Association Between Family History and Early-Onset Atrial Flutter Across Racial and Ethnic Groups.

BACKGROUND: Genetic and familial contributions to early-onset atrial fibrillation are described primarily in individuals of European ancestry. However, the role of racial and familial contributions in the pathogenesis of early-onset atrial flutter (EOAFL) is unclear. METHODS AND RESULTS: In this cross-sectional study, participants were enrolled prospectively from 2015 to 2021 in multiple academic centers with a diagnosis of atrial flutter (AFL) confirmed by ECG. EOAFL was defined as a diagnosis of AFL before age 66 years with no concomitant or previous diagnosis of atrial tachyarrhythmias. Family history was adjudicated through baseline questionnaires and direct family interviews about the diagnosis of atrial tachyarrhythmias, stroke, and cardiomyopathy. The primary exposure was a positive family history in first-degree relatives, and the primary outcome was the odds of EOAFL versus late-onset AFL. A total of 909 patients were enrolled. Participants with a positive family history of atrial tachyarrhythmias were younger, less likely to be of Black race, and more likely to have EOAFL. The adjusted odds ratio (OR) for EOAFL in those with a positive family history was 1.8 (95% CI, 1.1-3.0). There was an increased odds of EOAFL in those of Black race (OR, 2.1 [95% CI, 1.4-3.2]), alcohol use (OR, 1.6 [95% CI, 1.0-2.6]), and obstructive sleep apnea (OR, 1.9 [95% CI, 1.0-3.4]). Use of cardioselective ß blockers or calcium channel blockers before the diagnosis of AFL were associated with a lower odds of EOAFL (OR, 0.5 [95% CI, 0.2-0.9]). CONCLUSIONS: These findings suggest a potentially hereditary predisposition to EOAFL across race and ethnicity, warranting further study of the genetic contributions to AFL.

Genetic Susceptibility to Arrhythmia Phenotypes in a Middle Eastern Cohort of 14,259 Whole-Genome Sequenced Individuals.

Background: The current study explores the genetic underpinnings of cardiac arrhythmia phenotypes within Middle Eastern populations, which are under-represented in genomic medicine research. Methods: Whole-genome sequencing data from 14,259 individuals from the Qatar Biobank were used and contained 47.8% of Arab ancestry, 18.4% of South Asian ancestry, and 4.6% of African ancestry. The frequency of rare functional variants within a set of 410 candidate genes for cardiac arrhythmias was assessed. Polygenic risk score (PRS) performance for atrial fibrillation (AF) prediction was evaluated. Results: This study identified 1196 rare functional variants, including 162 previously linked to arrhythmia phenotypes, with varying frequencies across Arab, South Asian, and African ancestries. Of these, 137 variants met the pathogenic or likely pathogenic (P/LP) criteria according to ACMG guidelines. Of these, 91 were in ACMG actionable genes and were present in 1030 individuals (~7%). Ten P/LP variants showed significant associations with atrial fibrillation p < 2.4 × 10-10. Five out of ten existing PRSs were significantly associated with AF (e.g., PGS000727, p = 0.03, OR = 1.43 [1.03, 1.97]). Conclusions: Our study is the largest to study the genetic predisposition to arrhythmia phenotypes in the Middle East using whole-genome sequence data. It underscores the importance of including diverse populations in genomic investigations to elucidate the genetic landscape of cardiac arrhythmias and mitigate health disparities in genomic medicine.

