Molecular Networks Underlying Resilience to Alzheimer's Disease Among APOE E4 Carriers

APOE E4 携带者对阿尔茨海默病的抵抗力的分子网络

• 批准号: 10188369
• 负责人: Christopher A. Gaiteri
• 金额: $ 76.16万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-30 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10188369
• 关键词: Affect; Aging; Alleles; Alzheimer' s Disease; Alzheimer' s disease model; Alzheimer' s disease risk; Alzheimer’s disease biomarker; Apolipoprotein E; Bayesian Network; Biological; Biological Markers; Biology; Brain; Brain region; Cerebellum; Clinical; Complex; Consensus; DNA Methylation; Data; Dementia; Development; Disease; Disease susceptibility; Epigenetic Process; Ethnic Origin; Family history of; Future; Gender; Gene Expression; Genes; Genetic; Genetic Determinism; Genetic Predisposition to Disease; Genome; Genomics; Genotype; Goals; Health and Retirement Study; Heterogeneity; Human; Impaired cognition; Incidence; Individual; Intervention; Late Onset Alzheimer Disease; Lead; Longitudinal Studies; Memory; Mendelian randomization; Methods; Methylation; Modeling; Molecular; Multiomic Data; National Institute on Aging; Nature; Neocortex; Nerve Degeneration; Network-based; Pathogenesis; Pathway Analysis; Pathway interactions; Penetrance; Pharmacologic Substance; Pharmacology; Predisposition; Prefrontal Cortex; Prevention therapy; Primary Prevention; Process; Proteins; Proteome; Proteomics; Race; Research; Risk; Risk Factors; Sampling; Secondary Prevention; Statistical Models; System; Systems Biology; Tissue Sample; Tissues; apolipoprotein E-4; base; biological systems; effective therapy; epigenome; epigenomics; genetic signature; genome wide association study; health data; high dimensionality; high risk; high risk population; improved; innovation; multidimensional data; multiple omics; neuropathology; new therapeutic target; novel; polygenic risk score; predictive modeling; prevent; relating to nervous system; religious order study; repaired; resilience; risk prediction; screening; supervised learning; targeted biomarker; therapy development; transcriptome; transcriptome sequencing; transcriptomics

PROJECT SUMMARY/ABSTRACT The e4 allele of the Apolipoprotein E (ApoE) gene has been identified as one of the strongest genetic determinants of late-onset Alzheimer’s disease (AD). In general, the e4 allele is associated with reductions in neural protection and repair, increasing a carrier’s vulnerability to damage accumulated over his/her lifetime. Nevertheless, while the penetrance of ApoE e4 is relatively high, a significant proportion of e4 carriers will never develop AD. The overall goal of this project is to model interactions across multiple omics networks to identify the biological pathways involved in sporadic AD susceptibility versus resilience among high-risk individuals. The multifactorial nature of AD suggests that it may manifest as a result of complex interactions across the genome, epigenome, transcriptome, and proteome. Identifying the central networks involved in AD pathogenesis will require integrative Systems Biology approaches. The proposed research offers a new and innovative way to integrate networks—a dominant feature in biology—across multiple tissues and omics platforms, in order to identify innate and dynamic precursors of resilience to AD, among a high-risk population (e4+). Towards this goal, we will: (1) employ newly developed GWAS-based network analysis, to identify SNP networks that alter the association between ApoE e4 and cognitive decline/dementia; (2) generate DNA methylation and RNA-seq data from brain samples that we will analyze using weighted gene correlation network analysis (WGCNA) to identify networks associated with AD neuropathology and cognitive decline among ApoE e4+; (3) generate proteomic data from brain and CSF samples that we will analyze using WGCNA to identify networks associated with AD neuropathology and cognitive decline among ApoE e4+; (4) use advanced integromic network analysis to identify multi-omics and multi-tissue pathways and biological systems involved in AD resilience. The integration of multiple 'omics' data using systems biology will be crucial for unraveling the connections and interactions between various functional levels involved in complex diseases, such as AD. Overall, our proposed research will improve understanding of the complex biology underlying AD susceptibility. These studies have the potential to identify novel therapeutic targets that could inform the development of future pharmacologic interventions aimed at preventing or slowing AD pathogenesis.

项目总结/摘要 载脂蛋白E（ApoE）基因的e4等位基因已被鉴定为最强的遗传性疾病之一。 晚发性阿尔茨海默病（AD）的决定因素。一般而言，e4等位基因与以下降低相关： 神经保护和修复，增加了携带者一生中积累的损伤的脆弱性。 然而，虽然ApoE e4的表达率相对较高，但很大一部分e4携带者从未 发展AD。该项目的总体目标是对多个组学网络之间的相互作用进行建模，以识别 在高风险个体中，与偶发性AD易感性和恢复力相关的生物学途径。 AD的多因素性质表明，它可能表现为跨组织的复杂相互作用的结果。 基因组、表观基因组、转录组和蛋白质组。识别参与AD发病机制的中枢网络 将需要综合系统生物学方法。拟议的研究提供了一种新的创新方法， 整合网络-生物学中的主要特征-跨越多个组织和组学平台，以便 在高风险人群（e4+）中识别抗AD能力的固有和动态前体。为实现这一 目标，我们将：（1）采用新开发的基于GWAS的网络分析，以确定SNP网络，改变 ApoE e4与认知衰退/痴呆之间关联;（2）产生DNA甲基化和RNA-seq 我们将使用加权基因相关网络分析（WGCNA）分析来自大脑样本的数据， 在ApoE e4+中鉴定与AD神经病理学和认知衰退相关的网络;（3）产生 我们将使用WGCNA分析来自大脑和CSF样本的蛋白质组学数据，以确定相关网络。 AD伴神经病理学和认知功能减退者ApoE e4+;（4）采用高级积分网络分析 以确定多组学和多组织途径和生物系统参与AD的弹性。 使用系统生物学整合多个“组学”数据对于解开这些联系至关重要， 复杂疾病（如AD）中涉及的各种功能水平之间的相互作用。总的来说，我们的建议 研究将提高对AD易感性的复杂生物学基础的理解。这些研究有 有可能确定新的治疗靶点，为未来药理学的发展提供信息。 旨在预防或减缓AD发病机制的干预措施。