strong evidence of functionality identified via candidate gene association or linkage, may provide clues for ultimate validation for GWAS (see Fig. 1). Further, hypothesis-generation is one of the core features of the GWAS design and puts first a primary objective of biological discovery rather than risk prediction as promulgated by Hirschhorn (2009) and others (Cantor et al., 2010; Hall et al., 2016; Hirschhorn, 2009). The GWAS agnostic discovery approach effectively enables the potential to identify hitherto unknown and novel genes displaying a wide range of biological functions, which will be critical for a comprehensive understanding of the etiology of AUD. However, caution should still be taken when functional hypotheses are considered from the existing GWAS of alcohol dependence. Until sufficient sample sizes can be tested and results replicated, any one of the candidate genes we discuss could be a false positive due to the curse of stringent statistical corrections required for reducing false positive results due to multiple testing; however this stringent statistical threshold could very well hide evidence for identification of true positives as novel variants. Below we present the findings of a series of GWAS of alcohol dependence where biological functional information could be derived relevant to the
