Childhood Trauma as a Cause of Psychosis: Linking Genes, Psychology, and Biology
Bibliographic record
Abstract
Recent studies have provided robust evidence for an association between childhood trauma (CT) and psychosis. Meta-analyses have quantified the association, pointing to odds ratios in the order of around 3, and prospective studies have shown that reverse causation is unlikely to explain the association. However, more work is needed to address the possibility of a gene-environment correlation, that is, whether genetic risk for psychosis predicts exposure to CT. Nevertheless, multiple studies have convincingly shown that the association between CT and psychosis remains strong and significant when controlling for genetic risk, in agreement with a possible causal association. In addition, several studies have shown plausible psychological and neurobiological mechanisms linking adverse experiences to psychosis, including induction of social defeat and reduced self-value, sensitization of the mesolimbic dopamine system, changes in the stress and immune system, and concomitant changes in stress-related brain structures, such as the hippocampus and the amygdala, findings that should be integrated, however, in more complex models of vulnerability. It is currently unclear whether genetic vulnerability plays a role in conferring the mental consequences of adversity, and which genes are likely to be involved. The current, limited evidence points to genes that are not specifically involved in psychosis but more generally in regulating mood (serotonin transporter gene), neuroplasticity (brain-derived neurotrophic factor), and the stress-response system (FKBP5), in line with a general effect of CT on a range of mental disorders, rather than suggesting specificity for psychosis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".