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

Abstract

Background: Pathogenic 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). Methods: A 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. Results: A 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. Conclusions: The 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.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This publication was supported in part by the National Human Genome Research Institute of the National Institutes of Health for the Baylor College of Medicine/Stanford University Clinical Genome Resource-2U24HG009649 and from the National Cancer Institute U24 Curation Panels through the U24CA258119. It also was supported in part by the Intramural Research Program of the National Library of Medicine, National Institutes of Health.

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The data are openly available to the public before the initiation of the study via ClinVar and the APC LSDB (www.lovd.nl/APC)

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Data Availability

All data produced in the present work are contained in the manuscript

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