Abstract Body (Do not enter title and authors here): Background and Aims
Carotid plaque is an early manifestation of atherosclerosis and is closely associated with the risk of myocardial ischemia, ischemic stroke, and other atherosclerotic cardiovascular diseases (ASCVDs). This study aims to identify new protein biomarkers associated with carotid plaque, which will enhance early warning of ASCVD.
Methods
We launched a nested case-control study based on the blood samples at baseline and repeated carotid ultrasound measurements during follow-ups in the ChinaHEART cohort. Among participants without carotid plaque at baseline, 145 with incident carotid plaque within two-year follow-up were selected as cases, and 147 without incident carotid plaque during follow-up were matched for demographic characteristics and traditional risk factors as controls. After the Meso Scale Discovery test for 28 biomarkers, Least absolute shrinkage and selection operator (LASSO) regression was used to select potential predictors and constructed a logistic regression model for predicting carotid plaque. Furthermore, the incremental predictive value was validated in the UK Biobank of 30,800 subjects.
Results
A total of 11 biomarkers, including thrombomodulin, ICAM-3, P-Selectin, GDF-15, adiponectin, MCP-1, IL-10, PlGF, Tie-2, VEGF-D, and VCAM-1 were selected by LASSO regression and used to construct a prediction model for the carotid plaque. The area under the ROC curve (AUC) of the eventual model is 0.778 and it showed good calibration capability graphically with a Brier score of 0.192. In the UK Biobank cohort, when these biomarkers were added to a traditional predictive model, a better predictive power was generated, with an AUC improvement of 0.021 (P <0.001, Delong test), Brier score of 0.093, a continuous NRI of 0.259 (0.223-0.294, P <0.001), IDI of 0.017 (0.015-0.019, P <0.001) reference to the traditional model.
Conclusions
We found and validated the biomarkers, including thrombomodulin, ICAM-3, P-Selectin, GDF-15, adiponectin, MCP-1, IL-10, PlGF, Tie-2, VEGF-D, and VCAM-1, can predict the incidence of carotid plaque in ChinaHEART, and except for Tie-2, these biomarkers have additional value for the prediction of incident ASCVD in UK Biobank.