Engineered cocultures of iPSC-derived atrial cardiomyocytes and atrial fibroblasts for modeling atrial fibrillation.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia treatable with antiarrhythmic drugs; however, patient responses remain highly variable. Human induced pluripotent stem cell-derived atrial cardiomyocytes (iPSC-aCMs) are useful for discovering precision therapeutics, but current platforms yield phenotypically immature cells and are not easily scalable for high-throughput screening. Here, primary adult atrial, but not ventricular, fibroblasts induced greater functional iPSC-aCM maturation, partly through connexin-40 and ephrin-B1 signaling. We developed a protein patterning process within multiwell plates to engineer patterned iPSC-aCM and atrial fibroblast coculture (PC) that significantly enhanced iPSC-aCM structural, electrical, contractile, and metabolic maturation for 6+ weeks compared to conventional mono-/coculture. PC displayed greater sensitivity for detecting drug efficacy than monoculture and enabled the modeling and pharmacological or gene editing treatment of an AF-like electrophysiological phenotype due to a mutated sodium channel. Overall, PC is useful for elucidating cell signaling in the atria, drug screening, and modeling AF.

Correlations between Resting Electrocardiogram Findings and Disease Profiles: Insights from the Qatar Biobank Cohort.

BACKGROUND: Resting electrocardiogram (ECG) is a valuable non-invasive diagnostic tool used in clinical medicine to assess the electrical activity of the heart while the patient is resting. Abnormalities in ECG may be associated with clinical biomarkers and can predict early stages of diseases. In this study, we evaluated the association between ECG traits, clinical biomarkers, and diseases and developed risk scores to predict the risk of developing coronary artery disease (CAD) in the Qatar Biobank. METHODS: This study used 12-lead ECG data from 13,827 participants. The ECG traits used for association analysis were RR, PR, QRS, QTc, PW, and JT. Association analysis using regression models was conducted between ECG variables and serum electrolytes, sugars, lipids, blood pressure (BP), blood and inflammatory biomarkers, and diseases (e.g., type 2 diabetes, CAD, and stroke). ECG-based and clinical risk scores were developed, and their performance was assessed to predict CAD. Classical regression and machine-learning models were used for risk score development. RESULTS: Significant associations were observed with ECG traits. RR showed the largest number of associations: e.g., positive associations with bicarbonate, chloride, HDL-C, and monocytes, and negative associations with glucose, insulin, neutrophil, calcium, and risk of T2D. QRS was positively associated with phosphorus, bicarbonate, and risk of CAD. Elevated QTc was observed in CAD patients, whereas decreased QTc was correlated with decreased levels of calcium and potassium. Risk scores developed using regression models were outperformed by machine-learning models. The area under the receiver operating curve reached 0.84 using a machine-learning model that contains ECG traits, sugars, lipids, serum electrolytes, and cardiovascular disease risk factors. The odds ratio for the top decile of CAD risk score compared to the remaining deciles was 13.99. CONCLUSIONS: ECG abnormalities were associated with serum electrolytes, sugars, lipids, and blood and inflammatory biomarkers. These abnormalities were also observed in T2D and CAD patients. Risk scores showed great predictive performance in predicting CAD.

PPP1R12C Promotes Atrial Hypocontractility in Atrial Fibrillation.

