Caselli Chiara, Occhipinti Mariaelena, Pane Katia, De Gori Carmelo, Rocchiccioli Silvia, Botto Nicoletta, Prontera Concetta, Cavaliere Carlo, Ragusa Rosetta, Vecoli Cecilia, Sansone Francesco, Passaro Emanuela, Ceccherini Elisa, Morlando Antonio, Clemente Alberto, Franzese Monica, Maffei Erica, Punzo Bruna, Gimelli Alessia, Cademartiri Filippo, Neglia Danilo
Institute of Clinical Physiology, Department of Biomedical Sciences, Consiglio Nazionale delle Ricerche (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy.
Division of Cardiology, Fondazione Toscana Gabriele Monasterio, Via G. Moruzzi 1, 56124 Pisa, Italy.
Eur Heart J Open. 2025 Jan 28;5(1):oeaf005. doi: 10.1093/ehjopen/oeaf005. eCollection 2025 Jan.
Optimal medical treatment in patients with stable coronary artery disease (CAD) reduced morbidity and mortality but left a substantial residual risk (RR) of disease progression and events. According to recent evidence, insulin resistance or pre-diabetes together with elevated levels of triglycerides, low levels, and functionality of HDL-cholesterol, often associated with a chronic inflammatory state, are deemed to be relevant components of cardiometabolic and vascular RR. In the present project, we aim at discovering specific individual genetic/molecular profiles subtending emerging cardiometabolic and vascular risk patterns and associated with more severe stable CAD phenotypes. To this end, we will analyse clinical data, blood samples, and imaging data already gathered in a retrospective population of 561 patients with suspected stable coronary disease and will develop integrated predictive models of severity and extent of disease defined by qualitative and quantitative analysis of coronary plaques by cardiac computed tomography. The new predictive models, which will incorporate relevant clinical and genetic/molecular variables associated with more severe coronary atherosclerosis, will be validated in a similar prospective population of patients and extended to the prediction of progression (at 1 year follow-up) of coronary disease phenotypes, occurring despite optimal medical treatment. ClinicalTrials.gov ID: NCT06601153.
稳定型冠状动脉疾病（CAD）患者的最佳药物治疗可降低发病率和死亡率，但仍存在疾病进展和事件的大量残余风险（RR）。根据最近的证据，胰岛素抵抗或糖尿病前期，连同甘油三酯水平升高、高密度脂蛋白胆固醇水平降低及其功能异常，通常与慢性炎症状态相关，被认为是心脏代谢和血管残余风险的相关组成部分。在本项目中，我们旨在发现潜在的心脏代谢和血管风险模式以及与更严重的稳定型CAD表型相关的特定个体遗传/分子特征。为此，我们将分析已经收集的561例疑似稳定型冠状动脉疾病患者的回顾性队列中的临床数据、血液样本和影像数据，并通过心脏计算机断层扫描对冠状动脉斑块进行定性和定量分析，建立疾病严重程度和范围的综合预测模型。新的预测模型将纳入与更严重冠状动脉粥样硬化相关的相关临床和遗传/分子变量，并将在类似的前瞻性患者队列中进行验证，并扩展到预测尽管接受了最佳药物治疗仍会出现的冠状动脉疾病表型的进展（随访1年）。 临床试验注册号：NCT06601153。
