Table 2.

Combined logistic regression of 11 SNPs and POAG

		Estimate	Standard Error	p value
Intercept		−0.833	0.334	0.0126
African continental ancestry		0.432	0.250	0.0838
rs10529326	TMCO1	0.364	0.073	5.4×10−7
rs2432663	CYP1B1	0.476	0.119	6.3×10−5
rs199612704	FNDC3B	0.818	0.163	4.9×10−7
rs4328916	AFAP1	0.197	0.048	4.3×10−5
rs7009228	8q22	0.259	0.051	5.1×10−7
rs2383204	9p21#1	0.232	0.051	4.9×10−6
rs79721419	9p21#2	0.616	0.151	4.5×10−4
rs551169	ABO	0.196	0.046	1.7×10−5
rs8080535	GAS7	0.159	0.047	0.00071
rs235902	MYOC	0.174	0.067	0.0092
rs1332985	PMM2	0.104	0.053	0.050

The genotypes of those SNPs in Table 1 with negative effect sizes were re-coded to the other allele so that the number of alleles for each SNP was additive for increased POAG risk. All SNPs were then combined into a single logistic regression model. AD for each subject was estimated using Admixture 1.3.0 with K=3 on a subset of the genotyping data pruned for linkage disequilibrium. The dataset for this table, with genotypes coded to be additive, was then used to create Genetic Risk Score #1. Note that both 9p21 SNPs, rs2383204 and rs79721419, remained in this model, further supporting their statistical independence.