Table 4.
Kynurenine pathway metabolites can predict subclinical CVD markers as demonstrated by multiple linear regression
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Principal components (% variance explained) | Metabolite(s) only | + Age, gender, race, prior CVD history | + SBP, DM | + eGFR, UPCR | + CRP, serum albumin | ||||||
| β (95% CI) | P-value | β (95% CI) | P-value | β (95% CI) | P-value | β (95% CI) | P-value | β (95% CI) | P-value | ||
| Aorta calcium score (n = 82) | TRP:AA | −57 | <.01 | −54 | <.01 | −46 | <.01 | −45 | <.01 | −45 | <.01 |
| (53.6%) | (−92 to −22) | (−85 to −22) | (−79 to −13) | (−79 to −10) | (−79 to −10) | ||||||
| Coronary calcium score (n = 82) | QA:HAA:AA | 32 | <.01 | 28 | <.01 | 23 | <.01 | 24 | .01 | 23 | .01 |
| (60.2%) | (16–47) | (13–42) | (6.6–39) | (5.5–42) | (5.1–42) | ||||||
| Agatston CT score (n = 82) | KYN:KA:QA:HAA:AA | 9.4 | <.01 | 8.5 | <.01 | 6.7 | .03 | 8.6 | .03 | 7.6 | .07 |
| (58.3%) | (3.4–15.4) | (2.9–14.1) | (0.8–12.6) | (0.7–16.4) | (−0.5–15.7) | ||||||
| CIMT (n = 180) | QA:HAA | 0.012 | .02 | 0.007 | .07 | 0.005 | .18 | 0.005 | .26 | 0.006 | .20 |
| (71.9%) | (0.002–0.021) | (-0.001–0.015) | (-0.002–0.013) | (-0.004–0.014) | (-0.003–0.015) | ||||||
| LVMI (n = 121) | QA:AA | 0.593 | <.01 | 0.395 | .05 | 0.395 | .04 | 0.293 | .13 | 0.319 | .08 |
| (69.4%) | (0.163–1.023) | (0.007–0.783) | (0.025–0.765) | (−0.088–0.673) | (−0.041–0.679) | ||||||
| PWV (n = 75) | TRP:AA | −0.050 | <.01 | −0.038 | .02 | −0.031 | .04 | −0.019 | .25 | −0.018 | .28 |
| (53.6%) | (−0.086 to −0.014) | (−0.071 to −0.006) | (−0.062 to −0.001) | (−0.051–0.013) | (−0.050–0.015) | ||||||
DM, diabetes mellitus; CRP, C-reactive protein; TRP, tryptophan; AA, anthranilic acid; QA, quinolinic acid; HAA, hydroxyanthranilic acid; KYN, kynurenine; KA, kynurenic acid. Parameter estimates (β), 95% CIs and P-values are displayed. Statistically significant (P < .05) parameter estimates and P-values are in bold.