Genetic Testing for Diagnosis of Hypertrophic Cardiomyopathy Mimics

A bibliometric and visual analysis of research trends and hotspots of familial hypertrophic cardiomyopathy: A review

Familial hypertrophic cardiomyopathy (FHCM) is an inherited cardiac disease caused by mutations of sarcomere proteins and can be the underlining substrate for major cardiovascular events. Early identification and diagnosis of FHCM are essential to reduce sudden cardiac death. So, this paper summarized the current knowledge on FHCM, and displayed the analysis via bibliometrics method. The relevant literature on FHCM were screened searched via the Web of Science Core Collection database from 2012 to 2022. The literatures were was summarized and analyzed via the bibliometrics method analyzed via CiteSpace and VOSviewer according to topic categories, distribution of spatiotemporal omics and authors, as well as references. Since 2012, there are 909 research articles and reviews related to FHCM. The number of publication for the past 10 years have shown that the development of FHCM research has been steady, with the largest amount of literature in 2012. The most published papers were from the United States, followed by the United Kingdom and Italy. The University of London (63 papers) was the institution that published the most research articles, followed by Harvard University (45 papers) and University College London (45 papers). Keywords formed 3 clusters, focused on the pathogenesis of FHCM, the diagnosis of FHCM, FHCM complications, respectively. The bibliometric analysis and visualization techniques employed herein highlight key trends and focal points in the field, predominantly centered around FHCM's pathogenesis, diagnostic approaches, and its complications. These insights are instrumental in steering future research directions in this area.

Association of duration and intensity of exercise with phenotypic expression in hypertrophic cardiomyopathy

OBJECTIVES

There is limited data regarding the impact of exercise on phenotypic expression in hypertrophic cardiomyopathy (HCM). We aimed to investigate whether such an association exists in a cohort of genotype-positive HCM patients.

METHODS

In this cross-sectional study of genotype-positive HCM families, we used structured questionnaires to obtain data regarding intensity and duration of exercise of participants starting at the age of 10, as well as data regarding exercise recommendations and their impact on quality of life (QOL). The association of cumulative metabolic-equivalent hours of exercise at different ages with different measures of phenotypic expression (maximal wall thickness, left atrial diameter, extent of late gadolinium enhancement) was analyzed.

RESULTS

The study included 109 patients from 55 families, including 43 male (39%) and 90 (83%) phenotype-positive. No association was identified between exercise duration or intensity with any of the phenotypic markers with the exception of greater cumulative exercise associated with younger age at presentation. Similar results were obtained when analysis was limited to exercise until the age of 20, until the age of 30 or only after 30. Among phenotype-positive patients, 89% recalled receiving recommendations regarding exercise restriction, 29% noted reduction in exercise level following such recommendations and 25% noted this having a significant impact on their QOL.

CONCLUSION

We found no association between exercise intensity or duration and phenotypic expression in genotype-positive HCM patients. These findings are important for physician-patient discussions and support the recent trend towards more permissive exercise restrictions in HCM.

Real-world utilization of guideline-directed genetic testing in inherited cardiovascular diseases

Background

Cardiovascular disease continues to be the leading cause of death globally. Clinical practice guidelines aimed at improving disease management and positively impacting major cardiac adverse events recommend genetic testing for inherited cardiovascular conditions such as dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), long QT syndrome (LQTS), hereditary amyloidosis, and familial hypercholesterolemia (FH); however, little is known about how consistently practitioners order genetic testing for these conditions in routine clinical practice. This study aimed to assess the adoption of guideline-directed genetic testing for patients diagnosed with DCM, HCM, LQTS, hereditary amyloidosis, or FH.

Methods

This retrospective cohort study captured real-world evidence of genetic testing from ICD-9-CM and ICD-10-CM codes, procedure codes, and structured text fields of de-identified patient records in the Veradigm Health Insights Ambulatory EHR Research Database linked with insurance claims data. Data analysis was conducted using an automated electronic health record analysis engine. Patient records in the Veradigm database were sourced from more than 250,000 clinicians serving over 170 million patients in outpatient primary care and specialty practice settings in the United States and linked insurance claims data from public and private insurance providers. The primary outcome measure was evidence of genetic testing within six months of condition diagnosis.

