Managing differential performance of polygenic risk scores across groups: Real-world experience of the eMERGE Network.

The differential performance of polygenic risk scores (PRSs) by group is one of the major ethical barriers to their clinical use. It is also one of the main practical challenges for any implementation effort. The social repercussions of how people are grouped in PRS research must be considered in communications with research participants, including return of results. Here, we outline the decisions faced and choices made by a large multi-site clinical implementation study returning PRSs to diverse participants in handling this issue of differential performance. Our approach to managing the complexities associated with the differential performance of PRSs serves as a case study that can help future implementers of PRSs to plot an anticipatory course in response to this issue.

Risk factors affecting polygenic score performance across diverse cohorts.

Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed effects of covariate stratification and interaction on body mass index (BMI) PGS (PGSBMI) across four cohorts of European (N=491,111) and African (N=21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R2 being nearly double between best and worst performing quintiles for certain covariates. 28 covariates had significant PGSBMI-covariate interaction effects, modifying PGSBMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R2 differences among strata and interaction effects - across all covariates, their main effects on BMI were correlated with their maximum R2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGSBMI individuals have highest R2 and increase in PGS effect. Using quantile regression, we show the effect of PGSBMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGSBMI performance and effects, we investigated ways to increase model performance taking into account non-linear effects. Machine learning models (neural networks) increased relative model R2 (mean 23%) across datasets. Finally, creating PGSBMI directly from GxAge GWAS effects increased relative R2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGSBMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.

The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the young.

BACKGROUND: Sudden 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. METHODS: The SDY Case Registry is a National Institutes of Health/Centers for Disease Control and Prevention 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 < 20 years of age. SDY cases were collected from medical examiner and coroner offices spanning 13 US jurisdictions from 2015 to 2019. The cohort included 211 children (median age 0.33 year; range 0-20 years), determined to have died suddenly and unexpectedly and from whom DNA biospecimens for DNA extractions and next-of-kin consent were ascertained. A control cohort consisted of 211 randomly sampled, sex- and ancestry-matched individuals from the 1000 Genomes Project. Genetic variation was evaluated in epilepsy, cardiomyopathy, and arrhythmia genes in the SDY and control cohorts. American College of Medical Genetics/Genomics guidelines were used to classify variants as pathogenic or likely pathogenic. Additionally, pathogenic and likely pathogenic genetic variation was identified using a Bayesian-based artificial intelligence (AI) tool. RESULTS: The SDY cohort was 43% European, 29% African, 3% Asian, 16% Hispanic, and 9% 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, potentially damaging variants in epilepsy, cardiomyopathy, and arrhythmia-related genes. A greater number of rare epilepsy genetic variants correlated with younger age at death. CONCLUSIONS: While 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.

Identification of Clinical Drivers of Left Atrial Enlargement Through Genomics of Left Atrial Size.

BACKGROUND: Greater left atrial size is associated with a higher incidence of cardiovascular disease and mortality, but the full spectrum of diagnoses associated with left atrial enlargement in sex-stratified clinical populations is not well known. Our study sought to identify genetic risk mechanisms affecting left atrial diameter (LAD) in a clinical cohort. METHODS: Using Vanderbilt deidentified electronic health record, we studied 6163 females and 5993 males of European ancestry who had at least 1 LAD measure and available genotyping. A sex-stratified polygenic score was constructed for LAD variation and tested for association against 1680 International Classification of Diseases code-based phenotypes. Two-sample univariable and multivariable Mendelian randomization approaches were used to assess etiologic relationships between candidate associations and LAD. RESULTS: A phenome-wide association study identified 25 International Classification of Diseases code-based diagnoses in females and 11 in males associated with a polygenic score of LAD (false discovery rate q<0.01), 5 of which were further evaluated by Mendelian randomization (waist circumference [WC], atrial fibrillation, heart failure, systolic blood pressure, and coronary artery disease). Sex-stratified differences in the genetic associations between risk factors and a polygenic score for LAD were observed (WC for females; heart failure, systolic blood pressure, atrial fibrillation, and WC for males). By multivariable Mendelian randomization, higher WC remained significantly associated with larger LAD in females, whereas coronary artery disease, WC, and atrial fibrillation remained significantly associated with larger LAD in males. CONCLUSIONS: In a clinical population, we identified, by genomic approaches, potential etiologic risk factors for larger LAD. Further studies are needed to confirm the extent to which these risk factors may be modified to prevent or reverse adverse left atrial remodeling and the extent to which sex modifies these risk factors.

Common- and rare-variant genetic architecture of heart failure across the allele frequency spectrum.

Heart failure (HF) is a complex trait, influenced by environmental and genetic factors, that affects over 30 million individuals worldwide. Historically, the genetics of HF have been studied in Mendelian forms of disease, where rare genetic variants have been linked to familial cardiomyopathies. More recently, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with risk of HF. However, the relative importance of genetic variants across the allele-frequency spectrum remains incompletely characterized. Here, we report the results of common- and rare-variant association studies of all-cause heart failure, applying recently developed methods to quantify the heritability of HF attributable to different classes of genetic variation. We combine GWAS data across multiple populations including 207,346 individuals with HF and 2,151,210 without, identifying 176 risk loci at genome-wide significance (p < 5×10-8). Signals at newly identified common-variant loci include coding variants in Mendelian cardiomyopathy genes (MYBPC3, BAG3), as well as regulators of lipoprotein (LPL) and glucose metabolism (GIPR, GLP1R), and are enriched in cardiac, muscle, nerve, and vascular tissues, as well as myocyte and adipocyte cell types. Gene burden studies across three biobanks (PMBB, UKB, AOU) including 27,208 individuals with HF and 349,126 without uncover exome-wide significant (p < 3.15×10-6) associations for HF and rare predicted loss-of-function (pLoF) variants in TTN, MYBPC3, FLNC, and BAG3. Total burden heritability of rare coding variants (2.2%, 95% CI 0.99-3.5%) is highly concentrated in a small set of Mendelian cardiomyopathy genes, and is lower than heritability attributable to common variants (4.3%, 95% CI 3.9-4.7%) which is more diffusely spread throughout the genome. Finally, we demonstrate that common-variant background, in the form of a polygenic risk score (PRS), significantly modifies the risk of HF among carriers of pathogenic truncating variants in the Mendelian cardiomyopathy gene TTN. These findings suggest a significant polygenic component to HF exists that is not captured by current clinical genetic testing.

