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Record W1993508623 · doi:10.1136/jmedgenet-2013-101796

CAG size-specific risk estimates for intermediate allele repeat instability in Huntington disease

2013· article· en· W1993508623 on OpenAlexafffund
Alicia Semaka, Chris Kay, Crystal N. Doty, Jennifer A. Collins, Emilia K. Bijlsma, Fiona Richards, Y. Paul Goldberg, Michael R. Hayden

Bibliographic record

VenueJournal of Medical Genetics · 2013
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsChild and Family Research InstituteXenon Pharmaceuticals (Canada)University of British Columbia
FundersCanadian Institutes of Health Research
KeywordsHuntington's diseaseAlleleGeneticsBiologyDiseaseMedicineInternal medicineGene

Abstract

fetched live from OpenAlex

INTRODUCTION: New mutations for Huntington disease (HD) occur due to CAG repeat instability of intermediate alleles (IA). IAs have between 27 and 35 CAG repeats, a range just below the disease threshold of 36 repeats. While they usually do not confer the HD phenotype, IAs are prone to paternal germline CAG repeat instability. Consequently, they may expand into the HD range upon transmission to the next generation, producing a new mutation. Quantified risk estimates for IA repeat instability are extremely limited but needed to inform clinical practice. METHODS: Using small-pool PCR of sperm DNA from Caucasian men, we examined the frequency and magnitude of CAG repeat instability across the entire range of intermediate CAG sizes. The CAG size-specific risk estimates generated are based on the largest sample size ever examined, including 30 IAs and 18 198 sperm. RESULTS: Our findings demonstrate a significant risk of new mutations. While all intermediate CAG sizes demonstrated repeat expansion into the HD range, alleles with 34 and 35 CAG repeats were associated with the highest risk of a new mutation (2.4% and 21.0%, respectively). IAs with ≥33 CAG repeats showed a dramatic increase in the frequency of instability and a switch towards a preponderance of repeat expansions over contractions. CONCLUSIONS: These data provide novel insights into the origins of new mutations for HD. The CAG size-specific risk estimates inform clinical practice and provide accurate risk information for persons who receive an IA predictive test result.

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)0.001
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.022
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.295
Teacher spread0.266 · 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.

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

Citations88
Published2013
Admission routes2
Has abstractyes

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