Results

Between January 1, 2017, and December 31, 2021, 224,641 patients were newly diagnosed with DCM, HCM, LQTS, hereditary amyloidosis, or FH and included in this study. Substantial genetic testing care gaps were identified. Only a small percentage of patients newly diagnosed with DCM (827/101,919; 0.8%), HCM (253/15,507; 1.6%), LQTS (650/56,539; 1.2%), hereditary amyloidosis (62/1,026; 6.0%), or FH (718/49,650; 1.5%) received genetic testing.

Conclusions

Genetic testing is underutilized across multiple inherited cardiovascular conditions. This real-world data analysis provides insights into the delivery of genomic healthcare in the United States and suggests genetic testing guidelines are rarely followed in practice.

Advanced searching for hypertrophic cardiomyopathy heritability in real practice tomorrow

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease associated with morbidity and mortality at any age. As studies in recent decades have shown, the genetic architecture of HCM is quite complex both in the entire population and in each patient. In the rapidly advancing era of gene therapy, we have to provide a detailed molecular diagnosis to our patients to give them the chance for better and more personalized treatment. In addition to emphasizing the importance of genetic testing in routine practice, this review aims to discuss the possibility to go a step further and create an expanded genetic panel that contains not only variants in core genes but also new candidate genes, including those located in deep intron regions, as well as structural variations. It also highlights the benefits of calculating polygenic risk scores based on a combination of rare and common genetic variants for each patient and of using non-genetic HCM markers, such as microRNAs that can enhance stratification of risk for HCM in unselected populations alongside rare genetic variants and clinical factors. While this review is focusing on HCM, the discussed issues are relevant to other cardiomyopathies.

Imaging cardiac hypertrophy in hypertrophic cardiomyopathy and its differential diagnosis

PURPOSE OF REVIEW

The aim of this study was to review imaging of myocardial hypertrophy in hypertrophic cardiomyopathy (HCM) and its phenocopies. The introduction of cardiac myosin inhibitors in HCM has emphasized the need for careful evaluation of the underlying cause of myocardial hypertrophy.

RECENT FINDINGS

Advances in imaging of myocardial hypertrophy have focused on improving precision, diagnosis, and predicting prognosis. From improved assessment of myocardial mass and function, to assessing myocardial fibrosis without the use of gadolinium, imaging continues to be the primary tool in understanding myocardial hypertrophy and its downstream effects. Advances in differentiating athlete's heart from HCM are noted, and the increasing rate of diagnosis in cardiac amyloidosis using noninvasive approaches is especially highlighted due to the implications on treatment approach. Finally, recent data on Fabry disease are shared as well as differentiating other phenocopies from HCM.

SUMMARY

Imaging hypertrophy in HCM and ruling out other phenocopies is central to the care of patients with HCM. This space will continue to rapidly evolve, as disease-modifying therapies are under investigation and being advanced to the clinic.

Genetic Evaluation and Screening in Cardiomyopathies: Opportunities and Challenges for Personalized Medicine

Cardiomyopathy is a major cause of heart failure caused by abnormalities of the heart muscles that make it harder for it to fill or eject blood. With technological advances, it is important for patients and families to understand that there are potential monogenic etiologies of cardiomyopathy. A multidisciplinary approach to clinical genetic screening for cardiomyopathies involving genetic counseling and clinical genetic testing is beneficial for patients and families. With early identification of inherited cardiomyopathy, patients can initiate guideline-directed medical therapies earlier, resulting in a greater likelihood of improving prognoses and health outcomes. Identifying impactful genetic variants will also allow for cascade testing to determine at-risk family members through clinical (phenotype) screening and risk stratification. Addressing genetic variants of uncertain significance and causative variants that may change in pathogenicity is also important to consider. This review will dive into the clinical genetic testing approaches for the various cardiomyopathies, the significance of early detection and treatment, the value of family screening, the personalized treatment process associated with genetic evaluation, and current strategies for clinical genetic testing outreach.

