Prenatal Effects of Selective Serotonin Reuptake Inhibitor Antidepressants, Serotonin Transporter Promoter Genotype (SLC6A4), and Maternal Mood on Child Behavior at 3 Years of Age
Bibliographic record
Abstract
OBJECTIVES: To investigate whether prenatal selective serotonin reuptake inhibitor (SSRI) antidepressant exposure affects behavior in 3-year-olds of antenatally anxious or depressed mothers and whether risk was moderated by the serotonin transporter promoter (SLC6A4) genotype. DESIGN: Prospective longitudinal cohort design. SETTING: Vancouver. PARTICIPANTS: Mothers and their 3-year-old children (n = 33 SSRI exposed and n = 42 nonexposed). Main Exposures Prenatal exposure to SSRI antidepressants and prenatal and postnatal maternal mood disturbances. MAIN OUTCOME MEASURES: Parent report of child behavior (Child Behavior Checklist, ages 1.5-5 years) and the child SLC6A4 genotype. The covariates used were maternal mood during the third trimester, 3 months postpartum, and at the 3-year follow-up study and the child's 5-minute Apgar score. RESULTS: Prenatal exposure to both maternal depressed mood and SSRI antidepressants were associated with increased internalizing behaviors during early childhood, whereas current maternal mood increased risk for externalizing behaviors. Increased child anxiety and depression symptoms were predicted by higher third-trimester maternal anxiety only in children with 2 short S alleles. In contrast, increased aggression and externalizing behaviors were predicted by third-trimester maternal anxiety only in children with 2 copies of the L allele. CONCLUSIONS: Exposure to prenatal SSRIs and maternal mood had distinct effects on child behavior at 3 years of age, reflected in an increased level of internalizing behaviors. The impact of antenatal maternal anxiety on child mood was moderated by the child SLC6A4 genotype. Despite SSRI treatment for prenatal maternal mood disturbances, childhood behavior at 3 years of age remained at risk.
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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 | 0.001 |
| 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) | 0.001 | 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".