Aging research has catalogued dozens of hallmarks — genomic instability, telomere attrition, proteostasis collapse, mitochondrial dysfunction — but how these changes drive one another has remained unclear. In a review published in The Innovation Life, a team led by Baohua Liu of Shenzhen University proposes a unifying answer: aging follows a "central dogma," the classical information-flow scheme of molecular biology, expanded to include metabolites.
The original central dogma traces genetic information from DNA to RNA to protein. The new framework adds metabolites as a fourth layer, coupled to the others by four rules — coding, catalysis, constitution, and catabolism — and regulated within each layer by synthesis, modification, and degradation. Aging, the authors argue, emerges when these processes slip out of balance and the imbalances propagate across layers.
The propagation is not one-way. DNA damage stalls RNA polymerase and fuels transcriptional errors; cytoplasmic fragments of damaged DNA switch on the cGAS-STING pathway, sustaining chronic inflammation. Aberrant RNA is not merely a passive messenger: abnormal transcripts trigger interferon responses that independently drive the senescence-associated secretory phenotype. Misfolded proteins then accumulate faster than the ubiquitin-proteasome system and autophagy can clear them, dragging metabolism down and feeding stress back to RNA and DNA.
Metabolites close the loop. SAM supplies methyl groups for DNA and histone methylation; NAD+ activates sirtuins; acetyl-CoA shapes histone acetylation; α-ketoglutarate regulates epigenetic marks. Shifts in these molecules rewrite the upstream layers, so a small metabolic change can reset the whole network.
Around all four layers sits the exposome — environmental influences arranged in concentric shells, from oxygen, hormones and inflammatory factors in the cellular microenvironment, through systemic physiology, gut microbiota, diet, exercise and sleep, out to radiation, temperature, microgravity and pollutants. These exposures set how fast the network drifts, the authors contend, and interventions can enter at any level: caloric restriction, exercise, circadian routines, microbiome modulation, or clearance of senescent cells.
The framework is a hypothesis, not new experimental data, and the authors are explicit about uneven evidence: NAD+, SAM, β-hydroxybutyrate, spermidine and α-ketoglutarate have comparatively strong support as aging modulators, while succinate, lactate and ceramides remain largely correlates whose causal roles await testing. The most useful biomarkers, they argue, will be dynamic combinations that capture cross-layer information flow rather than any single-layer metric; the most effective interventions will stabilize multiple layers at once rather than chase one target.
If borne out, the model reframes the "hallmarks of aging" from a parallel checklist into a directional, testable network — and suggests why single-target drugs have so often disappointed.
