Maternal prenatal anxiety and child brain-derived neurotrophic factor (<i>BDNF</i>) genotype: Effects on internalizing symptoms from 4 to 15 years of age
Bibliographic record
Abstract
Multiple behavioral and health outcomes, including internalizing symptoms, may be predicted from prenatal maternal anxiety, depression, or stress. However, not all children are affected, and those that are can be affected in different ways. Here we test the hypothesis that the effects of prenatal anxiety are moderated by genetic variation in the child's brain-derived neurotrophic factor (BDNF) gene, using the Avon Longitudinal Study of Parents and Children population cohort. Internalizing symptoms were assessed from 4 to 13 years of age using the Strengths and Difficulties Questionnaire (n = 8,584); a clinical interview with the adolescents was conducted at age 15 years (n = 4,704). Obstetric and psychosocial risk and postnatal maternal symptoms were included as covariates. Results show that prenatal maternal anxiety predicted internalizing symptoms, including with the diagnostic assessment at 15 years. There was a main effect of two BDNF polymorphisms (rs6265 [val66met] and rs11030104) on internalizing symptoms up to age 13. There was also genetic moderation of the prenatal anxiety effect by different BDNF polymorphisms (rs11030121 and rs7124442), although significant effects were limited to preadolescence. The findings suggest a role for BDNF gene-environment interactions in individual vulnerability to the effects of prenatal anxiety on child internalizing symptoms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".