Modeling Gene Networks in Neuronal Adaptation to Alcohol

描述（由申请人提供）：本提案通过提供对体内平衡失调和酒精戒断的焦虑效应背后的神经元过程的理解，具有公共卫生服务相关性。这些影响使酗酒者无法戒酒，事实上，突然戒酒不仅令人不快，而且本身就有重大的健康风险。我们将发现与此相关的新过程，可以作为改善戒酒负面后果的潜在新目标进行探索。本提案旨在进行动物研究，以确定和表征与酒精戒断相关的基因。酒精对中枢神经系统（CNS）的影响是由不同区域和特定神经元类型中差异表达的基因和基因产物介导的。这些变化在特定的细胞类型中可能是不同的或相反的，或者可能只发生在特定的细胞类型中，并且可能相对较大或非常微妙。此外，很明显，对酒精戒断的反应并不局限于一个或几个基因，而是一个复杂的、动态的过程，涉及大量基因随时间的协调调节。我们建议收集全球基因表达数据集的时间序列，以揭示神经元酒精戒断的基因组过程和机制，从而发现和模拟大脑中酒精戒断的基因网络和细胞控制。我们提出的方法的主要优势是我们开发和使用的新颖而强大的微阵列技术和先进的生物信息学/数学分析。我们提出两个具体目标：（1)建立急性酒精戒断期间转录反应模式的统计模型，与慢性酒精状态和正常状态相比，在两个关键的神经元群体中(2)）识别不断发展的基因调控网络活动和机制，以及衍生的信号通路活动，通过使用计算方法建立酒精戒断过程的模型。并进行适当的实验验证研究，以引导未来的研究。

DESCRIPTION (provided by applicant): The present proposal has public health service relevance by providing understanding of the neuronal processes underlying the dysregulation of homeostasis and anxiogenic effects of alcohol withdrawal. These effects keep alcoholics from quitting drinking, and in fact make sudden cessation of drinking not just unpleasant but a significant health risk itself. We will discover new processes involved in this that can be explored as potential new targets for amelioration of the negative consequences of alcohol withdrawal. This proposal seeks to perform animal studies to identify and characterize genes associated with alcohol withdrawal. Alcohol's effects on the central nervous system (CNS) are mediated by genes and gene products differentially expressed in a variety of regions and specific neuron types. These changes can be different or opposite in specific cell types, or may occur in only particular cell types, and may be relatively large or very subtle. Furthermore, it is clear that the response to alcohol withdrawal is not confined to one or a few genes, but rather is a complex, dynamical process involving the coordinate regulation of large numbers of genes over time. We propose to collect a time series of global gene expression datasets that will reveal the genomic processes and mechanisms of the alcohol withdrawal of neurons in order to discover and model the gene networks and cellular controls of alcohol withdrawal in the brain. The major strengths of the approach we propose are the novel and robust microarray technology and advanced bioinformatics/mathematical analyses we have developed and employed. We propose two specific aims: (1) develop statistical models of the patterns of transcriptional response during acute alcohol withdrawal across time as compared to the chronic alcohol state and the normal state and within two key neuronal populations (2)) Identify the evolving gene regulatory network activities and mechanisms, and derived signaling pathway activities by which a alcohol withdrawal develops using computational approaches to develop models of the process of alcohol withdrawal, and perform appropriate experimental validation studies leading to future studies.