Variants with population maximum allele frequency ≥0.005 in the Genome Aggregation Database (gnomAD) were excluded. Predicted loss-of-function variants do not necessarily all meet current standards to be classified as pathogenic or likely pathogenic based on current American College of Medical Genetics (ACMG)/Association of Molecular Pathology criteria.
A, Distribution of left ventricular (LV) ejection fractions between carriers and noncarriers of cardiomyopathy variants, measured by echocardiography and adjusted for age and sex. B, Cumulative incidence of all-cause mortality over the length of follow-up stratified by cardiomyopathy variant carrier status, with results over follow-up period estimated using a Cox proportional hazards regression model standardized to age, sex, and the first 4 principal components of genetic ancestry. C, Raw cumulative incidence of outcome by age 75 years, stratified by carrier status.
A, Distribution of left ventricular (LV) ejection fractions between carriers and noncarriers of cardiomyopathy variants, measured by cardiac magnetic resonance imaging and adjusted for age and sex. B, Cumulative incidence of all-cause mortality over the length of follow-up stratified by cardiomyopathy variant carrier status, with results over follow-up period estimated using a Cox proportional hazards regression model standardized to age, sex, and the first 4 principal components of genetic ancestry. C, Raw cumulative incidence of outcome by age 75 years, stratified by variant carrier status.
eMethods. Study Cohorts, Exome Sequencing, Variant Quality Control and Classification, and Statistical Analysis
eTable 1. Curated Pathogenic and Likely Pathogenic Variants in Atherosclerosis in Risk Communities
eTable 2. Curated Pathogenic and Likely Pathogenic Variants in UK Biobank
eTable 3. General Imaging and Electrocardiographic Characteristics of Carriers and Noncarriers of Pathogenic Inherited Cardiomyopathy Variants
eTable 4. Additional Echocardiographic Findings in Carriers and Noncarriers of Pathogenic Cardiomyopathy Variants in Atherosclerosis in Risk Communities
eTable 5. Heart Failure Diagnosis and Medication Use Among Carriers and Noncarriers of Pathogenic Cardiomyopathy Variants in the UK Biobank
eFigure 1. Association of Pathogenic or Likely Pathogenic Variants for Actionable Inherited Cardiomyopathies, Incident Outcomes
eFigure 2. Cumulative Incidence of Outcome by Age 75 in Atherosclerosis in Risk Communities, African Ancestry
eFigure 3. Cumulative Incidence of Outcome by Age 75 in Atherosclerosis in Risk Communities, European Ancestry
eFigure 4. Association of Pathogenic or Likely Pathogenic Variants for Actionable Inherited Cardiomyopathies, Incident Outcomes in Atherosclerosis in Risk Communities Stratified by Ancestry
eFigure 5. Association of Pathogenic or Likely Pathogenic Variants for Actionable Inherited Cardiomyopathies in UK Biobank, Prevalent Disease
eFigure 6. Association of Pathogenic or Likely Pathogenic Variants for Actionable Inherited Cardiomyopathies in UK Biobank, Incident Arrhythmias
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Patel AP, Dron JS, Wang M, et al. Association of Pathogenic DNA Variants Predisposing to Cardiomyopathy With Cardiovascular Disease Outcomes and All-Cause Mortality. JAMA Cardiol. 2022;7(7):723–732. doi:10.1001/jamacardio.2022.0901
What is the prevalence and clinical importance of pathogenic variants in genes implicated in inherited cardiomyopathy?
In this genetic association study of 9667 participants in the US (Atherosclerosis in Risk Communities [ARIC]) and 49 744 participants in the UK (UK Biobank), a pathogenic or likely pathogenic variant for inherited cardiomyopathy was identified in 0.61% of ARIC participants and 0.73% of UK Biobank participants. These individuals were at 1.7- to 2.1-fold increased risk of heart failure, 2.1- to 2.9-fold increased risk of atrial fibrillation, and 1.5- to 1.7-fold increased risk of all-cause mortality, and they were not reliably identified by imaging.
Study results suggest that 0.7% of participants harbor a pathogenic variant related to inherited cardiomyopathy and are at increased risk of cardiovascular morbidity and all-cause mortality.
