Furthermore, there have been very few replicated associations other than the original SNP and some SNPs in nearby genes. Clearly this example alone is not evidence of the general predictive power of biological information, in this case a missense SNP in a gene whose protein product binds to the drug of interest, to predict true genetic association. Nevertheless, the results from a study by Saccone et al. (3) show that commercial SNP microarrays may miss a significant amount of coverage in some genes. The fact that an overall GWAS could be negative due to the omission of a single SNP that could be discovered by another study targeting a small number of highly biologically relevant SNPs [rs16969968 was in the top 10 over all of dbSNP when we used the GIN method to prioritize for nicotine dependence (4)] is something for GWAS researchers to consider, both for the post-GWAS selection of SNPs for further study and for the pre-GWAS supplementation of commercial arrays (3).
