Xu Ting, Zhang Yucong, Zhou Yi, Yin Lixue, Min Xinwen, Wu Shouling, Zhang Cuntai, Ruan Lei
Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China.
Key Laboratory of Vascular Aging, Ministry of Education, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China.
Clin Interv Aging. 2025 Mar 29;20:403-414. doi: 10.2147/CIA.S485597. eCollection 2025.
This study aimed to investigate the clinical implications of vascular aging (VAg) phenotypes based on the difference between chronological age (CA) and vascular age (VA).
We defined VA as the predicted age in a multivariable linear regression model including structural and functional parameters of arteries and conventional risk factors, in a multicentric, cross-sectional cohort (n=15580). According to the 10 and 90 percentiles of Δ-age (CA minus VA), we then classified the status of VAg into 3 phenotypes: the early VAg (EVA), the Normal VAg and the supernormal VAg (SUPERNOVA). We used Cox survival analysis to investigate the association between VAg phenotypes and the risk for adverse clinical outcomes (including all-cause death and cardiovascular disease) in an independent, prospective cohort (n=5316).
In the prospective cohort (11.07 years, 927 events), when compared to the Normal VAg phenotype, EVA had an increased risk (HR: 2.43; 95% CI: 1.80-3.27) and SUPERNOVA had a decrease risk (HR: 0.75; 95% CI: 0.64-0.90) of adverse clinical outcomes, in particular stroke events. EVA also showed a higher risk of myocardial infarction (HR: 3.21, 95% CI: 1.56-6.62) and all-cause death (HR: 1.79, 95% CI: 1.12-2.85). The associations were independent of the atherosclerotic cardiovascular disease risk score. Further, the C-statistics increased 0.010 ( < 0.001), 0.013 ( < 0.001) and 0.016 ( < 0.001) separately when adding baPWV, adding the combination of baPWV and CIMT, and adding the VAg phenotypes to a model of conventional risk factors in predicting cardiovascular events.
This is the first study to evaluate the clinical implications of VAg phenotypes using multicentric data and undergone external validation in China. Our results emphasized that the classification of VAg phenotypes may be a potential tool to identify individuals who were susceptible to or resilient to VAg.
本研究旨在基于实足年龄（CA）与血管年龄（VA）的差异，探讨血管老化（VAg）表型的临床意义。
在一个多中心横断面队列（n = 15580）中，我们将VA定义为多变量线性回归模型中的预测年龄，该模型包括动脉的结构和功能参数以及传统危险因素。然后根据年龄差值（CA减去VA）的第10和第90百分位数，将VAg状态分为3种表型：早期VAg（EVA）、正常VAg和超常VAg（SUPERNOVA）。我们使用Cox生存分析，在一个独立的前瞻性队列（n = 5316）中研究VAg表型与不良临床结局（包括全因死亡和心血管疾病）风险之间的关联。
在前瞻性队列（11.07年，927例事件）中，与正常VAg表型相比，EVA发生不良临床结局的风险增加（HR：2.43；95%CI：1.80 - 3.27），而SUPERNOVA发生不良临床结局的风险降低（HR：0.75；95%CI：0.64 - 0.90），尤其是中风事件。EVA发生心肌梗死的风险也更高（HR：3.21，95%CI：1.56 - 6.62）以及全因死亡风险更高（HR：1.79，95%CI：1.12 - 2.85）。这些关联独立于动脉粥样硬化性心血管疾病风险评分。此外，在预测心血管事件的传统危险因素模型中，分别添加臂踝脉搏波速度（baPWV）、添加baPWV与颈动脉内膜中层厚度（CIMT）的组合以及添加VAg表型时，C统计量分别增加0.010（<0.001）、0.013（<0.001）和0.016（<0.001）。
这是第一项利用多中心数据评估VAg表型的临床意义并在中国进行外部验证的研究。我们的结果强调，VAg表型分类可能是识别易患或抗VAg个体的潜在工具。
