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A premature truncation of MYBPHL in humans and a loss of Mybphl in mice is associated with dilated cardiomyopathy, atrial and ventricular arrhythmias, and atrial enlargement. MYBPHL encodes myosin binding protein H-like (MyBP-HL). Prior work in mice indirectly identified Mybphl expression in the atria and in small puncta throughout the ventricle. Because of its genetic association with human and mouse cardiac conduction system disease, we evaluated the anatomical localization of MyBP-HL and the consequences of loss of MyBP-HL on conduction system function. Immunofluorescence microscopy of normal adult mouse ventricles identified MyBP-HL-positive ventricular cardiomyocytes that co-localized with the ventricular conduction system marker contactin-2 near the atrioventricular node and in a subset of Purkinje fibers. Mybphl heterozygous ventricles had a marked reduction of MyBP-HL-positive cells compared to controls. Lightsheet microscopy of normal perinatal day 5 mouse hearts showed enrichment of MyBP-HL-positive cells within and immediately adjacent to the contactin-2-positive ventricular conduction system, but this association was not apparent in Mybphl heterozygous hearts. Surface telemetry of Mybphl-null mice revealed atrioventricular block and atrial bigeminy, while intracardiac pacing revealed a shorter atrial relative refractory period and atrial tachycardia. Calcium transient analysis of isolated Mybphl-null atrial cardiomyocytes demonstrated an increased heterogeneity of calcium release and faster rates of calcium release compared to wild type controls. Super-resolution microscopy of Mybphl heterozygous and homozygous null atrial cardiomyocytes showed ryanodine receptor disorganization compared to wild type controls. Abnormal calcium release, shorter atrial refractory period, and atrial dilation seen in Mybphl null, but not wild type control hearts, agree with the observed atrial arrhythmias, bigeminy, and atrial tachycardia, whereas the proximity of MyBP-HL-positive cells with the ventricular conduction system provides insight into how a predominantly atrial expressed gene contributes to ventricular arrhythmias and ventricular dysfunction.

BackgroundSudden unexpected death in children is a tragic event. Understanding the genetics of sudden death in the young (SDY) enables family counseling and cascade screening. The objective of this study was to characterize genetic variation in an SDY cohort using whole genome sequencing.MethodsThe SDY Case Registry is a National Institutes of Health/Centers for Disease Control surveillance effort to discern the prevalence, causes, and risk factors for SDY. The SDY Case Registry prospectively collected clinical data and DNA biospecimens from SDY cases ResultsThe SDY cohort was 42% European, 30% African, 17% Hispanic, and 11% with mixed ancestries, and 39% female. Six percent of the cohort was found to harbor a pathogenic or likely pathogenic genetic variant in an epilepsy, cardiomyopathy or arrhythmia gene. The genomes of SDY cases, but not controls, were enriched for rare, damaging variants in epilepsy, cardiomyopathy and arrhythmia-related genes. A greater number of rare epilepsy genetic variants correlated with younger age at death.ConclusionsWhile damaging cardiomyopathy and arrhythmia genes are recognized contributors to SDY, we also observed an enrichment in epilepsy-related genes in the SDY cohort, and a correlation between rare epilepsy variation and younger age at death. These findings emphasize the importance of considering epilepsy genes when evaluating SDY.

Polygenic risk scores (PRS) have led to enthusiasm for precision medicine. However, it is well documented that PRS do not generalize across groups differing in ancestry or sample characteristics e.g., age. Quantifying performance of PRS across different groups of study participants, using genome-wide association study (GWAS) summary statistics from multiple ancestry groups and sample sizes, and using different linkage disequilibrium (LD) reference panels may clarify which factors are limiting PRS transferability. To evaluate these factors in the PRS generation process, we generated body mass index (BMI) PRS (PRSBMI) in the Electronic Medical Records and Genomics (eMERGE) network (N=75,661). Analyses were conducted in two ancestry groups (European and African) and three age ranges (adult, teenagers, and children). For PRSBMI calculations, we evaluated five LD reference panels and three sets of GWAS summary statistics of varying sample size and ancestry. PRSBMI performance increased for both African and European ancestry individuals using cross-ancestry GWAS summary statistics compared to European-only summary statistics (6.3% and 3.7% relative R2 increase, respectively, pAfrican=0.038, pEuropean=6.26x10-4). The effects of LD reference panels were more pronounced in African ancestry study datasets. PRSBMI performance degraded in children; R2 was less than half of teenagers or adults. The effect of GWAS summary statistics sample size was small when modeled with the other factors. Additionally, the potential of using a PRS generated for one trait to predict risk for comorbid diseases is not well understood especially in the context of cross-ancestry analyses - we explored clinical comorbidities from the electronic health record associated with PRSBMI and identified significant associations with type 2 diabetes and coronary atherosclerosis. In summary, this study quantifies the effects that ancestry, GWAS summary statistic sample size, and LD reference panel have on PRS performance, especially in cross-ancestry and age-specific analyses.

Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .

Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk.To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores (PRS), monogenic risks, family history, and clinical risk assessments via a Genome Informed Risk Assessment (GIRA) report and will assess uptake of care recommendations after return of results.GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022.Return of a novel report for communicating monogenic, polygenic, and family history based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Patients with biallelic mutations in the nuclear-encoded mitochondrial gene C1QBP/p32 have been described with syndromic features and autosomal recessive cardiomyopathy. We describe the clinical course in two siblings who developed cardiomyopathy and ventricular fibrillation in infancy. We provide genomic analysis and clinical-pathologic correlation. Both siblings had profound cardiac failure with ventricular arrhythmia. One child died suddenly. The second sibling survived resuscitation but required extracorporeal cardiopulmonary support and died shortly afterward. On cardiac autopsy, the left ventricle was hypertrophied in both children. Histological examination revealed prominent cardiomyocyte cytoplasmic clearing, and electron microscopy confirmed abnormal mitochondrial structure within cardiomyocytes. DNA sequencing revealed compound heterozygous variants in C1QBP (p.Thr40Asnfs*45 and p.Phe204Leu) in both children. Family segregation analysis demonstrated each variant was inherited from an unaffected, heterozygous parent. Inherited loss of C1QBP/p32 is associated with recessive cardiomyopathy, ventricular fibrillation, and sudden death in early life. Ultrastructural mitochondrial evaluation in the second child was similar to findings in engineered C1qbp-deficient mice. Rapid trio analysis can define rare biallelic variants in genes that may be implicated in sudden death and facilitate medical management and family planning. (184/200).

