◽  
High Throughput ◽  
Feeding Behaviour ◽  
Nutrient Status ◽  
Fruit Fly ◽  
Model System ◽  
Genome Wide Association Studies ◽  
The Brain

AbstractMore than 300 genetic variants have been robustly associated with measures of human adiposity. Highly penetrant mutations causing human obesity do so largely by disrupting satiety pathways in the brain and increasing food intake. Most of the common obesity-predisposing variants are in, or near, genes that are expressed highly in the brain, but little is known about their function. Exploring the biology of these genes at scale in mammalian systems is challenging. We therefore sought to establish and validate the use of a multicomponent screen for feeding behaviour and nutrient status taking advantage of the tractable model organism Drosophila melanogaster. We validated our screen by demonstrating its ability to distinguish the effect of disrupting neuronal expression of four genes known to influence energy balance in flies from ten control genes. We then used our screen to interrogate two genetic data sets. Firstly, we investigated 53 genes that have been implicated in energy homeostasis by human genome wide association studies (GWASs): of the 53 Drosophila orthologues studied, we found that 16 significantly influenced feeding behaviour or nutrient status. Secondly, we looked at genes which are expressed and nutritionally responsive in specific populations of hypothalamic neurons involved in feeding/fasting (POMC and AgRP neurons): 50 Drosophila orthologues of 47 murine genes were studied, and 10 found by our screen to influence feeding behaviour or nutrient status in flies. In conclusion, Drosophila provide a valuable model system for high throughput interrogation of genes implicated in feeding behaviour and obesity in mammals.Author SummaryNew high-throughput technologies have resulted in large numbers of candidate genes that are potentially involved in the control of food intake and body-weight, many of which are highly expressed in the brain. How, though, are we to find the functionally most relevant genes from these increasingly long lists? Appetite needs to be explored in context of a whole animal, but studies in humans and mice take a long time and are expensive. The fruit fly, while clearly evolutionarily distant, shares a surprising amount of biology with mammals, with 75% of genes involved in inherited human diseases having an equivalent in flies. In particular, the fruit fly has surprisingly conserved neuronal circuitry when it comes to food intake. Here we have developed a suite of four different functional assays for studying the feeding behaviour and energy balance in flies. We then used these assays to explore the effects of disrupting the expression of genes in the neurons of flies, that either are implicated in body weight through human genetic studies or are expressed and nutritionally responsive in specific populations of neurons involved in feeding. We show that the use of fruit flies are time and cost efficient, and are a valuable model system for studying genes implicated in feeding behaviour and obesity in mammals.

ICI 182,780 antagonizes the effects of estradiol on estrous behavior and energy balance in Syrian hamsters

1993 ◽  
Vol 265 (6) ◽  
pp. R1399-R1403 ◽  
Author(s):  
G. N. Wade ◽  
J. B. Powers ◽  
J. D. Blaustein ◽  
D. E. Green
Keyword(s):  
Body Weight ◽  
Energy Balance ◽  
Food Intake ◽  
Fat Content ◽  
Estradiol Treatment ◽  
Syrian Hamsters ◽  
Ici 182,780 ◽  
The Brain ◽  
Estrous Behavior

Three experiments examined the effects of ICI 182,780, a steroidal "pure" antiestrogen that is thought to be active peripherally but not in the brain when given systemically, on energy balance, estrous behavior, and in vivo cell nuclear binding of [3H]estradiol in Syrian hamsters. Pretreatment with ICI 182,780 reduced in vivo uptake of [3H]estradiol in uterus but not in pooled hypothalamus-preoptic area. Ovariectomized Syrian hamsters were treated with estradiol benzoate (EB, 5 micrograms/day), ICI 182,780 (250 micrograms/day), or both EB and ICI 182,780 for 4 wk. Estradiol treatment caused significant decreases in food intake, body weight and fat content, and linear growth. Given alone, ICI 182,780 had no effect on these measures. When they were given concurrently, ICI 182,780 attenuated the effects of estradiol on body weight, growth, and fat content but not on food intake. Treatment with ICI 182,780 significantly diminished estrous behavior induced with either EB plus progesterone or with EB alone. These findings support the hypothesis that, in addition to its actions in the brain, estradiol acts peripherally to modulate estrous behavior and energy balance.

scholarly journals Leptin-mediated suppression of food intake by conserved Glp1r-expressing neurons prevents obesity

2021 ◽  
Author(s):  
Alan C. Rupp ◽  
Abigail J. Tomlinson ◽  
Alison H. Affinati ◽  
Cadence True ◽  
Sarah R. Lindsley ◽  
...  
Keyword(s):  
Body Weight ◽  
Energy Balance ◽  
Food Intake ◽  
Energy Expenditure ◽  
Mammalian Species ◽  
Neuron Population ◽  
Unbiased Manner ◽  
Hypothalamic Cells ◽  
Single Nucleus ◽  
The Brain

