DNA methylation profiling in human Huntington's disease brain
Bibliographic record
Abstract
Despite extensive progress in Huntington's disease (HD) research, very little is known about the association of epigenetic variation and HD pathogenesis in human brain tissues. Moreover, its contribution to the tissue-specific transcriptional regulation of the huntingtin gene (HTT), in which HTT expression levels are highest in brain and testes, is currently unknown. To investigate the role of DNA methylation in HD pathogenesis and tissue-specific expression of HTT, we utilized the Illumina HumanMethylation450K BeadChip array to measure DNA methylation in a cohort of age-matched HD and control human cortex and liver tissues. In cortex samples, we found minimal evidence of HD-associated DNA methylation at probed sites after correction for cell heterogeneity but did observe an association with the age of disease onset. In contrast, comparison of matched cortex and liver samples revealed tissue-specific DNA methylation of the HTT gene region at 38 sites (FDR < 0.05). Importantly, we identified a novel differentially methylated binding site in the HTT proximal promoter for the transcription factor CTCF. This CTCF site displayed increased occupancy in cortex, where HTT expression is higher, compared with the liver. Additionally, CTCF silencing reduced the activity of an HTT promoter-reporter construct, suggesting that CTCF plays a role in regulating HTT promoter function. Overall, although we were unable to detect HD-associated DNA methylation alterations at queried sites, we found that DNA methylation may be correlated to the age of disease onset in cortex tissues. Moreover, our data suggest that DNA methylation may, in part, contribute to tissue-specific HTT transcription through differential CTCF occupancy.
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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 | 0.000 | 0.001 |
| 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".