A <scp>DRD</scp> 4 gene by maternal sensitivity interaction predicts risk for overweight or obesity in two independent cohorts of preschool children
Bibliographic record
Abstract
BACKGROUND: Recent evidence suggests that early exposure to low maternal sensitivity is a risk factor for obesity in children and adolescents. A separate line of study shows that the seven-repeat (7R) allele of the dopamine-4 receptor gene (DRD4) increases susceptibility to environmental factors including maternal sensitivity. The current study integrates these lines of work by examining whether preschoolers carrying the 7R allele are more vulnerable to low maternal sensitivity as it relates to overweight/obesity risk. METHOD: The Maternal Adversity Vulnerability and Neurodevelopment (MAVAN) project in Canada was used as the discovery cohort (N = 203), while the Generation R study in the Netherlands was used as a replication sample (N = 270). Regression models to predict both continuous BMI z-scores and membership in any higher BMI category based on established World Health Organization (WHO) cutoffs for 48 months of age were completed. RESULTS: In both cohorts, there was a significant maternal sensitivity by DRD4 by sex interaction predicting higher body mass indices and/or obesity risk. As hypothesized, post hoc testing revealed an inverse relationship between maternal sensitivity and body mass indices in 7R allele carriers relative to noncarriers. This finding was strongest in girls in the Canadian cohort and in boys in the Dutch cohort. CONCLUSIONS: Many children who carry the 7R allele of DRD4 appear to be more influenced by maternal sensitivity as it relates to overweight/obesity risk, consistent with a plasticity effect. Given the relatively small sample sizes available for these analyses, further replications will be needed to confirm and extend these results.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".