Over the past 30 years, about 1,200 disease-causing genes have been identified by studying well characterized phenotypes and by using gene mapping techniques [1,2]. The same approach has not been as successful in identifying the genetic modifiers of common diseases that have a genetic component shown by familial aggregation but do not follow Mendelian laws of inheritance. Examples include many of the common age-related diseases such as hypertension [3], diabetes [4,5], cardiovascular disease [6], and dementia [7], which are presumed to be determined by several genes (epistasis), and their interaction with environmental factors (gene-environment interaction). These common traits are a large public health burden and the discovery of the genetic profiles that can be used for disease risk prediction, prevention or treatment is one of the priorities of modern “personalized” medicine. Genome-wide association studies (GWAS) of common diseases have begun to propel us toward this goal.
