Disentangling discrete lateral hypothalamic circuits involved in feeding and obesity
解开与进食和肥胖有关的离散外侧下丘脑回路
基本信息
- 批准号:10441656
- 负责人:
- 金额:$ 24.9万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-08-01 至 2024-07-31
- 项目状态:已结题
- 来源:
- 关键词:AblationAcuteAffectAnatomyAppetitive BehaviorAreaAttenuatedBehaviorBody WeightBrainBrain imagingBrain regionCalciumCellsConsummatory BehaviorCoupledDataDevelopmentDietDissectionDistalEatingEconomic BurdenElectric StimulationElectrophysiology (science)FastingFeeding behaviorsFoodFood Intake RegulationFutureGeneticGlutamatesGoalsHabenulaHeterogeneityHomeostasisHormonalHormonesHypothalamic structureImageIndividualK-Series Research Career ProgramsLateralLateral Hypothalamic AreaLeptinLightMeasuresMentorshipMolecularMonitorMotivationMovementMusNeurologicNeuronsNeurosciencesObesityOutputPathway interactionsPhysiologicalPopulationPopulation ControlPopulation ProjectionPositioning AttributePrevalencePropertyRegulationResearchResearch PersonnelRewardsRodentRoleSatiationSignal TransductionSliceStimulusStructureStructure of terminal stria nuclei of preoptic regionSynapsesTestingTherapeutic InterventionTrainingUnited StatesVentral Tegmental AreaWeight GainWorkbasecell typecostdiet-induced obesityelectrical propertyexperimental studyfeedingfood consumptionghrelinhindbrainin vivoinsightmolecular dynamicsneural circuitnoveloptogeneticsprogramsrelating to nervous systemresponsetooltwo-photon
项目摘要
Project Summary/Abstract
The prevalence of obesity in the United States is projected to rise to nearly 50% and cost over $400 billion by
the year 2030. Despite the staggering economic burden, the underlying physiological mechanisms contributing
to obesity are largely unknown. Appetitive and consummatory behaviors, thought to be dysregulated in obesity,
are governed by descending signals from the brain, but how specific neural circuits regulate such behaviors is
unclear. One critical component in the neural circuitry that orchestrates feeding behavior is the lateral
hypothalamic area (LHA), a molecularly and functionally heterogeneous hypothalamic area that is
interconnected with limbic and hindbrain structures. Ablating LHA abolishes feeding and disrupts body weight
regulation across species, while electrical stimulation of LHA potentiates appetitive behavior and promotes
food intake. However, such coarse manipulations have nonspecific effects on movement and motivation, which
are likely due to the striking heterogeneity of the LHA. As a result, the function of discrete cell types within the
LHA their contributions to feeding, energy homeostasis, and ultimately obesity remain elusive. Recent
technological developments have made it possible to acutely manipulate and monitor activity dynamics of
molecularly and anatomically defined neuron populations in behaving rodents. The goal of the proposed
research is to use contemporary circuit neuroscience tools to monitor and manipulate the activity of
molecularly- and anatomically-defined LHA neurons to determine how divergent projection pathways uniquely
contribute to obesity. This project will focus on glutamatergic output pathways from the LHA to the ventral
tegmental area or the lateral habenula, two brain regions that are known to regulate feeding and reward.
Activity dynamics of these neurons will be monitored using in vivo two-photon deep brain calcium imaging
coupled with optogenetics and electrophysiology throughout the onset of diet-induced obesity. Completion of
the proposed aims is expected to be impactful because these studies will illuminate the causal and
natural neural dynamics that underlie the onset of obesity. While neurons of the lateral hypothalamic
area have long been implicated in the regulation of food intake and body weight, the genetic,
molecular, and circuit mechanisms underlying these influences are unknown. Identifying how obesity
interacts with defined neural circuitry at the level of individual neurons is of critical importance
because without this information, we are unlikely to discover the ways in which obesity arises. This
career development award will provide technical and conceptual training as well as mentorship from
renowned experts in the field of circuit neuroscience. Ultimately, this training will uniquely position this
young investigator to transition to an independent research program focused on investigating the
neuronal basis of obesity.
