Classification models distinguish functional and trafficking effects of KCNQ1 variants to enhance variant interpretation.

ABSTRACT: Missense mutations compromise protein fitness by altering stability and function, which can lead to various clinical disease states. The potassium ion channel KCNQ1 underlies the majority of congenital long QT syndrome (LQTS) cases, one of the most common genetic arrhythmia syndromes. During genetic testing for LQTS, variants of uncertain significance (VUS) confound diagnosis and clinical management. KCNQ1 protein fitness metrics enable mechanistic classification of variants, directly informing the molecular basis for dysfunction and providing clinical interpretation of variants linked to LQTS and other channelopathies. We developed structure-aware random forest classifier models to predict seven metrics of KCNQ1 fitness, four functional electrophysiology measurements (peak current density

SUBMITTER: Chang-Gonzalez AC 

PROVIDER: S-EPMC12636340 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature