Case report finds molecular testing improves diagnosis in cardiomyopathies and arrhythmias, highlighting AI's role in accuracy.
Introduction/Objective Molecular genetic testing has revolutionized the approach to cardiomyopathies and arrhythmias in both diagnosis and management, facilitating early detection, personalized treatment, and family screening. However, challenges persist in variant interpretation and equitable access to testing. Methods/Case Report We report on a series of 103 probands referred for cardiac disease. Exome sequencing was performed and genes with definite or putative association with heart conditions were analyzed. Results Twenty-four out of the 103 patients were detected with pathogenic variants in genes associated with the phenotype. Sixty-six participants presented structural cardiac disorders, including hypertrophic, dilated and arrhythmogenic cardiomyopathy, and in 22.7% of cases a variant in genes encoding for sarcomeric and cytoskeletal proteins (MYH7, LMNA, TPM1, TTN, GATA5, MYBPC3, TNNI3, DSP) was found. The 24.3% of patients with electrical alterations were diagnosed with channellopathies (SCN4A, SCN5A, KCNQ1, DSC2). In 76% of the family members who shared the variant of the proband the phenotype was not present. Conclusion In the present cohort the yield of molecular testing in cardiomyopathies and electrical alterations are superimposable. These results highlight the importance of genetic testing in individuals with cardiac phenotype and their limitations, due to incomplete penetrance, variable expressivity and modifier genes that still complicate the risk stratification. Advances in artificial intelligence and machine learning promises to improve the interpretation of genetic data and the diagnostic accuracy.
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Rongioletti et al. (2025) studied this question.
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