Decoding sexually dimorphic proteomic landscapes in the context of aging and mortality

Aging-associated changes are major contributors to the onset and progression of chronic diseases. Different aging clocks have been developed to assess biological aging, demonstrating their utility in predicting mortality, diagnosing disease, and evaluating the efficacy of antiaging interventions. However, the protein profile underlying the accelerating or decelerating rates of aging, hidden behind aging clocks, remains poorly understood. Based on the UK Biobank (n = 53, 013; age range 39-71 years; 53.9% men and 46.1% women), we built a proteomic-based aging clock, ProteAge, and assessed its performance in predicting all-cause mortality. Sex-specific aging trajectories and aging rate–associated proteins (ARPs) were identified. ProteAge reveals distinct aging trajectories for males and females, with females exhibiting more nonlinear changes in the aging rate than males do. We identify hundreds of accelerating and decelerating aging rate proteins (ARPs) in both sexes. Given the critical role of mortality prediction in aging and longevity research, we identify a subset of mortality–aging-associated proteins among ARPs, with a total of 1 protein in females but 172 in males. Furthermore, the protective and risk factors in both sexes are identified based on these ARPs. These findings highlight sexually-dimorphic proteomic changes associated with aging and mortality, offering insights into the biological mechanisms underlying aging and longevity. We developed a proteomics-based aging clock, called ProteAge, using data from UK Biobank to estimate biological age and predict mortality risk. Our results showed that men and women have different patterns of aging trajectory. Women displayed more nonlinear changes in aging trajectory. We identified hundreds of proteins linked to acclerating or decelerating aging rates. Interestingly, only one of these proteins was associated with mortality in women, compared to 172 in men. These findings highlight important biological differences between sexes in the aging process and may help guide the development of personalized strategies for promoting healthy aging and preventing age-related diseases. Jin, Du et al. develop a proteomic-based aging clock, called ProteAge, designed to estimate biological age and predict mortality risk using proteomics data from the UK Biobank. Findings reveal clear sex-specific differences in aging trajectories with women showing more complex, nonlinear patterns, whereas men tend to age in a more linear fashion.