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在表观遗传时钟中的不确定性量化通过符合规范的定量回归

Yanping Li¹, Jaclyn M Goodrich², Karen E Peterson³

¹School of Statistics and Data Science, Nankai University, China.

medRxiv : the preprint server for health sciences

|September 16, 2024

概括

这项研究引入了一种新的方法,用于表观遗传时钟,使用定量回归和符合性预测. 它提供了更准确的生物年龄预测,并揭示了老龄化模式中的人口差异.

科学领域:

表观遗传学在表观遗传学中,表观遗传学是指表观遗传学.
生物统计学生物统计学
计算生物学计算生物学

背景情况:

基因甲基化 (DNAm) 是一种影响生物年龄的关键表观遗传修饰.
基于DNAm的表观遗传钟估计了生物年龄,但往往缺乏不确定性量化.
现有的时钟可以预测平均生物年龄,但不能完全捕捉人口异质性或提供预测间隔.

研究的目的:

开发一种用于训练表观遗传钟的新型管道,其中包括不确定性量化.
为了揭示种群异质性,并为生物年龄构建准确的预测间隔.
为了提高对生物衰老的理解,超出平均估计.

主要方法:

整合高维量子力回归和符合性预测用于表观遗传时钟训练.
开发适用于各种DNAm数据集的通用管道.
适用于来自儿童和青少年的11个DNAm数据集中的728个血液样本.

主要成果:

拟议的方法产生了具有名义覆盖范围的自适应预测间隔,并考虑到个体变化.
基于量子回归的预测间隔比传统平均回归更窄,这表明统计效率有所提高.
间隔揭示了与年龄加速同步的模式,揭示了儿童和青春期衰老中的细胞进化异质性.

结论:

合规化的高维量子力回归为有效的预测间隔提供了强大的框架,并揭示了表观遗传衰老中的人口异质性.
该方法提高了统计效率,并提供了对超出平均值的生物年龄分布的更深入的见解.
这种方法具有广泛的适用性,用于理解跨年龄组的表观遗传年龄,并为抗衰老干预提供信息.

关键词:

通过DNA甲基化.生物年龄生物年龄符合规范的预测预测表观遗传时钟的时间表.不同质性的异质性儿科儿科儿科儿科

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