A Bayesian method to estimate variant-induced disease penetrance

Variable Penetrance and Expressivity of a Rare Pore Loss-of-Function Mutation (p.L889V) of Nav1.5 Channels in Three Spanish Families

A novel rare mutation in the pore region of Nav1.5 channels (p.L889V) has been found in three unrelated Spanish families that produces quite diverse phenotypic manifestations (Brugada syndrome, conduction disease, dilated cardiomyopathy, sinus node dysfunction, etc.) with variable penetrance among families. We clinically characterized the carriers and recorded the Na+ current (INa) generated by p.L889V and native (WT) Nav1.5 channels, alone or in combination, to obtain further insight into the genotypic-phenotypic relationships in patients carrying SCN5A mutations and in the molecular determinants of the Nav1.5 channel function. The variant produced a strong dominant negative effect (DNE) since the peak INa generated by p.L889V channels expressed in Chinese hamster ovary cells, either alone (-69.4 ± 9.0 pA/pF) or in combination with WT (-62.2 ± 14.6 pA/pF), was significantly (n ≥ 17, p < 0.05) reduced compared to that generated by WT channels alone (-199.1 ± 44.1 pA/pF). The mutation shifted the voltage dependence of channel activation and inactivation to depolarized potentials, did not modify the density of the late component of INa, slightly decreased the peak window current, accelerated the recovery from fast and slow inactivation, and slowed the induction kinetics of slow inactivation, decreasing the fraction of channels entering this inactivated state. The membrane expression of p.L889V channels was low, and in silico molecular experiments demonstrated profound alterations in the disposition of the pore region of the mutated channels. Despite the mutation producing a marked DNE and reduction in the INa and being located in a critical domain of the channel, its penetrance and expressivity are quite variable among the carriers. Our results reinforce the argument that the incomplete penetrance and phenotypic variability of SCN5A loss-of-function mutations are the result of a combination of multiple factors, making it difficult to predict their expressivity in the carriers despite the combination of clinical, genetic, and functional studies.

Harnessing human genetics and stem cells for precision cardiovascular medicine

Human induced pluripotent stem cell (iPSC) platforms are valuable for biomedical and pharmaceutical research by providing tissue-specific human cells that retain patients' genetic integrity and display disease phenotypes in a dish. Looking forward, combining iPSC phenotyping platforms with genomic and screening technologies will continue to pave new directions for precision medicine, including genetic prediction, visualization, and treatment of heart disease. This review summarizes the recent use of iPSC technology to unpack the influence of genetic variants in cardiovascular pathology. We focus on various state-of-the-art genomic tools for cardiovascular therapies-including the expansion of genetic toolkits for molecular interrogation, in vitro population studies, and function-based drug screening-and their current applications in patient- and genome-edited iPSC platforms that are heralding new avenues for cardiovascular research.

Prognostic Value of Multiplexed Assays of Variant Effect and Automated Patch-clamping for KCNH2-LQTS Risk Stratification

Background

Long QT syndrome (LQTS) is a lethal arrhythmia condition, frequently caused by rare loss-of-function variants in the cardiac potassium channel encoded by KCNH2. Variant-based risk stratification is complicated by heterogenous clinical data, incomplete penetrance, and low-throughput functional data.

Objective

To test the utility of variant-specific features, including high-throughput functional data, to predict cardiac events among KCNH2 variant heterozygotes.

Methods

We quantified cell-surface trafficking of 18,323 variants in KCNH2 and recorded potassium current densities for 506 KCNH2 variants. Next, we deeply phenotyped 1150 KCNH2 missense variant patients, including ECG features, cardiac event history (528 total cardiac events), and mortality. We then assessed variant functional, in silico, structural, and LQTS penetrance data to stratify event-free survival for cardiac events in the study cohort.

Results

Variant-specific current density (HR 0.28 [0.13-0.60]) and estimates of LQTS penetrance incorporating MAVE data (HR 3.16 [1.59-6.27]) were independently predictive of severe cardiac events when controlling for patient-specific features. Risk prediction models incorporating these data significantly improved prediction of 20 year cardiac events (AUC 0.79 [0.75-0.82]) over patient-only covariates (QTc and sex) (AUC 0.73 [0.70-0.77]).

Conclusion

We show that high-throughput functional data, and other variant-specific features, meaningfully contribute to both diagnosis and prognosis of a clinically actionable monogenic disease.

ParSE-seq: A Calibrated Multiplexed Assay to Facilitate the Clinical Classification of Putative Splice-altering Variants

Background

Interpreting the clinical significance of putative splice-altering variants outside 2-base pair canonical splice sites remains difficult without functional studies.

