For example, application of computational prediction methods (including PolyPhen2, and PROVEAN) to LQTS genes has been shown to be moderately successful for predicting pathogenic KCNQ1 (LQTS type 1) and hERG (KCNH2; LQTS type 2) variants but less so for cardiac Na+ channel variants (SCN5A; LQTS type 3) (Leong et al., 2015) where LQTS (type 3) pathogenicity is predominantly associated with a gain of function (GOF) phenotype, with gating deficiencies (perturbed inactivation) in otherwise folding-competent pathogenic SCN5A variants (Giudicessi et al., 2018). Here, KCNH2 is linked to familial long QT syndrome.