Genetic variation in genes regulating metabolism may be advantageous in some settings but not others. The non-failing adult heart relies heavily on fatty acids as a fuel substrate and source of ATP. In contrast, the failing heart favors glucose as a fuel source. A bootstrap analysis for genes with deviant allele frequencies in cardiomyopathy cases versus controls identified the MTCH2 gene as having unusual variation. MTCH2 encodes an outer mitochondrial membrane protein, and prior genome-wide studies associated MTCH2 variants with body mass index, consistent with its role in metabolism. We identified the referent allele of rs1064608 (p.Pro290) as being overrepresented in cardiomyopathy cases compared to controls, and linkage disequilibrium analysis associated this variant with the MTCH2 cis eQTL rs10838738 and lower MTCH2 expression. To evaluate MTCH2, we knocked down Mtch in Drosophila heart tubes which produced a dilated and poorly functioning heart tube, reduced adiposity and shortened life span. Cardiac Mtch mutants generated more lactate at baseline, and they displayed impaired oxygen consumption in the presence of glucose but not palmitate. Treatment of cardiac Mtch mutants with dichloroacetate, a pyruvate dehydrogenase kinase inhibitor, reduced lactate and rescued lifespan. Deletion of MTCH2 in human cells similarly impaired oxygen consumption in the presence of glucose but not fatty acids. These data support a model in which MTCH2 reduction may be favorable when fatty acids are the major fuel source, favoring lean body mass. However, in settings like heart failure, where the heart shifts toward using more glucose, reduction of MTCH2 is maladaptive.

Background: Cardiomyopathy is a highly heritable disorder that carries a significant risk for heart failure and arrhythmias. Most inherited cardiomyopathies are characterized by variable penetrance and expressivity, which in part arises from additional genetic variation, known as genetic modifiers. Methods and Results: Genomic profiling of human cardiomyopathy cases identified enriched genetic variation in the gene MTCH2. Specifically, a truncating variant was found to be overrepresented in patients with cardiomyopathy compared to controls. MTCH2 encodes a mitochondrial carrier protein that has a role in regulating oxidative phosphorylation. To investigate fundamental mechanisms by which MTCH2 contributes to cardiac and metabolic phenotypes, we generated a knockdown model of the Drosophila MTCH2 ortholog, Mtch. We found that cardiac-specific Mtch reduction in flies produced heart tube dilation and reduced function as well as a shortened life span, documenting a clear role Mtch in the myocardium. Metabolomic profiling demonstrated cardiac deficiency of Mtch lowered the flux of glucose-derived metabolites to the citric acid cycle associated with reduced downstream oxygen consumption and ATP synthesis, causing an energy deficit. We generated a deletion of MTCH2 using gene editing in HEK293 cells. Similar to the fly model, these cells demonstrated reduced oxygen consumption in the presence of glucose, but not fatty acids, and had a higher level of inhibitory phosphorylation of pyruvate dehydrogenase, a critical regulator of glucose metabolism. These data suggest MTCH2 influences the efficiency of glucose oxidation and substrate usage, an important mode of cardiac energy generation, especially in the setting of heart failure. Conclusions: We identified MTCH2 as a modifier of the cardiomyopathy phenotype in humans. Reduction of MTCH2 resulted in impaired cardiac function with reduced oxygen consumption and increased glycolysis in a substrate dependent manner. Since failed hearts are more dependent on glycolysis, these data support that reduction of MTCH2 promotes heart failure and provides a mechanism by which MTCH2 acts as a deleterious genetic modifier in heart failure.

Importance Postmortem genetic testing of young individuals with sudden death has previously identified pathogenic gene variants. However, prior studies primarily considered highly penetrant monogenic variants, often without detailed decedent and family clinical information. Objective To assess genotype and phenotype risk in a diverse cohort of young decedents with sudden death and their families. Design, Setting, and Participants Pathological and whole-genome sequence analysis was conducted in a cohort referred from a national network of medical examiners. Cases were accrued prospectively from May 2015 to March 2019 across 24 US states. Analysis began September 2016 and ended November 2020. Exposures Evaluation of autopsy and clinical data integrated with whole-genome sequence data and family member evaluation. Results A total of 103 decedents (mean [SD] age at death, 23.7 [11.9] years; age range, 1-44 years), their surviving family members, and 140 sex- and genetic ancestry–matched controls were analyzed. Among 103 decedents, autopsy and clinical data review categorized 36 decedents with postmortem diagnoses, 23 decedents with findings of uncertain significance, and 44 with sudden unexplained death. Pathogenic/likely pathogenic (P/LP) genetic variants in arrhythmia or cardiomyopathy genes were identified in 13 decedents (12.6%). A multivariable analysis including decedent phenotype, ancestry, and sex demonstrated that younger decedents had a higher burden of P/LP variants and select variants of uncertain significance (effect size, −1.64;P = .001). These select, curated variants of uncertain significance in cardiac genes were more common in decedents than controls (83 of 103 decedents [86%] vs 100 of 140 controls [71%];P = .005), and decedents harbored more rare cardiac variants than controls (2.3 variants per individual vs 1.8 in controls;P = .006). Genetic testing of 31 parent-decedent trios and 14 parent-decedent dyads revealed 8 transmitted P/LP variants and 1 de novo P/LP variant. Incomplete penetrance was present in 6 of 8 parents who transmitted a P/LP variant. Conclusions and Relevance Whole-genome sequencing effectively identified P/LP variants in cases of sudden death in young individuals, implicating both arrhythmia and cardiomyopathy genes. Genomic analyses and familial phenotype association suggest potentially additive, oligogenic risk mechanisms for sudden death in this cohort.

The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.

AIMS : Our objective was to better understand the genetic bases of dilated cardiomyopathy (DCM), a leading cause of systolic heart failure. METHODS AND RESULTS : We conducted the largest genome-wide association study performed so far in DCM, with 2719 cases and 4440 controls in the discovery population. We identified and replicated two new DCM-associated loci on chromosome 3p25.1 [lead single-nucleotide polymorphism (SNP) rs62232870, P = 8.7 × 10(−11) and 7.7 × 10(−4) in the discovery and replication steps, respectively] and chromosome 22q11.23 (lead SNP rs7284877, P = 3.3 × 10(−8) and 1.4 × 10(−3) in the discovery and replication steps, respectively), while confirming two previously identified DCM loci on chromosomes 10 and 1, BAG3 and HSPB7. A genetic risk score constructed from the number of risk alleles at these four DCM loci revealed a 3-fold increased risk of DCM for individuals with 8 risk alleles compared to individuals with 5 risk alleles (median of the referral population). In silico annotation and functional 4C-sequencing analyses on iPSC-derived cardiomyocytes identify SLC6A6 as the most likely DCM gene at the 3p25.1 locus. This gene encodes a taurine transporter whose involvement in myocardial dysfunction and DCM is supported by numerous observations in humans and animals. At the 22q11.23 locus, in silico and data mining annotations, and to a lesser extent functional analysis, strongly suggest SMARCB1 as the candidate culprit gene. CONCLUSION : This study provides a better understanding of the genetic architecture of DCM and sheds light on novel biological pathways underlying heart failure.

