Epigenetic assimilation in the aging human brain
Bibliographic record
Abstract
BACKGROUND: Epigenetic drift progressively increases variation in DNA modification profiles of aging cells, but the finale of such divergence remains elusive. In this study, we explored the dynamics of DNA modification and transcription in the later stages of human life. RESULTS: We find that brain tissues of older individuals (>75 years) become more similar to each other, both epigenetically and transcriptionally, compared with younger individuals. Inter-individual epigenetic assimilation is concurrent with increasing similarity between the cerebral cortex and the cerebellum, which points to potential brain cell dedifferentiation. DNA modification analysis of twins affected with Alzheimer's disease reveals a potential for accelerated epigenetic assimilation in neurodegenerative disease. We also observe loss of boundaries and merging of neighboring DNA modification and transcriptomic domains over time. CONCLUSIONS: Age-dependent epigenetic divergence, paradoxically, changes to convergence in the later stages of life. The newly described phenomena of epigenetic assimilation and tissue dedifferentiation may help us better understand the molecular mechanisms of aging and the origins of diseases for which age is a risk factor.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".