Upside down: dissecting impulsivity in attention-deficit hyperactivity disorder through genotype-phenotype association analyses
Bibliographic record
Abstract
Introduction Better evaluation and understanding of the core symptoms have key importance both in clinical practice and the research of attention-deficit hyperactivity disorder (ADHD). One hallmark neurocognitive feature of ADHD is impaired inhibition, related to impulsivity. Given the high heritability of ADHD, the assessment of genetic background of impaired inhibition may contribute to our knowledge about the genetic background of the disorder. Objectives In our study we investigated whether different forms of impulsivity (attentive, motor, and nonplanning) and polymorphisms in genes of the noradrenergic, serotonergic, and dopaminergic neurotransmission, i.e. dopamine transporter-1 (DAT1), cathecoloamin-O-metiltransferase (COMT), and serotonin receptor-1B (HTR1B genes show association. Methods 208 aADHD patients diagnosed according to DSM-5 criteria from a clinical sample and 142 individuals from a population sample who screened positive for aADHD were included in the study. DNA samples were genotyped for the HTR-1B gene rs1321041 and the COMT gene rs4680 SNPs, moreover the DAT-1 VNTR polymorphism. Dimensional variables for impulsivity were compared between genotypes with the Generalized Linear Model procedure corrected for sex and age, using the PLINK 1.9 statistical software. Results The 9 repeat polymorphism in DAT1 was associated with the severity of hyperactivity, moreover, all impulsivity factors. The A allele in COMT was associated with hyperactivity and better motor inhibition activity. In carriers of the G allele in HTR1B we detected significantly higher inattention scores and increased reaction time. Conclusions Our results support the putative role of the investigated genetic polymorphisms in the etiology of impulsivity. Nevertheless, these polymorphisms demonstrate a heterogeneous associations. Disclosure No significant relationships.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".