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一个残留的方法来估计生物年龄从Gompertz建模
Hui Zhang1,2,3, Shuishan Zhang2, Xilu Wang1,2
1Department of Geriatrics, Huadong Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
medRxiv : the preprint server for health sciences
|November 24, 2025
概括
我们开发了基于Gompertz定律的余量 (GOLD-R) 框架,以准确估计生物年龄余量. 这种强大的方法可以改善对不同人群和数据类型的死亡率和疾病的预测.
科学领域:
- 老年学是一门学科.
- 生物统计学 生物统计学
- 计算生物学 计算生物学
背景情况:
- 生物年龄 (BA) 和其残留物量化衰老,但往往缺乏稳定性和临床适用性.
- 目前的方法与异质群体和年龄残留的直接临床衍生斗争.
研究的目的:
- 引入基于Gompertz定律的残留 (GOLD-R) 框架,用于直接估计生物年龄残留.
- 为横截面数据优化GOLD-R并证明其在多个数据集和群体中的稳定性.
主要方法:
- 在DNA甲基化数据 (EWAS数据中心) 上训练GOLD-R,并与表观遗传钟进行评估.
- 应用GOLD-R到英国生物银行蛋白质组学数据,用于生物体和器官特异性衰老措施.
- 利用NHANES和HRS临床生物标记数据,将GOLD-R残留与表观遗传和表型时钟进行比较.
主要成果:
- 在预测胰腺癌数据集中的死亡率方面,GOLD-R的表现优于已有的表观遗传钟.
- 在使用蛋白质组学数据预测疾病和死亡率方面,GOLD-R的衰老指标比传统方法更强大.
- 临床生物标志物的GOLD-R残留物在预测性能方面超过了表观遗传和表型钟.
结论:
- 黄金-R框架是一个强大的算法,用于生物年龄估计.
- GOLD-R为研究衰老研究中的研究和临床应用提供了一个实用的工具.
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