The Role of Genetic Testing in Diagnosis and Care of Inherited Cardiac Conditions in a Specialised Multidisciplinary Clinic

Abstract

ABSTRACTBackgroundThe diagnostic yield of genetic testing for inherited cardiac diseases is up to 40% and primarily indicated for screening of at-risk relatives. Here we evaluate the role of genomics in diagnosis and management among consecutive individuals attending a specialised clinic and identify those with highest likelihood of having a monogenic disease.MethodsRetrospective audit of 1697 consecutive, unrelated probands referred to a specialised, multidisciplinary clinic between 2002 and 2020. A concordant clinical and genetic diagnosis was considered solved. Cases were classified as likely monogenic based on a score comprising a positive family history, young age at onset and severe phenotype, whereas low scoring cases were considered to have a likely complex aetiology. The impact of a genetic diagnosis was evaluated.ResultsA total of 888 probands fulfilled inclusion criteria, and genetic testing identified likely pathogenic or pathogenic (LP/P) variants in 330 individuals (37%), and suspicious variants of uncertain significance (VUS) in 73 (8%). Research-focused efforts identified 46 (5%) variants, missed by conventional genetic testing. Where a variant was identified, this changed or clarified the final diagnosis in a clinically useful way for 51 (13%). The yield of suspicious VUS across ancestry groups ranged from 15-20%, compared to only 10% among Europeans. Even when the clinical diagnosis was uncertain, those with the most monogenic disease features had the greatest diagnostic yield from genetic testing.ConclusionResearch-focused efforts can increase the diagnostic yield by up to 5%. Where a variant is identified, this will have clinical utility beyond family screening in 13%. We demonstrate the value of genomics in reaching an overall diagnosis, and highlight inequities based on ancestry. Acknowledging our incomplete understanding of disease phenotypes, we propose a framework for prioritising likely monogenic cases to solve their underlying cause of disease.