This resource was built and is maintained by the Kroncke lab at the Vanderbilt University Medical Center (Kroncke lab website). Please send any questions or comments to email@example.com. Here we develop a model where information such as variant function and structural location can inform an estimate of the risk of disease before the observation of heterozygous carriers, a prior penetrance estimate for each variant. This analysis (described in greater detail on the Penetrance Analysis page) enables an estimate of penetrance for all variants for which these data are available, even before observing in a single individual.
KCNH2 (also known as the human ether a-go-go related gene, hERG) encodes a 1,159 amino acid protein, KV11.1, a voltage-gated potassium channel in the heart. Coding-altering variants in KCNH2 have been mostly linked to the heart arrhythmias, Long QT Syndrome Type 2 (LQT2), and Short QT Syndrome (SQT1). Loss-of-function variants in KCNH2 are associated LQT2 and gain-of-function variants are associated with short QT Syndrome. The risk of sudden cardiac death from these conditions can often be prevented with drug therapy or implantation of a defibrillator. KCNH2 variants are often studied in vitro in heterologous expression systems using patch clamp electrophysiology. Use the dropdown tab at the upper left of the screen to access the full KCNH2 dataset.
The KCNH2 dataset
The dataset described on this website is a dataset of patient data and in vitro patch clamp data. This dataset was first described in Kozek et al. 2021 in Circulation: Genomics and Precision Medicine. The data were curated from a comprehensive literature review from papers written about KCNH2 (or KV11.1, the protein product of KCNH2). In addition, five centers that hold cardiology clinics and conduct research gathered clinical phenotypes and genotypes for individuals heterozygous for KCNH2 variants, including Unité de Rythmologie, Centre de Référence Maladies Cardiaques Héréditaires, Service de Cardiologie, Hôpital Bichat, Paris, France; the Center for Cardiac Arrhythmias of Genetic Origin Istituto Auxologico Italiano IRCCS, Milan, Italy; Shiga University of Medical Science Department of Cardiovascular and Respiratory Medicine, Shiga, Japan; National Cerebral and Cardiovascular Center, Osaka, Japan; Nagasaki University, Nagasaki, Japan. We quantified the number of carriers presenting with and without disease for 871 reported KCNH2 variants (an additional 266 KCNH2 inframe/missense variants coming from the international cohort). For approximately 180 variants, data were also available for at least one of six KV11.1 electrophysiologic parameters collected heterzygously and/or homozygously: steady state maximum current, peak tail current, steady state V1/2 of activation and inactivation, recovery from inactivation, and/or deactivation time.
KCNQ1 encodes a 676 amino acid transmembrane protein, which along with its partner KCNE1, forms the IKs current, the slow component of cardiac repolarization. Heterozygous variants in KCNQ1 are associated with Long QT Syndrome (Type 1), Short QT Syndrome, and Atrial Fibrillation. Alongside its cardiac function, KCNQ1 is also expressed in the ear, the digestive track, and oocytes among other organs. Accordingly, there are additional functions such as KCNQ1-encoded RNA genes that function in X-inactivation, and SNPs linked to a number of complex diseases by common variant association studies. Interestingly, homozygous loss-of-funciton variants result in a more severe condition, Jervell and Lange-Nielsen Syndrome, characterized by both cardiac abnormality and congenital deafness. With regards to Long QT Syndrome, genetic data may be leveraged in the prospective clinical management of KCNQ1 variant heterozygotes. This work can potentially be life-saving through medicines or interventions, as sudden cardiac death through ventricular arrhythmias may arise as the sentinel disease manifestation.
The KCNQ1 dataset
This dataset hosted on this site was described in O’Neill et al., Genetics in Medicine. It contains searchable phenotype information from the literature and collaborative networks and a host of in silico, structural, and functional covariates for each variant. A comprehensive literature review was undertaken searching for all papers publishing clinical cardiac data on KCNQ1 variant heterozygotes to adjudicate LQTS status. We used the gnomAD database of genetic variation to find additional variant heterozygotes that were used as putatively unaffected controls. 3 tertiary care centers from around the world also contributed patient data, including Unité de Rythmologie, Centre de Référence Maladies Cardiaques Héréditaires, Service de Cardiologie, Hôpital Bichat, Paris, France; the Center for Cardiac Arrhythmias of Genetic Origin Istituto Auxologico Italiano IRCCS, Milan, Italy; National Cerebral and Cardiovascular Center, Osaka, Japan; Nagasaki University, Nagasaki, Japan. Combining the literature and the clinical cohorts (and manually excluding potential overlapping patients), we found 629 unique missense and in-frame insertion/deletion variants present among 10,389 variant heterozygotes. All raw data can be found on our GitHub page.
SCN5A encodes a 2,016 amino-acid ion channel, NaV1.5, the main voltage-gated sodium channel in the heart. Code-altering (missense) variants in SCN5A have been linked to many arrhythmia and cardiac conditions including Brugada Syndrome Type 1 (BrS1), Long QT Syndrome Type 3 (LQT3), dilated cardiomyopathy, cardiac conduction disease, and Sick Sinus Syndrome. Loss-of-function variants in SCN5A are associated with Brugada Syndrome and other cardiac conduction defects; gain-of-function variants are associated with Long QT Syndrome. SCN5A variants are often studied in vitro in heterologous expression systems using patch clamp electrophysiology.
The dataset described on this website is a dataset of patient data and in vitro patch clamp data. This dataset was first described in Kroncke and Glazer et al. 2018, Circulation: Genomic and Precision Medicine. The data were curated from a comprehensive literature review from papers written about SCN5A or NaV1.5. We quantified the number of carriers presenting with and without disease for 1,712 reported SCN5A variants. For 356 variants, data were also available for five NaV1.5 electrophysiologic parameters: peak current, late/persistent current, steady state V0.5 of activation and inactivation, and recovery from inactivation. We found that peak and late current significantly associated with BrS1 (p < 0.001, rho = -0.44, Spearman’s rank test) and LQT3 disease penetrance (p < 0.001, rho = 0.4). Steady state V0.5 activation and recovery from inactivation also associated significantly with BrS1 and LQT3 penetrance, respectively. This dataset was updated with papers published through January 2020. The description of the revised dataset published in Kroncke et al, 2020, PLOS Genetics. This paper also includes an updated Bayesian method for estimating the penetrance of each variant.