BACKGROUND Cardiovascular risk models have been developed primarily for incident events. Well-performing models are lacking to predict secondary cardiovascular events among people with a history of coronary heart disease, stroke, or heart failure who also have chronic kidney disease (CKD). We sought to develop a proteomics-based risk score for cardiovascular events in individuals with CKD and a history of cardiovascular disease. METHODS We measured 4638 plasma proteins among 1067 participants from the Chronic Renal Insufficiency Cohort (CRIC) and 536 individuals from the Atherosclerosis Risk in Communities Cohort (ARIC). All had non-dialysis-dependent CKD and coronary heart disease, heart failure, or stroke at study baseline. A proteomic risk model for secondary cardiovascular events was derived by elastic net regression in CRIC, validated in ARIC, and compared to clinical models. Biologic mechanisms of secondary events were characterized through proteomic pathway analysis. RESULTS A 16-protein risk model was superior to the Framingham risk score for secondary events, including a modified score that included estimated glomerular filtration rate (eGFR). In CRIC, the annualized area under the receiver operating characteristic (AUC) within 1 to 5 years ranged between 0.77 and 0.80 for the protein model and 0.57 and 0.72 for the clinical models. These findings were replicated in the ARIC validation cohort. Biologic pathway analysis identified pathways and proteins for cardiac remodeling and fibrosis, vascular disease, and thrombosis. CONCLUSIONS The proteomic risk model for secondary cardiovascular events outperformed clinical models based on traditional risk factors and eGFR.

中文翻译：

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CKD 个体继发性心血管事件风险的蛋白质组学评估。


背景 心血管风险模型主要是针对事件开发的。缺乏表现良好的模型来预测有冠心病、中风或心力衰竭病史但同时患有慢性肾脏病 （CKD） 的人的继发性心血管事件。我们试图为有心血管疾病史的 CKD 患者心血管事件开发基于蛋白质组学的风险评分。方法 我们测量了来自慢性肾功能不全队列 （CRIC） 的 1067 名参与者和来自社区动脉粥样硬化风险队列 （ARIC） 的 536 名个体的 4638 种血浆蛋白。所有患者在研究基线时均患有非透析依赖性 CKD 和冠心病、心力衰竭或中风。继发性心血管事件的蛋白质组学风险模型是通过 CRIC 中的弹性网回归得出的，在 ARIC 中得到验证，并与临床模型进行比较。通过蛋白质组学途径分析表征继发事件的生物学机制。结果 对于继发事件，16 蛋白风险模型优于 Framingham 风险评分，包括包括估计肾小球滤过率 （eGFR） 的改良评分。在 CRIC 中，蛋白质模型 1 至 5 年受试者工作特征 （AUC） 下的年化面积在 0.77 至 0.80 之间，临床模型在 0.57 至 0.72 之间。这些发现在 ARIC 验证队列中得到了复制。生物途径分析确定了心脏重塑和纤维化、血管疾病和血栓形成的途径和蛋白质。结论 继发性心血管事件的蛋白质组学风险模型优于基于传统危险因素和 eGFR 的临床模型。