生物学年龄评估衰老及其临床应用

doi:10.16288/j.yczz.26-015

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Hereditas(Beijing) ›› 2026, Vol. 48 ›› Issue (7): 690-700.doi: 10.16288/j.yczz.26-015

• Review • Previous Articles Next Articles

Assessment of biological age for aging evaluation and its clinical applications

Danqing Huang¹(), Jing Guo¹^,², Yan Guo¹, Tielin Yang¹^,²()

¹ Biomedical Informatics & Genomics Center, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China
² The Second Affiliated Hospital of Xi'an Jiaotong University, Xi’an 710004, China

Received:2026-01-23 Revised:2026-04-09 Online:2026-04-20 Published:2026-04-20
Contact: Tielin Yang E-mail:hdq3029@stu.xjtu.edu.cn;yangtielin@xjtu.edu.cn
Supported by:
Central Government Guides Local Science and Technology Development Project in Tibet Autonomous Region(XZ202501YD0013);National Natural Science Foundation of China(82401762);China Postdoctoral Science Foundation(2024M762573)

Abstract

Abstract:

As the global population ages, the development of methods that can accurately quantify individual aging status and overcome the limitations of chronological age assessment has become an important need in aging research and precision medicine. Biological age serves as an important tool for assessing an individual’s true physiological aging process and disease risk by integrating multi-omics data and organ-specific biomarkers. In this review, we systematically summarize the development of methods for assessing aging, with a focus on the construction strategies and evolution of aging clocks based on epigenetic, transcriptomic, proteomic, and metabolomic markers. We also discuss emerging approaches for organ-specific aging assessment based on imaging data and the integration of multi-omics data. By synthesizing evidence for the clinical applications of these approaches in the early screening and risk stratification of aging-related diseases, personalized interventions, and health management, we further highlight the importance and translational potential of biological age in precision aging assessment and intervention.

Key words: aging, biological age, biomarker, multi-omics, clinical application

Danqing Huang, Jing Guo, Yan Guo, Tielin Yang. Assessment of biological age for aging evaluation and its clinical applications[J]. Hereditas(Beijing), 2026, 48(7): 690-700.

Figures/Tables 3

Fig. 1

Table 1

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生物标志物类型	衰老时钟名称	优势	劣势
表观遗传学	Hannum时钟^[16]、Horvath时钟^[17]、DNAm GrimAge时钟^[19]、DunedinPoAm时钟^[21]等	• 预测精度高，跨组织/器官适用性强 • 可干预性明确，可逆性已临床验证	• 临床可及性有限，检测成本高 • 数据异质性高，不同平台和批次存在系统差异
转录组学	Peters时钟^[22]、Fleischer时钟^[23]、Meyer时钟^[24]等	• 模型可解释性强，直接关联基因表达 • 实验可验证性高	• 预测精度较低，不同队列间差异大 • 可干预性证据不足，调控效应不明确 • 临床可及性有限，不同平台数据异质性高
蛋白组学	Tanaka时钟^[31,33]、Lehallier时钟^[32]等	• 预测精度较高 • 功能关联性强，与临床结局密切相关	• 临床可及性中等，检测成本高于代谢组，不同平台数据异质性高 • 可干预性证据有限，系统性干预证据不足
代谢组学	Van den Akker时钟^[40]、Robinson时钟^[41]等	• 临床可及性高，检测成本低，适配大规模队列分析 • 代谢物通路富集明确	• 预测精度最低 • 可干预性证据不足，调控效应不明确

Assessment of biological age for aging evaluation and its clinical applications

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