Benchmarking computational variant effect predictors by their ability to infer human traits.

BACKGROUND: Computational variant effect predictors offer a scalable and increasingly reliable means of interpreting human genetic variation, but concerns of circularity and bias have limited previous methods for evaluating and comparing predictors. Population-level cohorts of genotyped and phenotyped participants that have not been used in predictor training can facilitate an unbiased benchmarking of available methods. Using a curated set of human gene-trait associations with a reported rare-variant burden association, we evaluate the correlations of 24 computational variant effect predictors with associated human traits in the UK Biobank and All of Us cohorts. RESULTS: AlphaMissense outperformed all other predictors in inferring human traits based on rare missense variants in UK Biobank and All of Us participants. The overall rankings of computational variant effect predictors in these two cohorts showed a significant positive correlation. CONCLUSION: We describe a method to assess computational variant effect predictors that sidesteps the limitations of previous evaluations. This approach is generalizable to future predictors and could continue to inform predictor choice for personal and clinical genetics.

Multifocal Ectopic Purkinje Premature Contractions due to neutralization of an SCN5A negative charge: structural insights into the gating pore hypothesis.

Background: We identified a novel SCN5A variant, E171Q, in a neonate with very frequent ectopy and reduced ejection fraction which normalized after arrhythmia suppression by flecainide. This clinical picture is consistent with multifocal ectopic Purkinje-related premature contractions (MEPPC). Most previous reports of MEPPC have implicated SCN5A variants such as R222Q that neutralize positive charges in the S4 voltage sensor helix of the channel protein NaV1.5 and generate a gating pore current. Methods and Results: E171 is a highly conserved negatively-charged residue located in the S2 transmembrane helix of NaV1.5 domain I. E171 is a key component of the Gating Charge Transfer Center, a region thought to be critical for normal movement of the S4 voltage sensor helix. We used heterologous expression, CRISPR-edited induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), and molecular dynamics simulations to demonstrate that E171Q generates a gating pore current, which was suppressed by a low concentration of flecainide (IC50 = 0.71±0.07 µM). R222Q shifts voltage dependence of activation and inactivation in a negative direction but we observed positive shifts with E171Q. E171Q iPSC-CMs demonstrated abnormal spontaneous activity and prolonged action potentials. Molecular dynamics simulations revealed that both R222Q and E171Q proteins generate a water-filled permeation pathway that underlies generation of the gating pore current. Conclusion: Previously identified MEPPC-associated variants that create gating pore currents are located in positively-charged residues in the S4 voltage sensor and generate negative shifts in the voltage dependence of activation and inactivation. We demonstrate that neutralizing a negatively charged S2 helix residue in the Gating Charge Transfer Center generates positive shifts but also create a gating pore pathway. These findings implicate the gating pore pathway as the primary functional and structural determinant of MEPPC and widen the spectrum of variants that are associated with gating pore-related disease in voltage-gated ion channels.

Detection of distant relatedness in biobanks for identification of undiagnosed carriers of a Mendelian disease variant: application to Long QT Syndrome.

Rare genetic diseases are typically studied in referral populations, resulting in underdiagnosis and biased assessment of penetrance and phenotype. To address this, we developed a generalizable method of genotype inference based on distant relatedness and deployed this to identify undiagnosed Type 5 Long QT Syndrome (LQT5) rare variant carriers in a non-referral population. We identified 9 LQT5 families referred to a single specialty clinic, each carrying p.Asp76Asn, the most common LQT5 variant. We uncovered recent common ancestry and a single shared haplotype among probands. Application to a non-referral population of 69,819 BioVU biobank subjects identified 22 additional subjects sharing this haplotype, subsequently confirmed to carry p.Asp76Asn. Referral and non-referral carriers had prolonged QTc compared to controls, and, among carriers, QTc polygenic score additively associated with QTc prolongation. Thus, our novel analysis of shared chromosomal segments identified undiagnosed cases of genetic disease and refined the understanding of LQT5 penetrance and phenotype.

Detection of distant familial relatedness in biobanks for identification of undiagnosed carriers of a Mendelian disease variant: application to Long QT syndrome.

