Genome-wide association studies in pharmacogenomics: untapped potential for translation

Since 2007, genome-wide association studies (GWASs) have emerged as a powerful tool to identify disease-related genes for many common human disorders and other phenotypes [1]. The National Human Genome Research Institute (NHGRI) [2] and the Centers for Disease Control and Prevention (CDC) both maintain online resources for tracking published GWASs. Data from the CDC HuGE Navigator [3,4], an online, curated and searchable knowledge base in human genome epidemiology, show that the number of published GWASs grew from only a handful before 2007 to more than 300 as of mid-March 2009.GWASs are characterized by the need for very large study populations and replication samples because the expected effect sizes are small and the expected number of false positive findings is large [5,6]. Thus, although the cost of genotyping has decreased rapidly (and is expected to decrease further), GWASs remain a costly approach. Recently, the National Cancer Institute announced $96 million in grants over 4 years to support post-GWAS cancer studies to replicate and understand the biological basis of gene discoveries [7]. These investments are in addition to the approximately $3 billion spent on the Human Genome Project [8], which was justified to the public largely on the basis of its potential to identify genetic risk factors leading to prevention and treatment of common diseases.The conventional GWAS approach is a hypothesis-free, systematic search of tagging single nucleotide polymorphisms (SNPs) across the genome to identify novel associations with common diseases. Although many such associations have been found and replicated, their effect sizes are modest at best (odds ratios mostly between 1.0 and 1.5) and they generally lack sufficient clinical sensitivity, specificity and predictive value to serve as risk or screening markers [9]. Furthermore, in the absence of contextual information - such as potential functional implications at the molecular level, influence on physiologic proce