By adopting this approach, we2and others3have used the genome-wide association study (GWAS) approach to identify novel susceptibility genes for glioma. In our study, we genotyped 550 000 tagging SNPs in a total of 1878 cases and 3670 controls, with validation in 3 additional independent series totaling 2545 glioma cases and 2953 controls. We have used publicly available controls, and they provide a cost-effective strategy for identifying genetic factors for many diseases. However, such public controls may not be useful for identifying gene environment factors because the environment of interest may not be available for these data sets. We identified 5 risk loci for glioma (shown in the Tableand Figure), namely, 5p15.33 (TERT, OMIM 187270), 8q24.21 (CCDC26, OMIM 613040), 9p21.3 (CDKN2A, OMIM 600160, and CDKN2B, OMIM 600431), 20q13.33 (RTEL1, OMIM 608833), and 11q23.3 (PHLDB1, OMIM 612834), and our results were in whole or in part based on the glioma GWAS data of Shete et al.2The second reported GWAS of glioma, conducted by Wrensch and colleagues,3was based on an analysis of 275 895 SNPs in 692 adult high-grade glioma cases and 3992 controls with a replication series of 176 high-grade glioma cases and 174 controls. This analysis provided further evidence to implicate the 9p21.3 (CDKN2A-CDKN2B) and 20q13.33 (RTEL1) variants.