Pathogenic variants associated with inherited cardiomyopathy are recognized as important and clinically actionable when identified, leading some clinicians to recommend population-wide genomic screening.
To determine the prevalence and clinical importance of pathogenic variants associated with inherited cardiomyopathy within the context of contemporary clinical care.
Design, Setting, and Participants
This was a genetic association study of participants in Atherosclerosis in Risk Communities (ARIC), recruited from 1987 to 1989, with median follow-up of 27 years, and the UK Biobank, recruited from 2006 to 2010, with median follow-up of 10 years. ARIC participants were recruited from 4 sites across the US. UK Biobank participants were recruited from 22 sites across the UK. Participants in the US were of African and European ancestry; those in the UK were of African, East Asian, South Asian, and European ancestry. Statistical analyses were performed between August 1, 2021, and February 9, 2022.
Rare genetic variants predisposing to inherited cardiomyopathy.
Main Outcomes and Measures
Pathogenicity of observed DNA sequence variants in sequenced exomes of 13 genes (ACTC1, FLNC, GLA, LMNA, MYBPC3, MYH7, MYL2, MYL3, PRKAG2, TNNI3, TNNT2, TPM1, and TTN) associated with inherited cardiomyopathies were classified by a blinded clinical geneticist per American College of Medical Genetics recommendations. Incidence of all-cause mortality, heart failure, and atrial fibrillation were determined. Cardiac magnetic resonance imaging, echocardiography, and electrocardiogram measures were assessed in a subset of participants.
A total of 9667 ARIC participants (mean [SD] age, 54.0 [5.7] years; 4232 women [43.8%]; 2658 African [27.5%] and 7009 European [72.5%] ancestry) and 49 744 UK Biobank participants (mean [SD] age, 57.1 [8.0] years; 27 142 women [54.5%]; 1006 African [2.0%], 173 East Asian [0.3%], 939 South Asian [1.9%], and 46 449 European [93.4%] European ancestry) were included in the study. Of those, 59 participants (0.61%) in ARIC and 364 participants (0.73%) in UK Biobank harbored an actionable pathogenic or likely pathogenic variant associated with dilated or hypertrophic cardiomyopathy. Carriers of these variants were not reliably identifiable by imaging. However, the presence of these variants was associated with increased risk of heart failure (hazard ratio [HR], 1.7; 95% CI, 1.1-2.8), atrial fibrillation (HR, 2.9; 95% CI, 1.9-4.5), and all-cause mortality (HR, 1.5; 95% CI, 1.1-2.2) in ARIC. Similar risk patterns were observed in the UK Biobank.
Conclusions and Relevance
Results of this genetic association study suggest that approximately 0.7% of study participants harbored a pathogenic variant associated with inherited cardiomyopathy. These variant carriers would be challenging to identify within clinical practice without genetic testing but are at increased risk for cardiovascular disease and all-cause mortality.
Congestive heart failure is responsible for a significant and growing burden of morbidity and mortality within the US.1 Genetic etiologies play an important role in predisposing a subset of individuals with a pathogenic variant to developing heart failure.
