Ethanol modulation of gene networks: implications for alcoholism - PubMed (original) (raw)

Review

Ethanol modulation of gene networks: implications for alcoholism

Sean P Farris et al. Neurobiol Dis. 2012 Jan.

Abstract

Alcoholism is a complex disease caused by a confluence of environmental and genetic factors influencing multiple brain pathways to produce a variety of behavioral sequelae, including addiction. Genetic factors contribute to over 50% of the risk for alcoholism and recent evidence points to a large number of genes with small effect sizes as the likely molecular basis for this disease. Recent progress in genomics (microarrays or RNA-Seq) and genetics has led to the identification of a large number of potential candidate genes influencing ethanol behaviors or alcoholism itself. To organize this complex information, investigators have begun to focus on the contribution of gene networks, rather than individual genes, for various ethanol-induced behaviors in animal models or behavioral endophenotypes comprising alcoholism. This chapter reviews some of the methods used for constructing gene networks from genomic data and some of the recent progress made in applying such approaches to the study of the neurobiology of ethanol. We show that rapid technology development in gathering genomic data, together with sophisticated experimental design and a growing collection of analysis tools are producing novel insights for understanding the molecular basis of alcoholism and that such approaches promise new opportunities for therapeutic development.

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Figures

Figure 1. Diagram of multiple potential subcomponent vectors contributing to the observed behavioral phenomenon of alcohol dependence

The figure illustrates the premise that observed behavioral phenotypes studied in humans or animal models are actually made up of multiple behavioral subcomponents (e.g. endophenotypes) that are in turn controlled by neural networks. The gene networks derived by genomic studies are a syncytium of gene regulation events occurring within multiple cells comprising a given neural network.

Figure 2. Acute ethanol disruption of baseline _Homer2-_associated gene network in BXD recombinant inbred mice

(A) Homer2 expression correlation network in prefrontal cortex under baseline conditions (B) Homer2 baseline correlation network 4 hours after acute ethanol (1.8 g/kg) treatment. The highly coherent network seen across control BXD strains was severely rearranged by acute ethanol treatment. This suggests that elements of the Homer 2 expression network are targets of acute ethanol action. Orange lines represent positive Pearson correlation coefficients ≥ 0.60; Blue lines represent negative Pearson correlation coefficients ≤ −0.60 (n = 29).

References

1. Baldwin NE, Chesler EJ, Kirov S, Langston MA, Snoddy JR, Williams RW, et al. Computational, integrative, and comparative methods for the elucidation of genetic coexpression networks. J Biomed Biotechnol. 2005;2005(2):172–80. - PMC - PubMed
1. Bertsch B, Ogden CA, Sidhu K, Le-Niculescu H, Kuczenski R, Niculescu AB. Convergent functional genomics: a Bayesian candidate gene identification approach for complex disorders. Methods. 2005;37(3):274–9. - PubMed
1. Bottomly D, Walter NA, Hunter JE, Darakjian P, Kawane S, Buck KJ, et al. Evaluating Gene Expression in C57BL/6J and DBA/2J Mouse Striatum Using RNA-Seq and Microarrays. PloS one. 2011;6(3):e17820. - PMC - PubMed
1. Butte AJ, Tamayo P, Slonim D, Golub TR, Kohane IS. Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks. Proc Natl Acad Sci U S A. 2000;97(22):12182–6. - PMC - PubMed
1. Chen J, Aronow BJ, Jegga AG. Disease candidate gene identification and prioritization using protein interaction networks. BMC Bioinformatics. 2009;10:73. - PMC - PubMed

Ethanol modulation of gene networks: implications for alcoholism - PubMed (original) (raw)