Aging clocks based on accumulating stochastic variation

Abstract

Aging clocks have provided one of the most important recent breakthroughs in the biology of aging, and may provide indicators for the effectiveness of interventions in the aging process and preventive treatments for age-related diseases. The reproducibility of accurate aging clocks has reinvigorated the debate on whether a programmed process underlies aging. Here we show that accumulating stochastic variation in purely simulated data is sufficient to build aging clocks, and that first-generation and second-generation aging clocks are compatible with the accumulation of stochastic variation in DNA methylation or transcriptomic data. We find that accumulating stochastic variation is sufficient to predict chronological and biological age, indicated by significant prediction differences in smoking, calorie restriction, heterochronic parabiosis and partial reprogramming. Although our simulations may not explicitly rule out a programmed aging process, our results suggest that stochastically accumulating changes in any set of data that have a ground state at age zero are sufficient for generating aging clocks.

Selection for early reproduction leads to accelerated aging and extensive metabolic remodeling inDrosophila melanogasterpopulations

“…Over the lifespan of the fly, the dynamics of the metabolome have been used to connect advancing chronological age to the rise in mortality risk that defines biological aging (Zhao et al 2022). Multivariate age prediction models (clocks), particularly epigenetic clocks, have been used to predict age across species (Meyer and Schumacher 2024; Lu et al 2023). The use of clock models to understand the evolutionary process however is just beginning (Parrott and Bertucci 2019).…”

“…to predict age across species (Meyer and Schumacher 2024;Lu et al 2023). The use of clock models to understand the evolutionary process however is just beginning (Parrott and Bertucci 2019).…”