Organ-specific proteomic aging clocks predict disease and longevity across diverse populations
Yunhe Wang, Sihao Xiao, Bowen Liu, Rongtao Jiang, Yuxi Liu, Yian Hang, Li Chen, Runsen Chen, Michael V. Vitiello, Derrick Bennett, Baihan Wang, Jun Lv, Canqing Yu, Danielle E. Haslam, Qianyan Zheng, Robert E. Gerszten, Yanping Bao, Jie Shi, Junqing Xie, Lin Lü, Liming Li, Cornelia M. van Duijn, Dong D. Wang, Zhengming Chen, Andrew T. Chan
Abstract
Aging and age-related diseases share convergent pathways at the proteome level. Here, using plasma proteomics and machine learning, we developed organismal and ten organ-specific aging clocks in the UK Biobank (n = 43,616) and validated their high accuracy in cohorts from China (n = 3,977) and the USA (n = 800; cross-cohort r = 0.98 and 0.93). Accelerated organ aging predicted disease onset, progression and mortality beyond clinical and genetic risk factors, with brain aging being most strongly linked to mortality. Organ aging reflected both genetic and environmental determinants: brain aging was associated with lifestyle, the GABBR1 and ECM1 genes, and brain structure. Distinct organ-specific pathogenic pathways were identified, with the brain and artery clocks linking synaptic loss, vascular dysfunction and glial activation to cognitive decline and dementia. The brain aging clock further stratified Alzheimer's disease risk across APOE haplotypes, and a super-youthful brain appears to confer resilience to APOE4. Together, proteomic organ aging clocks provide a biologically interpretable framework for tracking aging and disease risk across diverse populations.