Background Inherited cardiomyopathies display variable penetrance and expression, and a component of phenotypic variation is genetically determined. To evaluate the genetic contribution to this variable expression, we compared protein coding variation in the genomes of those with hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM). Methods and Results Nonsynonymous single‐nucleotide variants (nsSNVs) were ascertained using whole genome sequencing from familial cases of HCM (n=56) or DCM (n=70) and correlated with echocardiographic information. Focusing on nsSNVs in 102 genes linked to inherited cardiomyopathies, we correlated the number of nsSNVs per person with left ventricular measurements. Principal component analysis and generalized linear models were applied to identify the probability of cardiomyopathy type as it related to the number of nsSNVs in cardiomyopathy genes. The probability of having DCM significantly increased as the number of cardiomyopathy gene nsSNVs per person increased. The increase in nsSNVs in cardiomyopathy genes significantly associated with reduced left ventricular ejection fraction and increased left ventricular diameter for individuals carrying a DCM diagnosis, but not for those with HCM. Resampling was used to identify genes with aberrant cumulative allele frequencies, identifying potential modifier genes for cardiomyopathy. Conclusions Participants with DCM had more nsSNVs per person in cardiomyopathy genes than participants with HCM. The nsSNV burden in cardiomyopathy genes did not correlate with the probability or manifestation of left ventricular measures in HCM. These findings support the concept that increased variation in cardiomyopathy genes creates a genetic background that predisposes to DCM and increased disease severity.

Background: Inherited cardiomyopathy associates with a range of phenotypes, mediated by genetic and nongenetic factors. Noninherited cardiomyopathy also displays varying progression and outcomes. Expression of cardiomyopathy genes is under the regulatory control of promoters and enhancers, and human genetic variation in promoters and enhancers may contribute to this variability. Methods: We superimposed epigenomic profiling from hearts and cardiomyocytes, including promoter-capture chromatin conformation information, to identify enhancers for 2 cardiomyopathy genes, MYH7 and LMNA . Enhancer function was validated in human cardiomyocytes derived from induced pluripotent stem cells. We also conducted a genome-wide search to ascertain genomic variation in enhancers positioned to alter cardiac expression and correlated one of these variants to cardiomyopathy progression using biobank data. Results: Multiple enhancers were identified and validated for LMNA and MYH7 , including a key enhancer that regulates the switch from MYH6 expression to MYH7 expression. Deletion of this enhancer resulted in a dose-dependent increase in MYH6 and faster contractile rate in engineered heart tissues. We searched for genomic variation in enhancer sequences across the genome, with a focus on nucleotide changes that create or interrupt transcription factor binding sites. The sequence variant, rs875908, disrupts a T-Box Transcription Factor 5 binding motif and maps to an enhancer region 2 kilobases from the transcriptional start site of MYH7. Gene editing to remove the enhancer that harbors this variant markedly reduced MYH7 expression in human cardiomyocytes. Using biobank-derived data, rs875908 associated with longitudinal echocardiographic features of cardiomyopathy. Conclusions: Enhancers regulate cardiomyopathy gene expression, and genomic variation within these enhancer regions associates with cardiomyopathic progression over time. This integrated approach identified noncoding modifiers of cardiomyopathy and is applicable to other cardiac genes.

Introduction: Inherited cardiomyopathy is caused by mutations in more than 100 genes. A well-recognized clinical feature of genetic cardiomyopathy is varying phenotypic expression. Even with identical primary mutations, there is a range of clinical outcomes. Genetic variants in protein coding regions have been shown to alter the phenotypic expression of primary cardiomyopathy-causing mutations. However, the contribution of noncoding variation has been less well studied. Methods and Results: We used an integrative analysis of >20 publicly-available heart enhancer function and enhancer target datasets to identify genomic regions predicted to regulate the cardiomyopathy genes, MYH7 and LMNA . We identified two candidate enhancer clusters around the MYH7 gene and three clusters around the LMNA gene. We tested enhancers in these clusters using reporter assays and CRISPr-mediated deletion in human cardiomyocytes derived from induced pluripotent stem cells (iCMs). We identified a super enhancer upstream of MYH7 that is necessary for high MYH7 expression in iCMs. These regulatory regions contained sequence variants within transcription factor binding sites that altered enhancer function. We created an informatic pipeline that extended this strategy genomewide to identify an additional enhancer modifying variant upstream of MYH7 . This variant disrupts a transcription factor binding site upstream of MYH7 and limits MYH7 upregulation. We extended these analyses by examining clinical correlates, finding that this variant correlated with a more dilated left ventricle over time in patients with cardiomyopathy. Conclusions: We identified two enhancer regions important for MYH7 expression in iCMs. These enhancer regions may be utilized to induce MYH7 during human development and heart failure. MYH7 changes in heart failure have been linked to cardiomyopathy phenotypes. The variant upstream of MYH7 likely alters these changes and results in a more severe phenotype. These findings demonstrate that noncoding variants have clinical utility and targeted assessment of noncoding modifiers may become integrated into clinical care.

Introduction: Genetic testing after sudden death in the young can identify pathogenic cardiac gene variants. Hypothesis: Genomic methods, coupled with phenotype evaluation, reveal non-Mendalian risks. Methods: We conducted clinical analysis and whole genome sequencing on 103 decedents aged 1-40 (mean age at death 23.7 years) accrued prospectively from 2015 to 2019 across 22 states. Postmortem pathological findings were classified as: known cardiac disorders, findings of uncertain significance (FUS), or sudden unexplained death (SUD, indicating no postmortem pathological diagnosis). Parental DNA and clinical data were obtained where possible. Variants were classified by an independent clinical genetic laboratory. Results: Among the 103 decedents, 34 had a postmortem clinical diagnosis, 23 had FUS, and 46 were classified as SUD. Pathogenic/likely pathogenic (P/LP) variants in arrhythmia or cardiomyopathy genes were identified in 17 (16.5%) decedents. The distribution of P/LP variants was not associated with age at death (OR 1.01 [0.97, 1.05], p=0.54); however, a multivariable analysis including decedent phenotype, ancestry and sex demonstrated that younger decedents had a higher burden of curated P/LP/VUS variants (effect size -1.5, p=0.0019). DNA from 31 parent-decedent trios and 14 parent-decedent dyads revealed 9 transmitted P/LP variants and 1 de novo P/LP variant. More than half of parents transmitting a P/LP variant (5/9) did not have clinical findings associated with the genotype. Conclusions: Whole genome sequencing effectively revealed P/LP variants in cases of sudden death in the young, implicating both arrhythmia and cardiomyopathy genes. In addition, both genotype and phenotype analyses suggest additional non-Mendelian risk mechanisms.

