Reconstructing the temporal landscape of gene regulation in aging

项目摘要 R 01 AG 068579母合同的项目摘要未发生变更。 昼夜节律协调了大量的生化、生理和行为过程 24小时内一种时钟电路，由一组核心时钟的振荡激活和抑制驱动 基因，存在于每个细胞中，并调节所有组织中近一半基因组的表达。 大量的流行病学证据将昼夜节律调节与人类健康联系起来。尤其是睡眠和 昼夜节律紊乱与神经退行性变有关，在神经退行性变中，昼夜节律紊乱被认为是神经退行性变的后果， 阿尔茨海默病（AD）的危险因素。作为老年人中最常见的痴呆形式，AD迅速地 成为一场公共卫生危机，影响美国估计550万人（全球2400万人）， 预计在未来20年内将翻一番。解决这一危机需要对疾病有深刻的理解 机制和诊断/治疗靶点的鉴定。大量现有的转录组数据， 再加上用于时间重建和分析的复杂计算工具的发展， 提供了一个令人兴奋的机会，以确定在振荡模式的基因表达相关的失调 与衰老和AD有关。我们建议开发新的计算策略来破译振荡模式 使用现有的不定时转录组数据集的基因表达;并将其应用于现有的数据， AD的研究，以确定与AD相关的振荡模式的失调。我们的方法解决了 许多分析挑战，包括需要从不定时的样本中重建时间信息; 确保不同转录组学分析技术的通用性和准确性; 事实上，不定时的样本可能不会跨越全天;以及识别复杂的非正弦曲线的变化， 节奏总之，这些研究将揭示与衰老相关的基因表达的振荡模式， 老年痴呆症，并将提供创新的新方法，昼夜节律分析的不定时数据， 也可以应用于其他类型。

Project Summary There have been no changes to the Project Summary for the R01 AG068579 parent award. The circadian rhythm orchestrates a vast repertoire of biochemical, physiological, and behavioral processes with a 24-hour period. A clock circuit, driven by the oscillatory activation and repression of a set of core clock genes, is present in every cell and regulates the expression of nearly half the genome across all tissues. Abundant epidemiological evidence links circadian regulation to human health. In particular, sleep and circadian disruption is associated with neurodegeneration, where it is thought to be both a consequence and a risk factor for Alzheimer's disease (AD). As the most common form of dementia in the elderly, AD is rapidly becoming a public health crisis, affecting an estimated 5.5M people in the United States (24M world-wide) and is expected to double over the next 20 years. Addressing this crisis requires a deep understanding of disease mechanisms and the identification of diagnostic/therapeutic targets. A wealth of existing transcriptomic data, coupled with the development of sophisticated computational tools for temporal reconstruction and analysis, provide an exciting opportunity to identify dysregulation in oscillatory patterns of gene expression associated with aging and AD. We propose to develop novel computational strategies to decipher the oscillatory patterns of gene expression using existing untimed transcriptomic datasets; and to apply them to existing data from studies of AD to identify dysregulation in the oscillatory patterns associated with AD. Our methods address a number of analytical challenges, including the need to reconstruct temporal information from untimed samples; ensuring generalizability and accuracy across different transcriptomic profiling technologies; addressing the fact that untimed samples may not span the full day; and identifying changes in complex, non-sinusoidal rhythms. Together, these studies will reveal oscillatory patterns of gene expression associated with aging and Alzheimers disease, and will provide innovative new methods for the circadian analysis of untimed data that can be applied to other phenotypes.