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Record W4408502219 · doi:10.1016/j.gimo.2025.103058

P689: A multi-site study of constitutional ring chromosomes from 14 cytogenetics laboratories in the United States

2025· article· en· W4408502219 on OpenAlexaboutno aff
Jaclyn B. Murry, Barbara R. DuPont

Bibliographic record

VenueGenetics in Medicine Open · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsCytogeneticsRing (chemistry)Ring chromosomePolitical scienceGeneticsBiologyKaryotypeChemistryChromosome

Abstract

fetched live from OpenAlex

explored how inclusion of ClinGen VCEP specifications affected variant reclassification frequencies in our clinical laboratory as compared to the 2015 ACMG/ AMP guidelines.Methods: We reviewed laboratory data of patients who underwent hereditary cancer panel genetic testing between January 2016 -October 2024 at the North York General Hospital Molecular Genetics Laboratory, Toronto, Ontario.Germline missense, synonymous, intronic, and frameshift/nonsense variants in BRCA1, BRCA2, ATM, CDH1, PALB2, and mismatch repair (MMR) genes (PMS2, MLH1, MSH2, and MSH6) were originally classified using the 2015 ACMG/AMP sequence variant guidelines.Following VCEP guideline inclusion, variants were seen for reinterpretation and included for analysis.Information relating to variant curation, including pathogenicity and classification codes applied, was collected and compared before vs after inclusion of VCEP specifications.Results: Of the 4095 unique variants detected in our laboratory, 208 were seen for reclassification using VCEP specifications (95 BRCA1/2, 60 ATM, 13 CDH1, 22 PALB2, and 18 in MMR genes) within the study period.Overall, 26.4% of variants (55/208) were re-classified to a different category using VCEP specifications: 5.3% (11/208) were upgraded in pathogenicity, while 21.2% (44/208) were downgraded.Most classification changes occurred in VUS, with 38.3% (44/115) of VUS reclassified into a meaningful category (41 LB/B; 3 LP/P).Only one variant, ATM c.6154G>A, was downgraded from a meaningful category (LP) to VUS due to published functional and co-segregation studies no longer meeting VCEP specification code criteria.The BRCA1/2 VCEP specifications resulted in the greatest number of meaningful classification changes for VUS, with 69.4% (25/36) of VUS upgraded or downgraded (3 LP/P, 22 B/LB).The most common reason for downgrade was the use of BP1_Strong, which was applicable in 41.7% (15/36) of BRCA1/2 VUS.Notably, all LP variants in BRCA1/2 were upgraded to pathogenic: 3 frameshift/nonsense variants were upgraded due to the applicability of PM5_PTC, and 1 missense variant was upgraded due to the use of PP4_VeryStrong for multifactorial likelihood clinical data.The CDH1 VCEP specifications resulted in the second largest number of VUS reclassifications, with 66.6% (8/12) of VUS reclassified into a meaningful category (all were downgraded to LB/B).Applicability of the BS2 code was the most common reason for classification changes in CDH1.Conclusion: By adopting VCEP specifications for variant curation in our clinical laboratory, we achieved an overall 26.4% variant reclassification frequency, with 38.3% of VUS reclassified into a meaningful category that increased or decreased their clinical significance.The BRCA1/2 VCEP resulted in the most drastic reclassification frequency, demonstrating the utility of this VCEP in addressing ambiguous calls.Our results support VCEP specification implementation in clinical settings, which may help reduce VUS calls and ultimately result in more clinically meaningful findings for clinicians and patients.Further studies with larger cohorts are needed to explore the clinical utility and cost-effectiveness of incorporating gene-disease specific guidelines.Ultimately, these guidelines may help standardize variant curation across clinical laboratories, leading to more effective and accurate curations.

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 score0.029
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.325
Teacher spread0.274 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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