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Integrating evolutionary theory into a framework for the mechanistic evaluation of candidate anti-aging interventions
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Abstract
Despite decades of research into the molecular hallmarks of aging, geroscience lacks a unifying framework to guide the development of effective anti-aging interventions. Here, we integrate two leading evolutionary theories—the Disposable Soma Theory and Hyperfunction Theory—into a layered model of aging biology, the “Aging Onion”. In this framework, aging arises both from persistent activity of growth pathways and from insufficient investment into somatic maintenance. We use principles from caloric restriction (CR), a conserved pro-longevity intervention, to test the Aging Onion’s predictive and explanatory power. Pitting CR against rapamycin, a proposed pharmacological mimetic, we review evidence from the nutrient-sensing pathway and disease-prone mouse models. Here, the Aging Onion helps explain CR’s broader efficacy, which derives from simultaneous hyperfunction suppression and maintenance upregulation. Conversely, rapamycin primarily ablates growth signalling and falls short of reproducing CR’s multi-layered impact. Building on this insight, we propose a transcriptomic screening strategy that classifies gene expression changes according to their mechanistic role in aging: hyperfunction suppression vs. maintenance activation. Our approach offers a route to towards mechanistically informed intervention discovery. The ‘Aging Onion’ may thus provide a conceptual and methodological framework to align future candidate interventions with the causal architecture of aging.
DOI
https://doi.org/10.32942/X25H23
Subjects
Life Sciences
Keywords
Caloric Restriction; Disposable Soma Theory; Gene Expression Profiling; Geroprotectors; GLP-1 Receptor Agonists; Hyperfunction Theory; Rapamycin; Drug Discovery.
Dates
Published: 2026-01-30 15:56
Last Updated: 2026-01-30 15:56
License
CC BY Attribution 4.0 International
Additional Metadata
Conflict of interest statement:
None
Data and Code Availability Statement:
NA
Language:
English
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