The challenge of non-replication in candidate gene studies, the desire for identification of novel variants for addiction and the decreasing costs and increasing efficiency of large-scale, high-density genotyping has led to the increasing use of GWAS to study addiction. The primary challenge in these studies is the profound burden of multiple testing, which requires gene variants to exceed a threshold P-value of 5 × 10−8 for statistical significance. Initial GWAS of smoking (for example, N=2000),81 alcohol dependence (N=1884–3865)82, 83, 84, 85 (and heavy consumption, for example, N=3400–400086) and cannabis dependence (for example, N=3054)87 failed to find any statistically significant associations. Immediately recognizing the need for considerably larger samples, multiple research groups combined GWAS data to produce large meta-analyses. Studying cigarettes smoked per day (an indicator of liability to nicotine dependence), the Tobacco and Genetics Consortium (N=74,053),88 Thorgeirsson et al. (N=10,995)89 and Liu et al. (N=41,150)90 simultaneously identified rs1051730, which is highly correlated with a functional missense polymorphism (rs16969968) in the nicotinic acetylcholine receptor gene cluster (CHRNA5/A3/B4) on 15q25. It is worth noting that although the first study to identify the
