Metabolic Signatures in Coronary Artery Disease: Results from the BioHEART-CT Study

2021 
Despite effective prevention programs targeting cardiovascular risk factors, coronary artery disease (CAD) remains the leading cause of death. Novel biomarkers are needed for improved risk stratification and primary prevention. To assess for independent associations between plasma metabolites and specific CAD plaque phenotypes we performed liquid chromatography mass-spectrometry on plasma from 1002 patients in the BioHEART-CT study. Four metabolites were examined as candidate biomarkers. Dimethylguanidino valerate (DMGV) was associated with presence and amount of CAD (OR) 1.41 (95% Confidence Interval [CI] 1.12–1.79, p = 0.004), calcified plaque, and obstructive CAD (p < 0.05 for both). The association with amount of plaque remained after adjustment for traditional risk factors, s-coefficient 0.17 (95% CI 0.02–0.32, p = 0.026). Glutamate was associated with the presence of non-calcified plaque, OR 1.48 (95% CI 1.09–2.01, p = 0.011). Phenylalanine was associated with amount of CAD, s-coefficient 0.33 (95% CI 0.04–0.62, p = 0.025), amount of calcified plaque, (s-coefficient 0.88, 95% CI 0.23–1.53, p = 0.008), and obstructive CAD, OR 1.84 (95% CI 1.01–3.31, p = 0.046). Trimethylamine N-oxide was negatively associated non-calcified plaque OR 0.72 (95% CI 0.53–0.97, p = 0.029) and the association remained when adjusted for traditional risk factors. In targeted metabolomic analyses including 53 known metabolites and controlling for a 5% false discovery rate, DMGV was strongly associated with the presence of calcified plaque, OR 1.59 (95% CI 1.26–2.01, p = 0.006), obstructive CAD, OR 2.33 (95% CI 1.59–3.43, p = 0.0009), and amount of CAD, s-coefficient 0.3 (95% CI 0.14–0.45, p = 0.014). In multivariate analyses the lipid and nucleotide metabolic pathways were both associated with the presence of CAD, after adjustment for traditional risk factors. We report novel associations between CAD plaque phenotypes and four metabolites previously associated with CAD. We also identified two metabolic pathways strongly associated with CAD, independent of traditional risk factors. These pathways warrant further investigation at both a biomarker and mechanistic level.
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