MétaCan
Menu
Back to cohort
Record W2109970900 · doi:10.1002/ajmg.b.30023

Lack of association or linkage disequilibrium between schizophrenia and polymorphisms in the 5‐HT1Dα and 5‐HT1Dβ autoreceptor genes: Family‐based association study

2004· article· en· W2109970900 on OpenAlexafffund
Alda M. Ambrósio, James L. Kennedy, Fabìo Macciardi, Isabel Coelho, M.J. Soares, Catarina R. Oliveira, Carlos N. Pato

Bibliographic record

VenueAmerican Journal of Medical Genetics Part B Neuropsychiatric Genetics · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersMedical Research Council Canada
KeywordsLinkage disequilibriumTransmission disequilibrium testDisequilibriumTaqIHaplotypeGenetic associationGeneticsPopulationAutoreceptorBiologyPsychologyAllelePolymorphism (computer science)GeneMedicineReceptorGenotypeSingle-nucleotide polymorphism

Abstract

fetched live from OpenAlex

Genetic factors play a major role in the etiology of schizophrenia and disturbances of serotonergic pathways have been implicated in this disorder. The aim of the present study was to examine genetic association between schizophrenia and polymorphisms in the 5-HT1Dalpha (TaqI) and 5-HT1Dbeta (T261G and G861C) autoreceptor genes in ninety trios from Portugal. No association or linkage disequilibrium was obtained between schizophrenia and 5-HT1Dalpha and 5-HT1Dbeta autoreceptor genes with both haplotype relative risk (HRR) and transmission disequilibrium test (TDT). Concerning 5-HT1Dbeta autoreceptor gene, also negative results was obtained in the analysis of the haplotypes with transmit. Thus, our data provide no support for the hypothesis that polymorphisms at 5-HT1Dalpha (TaqI) and 5-HT1Dbeta (T261G and G861C) genes contributes to susceptibility to schizophrenia in the Portuguese population.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.024
GPT teacher head0.307
Teacher spread0.283 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueAmerican Journal of Medical Genetics Part B Neuropsychiatric GeneticsSame topicGenetic Associations and EpidemiologyFrench-language works237,207