Genetics of human startle reactivity: A systematic review to acquire targets for an anxiety endophenotype
Bibliographic record
Abstract
OBJECTIVES: Startle response is an objective physiological measure integral to the human defense system and a promising target for endophenotype investigations of anxiety. Given the alterations in startle reactivity observed among anxiety and related disorders, we searched for genetic variants associated with startle reactivity as they may be further involved in pathological anxiety risk. METHODS: A systematic literature review was performed to identify genetic variants associated with startle reactivity in humans, specifically baseline and fear- or anxiety-potentiated startle. RESULTS: ) were most commonly studied in human startle. In addition, several other genetic variants have also been identified as potential candidates that warrant further research, especially given their novelty in in the context of anxiety. CONCLUSIONS: Similar to psychiatric genetic studies, the studies on startle reactivity primarily focus on candidate genes and are plagued by non-replication. Startle reactivity is a promising endophenotype that requires concerted efforts to collect uniformly assessed, large, well-powered samples and hypothesis-free genome-wide strategies. To further support startle as an endophenotype for anxiety, this review suggests advanced genetic strategies for startle research.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".