Table 4.
Association between CAD PRS and 1-year change in risk factors by study intervention
| CRF | All study participants (n = 2,658) | PBO (n = 888) | MET (n = 880) | ILS (n = 890) | ||||
|---|---|---|---|---|---|---|---|---|
| β (95% CI) | P* | β (95% CI) | P* | β (95% CI) | P* | β (95% CI) | P* | |
| BMI, kg/m2 | 0.013 (−0.084, 0.109) | 0.799 | 0.015 (−0.134, 0.164) | 0.841 | 0.021 (−0.121, 0.163) | 0.770 | 0.001 (−0.204, −0.201) | 0.994 |
| Waist circumference, cm | −0.027 (−0.330, 0.277) | 0.863 | −0.008 (−0.474, 0.457) | 0.972 | −0.212 (−0.724, 0.288) | 0.398 | 0.168 (−0.433, 0.769) | 0.584 |
| Fasting glucose, mmol/L# | 0.998 (0.994, 1.004) | 0.728 | 0.999 (0.988, 1.005) | 0.414 | 0.998 (0.991, 1.005) | 0.526 | 1.002 (0.995, 1.011) | 0.502 |
| Diabetes risk | 1.021 (0.919, 1.136) | 0.696 | 0.952 (0.809, 1.120) | 0.552 | 1.088 (0.904, 1.309) | 0.371 | 1.068 (0.851, 1.341) | 0.571 |
| LDLc, mmol/L | 0.010 (−0.017, 0.036) | 0.481 | 0.012 (−0.036, 0.059) | 0.632 | −0.019 (−0.065, 0.028) | 0.424 | 0.034 (−0.012, 0.080) | 0.152 |
| HDLc, mmol/L | −0.007 (−0.015, 0.001) | 0.075 | −0.009 (−0.022, 0.003) | 0.147 | −0.002 (−0.016, 0.012) | 0.822 | −0.013 (−0.028, 0.002) | 0.094 |
| TG, mmol/L# | 1.016 (0.999, 1.033) | 0.059 | 1.009 (0.998, 1.038) | 0.562 | 1.011 (0.993, 1.040) | 0.427 | 1.028 (0.999, 1.058) | 0.063 |
| SBP, mmHg | 0.489 (−0.088, 1.067) | 0.097 | 0.685 (−0.314, 1.683) | 0.179 | −0.288 (−1.267, 0.692) | 0.565 | 0.951 (−0.073, 1.974) | 0.069 |
| DBP, mmHg | 0.085 (−0.291, 0.462) | 0.657 | 0.052 (−0.606, 0.711) | 0.876 | −0.150 (−0.797, 0.497) | 0.649 | 0.256 (−0.398, 0.911) | 0.442 |
| CRP, mg/dL# | 0.981 (0.947, 1.015) | 0.272 | 0.967 (0.913, 1.024) | 0.252 | 1.007 (0.946, 1.067) | 0.811 | 0.971 (0.927, 1.033) | 0.354 |
| tPA, ng/mL | 0.056 (−0.085, 0.197) | 0.440 | 0.090 (−0.162, 0.024) | 0.484 | 0.081 (−0.155, 0.318) | 0.501 | 0.229 (−0.214, 0.259) | 0.850 |
| Fibrinogen, μmol/L | −0.019 (−0.106, 0.069) | 0.679 | −0.028 (−0.188, 0.131) | 0.728 | 0.006 (−0.142, 0.154) | 0.935 | −0.037 (−0.188, 0.115) | 0.634 |
Each CRF represents a separate linear regression model on the association between 1-year change in CRF levels and the increment of 10 risk alleles in the PRS. Cox models were used to investigate the association between CAD PRS and diabetes incidence; estimates are reported as hazard ratios (95% CI).
#
Regression coefficients for natural log–transformed CRFs are expressed as exp(β) ratio of 1-year change in CAD risk factors in the entire study population and according to intervention group.
*
P value derived by general linear model adjusted for baseline risk factor, age at randomization, sex, and PCs ancestry markers.