High-Throughput Functional Evaluation of KCNQ1 Decrypts Variants of Unknown Significance

Abstract

Background The explosive growth in known human gene variation presents enormous challenges to current approaches for variant classification that have implications for diagnosis and treatment of many genetic diseases. For disorders caused by mutations in cardiac ion channels as in congenital arrhythmia syndromes, in vitro electrophysiological evidence has high value in discriminating pathogenic from benign variants, but these data are often lacking because assays are cost-, time- and labor-intensive. Methods We implemented a strategy for performing high throughput, functional evaluations of ion channel variants that repurposed an automated electrophysiological recording platform developed previously for drug discovery. Results We demonstrated success of this approach by evaluating 78 variants in KCNQ1, a major gene involved in genetic disorders of cardiac arrhythmia susceptibility. We benchmarked our results with traditional electrophysiological approaches and observed a high level of concordance. This strategy also enabled studies of dominant-negative behavior of variants exhibiting severe loss-of-function. Overall, our results provided functional data useful for reclassifying more than 65% of the studied KCNQ1 variants. Conclusions Our results illustrate an efficient and high throughput paradigm linking genotype to function for a human cardiac ion channel that will enable data-driven classification of large numbers of variants and create new opportunities for precision medicine.

A computational model of induced pluripotent stem-cell derived cardiomyocytes for high throughput risk stratification of KCNQ1 genetic variants

“…Population-based modeling provides a high-throughput method to examine trends across diverse cellular phenotypes, while also allowing for mechanistic insights into individual rare events observed in a particular model. Vanoye et al recently published a novel dataset of KCNQ1 mutations expressed in Chinese hamster ovary (CHO) cells, characterized using automated planar patch clamp [30]. The functional changes in KCNQ1 for each mutation can be implemented as relative changes in our previously developed iPSC-CM I Ks model.…”

“…This set of mutations is defined as test set 1 (TS1). To analyze the impact of mutations characterized in TS1, experimental data from Vanoye et al was used to develop a computational model of I Ks that incorporated the kinetic effects of each mutation [30]. For each mutant the I Ks model (Eqs 1-3) were fit to the relative change in G Ks , V 1/2 , and k between the wild-type (WT) and mutant KCNQ1.…”

“…For each mutant the I Ks model (Eqs 1-3) were fit to the relative change in G Ks , V 1/2 , and k between the wild-type (WT) and mutant KCNQ1. Models were optimized to fit measurements by Vanoye et al recorded using automated patch clamp PLOS COMPUTATIONAL BIOLOGY [30]. The resulting activation curves (x act,1 ) and I-V curves for the WT model and each TS1 I Ks mutant model are shown in Fig 1A and 1B, respectively.…”

“…Based on Clin-Var assessments of TS1 mutations, nine mutants are LQTS pathogenic (Y111C, L114P, P197L, C122Y, E160K, R174C, I204F, A344V, V110I), one mutant is LQTS likely pathogenic (A300T), one mutant is short QT pathogenic (F279I), one mutant is atrial fibrillation pathogenic (S209P), and one mutant is likely benign (V207M). Six of the pathogenic mutants in TS1, which result in insufficient current to measure KCNQ1 current density or V 1/2 (Vanoye et al, supplemental table S4a [30]), were modeled as complete I Ks block (G Ks = 0pA/pF).…”

Two-stage electro-mechanical coupling of a KV channel in voltage-dependent activation

“…Yet the mechanistic basis underlying how each mutation leads to channel dysfunction and disease cannot be simply inferred from their location. For example, a mutation within the VSD may affect either VSD stability, VSD activation, and/or E-M coupling to cause channel dysfunction 30,31 . These knowledge gaps in K V 7.1 voltage-dependent activation limit our ability to explain the molecular mechanisms by which these mutations disrupt channel function, limiting the power of precision-medicine approaches to address diverse LQT-associated mutations.…”