The American College of Medical Genetics and Genomics (ACMG) has compiled a list of genes within which specific variants are known to be causal in certain disorders and for which established clinical interventions exist for disease prevention or treatment.2,3 Thirteen of these genes contain variants known to cause inherited cardiomyopathies.4 Pathogenic variants in ACTC1, FLNC, GLA, LMNA, MYBPC3, MYH7, MYL2, MYL3, PRKAG2, TNNI3, TNNT2, TPM1, and TTN perturb key pathways in cardiac myocyte development and contraction.5-8
Similar to other genomic conditions, genetic cardiomyopathies remain underdiagnosed and undertreated in current clinical practice.9 The majority of individuals carrying pathogenic variants present after disease has already manifested. As heart failure often results from ubiquitous causes, many individuals do not undergo further genetic workup. Additionally, available estimates of prevalence of these cardiomyopathies vary significantly depending on source of ascertainment.10
In contrast to the commonly pursued phenotype-first practice, a genome-first approach, where knowledge of genetic variant carrier status is used to study and inform clinical management, has considerable potential to reduce morbidity by diagnosing and treating these conditions at an early stage. In select individuals where cardiomyopathy variant panels are assessed, cascade screening for family members may be offered if an individual is found to be a carrier of a pathogenic gene variant.11 If found early, validated monitoring strategies exist for asymptomatic carriers, and established goal-directed medical therapies exist for individuals with heart failure.12,13
Population genomic screening for inherited cardiomyopathies to facilitate earlier detection and implementation of risk mitigation strategies are increasingly feasible with falling sequencing costs and the advent of biobanks spanning large health care systems. However, several key uncertainties remain. First, the prevalence of actionable pathogenic variants for cardiomyopathy curated using exome sequencing and clinical-grade variant classification in a large, unascertained population is unknown. Prior studies have been limited by size,14 ascertained based on imaging findings,15 restricted to variants in a single gene,16,17 focused on largely European ancestry data sets,18 or lacked full manual curation of pathogenic variants by medical geneticists.19 Second, the relative risk of morbidity and mortality associated with these variants in aggregate is not fully characterized. Previous studies using manual curation of pathogenic variants have been underpowered to thoroughly evaluate a range of clinical end points.14 Third, it is unclear if early phenotypic signatures are present in these variant carriers that would inform more targeted genomic screening. Current clinical diagnostic criteria are used to identify individuals with manifest disease.12,20
We used gene sequencing data from individuals in the Atherosclerosis Risk in Communities (ARIC) study to perform blinded clinical-grade variant classification in cardiomyopathy-related genes identified by the ACMG. We then assessed the prevalence of carriers of these variants, their association with mortality and cardiovascular outcomes, and their early phenotypic signatures. We replicated these findings in the UK Biobank.
This genetic association study was approved by the Mass General Brigham institutional review board. All participants provided written informed consent. Information regarding ancestry was studied to assess heterogeneity in variant classification or association across groups. This study followed the Strengthening the Reporting of Genetic Association Studies (STREGA) reporting guidelines.
The ARIC study is a prospective cohort that enrolled approximately 15 000 participants between the ages of 45 and 64 years, starting in 1987.21 After an initial set of surveys at enrollment examining heart disease risk factors, surveillance data on hospitalization cause and death were collected, and participants were reassessed through study visits up to 2017. African and European ancestry were inferred from individual self-report of race as being either Black or White, respectively. A total of 9667 individuals with exome sequencing data available were included in this analysis. A subset of these individuals had echocardiograms (21 of 65 carriers [32.3%] and 6848 of 9551 noncarriers [71.7%]) and electrocardiograms (ECGs; 46 of 65 carriers [70.8%] and 3477 of 9551 noncarriers [36.4%]) performed. Further details are available in the eMethods in the Supplement.
The UK Biobank (UKBB) is a prospective cohort study that enrolled over 500 000 individuals between the ages of 40 and 69 years between 2006 and 2010.22,23 African, East Asian, South Asian, or European ancestry were inferred from individual self-report of ethnic background as being either Black, Asian, Chinese, or White, respectively. A total of 49 744 participants with whole-exome sequencing data available were included in this analysis. A detailed questionnaire completed by UKBB participants at enrollment assessed family history of heart disease, heart disease risk factors, and social and lifestyle factors. A subset of the participants underwent cardiac magnetic resonance imaging (92 of 364 carriers [25.3%] and 12 727 of 49 371 noncarriers [25.8%]) and another portion underwent ECG (90 of 364 carriers [24.7%] and 12 212 of 49 371 noncarriers [24.7%]). Further details are available in the eMethods in the Supplement.
