Plasma lipidomic analysis predicts non-calcified coronary artery plaque in asymptomatic patients at intermediate risk of coronary artery disease

Abstract

Aims The optimal management of asymptomatic subjects at intermediate risk of coronary artery disease (CAD) is often uncertain. Re-stratification to a high- or low-risk category may enable optimization of preventative strategies. Coronary computed tomographic angiography (CCTA) enables a minimally invasive assessment of coronary artery plaque quantity and composition. Non-calcified plaque by CCTA is lipid-rich and more vulnerable to rupture and resultant acute coronary syndromes. The purpose of this study was to determine whether novel approaches to CAD risk stratification, such as plasma lipid profiling, may predict non-calcified plaque burden in intermediate risk subjects. Methods and results CCTA and several markers of CAD (including plasma lipid profiling, carotid intima-media thickness, aortic pulse wave velocity, and high-sensitivity C-reactive protein) were prospectively performed in 100 asymptomatic patients at intermediate CAD risk according to the Framingham risk score. Segment stenosis scores (SSS) were calculated to evaluate the burden of total, calcified, and non-calcified coronary artery plaque. Non-calcified plaque was observed in 66 subjects and 158 (11%) of 1425 coronary artery segments. Eighteen lipid species demonstrated significant associations with non-calcified plaque burden, but not with total plaque or calcified plaque burden. No other marker of CAD was found to predict coronary artery plaque burden. Conclusions Plasma lipidomic analysis can predict the burden of non-calcified coronary plaque in asymptomatic subjects at intermediate risk of CAD. Re-stratification of these patients by plasma lipid profiling may enable more appropriate and effective primary prevention management strategies. © 2014 Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2014. For permissions please email: journals.permissions@oup.com.