Identifying the molecular systems, networks, and key molecules that underlie cognitive resilience

识别认知弹性背后的分子系统、网络和关键分子

• 批准号: 9565486
• 负责人: Christopher A. Gaiteri
• 金额: $ 86.09万
• 依托单位: RUSH UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9565486
• 关键词: Affect; Age; Aging; Alzheimer' s Disease; Animal Model; Automobile Driving; Autopsy; Base of the Brain; Biological; Biological Assay; Biological Models; Biological Process; Brain; Brain region; Cerebrovascular Disorders; Cessation of life; Characteristics; Clinical; Clinical/Radiologic; Cognition; Cognitive; Cohort Studies; Communities; Data; Dementia; Disease; Elderly; Freezing; Functional Magnetic Resonance Imaging; Fusiform gyrus; Gene Proteins; Goals; Human; Impaired cognition; Individual; Life Style; Link; Longitudinal Studies; Magnetic Resonance Imaging; Measures; Memory; Molecular; Molecular Structure; Neurodegenerative Disorders; Outcomes Research; Participant; Pathologic; Pathology; Pattern; Persons; Phenotype; Protein Region; Proteins; Proteome; Proteomics; Proxy; Religion and Spirituality; Resources; Risk Factors; System; Systems Biology; Testing; Therapeutic; Time; Ursidae Family; Validation; Work; age related; base; cognitive function; cognitive process; cohort; high dimensionality; in vivo; indexing; innovation; member; molecular marker; multiple omics; neuroimaging; neuropathology; novel; psychologic; resilience; response; support network; targeted treatment; therapeutic development; transcriptome; transcriptome sequencing

ABSTRACT The proposed study: Identifying the molecular systems, networks, and key molecules that underlie cognitive resilience is in response to RFA-AG-17-061. The overall goal of the proposed study is to identify the molecular networks underlying resilience to AD, other age-associated neuropathologies and risk factors associated with resilience. The proposal is highly responsive to the RFA in that it is focused on the function of networks supporting cognitive resilience. Specifically, we will generate high-dimensional molecular data, to which we will apply systems biology approaches, and then integrate these with measures of resilience that rely on longitudinal cognitive data and assays of age-related neuropathologies. A key outcome of this research will be linking environmental, lifestyle and experiential factors to specific molecular networks. In addition to protein validation in humans, we will utilize living human brain networks as a validation “model system”. We are able to do this, b ecause for the first time our omics will be acquired from persons who previously provided fMRI data. Therefore, we can provide a unified perspective on the basis of resilient brain function in molecular and brain networks, which provides high confidence validated molecules and networks driving resilience to AD and age-related neuropathologies in humans. Our main resources for the proposed study are two longitudinal studies of aging, which provide neuroimaging, omic detailed neuropathology, longitudinal cognition scores and a quantitative measure of resilience for each person. From these cohorts, in Aim 1 we will acquire RNAseq and TMT proteomics (9000+ measured proteins) from regions of the brain whose molecular structure varies in synchrony with a continuous measure of resilience, based on MRI of this cohort. After identifying the molecular systems active in these regions, we will (Aim 2) infer the networks contained within each molecular system, the connections between molecular systems, and the connections between molecular systems and resilience. Given the limitations of animal models in validating cognitive phenotypes, we utilize a unique resource to validate the gene and protein networks found to be associated with resilience. We will (Aim 3) use dynamic fMRI-based brain networks, previously acquired from the same individuals to validate the post-mortem molecular networks with this close proxy of cognitive function. Thus the proposal brings to bear several major perspectives on resilience – longitudinal cognition, neuropathology, multiple omics and neuroimaging to identify novel networks and targets to stimulate resilience, producing a strong and sustained impact on the field.

抽象的 拟议的研究：识别认知基础的分子系统、网络和关键分子 弹性是响应 RFA-AG-17-061。 拟议研究的总体目标是确定 AD、其他与年龄相关的神经病理学和风险的恢复能力的分子网络 与弹性相关的因素。 该提案对 RFA 做出了高度响应，因为它重点关注 具体来说，我们将支持认知弹性的网络功能。 生成高维分子 数据，我们将对其应用系统生物学方法，然后将其与弹性测量相结合 依赖于纵向认知数据和与年龄相关的神经病理学分析，这是该研究的一个关键结果。 研究将把环境、生活方式和经验因素与特定的分子网络联系起来。 除了人类蛋白质验证之外，我们还将利用活人大脑网络作为验证“模型” 我们能够做到这一点，b。 因为我们的组学将首次从以下人员那里获得 因此，我们可以在弹性大脑的基础上提供统一的视角。 在分子和大脑网络中发挥作用，提供高可信度的经过验证的分子和网络 提高人类对 AD 和与年龄相关的神经病理学的抵抗力。 我们拟议研究的主要资源是两项关于衰老的纵向研究，它们提供了神经影像学、 组学详细的神经病理学、纵向认知评分和每个人的弹性的定量测量 在目标 1 中，我们将从这些队列中获得 RNAseq 和 TMT 蛋白质组学（9000 多个测量值）。 蛋白质）来自大脑区域，其分子结构与连续测量同步变化 在确定这些区域活跃的分子系统后，我们将根据该队列的 MRI 来确定弹性。 （目标2） 推断每个分子系统内包含的网络、分子之间的联系 考虑到动物的局限性，以及分子系统和恢复力之间的联系。 在验证认知表型的模型中，我们利用独特的资源来验证基因和蛋白质 我们将（目标 3）使用基于动态功能磁共振成像的大脑网络， 之前从同一个人处获得，以验证死后分子网络 因此，该提案带来了关于复原力的几个主要观点—— 认知、神经病理学、多组学和神经影像学来识别纵向新网络和目标 激发韧性，对该领域产生强大而持续的影响。