How evolving heterogeneity distributions of resource allocation strategies shape mortality patterns

Area of Science:

• Evolutionary biology
• Gerontology
• Population dynamics

Background:

• Individual aging rates and timing vary, but the underlying mechanisms remain unclear.
• Understanding these differences is crucial for predicting human lifespan and aging determinants.
• Two main hypotheses suggest differences in aging rate versus aging timing.

Purpose of the Study:

• To model population heterogeneity emerging from evolutionary processes.
• To investigate how differences in aging rate or timing impact population heterogeneity and mortality patterns.
• To explore the evolutionary basis of observed mortality patterns across species.

Main Methods:

• Development of a computational model using an evolutionary algorithm.
• Simulation of population heterogeneity based on differing aging rates and timings.
• Extensive parameter exploration to validate model robustness.

Main Results:

• Both aging rate and timing differences generate distinct population heterogeneity.
• Despite differing heterogeneity, both scenarios yield similar population-level mortality patterns.
• These emergent mortality patterns qualitatively match those observed in yeasts, flies, worms, and humans.

Conclusions:

• Mortality patterns across species likely belong to a limited, robust set of curves.
• The model provides a framework for interpreting empirical data on individual variation and population-level aging.
• This approach links individual-level biological differences to population-level evolutionary dynamics.