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Brain‐derived neurotrophic factor (BDNF) gene not associated with antidepressant‐induced mania

2007· article· en· W2153219979 on OpenAlexafffund
Gwyneth Zai, Emanuela Mundo, John S. Strauss, Gregory W.H. Wong, James L. Kennedy

Bibliographic record

VenueBipolar Disorders · 2007
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersCentre for Addiction and Mental Health
KeywordsManiaNeurotrophic factorsAntidepressantBrain-derived neurotrophic factorPsychologyNeurotransmitterBipolar disorderEndophenotypeNeuroscienceInternal medicineMedicineEndocrinologyPsychiatryHippocampusCentral nervous systemCognitionReceptor

Abstract

fetched live from OpenAlex

BACKGROUND: Brain-derived neurotrophic factor (BDNF) plays an important role in the regulation of synaptic plasticity and neurotransmitter release across multiple neurotransmitter systems. Recent studies have suggested that BDNF plays a role in the pathogenesis of bipolar disorder (BPD). Moreover, increasing BDNF production might be one of the mechanisms involved in the alleviation of depression and aggravation of mania in antidepressant treatment. OBJECTIVES: Thus, we hypothesized that a genetic variant within the BDNF gene might influence susceptibility to antidepressant-induced mania, as has been suggested previously. METHODS: We performed a case-control study to test for allelic frequency and genotype distribution differences across six BDNF polymorphisms between 27 patients with antidepressant-induced mania (IM+) and 29 patients without antidepressant-induced mania (IM-). RESULTS: We did not observe any significant difference in either allelic or genotype frequencies between the two groups. CONCLUSIONS: Our results did not support the BDNF link to mania hypothesis proposed previously. However, a larger sample would allow for greater power to determine smaller effects of the BDNF gene in antidepressant-induced mania.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.261
Teacher spread0.228 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations22
Published2007
Admission routes2
Has abstractyes

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