Modeling Gene Networks in Neuronal Adaptation to Alcohol

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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 is in response to PA-03¿162 "Finding Genes for Alcohol-Related Behaviors and Risk for Alcoholism" and 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.