Identifying genetic variants that influence common complex diseases can provide valuable insights into their pathogenesis, prevention, and treatment. With well-defined clinical cohorts and the availability of high-quality and cost-effective genotyping platforms that capture much of human genetic variation [Barrett and Cardon, 2006; The International HapMap Consortium, 2005], the most recent wave of genome-wide association (GWA) studies have been well powered to detect “moderate” genetic effects. The much-publicized Wellcome Trust Case Control Consortium (WTCCC) was established to explore the utility, design, and analysis of GWA studies, aiming to improve our understanding of the aetiological basis of several common diseases, including coronary artery disease (CAD), type 1 and type 2 diabetes (T1D and T2D), and rheumatoid arthritis (RA). The main WTCCC experiment in 2,000 cases of each of seven diseases and 3,000 shared controls from the United Kingdom was powered to detect common variants with allelic odds ratios of the order of 1.5–1.7 [The Wellcome Trust Case Control Consortium, 2007]. The study identified many novel genetic associations, the majority of which have now been replicated in independent samples from the same and/or
