The effects of <scp>MAOA</scp> genotype, childhood trauma, and sex on trait and state‐dependent aggression
Bibliographic record
Abstract
Monoamine oxidase A (MAOA) genotypic variation has been associated with variation in aggression, especially in interaction with childhood trauma or other early adverse events. Male carriers of the low-expressing variant (MAOA-L) with childhood trauma or other early adverse events seem to be more aggressive, whereas female carriers with the high-expressing variant (MAOA-H) with childhood trauma or other early adverse events may be more aggressive. We further investigated the effects of MAOA genotype and its interaction with sex and childhood trauma or other early adverse events on aggression in a young adult sample. We hypothesized that the association between genotype, childhood trauma, and aggression would be different for men and women. We also explored whether this association is different for dispositional (trait) aggression versus aggression in the context of dysphoric mood. In all, 432 Western European students (332 women, 100 men; mean age 20.2) were genotyped for the MAOA gene. They completed measures of childhood trauma, state and trait measures of aggression-related behaviors (STAXI), and cognitive reactivity to sad mood (LEIDS-R), including aggression reactivity. Women with the MAOA-H had higher aggression reactivity scores than women with the MAOA-L. This effect was not observed in men, although the nonsignificant findings in men may be a result of low power. Effects on the STAXI were not observed, nor were there gene by environment interactions on any of the aggression measures. A protective effect of the low-expression variant in women on aggression reactivity is consistent with previous observations in adolescent girls. In females, the MAOA-H may predispose to aggression-related problems during sad mood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.002 | 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".