DiscoVari: A Web-Based Precision Medicine Tool for Predicting Variant Pathogenicity in Cardiomyopathy- and Channelopathy-Associated Genes.

Background: With genetic testing advancements, the burden of incidentally identified cardiac disease-associated gene variants is rising. These variants may carry a risk of sudden cardiac death, highlighting the need for accurate diagnostic interpretation. We sought to identify pathogenic hotspots in sudden cardiac death-associated genes using amino acid-level signal-to-noise (S:N) analysis and develop a web-based precision medicine tool, DiscoVari, to improve variant evaluation.

Methods: The minor allele frequency of putatively pathogenic variants was derived from cohort-based cardiomyopathy and channelopathy studies in the literature. We normalized disease-associated minor allele frequencies to rare variants in an ostensibly healthy population (Genome Aggregation Database) to calculate amino acid-level S:N. Amino acids with S:N above the gene-specific threshold were defined as hotspots. DiscoVari was built using JavaScript ES6 and using open-source JavaScript library ReactJS, web development framework Next.js, and JavaScript runtime NodeJS. We validated the ability of DiscoVari to identify pathogenic variants using variants from ClinVar and individuals clinically evaluated at the Duke University Hospitals with cardiac genetic testing.

Results: We developed DiscoVari as an internet-based tool for S:N-based variant hotspots. Upon validation, a higher proportion of ClinVar likely pathogenic/pathogenic variants localized to DiscoVari hotspots (43.1%) than likely benign/benign variants (17.8%; P<0.0001). Further, 75.3% of ClinVar variants reclassified to likely pathogenic/pathogenic were in hotspots, compared with 41.3% of those reclassified as variants of uncertain significance (P<0.0001) and 23.4% of those reclassified as likely benign/benign (P<0.0001). Of the clinical cohort variants, 73.1% of likely pathogenic/pathogenic were in hotspots, compared with 0.0% of likely benign/benign (P<0.01).

Conclusions: DiscoVari reliably identifies disease-susceptible amino acid residues to evaluate variants by searching amino acid-specific S:N ratios.