Tobacco-related behaviors and the underlying addiction to nicotine are complex tangles of genetic and environmental factors. Efforts to understand the genetic component of these traits have identified sites in the genome (single nucleotide polymorphisms, or SNPs) that might account for some part of the role of genetics in nicotine addiction. Encouragingly, some of these candidate SNPs remain significant in meta-analyses. However, genetic associations cannot be fully assessed, regardless of statistical significance, without an understanding of the functional consequences of the alleles present at these SNPs. The proper experimental test for allelic function can be very difficult to define, representing a roadblock in translating genetic results into treatment to prevent smoking and other nicotine-related behaviors. This roadblock can be navigated in part with a new web-based tool, the Encyclopedia of DNA Elements (ENCODE). ENCODE is a compilation of searchable data on several types of biochemical functions or "marks" across the genome. These data can be queried for the co-localization of a candidate SNP and a biochemical mark. The presence of a SNP within a marked region of DNA enables the generation of better-informed hypotheses to test possible functional roles of alleles at a candidate SNP. Two examples of such co-localizations are presented. One example reveals ENCODE's ability to relate a candidate SNP's function with a gene very far from the physical location of the SNP. The second example reveals a new potential function of the SNP, rs4105144, that has been genetically associated with the number of cigarettes smoked per day. Details for accessing the ENCODE data for this SNP are provided to serve as a tutorial. By serving as a bridge between genetic associations and biochemical function, ENCODE has the power to propel progress in untangling the genetic aspects of nicotine addiction - a major public health concern.
All Science Journal Classification (ASJC) codes
- Clinical Biochemistry
- Biological Psychiatry
- Behavioral Neuroscience