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Record W4387994788 · doi:10.1093/europace/euad317

Enhancing the interpretation of genetic observations in KCNQ1 in unselected populations: relevance to secondary findings

2023· article· en· W4387994788 on OpenAlexafffund
Valeria Novelli, Trent Faultless, Marina Cerrone, Melanie Care, Martina Manzoni, Sara L. Bober, Arnon Adler, Fabio De‐Giorgio, Danna Spears, Michael H. Gollob

Bibliographic record

VenueEP Europace · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsToronto General HospitalUniversity of Toronto
FundersUniversity of Toronto
KeywordsMedicineRelevance (law)Interpretation (philosophy)

Abstract

fetched live from OpenAlex

AIMS: Rare variants in the KCNQ1 gene are found in the healthy population to a much greater extent than the prevalence of Long QT Syndrome type 1 (LQTS1). This observation creates challenges in the interpretation of KCNQ1 rare variants that may be identified as secondary findings in whole exome sequencing.This study sought to identify missense variants within sub-domains of the KCNQ1-encoded Kv7.1 potassium channel that would be highly predictive of disease in the context of secondary findings. METHODS AND RESULTS: We established a set of KCNQ1 variants reported in over 3700 patients with diagnosed or suspected LQTS sent for clinical genetic testing and compared the domain-specific location of identified variants to those observed in an unselected population of 140 000 individuals. We identified three regions that showed a significant enrichment of KCNQ1 variants associated with LQTS at an odds ratio (OR) >2: the pore region, and the adjacent 5th (S5) and 6th (S6) transmembrane (TM) regions. An additional segment within the carboxyl terminus of Kv7.1, conserved region 2 (CR2), also showed an increased OR of disease association. Furthermore, the TM spanning S5-Pore-S6 region correlated with a significant increase in cardiac events. CONCLUSION: Rare missense variants with a clear phenotype of LQTS have a high likelihood to be present within the pore and adjacent TM segments (S5-Pore-S6) and a greater tendency to be present within CR2. This data will enhance interpretation of secondary findings within the KCNQ1 gene. Further, our data support a more severe phenotype in LQTS patients with variants within the S5-Pore-S6 region.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.249

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 head0.020
GPT teacher head0.283
Teacher spread0.263 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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