Maternal antenatal depression and child mental health: Moderation by genomic risk for attention-deficit/hyperactivity disorder
Bibliographic record
Abstract
Maternal antenatal depression strongly influences child mental health but with considerable inter-individual variation that is, in part, linked to genotype. The challenge is to effectively capture the genotypic influence. We outline a novel approach to describe genomic susceptibility to maternal antenatal depression focusing on child emotional/behavioral difficulties. Two cohorts provided measures of maternal depression, child genetic variation, and child mental health symptoms. We constructed a conventional polygenic risk score (PRS) for attention-deficit/hyperactivity disorder (ADHD) (PRSADHD) that significantly moderated the association between maternal antenatal depression and internalizing problems at 60 months (p = 2.94 × 10-4, R2 = .18). We then constructed an interaction PRS (xPRS) based on a subset of those single nucleotide polymorphisms from the PRSADHD that most accounted for the moderation of the association between maternal antenatal depression and child outcome. The interaction between maternal antenatal depression and this xPRS accounted for a larger proportion of the variance in child emotional/behavioral problems than models based on any PRSADHD (p = 5.50 × 10-9, R2 = .27), with similar findings in the replication cohort. The xPRS was significantly enriched for genes involved in neuronal development and synaptic function. Our study illustrates a novel approach to the study of genotypic moderation on the impact of maternal antenatal depression on child mental health and highlights the utility of the xPRS approach. These findings advance our understanding of individual differences in the developmental origins of mental health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".