AI Article Synopsis

  • The study focused on improving the classification of genetic variants linked to familial adenomatous polyposis using APC-specific criteria developed by an expert panel.
  • A total of 10,228 unique variants were analyzed, resulting in 41% of VUS from ClinVar and 61% from LOVD being reclassified, primarily as (Likely) Benign, which reduced the overall VUS by 37%.
  • The research highlighted a systematic approach to variant classification in large datasets that could be applied to other gene/disease interpretations and allowed for prioritization of VUS requiring further evidence collection.

Article Abstract

Background: Pathogenic constitutional variants underlie familial adenomatous polyposis, the most common hereditary gastrointestinal polyposis syndrome. To improve variant classification and resolve the interpretative challenges of variants of uncertain significance (VUS), APC-specific ACMG/AMP variant classification criteria were developed by the ClinGen-InSiGHT Hereditary Colorectal Cancer/Polyposis Variant Curation Expert Panel (VCEP).

Methods: A streamlined algorithm using the -specific criteria was developed and applied to assess all variants in ClinVar and the InSiGHT international reference LOVD variant database.

Results: A total of 10,228 unique variants were analysed. Among the ClinVar and LOVD variants with an initial classification of (Likely) Benign or (Likely) Pathogenic, 94% and 96% remained in their original categories, respectively. In contrast, 41% ClinVar and 61% LOVD VUS were reclassified into clinically actionable classes, the vast majority as (Likely) Benign. The total number of VUS was reduced by 37%. In 21 out of 36 (58%) promising variants that remained VUS despite evidence for pathogenicity, a data mining-driven work-up allowed their reclassification as (Likely) Pathogenic.

Conclusions: The application of -specific criteria substantially reduced the number of VUS in ClinVar and LOVD. The study also demonstrated the feasibility of a systematic approach to variant classification in large datasets, which might serve as a generalisable model for other gene-/disease-specific variant interpretation initiatives. It also allowed for the prioritization of VUS that will benefit from in-depth evidence collection. This subset of variants was approved by the VCEP and made publicly available through ClinVar and LOVD for widespread clinical use.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11092726PMC
http://dx.doi.org/10.1101/2024.05.03.24306761DOI Listing

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