Association study of 90 candidate gene polymorphisms in panic disorder
Bibliographic record
Abstract
OBJECTIVE: In the present investigation we screened a large number of single nucleotide polymorphisms in the genes relevant to the neurobiology of anxiety for their association with panic disorder (PD). METHODS: The study sample included 127 patients with PD and 146 healthy control subjects. Using Arrayed Primer Extension technology we genotyped 90 polymorphisms in 21 candidate genes of serotonin, cholecystokinin, dopamine and opioid neurotransmitter systems. The association and haplotype analyses were performed in the whole group (PD-all) and in the subgroups of PD comorbid with major depression (PD-comorbid, n = 60) and without any comorbidity (PD-pure, n = 42). RESULTS: From the set of 90 polymorphisms, eight single nucleotide polymorphism markers in eight genes displayed at least a nominal association with any of the studied PD phenotype subgroups. Several polymorphisms of cholecystokinin, serotonin and dopamine systems were associated with PD-all and/or PD-comorbid phenotypes, while pure PD was associated only with HTR2A receptor 102T-C (P = 0.01) and DRD1 receptor -94G-A (P = 0.02) polymorphisms. Haplotype analysis supported an association of the cholecystokinin gene TG haplotype with the PD-all group (P = 0.04), whereas DRD1 receptor CAA and HTR2A receptor AT haplotypes were associated with a lower risk for PD-pure phenotype (P = 0.03 and P = 0.04, respectively). CONCLUSIONS: The study results suggest that genetic variants of several candidate genes of neurotransmitter systems, each of a minor individual effect, may contribute to the susceptibility to PD. Our data also indicate that genetic variability may have a distinctive influence on pure and comorbid phenotypes of PD.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".