Associations between childhood maltreatment and oxidative nucleoside damage in affective disorders
Bibliographic record
Abstract
BACKGROUND: Childhood maltreatment is an established risk factor for incident unipolar disorder and bipolar disorder. It is separately observed that affective disorders (AD) are also associated with higher nucleoside damage by oxidation. Childhood maltreatment may induce higher levels of nucleoside damage by oxidation and thus contribute to the development of AD; however, this relation is only sparsely investigated. METHODS: In total, 860 participants (468 patients with AD, 151 unaffected first-degree relatives, and 241 healthy control persons) completed the Childhood Trauma Questionnaire (CTQ). The association between CTQ scores and markers of systemic DNA and RNA damage by oxidation as measured by urinary excretion of 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG) and 8-oxo-7,8-dihydroguanosine (8-oxoGuo) levels, respectively, was investigated. RESULTS: In multiple regression models adjusted for sex- and age, 8-oxodG and 8-oxoGuo levels were found to be higher in individuals who had experienced more childhood maltreatment. These associations persisted in models additionally adjusted for body mass index, alcohol, and current smoking status. Emotional abuse, sexual abuse, and emotional neglect were principally responsible for the foregoing associations. CONCLUSIONS: Our findings of an association between childhood maltreatment and oxidative stress markers suggest that childhood maltreatment overall, notably emotional abuse and emotional neglect, is associated with enhanced systemic damage to DNA and RNA in adulthood. Further, individuals with AD reported a higher prevalence of childhood maltreatment, which may induce higher levels of nucleoside damage by oxidation in adulthood, possibly leading to increased risk of developing AD. Longitudinal studies are needed to clarify this relationship further.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".