Background: The failing heart is characterized by changes in gene expression. However, the regulatory regions of the genome that drive these gene expression changes have not been well defined in human hearts. Methods: To define genome-wide enhancer and promoter use in heart failure, cap analysis of gene expression sequencing was applied to 3 healthy and 4 failed human hearts to identify promoter and enhancer regions used in left ventricles. Healthy hearts were derived from donors unused for transplantation and failed hearts were obtained as discarded tissue after transplantation. Results: Cap analysis of gene expression sequencing identified a combined potential for ≈23 000 promoters and ≈5000 enhancers active in human left ventricles. Of these, 17 000 promoters and 1800 enhancers had additional support for their regulatory function. Comparing promoter usage between healthy and failed hearts highlighted promoter shifts which altered aminoterminal protein sequences. Enhancer usage between healthy and failed hearts identified a majority of differentially used heart failure enhancers were intronic and primarily localized within the first intron, revealing this position as a common feature associated with tissue-specific gene expression changes in the heart. Conclusions: This data set defines the dynamic genomic regulatory landscape underlying heart failure and serves as an important resource for understanding genetic contributions to cardiac dysfunction. Additionally, regulatory changes contributing to heart failure are attractive therapeutic targets for controlling ventricular remodeling and clinical progression.

Background: Cardiomyopathy is a highly heritable disorder that carries a significant risk for heart failure and arrhythmias. The onset, severity, and progression of cardiomyopathy is influenced by genetic variation, with the most common form of inheritance in familial cases being autosomal dominant. All inherited cardiomyopathies are characterized by variable penetrance and expressivity, which in part arises from additional genetic variation, known as genetic modifiers. Methods and Results: Broad genomic profiling of human cardiomyopathy cases identified enriched genetic variation in the gene MTCH2. Specifically, a loss of function variant was found to be enriched in patients with cardiomyopathy. MTCH2 single nucleotide polymorphisms have also been linked to obesity, underscoring a critical role for MTCH2 in metabolic regulation. MTCH2 encodes a mitochondrial carrier protein that has a role in regulating oxidative phosphorylation. In order to investigate fundamental mechanisms by which MTCH2 contributes to cardiac and metabolic phenotypes, we generated a knockdown model of the Drosophila MTCH2 ortholog, Mtch. This knockdown model mimics what is seen in human carriers with the heterozygous loss of function allele. In the Drosophila model, Mtch RNA was reduced by approximately half. We found that cardiac-specific Mtch deficiency in flies produced heart tube dilated and reduced function as well as a shortened life span, documenting a clear role for cardiac Mtch. Cardiac deficiency of Mtch increased circulating lactate levels in flies. Oxygen consumption was reduced in cardiac Mtch deficiency flies in the presence of glucose, but not palmitate. Thus, loss of Mtch2 alters oxygen consumption in a substrate dependent manner. Conclusions: We identified MTCH2 as a modifier of the cardiomyopathy phenotype in humans. Reduction of Mtch in flies resulted in impaired cardiac function and reduced oxygen consumption under certain metabolic condition. As failed hearts are more dependent on glycolysis, these data support that reduction of MTCH2 promotes heart failure and provides a mechanism by which MTCH2 acts as a deleterious genetic modifier in heart failure.

Background: Mutations in more than 100 genes lead to dilated, hypertrophic and other forms of cardiomyopathy. Autosomal dominant mutations in the MYH7 and LMNA genes cause autosomal dominant hypertrophic and dilated cardiomyopathy, respectively. Individual mutations display a range of clinical expression from severe early onset disease to minimal or no symptoms. Genetic variation in noncoding gene regulatory regions including enhancers is expected to modify expression of cardiomyopathy genes and disease expressivity. In addition, heart failure is associated a fetal gene re-expression program, mediated by genetic regulatory regions. The contribution of noncoding genetic variation to cardiomyopathy and heart failure has been hampered by limited genome wide descriptions of human cardiac regulatory regions. Methods and Results: We used C ap A nalysis of G ene E xpression by sequencing (CAGE-seq) to profile the transcriptional start sites in healthy and failed human hearts. CAGE-seq detects the unidirectional signals of gene promoters and the bidirectional signal of transcribed enhancer regions. We identified ~17,000 transcriptional start sites associated with gene promoters and ~1,500 putative enhancer regions active in cardiac tissue. These CAGE-defined regulatory regions carried histone modifications and transcription factor binding properties characteristic of enhancers or promoters. We specifically identified promoter switching and differential enhancer usage between healthy and failed hearts. We intersected CAGE-defined enhancers with additional epigenomic datasets to identify regulatory regions for MYH7 and LMNA genes. We identified 13 putative enhancer regions and validated the functionality of a subset of these regulatory regions using reporter assays and gene editing. Conclusions: This CAGE-seq dataset defines the regulatory environment for heart failure. These promoter and enhancer regions could be used to target heart-failure associated gene expression changes. Additionally, this data can be used to identify enhancer regions regulating cardiomyopathy genes.

Background: Approximately 6 million adults in the United States have heart failure. The progression of heart failure is variable arising from differences in sex, age, genetic background including ancestry, and medication response. Many population-based genetic studies of heart failure have been cross-sectional in nature, failing to gain additional power from longitudinal analyses. As heart failure is known to change over time, using longitudinal data trajectories as a quantitative trait will increase power in genome wide association studies (GWAS). Methods: We used the electronic health record in a racially and ethnically diverse medical biobank from a single, metropolitan US center. We used whole genome data from 896 unrelated participants analyzed, including 494 who had at least 1 electrocardiogram and 324 who had more than 1 echocardiogram (average of 3 observations per person). A mixture model based semiparametric latent growth curve model was used to cluster outcome measures used for genome-wide analyses. Results: GWAS on the trajectory probability of QTc interval identified significant associations with variants in regulatory regions proximal to the WLS gene, which encodes Wntless, a Wnt ligand secretion mediator. WLS was previously associated with QTc and myocardial infarction, thus confirming the power of the method. GWAS on the trajectory probability of left ventricular diameter (LVIDd) identified significant associations with variants in regulatory regions near MYO10 , which encodes unconventional Myosin-10. MYO10 was previously associated with obesity and metabolic syndrome. Conclusions: This is the first study to show an association with variants in or near MYO10 and left ventricular dimension changes over time. Further, we found that using trajectory probabilities can provide increased power to find novel associations with longitudinal data. This reduces the need for larger cohorts, and increases yield from smaller, well-phenotyped cohorts, such as those found in biobanks. This approach should be useful in the study of rare diseases and underrepresented populations.

