Keywords: Aging, Aging, Multi-organ Imaging
Motivation: The heterogeneous nature of aging across different organs motivates the need for a deep understanding of organ-specific biological age to inform disease risks and potential interventions.
Goal(s): The study aims to provide an alternative aging clock to existing ones to provide better organ specificity and predictive ability for organ-specific diseases.
Approach: We constructed imaging-based aging clock with regularized machine learning model and predict incident of diseases with Cox regression and LightGBM.
Results: Imaging-based organ-specific aging clock could not only predict incident of organ-specific diseases and mortalities, but also associated with proteins that enriched in the functions that the corresponding organ are responsible for.
Impact: Our research has, for the first time, illustrated organ specificity of imaging-based aging clock from the macroscale and microscale perspective. Furthermore, imaging-based organ aging could predict the incident of organ-specific diseases, highlighting potential targets aimed at slowing organ-specific aging processes.
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