Discriminative accuracy of covariates, SNP-GRSS and CNV predicting BMI category in European- and African-Americans ModelAUC95% CIAsy. Sig. of ModelΔ AUC% Δ AUC p Δ AUC Overweight: n = 1443 (61.4%) 1. Covariates 0.679[0.657,0.700]2.68×10−48 --- 2. Model 1 + SNP-GRSS 0.692[0.671,0.714]9.23×10−56 0.0131.91% 0.001 3. Model 2 + CNV 0.694[0.672,0.715]1.27×10−56 0.0020.28%0.372 Obese Class I: n = 632 (26.9%) 1. Covariates 0.621[0.594,0.647]2.74×10−19 --- 2. Model 1 + SNP-GRSS 0.661[0.637,0.686]2.77×10−33 0.0406.44% 0.0001 3. Model 2 + CNV 0.662[0.638,0.687]1.12x10−33 0.0010.15%0.662 Obese Class II: n = 264 (11.2%) 1. Covariates 0.648[0.610,0.685]5.22×10−15 --- 2. Model 1 + SNP-GRSS 0.681[0.646,0.716]6.97×10−22 0.0335.09% 0.025 3. Model 2 + CNV 0.690[0.656,0.725]5.58×10−24 0.0091.32%0.123 Obese Class III: n = 106, (4.5%) 1. Covariates 0.711[0.660,0.762]1.97×1013 --- 2. Model 1 + SNP-GRSS 0.741[0.692,0.790]4.81×10−17 0.0304.22% 0.029 3. Model 2 + CNV 0.750[0.702,0.797]3.15×10−18 0.0091.21%0.152Note: BMI = body mass index kg/m2, SNP = single nucleotide polymorphism, SNP-GRSS = genetic risk sum score constructed from imputed probability of carrying 32 BMI-associated SNPs weighted by effect size reported in Speliotes et al. 2010, CNV = copy number variation, AUC = area-under the receiver operator criteria curve, Asy. Sig. = asymptotic significance, Δ AUC = change in AUC from previous model, % Δ AUC = percent change in AUC from previous
