(those changed in all three experiments) included CD81molecule, nucleoporin like 1, phosphatidylethanolamine-binding protein and aldehyde dehydrogenase 6 family,member A1.The studies outlined in this section demonstrate that largedata sets of gene expression data can be combined withbehavioural and genetic data to identify genes or functionalpathways that underlie ethanol-related phenotypes andother complex traits.Looking into the futureIncreasingly sophisticated genetic tools (haplotype and SNPmaps, mapping arrays, expression arrays and so on) are beingapplied to complex diseases ranging from cancer to schizo-phrenia. What is the desired or imagined outcome for suchstudies? For most diseases, genetic or genomic assessment ofrisk or susceptibility is a goal. Breast cancer prediction is anarea where genetics have been aggressively developed andmarketed, although the accuracy of such markers remainscontroversial. For alcoholism, family history and personalhistory are strong predictors of risk and it is not clear thatgeneticmarkersofriskwillbeapracticalorusefulcontribution. Areas of more importance for alcoholism are‘genetic medicines’ and genomic/proteomic biomarkers foralcohol abuse. The success (or lack thereof) for naltrexone inthe treatment of alcohol dependence depends in part on apolymorphism in themopioid receptor, and this gives thepossibility of genotype-based selection of pharmacotherapyfor alcoholism (Oslinet al., 2006). Another likely applicationof ‘omics’ to addiction medicine is selection of biomarkersfor alcohol and drug dependence or abuse based on changesin gene expression or protein levels in blood samples.Sensitive and selective biomarkers can only be defined aftermeasuring many different transcripts or proteins with arraytechnologies. This review presents many ‘candidate’ genesfor alcohol and drug dependence and a plethora of changesin gene expression that might, or might not, be responsiblefor development of dependence. When will we move past‘candidates’ to ‘defined’ genes? The history of genetics ofcomplex diseases brings great excitement about new techni-ques with large increases in genetic power (for example,selected lines, recombinant inbred strains, QTL analysis,gene expression arrays, SNP maps and so on). But applicationof these new approaches reveals that the complexity of thedisease and the genetics of the organism are much greaterthan we appreciated. This leads to the development of newapproaches, which reveal new complexities. The immediatefuture may bring the realization that we will not be able todefine the genetics of dependence until we better under-stand how genes interact with environmental variables toinfluence drug responses and related behaviours.