From gene to brain to behavior: schizophrenia‐associated variation in <i><scp>AMBRA</scp>1</i> alters impulsivity‐related traits
Bibliographic record
Abstract
Recently, genome-wide association between schizophrenia and an intronic variant in AMBRA1 (rs11819869) was reported. Additionally, in a reverse genetic approach in adult healthy subjects, risk allele carriers showed a higher medial prefrontal cortex blood oxygen level-dependent (BOLD) response during a flanker task examining motor inhibition as an aspect of impulsivity. To test whether this finding can be expanded to further aspects of impulsivity, we analysed the effects of the rs11819869 genotype on impulsivity-related traits on a behavioral, temperament and neural level in a large sample of healthy adolescents. We consider this reverse genetic approach specifically suited for use in a healthy adolescent sample, as these individuals comprise those who will eventually develop mental disorders in which impulsivity is implicated. Healthy adolescents from the IMAGEN study were included in the neuropsychological analysis (n = 848) and a functional magnetic resonance imaging (fMRI) task (n = 512). Various aspects of impulsivity were assessed using the Temperament and Character Inventory-Revised, the Substance Use Risk Profile Scale, the Cambridge Cognition Neuropsychological Test Automated Battery, and the Stop Signal Task (SST) in the fMRI paradigm. On a behavioral level, increased delay aversion was observed in risk allele carriers. Furthermore, risk allele carriers showed a higher BOLD response in an orbito-frontal target region during the SST, which declined to trend status after Family Wise Error correction. Our findings support the hypothesis that the schizophrenia-related risk variant of rs11819869 is involved in various aspects of impulsivity, and that this involvement occurs on a behavioral as well as an imaging genetics level.
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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 | 0.000 |
| 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) | 0.003 | 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".