Whole-exome sequencing was performed in ARIC participants and UKBB participants as previously described.24-26 Additional details with respect to sequencing and quality control are available in the eMethods in the Supplement. An American Board of Medical Genetics and Genomics board-certified laboratory geneticist blinded to any phenotype information classified the pathogenicity of observed variants in 13 genes related to dilated, hypertrophic, or other inherited cardiomyopathy according to current clinical standards9,27(eTables 1 and 2 in the Supplement). These 13 genes included ACTC1, FLNC, GLA, LMNA, MYBPC3, MYH7, MYL2, MYL3, PRKAG2, TNNI3, TNNT2, TPM1, and TTN as outlined in the most recent list of genes for reporting secondary findings in clinical sequencing by the ACMG.4
The primary end point studied was all-cause mortality. Within ARIC, death of study participants was ascertained through annual cohort follow-up, community-wide hospital surveillance, and linkage with national death registries. Additional end points included hospitalizations for heart failure and atrial fibrillation and diagnoses of dilated cardiomyopathy and hypertrophic cardiomyopathy (HCM). Incidence of heart failure and atrial fibrillation events was determined through cohort-wide surveillance for hospitalizations with disease-related International Statistical Classification of Diseases and Related Health Problems, Ninth (ICD-9) and Tenth Revision (ICD-10) discharge codes, abstraction by chart review, and adjudication by physicians, as previously described.28 Dilated and HCM diagnoses in ARIC were determined based on ICD-9 and ICD-10 codes for these conditions used during heart failure-related hospitalizations and did not undergo clinical adjudication.29 Case definitions for all end points in the UKBB were defined using a combination of self-reported data confirmed by trained health care professionals, hospitalization records, and death registries, as previously described.30,31
A 12-lead resting ECG was recorded according to the ARIC study protocol and were read by blinded coders using the Minnesota Code.32 UKBB participants underwent 12-lead ECG assessment (GE Cardiac Acquisition Module CAM-14) during the imaging assessment and were interpreted with help from GE CardioSoft system, with full procedures described elsewhere.33,34 Echocardiograms in the ARIC cohort were performed from 2011 to 2013 using dedicated iE33 ultrasound systems with Vision 2011 (Philips) and X5-1 xMatrix transducer for 2-dimensional, Doppler, and 3-dimensional data acquisition. Details of the procedures for echocardiography have been previously published.35 Cardiac magnetic resonance imaging in the UKBB cohort was performed with 1.5-T scanners (MAGNETOM Aera, Syngo Platform vD13A [Siemens Healthineers]) with ECG gating for cardiac synchronization.36 Further data acquisition and processing is detailed in the eMethods in the Supplement.
Comparison of baseline and phenotypic characteristics between carriers of pathogenic or likely pathogenic variants and noncarriers was performed with the χ2 test for categorical variables, and analysis of variance for continuous variables. Individuals with missing component data were excluded from respective analyses. The cumulative incidence of death was determined for each ancestry through summing of events over follow-up time, adjusted for age, sex, and the first 4 principal components of genetic ancestry.37 The cumulative incidence of outcome by age 75 years in variant carriers and noncarriers was quantified using an unadjusted Cox proportional-hazards model. Hazard ratios (HRs) for clinical end point incidence comparing carriers with noncarriers were calculated using Cox proportional-hazard models using covariates of enrollment age, sex, and the first 4 principal components of genetic ancestry after excluding individuals with prevalent disease at enrollment. Two-tailed statistical testing was performed with significance set at P < .05. Statistical analyses were performed with the use of R software, version 3.5 (R Project for Statistical Computing). Statistical analyses were performed between August 1, 2021, and February 9, 2022.
A total of 9667 ARIC participants (mean [SD] age, 54.0 [5.7] years; 4232 women [43.8%]; 5435 men [56.2%]; 2658 African [27.5%] and 7009 European [72.5%] ancestry) and 49 735 UKBB participants (mean [SD] age, 57.1 [8.0] years; 27 142 women [54.6%]; 22 593 men [45.4%]; 1006 African [2.0%], 173 East Asian [0.3%], 939 South Asian [1.9%], and 46 449 European [93.4%] ancestry) were included in the study. Sequencing of 9667 ARIC participants identified 14 812 total variants present in the 13 genes known to be causal for inherited cardiomyopathies. Initial bioinformatic filtering restricted these variants to those predicted to result in loss-of-function or rare missense variants (the maximum population allele frequency <0.005 in gnomAD, a publicly available genetic variant frequency database)38-40(Figure 1). This filtering resulted in 1528 candidate variants for subsequent classification, performed according to current ACMG criteria by laboratory geneticists blinded to any phenotype information.27 A total of 59 variants met stringent clinical criteria to be classified as pathogenic or likely pathogenic (eTable 1 in the Supplement). The majority of these variants were found in TTN, MYH7, and MYBPC3.