Familial Hypertrophic Cardiomyopathy: Diagnosis and Management

Hypertrophic cardiomyopathy (HCM) is widely recognized as one of the most common inheritable cardiac disorders. Since its initial description over 60 years ago, advances in multimodality imaging and translational genetics have revolutionized our understanding of the disorder. The diagnosis and management of patients with HCM are optimized with a multidisciplinary approach. This, along with increased safety and efficacy of medical, percutaneous, and surgical therapies for HCM, has afforded more personalized care and improved outcomes for this patient population. In this review, we will discuss our modern understanding of the molecular pathophysiology that underlies HCM. We will describe the range of clinical presentations and discuss the role of genetic testing in diagnosis. Finally, we will summarize management strategies for the hemodynamic subtypes of HCM with specific emphasis on the rationale and evidence for the use of implantable cardioverter defibrillators, septal reduction therapy, and cardiac myosin inhibitors.

Hypertrophic, Dilated, and Arrhythmogenic Cardiomyopathy: Where Are We?

Cardiomyopathies are a heterogeneous group of structural, mechanical, and electrical heart muscle disorders which often correlate with life-threatening arrhythmias and progressive heart failure accounting for significant cardiovascular morbidity and mortality. Currently, cardiomyopathies still represent a leading reason for heart transplantation worldwide. The last years have brought remarkable advances in the field of cardiomyopathies especially in terms of understanding the molecular basis as well as the diagnostic evaluation and management. Although most cardiomyopathy treatments had long focused on symptom management, much of the current research efforts aim to identify and act on the disease-driving mechanisms. Regarding risk assessment and primary prevention of sudden cardiac death, additional data are still pending in order to pave the way for a more refined and early patient selection for defibrillator implantation. This review summarizes the current knowledge of hypertrophic, dilated and arrhythmogenic cardiomyopathy with a particular emphasis on their pathophysiology, clinical features, and diagnostic approach. Furthermore, the relevant ongoing studies investigating novel management approaches and main gaps in knowledge are highlighted.

Approaches to Genetic Screening in Cardiomyopathies: Practical Guidance for Clinicians

Patients and families benefit when the genetic etiology of cardiomyopathy is elucidated through a multidisciplinary approach including genetic counseling and judicious use of genetic testing. The yield of genetic testing is optimized when performed on a proband with a clear phenotype, and interrogates genes that are validated in association with that specific form of cardiomyopathy. Variants of uncertain significance are frequently uncovered and should not be overinterpreted. Identifying an impactful genetic variant as the cause of a patient's cardiomyopathy can have important prognostic impact, and enable streamlined cascade testing to highlight at risk relatives. Certain genotypes are associated with unique potential cardiac and noncardiac risk factors and may dictate personalized approaches to treatment.

Patient and Clinician Perceptions of Precision Cardiology Care: Findings From the HeartCare Study

BACKGROUND

Routine genome-wide screening for cardiovascular disease risk may inform clinical decision-making. However, little is known about whether clinicians and patients would find such testing useful or acceptable within the context of a genomics-enabled learning health system.

METHODS

We conducted surveys with patients and their clinicians who were participating in the HeartCare Study, a precision cardiology care project that returned results from a next-generation sequencing panel of 158 genes associated with cardiovascular disease risk. Six weeks after return of results, we assessed patients' and clinicians' perceived utility and disutility of HeartCare, the effect of the test on clinical recommendations, and patients' attitudes toward integration of research and clinical care.

RESULTS

Among 666 HeartCare patients with a result returned during the survey study period, 42.0% completed a full or partial survey. Patient-participants who completed a full survey (n=224) generally had positive perceptions of HeartCare independent of whether they received a positive or negative result. Most patient-participants considered genetic testing for cardiovascular disease risk to have more benefit than risk (88.3%) and agreed that it provided information that they wanted to know (81.2%), while most disagreed that the test caused them to feel confused (77.7%) or overwhelmed (78.0%). For 122 of their patients with positive results, clinicians (n=13) reported making changes in clinical care for 66.4% of patients, recommending changes in health behaviors for 36.9% of patients, and recommending to 33.6% of patients that their family members have clinical testing.