项目总结/摘要
到2020年,美国的肥胖患病率预计将上升至近50%,造成的损失将超过4000亿美元
到2030年尽管经济负担惊人,但潜在的生理机制
与肥胖的关系在很大程度上是未知的食欲和消费行为,被认为是在肥胖失调,
是由来自大脑的下行信号控制的,但具体的神经回路如何调节这些行为,
不清楚神经回路中协调进食行为的一个关键组成部分是侧
下丘脑区(LHA),一个分子和功能异质的下丘脑区,
与边缘系统和后脑结构相互连接减少LHA会破坏进食并扰乱体重
调节跨物种,而LHA的电刺激增强食欲行为,并促进
食物摄入量然而,这种粗糙的操作对运动和动机有非特异性的影响,
可能是由于LHA的显著异质性。因此,细胞内离散细胞类型的功能
它们对进食、能量平衡和最终肥胖的贡献仍然是难以捉摸的。最近
技术的发展使人们能够敏锐地操纵和监测
分子和解剖学定义的神经元群体在行为啮齿动物。建议的目标
研究是使用当代电路神经科学工具来监测和操纵神经活动
分子和解剖学定义的LHA神经元,以确定不同的投射途径如何独特地
导致肥胖。本项目将重点研究从LHA到腹侧的海马神经元能输出通路
被盖区或外侧缰,这两个大脑区域被认为是调节进食和奖励的。
这些神经元的活动动力学将使用体内双光子脑深部钙成像进行监测
再加上光遗传学和电生理学在整个饮食诱导的肥胖症的发病。完成
预计拟议的目标将产生影响,因为这些研究将阐明因果关系,
肥胖症发病的神经动力学基础。下丘脑外侧核神经元
该区域长期以来一直与食物摄入量和体重的调节有关,遗传,
这些影响的分子和电路机制是未知的。确定肥胖如何
在单个神经元的水平上与定义的神经回路相互作用是至关重要的
因为如果没有这些信息,我们就不可能发现肥胖的产生方式。这
职业发展奖将提供技术和概念培训,并从
电路神经科学领域的著名专家。最终,这次培训将使这一点
年轻的研究人员过渡到一个独立的研究计划,重点是调查
肥胖的神经基础
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Mark Allen Rossi其他文献
Mark Allen Rossi的其他文献
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{{ truncateString('Mark Allen Rossi', 18)}}的其他基金
Lateral Hypothalamic circuit dysfunction underlying the development of diet-induced obesity
下丘脑外侧回路功能障碍是饮食引起的肥胖发生的基础
- 批准号:
10716539 - 财政年份:2023
- 资助金额:
$ 24.9万 - 项目类别:
Disentangling discrete lateral hypothalamic circuits involved in feeding and obesity
解开与进食和肥胖有关的离散外侧下丘脑回路
- 批准号:
10645145 - 财政年份:2021
- 资助金额:
$ 24.9万 - 项目类别:
Disentangling discrete lateral hypothalamic circuits involved in feeding and obesity
解开与进食和肥胖有关的离散外侧下丘脑回路
- 批准号:
10454304 - 财政年份:2021
- 资助金额:
$ 24.9万 - 项目类别:
Disentangling discrete lateral hypothalamic circuits involved in feeding and obesity
解开与进食和肥胖有关的离散外侧下丘脑回路
- 批准号:
9803879 - 财政年份:2019
- 资助金额:
$ 24.9万 - 项目类别:
Disentangling discrete lateral hypothalamic circuits involved in feeding and obesity
解开与进食和肥胖有关的离散外侧下丘脑回路
- 批准号:
9977770 - 财政年份:2019
- 资助金额:
$ 24.9万 - 项目类别:
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