Amino acid–level signal-to-noise analysis of incidentally identified variants in genes associated with long QT syndrome during pediatric whole exome sequencing reflects background genetic noise

Abstract

The prevalence of incidentally identified LQTS-associated variants is ∼38% among WES tests. These variants most likely represent benign healthy background genetic variation rather than disease-associated mutations.

Incidentally identified genetic variants in arrhythmogenic right ventricular cardiomyopathy‐associated genes among children undergoing exome sequencing reflect healthy population variation

“…Further, our application of a rare variant MAF threshold of <0.0001 was not applied to earlier work given the small cohort size (Kapplinger et al, 2011). Similar genetic background variation has been reported in the primary heritable arrhythmogenic disorders catecholaminergic polymorphic ventricular tachycardia and long QT syndrome, with rates of 6.0% and 12.9%, respectively (Landstrom et al, 2017(Landstrom et al, , 2018. While the background F I G U R E 5 Topological signal-to-noise (S:N) mapping between WES (blue line) and ARVC (orange line) cohorts, as normalized against gnomAD for (a) PKP2 (NP_001005242.2), and (b) DSG2 (NP_001934.2).…”

“…Gene-and amino acid-level (S:N) analyses were conducted as previously described (Landstrom et al, 2018) and are fully detailed in the Supplemental Methods.…”

“…These results demonstrate that variant frequency in the WES cohort, similar to the control cohort, was driven by contributions from variants in genes that are rarely associated with ARVC cases. Given evidence that disease-specific S:N calculations can distinguish background genetic noise from true pathologic variant burden, this analysis was applied to each gene locus (Landstrom et al, 2017(Landstrom et al, , 2018 Figure 3).…”

“…We have previously shown that amino acid-level S:N can distinguish incidentally identified from pathologic variants based on primary sequence location in genes associated with cardiac channelopathic disease (Landstrom et al, 2017(Landstrom et al, , 2018. We applied this methodology to ARVC-associated gene products.…”

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

“…Among the three major genes associated with LQTS, including KCNQ1, these incidentally identified variants lacked any significant signal-to-noise ratios. Furthermore, when protein-specific domain topology was overlaid against areas of high signal-to-noise, pathologic mutation "hotspots" localized to key functional domains of the proteins 14 . This methodology holds promise in determining 1) the likelihood a variant is disease-or population-associated, and 2) identifying novel critical functional domains of a protein associated with human disease.…”