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.

抽象的 性别差异对阿尔茨海默病 (AD) 的影响仍然知之甚少，尤其是在这种情况下 脆弱区域内蛋白质-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。尽管最近的高通量和生物信息学技术有助于理解分子和 衰老和 AD 中性别差异的遗传基础，依赖代表描述性的静态组学数据 生物分子清单，测量给定时间和条件下其化学计量的变化，限制功能 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，需要复杂的技术 计算算法，减少了对整个生物医学界的访问和影响。 为了解决这些限制，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获取相互作用组的扰动和功能结果 原生生物系统的此类变化。我们通过应用表观组学来假设 死后人类大脑 i) 捕捉疾病轨迹，ii) 涵盖 AD 易感人群和受影响较小的人群 区域，以及 iii）拥有关于患者特定相关性的强大并行信息，将使严格的假设成为可能- 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性方式发生。通过这种新颖的方法，我们 期望对受性别差异影响的特定功能障碍进行机制创新，从而获得见解 性别表型关系无法通过其他“组学”平台获得。通过评估、理解和 通过与性别影响相关的外表面组形成来预测相互作用组的变化（目标 1）以及 随后使用基于网络的输出进行直接计算分析（目标 2），这是首个全蛋白质组 深入了解性别差异对交互组网络脆弱性和功能障碍的影响 海马体和默认模式网络区域与相对幸存的小脑相关，两者都在 它们的性质和轨迹，会在脆弱的细胞和大脑区域中产生。信息如何压力源和 脆弱性（例如基因、环境、荷尔蒙状态）在细胞和大脑连接组水平上相互作用， 产生疾病脆弱性的异质表型图谱。我们提出了一个全新的 治疗范式途径将打开，提供以前无法获得的针对性别的精准医学 通过理解和瞄准跨无认知 AD 谱系的相互作用组来治疗 AD 通过压力源和脆弱性分析来诊断损伤、轻度认知障碍和 AD 痴呆。生的 来自交互组网络研究的数据集和数据分析将被存入免费访问门户 科学界可以进行额外的挖掘和假设检验研究。基于网络的用户- 还将设计便于数据处理和可视化的界面。