Continuous neurogenesis in the mammalian hippocampus

哺乳动物海马的持续神经发生

基本信息

批准号：
10711115
负责人：
HONGJUN SONG
金额：
$ 40.63万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-05-01 至 2024-04-30
项目状态：
已结题

项目摘要

As an Administrative Supplement to our current R35 funding, we are proposing to extend our rigorous and multifaceted analyses of hippocampal neurogenesis in mice and human induced pluripotent stem cell models to a focused study of human adult neurogenesis in postmortem hippocampal tissue obtained from age-matched neurotypical donors and Alzheimer’s Disease (AD) patients. In rodent models of AD, adult hippocampal neurogenesis is reduced, whereas enhancing adult hippocampal neurogenesis is sufficient to rescue the cognitive deficits. Little is known about the molecular characteristics of adult hippocampal neurogenesis in humans and in AD. We have recently completed a study using single-nucleus RNA-seq (snRNA-seq) to generate a transcriptional signature of human immature neurons in the hippocampus across the lifespan. Using this signature to profile neurogenesis in hippocampal tissue of the aging brain, in a pilot study we observed potential differences in both the number and transcriptional profile of immature neurons in samples from AD patients compared to matched controls. In this proposed study, we will expand our cohort size to rigorously test our hypotheses of both quantitative and qualitative changes in adult human hippocampal neurogenesis in the context of AD. Technically, we will build on our strengths using single-cell approaches to profile both the transcriptome and chromatin accessibility within the same cell. This combination of snRNA-seq and snATAC-seq will enhance our ability to identify additional cell types within the neurogenic trajectory and provide additional information on the epigenetic signatures of AD that may impact neurogenesis. We will also build on the strength of our machine learning-based analytical approach. Finally, we will take an integrated bioinformatic approach to combine single-cell profiling, pseudotime analyses to identify dynamic state transitions, and cellular interactions based on ligand-receptor expression levels. Together, our study will generate validated single-cell datasets from male and female AD patients and age-matched controls that will be a valuable resource for the AD research community and will generate mechanistic hypothesis about AD pathophysiology and potential therapeutic targets.

作为我们当前R35资金的行政补充，我们提议扩展我们的对小鼠和人类诱导的海马神经发生的严格和多方面分析多能干细胞模型，针对人类成年神经发生的重点研究从年龄匹配的神经型供体和阿尔茨海默氏病获得的海马组织（AD）患者。在AD的啮齿动物模型中，成年海马神经发生减少，而增强成年海马神经发生足以挽救认知缺陷。几乎没有关于人类和人类海马神经发生的分子特征广告。我们最近使用单核RNA-Seq（SnRNA-Seq）完成了一项研究在海马中产生人类未成熟神经元的转录特征寿命。使用此签名来介绍衰老大脑海马组织的神经发生，在一项试点研究，我们观察到在数量和转录曲线的潜在差异与匹配的对照组相比，AD患者的样品中未成熟的神经元。在此提议中研究，我们将扩大队列规模，以严格测试定量和在AD的背景下，成年人类海马神经发生的定性变化。从技术上讲，我们将使用单细胞方法来基于我们的优势，以介绍转录组和同一单元格中的染色质可及性。 SnRNA-Seq和Snatac-Seq的这种组合将增强我们在神经发生轨迹内识别其他细胞类型的能力，提供有关可能影响神经发生的AD表观遗传学特征的其他信息。我们还将基于基于机器学习的分析方法的实力。最后，我们将采用一种集成的生物信息学方法来结合单细胞分析，假频率分析以鉴定基于配体受体的动态状态过渡和细胞相互作用表达水平。我们的研究将共同生成来自男性和的经过验证的单细胞数据集女性广告患者和年龄匹配的对照，这将是广告的宝贵资源研究社区，将产生有关AD病理生理学和潜在的治疗靶标。