A general observation from comparing across studies is that each GWAS results in largely a different set of candidate genes. This observation is not surprising and underscores the presence of extensive genetic heterogeneity that is well documented for alcohol dependence (Litten et al., 2015). A parsimonious explanation can be derived when genetic heterogeneity is viewed in terms of self-organizing, chaotic, and complex genetic networks, which some have described as a new biology for medicine. (Coffey, 1998; Hawrylycz et al., 2015). Thus, key biological networks may be disrupted via many different genetic perturbations. Even if the phenotype in every affected individual arises from a different specific genetic polymorphism, each will nonetheless share disruption of related key biological processes. This notion is supported by the finding that brain gene expression networks from human alcoholic brain were enriched for signals from GWAS of alcohol dependence (Farris et al., 2015). Defining the ways in which biological networks for alcohol dependence are impacted by genetic variation remains the challenge for the future and will contribute substantially to the understanding of the etiology and provide important targets for pharmacological intervention.
