Predictive Added Value of Selected Plasma Lipids to a Re-estimated Minimal Risk Tool - Bodini, Antonella; Michelucci, Elena; Di Giorgi, Nicoletta; Caselli, Chiara; Signore, Giovanni; Neglia, Danilo; Smit, Jeff M.; Scholte, Arthur J.H.A.; Mincarone, Pierpaolo; Leo, Carlo G.; Pelosi, Gualtiero; Rocchiccioli, Silvia (Frontiers in Cardiovascular Medicine, 2021)
Background. Lipidomics is emerging for biomarker discovery in cardiovascular disease and circulating lipids are increasingly incorporated in risk to predict cardiovascular events. Moreover, specific classes of lipids such as sphingomyelins, ceramides and triglycerides have been related to coronary artery disease (CAD) severity and plaque characteristics. The only pre-test model available so far to rule out coronary atherosclerosis presence in patients with chest pain but normal coronary arteries, is the Minimal Risk Tool (MRT). Aim. By state-of-the-art statistical methods we aim to verify the additive predictive value of a set of lipids, derived from targeted plasma lipidomics of suspected CAD patients, to a re-estimated version of the MRT for ruling out the presence of coronary atherosclerosis assessed by coronary CT angiography (CCTA). Methods. 256 subjects with suspected stable CAD recruited from 5 European countries within H2020-SMARTool, undergoing CCTA and blood sampling for clinical biochemistry and lipidomics, were selected. The MRT was validated by regression methods and then re-estimated (reMRT). The (reMRT was used as a baseline model in a Likelihood Ratio Test approach to assess the added predictive value of each lipid from thirteen among ceramides, triglycerides and sphingomyelins. A sensitivity analysis was carried out by considering two alternative models developed on the cohort as baseline models. Results. In 205 subjects coronary atherosclerosis ranged from minimal lesions to overt obstructive CAD while in 51 subjects (19.9%) coronary arteries were intact. Four triglycerides and 7 sphingomyelins were significantly (p<0.05) and differentially expressed in the two groups, and at a lesser extent one ceramide (p=0.067). Cer(d18:1/16:0) (p=0.01), SM(40:2) (p=0.04) and at a lesser extent SM(41:1) (p=0.052) added a significant predictive value to reMRT. The sensitivity analysis confirmed this result. Furthermore, SM(34:1), SM(38:2), SM(41:2) and SM(42:4) provided improvement with respect to at least one of the other baseline models. None of the selected triglycerides was found to provide an added value. Conclusions. Plasma lipidomics can be a promising source of diagnostic and prognostic biomarkers in cardiovascular disease, exploitable not only to assess the risk of adverse events but also to identify subjects without coronary atherosclerosis, thus reducing unnecessary further testing in normal subjects.