Liu Xiangjing, Luo Da, Hu Zheng, Tian Hangyu, Jiang Hong, Chen Jing
Department of Cardiology, Renmin Hospital of Wuhan University, Hubei Provincial Key Laboratory of Cardiology, Cardiovascular Research Institute of Wuhan University, Wuhan 430060, China.
Zhejiang Da Xue Xue Bao Yi Xue Ban. 2025 Mar 25;54(2):241-249. doi: 10.3724/zdxbyxb-2024-0416.
To analyze the association between biological aging markers (phenotypic age and phenotypic age acceleration) and valvular heart diseases.
Research subjects who met the inclusion and exclusion criteria were selected from the UK Biobank from 2006 to 2010. The phenotypic age and phenotypic age acceleration were calculated. Cox multivariate analysis was used to examine the relationship between the aging markers and valvular heart diseases. Sensitivity analysis was conducted by removing missing values and subgroup analysis. The predictive accuracy of phenotypic age and phenotypic age acceleration for valvular heart diseases was analyzed using receiver operating characteristic (ROC) curves, and a clinical decision curve was generated based on logistic regression.
A total of 411 687 subjects were included in the study, among whom there were 14 258 patients with valvular heart diseases. The overall median follow-up time was 12.80 years, the median follow-up time for patients with non-rheumatic aortic valve diseases (=5238), non-rheumatic mitral valve diseases (=4558), and non-rheumatic tricuspid valve diseases (=411) were 12.82 years, 12.83 years and 12.84 years, respectively. After adjusting for demographic factors (gender, race, education, Townsend deprivation index), anthropometric factors (body mass index), lifestyle factors (smoking, alcohol consumption, Dietary Approaches to Stop Hypertension score), hypertension and hyperlipidemia, Cox multivariate analysis showed phenotypic age and phenotypic age acceleration were independent risk factors for valvular heart diseases, including non-rheumatic aortic valve diseases, non-rheumatic mitral valve diseases, and non-rheumatic tricuspid valve diseases (phenotypic age: corrected =1.04, <0.01; phenotypic age acceleration: corrected =1.03, <0.01), which was also confirmed by sensitivity analysis. ROC curves and clinical decision curves demonstrated that compared with the phenotypic age acceleration, phenotypic age had higher accuracy (the areas and the curves were 0.721 and 0.599) and higher net benefit in predicting valvular heart diseases. Moreover, compared with a single indicator, the combination of the two indicators had higher accuracy (the area under the curve was 0.725) and higher net benefit.
Phenotypic age and phenotypic age acceleration,as markers of biological aging, are independent risk factors for valvular heart diseases. Compared with phenotypic age acceleration, phenotypic age has a greater advantage in predicting valvular heart diseases. Overall, the combination of the two indicators offers a more effective approach for predicting valvular heart diseases.
分析生物衰老标志物（表型年龄和表型年龄加速）与心脏瓣膜病之间的关联。
从2006年至2010年的英国生物银行中选取符合纳入和排除标准的研究对象。计算表型年龄和表型年龄加速。采用Cox多变量分析来检验衰老标志物与心脏瓣膜病之间的关系。通过去除缺失值进行敏感性分析和亚组分析。使用受试者工作特征（ROC）曲线分析表型年龄和表型年龄加速对心脏瓣膜病的预测准确性，并基于逻辑回归生成临床决策曲线。
本研究共纳入411687名研究对象，其中有14258名心脏瓣膜病患者。总体中位随访时间为12.80年，非风湿性主动脉瓣疾病（n = 5238）、非风湿性二尖瓣疾病（n = 4558）和非风湿性三尖瓣疾病（n = 411）患者的中位随访时间分别为12.82年、12.83年和12.84年。在调整人口统计学因素（性别、种族、教育程度、汤森贫困指数）、人体测量因素（体重指数）、生活方式因素（吸烟、饮酒、终止高血压饮食评分）、高血压和高脂血症后，Cox多变量分析显示表型年龄和表型年龄加速是心脏瓣膜病的独立危险因素，包括非风湿性主动脉瓣疾病、非风湿性二尖瓣疾病和非风湿性三尖瓣疾病（表型年龄：校正后HR = 1.04，P < 0.01；表型年龄加速：校正后HR = 1.03，P < 0.01），敏感性分析也证实了这一点。ROC曲线和临床决策曲线表明，与表型年龄加速相比，表型年龄在预测心脏瓣膜病方面具有更高的准确性（曲线下面积分别为0.721和0.599）和更高的净效益。此外，与单一指标相比，两个指标的组合具有更高的准确性（曲线下面积为0.725）和更高的净效益。
表型年龄和表型年龄加速作为生物衰老的标志物，是心脏瓣膜病的独立危险因素。与表型年龄加速相比，表型年龄在预测心脏瓣膜病方面具有更大优势。总体而言，两个指标的组合为预测心脏瓣膜病提供了更有效的方法。
