https://www.nature.com/articles/s43587-025-00975-2
A sharing link from the author is here
https://www.twitter.com/Meyer_DH/status/1968802053280444434
GPT5:
Here’s a crisp take on the Perspective you shared.
What the authors argue
- Aging clocks ≠ an aging program. Highly accurate epigenetic (and other) clocks don’t imply a built-in biological “timer.” Instead, they mostly reflect stochastic (random) accumulation of molecular errors and the gradual loss of regulatory precision. (Nature)
- Aging is a default outcome of imperfect maintenance. Because macromolecules are inherently unstable and repair systems are never perfect, damage (DNA lesions, epimutations, transcription/translation errors, organelle damage) slowly accumulates, pushing biological systems toward higher entropy. (Nature)
- Evolution makes this likely. After reproduction, the force of natural selection declines (“selection shadow”), allowing late-life deterioration via mutation accumulation and antagonistic pleiotropy—no dedicated “death program” required. (Nature)
How clocks fit in
- Precision from predictable drift. Many CpG sites—especially near developmental/PRC2-linked regions—show reproducible, site-specific drifts toward local equilibria. This creates clock-like signals even though each individual change is stochastic. Damage and repair processes accelerate this drift. (Nature)
- Not (yet) causal readouts. Clocks predict outcomes (e.g., mortality), but whether lowering “epigenetic age” improves clinical endpoints remains unproven; technical and dataset-shift issues persist. (Nature)
Evidence threads highlighted
- Individual variability: Large lifespan spread even in clonal C. elegans; modest heritability of human lifespan ⇒ big non-genetic/stochastic component. (Nature)
- Cross-species clues: Enhanced DNA repair capacity aligns with exceptional mammalian longevity; PRC2-site hypermethylation rates correlate with species lifespan patterns. (Nature)
- Repair-defect models: Progeroid mice and engineered excess DNA breaks show accelerated epigenetic age, consistent with damage-driven drift. (Nature)
Implications the authors draw
- Target maintenance, not a mythical master switch. Prioritize bolstering genome maintenance, proteostasis, mitochondrial quality control, and repair fidelity, and reducing damage burden. (Nature)
- Mechanistic clocks. Treat clocks primarily as indicators of system-wide stochastic dysregulation, and keep working to tie specific clock features to mechanisms before using them as interventional biomarkers. (Nature)
Bottom line
Aging clocks are precise barometers of age-linked stochastic drift, not evidence of a programmed death plan. Aging emerges naturally from imperfect upkeep under the waning grip of selection, and interventions should therefore focus on improving maintenance/repair and limiting damage, not trying to “turn off” a program. (Nature)
If you’d like, I can condense this further into a 3–5 sentence abstract or pull out figures/claims to map directly onto your poster/paper sections.