BACKGROUND: Atrial fibrillation (AF)-the most common sustained cardiac arrhythmia-increases thromboembolic stroke risk 5-fold. Although atrial hypocontractility contributes to stroke risk in AF, the molecular mechanisms reducing myofilament contractile function remain unknown. We tested the hypothesis that increased expression of PPP1R12C (protein phosphatase 1 regulatory subunit 12C)-the PP1 (protein phosphatase 1) regulatory subunit targeting MLC2a (atrial myosin light chain 2)-causes hypophosphorylation of MLC2a and results in atrial hypocontractility. METHODS: Right atrial appendage tissues were isolated from human patients with AF versus sinus rhythm controls. Western blots, coimmunoprecipitation, and phosphorylation studies were performed to examine how the PP1c (PP1 catalytic subunit)-PPP1R12C interaction causes MLC2a dephosphorylation. In vitro studies of pharmacological MRCK (myotonic dystrophy kinase-related Cdc42-binding kinase) inhibitor (BDP5290) in atrial HL-1 cells were performed to evaluate PP1 holoenzyme activity on MLC2a. Cardiac-specific lentiviral PPP1R12C overexpression was performed in mice to evaluate atrial remodeling with atrial cell shortening assays, echocardiography, and AF inducibility with electrophysiology studies. RESULTS: In human patients with AF, PPP1R12C expression was increased 2-fold versus sinus rhythm controls (P=2.0×10-2; n=12 and 12 in each group) with >40% reduction in MLC2a phosphorylation (P=1.4×10-6; n=12 and 12 in each group). PPP1R12C-PP1c binding and PPP1R12C-MLC2a binding were significantly increased in AF (P=2.9×10-2 and 6.7×10-3, respectively; n=8 and 8 in each group). In vitro studies utilizing drug BDP5290, which inhibits T560-PPP1R12C phosphorylation, demonstrated increased PPP1R12C binding with both PP1c and MLC2a and dephosphorylation of MLC2a. Mice treated with lentiviral PPP1R12C vector demonstrated a 150% increase in left atrial size versus controls (P=5.0×10-6; n=12, 8, and 12), with reduced atrial strain and atrial ejection fraction. Pacing-induced AF in mice treated with lentiviral PPP1R12C vector was significantly higher than in controls (P=1.8×10-2 and 4.1×10-2, respectively; n=6, 6, and 5). CONCLUSIONS: Patients with AF exhibit increased levels of PPP1R12C protein compared with controls. PPP1R12C overexpression in mice increases PP1c targeting to MLC2a and causes MLC2a dephosphorylation, which reduces atrial contractility and increases AF inducibility. These findings suggest that PP1 regulation of sarcomere function at MLC2a is a key determinant of atrial contractility in AF.

Predicted Deleterious Variants in Cardiomyopathy Genes Prognosticate Mortality and Composite Outcomes in UK Biobank.

BACKGROUND: Inherited cardiomyopathies present with broad variation of phenotype. Data are limited regarding genetic screening strategies and outcomes associated with predicted deleterious variants in cardiomyopathy-associated genes in the general population. OBJECTIVES: The authors aimed to determine the risk of mortality and composite cardiomyopathy-related outcomes associated with predicted deleterious variants in cardiomyopathy-associated genes in the UK Biobank. METHODS: Using whole exome sequencing data, variants in dilated, hypertrophic, and arrhythmogenic right ventricular cardiomyopathy-associated genes with at least moderate evidence of disease causality according to ClinGen Expert Panel curations were annotated using REVEL (≥0.65) and ANNOVAR (predicted loss-of-function) considering gene-disease mechanisms. Genotype-positive and genotype-negative groups were compared using time-to-event analyses for the primary (all-cause mortality) and secondary outcomes (diagnosis of cardiomyopathy; composite outcome of diagnosis of cardiomyopathy, heart failure, arrhythmia, stroke, and death). RESULTS: Among 200,619 participants (age at recruitment 56.46 ± 8.1 years), 5,292 (2.64%) were found to host ≥1 predicted deleterious variants in cardiomyopathy-associated genes (CMP-G+). After adjusting for age and sex, CMP-G+ individuals had higher risk for all-cause mortality (HR: 1.13 [95% CI: 1.01-1.25]; P = 0.027), increased risk for being diagnosed with cardiomyopathy later in life (HR: 5.75 [95% CI: 4.58-7.23]; P < 0.0001), and elevated risk for composite outcome (HR: 1.29 [95% CI: 1.20-1.39]; P < 0.0001) than CMP-G- individuals. The higher risk for being diagnosed with cardiomyopathy and composite outcomes in the genotype-positive subjects remained consistent across all cardiomyopathy subgroups. CONCLUSIONS: Adults with predicted deleterious variants in cardiomyopathy-associated genes exhibited a slightly higher risk of mortality and a significantly increased risk of developing cardiomyopathy, and cardiomyopathy-related composite outcomes, in comparison with genotype-negative controls.