CONCLUSIONS

Both patients and clinicians thought the HeartCare panel screen for cardiovascular disease risk provided information that was useful in terms of personal or health benefits to the patient and that informed clinical care without causing patients to be confused or overwhelmed. Further research is needed to assess perceptions of genome-wide screening among the US cardiology clinic population.

Assessment of the Diagnostic Yield of Combined Cardiomyopathy and Arrhythmia Genetic Testing

Importance

Genetic testing can guide management of both cardiomyopathies and arrhythmias, but cost, yield, and uncertain results can be barriers to its use. It is unknown whether combined disease testing can improve diagnostic yield and clinical utility for patients with a suspected genetic cardiomyopathy or arrhythmia.

Objective

To evaluate the diagnostic yield and clinical management implications of combined cardiomyopathy and arrhythmia genetic testing through a no-charge, sponsored program for patients with a suspected genetic cardiomyopathy or arrhythmia.

Design, Setting, and Participants

This cohort study involved a retrospective review of DNA sequencing results for cardiomyopathy- and arrhythmia-associated genes. The study included 4782 patients with a suspected genetic cardiomyopathy or arrhythmia who were referred for genetic testing by 1203 clinicians; all patients participated in a no-charge, sponsored genetic testing program for cases of suspected genetic cardiomyopathy and arrhythmia at a single testing site from July 12, 2019, through July 9, 2020.

Main Outcomes and Measures

Positive gene findings from combined cardiomyopathy and arrhythmia testing were compared with findings from smaller subtype-specific gene panels and clinician-provided diagnoses.

Results

Among 4782 patients (mean [SD] age, 40.5 [21.3] years; 2551 male [53.3%]) who received genetic testing, 39 patients (0.8%) were Ashkenazi Jewish, 113 (2.4%) were Asian, 571 (11.9%) were Black or African American, 375 (7.8%) were Hispanic, 2866 (59.9%) were White, 240 (5.0%) were of multiple races and/or ethnicities, 138 (2.9%) were of other races and/or ethnicities, and 440 (9.2%) were of unknown race and/or ethnicity. A positive result (molecular diagnosis) was confirmed in 954 of 4782 patients (19.9%). Of those, 630 patients with positive results (66.0%) had the potential to inform clinical management associated with adverse clinical outcomes, increased arrhythmia risk, or targeted therapies. Combined cardiomyopathy and arrhythmia gene panel testing identified clinically relevant variants for 1 in 5 patients suspected of having a genetic cardiomyopathy or arrhythmia. If only patients with a high suspicion of genetic cardiomyopathy or arrhythmia had been tested, at least 137 positive results (14.4%) would have been missed. If testing had been restricted to panels associated with the clinician-provided diagnostic indications, 75 of 689 positive results (10.9%) would have been missed; 27 of 75 findings (36.0%) gained through combined testing involved a cardiomyopathy indication with an arrhythmia genetic finding or vice versa. Cascade testing of family members yielded 402 of 958 positive results (42.0%). Overall, 2446 of 4782 patients (51.2%) had only variants of uncertain significance. Patients referred for arrhythmogenic cardiomyopathy had the lowest rate of variants of uncertain significance (81 of 176 patients [46.0%]), and patients referred for catecholaminergic polymorphic ventricular tachycardia had the highest rate (48 of 76 patients [63.2%]).

Conclusions and Relevance

In this study, comprehensive genetic testing for cardiomyopathies and arrhythmias revealed diagnoses that would have been missed by disease-specific testing. In addition, comprehensive testing provided diagnostic and prognostic information that could have potentially changed management and monitoring strategies for patients and their family members. These results suggest that this improved diagnostic yield may outweigh the burden of uncertain results.

