Background: Large scale untargeted metabolomics studies are needed to understand the mechanisms of arterial stiffness.
Methods: We performed untargeted metabolomics profiling among 1,239 participants of the biracial Bogalusa Heart Study. After quality control, 1,202 metabolites were evaluated for associations with augmentation index (AI) and pulse-wave velocity (PWV) overall and by race, adjusting for age, sex, education, smoking, drinking, body mass index, and physical activity. Weighted correlation network analysis (WGCNA) was applied to build metabolites modules among all participants. Bonferroni correction was used to determine significant metabolites. Significant metabolites should also have P<0.05 and consistent effect directions in both races.
Results: We identified 4 and 17 novel metabolites associated with AI and PWV, respectively (Table). We also replicated associations of 12 previously reported metabolites with PWV in the overall sample, including 1,5-anhydroglucitol (P=5.55E-9), glucose (P=8.19E-14), glutamic acid (P=1.56E-8), glycine (P=9.87E-6), serine (P=0.003), urea (P=0.03), uridine (P=0.002), glutamine (P=0.001), 3-phenylpropionate (P=0.004), trans-4-hydroxyproline (P=0.001), pyruvate (P=0.002), and lysine (P=0.007). WGCNA identified two modules in significant associations with both AI (P=3E-4 and 8E-4, respectively) and PWV (P=2E-6 and 7E-5, respectively). One module was composed of metabolites of glycerolipids recycling pathway. The other module consisted of amino acids involved in glutamate, leucine, isoleucine, valine, methionione, systein, taurine, and alanine metabolisms. WGCNA also identified a network of sphingolipid metabolism for PWV (P=0.002). Investigation to hub metabolites of these modules identified 3 novel metabolites for AI and 4 novel metabolites for PWV (Table).
Conclusions: The current study identified important metabolites and metabolites networks associated with AI and PWV.