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Enregistrement W2113834749 · doi:10.1038/oby.2006.316

From Fat to Full: Peripheral and Central Mechanisms Controlling Food Intake and Energy Balance: View from the Chair

2006· article· en· W2113834749 sur OpenAlexaffabout
Keith A. Sharkey

Notice bibliographique

RevueObesity · 2006
Typearticle
Langueen
DomaineNeuroscience
ThématiqueRegulation of Appetite and Obesity
Établissements canadiensInstitute of Infection and ImmunityUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésOverconsumptionEnergy balanceObesityParacrine signallingMedicineEnergy supplyAdipose tissueEnergy (signal processing)PhysiologyNeuroscienceEndocrinologyBiologyInternal medicineEconomicsEcology

Résumé

récupéré en direct d'OpenAlex

It is now well recognized that there are numerous peripheral and central signaling systems that regulate food intake and energy balance ((1), (2), (3), (4), (5)). Because food is ultimately the only source of energy, it follows that food intake must be carefully regulated: balancing hunger and the drive to eat with energy stores and metabolic demands to maintain adequate levels of energy to ensure survival. For most animals, the amount of available food is generally limited, and a long-term excess of stored energy is rarely observed. In the last 10 to 20 years in Western society, this has not been the case with regard to food supply. The availability of cheap, highly palatable, energy dense foods has led to an explosion in overconsumption. This, coupled with a general reduction in physical activity, has figured prominently in the rising prevalence of obesity, which has now reached “epidemic” proportions ((6)). In the final session of the symposium “The Neurobiology of Obesity,” the proceedings of which form this supplement of Obesity Research, four papers were presented that dealt with some of the regulatory systems that control food intake and energy balance. In this short overview, a perspective on these papers will be provided. In the first of these papers, Rexford Ahima outlines how adipose tissue—the primary energy store—is itself a regulatory system for energy balance. Adipose tissue responds to nutrients, neural, and hormonal signals with the release of hormones and paracrine signaling molecules, termed adipokines, that control food intake and energy metabolism, as well as immune and neuroendocrine function ((1)). Of the numerous adipokines now identified, leptin remains the principal signal of adiposity ((7)). Leptin is the product of the ob gene, and mice deficient in this gene display hyperphagia, massive obesity, and metabolic syndrome. If energy stores fall, for example, during fasting, leptin levels are reduced, and food intake is stimulated. In addition, a range of other energy-sparing metabolic and cellular processes are activated. The hypothalamus is probably the primary region where integration of leptin signaling occurs in the brain, but extrahypothalamic sites in the brainstem or midbrain that express leptin receptors may be important and, as pointed out by Ahima, have yet to be fully explored. The question of how peripherally released adipokines activate central neurons, remains to be fully elucidated. For leptin, the answer lies with transporters, not yet cloned and sequenced, located on the blood–brain barrier that allow it to enter the parenchyma intact ((8)). However, for many adipokines, transporters have been neither identified nor may even exist. Adiponectin is one such example. Adiponectin plays an important role in promoting insulin sensitivity, potentiates the effects of leptin, and when injected inside the brain, activates central neurons ((1), (9)). However, there is no evidence that it crosses the blood–brain barrier ((10), (11)). Currently, it is not resolved whether adiponectin acts in the brain under physiological conditions. However, resolution of this issue may lie in activation of neurons in circumventricular organs ((12))—central structures that lie outside of the blood–brain barrier—which activate other central neurons. Alternatively, adipokines may activate endothelial cells of brain microvessels, which release secondary mediators to activate neurons inside the blood–brain barrier ((11)). Future work that is directed at how peripheral signals activate central neurons remains a high priority. As noted above, animals (and humans) lacking a functional copy of the leptin gene become severely obese ((7)). However, in common forms of obesity, leptin levels are not reduced, but, in fact, are elevated. Hyperleptinemia in common obesity is not associated with reduced food intake or increased energy expenditure, suggesting that neurons become resistant to its actions. Leptin resistance is discussed by Enriori et al., who highlight recent data