Wang Mengxing, Yan Hongyi, Zhang Yanli, Zhou Qi, Meng Xia, Lin Jinxi, Jiang Yong, Pan Yuesong, Wang Yongjun
Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Centre for Neurological Diseases, Beijing, China.
Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Centre for Neurological Diseases, Beijing, China.
EBioMedicine. 2025 Jan;111:105494. doi: 10.1016/j.ebiom.2024.105494. Epub 2024 Dec 10.
Biological age (BA), an integrated measure of physiological aging, has a clear link to stroke. There is a paucity of long-term longitudinal studies about the association between accelerated biological age and stroke prognosis in patients with previous strokes, and the differences in the predictive ability of various BA indicators calculated from clinical biochemistry biomarkers for future stroke outcomes are still unknown. To evaluate the role of three accelerated BA indicators for short- and long-term prognosis of patients with ischemic stroke or transient ischemic attack (TIA), and to identify the most appropriate predictor.
This study included 7396 patients from the Third China National Stroke Registry (CNSR-III), a prospective national registry of patients with acute ischemic stroke or TIA between August 2015 and March 2018 in China. We constructed accelerated BA using three widely recognized algorithms: PhenoAge, Klemera-Doubal, and HD method. To ascertain the association of accelerated BA with the risk of short- and long-term stroke outcomes, a Cox or logistic regression model was conducted for the analysis. The net reclassification index and integrated discrimination improvement were used to evaluate the added model improvement ability of BA acceleration.
Compared to those with the lowest of PhenoAge acceleration, patients with the highest were more likely to have a higher risk of stroke (HR 1.98, 95% CI 1.49-2.63, P < 0.001), ischemic stroke (HR 1.88, 95% CI 1.41-2.53, P < 0.001), composite vascular events (HR 2.03, 95% CI 1.53-2.68, P < 0.001), all-cause death (HR 7.02, 95% CI 3.41-14.47, P < 0.001) and the modified Rankin scale of 3-6 (OR 2.55, 95% CI 2.05-3.16, P < 0.001) at three months, and the association observed within one year and five years was similar to that within three months. The risk of all stroke outcomes for HDAge was consistent with PhenoAge acceleration, but KDMAge acceleration was the same, except for stroke within one year (HR 1.24, 95% CI 1.00-1.53, P = 0.053). PhenoAge acceleration provided a better improvement in the model's predictive ability for stroke prognosis, compared to BA determined by other algorithms.
In this prospective cohort study, BA acceleration, particularly PhenoAge, may help identify stroke patients with risks of short- and long-term poor outcomes, potentially enabling subclinical prevention and early intervention.
This work was supported by grants from Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (2019-I2M-5-029), the National Natural Science Foundation of China (U20A20358), Beijing Hospitals Authority Clinical Medicine Development of special funding support (ZLRK202312), the National Key R&D Program of China (No. 2022YFC3602500, 2022YFC3602505), Outstanding Young Talents Project of Capital Medical University (A2105), and Beijing High-Level Public Health Technical Personnel Construction Project (Discipline leader -03-12).
生物学年龄（BA）是生理衰老的综合指标，与中风有明确关联。关于既往中风患者中加速生物学年龄与中风预后之间的关联，长期纵向研究较少，且基于临床生化生物标志物计算的各种BA指标对未来中风结局的预测能力差异尚不清楚。为评估三种加速BA指标对缺血性中风或短暂性脑缺血发作（TIA）患者短期和长期预后的作用，并确定最合适的预测指标。
本研究纳入了来自中国国家卒中登记研究三期（CNSR-III）的7396例患者，这是一项针对2015年8月至2018年3月期间中国急性缺血性中风或TIA患者的前瞻性全国性登记研究。我们使用三种广泛认可的算法构建加速BA：PhenoAge、Klemera-Doubal和HD方法。为确定加速BA与短期和长期中风结局风险的关联，进行Cox或逻辑回归模型分析。使用净重新分类指数和综合判别改善来评估BA加速的模型附加改善能力。
与PhenoAge加速最低的患者相比，加速最高的患者在三个月时发生中风（风险比1.98，95%置信区间1.49-2.63，P<0.001）、缺血性中风（风险比1.88，95%置信区间1.41-2.53，P<0.001）、复合血管事件（风险比2.03，95%置信区间1.53-2.68，P<0.001）、全因死亡（风险比7.02，95%置信区间3.41-14.47，P<0.001）以及改良Rankin量表评分为3-6分（比值比2.55，95%置信区间2.05-3.16，P<0.001）的风险更高，且在一年和五年内观察到的关联与三个月内相似。HDAge的所有中风结局风险与PhenoAge加速一致，但KDMAge加速除一年内中风外（风险比1.24，95%置信区间1.00-1.53，P=0.053）情况相同。与其他算法确定的BA相比，PhenoAge加速对中风预后的模型预测能力有更好的改善。
在这项前瞻性队列研究中，BA加速，尤其是PhenoAge，可能有助于识别有短期和长期不良结局风险的中风患者，从而可能实现亚临床预防和早期干预。
本研究得到了中国医学科学院医学与健康科技创新工程（2019-I2M-5-029）、国家自然科学基金（U20A20358）、北京市医院管理局临床医学发展专项经费支持（ZLRK202312）、国家重点研发计划（2022YFC3602500、2022YFC3602505）、首都医科大学优秀青年人才项目（A2105）以及北京市高层次公共卫生技术人才培养项目（学科带头人-03-12）的资助。