Approximately 6 million adults in the US have heart failure (HF). HF progression is variable due in part to differences in sex, age, and genetic ancestry. Previous population-based genetic studies have largely focused on cross-sectional data related to HF, a disease known to change over time. Utilizing longitudinal data trajectory probabilities as a continuous trait may increase the likelihood of finding significant, biologically relevant associations in a genome-wide association (GWA) analysis. We analyzed data from the electronic health record in a medical biobank from a single, metropolitan US center to gather clinically pertinent data for analyses. We evaluated whole genome sequencing of 896 unrelated biobank participants, including 494 with at least 1 electrocardiogram and 324 who had more than 1 echocardiogram (∼3 observations per person). A censored normal distribution multivariable mixture model was used to cluster phenotype measures for genome-wide analyses. GWA analysis on the trajectory probability of the corrected QT measurement (QTc) taken from electrocardiograms identified significant associations with variants in regulatory regions proximal to theWLSgene, which encodes the Wnt ligand secretion mediator, Wntless.WLSwas previously associated with QT length using of approximately 16,000 participants supporting the utility of this method to uncover significant genetic associations in small datasets. GWA analysis on the trajectory probability of left ventricular diameter as taken from echocardiograms identified novel significant associations with variants in regulatory regions nearMYO10, which encodes the unconventional Myosin-10. We found that trajectory probabilities improved the ability to discover significant and relevant genetic associations. This novel approach increased yield from smaller, well-phenotyped cohorts with longitudinal data from a medical biobank.AUTHOR SUMMARYApproximately 6 million adults in the US have heart failure, a disease known to change over time. In a hospital based electronic health record, electrocardiograms and echocardiograms, used to evaluate heart failure, can be tracked over time. We utilized these data to create a novel trait that can be applied to genetic analyses. We analyzed genome sequence of 896 biobank participants from diverse racial/ethnic backgrounds. Genome-wide association (GWA) analyses were performed on a subset of these individuals for heart failure outcomes. A statistical model that incorporates cardiac data that are tracked over time was used to cluster these data using a probabilistic approach. These probabilities were used for a GWA analysis for corrected QT measurement (QTc) and left ventricular diameter (LVID). The QTc interval analysis identified significant correlations with variants in regulatory regions near theWLSgene which encodes the Wnt ligand secretion mediator, Wntless. Analysis of LVID identified significant associations with variants in regulatory regions near theMYO10gene which encodes the unconventional Myosin-10. Through these analyses, we found that using the trajectory probabilities can facilitate the discovery of novel significant, biologically relevant associations. This method reduces the need for larger cohorts, and increases yield from smaller, well-phenotyped cohorts.

The failed heart is characterized by re-expression of a fetal gene program, which contributes to adaptation and maladaptation in heart failure. To define genomewide enhancer and promoter use in heart failure, Cap Analysis of Gene Expression (CAGE-seq) was applied to healthy and failed human left ventricles to define short RNAs associated with both promoters and enhancers. Integration of CAGE-seq data with RNA sequencing identified a combined ∼17,000 promoters and ∼1,500 enhancers active in healthy and failed human left ventricles. Comparing promoter usage between healthy and failed hearts highlighted promoter shifts which altered amino-terminal protein sequences. Comparing enhancer usage between healthy and failed hearts revealed a majority of differentially utilized heart failure enhancers were intronic and primarily localized within the first intron, identifying this position as a common feature associated with tissue-specific gene expression changes in the heart. This dataset defines the dynamic genomic regulatory landscape underlying heart failure and serves as an important resource for understanding genetic contributions to cardiac dysfunction.

Background Genome sequencing coupled with electronic heath record data can uncover medically important genetic variation. Interpretation of rare genetic variation and its role in mediating cardiovascular phenotypes is confounded by variants of uncertain significance. Methods and Results We analyzed the whole genome sequence of 900 racially and ethnically diverse biobank participants selected from a single US center. Participants were equally divided among European, African, Hispanic, and mixed races/ethnicities. We evaluated the American College of Medical Genetics and Genomics medically actionable list of 59 genes, focusing on the cardiac genes. Variation was interpreted using the most recent reports in ClinVar, a database of medically relevant human variation. We identified 19 individuals with pathogenic or likely pathogenic variants in cardiac actionable genes (2%) and found evidence of related clinical correlates in the electronic health record. Participants of African ancestry, compared with those of European ancestry, had more variants of uncertain significance in the medically actionable genes including the 30 cardiac actionable genes, even when normalized to total variant count per person. Longitudinal measures of left ventricle size from ≈400 biobank participants (1723 patient‐years) were correlated with genetic findings. The presence of ≥1 uncertain variant in the actionable cardiac genes and a cardiomyopathy diagnosis correlated with increased left ventricular internal diameter in diastole and in systole. In particular, MYBPC 3 was identified as a gene with excess variants of uncertain significance. Conclusions These data indicate that a subset of uncertain genetic variants may confer risk and should not be considered benign.

Background Randomised controlled trials (RCTs) of vitamin D to prevent COPD exacerbations have yielded conflicting results. Individual participant data meta-analysis could identify factors that explain this variation. Methods PubMed, Embase, the Cochrane Central Register of Controlled Trials and Web of Science were searched from inception up to and including 5 October 2017 to identify RCTs of vitamin D supplementation in patients with COPD that reported incidence of acute exacerbations. Individual participant data meta-analysis was performed using fixed effects models adjusting for age, sex, Global Initiative for Chronic Obstructive Lung Disease spirometric grade and trial. Results Four eligible RCTs (total 560 participants) were identified; individual participant data were obtained for 469/472 (99.4%) participants in three RCTs. Supplementation did not influence overall rate of moderate/severe COPD exacerbations (adjusted incidence rate ratio (aIRR) 0.94, 95% CI 0.78 to 1.13). Prespecified subgroup analysis revealed that protective effects were seen in participants with baseline 25-hydroxyvitamin D levels Conclusions Vitamin D supplementation safely and substantially reduced the rate of moderate/severe COPD exacerbations in patients with baseline 25-hydroxyvitamin D levels Trial registration number CRD42014013953.

Importance Cardiac fibrosis is exceedingly rare in young adults. Identification of genetic variants that cause early-onset cardiomyopathy may inform novel biological pathways. Experimental models and a single case report have linked genetic deficiency of plasminogen activator inhibitor-1 (PAI-1), a downstream target of cardiac transforming growth factor β, with cardiac fibrosis. Objective To perform detailed cardiovascular phenotyping and genotyping in young adults from an Amish family with a frameshift variant (c.699_700dupTA) inSERPINE1, the gene that codes for PAI-1. Design, Setting, and Participants This observational study included participants from 3 related nuclear families from an Amish community in the primary analysis and participants from the extended family in the secondary analysis. Participants were recruited from May 2015 to December 2016, and analysis took place from June 2015 to June 2020. Main Outcomes and Measures (1) Multimodality cardiovascular imaging (transthoracic echocardiography and cardiac magnetic resonance imaging), (2) whole-exome sequencing, and (3) induced pluripotent stem cell–derived cardiomyocytes. Results Among 17 participants included in the primary analysis, the mean (interquartile range) age was 23.7 (20.9-29.9) years and 9 individuals (52.9%) were confirmed to be homozygous for theSERPINE1c.699_700dupTA variant. Late gadolinium enhancement was present in 6 of 9 homozygous participants (67%) with absolute PAI-1 deficiency vs 0 of 8 in the control group (P = .001). Late gadolinium enhancement patterns tended to be dense and linear, usually subepicardial but also midmyocardial and transmural with noncoronary distributions. Targeted whole-exome sequencing analysis identified that homozygosity for c.699_700dupTASERPINE1was the only shared pathogenic variant or variant of uncertain significance after examination of cardiomyopathy genes among those with late gadolinium enhancement. Induced pluripotent stem cell–derived cardiomyocytes from participants homozygous for theSERPINE1c.699_700dupTA variant exhibited susceptibility to cardiomyocyte injury in response to angiotensin II (increased transforming growth factor β1 secretion and release of lactate dehydrogenase) compared with control induced pluripotent stem cell–derived cardiomyocytes. In a secondary analysis based on echocardiography in 155 individuals across 3 generations in the extended family, no difference in global longitudinal strain was observed in carriers for theSERPINE1c.699_700dupTA variant compared with wild-type participants, supporting an autosomal recessive inheritance pattern. Conclusions and Relevance In this study, a highly penetrant, autosomal recessive, cardiac fibrosis phenotype among young adults with homozygous frameshift variant forSERPINE1was identified, suggesting an optimal range of PAI-1 levels are needed for cardiac homeostasis.

