With old age, the incidents of many diseases rise nearly exponentially. Strikingly, the exponential growth rates of nearly all age-related diseases, with a couple of notable exceptions, are almost the same. Despite differences in tissue architecture and disease aetiology, the “coincidence” of timescales hints at a system-wide physiological damage that connect age to specific diseases.
Recently, a mathematical model-the Saturating-Removal (SR) model-has been devevelopped to describe the temporal evolution and fluctuations of such age-related damamge. SR model has been shown to capture aging dynamics of model organisms onsets of age-related diseases. Furthermore, we have quantitatvely predicted new experimental data without retraining (Yang et al 2023), and uncovered hitero unknown relationship between healthspan and lifespan inequality (Yang et al 2025).
In this project, our goal is to identify the physiological nature of age-related damage in humans. While the SR model is very succesful in terms of the temporal evolution of damage in various organisms, it says relatively little about what precisesly is damage in any given organisms. Knowing what constitute age-realted damage so will lead to individualised, dynamic biomarkers of biological aging. Such biomarkers will help inform individual choices and future development of geroprotective therapies.
Known aging hallmarks such as cellular senescence and inflamaging in humans have been shown to partially constitute age-related damage. We hope a more methodogically rigorous study into deep phenotype data in UKBiobank would generate more complete, detailed and quatiative answer.