that shows resistance to leptin in the hypothalamic nuclei that coordinate the regulation of energy expenditure and food intake. Enriori et al. discuss the mechanisms of resistance in hypothalamic neurons, but as mentioned above, leptin requires a transporter to access the brain, and at least part of the resistance observed in obesity may at occur at this level. The cardiometabolic syndrome of obesity is also always associated with insulin resistance, and, like leptin, insulin also needs to be transported centrally to exert many of its actions ((5)). Convergent signaling pathways between leptin and insulin may explain these similarities ((5)) and require consideration to explain the reason why adiposity and other peripheral signals are not always “heard” in the obese state. Energy balance is not only regulated by signals from adipose tissue but also from the gastrointestinal tract ((2)). Peripheral signals arising from the gut are key elements in food intake regulation, as discussed by Timothy Moran. Gut peptides, released in response to luminal nutrients, signal short-term satiety, meal patterns, and energy balance over longer periods. A challenge remains to understand how these meal-stimulated signals are integrated with the adiposity signaling that occurs over a very different time-course. Perhaps the “set-point” of body weight and/or stored energy is the primary homeostat that other signals impinge on to allow optimal intake to occur; this is regulated carefully under conditions of optimal nutrition. However, the powerful higher brain centers involved in reward, social, and cognitive aspects of ingestion may override the homeostatic centers of the brainstem and hypothalamus and lead to overconsumption even in the face of normal regulatory signals. Potentially, the signals from the gut are directly linked to consumption, because they may be altered quantitatively or qualitatively by dietary or luminal factors or through actions in the periphery that alter the secretion of energy balance signals from adipocytes. For example, cholecystokinin (CCK),11 Nonstandard abbreviation: CCK, cholecystokinin. released as a short-term meal termination signal from the proximal intestine, may also alter leptin release by activating CCK2 receptors on adipocytes ((13)). Interestingly, the presence or absence of the stomach-colonizing bacterium Helicobacter pylori alters meal-stimulated levels of plasma leptin, CCK, and gastrin, and its eradication has been linked to increased appetite and alterations in gastric ghrelin expression ((14), (15), (16)). The brain–gut–adipocyte axis is complex, and unraveling the interrelationships of these various signaling systems remains a significant challenge. In the final paper in this section of the supplement, Jeff Tasker considers the effects of stress on feeding pathways. He shows the importance of glucocorticoids, in concert with endocannabinoids, in altering the function of hypothalamic integrative centers involved in energy balance. Glucocorticoids, released from the adrenal cortex, are potent stimulators of food intake. It has been recently shown in rats that glucocorticoids promote a shift in dietary intake from chow to highly palatable “comfort foods,” which in turn further suppress activation of the hypothalamic–pituitary–adrenal axis and reduce the peripheral and central responses to stressful stimuli ((17)). We live busy and stressful lives, and like laboratory rats, people also shift to eating sweet and savory comfort foods in times of stress if these foods are available (((17)), ((18))). Overconsumption of these foods may promote obesity even if they temporarily alleviate the stresses of daily life. The causes of obesity are complex and multifactorial. The brain–gut–adipocyte axis is central to the regulation and maintenance of body weight and food intake. As the papers following this perspective illustrate, we have made great strides in understanding the elements of this axis, but we are a long way yet from fully appreciating the subtle and complex nature of their interactions in the repertoire of homeostatic and non-homeostatic control of food intake and energy balance. K.A.S. is an Alberta Heritage Foundation for Medical Research Medical Scientist and the Crohn's and Colitis Foundation of Canada Chair in Inflammatory Bowel Disease Research at the University of Calgary. I thank Adam Chambers and Niall Hyland for valuable comments on the manuscript.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,631
Score d'incertitude au seuil0,494

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,011
Tête enseignante GPT0,206
Écart entre enseignants0,196 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2006
Routes d'admission2
Résumé présentoui

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