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arXiv · 2504.13044

The Dissipation Theory of Aging: A Quantitative Analysis Using a Cellular Aging Map

Farhan Khodaee·Rohola Zandie·Yufan Xia·Elazer R. Edelman
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Abstract

We propose a new theory for aging based on dynamical systems and provide a data-driven computational method to quantify the changes at the cellular level. We use ergodic theory to decompose the dynamics of changes during aging and show that aging is fundamentally a dissipative process within biological systems, akin to dynamical systems where dissipation occurs due to non-conservative forces. To quantify the dissipation dynamics, we employ a transformer-based machine learning algorithm to analyze gene expression data, incorporating age as a token to assess how age-related dissipation is reflected in the embedding space. By evaluating the dynamics of gene and age embeddings, we provide a cellular aging map (CAM) and identify patterns indicative of divergence in gene embedding space, nonlinear transitions, and entropy variations during aging for various tissues and cell types. Our results provide a novel perspective on aging as a dissipative process and introduce a computational framework that enables measuring age-related changes with molecular resolution.

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Farhan Khodaee, Rohola Zandie, Yufan Xia, Elazer R. Edelman. 2025-04-17. The Dissipation Theory of Aging: A Quantitative Analysis Using a Cellular Aging Map. https://arxiv.org/abs/2504.13044

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