My NIDA funded research investigates the biological mechanisms underlying the high relapse rate among smokers using electrophysiology, behavior, and Next Gen Sequencing technologies. Our lab has extensive experience using Next-Gen sequencing approaches to identify candidate molecules for functional evaluation in both rodent models and in the human population. For example, sequencing technologies identified a novel molecule, Neuregulin 3, in mechanisms underlying nicotine withdrawal phenotypes. We have now validated this association two independent cohorts of smokers, demonstrating that possession of a NRG3 risk allele can predict relapse to smoking (Turner et al, Mol Psych, 2014). This approach is an excellent example of how analytic integration of functional and genetic information across multiple species can accelerate the implementation of personalized medicine, such as that present in this application. Dr. Vassoler and myself are now proposing a similar approach to better understand how epigenomic changes and consequential transcriptomic alterations can drive complex behavioral responses in the offspring of drug-exposed individuals. I look forward to continuing to work with Dr. Vassoler on this project.
