Identifying gene networks driving neuronal states during alcohol withdrawal
Identifying gene networks driving neuronal states during alcohol withdrawal
批准号:
8718678
负责人:
James Park
金额:
$4.27万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-01 至 2016-08-31
关键词:
AffectAlcohol abuseAlcohol dependenceAlcohol withdrawal syndromeAlcoholsAmygdaloid structureAreaAutomobile DrivingBehaviorBrainBrain InjuriesBrain regionCalcitonin Gene-Related PeptideCell NucleusCellsChronicComplexDataDevelopmentDietEmotionalEmotionsExposure toFuzzy LogicGene ExpressionGene Expression ProfileGenesGoalsHomeostasisHypothalamic structureIndividualInflammatoryKnowledgeLiquid substanceMasksMeasuresMessenger RNAMethodsMicrofluidicsModelingMolecularMolecular ProfilingNatureNeuronsOutputPathologyPathway AnalysisPathway interactionsPhenotypePhysiologyPontine structurePopulationProcessProteinsPublishingRattusRegulator GenesSamplingSignal TransductionSourceStagingSynapsesTimeTissuesVisceralWithdrawalWorkalcohol exposurebasebiological adaptation to stresscell typecombinatorialcytokinein vivoinsightinterestlaser capture microdissectionnetwork modelspublic health relevancereceptorrelating to nervous systemrelease factorresponse
中文摘要
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英文摘要
7. Project Summary
Chronic alcohol exposure causes widespread changes in CNS molecular function impacting brain function and
behavior, contributing to alcohol dependence and pathology. Due to the nature of the alcohol withdrawal and
the emotional and physical consequences, the central nucleus of the amygdala (CeA) is an area of significant
interest. Recently published and preliminary data suggest that these molecular processes accommodate to
chronic alcohol exposure over time. However these same molecular processes respond quickly to abrupt
changes in alcohol exposure as reflected in significant changes in gene expression in whole tissue punches of
the CeA. These changes progress over a long period of time during alcohol withdrawal. Moreover, preliminary
data supports our hypothesis that neurons of a phenotypic brain nucleus are adaptive in response to changed
inputs. These varied inputs result in the formation of distinct functional states within a cell-phenotype. Taken in
context, we note that the CeA neurons integrate a variety of synaptic inputs and signals from sources including
catecholaminergic afferents, pontine-visceral inputs, and the hypothalamus. Therefore it is likely that individual
CeA neurons respond to varied and combinatorial inputs resulting in differentiated functional states. These
distinct functional states subsequently result in differentiated neuronal contributions to the evolving state of the
CeA during withdrawal. Thus, understanding the molecular framework of these distinct functional states will
help reveal mechanisms subtending the response of the CeA. To this end, I will characterize the responses of
neurons within the CeA at the molecular level under various stages of alcohol dependence and withdrawal. I
propose to develop gene regulatory network models that will help characterize the functional gene
relationships governing the adaptive response of individual neurons. The result will be refined network models
that will describe the complex functional relationships underlying distinct input-driven neuronal states.
Subsequently these refined networks will yield insight into how synaptic inputs drive individual neurons into
differentiated states that differentially contribute to the evolving response of the CeA associated with the
various stages of alcohol dependence and withdrawal.
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海外基金