Plasma proteins associate with carotid plaques and predict incident atherosclerotic cardiovascular events

Performing non-invasive carotid imaging is challenging, owing inter-operator variability and organizational barriers, but plasma proteomics can offer an alternative. We sought plasma proteins that associate with the presence of carotid plaques, their number and predict the incidence of clinically overt atherosclerotic cardiovascular events (ASCVD) above currently recognized risk factors in "apparently healthy" subjects.

We studied the plasma levels of 368 proteins in 664 subjects from the PLIC study, who underwent an ultrasound imaging screening of the carotids to check for the presence of plaques. We clustered, by artificial intelligence (A.I.), the proteins that associate with the presence, the number of plaques and that predict incident ASCVDs over 22 years (198 events were registered).

299/664 subjects had at least 1 carotid plaque (1+) (77 with only one plaque, 101 with 2 plaques, 121 with ≥3 plaques (3+)). The remaining 365 subjects with no plaques acted as controls. 106 proteins were associated with 1+ plaques, but 97 proteins significantly predicted 3+ plaques only (AUC = 0.683 (0.601-0.785), p < 0.001), when considered alone. A.I. underscored 87 proteins that improved the performance of the classical risk factors both in detecting 3+ plaques (AUC = 0.918 (0.887-0.943) versus risk factors alone, AUC = 0.760 (0.716-0.801), p < 0.001) and in predicting the incident ASCVD (AUC = 0.739 (0.704-0.773) vs risk factors alone AUC = 0.559 (0.521-0.598), p < 0.001). The chemotaxis/migration of leukocytes and interleukins/cytokines signaling were biological pathways mostly represented by these proteins.

Plasma proteomics marks the number of carotid plaques and improve the prediction of incidence ASCVDs in apparently healthy subjects.