In ARIC, a total of 59 individuals harbored any one of these pathogenic or likely pathogenic variants for dilated cardiomyopathy or HCM, corresponding to a prevalence of 0.61%. Of these carriers, 11 (18.6%) were of African ancestry and 48 (81.4%) were of European ancestry, corresponding to stratified carrier prevalence of 0.41% among African ancestry individuals and 0.68% among European ancestry individuals (Table). These 59 individuals included 30 (0.3%) with a variant specifically predisposing to dilated cardiomyopathy and 29 participants (0.3%) with a variant specifically predisposing to HCM (eFigure 1 in the Supplement). Baseline characteristics of carriers and noncarriers of pathogenic or likely pathogenic variants did not vary significantly and are provided in the Table.
Among the subset of ARIC participants who had echocardiography and ECG measurements available, carriers of pathogenic cardiomyopathy variants exhibited subtle, expected trends in cardiac function; however, they did not appear to have a distinct identifiable phenotypic signature. Overall, carriers of pathogenic variants associated with dilated cardiomyopathies had lower mean (SD) ejection fractions (EFs; 58.9% [14.8%]) and those with HCM had higher mean (SD) EFs (65.8% [6.7%]) when compared with noncarriers (64.9% [7.0%]); however, the majority still fell within the normal range (Figure 2A; eTable 3 in the Supplement). Modestly significant associations were noted between carrier status and parameters of diastolic function (eTable 4 in the Supplement). Notably, no carriers of the HCM variant in ARIC had interventricular wall thickness greater than 15 mm (supporting diagnosis of HCM), and only one was found to have hyperdynamic EF (left ventricular EF >75%) (eTable 3 in the Supplement).
Individuals who harbored a pathogenic or likely pathogenic variant were found to experience increased risk of all-cause mortality. In ARIC, 36 carriers (65.5%) compared with 4144 noncarriers (46.7%) had died over a median of 27 (IQR, 19-28) years of follow-up, corresponding to an HR of 1.5 (95% CI, 1.1-2.2; P = .01) (Figure 2B; eFigure 1 in the Supplement). Examining the absolute incidence of clinical events by age 75 years reinforced the clinical importance of these increased risk estimates. The cumulative risk of death was 33.3% in carriers and 23.6% in noncarriers, respectively (Figure 2C).
Carriers of pathogenic or likely pathogenic variants were also found to experience substantially increased risk of additional cardiovascular end points. Within ARIC, 16 carriers (33.3%) compared with 1833 noncarriers (22%) experienced hospitalization related to heart failure in the follow-up period, corresponding to an HR of 1.7 (95% CI, 1.1-2.8; P = .03). This translated to a cumulative incidence of heart failure by age 75 of 14.1% in carriers and 9.1% in noncarriers. Carriers of pathogenic variants associated with inherited cardiomyopathies were also found to have increased risk of hospitalization with atrial fibrillation compared with noncarriers in ARIC (HR, 2.9; 95% CI, 1.9-4.5; P < .001), with cumulative incidence by age 75 years of 15.6% for carriers and 6.0% for noncarriers (Figure 2C). Although variant carriers had significantly higher risk of being diagnosed with dilated cardiomyopathy (HR, 4.2; 95% CI, 2.1-8.4; P < .001) and HCM (HR, 30.5; 95% CI, 3.8-246.1; P < .001), the absolute incidence of these outcomes was low.
Within ARIC, we examined the association of pathogenic variants with disease stratified by ancestry and found that individuals of African ancestry had higher absolute incidence of outcomes when compared with individuals of European ancestry. By age 75 years, 45.5% of variant carriers (5 of 11) of African ancestry had died compared with 32.6% of noncarriers (863 of 2647); this is in comparison with 30.2% mortality in carriers of European ancestry compared with 20.4% in noncarriers (eFigures 2 and 3 in the Supplement). However, the relative risk of mortality associated with carrier status was similar among individuals of African (HR, 1.4; 95% CI, 0.6-3.1; P = .41) and European ancestry (HR, 1.6; 95% CI, 1.1-2.3; P = .01; P for heterogeneity = 0.79 across ancestries). Similar trends existed across the other examined clinical outcomes (eFigure 4 in the Supplement).
