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Echocardiographic Approaches and Protocols for Comprehensive Phenotypic Characterization of Valvular Heart Disease in Mice
Published on: February 14, 2017
Accelerated Biological Aging, Genetic Predisposition, and Incident Valvular Heart Disease
Yong-Jian Zhu1, Xiang-Ying Suo2, Jing Guo3
1Department of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Background:
The association between biological aging and valvular heart disease (VHD) has not yet been evaluated.
Objectives:
This study aimed to evaluate the associations between 2 biological age indicators, Klemera-Doubal method biological age (KDM-BA) acceleration and PhenoAge acceleration, and the risk of VHD, as well as explore the potential gene-environment interplay.
Methods:
The study included 341,460 UK Biobank participants without VHD at enrollment. Biological age was assessed using KDM-BA and PhenoAge methods. Genetic risk was measured by genome-wide-association study-based polygenic risk scores (PRS). Cox models were used to assess the individual and joint effects of biological age and PRS on incident VHD. Both multiplicative and additive interactions between the 2 factors were also estimated.
Results:
During a median follow-up of 13.58 years (Q1-Q3: 12.83-14.25 years), 8,146 VHD cases were documented. The results showed a significant association between older biological age and an increased risk of VHD, with a HR of 1.35 (95% CI: 1.32-1.38) for each 1-SD increase in KDM-BA acceleration, and 1.29 (95% CI: 1.26-1.32) for PhenoAge acceleration. Compared with individuals in the first quartile group (Q1) for KDM-BA acceleration, those in Q4 showed the highest risk of VHD, with an 86% higher risk (HR: 1.86; 95% CI: 1.74-1.99). There was an additive interaction between KDM-BA acceleration and PRS for VHD. Similar results were found for the association between PhenoAge acceleration and VHD.
Conclusions:
Advanced biological aging was significantly associated with an increased risk of VHD and could serve as a potential target for clinical prediction and intervention.
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