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Predicting physiological aging rates from a range of quantitative traits using machine learning.

Aging - 29 Oct 2021

Sun Eric D, Qian Yong, Oppong Richard, Butler Thomas J, Zhao Jesse, Chen Brian H, Tanaka Toshiko, Kang Jian, Sidore Carlo, Cucca Francesco, Bandinelli Stefania, Abecasis Gonçalo R, Gorospe Myriam, Ferrucci Luigi, Schlessinger David, Goldberg Ilya, Ding Jun

Abstract excerpt

It is widely thought that individuals age at different rates. A method that measures "physiological age" or physiological aging rate independent of chronological age could therefore help elucidate mechanisms of aging and inform an individual's risk of morbidity and mortality. Here we present machine learning frameworks for inferring individual physiological age from a broad range of biochemical and physiological...

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PMID: 34718232
DOI: 10.18632/aging.203660
PMCID: PMC8580337

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