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Abstract #0873

Imaging-based organ-specific aging clock predicts human diseases and mortalities

Peng Ren1, WenJing Su1, Ying Liang1, Jia You1, Weikang Gong1, and Wei Cheng1
1Institute of Science and Technology for Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China

Synopsis

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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