Peripheral gene expression profiling of CCK‐4‐induced panic in healthy subjects
Bibliographic record
Abstract
Progress in understanding the genetic basis of panic attacks may extend current knowledge on susceptibility to panic and pathogenesis of panic disorder. In the present study we applied the microarray Illumina platform for whole genome expression profiling in healthy subjects participating in the CCK-4-induced panic test. The study sample consisted of 31 male and female healthy volunteers, who were categorized according to predefined criteria as "panickers" or "non-panickers" to a CCK-4 challenge. The gene expression profiles were measured on peripheral blood cells at baseline and at 120 min post-CCK-4 injection using Illumina Human-6 v2 BeadChips. The fold change was used to demonstrate rate of changes in average gene expressions between studied groups. Statistical analyses were performed using the false discovery rate (FDR). Gene expression profiling 2 hr post-CCK-4 challenge showed changes in transcriptional levels of 226 genes. A total of 61 genes were differentially expressed between panickers and non-panickers with most of them related to immune, enzymatic or stress regulation systems. Other distinctive mRNA transcripts were from the genes known to be related to phenotypes associated with increased occurrence of panic attacks, such as asthma, diabetes, or myocardial ischemia. Our findings provide preliminary evidence for genetic substrates of panic attacks on the transcriptional level and indicate potential biological proximity between acute panicogenesis and several somatic conditions.
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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) | 0.001 | 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".