Tackling non-canonical splicing in arrhythmogenic cardiomyopathy to reduce the uncertain significance variants burden

Functional evaluation by minigene and SpliceAI prediction of non-canonical splicing variants in ACM genes

A study of 200 arrhythmogenic cardiomyopathy (ACM) probands submitted 20 non-canonical splicing variants to SpliceAI prediction, cardiac GTEx annotation, and functional testing by pSPL3 minigene assay. Aberrant splicing was confirmed in 9/20 variants (45%), including synonymous, missense, and non-canonical intronic changes. SpliceAI scores correlated strongly with PSA values (R²=0.86). Integration of algorithmic prediction, experimental validation, and segregation enabled reclassification of 16/20 variants (80%) in DSP, DSG2, DSC2, and FLNC.

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This paper demonstrates that non-canonical splicing variants represent a significant portion of missed diagnostic yield in ACM. The SpliceAI + minigene + segregation workflow is reproducible for other hereditary cardiomyopathies. The SpliceAI-PSA correlation (R²=0.86) validates confidence in algorithmic prediction alone in borderline cases.