Organ Function-Derived Protein Clocks Demonstrate Enhanced Prediction of Organ-Specific Disease and Mortality Risk

Traditional aging clocks, typically taking chronological age or mortality as targets, face a trade-off between predictive accuracy and biological interpretability. To address this limitation, we developed protein organ clocks (POA), a novel approach that integrates aging indices derived from organ function indicators and blood proteomic data. Systematic comparison with four traditional blood protein clocks and three organ-specific clocks revealed that POA outperformed these models in associating with aging markers, predicting the risk of major organ-related diseases and mortality, and identifying clinically relevant organ aging subtypes, capturing inter-individual heterogeneity in organ aging. Critically, we constructed reduced POA models using 387 proteins that closely replicate the performance of full models, significantly lowering analytical burden and enabling feasible large-scale clinical application. The superior performance of POA stems from its integrated analysis of organ function and plasma proteomics, which enhances aging signal detection, improves biological interpretability, and strengthens clinical translational potential. To facilitate broad adoption, we developed a web server (https://www.biosino.org/poa) that allows users to upload proteomics data and calculate POAs for the body and eight organs. This work establishes a new paradigm for aging quantification and informs strategies to extend healthy lifespan and optimize disease prevention.