The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the young.

Background: Sudden 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. Methods: The 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 <20 years of age. SDY cases were collected from medical examiner and coroner offices spanning 13 US jurisdictions from 2015-2019. The cohort included 211 children (mean age 1 year; range 0-20 years), determined to have died suddenly and unexpectedly and in whom DNA biospecimens and next-of-kin consent were ascertained. A control cohort consisted of 211 randomly sampled, sex-and ancestry-matched individuals from the 1000 Genomes Project. Genetic variation was evaluated in epilepsy, cardiomyopathy and arrhythmia genes in the SDY and control cohorts. American College of Medical Genetics/Genomics guidelines were used to classify variants as pathogenic or likely pathogenic. Additionally, genetic variation predicted to be damaging was identified using a Bayesian-based artificial intelligence (AI) tool. Results: The 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. Conclusions: While 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.

Opposing effects of genetic variation in MTCH2 for obesity versus heart failure.

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.

Quantifying factors that affect polygenic risk score performance across diverse ancestries and age groups for body mass index.

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.

Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure.

Heart failure is a leading cause of cardiovascular morbidity and mortality. However, the contribution of common genetic variation to heart failure risk has not been fully elucidated, particularly in comparison to other common cardiometabolic traits. We report a multi-ancestry genome-wide association study meta-analysis of all-cause heart failure including up to 115,150 cases and 1,550,331 controls of diverse genetic ancestry, identifying 47 risk loci. We also perform multivariate genome-wide association studies that integrate heart failure with related cardiac magnetic resonance imaging endophenotypes, identifying 61 risk loci. Gene-prioritization analyses including colocalization and transcriptome-wide association studies identify known and previously unreported candidate cardiomyopathy genes and cellular processes, which we validate in gene-expression profiling of failing and healthy human hearts. Colocalization, gene expression profiling, and Mendelian randomization provide convergent evidence for the roles of BCKDHA and circulating branch-chain amino acids in heart failure and cardiac structure. Finally, proteome-wide Mendelian randomization identifies 9 circulating proteins associated with heart failure or quantitative imaging traits. These analyses highlight similarities and differences among heart failure and associated cardiovascular imaging endophenotypes, implicate common genetic variation in the pathogenesis of heart failure, and identify circulating proteins that may represent cardiomyopathy treatment targets.

Partial and complete loss of myosin binding protein H-like cause cardiac conduction defects.

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.

Genetically based atrial fibrillation: Current considerations for diagnosis and management.

Atrial fibrillation (AF) is the most common atrial arrhythmia and is subcategorized into numerous clinical phenotypes. Given its heterogeneity, investigations into the genetic mechanisms underlying AF have been pursued in recent decades, with predominant analyses focusing on early onset or lone AF. Linkage analyses, genome-wide association studies (GWAS), and single gene analyses have led to the identification of rare and common genetic variants associated with AF risk. Significant overlap with genetic variants implicated in dilated cardiomyopathy syndromes, including truncating variants of the sarcomere protein titin, have been identified through these analyses, in addition to other genes associated with cardiac structure and function. Despite this, widespread utilization of genetic testing in AF remains hindered by the unclear impact of genetic risk identification on clinical outcomes and the high prevalence of variants of unknown significance (VUS). However, genetic testing is a reasonable option for patients with early onset AF and in those with significant family history of arrhythmia. While many knowledge gaps remain, emerging data support genotyping to inform selection of AF therapeutics. In this review, we highlight the current understanding of the complex genetic basis of AF and explore the overlap of AF with inherited cardiomyopathy syndromes. We propose a set of criteria for clinical genetic testing in AF patients and outline future steps for the integration of genetics into AF care.

Genomic Autopsy of Sudden Deaths in Young Individuals.

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.

Mitochondrial cardiomyopathy and ventricular arrhythmias associated with biallelic variants in C1QBP.

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).

Genomic Context Differs Between Human Dilated Cardiomyopathy and Hypertrophic Cardiomyopathy.

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.

Identification of Cardiac Fibrosis in Young Adults With a Homozygous Frameshift Variant in SERPINE1.

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 ß, 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) in SERPINE1, 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 the SERPINE1 c.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_700dupTA SERPINE1 was 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 the SERPINE1 c.699_700dupTA variant exhibited susceptibility to cardiomyocyte injury in response to angiotensin II (increased transforming growth factor ß1 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 the SERPINE1 c.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 for SERPINE1 was identified, suggesting an optimal range of PAI-1 levels are needed for cardiac homeostasis.

Genetic Variation in Enhancers Modifies Cardiomyopathy Gene Expression and Progression.

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.