Reversal of Epigenetic Age with Diet and Lifestyle in a Pilot Randomized Clinical Trial
Bibliographic record
Abstract
SUMMARY Manipulations to set back biological age and extend lifespan in animal models are well established, and translation to humans has begun. The length of human life makes it impractical to evaluate results by plotting mortality curves, so surrogate markers of age have been suggested and, at present, the best established surrogates are DNA methylation clocks. Herein we report on a randomized, controlled clinical trial designed to be a first step in evaluating the effect of a diet and lifestyle intervention on biological age. Compared to participants in the control group (n=20), participants in the treatment group tested an average 3.23 years younger at the end of the eight-week program according to the Horvath DNAmAge clock (p=0.018). Those in the treatment group (n=18) tested an average 1.96 years younger at the end of the program compared to the same individuals at the beginning with a strong trend towards significance (p=0.066 for within group change). This is the first such trial to demonstrate a potential reversal of biological age. In this study, the intervention was confined to diet and lifestyle changes previously identified as safe to use. The prescribed program included multiple components with documented mechanistic activity on epigenetic pathways, including moderate exercise, breathing exercises for stress, and a diet rich in methyl donor nutrients and polyphenols.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".