Next, we updated the case and control groups of the previous GWAS population [10] with the latest clinical information and ended up with 411 POAG patients and 289 controls (hereafter referred to as ''Previous GWAS''; Figure 1A ). One SNP (rs8181047) of 5 genome-wide significant SNPs in CDKN2B-AS1 identified from the Present GWAS was not able to be assessed in the Previous GWAS because a DNA probe of that particular SNP was not designed for the Affymetrix 500 K platform. Consequently, we combined the two sets of GWAS genotype data for the remaining 4 SNPs by use of the Mantel-Haenszel test [19] , and the level of significance of all 4 SNPs increased from P,5.2610 29 to P,5.8610 210 (Table 1 ). These 4 SNPs were highly correlated with one another (r 2 .0.98), and were considered to have a similar effect for POAG based on the conditional analysis. These results suggested that it was effective to combine the data since the population stratification between the two data sets seemed to be ignorable, which was also supported by the results of the heterogeneity test. Moreover, we assessed the confounding effects for these SNPs with respect to age and gender, and none were found to be statistically significant (Table S2) , thus suggesting that the obtained association results were specific to the case-control comparison. In addition, the two sets of GWAS data for 40 SNPs surrounding the significant 4 SNPs in the 9p21.3 locus were also combined and analyzed (Table S3, Table S4 ). Since these 44 SNPs, in total, were genotyped in both the Present and Previous GWAS, and all of the SNPs passed the genotyping quality controls, these SNPs should prove useful in providing a broader overview of the significance of the locus. The results showed that the significance of combined SNPs was generally high between 22.0-22.1 Mb ( Figure 3A ). Within the particular locus, there seemed to be two distinct LD blocks; one in the side including genome-wide significant SNPs (''LD Block 1'' in Figure 3D ) and one in the other side with modestly associated SNPs (''LD Block 2'' in Figure 3D ). For the subtype analyses ( Figure 1B) , the POAG patients from both the Present and Previous GWAS populations were divided into two subtypes based on the clinical record of IOP measurement: 1) POAG patients with HPG (IOP$22 mmHg) and 2) those with NPG (i.e., patients who consistently showed an IOP of less than 22 mmHg) [3] . The number of subjects in each subtype was found to be 330 HPG and 503 NPG patients and 215 HPG and 196 NPG patients in the Present and Previous GWAS, respectively ( Figure 1B) . When we performed the analysis separately using the Present GWAS data set, the Q-Q plots of HPG vs control and NPG vs control appeared to be quite different from one another ( Figure S1B , C). In particular, the HPG results indicated non-deviated Q-Q plots ( Figure S1B ). In fact, although none of the SNPs were genome-wide significant for HPG ( Figure  S4A ), we obtained 4 genome-wide significant SNPs that passed the Bonferroni correction threshold for NPG (Table S1, Figure S4B ). As for NPG, the significance level of all 4 SNPs also increased when the two data sets were combined ( Figure 3C , Table S3 , Table S4 ), however, the significance was still far from the Bonferroni threshold of significance in relation to HPG ( Figure 3B , Table S3, Table S4) . Although the significance level of SNPs residing in LD Block 2 showed slight differences among the different subtypes, the level in LD Block 1 seemed to be determining the difference of significance between the two subtypes, thus suggesting that the variants on LD Block 1 are closely associated with the susceptibility to glaucoma in the 9p21.3 locus ( Figure 3D) . Surprisingly, all of the significant SNPs from NPG overlapped with those obtained from POAG (Table S1) . However, when we performed the heterogeneity test between the HPG and NPG groups, the results were not significant (P = 0.21-0.25, Table S3 ), suggesting that the significant differences between the two subtypes could be due to the small sample size of the HPG group. Although we need to confirm the above results using a larger HPG cohort, these results suggested that the significant SNPs identified in CDKN2B-AS1 on the 9p21.3 locus probably serve as genetic markers of glaucoma, which could be useful for investigating the etiology of glaucoma with respect to the vulnerability of the optic nerve to IOP.