Brugada syndrome (BrS) is an inherited cardiac condition characterized by a hallmark ECG pattern and an increased risk of sudden cardiac death. Central to the aetiology of BrS, the SCN5A region harbours both common non-coding risk variants and rare coding variants that are causative in approximately 20% of patients. However, rare non-coding genetic variation in this region remains largely unexplored. Here, we used whole-genome sequencing (WGS) of 752 European-ancestry BrS cases and 1,827 ancestry-matched controls to identify BrS-associated rare non-coding genetic variation at the SCN5A locus. Sliding-window and cis -regulatory element (CRE)-based rare-variant aggregate testing implicated three conserved CREs, including a dense aggregation of case singleton variants within a 178 bp enhancer in intron 17 of SCN5A which replicated in an independent BrS cohort. Prioritised BrS-associated rare and low-frequency non-coding variants within these elements were predicted to alter cardiac transcription factor motifs, and altered CRE activity in hiPSC-CM luciferase assays or were associated with BrS-relevant ECG endophenotypes in the UK Biobank. Single-variant analysis across the region identified a Bonferroni-significant five-fold case-enriched low-frequency variant within a known CRE in intron 1 of SCN5A, which replicated, was associated with slower cardiac conduction in the UK Biobank and accounted for part of the BrS GWAS signal at this locus. Structural variant analyses identified a 10.5 kb deletion upstream of SCN5A in a BrS case that encompassed a cardiac CRE and reduced sodium current density in a hiPSC-CM model, as well as a 6 kb BrS-enriched retrotransposon insertion in SCN5A that appeared to underlie part of the GWAS signal in this region. Together, these findings implicate rare and low-frequency non-coding variation at the SCN5A locus in BrS susceptibility and demonstrate the value of targeted WGS analysis of key disease loci.

Importance:Cardiac conduction disorders have traditionally been regarded as a secondary manifestation of underlying structural heart diseases. However, isolated conduction disorders may precede the onset of heart failure (HF) suggesting shared mechanisms. Objective:To evaluate the prevalence and clinical significance of pathogenic/likely pathogenic (P/LP) rare variants in cardiomyopathy genes among individuals with conduction disorders. Design Setting and Participants:Biobank analysis of 192,834 participants with whole genome sequence data from Vanderbilt's BioVU and 353,092 participants from the All of Us Research Program (AoU). Participants with primary conduction disorder (left bundle branch block [LBBB], right bundle branch block [RBBB], high-grade atrioventricular block [AVB]) were identified after excluding secondary causes. Exposures:P/LP variants in cardiomyopathy genes. Main Outcomes and Measures:Primary outcome was P/LP carrier status by age and HF status. Secondary outcomes included incident HF and composite ventricular arrhythmias/sudden cardiac death/mortality (VA/SCD/mortality). Results:Among 16,959 participants with conduction disorders in BioVU and 13,442 in AoU, 432 (2.6%) and 206 (1.5%) were P/LP carriers, respectively. Conduction disorder was independently associated with carrier status (BioVU p<0.001; AoU p=0.005). Carrier probability varied by age at conduction disorder onset and HF status. Among participants with HF at age 30 years, predicted carrier probability for LBBB was 7.5% in BioVU and 20.2% in AoU; for high-grade AVB, 7.7% and 8.5%, respectively, compared with 3.7% and 2.9% among those with HF without conduction disorder. P/LP carrier status among participants with conduction disorders was associated with increased risk of incident HF (BioVU p<0.001; AoU p<0.001) and ventricular arrhythmia/sudden death/mortality (BioVU p<0.001; AoU p<0.001). Carriers also demonstrated increased susceptibility to conduction disorder following HF diagnosis, including more than two-fold higher risk of third-degree AVB (BioVU aOR 2.48, 95% CI 1.85-3.32; AoU aOR 2.26, 95% CI 1.35-3.80). Conclusions:Adults with primary conduction disorders have an increased prevalence of P/LP variants in cardiomyopathy genes, which is most pronounced with diagnoses at early ages of adulthood. Furthermore, there is evidence of an interaction between P/LP carrier status and conduction disorder to increase HF risk and composite cardiovascular outcomes, underscoring the potential role of genetic evaluation in patients with primary conduction disorders to inform long-term outcomes.

