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Record W2890345193 · doi:10.3389/fphar.2018.00974

Investigation of the HSPG2 Gene in Tardive Dyskinesia – New Data and Meta-Analysis

2018· article· en· W2890345193 on OpenAlexaff
Clement C. Zai, Frankie H. Lee, Arun K. Tiwari, Justin Lu, Vincenzo De Luca, Miriam S. Maes, Deanna Herbert, Anashe Shahmirian, Sheraz Cheema, Gwyneth Zai, Anupama Atukuri, Michael Sherman, Sajid A. Shaikh, Maria Tampakeras, Natalie Freeman, Nicole King, Daniel J. Müller, Lior Greenbaum, Bernard Lerer, Aristotle N. Voineskos, Steven G. Potkin, Jeffrey A. Lieberman, Herbert Y. Meltzer, Gary Remington, James L. Kennedy

Bibliographic record

VenueFrontiers in Pharmacology · 2018
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
FundersNational Institute of Mental Health
KeywordsTardive dyskinesiaAlleleDyskinesiaAntipsychoticMeta-analysisSchizophrenia (object-oriented programming)Genetic associationGenotypePharmacogeneticsMedicineGeneticsBioinformaticsGeneBiologyInternal medicinePsychiatrySingle-nucleotide polymorphism

Abstract

fetched live from OpenAlex

Tardive dyskinesia (TD) is a movement disorder that may occur after extended use of antipsychotic medications. The etiopathophysiology is unclear; however genetic factors play an important role. The Perlecan (HSPG2) gene was found to be significantly associated with TD in Japanese schizophrenia patients, and this association was subsequently replicated by an independent research group. To add to the evidence for this gene in TD, we conducted a meta-analysis specific to the relationship of HSPG2 rs2445142 with TD occurrence, while also adding our unpublished genotype data. Overall, we found a significant association of the G allele with TD occurrence (p=0.0001); however, much of the effect appeared to originate from the discovery dataset. Nonetheless, most study samples exhibit the same trend of association with TD for the G allele. Our findings encourage further genetic and molecular studies of HSPG2 in TD.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.276
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.076
GPT teacher head0.334
Teacher spread0.257 · 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 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

Citations22
Published2018
Admission routes1
Has abstractyes

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