Brain-Derived Neurotrophic Factor Val66Met and Behavioral Adjustment after Early Childhood Traumatic Brain Injury
Bibliographic record
Abstract
The present study examined the differential effect of the brain-derived neurotrophic factor ( BDNF ) Val66Met polymorphism on behavioral adjustment in children with traumatic brain injury (TBI) relative to children with orthopedic injury (OI). Participants were drawn from a prospective, longitudinal study of children who sustained a TBI ( n = 69) or OI ( n = 72) between 3 and 7 years of age. Parents completed the Child Behavior Checklist (CBCL) at the immediate post-acute period, 6, 12, and 18 months after injury, and an average of 3.5 and 7 years after injury. Longitudinal mixed models examined the BDNF Val66Met allele status (Met carriers vs. Val/Val homozygotes) × injury group (TBI vs. OI) interaction in association with behavioral adjustment. After adjusting for continental ancestry, socioeconomic status, time post-injury, and pre-injury functioning, the allele status × injury group interaction was statistically significant for Internalizing, Externalizing, and Total Behavior problems. Post hoc within-group analysis suggested a consistent trend of poorer behavioral adjustment in Met carriers relative to Val/Val homozygotes in the TBI group; in contrast, the opposite trend was observed in the OI group. These within-group differences, however, did not reach statistical significance. The results support a differential effect of the BDNF Val66Met polymorphism on behavioral adjustment in children with early TBI relative to OI, and suggest that the Met allele associated with reduced activity-dependent secretion of BDNF may impart risk for poorer long-term behavioral adjustment in children with TBI.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".