Long COVID affects a substantial proportion of the over 778 million individuals infected with SARS-CoV-2, yet predictive models remain limited in scope. While existing efforts, such as the National COVID Cohort Collaborative (N3C), have leveraged electronic health record (EHR) data for risk prediction, accumulating evidence points to additional contributions from social, behavioral, and genetic factors. Using a diverse cohort of SARS-CoV-2-infected individuals (n>17,200) from the NIH All of Us Research Program, we investigated whether integrating EHR data with survey-based and genomic information improves model performance. Our multi-scale approach outperformed EHR-only models original AUROC 0.736 (95% CI: 0.730, 0.741), achieving an AUROC of 0.748 (0.741,0.755). Among the top predictors, active-duty service status, self-reported fatigue, and chr19:4719431:G:A_A were among the most informative survey and genetic features. These findings highlight the importance of incorporating multi-scale data to improve risk stratification and inform personalized interventions for long COVID.

BACKGROUND AND AIMS:Brugada Syndrome (BrS) is an inherited arrhythmia disorder that causes an elevated risk of sudden cardiac death. Approximately 20% of patients with BrS have rare variants in SCN5A, which encodes the cardiac sodium channel NaV1.5. Genetic workup of BrS is often complicated by SCN5A variants of uncertain significance (VUS) and/or incomplete penetrance. This study deployed an SCN5A-BrS functional assay at cohort scale to facilitate the implementation of genetic and precision medicine. METHODS:All 252 missense and in-frame insertion/deletion SCN5A variants from a previously published large cohort of BrS cases (n = 3335 patients) were analysed using a calibrated high-throughput automated patch-clamp (APC) assay. Variant functional Z-scores were assigned evidence levels ranging from BS3_moderate (normal function) to PS3_strong (loss-of-function), as defined by American College of Medical Genetics and Genomics criteria. Functional evidence was combined with population frequency, hotspot, case counts, protein-length changes, and in silico predictions. Odds ratios of BrS case-control enrichment and penetrance for BrS were calculated from variant frequencies in the BrS cohort and in gnomAD. RESULTS:Most variants (146/252) were functionally abnormal (Z ≤ -2), with 100 having severe loss-of-function (Z ≤ -4). Functional evidence enabled the reclassification of 110 of 225 VUS; 104 to likely pathogenic and 6 to likely benign. SCN5A variants with loss-of-function were mainly localized to the transmembrane domains, especially the regions comprising the central pore. SCN5A variant penetrance was proportional to the severity of loss-of-function; variants with Z ≤ -6 had penetrance of 24.5% (15.9%-37.7% CI) and an odds ratio of 501 for BrS. CONCLUSIONS:This cohort-scale APC dataset stratifies SCN5A variants found in BrS patients into normal function 'bystander' variants that have a low risk of BrS and loss-of-function variants that have a high risk for BrS. Functional data can be integrated with other criteria to reclassify a substantial fraction of VUS. The dataset helps clarify the SCN5A-BrS relationship and will improve the diagnosis and clinical management of BrS probands and their families.

The Bruton’s tyrosine kinase (BTK) inhibitor ibrutinib has revolutionized treatment for B-cell malignancies but increases the incidence of atrial fibrillation (AF) compared to conventional chemotherapy. The downstream signaling pathways through which ibrutinib leads to AF are unknown and may represent a novel molecular mechanism for AF. To identify kinase signaling pathways that promote atrial fibrillation during ibrutinib therapy. Studies were performed in human atrial-specific cardiomyocytes derived from population control induced pluripotent stem cells (hiPSC-aCMs). Electrophysiologic measurements, including extracellular field potentials (EFPs), were conducted with the Nanion CardioExcyte96 system. Human phospho-kinase arrays determined the relative phosphorylation of 37 kinases in hiPSC-aCMs treated with either ibrutinib or vehicle control. Extracellular field potentials demonstrated a marked increase in spontaneous beat-to-beat variability, an in vitro correlate of arrhythmogenic behavior, with exposure to ibrutinib but not to second or third-generation BTK inhibitors, which are less associated with AF. Treatment with ibrutinib increased phosphorylation of multiple kinases (Src, Erk1/2, CREB) in the Src-Erk1/2 pathway; the most significant increase was with Erk1/2 phosphorylation (threefold). Pre-treatment of hiPSC-aCMs with the Erk1/2 inhibitors ulixertinib and SCH772984 inhibited the EFP arrhythmogenic signal seen with ibrutinib. In hiPSC-aCMs, ibrutinib treatment leads to increased arrhythmogenic behavior via the Src-Erk1/2 phosphorylation pathway. The inhibition of Erk1/2 or its downstream targets may represent novel pathways in the development of atrial fibrillation, providing new targets for therapeutic development.