Clinical significance of genetic variation in hypertrophic cardiomyopathy: comparison of computational tools to prioritize missense variants

Hypertrophic cardiomyopathy (HCM) is a common heart disease associated with sudden cardiac death. Early diagnosis is critical to identify patients who may benefit from implantable cardioverter defibrillator therapy. Although genetic testing is an integral part of the clinical evaluation and management of patients with HCM and their families, in many cases the genetic analysis fails to identify a disease-causing mutation. This is in part due to difficulties in classifying newly detected rare genetic variants as well as variants-of-unknown-significance (VUS). Multiple computational algorithms have been developed to predict the potential pathogenicity of genetic variants, but their relative performance in HCM has not been comprehensively assessed. Here, we compared the performance of 39 currently available prediction tools in distinguishing between high-confidence HCM-causing missense variants and benign variants, and we developed an easy-to-use-tool to perform variant prediction benchmarks based on annotated VCF files (VETA). Our results show that tool performance increases after HCM-specific calibration of thresholds. After excluding potential biases due to circularity type I issues, we identified ClinPred, MISTIC, FATHMM, MPC and MetaLR as the five best performer tools in discriminating HCM-associated variants. We propose combining these tools in order to prioritize unknown HCM missense variants that should be closely followed-up in the clinic.

Automatic Identification of Patients With Unexplained Left Ventricular Hypertrophy in Electronic Health Record Data to Improve Targeted Treatment and Family Screening

Background

Unexplained Left Ventricular Hypertrophy (ULVH) may be caused by genetic and non-genetic etiologies (e.g., sarcomere variants, cardiac amyloid, or Anderson-Fabry's disease). Identification of ULVH patients allows for early targeted treatment and family screening.

Aim

To automatically identify patients with ULVH in electronic health record (EHR) data using two computer methods: text-mining and machine learning (ML).

Methods

Adults with echocardiographic measurement of interventricular septum thickness (IVSt) were included. A text-mining algorithm was developed to identify patients with ULVH. An ML algorithm including a variety of clinical, ECG and echocardiographic data was trained and tested in an 80/20% split. Clinical diagnosis of ULVH was considered the gold standard. Misclassifications were reviewed by an experienced cardiologist. Sensitivity, specificity, positive, and negative likelihood ratios (LHR+ and LHR–) of both text-mining and ML were reported.

Results

In total, 26,954 subjects (median age 61 years, 55% male) were included. ULVH was diagnosed in 204/26,954 (0.8%) patients, of which 56 had amyloidosis and two Anderson-Fabry Disease. Text-mining flagged 8,192 patients with possible ULVH, of whom 159 were true positives (sensitivity, specificity, LHR+, and LHR– of 0.78, 0.67, 2.36, and 0.33). Machine learning resulted in a sensitivity, specificity, LHR+, and LHR– of 0.32, 0.99, 32, and 0.68, respectively. Pivotal variables included IVSt, systolic blood pressure, and age.

Conclusions

Automatic identification of patients with ULVH is possible with both Text-mining and ML. Text-mining may be a comprehensive scaffold but can be less specific than machine learning. Deployment of either method depends on existing infrastructures and clinical applications.

The mechanics of the heart: zooming in on hypertrophic cardiomyopathy and cMyBP-C

Hypertrophic cardiomyopathy (HCM), a disease characterized by cardiac muscle hypertrophy and hypercontractility, is the most frequently inherited disorder of the heart. HCM is mainly caused by variants in genes encoding proteins of the sarcomere, the basic contractile unit of cardiomyocytes. The most frequently mutated among them is MYBPC3, which encodes cardiac myosin-binding protein C (cMyBP-C), a key regulator of sarcomere contraction. In this review, we summarize clinical and genetic aspects of HCM and provide updated information on the function of the healthy and HCM sarcomere, as well as on emerging therapeutic options targeting sarcomere mechanical activity. Building on what is known about cMyBP-C activity, we examine different pathogenicity drivers by which MYBPC3 variants can cause disease, focussing on protein haploinsufficiency as a common pathomechanism also in nontruncating variants. Finally, we discuss recent evidence correlating altered cMyBP-C mechanical properties with HCM development.

