Predicting healthspan and disease risks through biological age

Gen Li; Linling Cheng; Io Nam Wong; Yun Yin; Jie Chen; Li Liu; Kang Zhang

doi:10.1016/j.molmed.2025.10.006

Predicting healthspan and disease risks through biological age

Trends Mol Med. 2025 Nov 28:S1471-4914(25)00257-6. doi: 10.1016/j.molmed.2025.10.006. Online ahead of print.

Authors

Gen Li¹, Linling Cheng², Io Nam Wong², Yun Yin³, Jie Chen⁴, Li Liu⁵, Kang Zhang⁶

Affiliations

¹ State Key Laboratory of Eye Health, Clinical Data Science Institute, Institute for Advanced Study on Eye Health and Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
² Institute for AI in Medicine and Faculty of Medicine, Macau University of Science and Technology, Macau.
³ State Key Laboratory of Eye Health, Clinical Data Science Institute, Institute for Advanced Study on Eye Health and Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China; Faculty of Bussiness and Faculty of Health and Wellness, City University of Macau, Macau, China. Electronic address: jennyyin629@gmail.com.
⁴ State Key Laboratory of Eye Health, Clinical Data Science Institute, Institute for Advanced Study on Eye Health and Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China. Electronic address: jiechen@eye.ac.cn.
⁵ Department of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, China; State Key Laboratory of Organ Failure Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China. Electronic address: liuli@i.smu.edu.cn.
⁶ State Key Laboratory of Eye Health, Clinical Data Science Institute, Institute for Advanced Study on Eye Health and Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China; Institute for AI in Medicine and Faculty of Medicine, Macau University of Science and Technology, Macau; Guangzhou National Laboratory, Guangzhou, China. Electronic address: kang.zhang@gmail.com.

PMID: 41314863
DOI: 10.1016/j.molmed.2025.10.006

Abstract

Aging is the gradual decline in physiological function essential for survival and reproduction. Unlike age-associated diseases, aging affects all individuals within a species, causing progressive impairments across multiple systems. Research shows that altering specific genes or dietary factors can extend lifespan, implicating molecular pathways in controlling senescence. Chronological age (CA) is a common measure of aging, but other hallmarks like telomere shortening better quantify functional decline. Identifying age-related hallmarks can help manipulate aging, spurring interest in aging clocks. These clocks predict biological age (BA) more precisely than CA, reflecting actual physiological health. As global life expectancy continues to rise, aging clocks hold promise for developing therapies to extend healthspan and improve life quality during aging.

Keywords: age gap; aging clocks; biological age; healthspan.

Publication types

Review