Abstract
OBJECTIVES: To analyze the association between biological aging markers (phenotypic age and phenotypic age acceleration) and valvular heart diseases. METHODS: 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. RESULTS: 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 (n=5238), non-rheumatic mitral valve diseases (n=4558), and non-rheumatic tricuspid valve diseases (n=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 HR=1.04, P<0.01; phenotypic age acceleration: corrected HR=1.03, P<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. CONCLUSIONS: 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.