Pediatric Hypertrophic Cardiomyopathy: Exploring the Genotype-Phenotype Association

Pediatric hypertrophic cardiomyopathy (HCM) is the most common form of cardiomyopathy in children and a leading cause of sudden cardiac death. Yet, the association between genotype variation, phenotype expression, and adverse events in pediatric HCM has not been fully elucidated. Although the literature on this topic is evolving in adult HCM, the evidence in children is lacking. Solidifying our understanding of this relationship could improve risk stratification as well as improve our comprehension of the underlying pathophysiological characteristics of pediatric HCM. In this state‐of‐the‐art review, we examine the current literature on genetic variations in HCM and their association with outcomes in children, discuss the current approaches to identifying cardiovascular phenotypes in pediatric HCM, and explore possible avenues that could improve sudden cardiac death risk assessment.

Cellular models and therapeutic perspectives in hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a clinically heterogeneous cardiac disease that is mainly characterized by left ventricular hypertrophy in the absence of any additional cardiac or systemic disease. HCM is genetically heterogeneous, inherited mainly in an autosomal dominant pattern, and so far pathogenic variants have been identified in more than 20 genes, mostly encoding proteins of the cardiac sarcomere. Based on its variable penetrance and expressivity, pathogenicity of newly identified variants often remains unsolved, underlining the importance of cellular and tissue-based models that help to uncover causative genetic alterations and, additionally, provide appropriate systems for the analysis of disease hallmarks as well as for the design and application of new therapeutic strategies like drug screenings and genome/base editing approaches. Here, we review the current state of cellular and tissue-engineered models and provide future perspectives for personalized therapeutic strategies of HCM.

The clinical utility of pediatric cardiomyopathy genetic testing: From diagnosis to a precision medicine-based approach to care

Background

Pediatric-onset cardiomyopathies are rare yet cause significant morbidity and mortality in affected children. Genetic testing has a major role in the clinical evaluation of pediatric-onset cardiomyopathies, and identification of a variant in an associated gene can be used to confirm the clinical diagnosis and exclude syndromic causes that may warrant different treatment strategies. Further, risk-predictive testing of first-degree relatives can assess who is at-risk of disease and requires continued clinical follow-up.

Aim of Review

In this review, we seek to describe the current role of genetic testing in the clinical diagnosis and management of patients and families with the five major cardiomyopathies. Further, we highlight the ongoing development of precision-based approaches to diagnosis, prognosis, and treatment.

Key Scientific Concepts of Review

Emerging application of genotype-phenotype correlations opens the door for genetics to guide a precision medicine-based approach to prognosis and potentially for therapies. Despite advances in our understanding of the genetic etiology of cardiomyopathy and increased accessibility of clinical genetic testing, not all pediatric cardiomyopathy patients have a clear genetic explanation for their disease. Expanded genomic studies are needed to understand the cause of disease in these patients, improve variant classification and genotype-driven prognostic predictions, and ultimately develop truly disease preventing treatment.

Deep Learning Analysis of Echocardiographic Images to Predict Positive Genotype in Patients With Hypertrophic Cardiomyopathy

Genetic testing provides valuable insights into family screening strategies, diagnosis, and prognosis in patients with hypertrophic cardiomyopathy (HCM). On the other hand, genetic testing carries socio-economical and psychological burdens. It is therefore important to identify patients with HCM who are more likely to have positive genotype. However, conventional prediction models based on clinical and echocardiographic parameters offer only modest accuracy and are subject to intra- and inter-observer variability. We therefore hypothesized that deep convolutional neural network (DCNN, a type of deep learning) analysis of echocardiographic images improves the predictive accuracy of positive genotype in patients with HCM. In each case, we obtained parasternal short- and long-axis as well as apical 2-, 3-, 4-, and 5-chamber views. We employed DCNN algorithm to predict positive genotype based on the input echocardiographic images. We performed 5-fold cross-validations. We used 2 reference models—the Mayo HCM Genotype Predictor score (Mayo score) and the Toronto HCM Genotype score (Toronto score). We compared the area under the receiver-operating-characteristic curve (AUC) between a combined model using the reference model plus DCNN-derived probability and the reference model. We calculated the p-value by performing 1,000 bootstrapping. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). In addition, we examined the net reclassification improvement. We included 99 adults with HCM who underwent genetic testing. Overall, 45 patients (45%) had positive genotype. The new model combining Mayo score and DCNN-derived probability significantly outperformed Mayo score (AUC 0.86 [95% CI 0.79–0.93] vs. 0.72 [0.61–0.82]; p < 0.001). Similarly, the new model combining Toronto score and DCNN-derived probability exhibited a higher AUC compared to Toronto score alone (AUC 0.84 [0.76–0.92] vs. 0.75 [0.65–0.85]; p = 0.03). An improvement in the sensitivity, specificity, PPV, and NPV was also achieved, along with significant net reclassification improvement. In conclusion, compared to the conventional models, our new model combining the conventional and DCNN-derived models demonstrated superior accuracy to predict positive genotype in patients with HCM.

Cardiomyopathies and Genetic Testing in Heart Failure: Role in Defining Phenotype-Targeted Approaches and Management

Cardiomyopathies represent an important cause of heart failure, often affecting young individuals, and have important implications for relatives. Genetic testing for cardiomyopathies is an established care pathway in contemporary cardiology practice. The primary cardiomyopathies where genetic testing is indicated are hypertrophic, dilated, arrhythmogenic, and restrictive cardiomyopathies, with left ventricular noncompaction as a variant phenotype. Early identification and initiation of therapies in patients with inherited cardiomyopathies allow for targeting asymptomatic and presymptomatic patients in stages A and B of the American College of Cardiology/American Heart Association classification of heart failure. The current approach for genetic testing uses gene panel-based testing with the ability to extend to whole-exome and whole-genome sequencing in rare instances. The central components of genetic testing include defining the genetic basis of the diagnosis, providing prognostic information, and the ability to screen and risk-stratify relatives. Genetic testing for cardiomyopathies should be coordinated by a multidisciplinary team including adult and pediatric cardiologists, genetic counsellors, and geneticists, with access to expertise in cardiac imaging and electrophysiology. A pragmatic approach for addressing genetic variants of uncertain significance is important. In this review, we highlight the indications for genetic testing in the various cardiomyopathies, the value of early diagnosis and treatment, family screening, and the care process involved in genetic counselling and testing.

Hypertrophic Cardiomyopathy: Genetic Testing and Risk Stratification

PURPOSE OF REVIEW

Our knowledge of the genetic basis and molecular pathogenesis of hypertrophic cardiomyopathy (HCM) continues to evolve. We describe the genetic basis of HCM, recent advances in genetic testing and the role of genetics in guiding risk stratification and management, both now and in the future.

RECENT FINDINGS

While initially thought to be an exclusively Mendelian disease, we now know there are important HCM sub-groups. A proportion will have sarcomere variants as the cause of their disease, while others will have genetic variants in genes that can give rise to conditions that can mimic HCM. The role of genetics is primarily for cascade genetic testing, though there is emerging evidence of a role for prognosis and patient management. Genetic testing is a useful addition to management. Genotype may play a greater role in risk stratification, management, treatment and prognosis in future, offering improved outcomes for patients and their families with HCM.

Cardiovascular genetics: the role of genetic testing in diagnosis and management of patients with hypertrophic cardiomyopathy

Genetic testing in hypertrophic cardiomyopathy (HCM) is a valuable tool to manage patients and their families. Genetic testing can help inform diagnosis and differentiate HCM from other disorders that also result in increased left ventricular wall thickness, thereby directly impacting treatment. Moreover, genetic testing can definitively identify at-risk relatives and focus family management. Pathogenic variants in sarcomere and sarcomere-related genes have been implicated in causing HCM, and targeted gene panel testing is recommended for patients once a clinical diagnosis has been established. If a pathogenic or likely pathogenic variant is identified in a patient with HCM, predictive genetic testing is recommended for their at-risk relatives to determine who is at risk and to guide longitudinal screening and risk stratification. However, there are important challenges and considerations to implementing genetic testing in clinical practice. Genetic testing results can have psychological and other implications for patients and their families, emphasising the importance of genetic counselling before and after genetic testing. Determining the clinical relevance of genetic testing results is also complex and requires expertise in understanding of human genetic variation and clinical manifestations of the disease. In this review, we discuss the genetics of HCM and how to integrate genetic testing in clinical practice.