Reduced Prefrontal Gyrification in Carriers of the Dopamine D4 Receptor 7-Repeat Allele With Attention Deficit/Hyperactivity Disorder: A Preliminary Report
Bibliographic record
Abstract
Objective: Structural and functional abnormalities have been noted in the prefrontal cortex of individuals with neurodevelopmental disorders such as Attention Deficit/Hyperactivity Disorder (ADHD). Cortical thickness and gyrification, both of which have been reported as abnormal in the prefrontal cortex in ADHD, are thought to be modulated by genetic influences during neural development. We aimed to investigate the effects of a polymorphism of the dopamine DRD4 gene (the 7-repeat ‘risk’ allele) on thickness and gyrification as distinct parameters of prefrontal cortical structure in children with ADHD. Method: We obtained structural images and genetic samples from 49 children aged 9-15 years (25 with ADHD and 24 matched controls) and calculated measures of cortical thickness and gyrification. Results: We observed a significant interaction between diagnosis and genotype on prefrontal gyrification, largely driven by reduced inferior frontal gyrification in patients who carried the DRD4 7R allele. Furthermore, inferior frontal gyrification - but not thickness - related to everyday executive functioning in 7-repeat allele carriers across groups. Conclusions: Prefrontal gyrification is reduced in children with ADHD who also carry the DRD4 7R allele and it relates to critical functional skills in the executive domain in carriers of the risk allele. More broadly, these effects highlight the importance of considering precise neurodevelopmental mechanisms through which risk alleles influence cortical neurogenesis and migration.
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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 | 0.001 | 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) | 0.003 | 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".