Implementing a New Algorithm for Reinterpretation of Ambiguous Variants in Genetic Dilated Cardiomyopathy

Abstract

Dilated cardiomyopathy is a heterogeneous entity that leads to heart failure and malignant arrhythmias. Nearly 50% of cases are inherited; therefore, genetic analysis is crucial to unravel the cause and for the early identification of carriers at risk. A large number of variants remain classified as ambiguous, impeding an actionable clinical translation. Our goal was to perform a comprehensive update of variants previously classified with an ambiguous role, applying a new algorithm of already available tools. In a cohort of 65 cases diagnosed with dilated cardiomyopathy, a total of 125 genetic variants were classified as ambiguous. Our reanalysis resulted in the reclassification of 12% of variants from an unknown to likely benign or likely pathogenic role, due to improved population frequencies. For all the remaining ambiguous variants, we used our algorithm; 60.9% showed a potential but not confirmed deleterious role, and 24.5% showed a potential benign role. Periodically updating the population frequencies is a cheap and fast action, making it possible to clarify the role of ambiguous variants. Here, we performa comprehensive reanalysis to help to clarify the role of most of ambiguous variants. Our specific algorithms facilitate genetic interpretation in dilated cardiomyopathy.