Molecule-dynamic-based Aging Clock and Aging Roadmap Forecast with Sundial
This work addresses bias in aging prediction for biomedical research, offering a novel approach to model aging dynamics, though it appears incremental as it builds on existing aging clock methods.
The authors tackled the bias in supervised aging clocks by introducing Sundial, a framework that models molecular dynamics with a diffusion field to estimate biological age and forecast aging roadmaps, showing that faster-aging individuals identified by Sundial have higher disease risk compared to those from supervised clocks.
Addressing the unavoidable bias inherent in supervised aging clocks, we introduce Sundial, a novel framework that models molecular dynamics through a diffusion field, capturing both the population-level aging process and the individual-level relative aging order. Sundial enables unbiasedestimation of biological age and the forecast of aging roadmap. Fasteraging individuals from Sundial exhibit a higher disease risk compared to those identified from supervised aging clocks. This framework opens new avenues for exploring key topics, including age- and sex-specific aging dynamics and faster yet healthy aging paths.