Integrative Analysis of the Molecular Mechanisms Governing LQTS in the KCNQ1 Potassium Channel

Abstract

Loss-of-function (LOF) pathogenic variants in the KCNQ1 cardiac potassium channel predispose to type 1 congenital long QT syndrome (LQT1), with the threat of sudden death. Accurate diagnosis of potential LQT1 patients is critical for preventative treatment. However, clinically viable prediction methods remain elusive, highlighting the necessity for detailed understanding of the molecular mechanisms driving LQT1 in KCNQ1. Our lab has conducted such research previously on the KCNQ1 voltage sensing domain (VSD), revealing that misfolding-induced mistrafficking was the predominant mechanism for this domain. We thus hypothesized that such might be the case for the channel more broadly. To expand these findings we used an integrative approach of biophysical, functional, and trafficking measurements of 61 KCNQ1 variants distributed throughout all domains of the channel. This approach required developing a novel application of the cellular thermal shift assay to quantitatively assess KCNQ1 thermal stability, providing a critical technical advance in the study of membrane protein folding and the impact of disease-causing variants. Additionally, we used previously established flow cytometry-based trafficking assays and automated whole-cell patch clamp electrophysiology to measure trafficking and function of these variants, respectively. Impaired trafficking to the plasma membrane was the most common cause of LOF across all channel domains, frequently coinciding with protein instability. However, many LOF variants, particularly in transmembrane domains, exhibited impaired conductance, altered voltage-dependence, or abnormal gating kinetics without corresponding loss of trafficking, highlighting diverse pathogenic mechanisms. From these results, five dysfunctional categories were identified, indicating a need for highly personalized treatment approaches for LQT1. Finally, we used the data from this work as well as our previous work on the VSD, a total of 112 LQT1-relevant variants, to benchmark variant pathogenicity prediction methods. The results of our analysis demonstrated that prediction accuracy depends on the dysfunctional mechanism associated with a given variant, with a clear over-reliance on protein sequence conservation scores. These findings thus elucidate the spectrum of mechanisms associated with LQT1 and provide hints for future improvements to pathogenicity prediction.