ANALYSIS HIGHLIGHTS NEW AREAS OF RESEARCH INTO GENETIC CAUSES OF ALCOHOLISM
18 April 2006 - University of Texas at Austin

The findings of a meta-analysis of microarray data of several mouse models that differ in voluntary alcohol consumption highlight new neurobiological targets for further study and provide researchers with a novel statistical approach for use in future microarray meta-analyses.

Insight into the genetic differences in gene expression associated with different levels of drinking may lead to a better understanding of alcoholism. Genetic studies of alcoholism have long confirmed the complexity of the disease and uncovering the underlying molecular mechanisms remains a formidable task.

The meta-analysis was completed by Susan Bergeson, an assistant professor of neurobiology at The University of Texas at Austin, and a multi-site research team participating in a National Institute on Alcohol Abuse and Alcoholism-supported Integrative Neuroscience Initiative on Alcoholism. It has led to new insights into the genetics of the predisposition to drink alcohol.

“What our results do is essentially generate candidate genes to be tested,” Bergeson said. “Many of the genes we identified have never previously been implicated in alcohol drinking, including several whose function remains completely unknown.”

The analysis involved nine mouse models, which differed in their levels of alcohol consumption. None of the mice were exposed to alcohol because the focus of the experiment was to study the genetic predisposition to drink alcohol.

Gene expression in the brain was assayed using microarray analysis, and a novel statistical approach to the meta-analysis identified nearly 4,000 differentially regulated genes between the high and low alcohol consuming mice.

The INIA investigators narrowed the significant changes using three different approaches.

An overlap analysis between human and mouse was completed using chromosomal regions shown to be associated with drinking and alcohol dependence in previously reported genetic studies. Thirty-three genes in the meta-analysis matched these regions where the human and mouse genetic alignments are the same; 11 were from three gene families.

In addition, the thousands of genes were narrowed to a much shorter list using bioinformatics approaches that identified overrepresentation within pathways.

Finally, 20 genes for one chromosomal region long been known to be involved in alcohol drinking in mice were identified using a novel filtering approach.

“We were able to measure total brain gene expression in each mouse model and narrow thousands of candidate genes to a transcriptional fingerprint in a way that would have been considerably more difficult without the meta-analysis,” Bergeson said. “In addition, there were several genes found associated with drinking in this study that have never previously been characterized. If we had done nothing else but point to a gene that would have not been otherwise discovered, that was a valuable thing to do.”

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