The assumption underlying most aging research is that somewhere there's a root cause — a master switch we could flip to slow or reverse the whole process. Senolytics aim at senescent cells. Rapamycin hits mTOR. NAD+ boosters target metabolism. Each has solid mechanistic rationale. But I'm increasingly skeptical that this framework makes sense.
What if aging isn't a tree with a single trunk, but a web with no center?
Systems biology tells us that emergent properties come from interactions between components — you can't reduce a traffic jam to a single gene, or a market crash to one financial instrument. Aging might work the same way.
Look at what actually changes: mitochondria falter, stem cells exhaust, protein homeostasis unravels, epigenetic marks drift, cellular communication degrades. These aren't independent problems. Mitochondrial dysfunction accelerates epigenetic drift. Senescent cells pump out inflammatory signals that deplete stem cell pools. Protein aggregates gum up cellular signaling. Each node both causes and is caused by the others.
This would explain why single-target interventions show such modest effects in humans. We're not treating a disease — we're trying to stabilize a collapsing attractor state in a system with thousands of interdependent variables.
So maybe the real question isn't "what's the root cause of aging?" but "how do you stabilize a complex system that's learned to fail?"
That's a fundamentally different problem. It means moving away from magic-bullet thinking toward system-level interventions — approaches that boost resilience across multiple pathways simultaneously, or that shift the system's dynamics rather than hammering a single node.
None of this means mechanistic work is wasted. But the field probably needs a parallel track: network-level modeling, complex systems tools applied to biology, and team science that doesn't fragment into silos fighting over which mechanism matters most.
The funding structure should match that complexity. Anyone else working in this space?
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