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从纵向表观遗传年龄数据最大化洞察力:模拟,应用和实际指导

Anna Großbach^1,2, Matthew J Suderman³, Anke Hüls^4,5,6

¹School of Mathematical and Statistical Sciences, University of Galway, Ireland.

Research square

|July 1, 2024

概括

这项研究发现,在线性混合模型中使用时间年龄最能估计表观遗传年龄加速 (EAA). 男人表现出更快的EAA,而高出生体重的儿童会随着时间的推移减缓EAA.

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.
基因组学就是基因组学.
生物统计学生物统计学

背景情况:

表观遗传年龄 (EA) 通过DNA甲基化 (DNAm) 来估计生物年龄.
表观遗传衰老加速 (EAA) 代表了与时间衰老的偏差,并与健康结果有关.
对EA的纵向研究越来越多,但方法上存在差异.

研究的目的:

评估不同统计模型的稳定性,以分析纵向表观遗传年龄 (EA) 数据.
确定最佳方法来估计预测因子和纵向EA或表观遗传年龄加速 (EAA) 之间的关联.

主要方法:

使用模拟来比较各种统计模型 (线性混合模型,GEE) 和结果变量 (EA与EAA).
年代年龄和年龄独立的时间变量被评估为时间动态.
用生物性别和出生体重作为预测因素的现实世界数据使用最佳模型进行了分析.

主要成果:

使用时间年龄的线性混合模型或通用估计方程提供了最准确的效果大小估计.
作为结果,在EA和EAA之间做出选择对估计的影响最小.
男性表现出加速EA,高出生体重与儿童随着时间的推移减缓EA有关.

结论:

这些发现为未来纵向表观遗传年龄 (EA) 研究中选择合适的方法提供了指导.
准确估计EA动态至关重要,以避免过度或低估协会.
方法选择对EA和EAA趋势的解释有很大的影响.

关键词:

在阿尔斯帕克 (ALSPAC) 地区.通过DNA甲基化.加快衰老的加速衰老.表观遗传年龄表观遗传年龄纵向研究是指纵向研究.

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