Xu Jiatang, Hu Zhensheng, Liu Hongze, Su Yangfan, Shen Runnan, Xie Chaoyu, Zhou Yi, Huang Kai
Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China.
Department of Cardiovascular Surgery, the First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.
Int J Surg. 2025 Jun 30. doi: 10.1097/JS9.0000000000002898.
Both age and genetic risk are associated with risk of thoracic aortic aneurysms (TAA). This study seeks to explore the association between phenotypic age acceleration (PhenoAgeAccel), a novel biomarker of aging, and risk of TAA, as well as to conduct risk stratification for TAA based on PhenoAgeAccel and genetic risk.
A total of 406,750 participants from the prospective cohort of UK Biobank were included. PhenoAgeAccel was calculated based on chronological age and 9 biomarkers. Associations between PhenoAgeAccel, genetic risk and incident TAA were explored based on cox proportional hazards models. Additionally, mediation analyses were conducted to explore whether PhenoAgeAccel mediated the pathogenic process of risk factors for TAA.
PhenoAgeAccel was significantly associated with increased risk of TAA (hazard ratio [HR]: 1.31; 95% confidence intervals [CI]: 1.15-1.48). Compared to biologically younger participants with low genetic risk, biologically older participants with high genetic risk had a 3.73 (95% CI: 2.70-5.16) folds risk of TAA. PhenoAgeAccel exhibited a significant additive interaction with genetic susceptibility. Mediation analyses revealed that PhenoAgeAccel mediates the association between various risk factors and the progression of TAA.
PhenoAgeAccel has the potential to serve as a novel aging biomarker for identifying high-risk populations of TAA. The combination of PhenoAgeAccel and genetic risk can further improve TAA risk stratification, thereby informing the formulation of screening strategy and primary prevention for TAA.
年龄和遗传风险均与胸主动脉瘤（TAA）风险相关。本研究旨在探讨衰老的新型生物标志物——表型年龄加速（PhenoAgeAccel）与TAA风险之间的关联，并基于PhenoAgeAccel和遗传风险对TAA进行风险分层。
纳入了英国生物银行前瞻性队列中的406,750名参与者。基于实际年龄和9种生物标志物计算PhenoAgeAccel。基于Cox比例风险模型探讨PhenoAgeAccel、遗传风险与TAA发病之间的关联。此外，进行中介分析以探讨PhenoAgeAccel是否介导了TAA危险因素的致病过程。
PhenoAgeAccel与TAA风险增加显著相关（风险比[HR]：1.31；95%置信区间[CI]：1.15 - 1.48）。与遗传风险低的生物学上年轻的参与者相比，遗传风险高的生物学上年长的参与者患TAA的风险高3.73倍（95% CI：2.70 - 5.16）。PhenoAgeAccel与遗传易感性表现出显著的相加相互作用。中介分析显示，PhenoAgeAccel介导了各种危险因素与TAA进展之间的关联。
PhenoAgeAccel有潜力作为一种新型衰老生物标志物，用于识别TAA的高危人群。PhenoAgeAccel与遗传风险的结合可进一步改善TAA风险分层，从而为TAA的筛查策略制定和一级预防提供依据。
