Epigenome-wide study uncovers tau pathology-driven changes of chromatin organization in the aging human brain
Bibliographic record
Abstract
Summary Accumulation of tau and amyloid-β are two pathologic hallmarks of Alzheimer’s disease (AD). Here, we conducted an epigenome-wide association study using the H3K9 acetylation (H3K9Ac) mark in 669 aged human prefrontal cortices: in contrast to amyloid-β, tau protein burden had a broad effect on the epigenome, affecting 5,590 out of 26,384 H3K9Ac domains. Tau-related alterations aggregated in large genomic segments reflecting spatial chromatin organization, and the magnitude of these effects correlated with the segment’s nuclear lamina association. We confirmed the functional relevance of these chromatin changes by demonstrating (1) consistent transcriptional changes in three independent datasets and (2) similar findings in two AD mouse models. Finally, we found that tau overexpression in iPSC-derived neurons disrupted chromatin organization and that these effects could be blocked by a small molecule predicted to reverse the tau effect. Thus, we report large-scale tau-driven chromatin rearrangements in the aging human brain that may be reversible with HSP90 inhibitors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".