Analysis of data from the UKBB yielded similar findings, collectively confirming and extending results from other recent studies.17,19 Sequencing of 49 744 UKBB participants identified 86 029 total variants present in the 13 genes known to be causal for inherited cardiomyopathies. Further filtering and blinded classification using current ACMG clinical criteria identified 226 pathogenic or likely pathogenic variants for HCM or dilated cardiomyopathy carried by a total of 364 individuals in the UKBB, corresponding to a prevalence of 0.73% (eTable 2 in the Supplement). The majority of these variants were also found in TTN, MYBPC3, and MYH7. These individuals included 183 with a variant predisposing specifically to dilated cardiomyopathy and 181 participants with a variant predisposing specifically to HCM.
Cardiomyopathy variant carrier status had similar clinical consequences in the UKBB cohort. Among UKBB participants with cardiac magnetic resonance imaging measurements available, carriers of pathogenic variants associated with dilated (EF, 59%) and hypertrophic cardiomyopathies (EF, 68%) had lower and higher mean EFs when compared with noncarriers (EF, 65%), respectively, however the majority still fell within the normal range (Figure 3A; eTable 3 in the Supplement). A higher percentage of carriers of pathogenic variants associated with dilated cardiomyopathy had an EF less than 50% (4 of 183 [8.9%]) when compared with noncarriers (147 of 49 552 [1.2%]). Individuals with prevalent disease at enrollment were significantly enriched for pathogenic variant carriers (15 of 303 individuals [5.0%] with heart failure and 25 of 968 individuals [2.6%] with atrial fibrillation) relative to individuals who would be diagnosed with incident disease in the follow-up period (16 of 1102 individuals [1.5%] with heart failure and 30 of 2137 individuals [1.4%] with atrial fibrillation). Pathogenic variant carrier status was associated with risk of prior heart failure (odds ratio [OR], 7.3; 95% CI, 4.3-12.5; P < .001) and prior atrial fibrillation (OR, 3.8; 95% CI, 2.5-5.8; P < .001) (eFigure 5 and eTable 5 in the Supplement).
In the UKBB, 26 of 364 carriers (7.1%) compared with 2112 of 49 371 noncarriers (4.3%) had died over a median of 10.0 (IQR, 9.9-10.2) years of follow-up, corresponding to an HR of 1.7 (95% CI, 1.1-2.5; P = .009) (Figure 3B) and cumulative incidence of all-cause mortality by age 75 years of 12.1% among carriers and 7.8% among noncarriers. Similarly, in the UKBB, 16 of 349 carriers (4.6%) were diagnosed with a new heart failure event compared with 1086 of 49 077 noncarriers (2.2%), corresponding to an HR of 2.1 (95% CI, 1.3-3.4; P = .004) and a cumulative incidence of heart failure by age 75 years of 7.8% among carriers and 4.1% among noncarriers (Figure 2C; eFigure 1 in the Supplement). Additionally, 30 of 339 carriers (8.8%) were diagnosed with new atrial fibrillation compared with 2107 of 48 422 noncarriers (4.4%), corresponding to an HR of 2.1 (95% CI, 1.5-3.0; P < .0001) and a cumulative incidence of atrial fibrillation by age 75 years of 15.7% among carriers and 8.3% among noncarriers. Furthermore, carriers also experienced increased incidence of ventricular tachycardia (HR, 3.7; 95% CI, 1.9-7.1; P < .001) diagnoses or underwent implantable cardioverter defibrillator placement (HR, 7.1; 95% CI, 3.1-16.1; P < .001) when compared with noncarriers (eFigure 6 in the Supplement). Carriers of pathogenic cardiomyopathy variants in the UKBB also had higher risk but low absolute incidence of dilated cardiomyopathy (HR, 10; 95% CI, 2.4-42.2; P < .001) and hypertrophic cardiomyopathy (HR, 9.5; 95% CI, 3.8-23.6; P < .001) diagnoses, relative to noncarriers.
In this genetic association study, among 59 409 middle-aged individuals across 2 large prospective cohort studies, 423 (0.7%) harbored an actionable pathogenic or likely pathogenic variant associated with dilated cardiomyopathy (59 [0.61%]) or HCM (364 [0.73%]). Presence of these variants was associated with 1.5- to 1.7-fold increased risk of death, 1.7- to 2.1-fold increased risk of heart failure, and 2.0- to 2.9-fold increased risk of atrial fibrillation across studies despite contemporary clinical care and could not be reliably identified based on imaging or electrocardiography signatures.
