"Higher order" addiction molecular genetics: convergent data from genome-wide association in humans and mice

Abstract

Family, adoption and twin data each support substantial heritability for addictions. Most of this heritable influence is not substance-specific. The overlapping genetic vulnerability for developing dependence on a variety of addictive substances suggests large roles for "higher order" pharamacogenomics in addiction molecular genetics. We and others have now completed genome-wide association (GWA) studies of DNAs from individuals with dependence on a variety of addictive substances versus appropriate controls. Recently reported replicated GWA observations identify a number of genes based on comparisons between controls and European-American and African-American polysubstance abusers. Here we review the convergence between these results and data that compares control samples and (a) alcohol-dependent European-Americans, (b) methamphetamine-dependent Asians and (c) nicotine dependent samples from European backgrounds. We also compare these human data to quantitative trait locus (QTL) results from studies of addiction-related phenotypes in mice that focus on alcohol, methamphetamine and barbiturates. These comparisons support a genetic architecture built from largely polygenic contributions of common allelic variants to dependence on a variety of legal and illegal substances. Many of the gene variants identified in this way are likely to alter specification and maintenance of neuronal connections.

Figure 1

Diagram of the chromosomal locations of linkage peaks with nominally significant LOD scores (as defined by the papers authors) for smoking related phenotypes in individual or repeated analyses of data from Framingham study participants, participants in the Collaborative Study on the Genetics of Alcoholism (COGA), smokers recruited in New Zealand and in Richmond, Virginia, nicotine family study participants in Oregon, Mission Indian samples studied for alcohol and smoking phenotype and participants in anxiety clinics [, , , –60]. Convergence between these results does not differ from chance in Monte Carlo simulations.