Fitting a Damage Accumulation Model of Aging to Variations in Species Life Span
If used sensibly, models of aging can offer some insight into the bounds of the possible with regard to which classes of biological mechanism are more or less important in determining pace of aging, onset of disease, and life span. Researchers here use a specific type of model, the saturating removal model of damage accumulation, and tinker with the parameters to see which of the processes represented by those parameters best predict the observed range of life spans across species. Perhaps the most interesting outcome is that mice and humans end up in different broad buckets in terms of categorizing how mechanisms of aging interact; this is far from the only study to suggest that this is the case.
The saturating removal (SR) model was defined and calibrated based on longitudinal damage measurements in mice (senescent cells) and Escherichia coli (membrane damage). The model is based on the simplifying hypothesis that the damage that causes aging can be summarized by a scalar x and that life cannot persist above a certain level of x. The biochemical nature of x can be different in each species. The SR model describes the dynamics of damage by a stochastic differential equation that includes production, removal, and noise. Production rises linearly with age, whereas removal saturates at high damage. Death occurs when damage exceeds a threshold. The SR model explains many quantitative patterns of aging including Gompertz and Weibull hazard curves, distributions of human frailty index, disease incidence curves, and heritability of lifespan.
Different species age in similar ways but their lifespans differ by orders of magnitude. It is not clear how these similarities and differences arise from the accumulation of damage that underlies aging. Does long lifespan arise from reduced damage production, increased removal, or enhanced robustness to damage? Here we apply the saturating removal model and fit it to survival data from well-studied species. Several parameters have near-universal values including ratios of removal rate, noise amplitude, and death threshold. The model parameter that best predicts lifespan is the damage production rate, which spans seven orders of magnitude.
We identify two distinct aging regimes: ballistic aging where damage production outpaces removal, characterizing yeast, nematodes, flies, and mice, and quasi-steady-state aging, where damage tracks a moving set point of balanced production and removal, characterizing humans, dogs, guinea pigs, and cats. These results provide a mechanistic model-based basis of comparative aging that awaits experimental validation.