Phylogenetic and physicochemical analyses enhance the classification of rare nonsynonymous single nucleotide variants in type 1 and 2 long-QT syndrome

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Abstract

Background: Hundreds of nonsynonymous single nucleotide variants (nsSNVs) have been identified in the 2 most common long-QT syndrome-susceptibility genes (KCNQ1 and KCNH2). Unfortunately, an ≈3% background rate of rare KCNQ1 and KCNH2 nsSNVs amongst healthy individuals complicates the ability to distinguish rare pathogenic mutations from similarly rare yet presumably innocuous variants. Methods and Results: In this study, 4 tools [(1) conservation across species, (2) Grantham values, (3) sorting intolerant from tolerant, and (4) polymorphism phenotyping] were used to predict pathogenic or benign status for nsSNVs identified across 388 clinically definite long-QT syndrome cases and 1344 ostensibly healthy controls. From these data, estimated predictive values were determined for each tool independently, in concert with previously published protein topology-derived estimated predictive values, and synergistically when =3 tools were in agreement. Overall, all 4 tools displayed a statistically significant ability to distinguish between case-derived and control-derived nsSNVs in KCNQ1, whereas each tool, except Grantham values, displayed a similar ability to differentiate KCNH2 nsSNVs. Collectively, when at least 3 of the 4 tools agreed on the pathogenic status of C-terminal nsSNVs located outside the KCNH2/Kv11.1 cyclic nucleotide-binding domain, the topology-specific estimated predictive value improved from 56% to 91%. Conclusions: Although in silico prediction tools should not be used to predict independently the pathogenicity of a novel, rare nSNV, our results support the potential clinical use of the synergistic utility of these tools to enhance the classification of nsSNVs, particularly for Kv11.1's difficult to interpret C-terminal region. © 2012 American Heart Association, Inc.

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Giudicessi, J. R., Kapplinger, J. D., Tester, D. J., Alders, M., Salisbury, B. A., Wilde, A. A. M., & Ackerman, M. J. (2012). Phylogenetic and physicochemical analyses enhance the classification of rare nonsynonymous single nucleotide variants in type 1 and 2 long-QT syndrome. Circulation: Cardiovascular Genetics, 5(5), 519–528. https://doi.org/10.1161/CIRCGENETICS.112.963785

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