Background: Cardiomyopathy and arrhythmias are under significant genetic influence. Here, we studied a family with dilated cardiomyopathy and associated conduction system disease in whom prior clinical cardiac gene panel testing was unrevealing. Methods: Whole-genome sequencing and induced pluripotent stem cells were used to examine a family with dilated cardiomyopathy and atrial and ventricular arrhythmias. We also characterized a mouse model with heterozygous and homozygous deletion of Mybphl . Results: Whole-genome sequencing identified a premature stop codon, R255X, in the MYBPHL gene encoding MyBP-HL (myosin-binding protein-H like), a novel member of the myosin-binding protein family. MYBPHL was found to have high atrial expression with low ventricular expression. We determined that MyBP-HL protein was myofilament associated in the atria, and truncated MyBP-HL protein failed to incorporate into the myofilament. Human cell modeling demonstrated reduced expression from the mutant MYBPHL allele. Echocardiography of Mybphl heterozygous and null mouse hearts exhibited a 36% reduction in fractional shortening and an increased diastolic ventricular chamber size. Atria weight normalized to total heart weight was significantly increased in Mybphl heterozygous and null mice. Using a reporter system, we detected robust expression of Mybphl in the atria, and in discrete puncta throughout the right ventricular wall and septum, as well. Telemetric electrocardiogram recordings in Mybphl mice revealed cardiac conduction system abnormalities with aberrant atrioventricular conduction and an increased rate of arrhythmia in heterozygous and null mice. Conclusions: The findings of reduced ventricular function and conduction system defects in Mybphl mice support that MYBPHL truncations may increase risk for human arrhythmias and cardiomyopathy.

Rationale: Cardiomyopathies are a major cause of heart failure and have a strong heritable component. Objective: Determine the role of both common and rare nonsynonymous genetic variation in hypertrophic (HCM) and dilated familial cardiomyopathy (DCM). Methods and Results: Whole genome sequencing was used to determine common and rare nonsynonymous genetic variation in familial cases of HCM (n=56) or DCM (n=71). Variation was evaluated in 102 cardiomyopathy genes routinely assayed in clinical and commercial gene testing panels. We used cardiac gene expression data from GTEx (Genotype-Tissue Expression database) to define additional genes expressed in the heart. The number of nonsynonymous single nucleotide variants (nsSNVs), the majority of which were missense variants, was correlated with echocardiographic measurements. Principal component analysis (PCA) of left ventricular measures separated HCM and DCM. Regression of the first principal component using all nonsynonymous single nucleotide variants (nsSNVs) in cardiomyopathy genes showed the number of nsSNVs predicted DCM but not HCM. DCM probability in the cohort significantly increased as the number of cardiomyopathy gene nsSNVs increased (p Conclusions: DCM subjects carry a greater burden of nsSNVs in cardiomyopathy genes. This genomic burden translates to impaired systolic cardiac function in DCM. In contrast, nsSNV burden in cardiomyopathy genes did not correlate with the probability or manifestation of left ventricular measures in HCM. These findings support a complex inheritance for DCM where increased variation in cardiomyopathy genes creates a genetic background that predisposes to DCM and increased disease severity. The distinct genetic landscapes of HCM and DCM suggest that greater genetic variation in cardiac genes provokes unfavorable ventricular remodeling with reduced systolic function.

Dilated cardiomyopathy is under significant genetic influence. Using whole-genome sequencing, we found a premature stop variant (R255X) in the MYBPHL gene in a family with DCM and conduction system disease. A Mybphl null mouse model revealed systolic dysfunction with atrial and ventricular conduction system (VCS) abnormalities. We found MyBP-HL protein highly expressed in both human and mouse atria and in a subset of ventricular cardiomyocytes. We hypothesize that MyBP-HL regulates VCS function and loss of MyBP-HL causes ventricular arrhythmia and cardiac dysfunction. We now examined hearts and isolated VCMs from Mybphl WT, het, and null mice using immunofluorescence microscopy (IFM). Clusters of MyBP-HL+ ventricular cardiomyocytes were evident in WT hearts (~1/200,000), with only 10% as many MyBP-HL+ cardiomyocytes in het samples. In WT hearts, MyBP-HL+ cells localized in the right ventricular free wall, with significantly fewer MyBP-HL+ cells in the right ventricular free wall in het hearts. The VCS marker contactin-2 (Cntn2) was used to assess MyBP-HL co-localization in the VCS. MyBP-HL co-localized with Cntn2+ cardiomyocytes in the transition zone between the atria and ventricle near the AV node, as well as in a subset of Cntn2+ Purkinje fibers. MyBP-HL+ ventricular cardiomyocytes were also found outside the VCS, suggesting other roles for those cells in regulating ventricular function. To discern MyBP-HL myofilament localization, we used super-resolution structured illumination microscopy on atrial cardiomyocytes. MyBP-HL co-localized with cMyBP-C in the C-zone of the A-band but also occupied space in the inner portion of the A-band near the M-line. This localization was not altered in het mice; however, the ratio of MyBP-HL in the inner portion of the A-band was diminished in het mice compared to WT. This suggests that MyBP-HL may bind the light meromyosin coiled-coil tail that originates from the M-line. Following the discovery that loss of MyBP-HL is associated with DCM and arrhythmia, we identified that MyBP-HL associates with the VCS and reduced MyBP-HL levels reduce the amount of MyBP-HL positive VCMs. These data suggest that loss of MyBP-HL may impair the development and function of the VCS, resulting in arrhythmias.