BACKGROUND:An estimated 1 in 500 people lives with hypertrophic cardiomyopathy (HCM), a disease for which genetic diagnosis can identify family members at risk and increasingly guide therapy. Variants in the MYBPC3 gene, which encodes cardiac myosin-binding protein C (cMyBP-C), account for a significant proportion of HCM cases. However, many of these are classified as variants of uncertain significance, complicating clinical decision-making. Scalable methods for variant interpretation in disease-specific cell types are crucial for understanding variant impact and uncovering disease mechanisms. METHODS:We developed a scaled multidimensional mapping strategy to evaluate the functional impact of variants across a critical domain of cMyBP-C. We incorporate saturation base editing at the native MYBPC3 locus, a long-read RNA sequencing-enabled assay of variant splice effects, and measurements of HCM-relevant phenotypes, including cMyBP-C abundance, hypertrophic signaling, and ubiquitin-proteasome function in human induced pluripotent stem cell-derived cardiomyocytes. RESULTS:Our multidimensional mapping strategy enabled high-resolution functional analysis of MYBPC3 variants in induced pluripotent stem cell-derived cardiomyocytes. Our massively parallel splicing assay identified novel splice-disrupting variants. Targeted transient base editing generated a comprehensive variant library at the native locus, capturing diverse variant effects on cellular HCM-relevant phenotypes. Integration of functional assays revealed that decreased cMyBP-C abundance is a key driver of HCM-related phenotypes. In parallel, downregulation of protein degradation was observed to correlate with MYBPC3 loss of function, and novel potential disease mechanisms were identified for missense variants near a critical binding domain. Bayesian estimates of variant effects enable the reclassification of clinical variants. CONCLUSIONS:This work provides a platform for extending genome engineering in induced pluripotent stem cells to multiplexed assays of variant effects across diverse disease-relevant cellular phenotypes, enhancing our understanding of variant pathogenicity and uncovering novel biological mechanisms that could inform therapeutic strategies.

ABSTRACT Background Atrial Fibrillation (AF) is a common and clinically heterogeneous arrythmia. Machine learning (ML) algorithms can define data-driven disease subtypes in an unbiased fashion, but whether the AF subgroups defined in this way align with underlying mechanisms, such as high polygenic liability to AF or inflammation, and associate with clinical outcomes is unclear. Methods We identified individuals with AF in a large biobank linked to electronic health records (EHR) and genome-wide genotyping. The phenotypic architecture in the AF cohort was defined using principal component analysis of 35 expertly curated and uncorrelated clinical features. We applied an unsupervised co-clustering machine learning algorithm to the 35 features to identify distinct phenotypic AF clusters. The clinical inflammatory status of the clusters was defined using measured biomarkers (CRP, ESR, WBC, Neutrophil %, Platelet count, RDW) within 6 months of first AF mention in the EHR. Polygenic risk scores (PRS) for AF and cytokine levels were used to assess genetic liability of clusters to AF and inflammation, respectively. Clinical outcomes were collected from EHR up to the last medical contact. Results The analysis included 23,271 subjects with AF, of which 6,023 had available genome-wide genotyping. The machine learning algorithm identified 3 phenotypic clusters that were distinguished by increasing prevalence of comorbidities, particularly renal dysfunction, and coronary artery disease. Polygenic liability to AF across clusters was highest in the low comorbidity cluster. Clinically measured inflammatory biomarkers were highest in the high comorbid cluster, while there was no difference between groups in genetically predicted levels of inflammatory biomarkers. Subgroup assignment was associated with multiple clinical outcomes including mortality, stroke, bleeding, and use of cardiac implantable electronic devices after AF diagnosis. Conclusion Patient subgroups identified by unsupervised clustering were distinguished by comorbidity burden and associated with risk of clinically important outcomes. Polygenic liability to AF across clusters was greatest in the low comorbidity subgroup. Clinical inflammation, as reflected by measured biomarkers, was lowest in the subgroup with lowest comorbidities. However, there were no differences in genetically predicted levels of inflammatory biomarkers, suggesting associations between AF and inflammation is driven by acquired comorbidities rather than genetic predisposition.

