Perhaps the most dramatic illustration of the utility of genotype imputation has been the ability of researchers to conduct meta-analysis of genomewide association scans even in samples that were originally genotyped using several different platforms. Genotype imputation was first used to combine genomewide association scans for blood lipid levels (43, 111) and height (89) and soon thereafter to combine data across genomewide scans for type 2 diabetes (116), body-mass index (62) and Crohn's disease (6). The success of these meta-analysis can be quite dramatic: in the case of blood lipid levels (43, 111) a meta-analysis of three studies with relatively modest findings (each identifying one to three strongly associated loci), resulted in a total of 19 strongly associated loci including 7 loci not previously implicated in regulating cholesterol and lipoprotein levels in humans. Because it greatly simplifies issues related to examining data collected on multiple different platforms, genotype imputation also makes it simple for researchers to compare results of genomewide association studies that target related traits. In this way, it has been possible to contrast results from genetic studies of