Sample size determination for adaptive crossover trial in detecting gene-drug interactions.

Parallel design and crossover design are two of the most frequently used designs for studying drug-gene interactions. Due to the concerns of statistical power and ethics, it is often more prudent to use the crossover design while allowing the patients to have choices of not switching the treatment if the first stage treatment is effective. This complicates the calculation of the required sample size to achieve pre-specified statistical power. We propose a method to determine the required sample size with a closed-form formula. The proposed approach is applied to determine the sample size of an adaptive crossover trial in studying gene-drug interaction in treating atrial fibrillation, the most common cardiac arrhythmia in clinical practice. Our simulation study confirms the power achieved by the sample size determined using the proposed approach. Issues related to the adaptive crossover trial are also discussed and practical guidelines are provided.

Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants.

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-sequencing data in GTEx V8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased whole genome sequencing data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

Myosin Light Chain Dephosphorylation by PPP1R12C Promotes Atrial Hypocontractility in Atrial Fibrillation.

Background: Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, increases thromboembolic stroke risk five-fold. Although atrial hypocontractility contributes to stroke risk in AF, the molecular mechanisms reducing myofilament contractile function remain unknown. We tested the hypothesis that increased expression of PPP1R12C, the PP1 regulatory subunit targeting atrial myosin light chain 2 (MLC2a), causes hypophosphorylation of MLC2a and results in atrial hypocontractility. Methods: Right atrial appendage tissues were isolated from human AF patients versus sinus rhythm (SR) controls. Western blots, co-immunoprecipitation, and phosphorylation studies were performed to examine how the PP1c-PPP1R12C interaction causes MLC2a de-phosphorylation. In vitro studies of pharmacologic MRCK inhibitor (BDP5290) in atrial HL-1 cells were performed to evaluate PP1 holoenzyme activity on MLC2a. Cardiac-specific lentiviral PPP1R12C overexpression was performed in mice to evaluate atrial remodeling with atrial cell shortening assays, echocardiography, and AF inducibility with EP studies. Results: In human patients with AF, PPP1R12C expression was increased two-fold versus SR controls ( P =2.0×10 -2 , n=12,12 in each group) with > 40% reduction in MLC2a phosphorylation ( P =1.4×10 -6 , n=12,12 in each group). PPP1R12C-PP1c binding and PPP1R12C-MLC2a binding were significantly increased in AF ( P =2.9×10 -2 and 6.7×10 -3 respectively, n=8,8 in each group). In vitro studies utilizing drug BDP5290, which inhibits T560-PPP1R12C phosphorylation, demonstrated increased PPP1R12C binding with both PP1c and MLC2a, and dephosphorylation of MLC2a. Lenti-12C mice demonstrated a 150% increase in LA size versus controls ( P =5.0×10 -6 , n=12,8,12), with reduced atrial strain and atrial ejection fraction. Pacing-induced AF in Lenti-12C mice was significantly higher than controls ( P =1.8×10 -2 and 4.1×10 -2 respectively, n= 6,6,5). Conclusions: AF patients exhibit increased levels of PPP1R12C protein compared to controls. PPP1R12C overexpression in mice increases PP1c targeting to MLC2a and causes MLC2a dephosphorylation, which reduces atrial contractility and increases AF inducibility. These findings suggest that PP1 regulation of sarcomere function at MLC2a is a key determinant of atrial contractility in AF.

Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease.

The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.

Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants.

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-seq data in GTEx v8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased WGS data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants.

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.

Adalimumab in the treatment of cardiac sarcoidosis: Single center case series and narrative literature review.