Importance: The diagnosis and study of rare genetic disease is often limited to referral populations, leading to underdiagnosis and a biased assessment of penetrance and phenotype. Objective: To develop a generalizable method of genotype inference based on distant relatedness and to deploy this to identify undiagnosed Type 5 Long QT Syndrome (LQT5) rare variant carriers in a non-referral population. Participants: We identified 9 LQT5 probands and 3 first-degree relatives referred to a single Genetic Arrhythmia clinic, each carrying D76N (p.Asp76Asn), the most common variant implicated in LQT5. The non-referral population consisted of 69,879 ancestry-matched subjects in BioVU, a large biobank that links electronic health records to dense array data. Participants were enrolled from 2007-2022. Data analysis was performed in 2022. Exposures: We developed and applied a novel approach to genotype inference (Distant Relatedness for Identification and Variant Evaluation, or DRIVE) to identify shared, identical-by-descent (IBD) large chromosomal segments in array data. Main Outcomes and Measures: We sought to establish genetic relatedness among the probands and to use genomic segments underlying D76N to identify other potential carriers in BioVU. We then further studied the role of D76N in LQT5 pathogenesis. Results: Genetic reconstruction of pedigrees and distant relatedness detection among clinic probands using DRIVE revealed shared recent common ancestry and identified a single long shared haplotype. Interrogation of the non-referral population in BioVU identified a further 23 subjects sharing this haplotype, and sequencing confirmed D76N carrier status in 22, all previously undiagnosed with LQT5. The QTc was prolonged in D76N carriers compared to BioVU controls, with 40% penetrance of QTc ≥ 480 msec. Among D76N carriers, a QTc polygenic score was additively associated with QTc prolongation. Conclusions and Relevance: Detection of IBD shared chromosomal segments around D76N enabled identification of distantly related and previously undiagnosed rare-variant carriers, demonstrated the contribution of polygenic risk to monogenic disease penetrance, and further established LQT5 as a primary arrhythmia disorder. Analysis of shared chromosomal regions spanning disease-causing mutations can identify undiagnosed cases of genetic diseases.

Left atrial appendage dimension predicts elevated brain natriuretic peptide in nonvalvular atrial fibrillation.

INTRODUCTION: BNP elevation in patients with AF is observed in the absence of heart failure; however, prior mechanistic studies have not included direct left atrial pressure measurements. This study sought to understand how emptying function of the left atrial appendage (LAA) and LAA dimension contributes to brain-natriuretic peptide elevations (BNP) in atrial fibrillation (AF) accounting for left atrial pressure (LAP). METHODS: 132 patients referredfor left atrial appendage occlusion (LAAO) were prospectively enrolled in this study. BNP levels and LAP were measured just before LAAO. Statistical analysis considered BNP, rhythm at time of procedure, LAP, LAA morphology, LAA size (ostial diameter, depth, volume), LAA emptying velocity, CHADS2-VASc score, body mass index (BMI), left ventricular ejection fraction (LVEF), estimated glomerular filtration rate (eGFR), and obstructive sleep apnea (OSA) diagnosis as covariates. RESULTS: Bivariate statistical analysis demonstrated positive associations with age, LAA ostial diameter, depth, and volume, LAP, AF status at time of measurement, OSA, and CHADS2-VASc score. BNP was negatively associated with LVEF, eGFR, LAA emptying velocity and BMI. With multivariate logistic regression including LAP as covariate, significant relationships between BNP and AF/AFL(OR 1.99 [1.03, 3.85]), LAP (OR 1.13 [1.06, 1.20]), LAA diameter (OR 1.14 [1.03, 1.27]), LAA depth (OR 1.14 [1.07, 1.22]), and LAA emptying velocity (OR 0.97 [0.96,0.99]) were observed; however, no significant associations were seen with LAA morphology or CHADS2-VASc score. CONCLUSIONS: BNP elevations in AF are associated with LAA size and function, but not CHADS2-VASc score or appendage morphology after accounting for changes in LAP.

Arrhythmias as Presentation of Genetic Cardiomyopathy.

There is increasing evidence regarding the prevalence of genetic cardiomyopathies, for which arrhythmias may be the first presentation. Ventricular and atrial arrhythmias presenting in the absence of known myocardial disease are often labelled as idiopathic, or lone. While ventricular arrhythmias are well-recognized as presentation for arrhythmogenic cardiomyopathy in the right ventricle, the scope of arrhythmogenic cardiomyopathy has broadened to include those with dominant left ventricular involvement, usually with a phenotype of dilated cardiomyopathy. In addition, careful evaluation for genetic cardiomyopathy is also warranted for patients presenting with frequent premature ventricular contractions, conduction system disease, and early onset atrial fibrillation, in which most detected genes are in the cardiomyopathy panels. Sudden death can occur early in the course of these genetic cardiomyopathies, for which risk is not adequately tracked by left ventricular ejection fraction. Only a few of the cardiomyopathy genotypes implicated in early sudden death are recognized in current indications for implantable cardioverter defibrillators which otherwise rely upon a left ventricular ejection fraction ≤0.35 in dilated cardiomyopathy. The genetic diagnoses impact other aspects of clinical management such as exercise prescription and pharmacological therapy of arrhythmias, and new therapies are coming into clinical investigation for specific genetic cardiomyopathies. The expansion of available genetic information and implications raises new challenges for genetic counseling, particularly with the family member who has no evidence of a cardiomyopathy phenotype and may face a potentially negative impact of a genetic diagnosis. Discussions of risk for both probands and relatives need to be tailored to their numeric literacy during shared decision-making. For patients presenting with arrhythmias or cardiomyopathy, extension of genetic testing and its implications will enable cascade screening, intervention to change the trajectory for specific genotype-phenotype profiles, and enable further development and evaluation of emerging targeted therapies.