Epigenetic ageing clocks: statistical methods and emerging computational challenges

被引:1
|
作者
Teschendorff, Andrew E. [1 ]
Horvath, Steve [2 ]
机构
[1] Univ Chinese Acad Sci, Shanghai Inst Nutr & Hlth, Chinese Acad Sci, CAS Key Lab Computat Biol, Shanghai, Peoples R China
[2] Altos Labs, Cambridge, England
基金
中国国家自然科学基金;
关键词
DNA METHYLATION MICROARRAY; BIOLOGICAL AGE; POTENTIAL REVERSAL; GENE-EXPRESSION; CANCER-RISK; CPG SITES; TISSUE; HETEROGENEITY; VALIDATION; MODELS;
D O I
10.1038/s41576-024-00807-w
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Over the past decade, epigenetic clocks have emerged as powerful machine learning tools, not only to estimate chronological and biological age but also to assess the efficacy of anti-ageing, cellular rejuvenation and disease-preventive interventions. However, many computational and statistical challenges remain that limit our understanding, interpretation and application of epigenetic clocks. Here, we review these computational challenges, focusing on interpretation, cell-type heterogeneity and emerging single-cell methods, aiming to provide guidelines for the rigorous construction of interpretable epigenetic clocks at cell-type and single-cell resolution.
引用
收藏
页码:350 / 368
页数:19
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