Multimodal clocks of human aging.

Jiaming Li, Beier Jiang, Wei Zhang, Junwei Hao, Zhili Liu, Qianzhao Ji, Yandong Zheng, Xiaoyong Lu, Zikai Zheng, Shuai Ma, Yanlin Fan, Dan-Dan Gao, Xiao-Wen Hou, Jing Li, Jiazhen Tang, Yaobin Jing, Lingling Geng, Ruochen Wu, Baohu Zhang, Shuhui Sun, Yusheng Cai, Kaowen Yan, Muzhao Xiong, Chen Dong, Xibo Ma, Gang Xu, Zhejun Ji, Haoteng Yan, Quan Zheng, Honghao Huang, Li Zhang, Junming Li, Mengmeng Jiang, Liu-Jun Xu, Yifan Chen, Geyue Qu, Wan Lei, Hengchao Wang, Jun Ping, Jia Zhou, Ming Yi, Mingjin Jiang, Ying Jing, Wei-Dong Ye, Xiao Zhang, Xi Chu, Yuting He, Qian Zhao, Qi Wu, Meiling He, Lina Ma, Peng Liu, Liyun Zhao, Qiao-Cheng Zhai, Jun Qin, Jie Lu, Xianhe Yang, Shuo Zhang, Yu Xiong, Hua Ren, Wei Yang, Zhanmei Huang, Jiachen Zhang, Min Zhang, Pei Chen, Jian Dong, Yu Zhang, Tingting Yan, Jin-Lin Ye, Ping Huang, Zhigang Qi, Yong Liu, Jichen Shuai, Cheng-Shui Chen, Ping Li, Dawei Li, Xiuhua Xu, Xuexian Song, Jingyi Li, Jiale Ping, Jinghao Hu, Xiaoyan Sun, Jiaqi Ai, Zhengqin Wang, Yuxin Zhang, Peng Yang, Taixin Ning, Yan Yu, Zan He, Hui Zhang, Tianyang Zhang, Yuanhan Yang, Qiaoran Wang, Fangmin Lin, Xiangmei Jin, Xuewei Chen, Jie Ren, Moshi Song, Si Wang, Jiayin Yang, Jianming Li, Weihong Song, Fuchu He, Yun-Gui Yang, Gang Pei, Jing Qu, Wei Zhang, Jun Pu, Feng Zhang, Guoguang Zhao, Weiqi Zhang, Guang-Hui Liu

Beijing Key Laboratory of Intelligent Governance and Application of Biological Big Data, China National Center for Bioinformation and Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.Beijing Key Laboratory of Intelligent Governance and Application of Biological Big Data, China National Center for Bioinformation and Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China. · pubmed

Paper

Abstract

Human aging is characterized by complex structural and functional decline, but quantifying its heterogeneity and assessing biological age remain challenges. We present the mCAS (multicentric Chinese aging standardized cohort) developed from 2,019 Chinese individuals aged 18-91 years. Integrating high-dimensional clinical, physiological, and molecular-level data, we constructed a three-tiered aging framework: the core capacity clock (CC-clock) to quantify clinical physiological decline, the multimodal clock (MM-clock) with extensive parameter coverage and enhanced predictive precision, and organ-associated aging clocks. Cross-layer analysis demonstrates that plasma protein clocks not only capture chronological age but also serve as efficient proxies for systemic physiological capacity. Leveraging this framework for discovery, we identified the age-dependent accumulation of coagulation factors as a driver of multi-organ senescence and systemic inflammatory activation. This study provides a foundational framework that bridges molecular signatures with functional decline, identifies new biomarkers for aging assessment, and reveals a novel translational driver of aging.

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Research summary

The study constructs a multimodal aging clock framework using a Chinese cohort to correlate molecular signatures with physiological decline, identifying coagulation factors as a potential driver of senescence. This represents an incremental advance in biomarker development and aging phenotyping rather than a breakthrough in understanding or intervening in the root causes of aging.

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