Recent technological advances have enabled genome-wide association (GWA) studies. Here, single nucleotide polymorphisms (SNPs) across the entire genome are systematically tested for association with a given trait. The approach is considered “hypothesis-free” since no prior knowledge of gene function is considered. GWA studies have been successful in identifying some genetic variants underlying disease traits (Burton, et al., 2007; Visscher & Montgomery, 2009). They have also had some success in identifying genetic variants associated with smoking (e.g. LiuTozzi, et al., 2010), and with complex mental disorders including schizophrenia (Shi, et al., 2009; Stefansson, et al., 2009; The International Schizophrenia Consortium, 2009), bipolar disorder (The International Schizophrenia Consortium, 2009), and autism (Wang, et al., 2009). However, despite the high heritability of these disorders and traits, the identified genetic variants have been of very small effect (<1% of variance accounted for) and the aggregate effect of all the individual variants only accounts for a few percent of the trait variance, at most.
