One approach to describing the convergence between these datasets relies on the overall convergence, as described above. Another approach relies on identifying the numbers of nominally-positive SNPs that lie in genes nominated by an initial dataset. We begin here with the set of genes identified in [68
], which were initially identified on the basis of strong support from clustered, reproducibly-positive SNPs in European- and African American samples from NIDA with more modest levels of support from 100k SNP genome wide association datasets from JGIDA methamphetamine-dependence and COGA alcohol-dependence samples.
Current availability of data based on 520,000 – 630,000 autosomal SNPs from these samples, our ability to move these datasets to the more-complete build 36.1 of the NCBI human genome assembly and the availability of data from other samples listed above provides the data for . To be able to display data from all of the samples in the same way, this table documents convergence of data from all nominally positive SNPs (not just those that cluster). Nevertheless, this data strongly supports the overall convergences documented in the simulations above for virtually all of the genes identified in Liu et al
]. Altered marker locations in human genome build 36 data do move previously-reported positive association signals away from the PCDH9, DEFB1 and XKR5 genes that are included in build 35 data in Liu et al
Table I Genes and classes of genes that contain clustered SNPs that provide nominally-significant abuser vs control differences in both European-American and African-American NIDA (N) samples . The numbers of SNPs within each gene (exons +/− 100kb (more ...)
The genes that we identify in this way are involved in cell adhesion, enzymatic activities, protein translation, trafficking and degradation; transcriptional regulation, receptor, ion channel and transport processes, disease processes, cell structures and other functions (). Most are expressed in the brain. The genes whose products are involved in cell adhesion processes provide especially interesting results. Cell adhesion mechanisms are central for properly establishing and regulating neuronal connections during development and can play major roles in mnemonic processes in adults [89
]. Almost all of these cell adhesion-related genes are expressed in brain regions involved in memory, including hippocampus and cerebral cortex. By contrast, substantial expression in mesolimbic/mesocortical dopamine “reward system” neurons is not documented for most. These genes represent glycophosphoinositol (GPI)-anchored, single-transmembrane, and seven transmembrane cell adhesion molecules as well as genes whose products bind to cell adhesion-related protein complexes including CTNND2, TRIO, CTNNA3, ANKS1B and POSTN. These cell adhesion related genes thus provide attractive candidates for future studies of their possible relationships with addiction phenotypes.
Our identification of SNP markers whose allelic frequencies distinguish addicts of several different ethnicities from matched controls supports “common disease/common allele” genetic architecture [68
] for addiction vulnerability. The convergent data derived from studies of individuals with addictions to substances in several different pharmacological classes supports the idea that “higher order pharmacogenomic/pharmacogenetic” variations enhance vulnerability to many addictions. These results do not exclude additional contributions to addiction vulnerability from genomic variants that influence vulnerability to specific substances or variants that are found only in specific populations. Nevertheless, the findings presented here provide promise for enhancing understanding of features that are common to human addictions in ways that could facilitate efforts to personalize prevention and treatment strategies for debilitating addictive disorders.