Methods

We developed Parallel Splice Effect Sequencing (ParSE-seq), a multiplexed minigene-based assay, to test variant effects on RNA splicing quantified by high-throughput sequencing. We studied variants in SCN5A, an arrhythmia-associated gene which encodes the major cardiac voltage-gated sodium channel. We used the computational tool SpliceAI to prioritize exonic and intronic candidate splice variants, and ClinVar to select benign and pathogenic control variants. We generated a pool of 284 barcoded minigene plasmids, transfected them into Human Embryonic Kidney (HEK293) cells and induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), sequenced the resulting pools of splicing products, and calibrated the assay to the American College of Medical Genetics and Genomics scheme. Variants were interpreted using the calibrated functional data, and experimental data were compared to SpliceAI predictions. We further studied some splice-altering missense variants by cDNA-based automated patch clamping (APC) in HEK cells and assessed splicing and sodium channel function in CRISPR-edited iPSC-CMs.

Results

ParSE-seq revealed the splicing effect of 224 SCN5A variants in iPSC-CMs and 244 variants in HEK293 cells. The scores between the cell types were highly correlated (R2=0.84). In iPSCs, the assay had concordant scores for 21/22 benign/likely benign and 24/25 pathogenic/likely pathogenic control variants from ClinVar. 43/112 exonic variants and 35/70 intronic variants with determinate scores disrupted splicing. 11 of 42 variants of uncertain significance were reclassified, and 29 of 34 variants with conflicting interpretations were reclassified using the functional data. SpliceAI computational predictions correlated well with experimental data (AUC = 0.96). We identified 20 unique SCN5A missense variants that disrupted splicing, and 2 clinically observed splice-altering missense variants of uncertain significance had normal function when tested with the cDNA-based APC assay. A splice-altering intronic variant detected by ParSE-seq, c.1891-5C>G, also disrupted splicing and sodium current when introduced into iPSC-CMs at the endogenous locus by CRISPR editing.

Conclusions

ParSE-seq is a calibrated, multiplexed, high-throughput assay to facilitate the classification of candidate splice-altering variants.

Functional Characterisation of the Rare SCN5A p.E1225K Variant, Segregating in a Brugada Syndrome Familial Case, in Human Cardiomyocytes from Pluripotent Stem Cells

Brugada syndrome (BrS) is an inherited autosomal dominant cardiac channelopathy. Pathogenic rare mutations in the SCN5A gene, encoding the alpha-subunit of the voltage-dependent cardiac Na⁺ channel protein (Nav1.5), are identified in 20% of BrS patients, affecting the correct function of the channel. To date, even though hundreds of SCN5A variants have been associated with BrS, the underlying pathogenic mechanisms are still unclear in most cases. Therefore, the functional characterization of the SCN5A BrS rare variants still represents a major hurdle and is fundamental to confirming their pathogenic effect. Human cardiomyocytes (CMs) differentiated from pluripotent stem cells (PSCs) have been extensively demonstrated to be reliable platforms for investigating cardiac diseases, being able to recapitulate specific traits of disease, including arrhythmic events and conduction abnormalities. Based on this, in this study, we performed a functional analysis of the BrS familial rare variant NM_198056.2:c.3673G>A (NP_932173.1:p.Glu1225Lys), which has been never functionally characterized before in a cardiac-relevant context, as the human cardiomyocyte. Using a specific lentiviral vector encoding a GFP-tagged SCN5A gene carrying the specific c.3673G>A variant and CMs differentiated from control PSCs (PSC-CMs), we demonstrated an impairment of the mutated Nav1.5, thus suggesting the pathogenicity of the rare BrS detected variant. More broadly, our work supports the application of PSC-CMs for the assessment of the pathogenicity of gene variants, the identification of which is increasing exponentially due to the advances in next-generation sequencing methods and their massive use in genetic testing.

Continuous Bayesian variant interpretation accounts for incomplete penetrance among Mendelian cardiac channelopathies

PURPOSE

The congenital Long QT Syndrome (LQTS) and Brugada Syndrome (BrS) are Mendelian autosomal dominant diseases that frequently precipitate fatal cardiac arrhythmias. Incomplete penetrance is a barrier to clinical management of heterozygotes harboring variants in the major implicated disease genes KCNQ1, KCNH2, and SCN5A. We apply and evaluate a Bayesian penetrance estimation strategy that accounts for this phenomenon.

METHODS

We generated Bayesian penetrance models for KCNQ1-LQT1 and SCN5A-LQT3 using variant-specific features and clinical data from the literature, international arrhythmia genetic centers, and population controls. We analyzed the distribution of posterior penetrance estimates across 4 genotype-phenotype relationships and compared continuous estimates with ClinVar annotations. Posterior estimates were mapped onto protein structure.

RESULTS

Bayesian penetrance estimates of KCNQ1-LQT1 and SCN5A-LQT3 are empirically equivalent to 10 and 5 clinically phenotype heterozygotes, respectively. Posterior penetrance estimates were bimodal for KCNQ1-LQT1 and KCNH2-LQT2, with a higher fraction of missense variants with high penetrance among KCNQ1 variants. There was a wide distribution of variant penetrance estimates among identical ClinVar categories. Structural mapping revealed heterogeneity among "hot spot" regions and featured high penetrance estimates for KCNQ1 variants in contact with calmodulin and the S6 domain.

