Table 3a.
Comparisons of Results from the Logistic Regression and Proposed Hierarchical Modeling Approaches – Main G Effects
| SNP (Gene) | Loaistic Regression | HM1a | HM1b | HM2a | HM2b | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| OR (95% CI) | Wald P | OR (95% CI) | Posterior P | OR (95% CI) | Posterior P | OR (95% CI) | Posterior P | OR (95% CI) | Posterior P | |
| ADRB2 | 1.00 (0.73, 1.38) | 0.988 | 1.00 (0.73, 1.33) | 0.457 | 1.04 (0.80, 1.33) | 0.41 | 1.06 (0.92, 1.22) | 0.225 | 1.06 (0.92, 1.22) | 0.211 |
| CAT | 0.58 (0.41, 0.82) | 0.002 | 0.63 (0.45, 0.84) | <0.001 | 0.64 (0.46, 0.85) | 0.001 | 0.93 (0.79, 1.06) | 0.135 | 0.76 (0.63, 0.89) | <0.001 |
| CC16 | 1.66 (1.21, 2.27) | 0.002 | 1.55 (1.16, 2.05) | 0.002 | 1.59 (1.18, 2.11) | 0.003 | 1.12 (0.97, 1.29) | 0.057 | 1.41 (1.17, 1.69) | <0.001 |
| EPHX1 | 1.31 (0.95, 1.81) | 0.098 | 1.30 (0.95, 1.71) | 0.05 | 1.25 (0.93, 1.64) | 0.071 | 1.02 (0.89, 1.16) | 0.406 | 1.03 (0.89, 1.18) | 0.378 |
| GPX1 | 1.15 (0.85, 1.57) | 0.362 | 1.18 (0.87, 1.57) | 0.164 | 1.15 (0.87, 1.50) | 0.181 | 1.01 (0.89, 1.15) | 0.457 | 1.02 (0.89, 1.18) | 0.386 |
| GSTM1 | 0.90 (0.66, 1.24) | 0.529 | 0.93 (0.69, 1.24) | 0.298 | 0.91 (0.68, 1.19) | 0.253 | 1.00 (0.87, 1.15) | 0.501 | 0.86 (0.73, 1.01) | 0.032 |
| GSTM3 | 1.15 (0.82, 1.61) | 0.423 | 1.16 (0.82, 1.57) | 0.193 | 1.07 (0.80, 1.43) | 0.365 | 0.96 (0.83, 1.09) | 0.244 | 0.95 (0.83, 1.09) | 0.215 |
| GSTP1 | 1.28 (0.93, 1.76) | 0.127 | 1.27 (0.94, 1.70) | 0.062 | 1.23 (0.93, 1.62) | 0.078 | 1.05 (0.92, 1.20) | 0.265 | 1.04 (0.91, 1.19) | 0.312 |
| HO1 | 0.75 (0.54, 1.04) | 0.088 | 0.81 (0.58, 1.08) | 0.075 | 0.74 (0.55, 0.98) | 0.017 | 0.99 (0.86, 1.15) | 0.429 | 0.82 (0.70, 0.97) | 0.008 |
| ICAM-1 | 1.01 (0.70, 1.46) | 0.949 | 1.01 (0.70, 1.39) | 0.51 | 1.07 (0.74, 1.46) | 0.365 | 1.01 (0.87, 1.17) | 0.453 | 1.24 (1.03, 1.47) | 0.008 |
| MMP9 | 0.81 (0.60, 1.11) | 0.192 | 0.86 (0.63, 1.14) | 0.144 | 0.88 (0.66, 1.16) | 0.181 | 0.99 (0.86, 1.11) | 0.405 | 1.12 (0.94, 1.31) | 0.102 |
| NOS3 | 1.00 (0.73, 1.37) | 0.999 | 0.99 (0.72, 1.32) | 0.453 | 1.02 (0.76, 1.35) | 0.473 | 1.04 (0.91, 1.19) | 0.325 | 1.04 (0.91, 1.19) | 0.287 |
| NQO1 | 0.60 (0.43, 0.84) | 0.003 | 0.66 (0.48, 0.90) | 0.004 | 0.67 (0.49, 0.89) | 0.002 | 0.94 (0.82, 1.08) | 0.178 | 0.77 (0.65, 0.90) | 0.002 |
| PPARR | 1.36 (0.94, 1.98) | 0.107 | 1.36 (0.93, 1.91) | 0.064 | 1.27 (0.90, 1.74) | 0.087 | 1.06 (0.92, 1.24) | 0.206 | 1.05 (0.89, 1.24) | 0.279 |
| TGFβ1 | 1.05 (0.77, 1.44) | 0.74 | 1.07 (0.80, 1.38) | 0.344 | 1.10 (0.81, 1.45) | 0.287 | 0.99 (0.86, 1.13) | 0.414 | 1.22 (1.02, 1.44) | 0.013 |
| TNFA | 1.47 (1.05, 2.07) | 0.027 | 1.40 (1.00, 1.88) | 0.025 | 1.48 (1.07, 1.98) | 0.007 | 1.03 (0.88, 1.18) | 0.372 | 1.28 (1.08, 1.53) | 0.002 |
Note: For the standard one-level logistic regression analysis, maximum likelihood estimates of odds ratios (ORs), 95% confidence intervals (CIs), and p value of Wald significant testing were reported in this summary table.
Note: For each of the four hierarchical modeling approaches, posterior estimates of odds ratios (ORs), 95% credible intervals (CIs), and p value were reported in this summary table.
Note: Statisitcal significant findings (two-sided p values less than 5%) were highlighted in red.