The Electronic Medical Records and Genomics (eMERGE) Network developed and implemented a genome-informed risk assessment (GIRA) to communicate genomic (polygenic risk scores [PRSs], integrated risk scores [IRSs], and monogenic results), clinical, and family history-based risk for 11 chronic diseases and provide recommended healthcare recommendations. GIRA reports have now been returned to 23,840 participants and their providers in a large prospective cohort study. We present here the study design and analysis framework for assessing the attributable impact of GIRA return. Pre-specified outcomes include (1) provider/participant adoption of recommended healthcare actions, (2) new diagnosis of disease, (3) treatment initiation/intensification, and (4) clinical outcomes (surrogate markers or clinical events). We assess outcomes in high risk vs. not-high-risk participants, adjusting for covariates. We evaluate the effect of PRS/IRS at pre-established high-risk thresholds using regression discontinuity (RD), a quasi-experimental method that mimics randomization near a cutoff, enabling estimation of causal effects and controlling for unobserved confounders. Monogenic and family history-based risk stratification are analyzed using logistic regression. With 23,840 participants and 12 months of follow-up, the study is powered to detect differences of 2%-11% with 80% power (α = 0.05 in the adoption outcome). Longer follow-up will be required to enable assessment of new disease diagnosis, treatment changes, and clinical outcomes. Through innovative RD analyses and defined outcomes and comparison groups, this study will provide new insights into the real-world clinical impact of genomic risk assessment, address critical evidence gaps, advance understanding of genomic medicine outcomes, and inform future research.

BACKGROUND:Individuals of African ancestry are underrepresented in genetic studies, contributing to disproportionately higher rates of variants of uncertain significance (VUS) and fewer actionable results in genetic testing for cardiomyopathies and arrhythmias. We aimed to determine whether ancestry-enriched VUS confer measurable cardiovascular risk among individuals of African ancestry. METHODS:We identified VUS enriched in individuals of African ancestry in 18 cardiomyopathy and arrhythmia genes. We defined enriched as allele frequency in gnomAD ≥2-fold higher than in European (non-Finnish) individuals, and we confined the analysis to VUS with allele frequency >0.05% in individuals of African ancestry. Associations with cardiovascular phenotypes were assessed in 96 897 individuals of African ancestry from the All of Us (n=65 481) and BioVU (n=31 416) biobanks using fixed-effects meta-analysis. Analyses were stratified by heart failure (HF) status and conventional cardiovascular risk factors. RESULTS:We identified 82 ancestry-enriched VUS. Exploratory analysis in All of Us identified 10 variants associated with composite cardiovascular outcome, 4 of which were associated with individual cardiovascular phenotypes in pooled meta-analysis across both cohorts. PKP2 p.Val558Ile was associated with a 4-fold increased risk of ventricular arrhythmias or sudden cardiac death (adjusted odds ratio [aOR], 4.02 [95% CI, 1.85-8.71]; P=0.004). ELAC2 p.Ile396Val was associated with HF (aOR, 1.67 [95% CI, 1.17-2.39]; P=0.02) and atrial arrhythmias (aOR, 1.88 [95% CI, 1.27-2.78]; P=0.02). FLNC p.Gly11Ser and PKP2 p.Val842Ile were associated with HF (aOR, 1.96 [95% CI, 1.24-3.10]; P=0.02 and aOR, 1.99 [95% CI, 1.16-3.41]; P=0.039). The presence of cardiovascular risk factors was associated with earlier onset of HF (adjusted hazard ratio, 1.71 [95% CI, 1.25-2.33]; P=0.0006) and atrial arrhythmias (adjusted hazard ratio, 1.17 [95% CI, 1.06-1.29]; P=0.0019) in pooled variant carriers. PKP2 p.Val558Ile, SCN5A p.Gln1832Glu, and FLNC p.Gly11Ser demonstrated increased arrhythmia burden specifically in participants with HF. Using American College of Medical Genetics and Genomics guidelines, PKP2 p.Val558Ile met criteria for likely pathogenic classification, potentially affecting an estimated 24 000 Black adults in the United States. CONCLUSIONS:Large-scale biobank analysis identified variants classified as VUS that conferred increased risk of cardiomyopathy and arrhythmia in individuals with African ancestry. The risk associated with these variants was increased in the presence of cardiovascular risk factors and HF.

