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Mining the genome for addiction genes
Aug 11, 2005, 17:08, Reviewed by: Dr.
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The authors identified 38 candidate genetic loci displaying robust allele frequency differences between abusers and controls, including an alcohol/acetaldehyde dehydrogenase gene cluster and genes involved in metabolism, cell signaling, gene regulation, development, and cell adhesion.
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By Proceedings of the National Academy of Sciences,
Using association genome scanning, Qing-Rong Liu et al. identified multiple genetic loci believed to be involved in drug addiction.
Unlike traditional gene identification methods for complex disorders, association genome scanning does not require the participation of family members and allows pooling of multiple samples. These attributes may help preserve confidentiality and reduce costs.
To determine the efficacy of this method in identifying potential drug addiction genes, Liu et al. used 10k SNP microarrays to analyze pooled DNA samples from polysubstance abusers (addicts who abuse multiple drugs) and control subjects.
The authors identified 38 candidate genetic loci displaying robust allele frequency differences between abusers and controls, including an alcohol/acetaldehyde dehydrogenase gene cluster and genes involved in metabolism, cell signaling, gene regulation, development, and cell adhesion. Because many of the genetic loci were comparable to linkage and association results from other methods, this study may validate association genome scanning as a reliable and cost-effective strategy to identify the genetic underpinnings of complex disorders. 
- "Pooled association genome scanning: Validation and use to identify addiction vulnerability loci in two samples" by Qing-Rong Liu, Tomas Drgon, Donna Walther, Catherine Johnson, Oxanna Poleskaya, Judith Hess, and George R. Uhl
Full Text at Proceedings of the National Academy of Sciences
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