Number of manic episodes is associated with elevated DNA oxidation in bipolar I disorder
Bibliographic record
Abstract
Bipolar disorder (BD) is a major public health problem characterized by progressive functional impairment. A number of clinical variables have been associated with progression of the disease, most notably number of affective episodes and presence of psychotic symptoms, both of which correlate with greater cognitive impairment, lower response rates for lithium, and possibly lower levels of neurotrophic factors. Oxidative damage to cytosine and guanosine (8-OHdG) has been described as a modulator of DNA methylation, but the extent of DNA oxidative damage involvement in BD remains unclear. The aim of this study was to evaluate the extent of DNA oxidative damage to 8-OHdG and 5-methylcytosine (5-HMec), as well as global methylation (5-Mec), in BD patients and healthy controls. Potential association with clinical variables was also investigated. DNA levels of 8-OHdG, 5-HMec and 5-Mec were measured in 50 BD type I patients and 50 healthy controls. DNA 8-OHdG levels were higher in BD patients compared to healthy controls and found to be positively influenced by number of previous manic episodes. BD subjects had lower levels of 5-HMec compared to controls, whereas this measure was not influenced by the clinical features of BD. Number of manic episodes was correlated with higher levels of 8-OHdG, but not of 5-Mec or 5-HMec. Lower demethylation activity (5-HMec) but no difference in global 5-Mec levels was observed in BD. This finding suggests that oxidative damage to 8-OHdG might be a potential marker of disease progression, although further prospective cross-sectional studies to confirm neuroprogression in BD are warranted.
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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 | 0.001 |
| 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 | 0.000 |
| 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".