(1) Background: Defects in gene CACNA1C, which encodes the pore-forming subunit of the human Cav1.2 channel (hCav1.2), are associated with cardiac disorders such as atrial fibrillation, long QT syndrome, conduction disorders, cardiomyopathies, and congenital heart defects. Clinical manifestations are known only for 12% of CACNA1C missense variants, which are listed in public databases. Bioinformatics approaches can be used to predict the pathogenic/likely pathogenic status for variants of uncertain clinical significance. Choosing a bioinformatics tool and pathogenicity threshold that are optimal for specific protein families increases the reliability of such predictions. (2) Methods and Results: We used databases ClinVar, Humsavar, gnomAD, and Ensembl to compose a dataset of pathogenic/likely pathogenic and benign variants of hCav1.2 and its 20 paralogues: voltage-gated sodium and calcium channels. We further tested the performance of sixteen in silico tools in predicting pathogenic variants. ClinPred demonstrated the best performance, followed by REVEL and MCap. In the subset of 309 uncharacterized variants of hCav1.2, ClinPred predicted the pathogenicity for 188 variants. Among these, 36 variants were also categorized as pathogenic/likely pathogenic in at least one paralogue of hCav1.2. (3) Conclusions: The bioinformatics tool ClinPred and the paralogue annotation method consensually predicted the pathogenic/likely pathogenic status for 36 uncharacterized variants of hCav1.2. An analogous approach can be used to classify missense variants of other calcium channels and novel variants of hCav1.2.

The NOTCH-signaling pathway is responsible for intercellular interactions and cell fate commitment. Recently, NOTCH pathway genes were demonstrated to play an important role in aortic valve development, leading to an increased calcified aortic valve disease (CAVD) later in life. Here, we further investigate the association between genetic variants in the NOTCH pathway genes and aortic stenosis in a case–control study of 90 CAVD cases and 4723 controls using target panel sequencing of full-length 20 genes from a NOTCH-related pathway (DVL2, DTX2, MFNG, NUMBL, LFNG, DVL1, DTX4, APH1A, DTX1, APH1B, NOTCH1, ADAM17, DVL3, NCSTN, DTX3L, ILK, RFNG, DTX3, NOTCH4, PSENEN). We identified a common intronic variant in NOTCH1, protecting against CAVD development (rs3812603), as well as several rare and unique new variants in NOTCH-pathway genes (DTX4, NOTCH1, DTX1, DVL2, NOTCH1, DTX3L, DVL3), with a prominent effect of the protein structure and function.