Integrating multidimensional genomic data to discover clinically-relevant predictive models-Alzheimer's Supplement

整合多维基因组数据以发现临床相关的预测模型-阿尔茨海默氏症补充品

• 批准号: 10286414
• 负责人: Brittany Nicole Lasseigne
• 金额: $ 21.4万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-12 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10286414
• 关键词: 3xTg-AD mouse; Administrative Supplement; Age; Aging; Alzheimer' s Disease; Alzheimer' s disease model; Alzheimer' s disease related dementia; Alzheimer’s disease biomarker; Aneuploidy; Animal Disease Models; Applications Grants; Award; Biological; Biological Markers; Blood; Brain; Cancer Science; Chromosomal Instability; Chromosomes; Collaborations; Consensus; Copy Number Polymorphism; CpG Island Methylator Phenotype; DNA; DNA Methylation; Data; Data Analyses; Data Science; Data Set; Deterioration; Disease; Etiology; Future; Genomic Instability; Genotype; Geroscience; Goals; Hippocampus (Brain); Human; Interdisciplinary Study; Knowledge; Link; Maintenance; Malignant Neoplasms; Measures; Methodology; Methods; Methylation; Mus; Muscle; National Human Genome Research Institute; Organ; Parents; Pathogenesis; Peripheral; Plasma; Positioning Attribute; Precision therapeutics; Research; Risk Factors; Role; Sentinel; Structure; Technology; Testing; Therapeutic; Work; base; brain tissue; circulating biomarkers; clinically relevant; density; design; drug repurposing; early detection biomarkers; genome sciences; genomic data; human disease; neuron development; parent project; predictive modeling; promoter; response; sex; targeted biomarker; tibialis anterior muscle; tool

Genomic instability (GIN) is a primary hallmark of aging, which is the greatest known risk factor for both Alzheimer’s disease (AD) and cancer. Because there is no consensus on which measures of GIN are most biologically and clinically relevant, in our parent project we are testing GIN metrics and developing tools for assessing GINs reproducibly across cancer. Our approaches are designed to be technology-, platform-, and disease-agnostic and therefore should also apply to AD. Our focus, thus far, has been on chromosomal instability (CIN, altered chromosome number and structure; e.g., total number of breakpoints, percent of bases with copy number variation, total functional aneuploidy, etc.) and DNA methylation instabilities (DNAm, e.g., CpG island methylator phenotype; CIMP, widespread altered promoter methylation, density of methylated to non-methylated CpGs, etc.). In cancer we and others have shown GIN is linked to disease etiology and progression, response to therapeutics, and is a potential disease biomarker. While AD animal models confirm DNA integrity impacts neuronal development, function, and maintenance and human aging studies further implicate a role for GIN in brain deterioration, GIN’s role in AD is not clear. There is a critical need to evaluate AD-specific GIN, particularly as potential precision therapy targets and early biomarkers defining therapeutic windows. Our interdisciplinary research team has AD, aging, genomic instability, cancer, genomics, and data science expertise and is well positioned to undertake these studies. Our long term research goal is to understand the role of GIN in the context of aging for multiple conditions and how GIN further contributes to disease etiology, progression, and treatment. Here, we propose the first steps towards demonstrating utility of our methodology in additional diseases by applying them to publicly available AD human and mouse data and comparing the resulting GIN profiles to cancer data analyses in our parent award. We hypothesize this will determine the extent and type of CIN (Aim 1) and DNAm instability (Aim 2) in AD. Critically, we will demonstrate how generalizable our methods and gained knowledge are, add AD examples and vignettes to the tools we are developing, and compare GINs across diseases (AD and cancers), species (human and mouse), and with respect to sex and age. Additionally, we will generate genotype and DNAm data from 3xTG-AD mouse hippocampus (AD-relevant brain tissue), tibialis anterior muscle (as a sentinel organ), and plasma (as a circulating factor) to investigate GIN as an AD biomarker. Critically, with this supplement we will demonstrate generalizability of the parent award methods and knowledge by expanding our existing non-AD NHGRI award to have an AD focus. This work will also stimulate additional activity and collaborations in AD and related dementias by providing preliminary data for several future grant proposals targeting the role of GIN in aging as a general disease mechanism, in AD pathogenesis, for drug repurposing and shared etiology studies between cancer and AD, and with respect to the utility of GINs as peripheral or circulating biomarkers.

