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Recessive Mutations in POLR3B Encoding the Second Largest Subunit of Pol III Cause a Rare Hypomyelinating Leukodystrophy (P05.136)

2012· article· en· W2017962055 on OpenAlexaffabout
Martine Tétreault, Karine Choquet, Simona Orcesi, Davide Tonduti, U. Ballotin, Martin Teichmann, Sébastien Fribourg, Raphael Schiffmann, Bernard Brais, Adeline Vanderver, Geneviève Bernard

Bibliographic record

VenueNeurology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA regulation and disease
Canadian institutionsMontreal Children's HospitalMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsLeukodystrophyProtein subunitGeneticsBiologyMedicineGeneInternal medicineDisease

Abstract

fetched live from OpenAlex

Objective: Search for mutations in the second largest subunit of RNA polymerase III (Pol III), POLR3B , in case negative for mutation in POLR3A . Background Leukodystrophies are a heterogeneous group of neurodegenerative disorders characterized by abnormal central nervous system white matter. It is estimated that at least 30% to 40% of patients with leukodystrophies remain without a precise diagnosis, despite extensive investigations. We recently demonstrated that mutations in POLR3A, encoding the largest subunit of RNA polymerase III (Pol III), were responsible for the majority of cases presenting with three clinically overlapping hypomyelinating leukodystrophy phenotypes. Design/Methods: We sequenced all exons, exon-intron boundaries and 39 and 59 UTR of POLR3B (NM_018082, hg19) on available genomic DNA from four 4H cases not found previously to carry POLR3A mutations. Results: We uncovered in four cases without POLR3A mutation, recessive mutations in POLR3B which codes for the second largest subunit of Pol III. All four cases were found to be compound heterozygote for mutations in POLR3B , with one missense mutation being common to all individuals. Conclusions: Mutations in genes coding for Pol III subunits are a major cause of childhood-onset hypomyelinating leukodystrophies typically characterized by prominent cerebellar dysfunction, oligodontia and hypogonadotropic hypogonadism. Supported by: Dr G Bernard received fellowship scholarships from the RMGA (Reseau de Medecine Genetique Appliquee) and FRSQ (Fonds de Recherche en Sante du Quebec). M. Tetreault received the Frederick Banting and Charles Best Doctoral scholarship from the CIHR (Canadian Institute of Health Research). This work was supported by Fondation sur les Leucodystrophies and the European Leukodystrophy Association (ELA). Disclosure: Dr. Tetreault has nothing to disclose. Dr. Choquet has nothing to disclose. Dr. Orcesi has nothing to disclose. Dr. Tonduti has nothing to disclose. Dr. Ballotin has nothing to disclose. Dr. Teichmann has nothing to disclose. Dr. Fribourg has nothing to disclose. Dr. Schiffmann has received personal compensation for activities with Amicus Therapeutics and Shire Human Genetic Therapies. Dr. Schiffmann has received research support from Shire Human Genetic Therapies, Amicus Therapeutics, and Genzyme Corporation. Dr. Brais has nothing to disclose. Dr. Vanderver has nothing to disclose. Dr. Bernard has received personal compensation for activities with Actelion Pharmaceuticals Canada Inc, Santhera, Venture in Research as a participant on advisory boards and research teams.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.612
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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