Alterations in DNA 5-hydroxymethylation Patterns in the Hippocampus of an Experimental Model of Refractory Epilepsy
Bibliographic record
Abstract
Abstract Temporal lobe epilepsy (TLE) is a type of focal epilepsy characterized by spontaneous recurrent seizures originating from the hippocampus. The epigenetic reprogramming hypothesis of epileptogenesis suggests that the development of TLE is associated with alterations in gene transcription changes resulting in a hyperexcitable network in TLE. DNA 5-methylcytosine (5-mC) is an epigenetic mechanism that has been associated with chronic epilepsy. However, the contribution of 5-hydroxymethylcytosine (5-hmC), a product of 5-mC demethylation by the Ten-Eleven Translocation (TET) family proteins in chronic TLE is poorly understood. 5-hmC is abundant in the brain and acts as a stable epigenetic mark altering gene expression through several mechanisms. Here, we found that the levels of bulk DNA 5-hmC but not 5-mC were significantly reduced in the hippocampus of human TLE patients and in the kainic acid (KA) TLE rat model. Using 5-hmC hMeDIP-sequencing, we characterized 5-hmC distribution across the genome and found bidirectional regulation of 5-hmC at intergenic regions within gene bodies. We found that hypohydroxymethylated 5-hmC intergenic regions were associated with several epilepsy-related genes, including Gal , SV2, and Kcnj11 and hyperdroxymethylation 5-hmC intergenic regions were associated with Gad65 , TLR4 , and Bdnf gene expression. Mechanistically, Tet1 knockdown in the hippocampus was sufficient to decrease 5-hmC levels and increase seizure susceptibility following KA administration. In contrast, Tet1 overexpression in the hippocampus resulted in increased 5-hmC levels associated with improved seizure resiliency in response to KA. These findings suggest an important role for 5-hmC as an epigenetic regulator of epilepsy that can be manipulated to influence seizure outcomes.
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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 | 0.001 | 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 | 0.001 |
| 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".