New Approaches to Gene-environment Interaction Modeling in Parkinson's Disease
帕金森病基因-环境相互作用建模的新方法
基本信息
- 批准号:8089751
- 负责人:
- 金额:$ 9万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-06-01 至 2012-02-09
- 项目状态:已结题
- 来源:
- 关键词:AcuteAddressAdvisory CommitteesAffectAmericanAnimal ModelAwardBehavioralBrainBrain regionCatecholaminesCellsChlorpyrifosCorpus striatum structureDataDevelopmentDevelopment PlansDisease modelDopamineDoseEnvironmentEnvironmental ExposureEpidemiologyFeedbackGenesGeneticGenetic ModelsGoalsHealthHerbicidesHumanInheritedInsecticidesIronKnock-outLRRK2 geneLaboratoriesLeadLearningLinkLongevityMentorsModelingMutationNeurodegenerative DisordersOxidation-ReductionParaquatParkinson DiseasePathologyPathway interactionsPlayProteinsRattusRegimenRelative (related person)ResearchResearch PersonnelRiskRodentRodent ModelRoleRouteScreening procedureSolventsStagingSystemTechniquesTestingTherapeuticToxic Environmental SubstancesToxicant exposureTrainingTransgenesTransgenic OrganismsTrichloroethyleneUrsidae FamilyViralWorkalpha synucleincareer developmentdesigndopaminergic neuronexposed human populationexpression vectorgene environment interactiongene therapyin vivo Modelmeetingsneurobehavioralneurochemistryneuron lossnovel strategiesnovel therapeutic interventionoverexpressionpreventpublic health relevancesmall hairpin RNAsynucleintoxicanttransgene expressionvector
项目摘要
DESCRIPTION (provided by applicant)
This proposal is for a pathway to independence award. The candidate will learn new techniques and create a divergent research focus from the mentor laboratory. The candidate's primary goal is to become an independent investigator and make major scientific contributions to the neurodegenerative disease research field. A detailed Career Development Plan that includes coursework, learning new techniques, scientific meeting attendance, and specific feedback from an advisory committee has been constructed to help the candidate achieve this goal. The research focus of this proposal is on gene-environment interactions in Parkinson's disease (PD). New approaches to modeling such interactions are a major focus of this proposal. The causes of most PD cases are unknown, about 10% are inherited. The causes of the remaining "sporadic", about 90% are unknown. Epidemiological evidence has repeatedly suggested that environmental exposures increase the risk for PD. However, no single toxicant has been identified as a causative agent. Most cases may arise from both environmental and genetic factors. However, such interactions are poorly understood. Research to date on gene-environment interactions has typically utilized toxicant models that have little relevance to human health. Indeed, current PD models have major etiological limitations. Toxicant models typically use large acute doses by unrepresentative routes of exposure and genetic models often use complete life-span knockout of a gene or massive transgene expression. The candidate hypothesizes that: "early-stage" environmental PD modeling is best suited to study gene-environment interactions. He proposes to overcome current barriers by: Aim 1) Creating both "early" and "late" stage PD models using relevant environmental toxicants. Here, toxicants recently linked to PD will be used to create new rodent models that reproduce the key features of both early and late-stage PD and utilize environmentally relevant toxicants. This aim will serve as a "screen" to identify the optimal toxicant model to advance to later aims. The toxicant producing the best model will move forward to later aims. Aim 2) "Real-world" exposure modeling: This aim will utilize toxicant exposure through dosing regimens that bear relevance to human health. Aim 3) Creating new gene-environment interaction models: Here, transgenic rats expressing mutations known to cause PD in humans will be exposed to the optimal toxicant from aim 1. Thus a new gene-environment rodent PD model will be created that utilizes an environmental toxicant linked to PD and expresses a mutation known to cause human PD. Brain toxicant levels will be determined and correlated with pathological observations (Aims 1-3). Aim 4) Testing gene therapy approaches in these models: In vivo modulation of PD genes will be tested as a potential therapeutic approach in newly created toxicant models. This project is expected to produce major advances in gene-environment interaction modeling. Newly created models will be used to identify pathogenic pathways and test new therapeutic approaches.
Public Health Relevance: Parkinson's disease (PD) affects roughly 1 million Americans and the causes are largely unknown, although much data suggests that environmental exposures play a role. The proposed work will focus on the development of new models using compounds that have been linked to PD. These newly developed models will be used to test interactions between environmental and genetic factors and also to test potential treatments.
描述(由申请人提供)
该提议是为获得独立奖的途径。 候选人将学习新技术,并从导师实验室中建立不同的研究重点。 候选人的主要目标是成为独立研究者,并对神经退行性疾病研究领域做出重大科学贡献。 一项详细的职业发展计划,包括课程,学习新技术,科学会议的出勤以及咨询委员会的具体反馈,以帮助候选人实现这一目标。 该提案的研究重点是帕金森氏病(PD)中的基因环境相互作用。 建模这种相互作用的新方法是该建议的重点。 大多数PD病例的原因尚不清楚,约有10%是继承的。 其余“零星”的原因,约90%是未知的。 流行病学证据反复表明,环境暴露会增加PD的风险。 但是,尚无单一毒物被确定为病因剂。 大多数情况可能来自环境和遗传因素。 但是,这种互动知之甚少。 迄今为止,有关基因环境相互作用的研究通常使用与人类健康无关的有毒模型。 实际上,当前的PD模型具有重大的病因限制。有毒模型通常通过未代表性的暴露途径使用大型急性剂量,而遗传模型通常使用基因或大量转基因表达的完整寿命敲除。 候选人假设:“早期”环境PD建模最适合研究基因环境相互作用。 他建议通过以下方式克服当前障碍:1)使用相关的环境有毒物质同时创建“早期”和“晚期”阶段的PD模型。 在这里,最近与PD相关的有毒物质将用于创建新的啮齿动物模型,以重现早期和晚期PD的关键特征,并利用与环境相关的有毒物质。该目标将作为“屏幕”,以确定最佳的有毒模型,以促进以后的目标。 产生最佳模型的有毒物质将继续前进。 目标2)“现实世界”暴露建模:此目标将通过与人类健康相关的给药方案利用有毒物质的暴露。 目的3)创建新的基因环境相互作用模型:在这里,表达在人类中引起PD的突变的转基因大鼠将暴露于AIM 1的最佳毒物中。因此,将创建一种新的基因 - 环境啮齿动物PD模型,以利用与PD链接的环境有毒物质并表达与PD链接的环境有毒物,并表达了引起人类PD的突变。 脑有毒水平将与病理观察结果确定并相关(目标1-3)。 目标4)在这些模型中测试基因治疗方法:在新创建的有毒模型中,PD基因的体内调节将作为一种潜在的治疗方法测试。 预计该项目将在基因 - 环境相互作用建模中产生重大进展。 新创建的模型将用于识别致病途径并测试新的治疗方法。
公共卫生相关性:帕金森氏病(PD)影响了大约100万美国人,而原因在很大程度上未知,尽管许多数据表明环境暴露起着作用。拟议的工作将着重于使用已与PD相关的化合物的新模型的开发。这些新开发的模型将用于测试环境和遗传因素之间的相互作用,并测试潜在的治疗方法。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
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Jason R Cannon其他文献
Jason R Cannon的其他文献
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{{ truncateString('Jason R Cannon', 18)}}的其他基金
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