Inherited cardiovascular diseases are rare diseases that are difficult to diagnose by non-expert professionals. Genetic analyses play a key role in the diagnosis of these diseases, in which the identification of a pathogenic genetic variant is often a diagnostic criterion. Therefore, genetic variant classification and routine reinterpretation as data become available represent one of the main challenges associated with genetic analyses. Using the genetic variants identified in an inherited cardiovascular diseases unit during a 10-year period, the objectives of this study were: 1) to evaluate the impact of genetic variant reinterpretation, 2) to compare the reclassification rates between different cohorts of cardiac channelopathies and cardiomyopathies, and 3) to establish the most appropriate periodicity for genetic variant reinterpretation. All the evaluated cohorts (full cohort of inherited cardiovascular diseases, cardiomyopathies, cardiac channelopathies, hypertrophic cardiomyopathy, dilated cardiomyopathy, arrhythmogenic cardiomyopathy, Brugada syndrome, long QT syndrome and catecholaminergic polymorphic ventricular tachycardia) showed reclassification rates above 25%, showing even higher reclassification rates when there is definitive evidence of the association between the gene and the disease in the cardiac channelopathies. Evaluation of genetic variant reclassification rates based on the year of the initial classification showed that the most appropriate frequency for the reinterpretation would be 2 years, with the possibility of a more frequent reinterpretation if deemed convenient. To keep genetic variant classifications up to date, genetic counsellors play a critical role in the reinterpretation process, providing clinical evidence that genetic diagnostic laboratories often do not have at their disposal and communicating changes in classification and the potential implications of these reclassifications to patients and relatives.
Copyright: © 2024 Fernandez-Falgueras et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.