AbstractThe adipose-derived hormone leptin acts via its receptor (LepRb) in the brain to control energy balance. A previously unidentified population of GABAergic hypothalamic LepRb neurons plays key roles in the restraint of food intake and body weight by leptin. To identify markers for candidate populations of LepRb neurons in an unbiased manner, we performed single-nucleus RNA-sequencing of enriched mouse hypothalamic LepRb cells, as well as with total hypothalamic cells from multiple mammalian species. In addition to identifying known LepRb neuron types, this analysis identified several previously unrecognized populations of hypothalamic LepRb neurons. Many of these populations display strong conservation across species, including GABAergic Glp1r-expressing LepRb (LepRbGlp1r) neurons that express more Lepr and respond more robustly to exogenous leptin than other LepRb populations. Ablating LepRb from these cells provoked hyperphagic obesity without impairing energy expenditure. Conversely, reactivating LepRb in Glp1r-expressing cells decreased food intake and body weight in otherwise LepRb-null mice. Furthermore, LepRb reactivation in GABA neurons improved energy balance in LepRb-null mice, and this effect required the expression of LepRb in GABAergic Glp1r-expressing neurons. Thus, the conserved GABAergic LepRbGlp1r neuron population plays crucial roles in the control of food intake and body weight by leptin.

Insulin and central regulation of spontaneous fattening and weight loss

1985 ◽  
Vol 249 (2) ◽  
pp. R203-R208
Author(s):  
R. B. Melnyk ◽  
J. M. Martin
Keyword(s):  
Weight Loss ◽  
Body Weight ◽  
Weight Gain ◽  
Energy Balance ◽  
Binding Capacity ◽  
Insulin Receptors ◽  
Insulin Binding ◽  
Strong Positive Correlation ◽  
Central Regulation ◽  
Isolated Pancreatic Islets

Insulin binding to receptors in a partially purified hypothalamic membrane preparation is altered by prolonged starvation. To define further the relationship between hypothalamic insulin binding and energy balance, we studied the Richardson's ground squirrel, a hibernator that exhibits spontaneous 6- to 8-mo body weight cycles when kept in constant conditions. Isolated pancreatic islets from squirrels killed during the weight gain phase had greater glucose-stimulated insulin secretion than those from weight loss phase animals, and adipocytes showed significantly greater glucose incorporation into total lipid in response to insulin. Differences in lipogenesis were not attributable to changes in insulin-binding capacity. Hypothalamic tissue from weight gain phase animals bound more insulin than that from weight loss phase animals. Maximal binding was correlated with pancreatic islet responsiveness and maximal insulin-stimulated lipogenesis. The strong positive correlation between peripheral metabolic events associated with spontaneous alterations in energy balance and the binding kinetics of hypothalamic insulin receptors suggests that insulin may play an important role in the central regulation of body weight.

scholarly journals Phenotyping Women Based on Dietary Macronutrients, Physical Activity, and Body Weight Using Machine Learning Tools

Nutrients ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1681 ◽  
Author(s):  
Ramyaa Ramyaa ◽  
Omid Hosseini ◽  
Giri P. Krishnan ◽  
Sridevi Krishnan
Keyword(s):  
Physical Activity ◽  
Machine Learning ◽  
Cluster Analysis ◽  
Body Weight ◽  
Energy Balance ◽  
Numerical Data ◽  
Support Vector ◽  
Learning Tools ◽  
K Nearest Neighbor ◽  
Numerical Predictions

Nutritional phenotyping can help achieve personalized nutrition, and machine learning tools may offer novel means to achieve phenotyping. The primary aim of this study was to use energy balance components, namely input (dietary energy intake and macronutrient composition) and output (physical activity) to predict energy stores (body weight) as a way to evaluate their ability to identify potential phenotypes based on these parameters. From the Women’s Health Initiative Observational Study (WHI OS), carbohydrates, proteins, fats, fibers, sugars, and physical activity variables, namely energy expended from mild, moderate, and vigorous intensity activity, were used to predict current body weight (both as body weight in kilograms and as a body mass index (BMI) category). Several machine learning tools were used for this prediction. Finally, cluster analysis was used to identify putative phenotypes. For the numerical predictions, the support vector machine (SVM), neural network, and k-nearest neighbor (kNN) algorithms performed modestly, with mean approximate errors (MAEs) of 6.70 kg, 6.98 kg, and 6.90 kg, respectively. For categorical prediction, SVM performed the best (54.5% accuracy), followed closely by the bagged tree ensemble and kNN algorithms. K-means cluster analysis improved prediction using numerical data, identified 10 clusters suggestive of phenotypes, with a minimum MAE of ~1.1 kg. A classifier was used to phenotype subjects into the identified clusters, with MAEs <5 kg for 15% of the test set (n = ~2000). This study highlights the challenges, limitations, and successes in using machine learning tools on self-reported data to identify determinants of energy balance.

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