Complex adaptive systems, aging and longevity.

Area of Science:

• Gerontology
• Evolutionary Biology
• Complex Systems Theory

Background:

• Mortality and reproduction are critical factors in understanding aging and longevity.
• Existing theories of aging, such as mutation accumulation and antagonistic pleiotropy, need integration with the somatic environment.
• The disposable soma theory provides a framework for understanding aging, but requires operationalization.

Purpose of the Study:

• To apply complex adaptive systems theory to fundamental questions in aging and longevity.
• To develop dynamic state variable models for a deeper understanding of aging.
• To unify genetic and phenotypic theories of aging.

Main Methods:

• Application of nonlinear, stochastic, and dynamic methods from complex adaptive systems theory.
• Development of dynamic state variable models using stochastic dynamic programming.
• Embedding genetic theories of senescence within the somatic environment.

Main Results:

• The study addresses key questions regarding evolutionary mortality trajectories, caloric restriction, reproduction, and compensatory growth.
• Dynamic state variable models are shown to operationalize the disposable soma theory of aging.
• A framework is established for unifying genetic and phenotypic theories of aging.

Conclusions:

• Complex adaptive systems provide a powerful lens for aging research.
• Dynamic models can bridge the gap between genetic predispositions and somatic realities in aging.
• This approach offers a unified perspective on the mechanisms driving aging and longevity.