Are we ready for genome-wide association studies?

The tension between hypothesis-driven and exploratory research crosses scientific disciplines (1) but is particularly well illustrated in the current excitement about genome-wide association (GWA) studies. Standard linkage analysis has the potential to localize major susceptibility genes to within a few million base pairs using as few as 300 microsatellite markers for a genome-wide scan. However, it has increasingly been recognized that linkage analysis may not be powerful enough to detect genes involved in ‘‘complex diseases’’ like cancer, which are caused by multiple genes and multiple environmental factors, interacting in complicated ways. Thus, molecular epidemiologists are turning to candidate-gene association studies or studies of entire candidate pathways, driven by specific biological hypotheses, as an alternative approach. Now comes the prospect, first seriously proposed a decade ago by Risch and Merikangas (2), of testing virtually all f10 million common single nucleotide polymorphisms (SNP) in the human genome for associations with a given disease, either directly or by linkage disequilibrium with other SNPs. Recent developments in ultra-high-volume genotyping chip technology now make the study of as many as 500,000 SNPs commercially viable. Coupled with the extensive haplotype tagging SNP information being catalogued by the HapMap project (3), it now seems that that this density may be sufficient to permit indirect tests of association with the majority of all common SNPs (4), although this fundamental assumption has recently been questioned (5). Does this development mark the end of pathway-driven research? I suggest that it is possible to marry the hypothesis-driven and exploratory approaches in a way that will make better use of this novel but expensive technology.