Association between biological age acceleration and the risk of aortic valve stenosis: An observational epidemiologic and Mendelian randomization study

@article{zheng2026association,
  title = {{Association between biological age acceleration and the risk of aortic valve stenosis: An observational epidemiologic and Mendelian randomization study}},
  author = {Yiqi Zheng and Xinghao Xu and Ruijie Li and Zhenyu Xiong and Han Wen and Yue Guo and Menghui Liu and Huimin Zhou and Xingfeng Xu and Shaozhao Zhang and Rihua Huang and Zezhi Ke and Zihao Huang and Jiayuan Zhang and Xiaodong Zhuang and Xinxue Liao},
  journal = {The Journal of Nutrition, Health and Aging},
  year = {2026},
  month = nov,
  doi = {10.1016/j.jnha.2026.101024},
  url = {https://doi.org/10.1016/j.jnha.2026.101024},
  note = {CC BY},
}

TY  - JOUR
TI  - Association between biological age acceleration and the risk of aortic valve stenosis: An observational epidemiologic and Mendelian randomization study
AU  - Yiqi Zheng
AU  - Xinghao Xu
AU  - Ruijie Li
AU  - Zhenyu Xiong
AU  - Han Wen
AU  - Yue Guo
AU  - Menghui Liu
AU  - Huimin Zhou
AU  - Xingfeng Xu
AU  - Shaozhao Zhang
AU  - Rihua Huang
AU  - Zezhi Ke
AU  - Zihao Huang
AU  - Jiayuan Zhang
AU  - Xiaodong Zhuang
AU  - Xinxue Liao
PY  - 2026
DA  - 2026/11/08
JO  - The Journal of Nutrition, Health and Aging
DO  - 10.1016/j.jnha.2026.101024
UR  - https://doi.org/10.1016/j.jnha.2026.101024
AB  - Introduction: Biological age acceleration (BAA) is thought to be a major risk factor for age-related diseases, but its role in aortic valve stenosis (AVS) remains uncertain. We aimed to assess the associations between biological aging and the risk of AVS. Methods: This study involved 4526 participants from the Real-world Data of Cardiometabolic Protection (RED-CARPET) study and 5114 participants from the Atherosclerosis Risk in Communities (ARIC) study. BAA was assessed using clinical biomarkers through the Klemera-Doubal method (KDM) and the PhenoAge algorithm. We employed multivariable logistic regression and restricted cubic spline (RCS) regression to examine the association between BAA and AVS risk. Additionally, Mendelian randomization (MR) analysis was conducted to assess causality. Results: In the RED-CARPET cohort of 4526 participants (mean age 60.93 years, 33.5% female), 113 AVS events were recorded. In the ARIC cohort of 5114 participants (mean age 51.94 years, 56.4% female, 82.3% White), there were 266 AVS events. After fully adjusting for confounding variables, each standard deviation increase in BAA was significantly associated with elevated AVS risk (RED-CARPET: KDM-BA acceleration: OR 1.29, 95% CI 1.07−1.55; PhenoAge acceleration: OR 1.48, 95% CI 1.24−1.77; ARIC: KDM-BA acceleration: OR 1.42, 95% CI 1.24−1.63; PhenoAge acceleration: OR 1.30, 95% CI 1.11−1.51). The RCS regression model revealed significant linear relationships between BAA and the risk of AVS in both cohorts. MR analysis suggested a potential causal relationship between KDM-BA acceleration and AVS risk (OR 1.38, 95% CI 1.21–1.57). Conclusion: BAA, as derived from clinical biomarkers, is independently associated with an increased risk of AVS. This finding suggests that BAA, as a composite indicator of systemic biological aging, may complement traditional risk factors in the early identification of high-risk populations for AVS, and offer the possibility of early intervention for prevention.
SN  - 1760-4788
ER  -