This review summarizes the proceedings of a symposium presented at the "Alcoholism and Stress: A Framework for Future Treatment Strategies" conference held in Volterra, Italy on May 6-9, 2014. The overall goal of the symposium titled "Applying the New Genomics to Alcohol Dependence", chaired by Dr. Adron Harris, was to highlight recent genomic discoveries and applications for profiling alcohol use disorder (AUD). Dr. Sean Farris discussed the gene expression networks related to lifetime consumption of alcohol within human prefrontal cortex. Dr. Andrzej Pietrzykowski presented the effects of alcohol on microRNAs in humans and animal models. Alcohol-induced alterations in the synaptic transcriptome were discussed by Dr. Michael Miles. Dr. Pietro Sanna examined methods to probe the gene regulatory networks that drive excessive alcohol drinking, and Dr. Samir Zakhari served as a panel discussant and summarized the proceedings. Collectively, the presentations emphasized the power of integrating multiple levels of genetics and transcriptomics with convergent biological processes and phenotypic behaviors to determine causal factors of AUD. The combined use of diverse data types demonstrates how unique approaches and applications can help categorize genetic complexities into relevant biological networks using a systems-level model of disease.
Bibliographical noteFunding Information:
The following NIH/NIAAA grants provided funding for the work: AA017481 and AA017920 and a Pilot Project from the INIA-West consortium ( AA013517 ) to AZP; U01AA016667 and P20AA017828 to MFM and F31AA021035 to MAO; AA020960 and AA021667 to PPS; INIA-West consortium ( U01AA020926 ) and RC2AA019382 to RDM; INIA-West consortium ( U01AA013520 ) and AA012404 to RAH; and NIAAA Conference Grant AA017581 . Dr. Miles thanks members of his laboratory for support and Dr. John Bigbee for assistance in the characterization of synaptoneurosomal fractions. The authors thank Dr. Jody Mayfield for thoughtful critiques and help writing and editing the manuscript.
© 2015 Elsevier Inc.
- Gene expression networks
- Synaptic transcriptome
- Systems biology