基因组不稳定性（GIN）是衰老的主要标志，也是两者的最大已知风险因素 阿尔茨海默病（AD）和癌症。因为没有共识的措施GIN是最 生物学和临床相关，在我们的母项目中，我们正在测试GIN指标并开发工具， 在癌症中可重复地评估GIN。我们的方法旨在成为技术、平台和 疾病不可知，因此也适用于AD。到目前为止，我们的重点是染色体 不稳定性（CIN，改变的染色体数目和结构;例如，断点总数，碱基百分比 具有拷贝数变异、总功能性非整倍性等）和DNA甲基化不稳定性（DNAm，例如， CpG岛甲基化表型; CIMP，广泛改变的启动子甲基化，甲基化密度， 非甲基化CpG等）。在癌症中，我们和其他人已经表明GIN与疾病病因有关， 进展，对治疗剂的反应，并且是潜在的疾病生物标志物。虽然AD动物模型证实 DNA完整性影响神经元发育、功能和维持以及人类衰老研究 暗示GIN在脑退化中作用，GIN在AD中的作用尚不清楚。迫切需要评估 AD特异性GIN，特别是作为潜在的精确治疗靶点和定义治疗的早期生物标志物 Windows.我们的跨学科研究团队有AD、衰老、基因组不稳定性、癌症、基因组学、数据 科学专业知识，并有能力进行这些研究。我们的长期研究目标是 了解GIN在多种疾病衰老背景下的作用，以及GIN如何进一步促进 疾病病因、进展和治疗。在这里，我们提出了第一步，以证明效用的 我们的方法在其他疾病中的应用，将其应用于公开的AD人类和小鼠数据， 将由此产生的GIN概况与我们的母公司奖项中的癌症数据分析进行比较。我们假设这将 确定AD中CIN（Aim 1）和DNAm不稳定性（Aim 2）的程度和类型。关键是，我们会 演示我们的方法和获得的知识是如何推广的，添加AD示例和插图， 我们正在开发的工具，并比较疾病（AD和癌症），物种（人类和 小鼠），以及关于性别和年龄。此外，我们将从以下数据中生成基因型和DNAm数据： 3xTG-AD小鼠海马（AD相关脑组织）、胫骨前肌（作为前哨器官），以及 血浆（作为循环因子），以研究GIN作为AD生物标志物。关键是，有了这个补充，我们将 通过扩展我们现有的非AD，展示母公司奖励方法和知识的普遍性 NHGRI奖有一个AD的重点。这项工作还将促进AD领域的更多活动和合作 通过为未来几项针对GIN作用的拨款提案提供初步数据， 在衰老作为一般疾病机制，在AD发病机制，为药物再利用和共同病因 癌症和AD之间的研究，以及GIN作为外周或循环生物标志物的实用性。

项目成果

Nucleic acid liquid biopsies in Alzheimer's disease: current state, challenges, and opportunities.

• DOI: 10.1016/j.heliyon.2022.e09239
• 发表时间: 2022-04
• 期刊: HELIYON
• 影响因子: 4
• 作者: Soelter, Tabea M.;Whitlock, Jordan H.;Williams, Avery S.;Hardigan, Andrew A.;Lasseigne, Brittany N.
• 通讯作者: Lasseigne, Brittany N.

Evaluating cancer cell line and patient-derived xenograft recapitulation of tumor and non-diseased tissue gene expression profiles in silico.

评估癌细胞系和患者来源的异种移植物在计算机中再现肿瘤和非患病组织基因表达谱。

• DOI: 10.1101/2023.04.11.536431
• 发表时间: 2023
• 期刊: bioRxiv : the preprint server for biology
• 作者: Williams,AveryS;Wilk,ElizabethJ;Fisher,JenniferL;Lasseigne,BrittanyN
• 通讯作者: Lasseigne,BrittanyN

Inferring chromosomal instability from copy number aberrations as a measure of chromosomal instability across human cancers.

从拷贝数畸变推断染色体不稳定性作为人类癌症染色体不稳定性的衡量标准。

• DOI: 10.1101/2023.05.24.542174
• 发表时间: 2023
• 期刊: bioRxiv : the preprint server for biology
• 作者: Taluri,Sasha;Oza,VishalH;Soelter,TabeaM;Fisher,JenniferL;Lasseigne,BrittanyN
• 通讯作者: Lasseigne,BrittanyN