Harnessing Molecular Networks of Resilience for Therapeutic Discoveries in AD

利用弹性分子网络进行 AD 治疗发现

• 批准号: 10170201
• 负责人: NILUFER ERTEKIN-TANER
• 金额: $ 113.04万
• 依托单位: MAYO CLINIC JACKSONVILLE
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10170201
• 关键词: Age; Aging; Alleles; Alzheimer' s Disease; Alzheimer' s disease pathology; Alzheimer' s disease risk; Alzheimer' s disease therapeutic; Alzheimer’s disease biomarker; Amyloid; Amyloid beta-Protein; Area; Astrocytes; Autopsy; Biological; Biological Markers; Biological Models; Biological Process; Biology; Blood Vessels; Brain; Cell Nucleus; Cells; Clinic; Clinical; Cognitive; Cohort Studies; Coin; Complex; Crystallization; DNA; Data; Databases; Development; Disease; Drug Targeting; Elderly; Ensure; Environmental Risk Factor; Etiology; Experimental Models; Functional disorder; Gene Proteins; Genetic; Genetic Transcription; Genotype; Human; Impaired cognition; Individual; Knowledge; Lead; Longitudinal Studies; Medicine; Microglia; Modeling; Molecular; Molecular Target; Multiomic Data; Natural Immunity; Nerve Degeneration; Neurons; Oligodendroglia; Organoids; Outcome; Participant; Pathologic; Pathology; Pathway interactions; Peripheral; Pharmacogenomics; Positron-Emission Tomography; Predisposition; Proteins; Proteome; RNA; RNA Sequences; Sampling; Side; Specificity; Structure; System; Systems Biology; Temporal Lobe; Testing; Therapeutic; Time; Translating; Translations; United States National Institutes of Health; Validation; apolipoprotein E-4; base; brain cell; brain tissue; cell type; cohort; comorbidity; data tools; drug candidate; druggable target; genetic risk factor; human data; human old age (65+); induced pluripotent stem cell; mild cognitive impairment; myelination; neuropathology; novel; novel therapeutics; pathological aging; prophylactic; resilience; screening; therapeutic target; tool; transcriptome; transcriptome sequencing; whole genome

Although protection from and resilience to Alzheimer's disease (AD) constitute a fundamental aspect to understanding AD pathophysiology, this is a relatively understudied area and the molecular basis of resilience to AD is largely unknown. This is a critical knowledge gap, as uncovering biological pathways of resilience could lead to the discovery of novel therapeutic or prophylactic drug targets in AD. It is clear that there are individuals who may be protected from developing AD pathology, despite advanced age and having highly penetrant genetic risk factors for AD, such as APOE ε4 allele. Additionally, there are people with cognitive resilience who remain free of cognitive decline despite having pathologic or biomarker changes of AD. Current therapeutic discovery efforts in AD are largely focused on uncovering the biological pathways that are perturbed in this condition, the key molecules in these pathways, and identification of therapeutic compounds to stop and/or reverse these perturbations. These efforts are based on the hypothesis that concerted perturbations of molecular networks that serve key biological functions underlie the pathophysiology of many common, complex diseases including AD. While it is critically important to discover perturbed molecular networks in AD, this is only one side of the coin. We postulate that application of network biology approaches to investigate individuals who are protected from and resilient to AD can uncover novel biological pathways that underlie resilience to AD. In addition to revealing novel resilience pathways, study of resilient individuals is also critical for the validation of perturbed disease networks, as we expect some of the susceptibility and resilience networks to overlap but have opposite direction of effect. Such validation efforts are essential for the translation of these discoveries to viable drug targets. In this proposal, we plan to study individuals who are protected from and resilient to AD by leveraging samples from autopsied and living human cohorts, to utilize existing and generate new molecular data, including RNA sequence (RNAseq) and whole genome sequence (WGS), and to apply analytic approaches to identify resilience networks. We will utilize single-nucleus RNAseq (snRNAseq) to identify cell-specific molecular changes of resilience in brain and validate these using iPSC- based models. To translate this knowledge to therapeutic targets, we will apply novel pharmacogenomics tools. Our proposal is responsive to the RFA-AG-18-029 and aims to: 1) Identify molecular targets of resilience to development and propagation of AD pathology in an autopsy cohort enriched for older controls; 2) Identify molecular targets of cognitive resilience in the presence of AD biomarkers in a longitudinally assessed older cohort enriched for clinically normal individuals with positive amyloid PET and APOE ε34 or ε44 genotypes; 3) Validate cell-specific molecular changes in iPSC-based models; 4) Decipher druggable targets of AD resilience and potential therapeutic compounds using systems-based pharmacogenomics tools. We will integrate our findings with those from AMP-AD, M2OVE-AD, ADNI and ADSP and share all generated data and tools.

尽管预防和抵御阿尔茨海默病 (AD) 是预防阿尔茨海默病 (AD) 的一个基本方面 了解 AD 病理生理学，这是一个相对未被充分研究的领域，也是恢复能力的分子基础 AD 很大程度上是未知的。这是一个关键的知识差距，因为揭示了复原力的生物学途径 可能导致 AD 中新的治疗或预防药物靶标的发现。显然有 尽管年事已高且患有高度 AD 的渗透性遗传风险因素，例如 APOE ε4 等位基因。此外，还有一些有认知能力的人 尽管存在 AD 的病理或生物标志物变化，但仍没有认知能力下降的复原力。当前的 AD 治疗发现工作主要集中于揭示 AD 的生物学途径 在这种情况下受到干扰，这些途径中的关键分子以及治疗化合物的鉴定 停止和/或扭转这些扰动。这些努力是基于以下假设：协调一致 服务于关键生物功能的分子网络的扰动是许多疾病病理生理学的基础 常见、复杂的疾病，包括 AD。虽然发现扰动分子至关重要 AD 中的网络，这只是硬币的一方面。我们假设网络生物学方法的应用 调查那些免受 AD 影响并具有抵抗力的个体可以发现新的生物学途径 这是 AD 恢复能力的基础。除了揭示新的复原力途径之外，对复原力个体的研究还包括 对于验证受干扰的疾病网络也至关重要，因为我们预计一些易感性和 弹性网络重叠，但作用方向相反。此类验证工作对于 将这些发现转化为可行的药物靶点。在本提案中，我们计划研究以下个人： 通过利用尸检和活体人类队列的样本来预防 AD 并对其具有抵抗力，以利用 现有的并生成新的分子数据，包括 RNA 序列 (RNAseq) 和全基因组序列 （WGS），并应用分析方法来识别弹性网络。我们将利用单核 RNAseq (snRNAseq) 识别大脑弹性的细胞特异性分子变化，并使用 iPSC 验证这些变化 为基础的模型。为了将这些知识转化为治疗靶点，我们将应用新型药物基因组学 工具。我们的提案是对 RFA-AG-18-029 的回应，旨在：1) 确定恢复力的分子目标 AD 病理学在尸检队列中的发展和传播，该队列丰富了老年对照； 2）识别 在纵向评估的老年人中存在 AD 生物标志物时认知弹性的分子目标 队列富集了淀粉样蛋白 PET 和 APOE ε34 或 ε44 基因型呈阳性的临床正常个体； 3） 验证基于 iPSC 的模型中细胞特异性的分子变化； 4) 破译 AD 恢复力的药物靶标 和使用基于系统的药物基因组学工具的潜在治疗化合物。我们将整合我们的 与 AMP-AD、M2OVE-AD、ADNI 和 ADSP 的研究结果相结合，并共享所有生成的数据和工具。