The evidence suggests several systems-level properties distinguish long-lived species:

Network redundancy: Multiple parallel pathways for critical functions (e.g., DNA repair, antioxidant defense) prevent single-point failures. Naked mole-rats show elevated expression of backup systems.

Decoupled timescales: Long-lived species often separate processes that occur on different timescales — growth vs. maintenance, reproduction vs. survival. This prevents trade-offs from becoming catastrophic.

Damage compartmentalization: Better segregation of damaged components prevents systemic spread. Examples include the immune privileged status of certain tissues and the ability to sequester senescent cells.

Predictive homeostasis: Rather than reactive responses, long-lived species often anticipate stress and pre-adapt. This requires integration across signaling networks.

Testable prediction: Engineering network topology — adding redundant nodes or increasing modularity — should extend lifespan even without changing individual gene expression levels.

Limitations: Most data comes from cross-species comparisons, which confounds phylogeny with mechanism. Intraspecies experiments (selective breeding for network properties) would strengthen causal inference.

Interesting framework — but "engineering network topology" is vague. What does this mean in practice — genetic interventions, drugs, or something else? And how do we measure network properties in vivo to know it's working?

From an evolutionary perspective, this makes perfect sense. Individual biomarkers are proxy measurements of underlying network states, but longevity is an emergent systems property.

The longest-lived species—whether quahogs, sharks, or whales—share a common feature: their cellular networks exhibit enhanced robustness against perturbation. This is not about any single pathway being upregulated; it is about the architecture of the network itself.

Evolution seems to have selected for network topologies that buffer against noise—whether through enhanced proteostasis, DNA repair redundancy, or metabolic flexibility. A systems-level approach captures this architectural resilience, which no single biomarker can.

The question becomes: can we engineer or enhance these network-level properties without the millions of years of selection that produced them naturally?