Enhancing the curation of variants of uncertain significance

Abstract

The increased demand for genetic sequencing has consequently led to a rise in the number of Variants of Uncertain Significance (VUS), which are classified as such due to insufficient evidence to determine their pathogenicity. These variants lead to incomplete diagnosis for patients, thus potentially causing anxiety and unease due to the uncertainty associated with VUS and may result in unnecessary treatments. The Laboratory of Molecular Pathology and Genetics, Pathology Department, Mater Dei Hospital, situated at the University of Malta, currently utilises software including VarSome and Franklin, to analyse genetic data and provide variant classifications based on the American College of Medical Genetics and Genomics (ACMG) guidelines. Any VUS identified through this analysis are recorded in Excel files which makes management and reclassification challenging. We developed a software, VUSVista, for organised and semi-automated VUS curation by offering ACMG criteria management, referencing of external databases like dbSNP and ClinVar, using standardised Human Phenotype Ontology (HPO) terms to describe sample phenotypes, and linking variants to pseudonymised samples. The absence of personal identifiers in the software safeguards patients’ privacy and makes it GDPR-compliant. VUSVista automatically checks for any updates to ClinVar’s germline classification entries for recorded VUS and searches for newly released publications referencing its VUS using LitVar 2.0. Users receive email notifications whenever a ClinVar entry is updated or a relevant publication is found, which enables them to stay informed about discoveries made by the scientific community. If significant evidence is obtained either from these discoveries or generated internally in the laboratory, users may reclassify the VUS using VUSVista. Our software maintains three audit trails for each of its recorded VUS: one representing any changes applied to the VUS, one for ClinVar update checks and one for publication checks. These audit trails are essential for ensuring traceability and accountability within the diagnostics laboratory’s Quality Management System (QMS). Five individuals working at the aforementioned laboratory participated in one-to-one sessions to evaluate VUSVista and its features. This was followed by a focus group where they discussed the system and shared feedback. During the system’s evaluation, the participants highlighted the automated checks, notification emails, audit trails, and the ability to link variants to samples as significantly useful features that set VUSVista apart from the other systems which they currently use. The participants also suggested improvements to increase the likelihood of adopting the system, such as filtering notifications to only include updates about variants of interest and adding intermediate strengths for ACMG criteria. Overall, VUSVista is a software designed to facilitate VUS curation and reclassification which increases the likelihood of patients receiving a comprehensive diagnosis and in turn, the most accurate management.