Identification of human genomic signatures of episodic memory

情景记忆的人类基因组特征的识别

• 批准号: 9789072
• 负责人: Genevieve Konopka
• 金额: $ 24.3万
• 依托单位: UT SOUTHWESTERN MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-20 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9789072
• 关键词: Address; Animal Experimentation; Animal Model; Brain; Cadaver; Child Rearing; Cognition; Cognition Disorders; Cognitive; Collection; Complex; Data; Data Set; Databases; Development; Discipline; Disease; Electrodes; Electroencephalography; Epilepsy; Episodic memory; Evaluation; Excision; Exploratory/Developmental Grant; Expression Profiling; Foundations; Gene Expression; Gene Expression Profiling; Generations; Genes; Goals; Human; Impaired cognition; Individual; Intractable Epilepsy; Investigation; Ion Channel; Knowledge; Link; Literature; Lobectomy; Location; Maps; Memory; Memory Disorders; Memory Loss; Methodology; Molecular; Monitor; Neurosciences; Operating Rooms; Operative Surgical Procedures; Pathway interactions; Patients; Pattern; Performance; Population; Proteins; Publishing; Research Personnel; Retrieval; Seizures; Specimen; Techniques; Temporal Lobe; Therapeutic; Time; Tissue Sample; Tissues; Work; awake; base; brain tissue; cognitive function; computerized data processing; data warehouse; demographics; differential expression; disability; experimental study; gene discovery; genomic signature; innovation; insight; mathematical analysis; memory process; memory recall; mild cognitive impairment; new therapeutic target; novel; novel strategies; population based; signal processing; success; therapeutic target; tissue processing; tool; transcriptome sequencing; whole genome

PROJECT SUMMARY Our proposal seeks to unite two powerful tools in contemporary neuroscience: brain recordings from awake, behaving individuals and large-scale gene expression from human brain tissue. We hope to understand more about cognitive function in epilepsy and other disorders by studying gene expression profiles linked with brain oscillation information. The key innovation of this proposal is the collection of these two types of data from the same patients at different stages of their evaluation and treatment for epilepsy. In our first aim, we will build upon our recent findings examining gene/oscillation correlations through the generation of a proposed new large dataset of brain oscillations and by extending our analysis to include item retrieval during episodic memory. In our second aim, we will build an entirely new dataset by collecting intracranial EEG oscillatory data as subjects perform an episodic memory task and then also collect temporal lobe tissue specimens from the same patients. This is because the patients first undergo seizure mapping with intracranial electrodes, and then undergo resection of the temporal lobe. This offers the possibility of capturing oscillatory and gene expression data from the same tissue across subjects. In our third aim, we will generate gene expression data from surgical epilepsy patients and compare these profiles to datasets derived from cadaveric tissue samples. These comparisons will serve as a control to help interpret our correlation results and as a substantial contribution to the literature in its own right. Although this ambitious plan requires close integration between labs with expertise in gene expression analysis and signal processing, and requires a pipeline for processing tissue obtained in the operating room as well as specific surgical techniques to produce good specimens, the methodological groundwork we have established and preliminary data we show demonstrate that our plans have a high chance of success. The genes we identify as being highly correlated with mnemonic processing will be strong candidates for further animal experimentation and potential therapeutic targeting. We believe this line of investigation is a novel way to address the problem of cognitive decline in epilepsy and potentially other disorders such as mild cognitive impairment.

项目摘要 我们的提议试图将当代神经科学中的两种强大工具结合起来：清醒时的大脑记录， 行为个体和人类大脑组织的大规模基因表达。我们希望了解更多 通过研究与大脑相关的基因表达谱来了解癫痫和其他疾病的认知功能 振荡信息本提案的主要创新之处在于从 相同的患者在不同阶段的评估和治疗癫痫。在我们的第一个目标中，我们将建立在 我们最近的研究结果通过产生一个新的大的基因/振荡的相关性， 数据集的脑振荡，并扩展我们的分析，包括项目检索在情节记忆。在 我们的第二个目标，我们将建立一个全新的数据集，收集颅内脑电振荡数据作为主题 执行情景记忆任务，然后也从相同的患者中收集颞叶组织样本。 这是因为患者首先使用颅内电极进行癫痫发作标测，然后进行 颞叶切除术这提供了捕获振荡和基因表达数据的可能性， 相同的组织。在我们的第三个目标中，我们将从外科癫痫中产生基因表达数据， 并将这些图谱与来自尸体组织样本的数据集进行比较。这些比较将 作为一个对照，以帮助解释我们的相关结果，并作为一个实质性的贡献，在其文献 自己的权利。尽管这项雄心勃勃的计划需要拥有基因表达专业知识的实验室之间的密切整合 分析和信号处理，并且需要用于处理在手术室中获得的组织的管道， 以及特定的手术技术来制作好的标本，我们所拥有的方法学基础 我们展示的既定和初步数据表明，我们的计划有很大的成功机会。的基因 我们认为与记忆处理高度相关的动物将是进一步研究的有力候选者。 实验和潜在的治疗靶向。我们相信这条调查路线是一种新颖的方式来解决 癫痫和潜在的其他疾病如轻度认知障碍的认知能力下降问题。