Human Biomarker of Aging Modeling from Gero
The Gero staff have in recent years performed scientifically interesting modeling of data, from aging animals and humans, in support of their drug development program. One might look back on their categorization of age-related degeneration into two components, which they call "aging" and "frailty", but which are really just labels for what appear to be two distinct aspects of biomarker progression with chronological age that emerge from their data. Humans and mice have quite different balances of "aging" versus "frailty", which could in principle inform unbiased screening programs for drugs that might slow the progression of aging. In this open access paper, the Gero team look at human biomarkers of aging over time to build a model of loss of resilience; again scientifically interesting.
Most important factors that are strongly associated with age are also known as the hallmarks of aging and may be, at least in principle, modified pharmacologically. In addition to that, the dynamic properties such as physiological resilience measured as the recovery rate from the organism state perturbations were also associated with mortality and thus may serve as an early warning sign of impending health outcomes.
We conducted a systematic investigation of aging, organism state fluctuations, and gradual loss of resilience in a dataset involving multiple Complete Blood Counts (CBC) measured over short periods of time (a few months) from the same person along the individual aging trajectory. Instead of focusing on individual factors, to simplify the matters, we followed and described the organism state by means of a single variable, henceforth referred to as the dynamic organism state indicator (DOSI) in the form of the all-cause mortality model predictor. First, we observed that early in life the DOSI dynamics quantitatively follows the universal ontogenetic growth trajectory. Once the growth phase is completed, the indicator demonstrated all the expected biological age properties, such as association with age, multiple morbidity, unhealthy lifestyles, mortality and future incidence of chronic diseases.
Late in life, the dynamics of the organism state captured by DOSI along the individual aging trajectories is consistent with that of a stochastic process (random walk) on top of the slow aging drift. The increase in the DOSI variability is approximately linear with age and can be explained by the rise of the organism state recovery time. The latter is thus an independent biomarker of aging and a characteristic of resilience. Our analysis shows that the auto-correlation time of DOSI fluctuations grows (and hence the recovery rate decreases) with age from about 2 weeks to over 8 weeks for cohorts aging from 40 to 90 years. The divergence of the recovery time at advanced ages appeared to be an organism-level phenomenon.
We put forward arguments suggesting that such behavior is typical for complex systems near a bifurcation (disintegration) point and thus the progressive loss of resilience with age may be a dynamic origin of the Gompertz law of mortality. Finally, we noted, by extrapolation, that the recovery time would diverge and hence the resilience would be ultimately lost at the critical point at the age in the range of 120-150 years, thus indicating the absolute limit of human lifespan, absent novel interventions.