The methyl donor S-adenosyl methionine reverses the DNA methylation signature of chronic neuropathic pain in mouse frontal cortex
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Chronic pain is associated with persistent but reversible structural and functional changes in the prefrontal cortex (PFC). This stable yet malleable plasticity implicates epigenetic mechanisms, including DNA methylation, as a potential mediator of chronic pain–induced cortical pathology. We previously demonstrated that chronic oral administration of the methyl donor S-adenosyl methionine (SAM) attenuates long-term peripheral neuropathic pain and alters global frontal cortical DNA methylation. However, the specific genes and pathways associated with the resolution of chronic pain by SAM remain unexplored. Objective: To determine the effect of long-term therapeutic exposure to SAM on the DNA methylation of individual genes and pathways in a mouse neuropathic pain model. Methods: Male CD-1 mice received spared nerve injury or sham surgery. Three months after injury, animals received SAM (20 mg/kg, oral, 3× a week) or vehicle for 16 weeks followed by epigenome-wide analysis of frontal cortex. Results: Peripheral neuropathic pain was associated with 4000 differentially methylated genomic regions that were enriched in intracellular signaling, cell motility and migration, cytoskeletal structure, and cell adhesion pathways. A third of these differentially methylated regions were reversed by SAM treatment (1415 regions representing 1013 genes). More than 100 genes with known pain-related function were differentially methylated after nerve injury; 29 of these were reversed by SAM treatment including Scn10a, Trpa1, Ntrk1, and Gfap . Conclusion: These results suggest a role for the epigenome in the maintenance of chronic pain and advance epigenetic modulators such as SAM as a novel approach to treat chronic pain.
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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 | 0.013 | 0.006 |
| 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 it