GOSH BRC Project: Identification of Variants of Uncertain Significance (VUS) data in COL3A1 causing vEDS, by extraction of diagnostic laboratory data from the Sheffield Diagnostic Genetics Service and reclassification according to the ACMG criteria.

Vascular Ehlers-Danlos Syndrome (vEDS) is a hereditary genetic condition of the connective tissue, caused by mutations in COL3A1, which encodes type III collagen. This results in vascular fragility, including ruptured blood vessels, aneurysms, and arterial dissections. Patients may also present with characteristic atrophic scars, spontaneous hematomas, and gastrointestinal complications. The diagnosis of vEDS relies on clinical examination, family history and genetic testing. While a positive genetic test for a pathogenic variant in the COL3A1 gene is necessary for formal diagnosis, over 570 genetic variants have been recorded in the Ehlers-Danlos Syndrome Variant Database. The nature of these variants is directly related to the phenotype and prognosis for the disease. Studying variants of uncertain significance is crucial, as some may be associated with milder or more severe clinical phenotypes, impacting clinical management and prognosis. Periodic re-evaluation of genetic variants in accordance with the latest ACMG guidelines allows variants to be updated from variants of unknown significance (class 3 variants) to pathogenic or likely pathogenic (class 4 or 5 variants). This would be crucial in improving diagnosis and clinical management of patients affected with vEDS. Project plan: Identify and reclassify the VUS most prevalent in patients according to the criteria set by the Association for Clinical Genomic Science (ACGS) and the American College of Medical Genetics and Genomics (ACMG), through the re-evaulation of current VUSs in the lab database. This will be correlated with clinical phenotype using clinical notes review from Clinical Genetics EDS service. Anticipated outcomes: Identify VUS in genes causing vEDS through mining diagnostic laboratory database based at Sheffield Diagnostic Genetics Service, Generate a database of VUS so far reported and collate clinical data from such data mining, Reclassify VUS using current ACMG criteria to enable upgrading of disease-causing variants, Genotype-phenotype correlation with clinical phenotyping data using notes review.