Abstract
BACKGROUND: Contemporary risk assessment in patients with coronary atherosclerotic disease (CAD) often relies on invasive angiography. However, we aimed to explore the potential of metabolomic biomarkers in reflecting residual risk in patients with CAD after moderate lipid-lowering therapy. METHODS AND RESULTS: We analyzed serum metabolomic profile among 2560 patients with newly diagnosed CAD undergoing moderate lipid-lowering therapy, through nuclear magnetic resonance spectroscopy and quantified 175 metabolites, predominantly lipoproteins and their components. CAD severity was evaluated using Gensini score for plaque burden and circulating cardiac troponin T levels for plaque instability. The association of metabolites with CAD severity was examined using multivariate linear regression, and the underlying potential causality was explored using a 2-sample Mendelian randomization approach. Two composite metabolomic indices were constructed to reflect CAD severity using least absolute shrinkage and selection operator linear regression, and their associations with risk of major adverse cardiac events during a median follow-up of 3.8 years were evaluated using Cox models. Our investigation revealed that triglycerides and apolipoprotein B in low-density lipoprotein particles displayed stronger associations with CAD severity compared with the clinically used low-density lipoprotein cholesterol marker. In large high-density lipoprotein, components like cholesterol, cholesterol esters, triglyceride, apolipoprotein A1/A2 showed inverse associations with CAD severity. Certain metabolites, including apolipoprotein B and dihydrothymine, showed a putative causal link with Gensini score. Notably, per standard deviation increase in Gensini score-based metabolomic index was associated with 14.8% higher major adverse cardiac event risk (hazard ratio, 1.148 [95% CI, 1.018-1.295]) independent of demographic factors, medication use, and disease status. CONCLUSIONS: Our findings highlight the potential of nuclear magnetic resonance-based metabolomics in identifying novel biomarkers of plaque burden and instability. Metabolites related to plaque burden may facilitate noninvasive assessment of CAD prognosis.