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Record W122252776 · doi:10.1177/070674371305800202

Gene—Environment Interaction in Panic Disorder and Posttraumatic Stress Disorder

2013· review· en· W122252776 on OpenAlexaffvenue
Marco Battaglia

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2013
Typereview
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversité LavalInstitut Universitaire en Santé Mentale de Québec
Fundersnot available
KeywordsPanic disorderPsychologyGene–environment interactionPhenotypePosttraumatic stressGeneClinical psychologyGeneticsBiologyPsychiatryAnxiety

Abstract

fetched live from OpenAlex

Gene-environment interaction is a form of causal interplay, whereby genetic effects on phenotypic variation change as a function of environmental exposure. While conceptually appealing, there is still much debate on the veracity and the relevance of this form of etiological interdependence for psychiatric disorders. By focusing on panic disorder (PD) and posttraumatic stress disorder (PTSD), this article outlines why gene-environment interaction is controversial, why it can be important for both researchers and clinicians, and how it is investigated by quantitative genetic, molecular genetic, and genomic strategies. It is suggested that gene-environment interaction effects are more reliable and meaningful when they can be harnessed to pinpoint specific biological pathways and mechanisms. In psychiatry, this can be guided by phenotypic dissection and realized by adopting intermediate phenotypes of a physiological nature, such as carbon dioxide sensitivity for PD, or gene expression profiling after stress for PTSD. A developmental framework of reference and the possibility of transferring the investigation to animal models are additional key elements in this debate.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.042
GPT teacher head0.296
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations15
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of Psychiatry→Same topicStress Responses and Cortisol→French-language works237,207→