The 5-HTTLPR polymorphism of the serotonin transporter gene and child's sex moderate the relationship between disaster-related prenatal maternal stress and autism spectrum disorder traits: The QF2011 Queensland flood study
Bibliographic record
Abstract
The 5-HTTLPR polymorphism of the serotonin transporter has been shown to play a role in autism spectrum disorders (ASD). Moreover, disaster-related prenatal maternal stress (PNMS) has also been shown to be associated with ASD. However, no study to date has examined whether these two factors, either individually or in combination, are predictive of ASD traits in the same sample. We hypothesized that children, particularly boys, with the LL genotype exposed to high levels of disaster-related PNMS would exhibit higher levels of ASD traits compared to boys with the LS or SS genotypes and girls regardless of genotype. Genotype and ASD levels obtained using the Australian normed Autism Spectrum Rating Scales - Short Form were available for 105 30-month-old children exposed to varying levels of PNMS following the 2011 Queensland Flood. For boys, higher ASD traits were associated with the 5-HTTLPR LL genotype in combination with either a negative maternal appraisal of the flood, or high levels of maternal composite subjective stress, PSTD-like or peritraumatic dissociation symptoms. For girls, maternal peritraumatic dissociation levels in combination with the 5-HTTLPR LS or SS genotype were associated with higher ASD traits. The present findings are the first to demonstrate that children's genotype moderates effects of disaster-related PNMS on ASD traits, with different pattern according to child sex.
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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 | 0.001 |
| 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 | 0.001 |
| 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".