These results build upon previous efforts to understand the prevalence and clinical importance of monogenic risk variants for cardiomyopathy in several key ways. First, blinded manual classification of genetic variants identified using systematic gene sequencing was performed by a clinical laboratory geneticist using ACMG standards. Second, estimates of increased risks for all-cause mortality and each cardiovascular end point were provided within the context of clinical care. Third, individuals from 2 prospective cohorts spanning the UK and US were analyzed. Although a subset of participants reported African and Asian ancestry, this made up a small portion of the entire study population. We confirmed prior reports of lower rates of identification of pathogenic variants in non-European groups, which could be potentially be related to limitations in databases of genetic variation or case-control studies in non-European populations.41 Fourth, availability of deep phenotyping data on all participants and imaging data on a subset of participants allowed assessment for heterogeneity in phenotypic signatures.
These results suggest that individuals with DNA variants predisposing to cardiomyopathy have variable penetrance of disease and will be difficult to reliably identify without direct gene sequencing. In this study, heart failure was reported in only a minority of those who harbored a pathogenic or likely pathogenic variant. Imaging data demonstrated modest variation in quantitative parameters but no distinct signature that could distinguish carriers from noncarriers. Although variability in this penetrance is thought to be influenced by comorbidities and environmental exposures, a recent study identified a significant association of HCM penetrance with male sex.42 Furthermore, within given genes, whether or not a variant is protein-truncating or located in a specific structural domain can further lead to heterogeneity in effects.43 To help address difficulties in phenomapping approaches associated with incomplete penetrance, recent studies demonstrated the potential of using machine learning algorithms to analyze electronic medical record and imaging data to help identify individuals with wildtype cardiac amyloidosis.44-46 Additional studies have highlighted roles that machine learning applied to imaging data could play in the early identification of cardiac pathology, which could enable new genetic discoveries.19,47-49
Although current guidelines for the management of heart failure focus on treatment once patients are symptomatic or have evidence of significant cardiac dysfunction, knowledge of pathogenic variant carrier status early on in life may offer a potential opportunity for disease prevention in these individuals.12 Recent studies have demonstrated an important role of more intensive blood pressure lowering in reducing the risk of incident heart failure and atrial fibrillation in the population, and this could be more routinely applied in cardiomyopathy variant carriers.50-52 Similarly, within the Valsartan for Attenuating Disease Evolution in Early Sarcomeric HCM trial (VANISH), treatment with valsartan was associated with improvement in measures of cardiac structure and function in asymptomatic carriers of sarcomeric HCM variants.53,54 In patients with hypertrophic obstructive cardiomyopathy, targeted therapy with mavacamten has been shown to improve functional capacity and other parameters.55 Similar randomized clinical trials of preventative therapies could be designed for carriers of variants in other genes regardless of stage of disease present.
These results should be interpreted within the context of potential limitations. First, ARIC participants were recruited at age 45 to 64 years and UKBB participants were recruited at age 40 to 69 years, raising the possibility of survivorship or selection bias that limits generalizability to younger patients. Second, dilated cardiomyopathy and HCM diagnoses in ARIC were ascertained through diagnosis codes from inpatient admissions without clinical adjudication, and all UKBB disease end points were similarly ascertained through participant self-report, diagnosis codes from inpatient admissions, national procedure, and death registries. Furthermore, only a portion of these individuals had imaging and ECG data available. Third, participants in research studies tend to be healthier than the general population; as a result, recalibration of disease risk models for a given target population may be needed before clinical deployment.22-24 Fourth, all pathogenic and likely pathogenic variants for each monogenic condition were studied in aggregate, but, even among this group, heterogeneity in risk for each specific variant or gene may be present and detectable with larger cohorts.27 Fifth, variants in only ACMG-designated actionable cardiomyopathy genes were studied, although numerous other genes are also associated with dilated cardiomyopathy and HCM.11 Sixth, the use of exome data instead of curated gene panels may lead to underreporting of variants owing to lower sequencing depth. Finally, the stringent use of ACMG criteria may also lead to underestimation of true carrier prevalence with respect to pathogenic variants in the studied genes.