Exon skipping uses chemically modified antisense oligonucleotides to modulate RNA splicing. Therapeutically, exon skipping can bypass mutations and restore reading frame disruption by generating internally truncated, functional proteins to rescue the loss of native gene expression. Limb-girdle muscular dystrophy type 2C is caused by autosomal recessive mutations in the SGCG gene, which encodes the dystrophin-associated protein γ-sarcoglycan. The most common SGCG mutations disrupt the transcript reading frame abrogating γ-sarcoglycan protein expression. In order to treat most SGCG gene mutations, it is necessary to skip 4 exons in order to restore the SGCG transcript reading frame, creating an internally truncated protein referred to as Mini-Gamma. Using direct reprogramming of human cells with MyoD, myogenic cells were tested with 2 antisense oligonucleotide chemistries, 2'-O-methyl phosphorothioate oligonucleotides and vivo-phosphorodiamidate morpholino oligomers, to induce exon skipping. Treatment with vivo-phosphorodiamidate morpholino oligomers demonstrated efficient skipping of the targeted exons and corrected the mutant reading frame, resulting in the expression of a functional Mini-Gamma protein. Antisense-induced exon skipping of SGCG occurred in normal cells and those with multiple distinct SGCG mutations, including the most common 521ΔT mutation. These findings demonstrate a multiexon-skipping strategy applicable to the majority of limb-girdle muscular dystrophy 2C patients.

IMPORTANCE: The genetic variant MYBPC3(Δ25bp) occurs in 4% of South Asian descendants, with an estimated 100 million carriers worldwide. MYBPC3 (Δ25bp) has been linked to cardiomyopathy and heart failure. However, the high prevalence of MYBPC3(Δ25bp) suggests that other stressors act in concert with MYBPC3(Δ25bp). OBJECTIVE: To determine whether there are additional genetic factors that contribute to the cardiomyopathic expression of MYBPC3(Δ25bp). DESIGN, SETTING, ANDPARTICIPANTS: South Asian individuals living in the United States were screened for MYBPC3(Δ25bp), and a subgroup was clinically evaluated using electrocardiograms and echocardiograms at Loyola University, Chicago, Illinois, between January 2015 and July 2016. MAIN OUTCOMES AND MEASURES: Next-generation sequencing of 174 cardiovascular disease genes was applied to identify additional modifying gene mutations and correlate genotype-phenotype parameters. Cardiomyocytes derived from human-induced pluripotent stem cells were established and examined to assess the role of MYBPC3(Δ25bp). RESULTS: In this genotype-phenotype study, individuals of South Asian descent living in the United States from both sexes (36.23% female) with a mean population age of 48.92 years (range, 18-84 years) were recruited. Genetic screening of 2401 US South Asian individuals found an MYBPC3(Δ25bp)carrier frequency of 6%. A higher frequency of missense TTN variation was found in MYBPC3(Δ25bp) carriers compared with noncarriers, identifying distinct genetic backgrounds within the MYBPC3(Δ25bp) carrier group. Strikingly, 9.6% of MYBPC3(Δ25bp) carriers also had a novel MYBPC3 variant, D389V. Family studies documented D389V was in tandem on the same allele as MYBPC3(Δ25bp), and D389V was only seen in the presence of MYBPC3(Δ25bp). In contrast to MYBPC3(Δ25bp), MYBPC3(Δ25bp/D389V) was associated with hyperdynamic left ventricular performance (mean [SEM] left ventricular ejection fraction, 66.7 [0.7%]; left ventricular fractional shortening, 36.6 [0.6%]; P

With the wider deployment of massively-parallel, next-generation sequencing, it is now possible to survey human genome data for research and clinical purposes. The reduced cost of producing short-read sequencing has now shifted the burden to data analysis. Analysis of genome sequencing remains challenged by the complexity of the human genome, including redundancy and the repetitive nature of genome elements and the large amount of variation in individual genomes. Public databases of human genome sequences greatly facilitate interpretation of common and rare genetic variation, although linking database sequence information to detailed clinical information is limited by privacy and practical issues. Genetic variation is a rich source of knowledge for cardiovascular disease because many, if not all, cardiovascular disorders are highly heritable. The role of rare genetic variation in predicting risk and complications of cardiovascular diseases has been well established for hypertrophic and dilated cardiomyopathy, where the number of genes that are linked to these disorders is growing. Bolstered by family data, where genetic variants segregate with disease, rare variation can be linked to specific genetic variation that offers profound diagnostic information. Understanding genetic variation in cardiomyopathy is likely to help stratify forms of heart failure and guide therapy. Ultimately, genetic variation may be amenable to gene correction and gene editing strategies.

Background— Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of >50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift toward comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results— Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused on 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1 to 14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and segregation analysis, where available. Three of 3 previously identified primary mutations were detected by this analysis. In 6 subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and had additional pathological correlation to provide evidence for causality. For 2 subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. Conclusions— These pilot data demonstrate that ≈30 to 40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.

Heredity strongly influences multiple cardiovascular disorders, including arrhythmia syndromes, aortic aneurysms, dyslipidemias, cardiomyopathy, and heart failure. Genetic testing has emerged as an effective clinical tool, especially in the cardiomyopathies, because it provides information useful for diagnosis and stratification.1 Genetic testing for clinical diagnosis currently relies on gene panels, where many genes are sequenced simultaneously. With gene panel sequencing, the coding regions of specific genes are first captured and then sequenced. Most mutations detected with this method are single nucleotide polymorphisms or small insertions/deletions. It is also possible to detect larger exonic-level deletions or duplications. Most cardiomyopathy mutations are inherited in an autosomal dominant manner, and these methods can detect heterozygous variants. See Article by Cirino et al Cardiomyopathy gene panels have grown in size and scope, and it has now become commonplace to evaluate 50 to 120 genes in a single test, depending on the specific cardiomyopathy subtype and accompanying cardiac arrhythmias.2 Hypertrophic cardiomyopathy (HCM) is a more genetically restricted disease compared with dilated cardiomyopathy. The majority of HCM arises from heterozygous mutations in genes encoding sarcomere proteins with MYH7 and MYBPC3 accounting for 70% to 80% of familial HCM. The limited yield of larger panels combined with the enrichment of MYH7/MYBPC3 mutations has prompted the suggestion that genetic testing for HCM should first focus on these 2 genes.3,4 In contrast, dilated cardiomyopathy is linked to many more genes, with 1 gene, TTN , accounting for 20% of genetic dilated cardiomyopathy, and ≥80 genes explaining an additional fraction.5–7 This genetic heterogeneity has led some to suggest that >1 variant may contribute to disease onset, supporting an oligogenic pathogenesis. The sensitivity of genetic panels for cardiomyopathies ranges from 30% to 50%, depending on the subtype. The rate of variant discovery should improve as …

