New computational tools for understanding and predicting AD via age-associated DNA methylation changes

通过与年龄相关的 DNA 甲基化变化来理解和预测 AD 的新计算工具

• 批准号: 10509428
• 负责人: Lily Wang
• 金额: $ 202.07万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10509428
• 关键词: Acceleration; Affect; Age; Aging; Alzheimer' s Disease; Alzheimer' s disease diagnosis; Alzheimer' s disease risk; Alzheimer’s disease biomarker; Attenuated; Bioconductor; Bioinformatics; Biological; Biological Aging; Biological Markers; Blood; Blood specimen; Brain; Chronology; Clinical; Clinical Trials; Cognitive; Communities; Computer software; Cost of Illness; DNA Methylation; Data; Data Analyses; Data Set; Databases; Dementia; Development; Diagnosis; Diet; Disease; Disease Progression; Elderly; Environment; Epigenetic Process; Financial cost; Genome; Genomic approach; Genomics; Knowledge; Late Onset Alzheimer Disease; Measures; Medical Genetics; Meta-Analysis; Methylation; Modeling; Monitor; Neurodegenerative Disorders; Onset of illness; Outcome; Persons; Plasma; Population; Prognosis; Public Health; Research; Research Personnel; Risk; Role; Sampling; Smoking; Source; Surrogate Markers; Tissues; Training; base; computational pipelines; computerized tools; diagnostic value; diet and exercise; disease phenotype; disease prognosis; experience; functional decline; genomic data; heterogenous data; human old age (65+); innovation; insight; lifestyle factors; minimally invasive; open source; predictive marker; predictive modeling; prognosis biomarker; prognostic value; progression marker; tool; treatment strategy; web interface

Alzheimer’s disease (AD) is the most common neurodegenerative disorder, with late-onset AD affecting about 1 in 9 people over 65 years old in the US. The increasing elderly population in the US makes AD a major public health concern and one of the most financially costly diseases. Currently, a major challenge is the lack of reliable, minimally invasive, inexpensive biomarkers to aid the diagnosis, prognosis, and ultimately development of new AD treatment strategies. One potential source of biomarkers for AD is DNA methylation (DNAm). Changes in DNAm have been implicated in both aging and AD. Moreover, DNAm is relatively stable and can be easily detected. DNAm is an epigenetic mechanism at the interface of the genome and environment, and it is influenced by aging and many lifestyle factors such as smoking, diet, and exercise, which in turn might modify the risk of AD. In the past few years, we have developed several innovative open-source software for DNAm and other genomics data analyses. In this proposal, building on our previous experiences in developing and applying tools for integrative genomics analyses of large-scale heterogeneous datasets, we propose to harmonize a large number of DNAm datasets to clarify the role of DNAm in aging and AD, to develop a web interface that disseminates the analyses results, and to develop epigenetic clocks tailored for predicting AD phenotypes. We hypothesize a number of DNAm-based regulatory changes are relevant to both aging and AD, and some age- associated DNAm changes also contribute to AD onset and progression. In Aim 1, we will aggregate, harmonize, and meta-analyze a large number of DNAm aging datasets measured in brain and blood samples to identify DNAm changes associated with aging and AD, and determine age-associated DNAm differences that also contribute to AD. We will develop two tools: (1) a searchable web interface that clarifies the role of DNA methylation in aging and AD and (2) an open-source R package for performing meta-analyses of DNAm methylation regions. In Aim 2, we will develop a new epigenetic clock tailored for predicting AD phenotypes. The diagnostic and prognostic values of the new epigenetic clock will be evaluated using available CSF biomarkers and clinical cognitive outcomes and compared with known clinical and genetic factors, as well as currently available plasma biomarkers. The searchable web interface will significantly enhance our understanding and enable new biological insights on the role of age-associated epigenetic changes in AD. The new epigenetic clock tailored to predicting AD phenotypes will facilitate the development of surrogate biomarkers that provide a degree of objectivity for monitoring disease progression in clinical trials, as well as assessing individualized risk profiles for AD diagnosis and prognosis. The successful completion of the project will also provide us with computational pipelines and tools that can be easily adapted and applied to analyze datasets generated for other types of dementias.

阿尔茨海默病 (AD) 是最常见的神经退行性疾病，晚发性 AD 影响约 1 美国 65 岁以上人口中有 9 人患有 AD。 健康问题和经济代价最高的疾病之一，目前面临的主要挑战是缺乏可靠、可靠的治疗方法。 微创、廉价的生物标志物有助于诊断、预后并最终开发新的 AD 治疗策略 AD 生物标志物的一种潜在来源是 DNA 甲基化 (DNAm) 的变化。 DNAm 与衰老和 AD 都有关联，而且 DNAm 相对稳定并且很容易被研究。 DNAm 是基因组和环境界面的表观遗传机制，并且受到影响。 衰老和许多生活方式因素（例如吸烟、饮食和运动）可能会改变患此病的风险 在过去的几年里，我们为 DNAm 和其他开发了多种创新的开源软件。 在本提案中，我们以我们之前开发和应用工具的经验为基础。 对于大规模异构数据集的综合基因组学分析，我们建议协调大型 大量 DNAm 数据集，以阐明 DNAm 在衰老和 AD 中的作用，开发一个 Web 界面 传播分析结果，并开发用于预测 AD 表型的表观遗传时钟。 保持一些基于DNAm的监管变化与衰老和AD相关，并且一些年龄- 相关的 DNAm 变化也有助于 AD 的发生和进展。在目标 1 中，我们将汇总、协调、 并对大脑和血液样本中测量的大量 DNAm 老化数据集进行荟萃分析，以确定 DNAm 变化与衰老和 AD 相关，并确定与年龄相关的 DNAm 差异，这些差异也 我们将开发两个工具：（1）一个可搜索的网络界面，阐明 DNA 的作用。 衰老和 AD 中的甲基化以及 (2) 用于对 DNAm 进行荟萃分析的开源 R 包 在目标 2 中，我们将开发一种用于预测 AD 表型的新表观遗传时钟。 新表观遗传时钟的诊断和预后价值将使用可用的脑脊液生物标志物进行评估 和临床认知结果，并与已知的临床和遗传因素进行比较，以及目前 可搜索的网络界面将显着增强我们的理解和发现。 为了解与年龄相关的表观遗传变化在 AD 中的作用提供了新的生物学见解。 专门用于预测 AD 表型将促进替代生物标志物的开发，从而提供一定程度的 临床试验中监测疾病进展以及评估个体化风险状况的客观性 该项目的成功完成也将为我们提供计算能力。 可以轻松调整并应用于分析为其他类型生成的数据集的管道和工具 痴呆症。