Results of this genetic association study suggest that approximately 0.7% of middle-aged adults in 2 cohort studies harbor an actionable pathogenic variant associated with dilated cardiomyopathy or HCM. These individuals are at substantially increased risk of death, heart failure, and atrial fibrillation, and are not reliably detected based on imaging or ECG. Population genomic screening efforts may enable identification of these at-risk individuals before disease onset, with the ultimate aim of empowering them to overcome inherited disease susceptibility with established risk mitigation strategies.
Accepted for Publication: March 8, 2022.
Published Online: May 11, 2022. doi:10.1001/jamacardio.2022.0901
Corresponding Author: Amit V. Khera, MD, MSc, Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, 185 Cambridge St, CPZN 6.256, Boston, MA 02114 (email@example.com).
Author Contributions: Dr Khera had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Patel, Natarajan, Ellinor, Khera.
Acquisition, analysis, or interpretation of data: Patel, Dron, Wang, Pirruccello, Ng, Lebo, Aragam, Khera.
Drafting of the manuscript: Patel, Khera.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Patel, Wang.
Obtained funding: Patel, Ng, Ellinor, Khera.
Administrative, technical, or material support: Dron, Pirruccello, Natarajan, Aragam.
Supervision: Ng, Natarajan, Lebo, Ellinor, Aragam, Khera.
Conflict of Interest Disclosures: Dr Patel reported receiving grants from the National Human Genome Research Institute and Harvard University Catalyst during the conduct of the study. Dr Pirruccello reported receiving personal fees from Maze Therapeutics during the conduct of the study. Dr Ng reported being employed by IBM. Dr Natarajan reported receiving grants from Amgen, Apple, AstraZeneca, Boston Scientific, and Novartis; personal fees from Apple, AstraZeneca, Blackstone Life Sciences, Genentech, Novartis, Foresite Labs, and TenSixteen Bio; equity from TenSixteen Bio and geneXwell; and having spousal employment from Vertex outside the submitted work. Dr Lebo reported being employed at a not-for-profit clinical molecular genetics laboratory (Mass General Brigham Lab for Molecular Medicine) that provides diagnostic testing and screening for inherited cardiomyopathies. Dr Ellinor reported receiving grants from Bayer AG and IBM Research and personal fees from Bayer AG, MyoKardia, and Novartis during the conduct of the study. Dr Khera reported receiving grants from the National Human Genome Research Institute, IBM Research-Sponsored Research Agreement, and Novartis; personal fees and equity from Verve Therapeutics Employee; and personal fees from Amgen, Maze Therapeutics, Navitor Pharmaceuticals, Sarepta Therapeutics, Silence Therapeutics, Color Health, Korro Bio, Third Rock Ventures, and Foresite Labs outside the submitted work. No other disclosures were reported.
Funding/Support: Funding for this study was provided in part by grants T32HL007208 and 1U01HG011719 (Dr Patel), grants 1RO1HL092577, R01HL128914, and K24HL105780 (Dr Ellinor), and grants R01HL142711, R01HL148565, and R01HL148050 (Dr Natarajan) from the National Heart, Lung, and Blood Institute; grant 14CVD01 (Dr Ellinor) and grant TNE-18CVD04 (Dr Natarajan) from Fondation Leducq; grant 8533321 (Dr Patel), grant 18SFRN34110082 (Dr Ellinor), and grant 17IFUNP3384001 (Dr Aragam) from the American Heart Association; Hassenfeld Scholar Awards from Massachusetts General Hospital (Drs Natarajan and Khera); a Merkin Institute Fellowship from the Broad Institute of MIT and Harvard (Dr Khera); grants 1K08HG010155 and 1U01HG011719 (Dr Khera) and R01HG010372 (Dr Lebo) from the National Human Genome Research Institute; grant KL2 TR002542 (Dr Aragam) from Harvard University Catalyst; and a sponsored research agreement from IBM Research (Dr Khera).
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: We thank the UK Biobank, Atherosclerosis in Risk Communities, and their participants who provided biological samples and data for this analysis. No one received financial compensation for their contributions.