CONCLUSIONS

Bayesian penetrance estimates provide a continuous framework for variant interpretation.

Atrial Standstill in the Pediatric Population: A Multi-Institution Collaboration

BACKGROUND

Atrial standstill (AS) is a rare condition characterized by absence of electrical activity within the atria. Studies to date have been limited.

OBJECTIVES

The authors sought to describe the clinical characteristics, genetics, and outcomes of patients with AS.

METHODS

This was a retrospective multicenter study of patients <18 years at AS diagnosis, defined as absence of atrial activity documented during an electrophysiology study, device placement, or noninvasive rhythm tracings and confirmed by echocardiogram. Patients with acquired disorders were excluded. Clinical details and genetic variants were recorded and analyzed.

RESULTS

Twenty patients were diagnosed at a median age of 6.6 years (IQR: 2.9-10.8 years). Arrhythmias included 16 (80%) with atrial/supraventricular arrhythmias and 8 (40%) with ventricular tachycardia, including 4 with cardiac arrests. A type 1 Brugada pattern was documented in 4. Pacemakers were implanted in 18 (90%). Although atrial leads were attempted in 15, only 4 achieved pacing at implantation. During a median follow-up of 6.9 years (IQR: 1.2-13.3 years), 7 (35%) had thromboembolic events. Of these, none had atrial pacing, 6 were not on anticoagulation, and 1 was on aspirin. Genetic testing identified SCN5A variants in 13 patients (65%). Analyses suggest SCN5A loss-of-function may be one mechanism driving AS. Ventricular arrhythmias and cardiac arrest were more commonly seen in patients with biallelic SCN5A variants.

CONCLUSIONS

AS may be associated with loss-of-function SCN5A variants. Patients demonstrate atrial and ventricular arrhythmias, and may present challenges during device placement. Patients without the capacity for atrial pacing are at risk for thromboembolic events and warrant anticoagulation.

How Functional Genomics Can Keep Pace With VUS Identification

Over the last two decades, an exponentially expanding number of genetic variants have been identified associated with inherited cardiac conditions. These tremendous gains also present challenges in deciphering the clinical relevance of unclassified variants or variants of uncertain significance (VUS). This review provides an overview of the advancements (and challenges) in functional and computational approaches to characterize variants and help keep pace with VUS identification related to inherited heart diseases.

Estimating the Posttest Probability of Long QT Syndrome Diagnosis for Rare KCNH2 Variants

BACKGROUND

The proliferation of genetic profiling has revealed many associations between genetic variations and disease. However, large-scale phenotyping efforts in largely healthy populations, coupled with DNA sequencing, suggest variants currently annotated as pathogenic are more common in healthy populations than previously thought. In addition, novel and rare variants are frequently observed in genes associated with disease both in healthy individuals and those under suspicion of disease. This raises the question of whether these variants can be useful predictors of disease. To answer this question, we assessed the degree to which the presence of a variant in the cardiac potassium channel gene KCNH2 was diagnostically predictive for the autosomal dominant long QT syndrome.

METHODS

We estimated the probability of a long QT diagnosis given the presence of each KCNH2 variant using Bayesian methods that incorporated variant features such as changes in variant function, protein structure, and in silico predictions. We call this estimate the posttest probability of disease. Our method was applied to over 4000 individuals heterozygous for 871 missense or in-frame insertion/deletion variants in KCNH2 and validated against a separate international cohort of 933 individuals heterozygous for 266 missense or in-frame insertion/deletion variants.

RESULTS

Our method was well-calibrated for the observed fraction of heterozygotes diagnosed with long QT syndrome. Heuristically, we found that the innate diagnostic information one learns about a variant from 3-dimensional variant location, in vitro functional data, and in silico predictors is equivalent to the diagnostic information one learns about that same variant by clinically phenotyping 10 heterozygotes. Most importantly, these data can be obtained in the absence of any clinical observations.

CONCLUSIONS

We show how variant-specific features can inform a prior probability of disease for rare variants even in the absence of clinically phenotyped heterozygotes.

Promise and Peril of Population Genomics for the Development of Genome-First Approaches in Mendelian Cardiovascular Disease

The rich tradition of cardiovascular genomics has placed the field in prime position to extend our knowledge toward a genome-first approach to diagnosis and therapy. Population-scale genomic data has enabled exponential improvements in our ability to adjudicate variant pathogenicity based on allele rarity, and there has been a significant effort to employ these sizeable data in the investigation of rare disease. Certainly, population genomics data has great potential to aid the development of a genome-first approach to Mendelian cardiovascular disease, but its use in the clinical and investigative decision making is limited by the characteristics of the populations studied, and the evolutionary constraints on human Mendelian variation. To truly empower clinicians and patients, the successful implementation of a genome-first approach to rare cardiovascular disease will require the nuanced incorporation of population-based discovery with detailed investigation of rare disease cohorts and prospective variant evaluation.