Key result
Entropy in electrocardiograms, quantified using Mahalanobis distance, predicts aging-related outcomes including fracture and mortality beyond the heart.
Highlights the potential of quantifying entropy in physiological signals like electrocardiograms to predict systemic aging-related outcomes.
Entropy, a measure of disorder and randomness, is an essential feature of thermodynamics, chemistry, and information theory, but there has been little study of entropy in human aging. Entropy arises from random molecular interactions or other forms of damage and will manifest at all levels of human biology. It should also progress in concert across many systems and increase the risk of numerous aging-related conditions. Illustrating these principles, research by Hong in this issue of Aging Cell applies Mahalanobis distance to quantify entropy in electrocardiograms showing that entropy in one system predicts aging-related outcomes-fracture and mortality-beyond the heart. Important issues for research on entropy and human aging include the best methods for quantifying entropy and whether the development of entropy can be slowed or reversed in humans.
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Cummings et al. (2025) conducted an editorial in Human aging. Entropy in electrocardiograms was evaluated on Fracture and mortality. Entropy in electrocardiograms, quantified using Mahalanobis distance, predicts aging-related outcomes including fracture and mortality beyond the heart.
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