Table 2.
Clinical correlates of Angiopoietin-2 and soluble Tie-2 as determined by linear regression models.
| Increase/decrease in log-Biomarker level |
Percent increase/decrease in biomarker in natural units |
||||||
|---|---|---|---|---|---|---|---|
| 95% confidence interval | 95% confidence interval | ||||||
| Angiopoietin-2 | Estimate | Lower Limit | Upper Limit | Estimate | Lower Limit | Upper Limit | p-value |
| Age, years | 0.019 | 0.003 | 0.035 | 1.92% | 0.30% | 3.56% | 0.02 |
| Men | −0.149 | −0.178 | −0.12 | −13.84% | −16.31% | −11.31% | <.0001 |
| Smoking | 0.159 | 0.119 | 0.198 | 17.23% | 12.64% | 21.90% | <.0001 |
| Total cholesterol, mg/dL | −0.037 | −0.051 | −0.023 | −3.63% | −4.97% | −2.27% | <.0001 |
| Antihypertensive Medication | 0.091 | 0.04 | 0.142 | 9.53% | 4.08% | 15.26% | 0.0004 |
| Diastolic blood pressure, mm Hg | −0.045 | −0.064 | −0.025 | −4.40% | −6.20% | −2.47% | <.0001 |
| Systolic blood pressure, mm Hg | 0.031 | 0.011 | 0.051 | 3.15% | 1.11% | 5.23% | 0.003 |
| Diabetes | 0.097 | 0.001 | 0.192 | 10.19% | 0.10% | 21.17% | 0.048 |
| Soluble Tie-2 | |||||||
| Age, years | −0.045 | −0.056 | −0.034 | −4.40% | −5.45% | −3.34% | <.0001 |
| Men | 0.043 | 0.024 | 0.062 | 4.39% | 2.43% | 6.40% | <.0001 |
| Body mass index, kg/m2 | 0.016 | 0.006 | 0.027 | 1.61% | 0.60% | 2.74% | 0.002 |
| Diabetes | 0.102 | 0.04 | 0.164 | 10.74% | 4.08% | 17.82% | 0.001 |
| eGFR, ml/min/1.73m2 | −0.017 | −0.027 | −0.007 | −1.69% | −2.66% | −0.70% | 0.0005 |
| Alcohol consumption | −0.011 | −0.023 | −0.0004 | −1.09% | −2.27% | −0.04% | 0.04 |
| Triglycerides, mg/dL | 0.012 | 0.003 | 0.021 | 1.21% | 0.30% | 2.12% | 0.01 |
The first three columns describe the estimates (and 95% CI) representing the increase in log-biomarker levels per 1-SD increment in the predictor variable for continuous traits. For binary traits, estimates indicate increase in log-biomarker levels for presence vs. absence of the trait. For example, men have 14% lower (e−0.149 =0.86) Ang-2 levels as compared to women, adjusting for all other covariates in the model. In the next three columns, the % change in biomarker levels in natural units per 1-SD increment in the predictor variable (presence vs. absence of binary traits) is shown. The multivariable model explained 6.8% and 3.8% of the inter-individual variation in circulating Ang-2 and sTie-2 concentrations, respectively.
Alcohol consumption in ounces per week.