Genetic testing is now recommended for select patients with early-onset atrial fibrillation (AF). Hemochromatosis is an autosomal recessive syndrome that occurs in patients who carry two pathogenic or likely-pathogenic (P/LP) variants in HFE. HFE is included on some genetic testing panels used for patients with AF. Hemochromatosis causes cardiomyopathy due to iron overload in the ventricle; however, it is unknown whether AF can be an early manifestation that is identified by genetic testing. A total of 347 patients were referred to a dedicated AF precision medicine clinic. The clinical diagnostic evaluation included an H&P, 12-lead ECG, ambulatory ECG monitoring, and cardiac imaging (cardiac MRI and/or TTE). Genetic testing was performed using CLIA-approved laboratories: Labcorp/Invitae, GeneDx, or Vanderbilt University Medical Center. HFE was included on the cardiomyopathy panel used by 2 of the 3 laboratories. HFE was tested in 165 participants (median age 46 years [IQR 35-55], 115 [70%] male, 149 [90%] White). Six participants (4%) had two pathogenic variants in HFE. All of them were C282Y/H63D compound heterozygotes. Forty-one participants (25%) were heterozygous carriers of one pathogenic HFE variant. Among the 6 participants with 2 pathogenic HFE variants, the median ferritin level was 346 mcg/L [IQR 262, 496] (normal <300 mcg/L males, <200 mcg/L females). Three participants (50%) met laboratory criteria for iron overload. One individual had isolated ferritin elevation with normal transferrin saturation. All 6 underwent cardiac MRI as part of the genetic evaluation for early onset AF, and there was no evidence of cardiac siderosis based on cardiac T1 mapping median 990 ms [IQR 968-1024] (normal 960-1030 ms). Dedicated sequences to evaluate for iron overload demonstrated short hepatic T2* in one individual, indicating presence of hepatic iron overload (9 ms, normal >11.4 ms; liver iron concentration 3.4 mg/g, normal <2 mg/g). Three out of 6 participants were referred for a hematology evaluation and 2 out of 6 were started on therapeutic phlebotomy. Genetic testing can identify patients with early-onset AF who are genetically susceptible to hemochromatosis, have evidence of iron overload, and receive early intervention with therapeutic phlebotomy. These results suggest HFE should be sequenced as part of genetic testing for early-onset AF, but larger sample sizes are needed to confirm these results.

Entrectinib is a tropomyosin receptor kinase (TrK) inhibitor currently approved for the treatment of ROS1-positive non-small cell lung cancer (NSCLC) and neurotrophic tyrosine receptor kinase (NTRK) gene fusion-positive solid tumors. Two case reports of ventricular tachycardia and a Brugada ECG pattern following entrectinib treatment have been published, and we observed a third case in our clinical practice. Genetic testing on the patient showed no variants in SCN5A. To determine if entrectinib treatment of human cardiomyocytes results in alterations in sodium currents, which may lead to Brugada phenocopy and ventricular tachycardia. Studies were performed in human ventricular cardiomyocytes (hiPSC-vCMs) derived from population-control induced pluripotent stem cells. hiPSC-vCMs were treated with entrectinib (1 µM) for either a brief (15 min) or prolonged exposure (48 h) prior to experimental analysis. Treatment of hiPSC-vCMs with entrectinib (1 µM) for 48 h resulted in a significant decrease in sodium currents during channel activation and inactivation. Treatment with entrectinib for 15 min did not significantly change sodium currents. Western blot analysis revealed no changes in NaV1.5 protein expression after 48 h of entrectinib treatment. Prolonged treatment with entrectinib decreased sodium currents in hiPSC-vCMs, which may lead to Brugada phenocopy and ventricular arrhythmias. Brief treatment with entrectinib did not affect sodium currents, and no changes in NaV1.5 protein expression were observed following prolonged treatment, indicating that inhibition of sodium currents likely results through a phospho-signaling mechanism rather than by direct channel inhibition.

Rare coding genetic variants may exert large effects on risk of common disease, yet their contribution to disease architecture and their utility in gene prioritization remain limited by inadequate sample sizes. Here, we performed a massive-scale rare variant association study (RVAS), analyzing over 1.1 million sequenced participants among which 130,000 had atrial fibrillation (AF). Through a multi-mask burden testing approach, we identified 15 genes significantly associated with AF through rare large-effect variation. Integrative analyses revealed strong convergence between genes implicated by rare and common variation, and highlighted instances where RVAS data may aid in GWAS prioritization. Nevertheless, several RVAS genes were not among GWAS loci ( FAM189A2 , ACTC1 , FNIP1 , FBN1 ), or were not nominated through contemporary GWAS prioritization ( KDM5B , ZFP36L2 ). Finally, we observed that ultra-rare protein-disrupting variants - concentrated in a small number of large-effect size genes - explained at least 2% of AF susceptibility across European and African ancestry groups. These findings refine the genetic architecture of AF, while highlighting the value and cost of RVAS for genomic discovery in common disease.