Background: Tumor necrosis factor (TNF) inhibitors have been used in the treatment of cardiac sarcoidosis, infliximab being the most commonly used. We have previously reported a case of effective treatment of cardiac sarcoidosis using adalimumab. Objective: To describe our experience of using adalimumab in the treatment of cardiac sarcoidosis. Methods: We conducted a retrospective study to evaluate patients with cardiac sarcoidosis who received adalimumab treatment at the University of Illinois Health between 2011 and 2022. The outcome was evaluated by assessing safety, tolerability, and ability to taper systemic corticosteroids therapy following initiation of adalimumab. Results: Seven patients met the inclusion criteria. Clinical responses to adalimumab were universally positive. Corticosteroid therapy was discontinued in five patients and the dose was reduced in two patients. Furthermore, adalimumab was well tolerated, and no adverse events were reported. Conclusion: Adalimumab was safe and well-tolerated in seven patients with cardiac sarcoidosis seen at our medical center and exhibited corticosteroid-sparing effects. Our observation further warrants large prospective studies to evaluate the safety and efficacy of adalimumab in the treatment of cardiac sarcoidosis.

Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways.

The QT interval is an electrocardiographic measure representing the sum of ventricular depolarization and repolarization, estimated by QRS duration and JT interval, respectively. QT interval abnormalities are associated with potentially fatal ventricular arrhythmia. Using genome-wide multi-ancestry analyses (>250,000 individuals) we identify 177, 156 and 121 independent loci for QT, JT and QRS, respectively, including a male-specific X-chromosome locus. Using gene-based rare-variant methods, we identify associations with Mendelian disease genes. Enrichments are observed in established pathways for QT and JT, and previously unreported genes indicated in insulin-receptor signalling and cardiac energy metabolism. In contrast for QRS, connective tissue components and processes for cell growth and extracellular matrix interactions are significantly enriched. We demonstrate polygenic risk score associations with atrial fibrillation, conduction disease and sudden cardiac death. Prioritization of druggable genes highlight potential therapeutic targets for arrhythmia. Together, these results substantially advance our understanding of the genetic architecture of ventricular depolarization and repolarization.

Mortality Among Patients With Early-Onset Atrial Fibrillation and Rare Variants in Cardiomyopathy and Arrhythmia Genes.

Importance: Patients with early-onset atrial fibrillation (AF) are enriched for rare variants in cardiomyopathy and arrhythmia genes. The clinical significance of these rare variants in patients with early-onset AF is unknown. Objective: To assess the association between rare variants in cardiomyopathy and arrhythmia genes detected in patients with early-onset AF and time to death. Design, Setting, and Participants: This prospective cohort study included participants with AF diagnosed before 66 years of age who underwent whole-genome sequencing through the National Heart, Lung and Blood Institute's Trans-Omics for Precision Medicine program. Participants were enrolled from November 23, 1999, to June 2, 2015. Data were analyzed from February 26 to September 19, 2021. Exposures: Rare variants identified in a panel of 145 genes that are included in cardiomyopathy and arrhythmia panels used by commercial clinical genetic testing laboratories. Main Outcomes and Measures: The primary study outcome was time to death and was adjudicated from medical records and the National Death Index. Multivariable Cox proportional hazards regression was used to evaluate the association of disease-associated variants with risk of death after adjustment for age at AF diagnosis, sex, race, body mass index, left ventricular ejection fraction, and an interaction term of age at AF diagnosis and disease-associated variant status. Results: Among 1293 participants (934 [72%] male; median age at enrollment, 56.0 years; IQR, 48.0-61.0 years), disease-associated (pathogenic or likely pathogenic) rare variants were found in 131 (10%). During a median follow-up of 9.9 years (IQR, 6.9-13.2 years), 219 participants (17%) died. In univariable analysis, disease-associated variants were associated with an increased risk of mortality (hazard ratio, [HR], 1.5; 95% CI, 1.0-2.1; P = .05); the association remained significant in multivariable modeling when adjusted for age at AF diagnosis, sex, race, body mass index, left ventricular ejection fraction, and an interaction term between disease-associated variant status and age at AF diagnosis. The interaction demonstrated that disease-associated variants were associated with a significantly higher risk of mortality compared with no disease-associated variant when AF was diagnosed at a younger age (P = .008 for interaction). Higher body mass index (per IQR: HR, 1.4; 95% CI, 1.2-1.6; P < .001) and lower left ventricular ejection fraction (per IQR: HR, 0.8; 95% CI, 0.7-0.8; P < .001) were associated with higher mortality risk. There were 73 cardiomyopathy-related deaths, 40 sudden deaths, and 10 stroke-related deaths. Mortality among patients with the most prevalent genes with disease-associated variants was 26% (10 of 38 patients) for TTN, 33% (6 of 18) for MYH7, 22% (2 of 9) for LMNA, 0% (0 of 10) for MYH6, and 0% (0 of 8) for KCNQ1. Conclusions and Relevance: The findings suggest that rare variants in cardiomyopathy and arrhythmia genes may be associated with increased risk of mortality among patients with early-onset AF, especially those diagnosed at a younger age. Genetic testing may provide important prognostic information for patients with early-onset AF.

Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed.

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value <5×10-9) in 36 loci associated with telomere length, including 20 newly associated loci (13 were replicated in external datasets). There was little evidence of effect size heterogeneity across populations. Fine-mapping at OBFC1 indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated our TL polygenic trait scores (PTS) were associated with increased risk of cancer-related phenotypes.

The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations.

Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRScommon) with a rare variant PRS (PRSrare) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m2), obesity (BMI ≥ 30 kg/m2), and extreme obesity (BMI ≥ 40 kg/m2). We built PRSscommon and PRSsrare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRScommon explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRSrare explained 1.49%, and 2.97% and 3.68%, respectively. The PRSrare was associated with an increased risk of obesity and extreme obesity (ORobesity = 1.37 per SDPRS, Pobesity = 1.7x10-85; ORextremeobesity = 1.55 per SDPRS, Pextremeobesity = 3.8x10-40), which was attenuated, after adjusting for PRScommon (ORobesity = 1.08 per SDPRS, Pobesity = 9.8x10-6; ORextremeobesity= 1.09 per SDPRS, Pextremeobesity = 0.02). When PRSrare and PRScommon are combined, the increase in explained variance attributed to PRSrare was small (incremental Nagelkerke R2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRSrare to PRScommon provided little improvement to the prediction of obesity (PRSrare AUC = 0.591; PRScommon AUC = 0.708; PRScombined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRSrare provides limited improvement over PRScommon in the prediction of obesity risk, based on these large populations.

Mutant ANP induces mitochondrial and ion channel remodeling in a human iPSC-derived atrial fibrillation model.

Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) can model heritable arrhythmias to personalize therapies for individual patients. Although atrial fibrillation (AF) is a leading cause of cardiovascular morbidity and mortality, current platforms to generate iPSC-atrial (a) CMs are inadequate for modeling AF. We applied a combinatorial engineering approach, which integrated multiple physiological cues, including metabolic conditioning and electrical stimulation, to generate mature iPSC-aCMs. Using the patient's own atrial tissue as a gold standard benchmark, we assessed the electrophysiological, structural, metabolic, and molecular maturation of iPSC-aCMs. Unbiased transcriptomic analysis and inference from gene regulatory networks identified key gene expression pathways and transcription factors mediating atrial development and maturation. Only mature iPSC-aCMs generated from patients with heritable AF carrying the non-ion channel gene (NPPA) mutation showed enhanced expression and function of a cardiac potassium channel and revealed mitochondrial electron transport chain dysfunction. Collectively, we propose that ion channel remodeling in conjunction with metabolic defects created an electrophysiological substrate for AF. Overall, our electro-metabolic approach generated mature human iPSC-aCMs that unmasked the underlying mechanism of the first non-ion channel gene, NPPA, that causes AF. Our maturation approach will allow for the investigation of the molecular underpinnings of heritable AF and the development of personalized therapies.

Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data.

Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.