Functional Characterization of a Spectrum of Novel Romano-Ward Syndrome KCNQ1 Variants.
Susanne RinnéAnnemarie OertliClaudia NagelPhilipp TomsitsTina JeneweinStefan KääbSilke KaufersteinAxel LoeweBritt Maria BeckmannNiels DecherPublished in: International journal of molecular sciences (2023)
The KCNQ1 gene encodes the α-subunit of the cardiac voltage-gated potassium (Kv) channel KCNQ1, also denoted as Kv7.1 or KvLQT1. The channel assembles with the ß-subunit KCNE1, also known as minK, to generate the slowly activating cardiac delayed rectifier current I Ks , a key regulator of the heart rate dependent adaptation of the cardiac action potential duration (APD). Loss-of-function variants in KCNQ1 cause the congenital Long QT1 (LQT1) syndrome, characterized by delayed cardiac repolarization and a QT interval prolongation in the surface electrocardiogram (ECG). Autosomal dominant loss-of-function variants in KCNQ1 result in the LQT syndrome called Romano-Ward syndrome (RWS), while autosomal recessive variants affecting function, lead to Jervell and Lange-Nielsen syndrome (JLNS), associated with deafness. The aim of this study was the characterization of novel KCNQ1 variants identified in patients with RWS to widen the spectrum of known LQT1 variants, and improve the interpretation of the clinical relevance of variants in the KCNQ1 gene. We functionally characterized nine human KCNQ1 variants using the voltage-clamp technique in Xenopus laevis oocytes, from which we report seven novel variants. The functional data was taken as input to model surface ECGs, to subsequently compare the functional changes with the clinically observed QTc times, allowing a further interpretation of the severity of the different LQTS variants. We found that the electrophysiological properties of the variants correlate with the severity of the clinically diagnosed phenotype in most cases, however, not in all. Electrophysiological studies combined with in silico modelling approaches are valuable components for the interpretation of the pathogenicity of KCNQ1 variants, but assessing the clinical severity demands the consideration of other factors that are included, for example in the Schwartz score.
Keyphrases
- copy number
- heart rate
- left ventricular
- genome wide
- heart failure
- blood pressure
- machine learning
- gene expression
- heart rate variability
- risk assessment
- magnetic resonance
- computed tomography
- transcription factor
- staphylococcus aureus
- cystic fibrosis
- molecular dynamics simulations
- duchenne muscular dystrophy
- contrast enhanced
- drug induced
- intellectual disability
- human health