Association of Genetic Factors and Gene–Environment Interactions With Risk of Developing Posttraumatic Stress Disorder in a Case–Control Study
Bibliographic record
Abstract
BACKGROUND: The dopamine receptor D2 (DRD2) and serotonin transporter (5-HTT) genes are associated with posttraumatic stress disorder (PTSD). However, it remains largely unknown whether these genes interact with environmental factors to affect the development of PTSD. PURPOSE: The purpose of this study was to examine the associations of gene polymorphisms and gene-environment interactions with the risk of developing PTSD among adolescent earthquake survivors. METHOD: A total of 183 adolescent survivors from an earthquake-stricken area participated in this study. Measures included a questionnaire about demographic characteristics and earthquake exposure, the PTSD Checklist-Civilian Version and the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, fourth edition disorders. Genotypes were analyzed by using the polymerase chain reaction-based restriction fragment length polymorphism. RESULTS: The 5-HTTLPR and 5-HTTVNTR polymorphisms and earthquake exposure had statistically significant positive effects on PTSD. The interaction effects of 5-HTTLPR × Earthquake Exposure and 5-HTTVNTR × Earthquake Exposure were statistically significant. CONCLUSION: The development of PTSD is the result not only of a genetic effect and environmental factors but also of the interactive effect between gene and environment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".