Impact of sex differences on the trajectory of interactome dysfunctions across the AD spectrum

性别差异对 AD 谱系中相互作用组功能障碍轨迹的影响

• 批准号: 10300853
• 负责人: GABRIELA CHIOSIS
• 金额: $ 124.06万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10300853
• 关键词: Address; Affect; Aging; Alzheimer' s Disease; Alzheimer' s disease brain; Autopsy; Bioinformatics; Biological; Biology; Brain; Brain region; Cells; Cerebellum; Chemicals; Clinical; Cognitive; Communities; Complex; Complex Analysis; Computational algorithm; Computer Analysis; Data; Data Analytics; Data Set; Defect; Deposition; Development; Disease; Environment; Equipment and supply inventories; Freezing; Functional disorder; Generations; Genes; Genotype; Global Change; Heterogeneity; Hippocampus (Brain); Hormonal; Human; Image; Impaired cognition; Individual; Knowledge; Knowledge Portal; Link; Measures; Metadata; Mining; Molecular; Molecular Genetics; Nature; Nerve Degeneration; Neuroglia; Neurons; Online Systems; Outcome; Output; Pathologic; Pathway interactions; Patients; Phenotype; Phenotypic Sex; Positioning Attribute; Prevention; Process; Proteins; Proteome; Recording of previous events; Resources; Risk Factors; Sampling; Severities; Sex Differences; Site; Sorting - Cell Movement; Specimen; System; Technology; Temporal Lobe; Testing; Time; Transcript; Translating; biological systems; brain cell; brain tissue; cell type; comorbidity; computerized data processing; connectome; data visualization; design; disease heterogeneity; disease phenotype; frontal lobe; functional outcomes; genome wide association study; healthy aging; innovation; insight; interest; large scale data; laser capture microdissection; member; mild cognitive impairment; multidisciplinary; network dysfunction; novel strategies; open source; precision medicine; protein protein interaction; response; sex; spatiotemporal; stoichiometry; stressor; therapy development; user-friendly; web platform

ABSTRACT The impact of sex differences in Alzheimer's disease (AD) remains poorly understood, especially in the context of protein-protein interactions within vulnerable regions that drive dysfunction. Despite growing appreciation of the clinical course, presentation, and severity of AD, studies of sex impacting AD development and progression are lacking. Although recent high-throughput and bioinformatics technologies help to understand molecular and genetic basis of sex differences in aging and AD, reliance on static `omics data representing a descriptive inventory of biomolecules measuring changes in their stoichiometry at a given time and condition limits functional insights. Another roadblock is translating these complex datasets into biological insights requires sophisticated computational algorithms, diminishing access and impact to the biomedical community at large. To address these limitations this proposal introduces epichaperomics, an unbiased state-of-the-art `omics approach we invented to generate direct access to interactome perturbations and to the functional outcome of such changes in native biological systems. We posit by applying epichaperomics to well-characterized postmortem human brains that i) capture the disease trajectory, ii) encompass AD vulnerable and less affected regions, and iii) have robust parallel information on patient-specific correlates, will enable rigorous hypothesis- generating analyses on potential impact of stressors and vulnerabilities on disease trajectory, and on interactome as well as connectome dysfunctions as they occur in sex-dependent manner. Through this novel approach we expect to derive mechanistic innovation on specific dysfunctions impacted by sex differences leading to insights into sex-phenotype relationships not available through other `omics platforms. By evaluating, understanding, and anticipating interactome changes through epichaperome formation in relation to sex impact (Aim 1) and subsequent straightforward computational analysis with web-based output (Aim 2), first-of-a-kind proteome-wide insights into the impact of sex differences on interactome networks vulnerabilities and dysfunctions within the hippocampus and regions of the default mode network in relation to the relatively spared cerebellum, both on their nature and trajectory, in vulnerable cells and brain regions will be generated. Information how stressors and vulnerabilities (e.g., genes, environment, hormonal status) interact at cell and brain connectome levels to produce heterogeneous phenotype mapping of disease vulnerability will be produced. We posit a whole new treatment paradigm avenue will open, providing a previously unavailable sex-specific precision medicine approach to AD by understanding and targeting the interactome across the AD spectrum of no cognitive impairment, mild cognitive impairment, and AD dementia through stressor and vulnerability analysis. Raw datasets and data analytics from interactome network studies will be deposited into free-access portals accessible by the scientific community for additional mining and hypothesis testing studies. A web-based user- interface will also be designed facilitating data processing and visualization.

摘要 阿尔茨海默病（AD）中性别差异的影响仍然知之甚少，特别是在 脆弱区域内的蛋白质-蛋白质相互作用导致功能障碍。尽管人们越来越欣赏 AD的临床病程、表现和严重程度，性别影响AD发生和进展的研究 缺乏。虽然最近的高通量和生物信息学技术有助于理解分子和生物信息学， 衰老和AD的性别差异的遗传基础，依赖于静态组学数据， 在给定的时间和条件下测量其化学计量变化的生物分子的库存限制了功能 见解.另一个障碍是将这些复杂的数据集转化为生物学见解需要复杂的 计算算法，减少了对整个生物医学界的访问和影响。 为了解决这些局限性，该提案引入了epichaperomics，一种无偏见的最先进的“组学” 我们发明的方法可以直接访问相互作用体扰动和功能结果， 这种变化在自然生物系统中。我们通过将epichaperomics应用于表征良好的 死后人脑，i）捕获疾病轨迹，ii）包括AD脆弱和受影响较小 区域，和iii）具有关于患者特异性相关性的稳健的平行信息，将使得能够进行严格的假设- 分析压力源和脆弱性对疾病轨迹和相互作用组的潜在影响 以及连接体功能障碍，因为它们以性别依赖的方式发生。通过这种新方法，我们 期望获得关于受性别差异影响的特定功能障碍的机制创新，从而获得见解 其他“组学”平台无法提供的性别-表型关系。通过评估、理解和 通过epichaperome形成预测与性别影响有关的相互作用组变化（目标1）， 随后的直接计算分析与基于网络的输出（目标2），第一类蛋白质组范围 深入了解性别差异对相互作用组网络脆弱性和功能障碍的影响， 海马和默认模式网络的区域与相对备用的小脑有关， 它们的性质和轨迹，在脆弱的细胞和大脑区域将被生成。压力源和 弱点（例如，基因、环境、激素状态）在细胞和脑连接体水平上相互作用， 将产生疾病易感性的异质表型图谱。我们为您提供全新的 治疗范式大道将开放，提供以前无法提供的性别特异性精准医学 通过理解和靶向非认知AD谱系的相互作用组来治疗AD 通过应激源和脆弱性分析，研究认知功能障碍、轻度认知功能障碍和AD痴呆的关系。原 来自互动基因组网络研究的数据集和数据分析将被存入免费访问的门户网站 科学界可以利用这些数据进行更多的挖掘和假设检验研究。一个基于Web的用户- 还将设计便于数据处理和可视化的界面。