medRxivGenetic & Genomic MedicinePreprint
Systematic large-scale application of ClinGen InSiGHT APC-specific ACMG/AMP variant classification criteria substantially alleviates the burden of variants of uncertain significance in ClinVar and LOVD databases
Xiaoyu YiniD, Marcy E. RichardsoniD, Andreas LaneriD, Xuemei Shi, Elisabet OgnedaliD, Valeria VastaiD, Thomas van Overeem HanseniD, Marta PinedaiD, Deborah RitteriD, Johan T. den DunneniD, Emadeldin HassaniniD, Wencong Lyman Lin, Ester Borràs, Karl Krahn, Margareta NordlingiD, Alexandra MartinsiD, Khalid MahmoodiD, Emily A.W. NadeauiD, Victoria BeshayiD, Carli M.J. TopsiD, Maurizio GenuardiiD, Tina F. PesaraniD, Ian M. FraylingiD, Gabriel CapelláiD, Andrew R. LatchfordiD, , Stefan AretziD
Abstract
BackgroundPathogenic constitutional APC 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). MethodsA streamlined algorithm using the APC-specific criteria was developed and applied to assess all APC variants in ClinVar and the InSiGHT international reference APC LOVD variant database. ResultsA total of 10,228 unique APC 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 APC variants that remained VUS despite evidence for pathogenicity, a data mining-driven work-up allowed their reclassification as (Likely) Pathogenic. ConclusionsThe application of APC-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 APC variants was approved by the VCEP and made publicly available through ClinVar and LOVD for widespread clinical use.
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Curated Multiple Sequence Alignment for the Adenomatous Polyposis Coli (APC) Gene and Accuracy of In Silico Pathogenicity Predictions
Alexander D. Karabachev, Dylan J. Martini, … Marc S. Greenblatt·PLoS ONEPeer-reviewed·Aug 4, 2020
- Evaluation of Bayesian Point-Based System on the Variant Classification of Hereditary Cancer Predisposition Genes
Mohammad K. Eldomery, Jamie L. Maciaszek, … Patrick R. Blackburn·Genetics in MedicinePeer-reviewed·Sep 19, 2024
- ClinGen Variant Curation Interface: A Variant Classification Platform for the Application of Evidence Criteria from ACMG/AMP Guidelines
Christine G. Preston, Matt W. Wright, … Helio A. Costa·Genome MedicinePeer-reviewed·Jan 17, 2022
- Informing Variant Assessment using Structured Evidence from Prior Classifications (PS1, PM5, and PVS1 Sequence Variant Interpretation Criteria)
Vineel Bhat, Ivan A. Adzhubei, … Christopher A. Cassa·Genetics in MedicinePeer-reviewed·Oct 28, 2022
- From Uncertain to Actionable: Significant Reduction in Variants of Uncertain Significance in Hereditary Germline Testing via Multi-Institutional Real-World Evidence
Kelly M. Schiabor Barrett, Matthew J. Ferber, … Elizabeth T. Cirulli·medRxiv·Aug 12, 2025
- Validation of the ACMG/AMP guidelines-based seven-category variant classification system
Jian‐Min Chen, Emmanuelle Masson, … Claude Férec·medRxiv·Jan 23, 2023