Background: Congestive heart failure (CHF) is an increasing medical problem that is disabling and costly, and CHF currently affects more than 5 million Americans. A leading cause of CHF is cardiomyopathy, a disorder with a high heritable component. Genetic studies of familial cardiomyopathy have identified more than 50 responsible genes. Knowledge of the genetic underpinnings of disease provides prognostic information and can guide clinical decision- making. Clinical genetic testing employs gene panels for diagnosis, and typical panels include 20-100 genes. We assessed the viability of whole genome sequencing (WGS) to identify potentially pathogenic cardiomyopathy-associated genetic variants in established and novel genes. Methods: WGS was conducted on 91 families (99 individuals) with cardiomyopathy. In 46/91 (50%) families, there was a prior history of unrevealing panel-based clinical genetic testing. WGS was performed using Illumina next generation sequencing. Variants were called and annotated using MegaSeq and MegaSeq2. MegaSeq2 refines the number of candidate variants from ~4 million to Results: MegaSeq2 was applied to 99 cardiomyopathy genomes and in 45/91 families (49%), a potentially pathogenic or likely pathogenic variant was identified. Here we describe identification and segregation analysis in 4 families. Two families have unique RBM20 variants that segregate with cardiomyopathy. One family was found to carry a premature stop in SCN5A and exhibits variable phenotypes including sudden death, arrhythmia and cardiomyopathy. The fourth family has cardiomyopathy that segregates with a BAG3 early termination variant. Conclusions: WGS was able to identify potentially pathogenic variants in nearly half (45/91). While some of the variants identified were in novel genes, the majority of pathogenic variants were in established cardiomyopathy genes despite previous panel-based testing. More comprehensive analysis, like WGS, allows for re-evaluation of variation as additional genetic information becomes available.

As of 2014, cardiovascular disease (CVD) was listed as the underlying cause for 1 of every 3 deaths in the United States.1 Many forms of CVD have a strong genetic component, and the number of causal genes elucidated greatly depends on the type of CVD under study. Understanding the molecular basis of CVD can guide medical decisions of the practitioner, patient, and family members. Currently, gene panels are used in the clinical setting to screen for disease-causing variation. Panels vary greatly in size depending on the number of genetic causes of the disease in question. There is often a great deal of phenotypic overlap between the inherited CVDs. To accommodate these variable phenotypes, many testing laboratories now use large panels that include >75 genes. Another route that is more commonly being used is the use of whole exome sequencing and whole genome sequencing to identify causal and contributory variants.2,3 Whole exome sequencing or whole genome sequencing can begin with focus on rare variants in genes most commonly associated with disease, and, if no attractive candidates are identified, the search is broadened to include genes not currently associated with disease. Such broad searches can lead to the identification of new disease genes; a great benefit in the research context, but a burden in the clinical-setting making disease risk assessment more difficult. It is also an ever-evolving target to determine the amount of validation necessary to deem variants pathogenic and therefore reportable, especially when variants are unique to individuals or to individual families.4 It can be especially troubling when the disease in question involves sudden death where there is significant risk for surviving family members. It is imperative that new, potential CVD genes continue to be validated using a variety of methods, including family studies, animal- and …

Nesprins-1 and -2 are highly expressed in skeletal and cardiac muscle and together with SUN (Sad1p/UNC84)-domain containing proteins and lamin A/C form the LInker of Nucleoskeleton-and-Cytoskeleton (LINC) bridging complex at the nuclear envelope (NE). Mutations in nesprin-1/2 have previously been found in patients with autosomal dominant Emery–Dreifuss muscular dystrophy (EDMD) as well as dilated cardiomyopathy (DCM). In this study, three novel rare variants (R8272Q, S8381C and N8406K) in the C-terminus of the SYNE1 gene (nesprin-1) were identified in seven DCM patients by mutation screening. Expression of these mutants caused nuclear morphology defects and reduced lamin A/C and SUN2 staining at the NE. GST pull-down indicated that nesprin-1/lamin/SUN interactions were disrupted. Nesprin-1 mutations were also associated with augmented activation of the ERK pathway in vitro and in hearts in vivo. During C2C12 muscle cell differentiation, nesprin-1 levels are increased concomitantly with kinesin light chain (KLC-1/2) and immunoprecipitation and GST pull-down showed that these proteins interacted via a recently identified LEWD domain in the C-terminus of nesprin-1. Expression of nesprin-1 mutants in C2C12 cells caused defects in myoblast differentiation and fusion associated with dysregulation of myogenic transcription factors and disruption of the nesprin-1 and KLC-1/2 interaction at the outer nuclear membrane. Expression of nesprin-1α2 WT and mutants in zebrafish embryos caused heart developmental defects that varied in severity. These findings support a role for nesprin-1 in myogenesis and muscle disease, and uncover a novel mechanism whereby disruption of the LINC complex may contribute to the pathogenesis of DCM.

Cardiovascular disease is a major health concern affecting over 80,000,000 people in the U.S. alone. Heart failure, cardiomyopathy, heart rhythm disorders, atherosclerosis and aneurysm formation have significant heritable contribution. Supported by familial aggregation and twin studies, these cardiovascular diseases are influenced by genetic variation. Family-based linkage studies and population-based genome-wide association studies (GWAS) have each identified genes and variants important for the pathogenesis of cardiovascular disease. The advent of next generation sequencing has ushered in a new era in the genetic diagnosis of cardiovascular disease, and this is especially evident when considering cardiomyopathy, a leading cause of heart failure. Cardiomyopathy is a genetically heterogeneous disorder characterized by morphologically abnormal heart with abnormal function. Genetic testing for cardiomyopathy employs gene panels, and these panels assess more than 50 genes simultaneously. Despite the large size of these panels, the sensitivity for detecting the primary genetic defect is still only approximately 50%. Recently, there has been a shift towards applying broader exome and/or genome sequencing to interrogate more of the genome to provide a genetic diagnosis for cardiomyopathy. Genetic mutations in cardiomyopathy offer the capacity to predict clinical outcome, including arrhythmia risk, and genetic diagnosis often provides an early window in which to institute therapy. This discussion is an overview as to how genomic data is shaping the current understanding and treatment of cardiovascular disease.

Motivation: The declining cost of generating DNA sequence is promoting an increase in whole genome sequencing, especially as applied to the human genome. Whole genome analysis requires the alignment and comparison of raw sequence data, and results in a computational bottleneck because of limited ability to analyze multiple genomes simultaneously. Results: We now adapted a Cray XE6 supercomputer to achieve the parallelization required for concurrent multiple genome analysis. This approach not only markedly speeds computational time but also results in increased usable sequence per genome. Relying on publically available software, the Cray XE6 has the capacity to align and call variants on 240 whole genomes in ∼50 h. Multisample variant calling is also accelerated. Availability and implementation: The MegaSeq workflow is designed to harness the size and memory of the Cray XE6, housed at Argonne National Laboratory, for whole genome analysis in a platform designed to better match current and emerging sequencing volume. Contact: emcnally@uchicago.edu