Alcohol addiction develops through a series of stages, and mechanistic studies are needed to understand the transition from initial drug use to sustained controlled alcohol consumption followed by abuse and physical dependence. The focus of this study was to examine the effects of voluntary alcohol consumption on brain gene expression profiles using a mouse model of binge drinking.
The main goal was to identify alcohol-responsive genes and functional categories after a single episode of drinking to intoxication.
The main goal was to identify alcohol-responsive genes and functional categories after a single episode of drinking to intoxication.
We used a modification of a “Drinking In the Dark” (DID) procedure (Rhodes et al., 2005) that allows mice to experience physiologically relevant amounts of alcohol in a non-stressful environment and also allows for detection of alcohol-sensitive molecular changes in a dose-dependent manner. C57BL/6J male mice were exposed to either 20% ethanol solution or water (single bottle) starting 3 hours after lights off for 4 hours and brains were harvested immediately after the drinking session. cDNA microarrays were used to assess the effects of voluntary drinking on global gene expression in 6 brain regions. We employed three statistical approaches to analyze microarray data.
A commonly used approach that applies a strict statistical threshold identified the eight top statistically significant genes whose expression was significantly correlated with blood ethanol concentration (BEC) in one of the brain regions.
We then used a systems network approach to examine brain region-specific transcriptomes and identify modules of co-expressed (correlated) genes. In each brain region, we identified alcohol-responsive modules, i.e., modules significantly enriched for genes whose expression was correlated with BEC.
A functional over-representation analysis was then applied to examine the organizing principles of alcohol-responsive modules. Genes were clustered into modules according to their roles in different physiological processes, functional groups, and cell types, including blood circulation, signal transduction, cell–cell communication, and striatal neurons.
Finally, a meta-analysis across all brain regions suggested a global role of increasing alcohol dose in coordination of brain blood circulation and reaction of astrocytes.
We then used a systems network approach to examine brain region-specific transcriptomes and identify modules of co-expressed (correlated) genes. In each brain region, we identified alcohol-responsive modules, i.e., modules significantly enriched for genes whose expression was correlated with BEC.
A functional over-representation analysis was then applied to examine the organizing principles of alcohol-responsive modules. Genes were clustered into modules according to their roles in different physiological processes, functional groups, and cell types, including blood circulation, signal transduction, cell–cell communication, and striatal neurons.
Finally, a meta-analysis across all brain regions suggested a global role of increasing alcohol dose in coordination of brain blood circulation and reaction of astrocytes.
This study showed that acute drinking resulted in small but consistent changes in brain gene expression which occurred in a dose-dependent manner. We identified both general and region-specific changes, some of which represent adaptive changes in response to increasing alcohol dose, which may play a role in alcohol-related behaviours, such as tolerance and consumption. Our systems approach allowed us to estimate the functional values of individual genes in the context of their genetic networks and formulate new refined hypotheses.
An integrative analysis including other alcohol studies suggested several top candidates for functional validation, including Mt2, Gstm1, Scn4b, Prkcz, and Park7.
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An integrative analysis including other alcohol studies suggested several top candidates for functional validation, including Mt2, Gstm1, Scn4b, Prkcz, and Park7.
Read Full Abstract
Request Reprint E-Mail: piatut@mail.utexas.edu
